Approximate Values Research Articles

Performance of the Mean, Highest, and Admission Day Pediatric Sequential Organ Failure Assessment Scores As Outcome Predictors in a Pediatric Intensive Care Unit: A Prospective Observational Study

AbstractThe pediatric sequential organ failure assessment (pSOFA) score has been recently validated from its adult version having included the six clinical and biochemical parameters of organ dysfunction (respiratory, coagulation, cardiovascular, neurological, hepatic, and renal) and adapting age-adjusted cutoffs. Our goal was to find out which among the pSOFA scores (recorded on admission, highest score, and the mean score i.e., pSOFA1, pSOFAh, and pSOFAm respectively) performed better to predict mortality among the patients admitted in our pediatric intensive care unit (PICU). This prospective observational study was conducted on 104 patients (1 month to 12 years of age) admitted in the eight bedded PICU of a tertiary care hospital in India who met the inclusion criteria. The highest values of serial pSOFA scores were recorded on every alternate day starting from the day of admission up to day 9. The mean and median values of the pSOFA1, pSOFAm, and pSOFAh were higher in the nonsurvivor group than in the survivors. The mean pSOFA (with a diagnostic accuracy of 92.3% at a mean cut-off value of 12.8) has outperformed the other two pSOFA scores. In this exploratory analysis, the pSOFAm is the best tool in predicting the mortality outcome of any critically ill child. The use of the pSOFA score at admission and the mean values helps the clinician to quantify the organ dysfunction, and it may be helpful for the clinicians to take steps for further management. It may be useful to communicate to the parents of the sick child for prognostication too. The pSOFA1 also reflects well on the early prognostication when multiple pSOFA scores are unavailable. In the resource constraint settings, one may rely on the pSOFA1 and the approximate pSOFAm value may be predicted from the pSOFA1 as pSOFAm=[(1.03 XpSOFA1) – 0.9] within limitations.

Subspace screening rule for multi-label estimator with sparsity-inducing regularization

Multi-label learning has drawn wide attention for the last decade. To exploit the correlation between labels, a multi-label classifier based on the nuclear norm has been proposed recently, which joints Ranking support vector machine (RankSVM) and Binary Relevance (BR) with robust Low-rank learning (RBRL). Therefore, it has satisfactory classification outcomes in the application. Nonetheless, tackling the large-scale problem still remains a challenge for RBRL. Motivated by this, a Subspace Screening Rule (SSR) for RBRL is proposed to accelerate the solving process. Its primary strategy is to reduce the size of the matrix variable to be estimated, based on the fact that a low-rank matrix can be represented by a few subspaces. Specifically, at each iteration we delete a majority of subspaces with zero coefficients in the optimal solution by matrix decomposition and optimality condition. Then, we solve the small-scale reduced problem rather than the initial large-scale matrix problem. An excellent acceleration effect is obtained. To further improve the solving speed, Approximate Singular Value Decomposition (ASVD) and Accelerated Proximal Gradient (APG) are employed in the different stages. Extensive experiments on seven benchmark datasets as well as an artificial dataset demonstrate the efficiency of SSR.

Sustainable Thermal Insulation Derived from Recycled Textile Waste

The textile industry is one of the oldest industries and the third most important industry branch in Macedonia. It has had a steady increase in production over the years. Growing production line proportionally generates textile waste. Although it is terminologically categorized as waste, textile waste can be a valuable resource and is one of the textile industry’s main challenges. Textile waste, appropriately treated with the possibilities offered by the recycling process or used as a clean waste, can find multi-faced application in different construction areas. This paper covers research that examines the possibilities of applying textile waste in the field of thermal insulations in buildings. The focus is on developing thermal insulation solutions applied in sustainable and ecologic buildings. Applied thermal insulation has a primary impact on reducing electricity consumption and greenhouse gas emissions associated with indoor air conditioning. That would mean that buildings incorporating appropriate thermal insulation offer greater comfort, directly increasing the quality of life. This is an additional economic-environmental dimension. According to the experimental testing, the thermal conductivity coefficient of the textile waste is obtained at 0.039 W/m·K. Its value defines a thermal insulation material suitable for the purpose and has approximate values to the other materials usually used for thermal insulation in buildings. Implementing a product made of textile waste with appropriate performance would bring economic benefits to the industry and open new job opportunities.

Green in the City: Estimating the Ecosystem Services Provided by Urban and Peri-Urban Forests of Tbilisi Municipality, Georgia

Green spaces play a significant role in providing essential natural services to cities. This study aims to estimate Tbilisi’s green cover and identify the surface cover classes, volumes, and values of ecosystem services. The study area embraces the territory of Tbilisi municipality in its legal/administrative boundaries, which is equal to 502 sq. km. We use the i-Tree Canopy program (v.7.1) to identify the surface cover classes and quantify and price the ecosystem services provided by Tbilisi’s urban and peri-urban forests. The analysis includes the identification and distribution of the surface classes of the territory of Tbilisi, which is presented as follows: grass/herbaceous (38.71% +/− 1.36%), various impervious surfaces (approx. 21.18%), soil/bare ground (8.61% +/− 0.78%), trees/shrubs (28.55% +/− 1.26%), and water (2.95% +/− 0.47) surfaces. Analysis revealed the volumes of the removal of atmospheric pollutants, the annual removal of atmospheric carbon, and the total carbon stock fixed in the trees and shrub vegetation and provided the monetary values, expressed in US Dollars rounded per sq. km, of stored and sequestered carbon and pollution removal on the studies territory. The results showed that the annual removal of air pollutants (CO, NO2, O3, SO2, PM2.5 and PM10) totals 1227 tons or 2.444 t/sq.km. The average annual carbon sequestration by trees and other vegetation is 43.72 thousand tons (87.09 t/sq.km), with an approximate value of 8.22 million USD. The trees are storing 1097.9 kilotons of carbon (2187.95 t/sq.km) with its CO2 equivalent of 4025 kilotons. The estimated value of this service equals 206.4 million USD. This type of analysis of surface covers and ecosystem services has been performed in Tbilisi for the first time. The study revealed the significant magnitude and the great potential of “green benefits” provided by the urban vegetation to the city. It gives additional arguments for better utilization of this knowledge for advanced planning of the urban green infrastructure of Tbilisi for strengthening its sustainable and resilient development.

Initial validation of the GUESS-18 for usability in virtual reality gaming environments: a pilot study

Virtual reality (VR) technology has developed rapidly in recent years with head-mounted displays (HMDs), which provide immersive VR experiences by inserting users into an artificially constructed digital world. However, there is currently no standardized tool for measuring usability in VR environments. The purpose of this study was to provide initial validation of the GUESS-18, a usability questionnaire for video games, for measuring usability of VR in a gaming environment. Participants played a racing game with an HMD in VR and a traditional monitor and completed the GUESS-18 and the System Usability Scale (SUS). Confirmatory factor analysis was performed to determine GUESS-18 validity. The Comparative Fit Index (CFI) and Root Mean Square Error of Approximation (RMSEA) values indicate appropriate model fit, with values of 0.967 and 0.056, respectively. Internal consistency (Cronbach’s alpha) was satisfactory for all factors except for social connectivity. Scores from the GUESS-18 were significantly higher with VR by about 6.4%, but SUS scores were equivalent between display types. Playing the game in VR resulted in greater immersion and personal gratification than playing with the monitor. Overall, the GUESS-18 can measure usability of VR games as it distinguishes VR from traditional monitor environments and shows satisfactory validity and consistency.

ESTIMATING PREVALENCE OF CARPAL TUNNEL SYNDROME AND SEVERITY USING BOSTON CARPAL TUNNEL SYNDROME QUESTIONNAIRE AMONG DEXTEROUS POPULATION

Objective: The study was designed to estimate the prevailing percentage of Carpal Tunnel Syndrome (CTS) using Boston Carpal tunnel syndrome questionnaire (BCTSQ) in the dexterous population and to assess its severity. Study Design: This was a Cross-sectional survey. Study Settings and Participants: The study setting was Karachi where 226 Dexterous workers including; musicians, typist, dentists, butchers office workers, working for more than 1 year were recruited using non-probability convenience sampling. Outcome Measures: Boston Carpal Tunnel Syndrome Questionnaire. Results: This study enrolled 226 participants, 140 (61.9%) of which were males and 86 (38.1%) were females with mean age of 34.05±10.93. Out of the total 25 were diagnosed with CTS in which, 10 (40%) were males and 15 (60%) were females with mean age of 37.60±14.41. Hence, the prevalence of CTS among dexterous population was found to be 11.06%. Conclusion: The results of our study revealed that CTS is a prevalent neuromuscular disorder among dexterous population. The severity level varies among the population. More epidemiological studies are required to get the approximate value to promote ergonomic awareness.

Efficient Point-to-Point Resistance Distance Queries in Large Graphs

We describe a method to efficiently compute point-to-point resistance distances in a graph, which are notoriously difficult to compute from the raw graph data. Our method is based on a relatively compact hierarchical data structure which ''compresses'' the resistance distance data present in a graph, constructed by a nested bisection of the graph using compact edge-cuts. Built and stored in a preprocessing step (which is amenable to massive parallel processing), efficient traversal of a small portion of this data structure supports efficient and exact answers to resistance distance queries. The size of the resulting data structure for a graph of $n$ vertices is $O(nk\log n)$, where $k$ is the size of a balanced edge-cut of the graph. Exact queries then require $O(k\log n)$ worst-case time and $O(k)$ average-case time. Approximate values may be obtained significantly faster by applying standard dimension reduction techniques to the ''coordinates'' stored in the structure.

Improving machine assemblies’ diagnosis with the use of thermal imaging camera

Thermal imaging camera is used in the construction industry, energy industry and some other areas. Considering that a vehicle uses engines, interacting parts, electrical wiring and electrical equipment, it is advisable to use thermal imaging diagnostic method for vehicles as well, including specialized (trucks, road construction and others). Thermal imaging method of machinery diagnosing can be used in the conditions of the specialized automobile service enterprise (dealer or universal), visiting service (servicing of specialized machines by dealer), as well as using own service base of the enterprise. This task is especially urgent in connection with the necessity of pre-shift inspection, which is usually carried out by the company's own maintenance service. Rapid vehicle diagnosis using instrumented testing is therefore an important task. Brakes, bearings, engine, gearbox, transfer case, axles and electrical wiring can all be checked with a thermal imaging camera. Possibility of application of a thermal imaging camera for determining the condition of an angle or an aggregate both by comparison (brake mechanisms, hub bearings) and by determining the actual temperatures of the diagnosed object and comparing them with the approximate values which are determined beforehand on the basis of the previously made measurements. Thus, the use of thermal imaging method of vehicle diagnostics will allow for faster and more accurate assessment of the actual condition of vehicle units and assemblies, increasing its efficiency.

NONLINEAR VIBRATION WITH DISCONTINUITIES IN A FRACTAL SPACE: ITS VARIATIONAL FORMULATION AND PERIODIC PROPERTY

A vibration system with discontinuities has triggered off rocketing interest in various fields including mechanical engineering, physics, and mathematics because it has many striking and amazing properties which cannot be unexplained by traditional vibration theory. This paper studies the problem using the energy conservation frame in a fractal time. A variational formulation is developed, and its periodic property is elucidated by the frequency–amplitude formulation. For discontinuity, this paper aims to propose a new frequency formulation by means of the golden average. Comparison between the approximate and exact frequency values is presented to validate our method.

Effects of Physical Activity on Physical Fitness and Functional Ability in Older Adults.

A cross-sectional survey was done to investigate the pathways the physical activity acts in improving physical fitness and functional outcomes of older adults (60 years and above) using 880 community-dwelling older adults in Sri Lanka. Structural Equation Modeling (SEM) was used. The final SEM model included five latent factors and 14 co-variances. Goodness of Fit Index (GFI), Comparative fit index (CFI) and Root Mean Square Error of Approximation (RMSEA) values of the model were 0.95, 0.93, 0.91, and 0.05 respectively, indicating a good model fit. Strength enhances balance (β = .52, p < .01) and reduces the time required to complete physical functions (β = -.65, p < .01). Since strength declines with advancing age, muscle-strengthening activity programs should be promoted to enhance balance and functional performances in older adults in advanced ages. Strength test (hand grip and leg strength) can be used as a screening test to predict potential risk of falls and functional disabilities in older adults.

On the mechanism of intermolecular nitrogen-atom transfer from a lattice-isolated diruthenium nitride intermediate.

Catalyst confinement within microporous media provides the opportunity to site isolate reactive intermediates, enforce intermolecular functionalization chemistry by co-localizing reactive intermediates and substrates in molecular-scale interstices, and harness non-covalent host-guest interactions to achieve selectivities that are complementary to those accessible in solution. As part of an ongoing program to develop synthetically useful nitrogen-atom transfer (NAT) catalysts, we have demonstrated intermolecular benzylic amination of toluene at a Ru2 nitride intermediate confined within the interstices of a Ru2-based metal-organic framework (MOF), Ru3(btc)2X3 (btc = 1,3,5-benzenetricarboxylate, i.e., Ru-HKUST-1 for X = Cl). Nitride confinement within the extended MOF lattice enabled intermolecular C-H functionalization of benzylic C-H bonds in preference to nitride dimerization, which was encountered with soluble molecular analogues. Detailed study of the kinetic isotope effects (KIEs, i.e., kH/kD) of C-H amination, assayed both as intramolecular effects using partially labeled toluene and as intermolecular effects using a mixture of per-labeled and unlabeled toluene, provided evidence for restricted substrate mobility on the time scale of interstitial NAT. Analysis of these KIEs as a function of material mesoporosity provided approximate experimental values for functionalization in the absence of mass transport barriers. Here, we disclose a combined experimental and computational investigation of the mechanism of NAT from a Ru2 nitride to the C-H bond of toluene. Computed kinetic isotope effects for a H-atom abstraction (HAA)/radical rebound (RR) mechanism are in good agreement with experimental data obtained for C-H amination at the rapid diffusion limit. These results provide the first detailed analysis of the mechanism of intermolecular NAT to a C-H bond, bolster the use of KIEs as a probe of confinement effects on NAT within MOF lattices, and provide mechanistic insights unavailable by experiment because rate-determining mass transport obscured the underlying chemical kinetics.

User’s Perception of Indoor Air Quality (IAQ) in Tall Office Buildings as the Cause of Symptoms of Sick Building Syndrome

The user’s assessment or perception of indoor air quality (IAQ) refers to an individual’s subjective assessment or perception of the quality of the air they breathe inside a particular building or space. This assessment or perception is very individual and can vary from one individual to another. This study aims to determine the IAQ felt by users of the Rectorate Building, State University of Malang, and its effect on Sick Building Syndrome (SBS) symptoms. This research is included in the quantitative research with the study population being all employees at the building, which has 215 people. The data collection technique in this study used the MM040NA questionnaire and the data analysis technique used was binary logistic regression analysis with the help of the IBM SPSS Statistics with crosstabs test. The results of this study indicate that all independent variables have no significant relationship with SBS symptoms experienced by respondents and all independent variables have a very weak correlation. In addition, from 80 respondents, 27 people (33.75%) experienced SBS and 53 people (66.25%) did not experience SBS. This shows that there is a SBS phenomenon in the building. The significance value for all independent variables is greater than the significance level value (&gt;0.05). Furthermore, based on the test criteria, it is concluded that the variable airflow, high temperature, temperature change, low temperature, stale air, dry air, odor, air electrostatics, cigarette smoke, sound level, lighting, and air pollution have approximate significance values greater than 0.05 (null hypothesis was failed to be rejected). It is concluded that those variables have no significant relationship to the dependent variable (the SBS symptoms) experienced by the respondents.

An Actor Critic Method for Free Terminal Time Optimal Control

Optimal control problems with free terminal time present many challenges including nonsmooth and discontinuous control laws, irregular value functions, many local optima, and the curse of dimensionality. To overcome these issues, we propose an adaptation of the model-based actor-critic paradigm from the field of Reinforcement Learning via an exponential transformation to learn an approximate feedback control and value function pair. We demonstrate the algorithm's effectiveness on prototypical examples featuring each of the main pathological issues present in problems of this type.

A Study on Calories Burnt Prediction Using Machine Learning

In this growing technological era, People are less aware of their health and mental stability. Due to lack of time, they intake more junk food than healthy options, which leads to an increase in the total calorie rate in their body. which is a major cause of obesity a calorie is the rate of energy stored and energy expenditure. People nowadays want quick solutions to every problem they want to exercise less and get more results, so to check the level of improvement and the burnt calories level after exercise in the human body we came up with this machine Learning System which takes some attributes as input and gives approximate calories burnt value which will motivate people to do more exercise and will show their daily growth The project is nourished with more than 15,000 data and its MAE (Mean Absolute error) is 1.48 which will enhance over time for better Results.

Stable and Accurate Estimation of SOC Using eXogenous Kalman Filter for Lithium-Ion Batteries

The state of charge (SOC) for a lithium-ion battery is a key index closely related to battery performance and safety with respect to the power supply system of electric vehicles. The Kalman filter (KF) or extended KF (EKF) is normally employed to estimate SOC in association with the relatively simple and fast second-order resistor-capacitor (RC) equivalent circuit model for SOC estimations. To improve the stability of SOC estimation, a two-stage method is developed by combining the second-order RC equivalent circuit model and the eXogenous Kalman filter (XKF) to estimate the SOC of a lithium-ion battery. First, approximate SOC estimation values are observed with relatively poor accuracy by a stable observer without considering parameter uncertainty. Second, the poor accuracy SOC results are further fed into XKF to obtain relative stable and accurate SOC estimation values. Experiments demonstrate that the SOC estimation results of the present method are superior to those of the commonly used EKF method. It is expected that the present two-stage XKF method will be useful for the stable and accurate estimation of SOC in the power supply system of electric vehicles.

On the properties of some inversion methods of the Laplace transform

The problem of inversion of the integral Laplace transform, which belongs to the class of ill-posed problems, is considered. Integral equations are reduced to ill-conditioned systems of linear algebraic equations, in which the unknowns are either the coefficients of the series expansion in terms of special functions, or the approximate values of the desired original at a number of points. Described method of inversion using special quadrature formulas of the highest degree of accuracy and the characteristics of the accuracy and stability of this method are indicated. Quadrature inversion formulas are constructed, which are adapted for the inversion of long-term and slow processes of linear viscoelasticity. A method of deformation of the integration contour in the Riemann-Mellin inversion formula is proposed, which leads the problem to the calculation of certain integrals and allows obtaining error estimates. A method is described for determining the possible breakpoints of the original and calculating the magnitude of the jump at these points.

GLOBAL DYNAMICS OF A MOSQUITO POPULATION SUPPRESSION MODEL UNDER A PERIODIC RELEASE STRATEGY

It has been proved that periodic releases of <i>Wolbachia</i>-infected or irradiation-treated mosquitoes is an effective way to suppress wild mosquitoes and prevent the prevalence of mosquito-borne diseases. We have discussed some cases in consideration of the release amount $c$ and release period $T$, and in this paper we continue to explore the remaining complementary case and investigate the relevant stability of the origin and the exact number of periodic solutions in the switching model. Based on the release period threshold $T^*$ introduced in the extant works, we define a new threshold $T^{**}$ between the sexual lifespan $\bar{T}$ of sterile mosquitoes and $T^*$, and reveal the complete dynamics of the model, particularly, no $T$-periodic solutions when $T\in(\bar{T}, T^{**})$, a unique $T$-periodic solution when $T=T^{**}$, and exactly two $T$-periodic solutions when $T\in(T^{**}, T^*)$. Finally, we give some numerical simulations to seek the approximate value of $T^{**}$ and demonstrate the global dynamical behaviors of wild mosquito population.

An application of approximate dynamic programming in multi-period multi-product advertising budgeting

&lt;p style='text-indent:20px;'&gt;Advertising has always been considered a key part of marketing strategy and played a prominent role in the success or failure of products. This paper investigates a multi-product and multi-period advertising budget allocation, determining the amount of advertising budget for each product through the time horizon. Imperative factors including life cycle stage, &lt;inline-formula&gt;&lt;tex-math id="M1"&gt;\begin{document}$ BCG $\end{document}&lt;/tex-math&gt;&lt;/inline-formula&gt; matrix class, competitors' reactions, and budget constraints affect the joint chain of decisions for all products to maximize the total profits. To do so, we define a stochastic sequential resource allocation problem and use an approximate dynamic programming (&lt;inline-formula&gt;&lt;tex-math id="M2"&gt;\begin{document}$ ADP $\end{document}&lt;/tex-math&gt;&lt;/inline-formula&gt;) algorithm to alleviate the huge size of the problem and multi-dimensional uncertainties of the environment. These uncertainties are the reactions of competitors based on the current status of the market and our decisions, as well as the stochastic effectiveness (rewards) of the taken action. We apply an approximate value iteration (&lt;inline-formula&gt;&lt;tex-math id="M3"&gt;\begin{document}$ AVI $\end{document}&lt;/tex-math&gt;&lt;/inline-formula&gt;) algorithm on a numerical example and compare the results with four different policies to highlight our managerial contributions. In the end, the validity of our proposed approach is assessed against a genetic algorithm. To do so, we simplify the environment by fixing the competitor's reaction and considering a deterministic environment.&lt;/p&gt;

An Adaptive Multi-Level Max-Plus Method for Deterministic Optimal Control Problems

We introduce a new numerical method to approximate the solution of a finite horizon deterministic optimal control problem. We exploit two Hamilton-Jacobi-Bellman PDE, arising by considering the dynamics in forward and backward time. This allows us to compute a neighborhood of the set of optimal trajectories, in order to reduce the search space. The solutions of both PDE are successively approximated by max-plus linear combinations of appropriate basis functions, using a hierarchy of finer and finer grids. We show that the sequence of approximate value functions obtained in this way does converge to the viscosity solution of the HJB equation in a neighborhood of optimal trajectories. Then, under certain regularity assumptions, we show that the number of arithmetic operations needed to compute an approximate optimal solution of a d-dimensional problem, up to a precision ε, is bounded by O(Cd|logε|), for some constant C > 1, whereas ordinary grid-based methods have a complexity in O(1/εad) for some constant a > 0.

Value-gradient iteration with quadratic approximate value functions

We propose a method for designing policies for convex stochastic control problems characterized by random linear dynamics and convex stage cost. We consider policies that employ quadratic approximate value functions as a substitute for the true value function. Evaluating the associated control policy involves solving a convex problem, typically a quadratic program, which can be carried out reliably in real-time. Such policies often perform well even when the approximate value function is not a particularly good approximation of the true value function. We propose value-gradient iteration, which fits the gradient of value function, with regularization that can include constraints reflecting known bounds on the true value function. Our value-gradient iteration method can yield a good approximate value function with few samples, and little hyperparameter tuning. We find that the method can find a good policy with computational effort comparable to that required to just evaluate a control policy via simulation.