Optimal Masses Research Articles

Analytical study on lead elimination by anionic clays: Characterization, adsorption kinetics, isotherm, thermodynamic, mechanism and adsorption

The co-precipitation method synthesized the synthetic anionicMg–Al and Ni-Al clays with three molar ratios (Mg/Al, Ni/Al). The samples were characterized by powder XRD, Fourier transform infrared spectroscopy (FTIR), and scanning electron microscopy (SEM). No other crystalline phases were detected in the powder XRD patterns of the co-precipitated samples. The infrared spectra obtained all the functional groups that characterize these two types of anionic clays. SEM micrographs indicate the presence of particles and aggregates. The particles, or aggregates, are in the form of plates, supported by particles of acceptable sizes. The optimal pH for maximum lead adsorption is about 6.5 for both clays. The optimal adsorbent masses for the maximum percentages of lead removal are 0.2 g for Mg3AlCO3 and 0.25 g for Ni3AlCO3. The Mg3AlCO3 has a maximum adsorption capacity of lead, where qm=73.42 mg g-1. The adsorbed amount increases with increasing temperature for both types of clays studied. The equilibrium time of Pb2+ adsorption is reached after 5 min for both clays. The most appropriate models to describe the experimental data of adsorption kinetics and isotherms are pseudo-second-order and Langmuir. The detection limit (LOD) was 0.272 mg L-1. The linearity range was 1 to 5 mg L-1(R2 0.9997).

Advancing Intact Protein Quantitation with Updated Deconvolution Routines.

Analysis of intact proteins by mass spectrometry enables direct quantitation of the specific proteoforms present in a sample and is an increasingly important tool for biopharmaceutical and academic research. Interpreting and quantifying intact protein species from mass spectra typically involves many challenges including mass deconvolution and peak processing as well as determining optimal spectral averaging parameters and matching masses to theoretical proteoforms. Each of these steps can present informatic hurdles, as parameters often need to be tailored specifically to the data sets. To reduce intact mass deconvolution data analysis burdens, we built upon the widely used "sliding window" mass deconvolution technique with several additional concepts. First, we found that how spectra are averaged and the overlap in spectral windows can be tuned to favor either sensitivity or speed. A multiple window averaging approach was found to be the most effective way to increase mass detection and yielded a >2-fold increase in the number of masses detected. We also developed a targeted feature-finding routine that boosted sensitivity by >2-fold, decreased coefficient of variation across replicates by 50%, and increased the quality of mass elution profiles through 3-fold more detected time points. Lastly, we furthered existing approaches for annotating detected masses with potential proteoforms through spectral fitting for possible proteoform family modifications and network viewing. These proteoform annotation approaches ultimately produced a more accurate way of finding related, but previously unknown proteoforms from intact mass-only data. Together, these quantitation workflow improvements advance the information obtainable from intact protein mass spectrometry analyses.

CatMass: software for calculating optimal sample masses for X-ray absorption spectroscopy experiments involving complex sample compositions.

This paper presents software for calculating the optimal mass of samples with complex compositions (e.g. supported metal catalysts) for X-ray absorption spectroscopy (XAS) and scattering measurements. The ability to calculate the sample mass and other relevant parameters needed for an XAS measurement allows experimentalists to be better prepared in terms of detector selection, energy range of scan and overall time needed to complete the measurement, thus increasing efficiency. CatMass builds on existing sample mass calculators allowing users to determine the optimum sample preparation, collection geometry, usable energy range for a scan and approximate edge step of the absorption event. Visualization tools present the absorption calculation results in a format familiar to XAS experimentalists, with the added ability to save calculations and plots for future reference or recalculation. CatMass is a program broadly applicable in catalysis and is helpful for users with complex samples due to composition/stoichiometry or multiple competing elements.

Energy Minimization of New Robotic-Type Above-Knee Prosthesis for Higher Battery Lifetime

In this paper, an optimization problem for the energy minimization of a new robotic-type three-axes above-knee prosthesis is carried out based on the actuator power consumption. The optimization problem aims to find the optimal link masses with which to minimize the electrical energy drawn from the battery of the new prosthesis, subject to the kinematic and dynamic constraints. Particle swarm optimization (PSO) is used as the optimization algorithm. A discrete-time PID controller is used to represent the saved energy by means of mass optimization. Optimization illustrated that energy consumption in the batteries can be reduced 51% and provides 1.89 h of additional battery lifetime, according to the literature, by optimizing prosthetic link masses while providing acceptable prosthesis stiffness.

Исследования проектного облика электротермического микродвигателя с пористой структурой для двигательных установок малых космических аппаратов

The results of experimental studies on nitrogen with an overpressure of 0,02 MPa resistojet propulsion system of a small spacecraft with a porous structure weighing 45 g and an autonomous heating element with a radius of 3 mm with a power consumption of up to 60 watts for a warm-up time of up to 300 s are presented. The possibility of using a porous structure as a volumetric fuel gas pipeline with an increase in heat transfer intensity has been experimentally proved and the actual specific heat capacity of the porous structure has been determined. Taking into account the actual specific heat capacity, theoretical studies of the mass and geometry of the porous structure in the resistojet composition are carried out, optimal with respect to the autonomous heating element used by the power and the amount of fuel heating in the range (573–1273) K. Taking into account the radius of the heating element, the fuel temperature range (573–973) K corresponding to the optimal masses and radii of the porous structure for the formation of the resistojet design layout is determined.

Application of Metastructures for Targeted Low-Frequency Vibration Suppression in Plates

PurposeWe present an approach that combines finite element analysis and genetic algorithms to find the optimal configuration of local resonators created in the host structure to suppress their vibration in a target low-frequency range. Such local resonators are indeed metastructures that alter the wave propagation in the host structure, thereby attenuating their vibration.MethodsTo demonstrate the approach, we cutout zigzag resonators in a thin aluminium plate that is subjected to base-excitations. The thin plate and the zigzag cutouts are modelled using the finite element method, and the optimal location and optimal tip mass of the zigzag cutouts are obtained using genetic algorithms through iterative simulations. Two case studies are considered, and the fitness function used in the optimization problem is the plate’s root mean square of vibration in a specific low-frequency range. In the first case, the plate has two aligned zigzag cutouts. In this case, the objective is to find the optimal linear location and tip masses of the two zigzag cutouts. In the second case, the plate also has two zigzag cutouts, but their linear and transverse locations can vary along with the respective tip masses. The two optimal specimens are manufactured and tested experimentally.Results Numerical results were compared to experimental results which demonstrate that the proposed approach is reliable and can be used to tune the band gap of plates, thereby maximizing the vibration attenuation in the target frequency range.Conclusion Genetic algorithms can be used along with finite element analysis and zigzag cutouts to tune the band gap of plates subjected to base-excitations. The approach can be extended to plates/structures with other types of excitations and boundary conditions.

Exploring the potential of water injection (WI) in a high-load diesel engine under different fuel injection strategies

Water injection (WI) is a promising technology in diesel engines. However, the joint effects of WI and fuel injection strategy have not been investigated well. Furthermore, the comparison between WI and exhaust gas recirculation (EGR) requires further clarification. This study aims to identify the optimal way of WI and its benefits for a high-load diesel engine operated with various fuel injection strategies. Therefore, four schemes, i.e., diesel single injection strategy with/without WI and diesel double injection strategy with/without WI, were optimized by employing numerical simulation. The optimal water injection timing for single injection strategy is near −108°CA ATDC, while it is 8–20°CA before the first diesel injection for double injection strategy. Water mass is the most decisive parameter, and the optimal water masses are 10%–35% and 29%–51% of the fuel mass, respectively. When WI is employed alone without introducing EGR, NOx can be reduced by 30% and 90% respectively. Compared with EGR, the main superiority of WI is reduced NOx emissions without sacrificing fuel economy until the water mass reaches 50% of the fuel mass. For single injection strategy, the cooling effect of WI is the dominant factor, while for double injection strategy, the dilution effect becomes prominent.

Co-digestion of water hyacinth, municipal solid waste and cow dung: A methane optimised biogas–liquid petroleum gas hybrid system

Fossil fuels are still the major source of energy in developing countries, howbeit expensive and environmentally unsustainable. Co-digestion substrate proportions and the respective biogas potentials for a huge number of biomaterials for anaerobic digestion are yet to be ascertained let alone optimised. This paper presents a novel methane-optimised biogas–liquid petroleum gas hybrid system concept. Herein this research, biogas is produced from the anaerobic co-digestion of water hyacinth, municipal solid waste and cow dung. A model that incorporated seasonal variations of biomass feedstocks was developed; an optimisation problem was formulated and solved using the Optimisation Interface tool (OptiTool) in combination with the Solving Constraint Integer Programs (SCIP) toolbox in Matrix Laboratory (MATLAB). The biogas production reactions are optimised in such a way that the methane component of the biogas is maximised, and the other components minimised by the integration of a model which necessitates the feed in of optimal substrate masses as per the ratios ascertained for the substrates considered thereby yielding a high quality combustible biogas product. The methane-optimised biogas is channelled towards some community gas demand and liquid petroleum gas comes in to fill the discrepancy between the methane-optimised biogas and the gas demand. Consideration of seasonality changes in the availability of substrates in the modelling and optimisation led to an increase of 174.58% in annual biogas output. A 6.97% annual lowest cost savings was realised in winter and 18.24% annual highest cost savings was realised in summer from the methane-optimised biogas–liquid petroleum gas hybrid system.

Thermal performance of a PCM firefighting suit considering transient periods of fire exposure, post – fire exposure and resting phases

Firefighting scenarios may be characterized by various transient periods (i.e. phases), which consist of diverse environmental conditions. Firefighters usually encounter fire exposure, post fire exposure and resting phases. Development of new and improved protective clothing must be able to provide protection throughout all these phases, as burnouts may still occur after fire exposure due to accumulation of heat in the garment. The incorporation of phase change materials (PCMs) in firefighting garments has been shown to minimize the potential of heat hazards only during fire exposure. Thus to get more knowledge on their thermal performance, in the present study, the effect of PCM incorporation in post fire and resting phases were also numerically studied. The numerical code was validated for all phases. Five potential PCM candidates were considered. Exposure phases were characterized by high- medium and low- heat flux intensities (84, 12 and 5 kW∙m−2) with variable exposure times whilst post –exposure and resting phases where characterized by different wind speeds (i.e. ambient convective coefficients). Optimal PCM masses, times to second and third – degree burns as well as PCM suit cooling times were calculated to reflect thermal protective performance in each respective phase. The data generated allows for PCM short-listing from a set of potential PCM candidates along with its geometrical parameters, considering a wide range of characteristics of the various phases that consist a typical firefighting scenario.

Effects of segment masses and cut-off frequencies on the estimation of vertical ground reaction forces in running

The purpose of this study is to examine the effect of the body’s mass distribution to segments and the filtering of kinematic data on the estimation of vertical ground reaction forces from positional data. A public dataset of raw running biomechanics was used for the purposes of the analysis, containing recordings of twenty-eight competitive or elite athletes running on an instrumented treadmill at three different speeds. A grid-search on half of the trials was employed to seek the values of the parameters that optimise the approximation of biomechanical loads. Two-way ANOVAs were then conducted to examine the significance of the parameterised factors in the modelled waveforms. The reserved recordings were used to validate the predictive accuracy of the model. The cut-off filtering frequencies of the pelvis and thigh markers were correlated to running speed and heel-strike patterns, respectively. Optimal segment masses were in agreement with standardised literature reported values. Root mean square errors for slow running (2.5 m/s) were on average equal to 0.1 (body weight normalized). Errors increased with running speeds to 0.13 and 0.18 for 3.5 m/s and 4.5 m/s, respectively. This study accurately estimated vertical ground reaction forces for slow-paced running by only considering the kinematics of the pelvis and thighs. Future studies should consider configuring the filtering of kinematic inputs based on the location of markers and type of running.

State-of-charge estimation based on theory of evidence and interval analysis with differential evolution optimization

In this paper, we propose a new method for estimating the state-of-charge (SoC) of a lithium battery. There are remaining drawbacks of the existing methods, such as inaccurate estimation, high computation, and the need for massive datasets or an expensive sensor. Hence, the technique that we use to resolve such problems is derived from the theory of evidence (Dempster–Shafer theory) in which the degree of belief, namely mass, based on prior knowledge has to be assigned to each source of a variable. The proposed method is based on bounded-error state estimation with forward-backward propagation. However, instead of describing each variable error that propagates in the propagation process by a single error bound or a single interval, we define it by sets of intervals. In addition, to determine the optimal masses assigned to the variables, differential evolution is applied. To evaluate the proposed method, we carried out the experiments that used two different current sensors and two different voltage sensors to represent those variables with varying levels of uncertainty. Experimental results show that the root-mean-square errors of the proposed method are slightly better than those of a Kalman-filtering-based approach. The optimum masses also show the best performance, compared with masses assigned randomly. The results suggest that the proposed method can correctly estimate the SoC of a lithium battery.

Secure multimodal biometric system based on diffused graphs and optimal score fusion

Biometric authentication systems offer potential advantages over traditional knowledge-based methods. However, most of the biometric systems which are extensively used lack template security and robustness. In order to address these issues, in this study, the authors have proposed a multimodal biometric system based on the combination of multiple modalities and optimal score level fusion. In addition, key features are introduced for each modality for generating cancellable biometric features. Features from individual traits are combined with corresponding key features to provide feature transformation. A robust template is generated by diffusion of individual transformed matrices using graph-based random walk cross-diffusion. In addition, individual classifier score is optimally fused using proposed multistage score level fusion model. Optimal belief masses for individual classifier are determined using cuckoo search optimisation. Wherein, optimal classifier beliefs are fused using DSmT based proportional conflict redistribution (PCR-6) rules. Experimental results demonstrate that optimal score fusion applied on cross-diffused features produce better results than existing state-of-the-art multimodal fusion schemes. On average of the outcome, equal error rate and accuracy achieved using the proposed method on four chimeric benchmarked datasets, are 2.32 and 98.316%.

Optimal Body Masses for Different Olympic Sports

Background. The weight of the best athletes at different distances and in different sports can be very different. It is known that rowers, as a rule, are very massive. In order to give a chance to athletes with a small mass, the rowing federation was introduced a special category with the weight restrictions. These facts are connected with the peculiarities of the aerobic and un-aerobic activities, drag and propulsion characteristics. Objective. In this paper, we don’t try to explain the body mass differences. We will only fix them for different sports: running, swimming (free style), skiing, skating, cycling, and rowing and for different Olympic distances. Methods. A significant amount of data on the velocity and body mass of the best athletes professionals (both female and male) in Olympic sports (running, swimming, skiing, skating, cycling and rowing) was collected and analyzed. Since the weights of the best athletes only are taken into consideration, the expected results can be treated as the most suitable (optimal) body masses for different sports and distances. In order to check, how the values of body mass and average speed on the distance fit the linear dependence, the equation of the linear regression was used. The regression coefficient and two parameters of the straight line were calculated. In order to check that the velocity of skating doesn’t depend on the athlete mass, the Fisher test was used. Results. The optimal masses of athletes for different distances and sports were calculated. In general, for the short distances, the large masses of athletes are optimal and they decrease for long distances. Exception is the results for female swimming and running, where the largest masses of athletes correspond to the medium distances. For longer distances, results show that the most performing athletes are characterized by a lower body mass, except for skating. For a fixed distance, the optimal weights of female athletes are 79.5 ± 3.1% of the weight of male athletes, at the same time they develop 89.4 ± 1.8% of the speed of men. Conclusions. The presented statistical analysis indicates that within one distance there is no significant dependence of speed on the mass (the exception is only rowing). For each distance there are their optimal masses of athletes, which are different for different sports. The revealed facts can be used in athlete selection and training. They need also further investigations with the use of the metabolic and propulsion peculiarities.

Versatile Launcher Preliminary Design

Launcher design studies aim at finding the cheapest configuration able to perform a set of reference missions. The design problem is multidisciplinary, involving staging, propulsion, and trajectory optimization. It is also multiobjective because several missions must be considered simultaneously. Such problems are generally addressed by iterative methods splitting the launcher design and the trajectory optimization. An all-in-one solution method is proposed. It is based on an analytical costate guess that significantly reduces the trajectory control variables. The design and trajectory problems can thus be solved simultaneously without iterations in order to find the optimal propellant masses and engine thrust levels. Versatile launcher configurations are easily defined by considering different design options, such as booster addition or upper-stage variable loading. Model uncertainties are also accounted for in order to ensure the performance robustness at a given probability level.

Guidelines for the specification of a PCM layer in firefighting protective clothing ensembles

Phase change materials are increasingly seen not only as a solution to reduce the mismatch between demand and supply of energy, but also as an adequate tool for heat management. Firefighters usually encounter high heat flux exposures, which can cause severe burns. The addition of a PCM layer into a typical firefighting garment ensemble can be used to mitigate this effect, increasing the time to second-degree burns. A numerical approach was used to investigate the effect of PCM latent heat, mass, melting temperature, and position within the garment ensemble, to assess the implications in terms of thermal performance and time to second-degree burns, under high-, medium- and low-intensity heat exposures. Guidelines for the specification of PCM characteristics are provided with respect to the heat exposure scenario considered, to enable informed decisions regarding the choice and features of the PCM, in function of the intended application and required time-windows without burns. The data discussed in this work provide insight on how a PCM layer influences the thermal burden on a firefighter, which enables the estimation of optimal PCM masses, and thus the minimization of the load to be carried by the firefighter, and the costs associated with the integration of high loads of PCM in a garment.

On Minimizing the Maximal Characteristic Frequency of a Linear Chain

We consider a linear chain of masses, each coupled to its two nearest neighbors by elastic springs. The maximal characteristic frequency of this dynamical system is a strictly convex function of certain parameters that depend on the masses and spring elasticities. Minimizing the maximal characteristic frequency under an affine constraint on these parameters is thus a convex optimization problem. For a homogeneous affine constraint, we prove that the mass and elasticity values that minimize the maximal characteristic frequency have a special structure: They are symmetric with respect to the middle of the chain and the optimal masses [spring elasticities] increase [decrease] toward the center of the chain. Intuitively speaking, this means that in order to minimize the maximal characteristic frequency we need to “fix” the center of the chain, by increasing [decreasing] the masses [spring elasticities] there. We further show that minimizing the maximal characteristic frequency of the linear chain is equivalent to maximizing the steady-state protein production rate in an important model from systems biology called the ribosome flow model.

Infinite continuous adaptivity for incompressible SPH

In this paper we introduce a novel method to adaptive incompressible SPH simulations. Instead of using a scheme with a number of fixed particle sizes or levels, our approach allows continuous particle sizes. This enables us to define optimal particle masses with respect to, e.g., the distance to the fluid's surface. A required change in mass due to the dynamics of the fluid is properly and stably handled by our scheme of mass redistribution. This includes temporally smooth changes in particle masses as well as sudden mass variations in regions of high flow dynamics. Our approach guarantees low spatial variations in particle size, which is a core property in order to achieve large adaptivity ratios for incompressible fluid simulations. Conceptually, our approach allows for infinite continuous adaptivity, practically we achieved adaptivity ratios up to 5 orders of magnitude, while still being mass preserving and numerically stable, yielding unprecedented vivid surface detail at comparably low computational cost and moderate particle counts.

Testing the adaptive radiation hypothesis for the lemurs of Madagascar.

Lemurs, the diverse, endemic primates of Madagascar, are thought to represent a classic example of adaptive radiation. Based on the most complete phylogeny of living and extinct lemurs yet assembled, I tested predictions of adaptive radiation theory by estimating rates of speciation, extinction and adaptive phenotypic evolution. As predicted, lemur speciation rate exceeded that of their sister clade by nearly twofold, indicating the diversification dynamics of lemurs and mainland relatives may have been decoupled. Lemur diversification rates did not decline over time, however, as predicted by adaptive radiation theory. Optimal body masses diverged among dietary and activity pattern niches as lineages diversified into unique multidimensional ecospace. Based on these results, lemurs only partially fulfil the predictions of adaptive radiation theory, with phenotypic evolution corresponding to an ‘early burst’ of adaptive differentiation. The results must be interpreted with caution, however, because over the long evolutionary history of lemurs (approx. 50 million years), the ‘early burst’ signal of adaptive radiation may have been eroded by extinction.

Use of Mathematical Modeling in Building Ceramics Functional Properties Studies

The peculiarities of using mathematical and statistical data processing methods in studying the intensification in the process of sintering a ceramic material with a high content of high-calcium waste, and mineralizing sintering lithium-containing waste were studied. The region of optimal ceramic masses composition, which allows obtaining ceramic tiles with high functional properties, was defined.

Properties of Extrudable Moulding Compositions Based on a Mixture Aluminum Hydroxides

Moulding compositions for extrusive granulation were synthesized based on a mixture of aluminum hydroxides prepared by hydration of thermo activated products of hydrargillite – flush and CTA (centrifugal thermal activated) – in electrolyte solutions (NaOH, H2O, HNO3). The molding compositions were obtained by peptization of the hydroxides with nitric acid free of surfactants. Structural and mechanical properties of the compositions such as elasticity (λ), plasticity (Ps), relaxation period (Θ), etc. were determined using an instrument with a plane-parallel gap, the principle of its operation being based on measuring the time tangential shift. The plastic strength (Pm) and optimal moisture content (ϕ) was measured using the penetrometric method by immersing the working body (cone) into the composition under study. The 1 or 2 structuralmechanical type with predominant propagation of slow elastic deformations was shown to be characteristic of the compositions under study. Ranges of elasticity (λ = 0,39÷0,42), plasticity (Ps = (2÷5,6)·10–6 s–1) and relaxation period (Θ =1700÷3350) were determined. The plastic strength (Pm) and optimal masses moisture (φ) were determined to depend on the preparation conditions of the hydroxides and to range as follows: ϕ = 25,98÷30,83 wt.% and Pm = 11,71÷71,44·104 Pa.