Stochastic Modes Research Articles

Real-time reduced-order modeling of stochastic partial differential equations via time-dependent subspaces

We present a new methodology for the real-time reduced-order modeling of stochastic partial differential equations called the dynamically/bi-orthonormal (DBO) decomposition. In this method, the stochastic fields are approximated by a low-rank decomposition to spatial and stochastic subspaces. Each of these subspaces is represented by a set of orthonormal time-dependent modes. We derive exact evolution equations of these time-dependent modes and the evolution of the factorization of the reduced covariance matrix. We show that DBO is equivalent to the dynamically orthogonal (DO) [1] and bi-orthogonal (BO) [2] decompositions via linear and invertible transformation matrices that connect DBO to DO and BO. However, DBO shows several improvements compared to DO and BO: (i) DBO performs better than DO and BO for cases with ill-conditioned covariance matrix; (ii) In contrast to BO, the issue of eigenvalue crossing is not present in the DBO formulation; (iii) In contrast to DO, the stochastic modes are orthonormal, which leads to more accurate representation of the stochastic subspace. We study the convergence properties of the method and compare it to the DO and BO methods. For demonstration, we consider three cases: (i) stochastic linear advection equation, (ii) stochastic Burgers' equation, and (iii) stochastic incompressible flow over a bump in a channel. Overall we observe improvements in the numerical accuracy of DBO compared against DO and BO.

Non-Destructive, Non-Invasive Noise Measurements for Metallic Lithium Anodes for Lithium Ion Batteries

Electrochemical Noise measurements have been in the spotlight of electrochemical analysis for measurements on stochastic modes of corrosion since the days of Dawson (Hladky and Dawson Corrosion Science 21(4), (1981),317-322). More recently, electrochemical noise measurements for fuel cells and batteries came up as non-invasive and non-perturbing testing methods that can be used for research(Journal of The Electrochemical Society, 165 (11) A2557-A2562 (2018)) and a potential real-time monitoring tool (Denisov et.al. Fuel Cells 17,(2017),225-237).Metallic lithium anodes are currently commercially employed for non-rechargeable batteries (e.g LiSOCl2 or LiMnO2). The main hurdle along the way of implementation in rechargeable batteries is the dendrite formation during the charging process (Cheng, et.al. Chem. Rev. 2017, 117, 10403−10473). The formation of dendrites during charging can lead to catastrophic failure of the batteries including thermal runaway. Though studies on avoiding such failures through either modifying the surface of the electrode and/or the kinetics of deposition are underway, however, as indicated by the review: “more smartly designed in situ or operando techniques are urgently needed to track the process in a working cell”.We have been working on battery noise measurements for the past number of years (Turkish Journal of Chemistry, 42, (2018), 859-868). We have recently shown that the noise of primary Li/MnO2 batteries increase to measurable levels upon suffering a short circuit (Journal of the Electrochemical Society 165(11),(2018),A2557-A2562) and that this is due to the uneven discharge of the metallic lithium anode(Journal of the Electrochemical Society, submitted).In this contribution, we are going to be reporting electrochemical noise as a truly operando method to study dendrite formation. As the measurement requires no modification to the cell (i.e. no windows in the case or the current collectors, no geometry change, not a half cell) and no perturbation in the applied current or the voltage, it is the ultimate non-invasive and non-perturbing method that has the potential to be used as not only a research tool, but also a real-time implementable sensor that can be commercially deployed.As shown in the figure below, using a metallic lithium anode, the noise after a charging attempt with a high current does show an increased noise level due to the uneven formation of dendrites. Figure 1

Stochastic thermodynamics and modes of operation of a ribosome: A network theoretic perspective.

The ribosome is one of the largest and most complex macromolecular machines in living cells. It polymerizes a protein in a step-by-step manner as directed by the corresponding nucleotide sequence on the template messenger RNA (mRNA) and this process is referred to as "translation" of the genetic message encoded in the sequence of mRNA transcript. In each successful chemomechanical cycle during the (protein) elongation stage, the ribosome elongates the protein by a single subunit, called amino acid, and steps forward on the template mRNA by three nucleotides called a codon. Therefore, a ribosome is also regarded as a molecular motor for which the mRNA serves as the track, its step size is that of a codon and two molecules of GTP and one molecule of ATP hydrolyzed in that cycle serve as its fuel. What adds further complexity is the existence of competing pathways leading to distinct cycles, branched pathways in each cycle, and futile consumption of fuel that leads neither to elongation of the nascent protein nor forward stepping of the ribosome on its track. We investigate a model formulated in terms of the network of discrete chemomechanical states of a ribosome during the elongation stage of translation. The model is analyzed using a combination of stochastic thermodynamic and kinetic analysis based on a graph-theoretic approach. We derive the exact solution of the corresponding master equations. We represent the steady state in terms of the cycles of the underlying network and discuss the energy transduction processes. We identify the various possible modes of operation of a ribosome in terms of its average velocity and mean rate of GTP hydrolysis. We also compute entropy production as functions of the rates of the interstate transitions and the thermodynamic cost for accuracy of the translation process.

Assessment of Water Supply Dam Failure Risk: Development of New Stochastic Failure Modes and Effects Analysis

This study presents an innovative stochastic approach based on the failure modes and effects analysis to evaluate the failure risk of Amir Kabir dam in Iran. To compute the risk priority number, several risk factors including, occurrence probability, severity, and detectability are quantified using expert opinions. In this way, the participant experts are divided into four groups including; dam operation staff, water company staff, academic staff and, other experts. Moreover, the weights of the expert groups are also considered to compute the risk priority number. Hence, a new failure modes and effects analysis called modified stochastic failure modes and effects analysis is provided by considering weights of expert groups and risk factors. Furthermore, Monte Carlo simulation is used to consider the weights uncertainty and compute a stochastic-based risk priority number. Results show that the first priority failure modes of the upstream and downstream basins of Amir Kabir dam are the human-based failure modes while a nature-based failure mode is observed with most priority in dam body. In general, the proposed stochastic failure risk method provides reliable results with low uncertainty to evaluate the failure modes through a risk assessment process.

Scaling Relations for Solar-Like Oscillations: A Review

The scaling relations for solar-like oscillations provide a translation of the features of the stochastic low-degree modes of oscillation in the Sun to predict the features of solar-like oscillations in other stars with convective outer layers. This prediction is based on their stellar mass, radius and effective temperature. Over time, the original scaling relations have been reversed in their use from predicting features of solar-like oscillations to deriving stellar parameters. Updates to the scaling relations as well as their reference values have been proposed to accommodate for the different requirements set by the change in their use. In this review the suggestions for improving the accuracy of the estimates of stellar parameters through the scaling relations for solar-like oscillations are presented together with a discussion of pros and cons of different approaches.

Fast Beamforming With Fault Tolerance in Massive Phased Arrays Using Intelligent Learning Control

This paper presents a novel algorithm called the recursive intelligent optimizer (RIO) applied to a digital phase control in dynamically reconfigurable phased arrays with applications mainly in radar systems and communication antennas. The RIO belongs to the class of iterative learning control algorithms and operates in deterministic, stochastic, and population initialization modes which are valuable in fast dynamic array reconfiguration. The array factor of a centro-symmetric array is modeled by a linear transformation and mainly optimized for the sidelobe level (SLL), beam steering, and interference suppression. The RIO dynamic reconfiguration is achieved in less than 1.2 s for an array of 100 elements where initial phases are optimized with recursive learning adding up to 5.7 and 8.5 dB to the SLL of 100 and 200 elements arrays, respectively. Failed phase shifters are turned off and the array synthesis is reoptimized for new digital phases with a minimal performance loss. Indeed, the failure of 10% of elements producing a heavy loss of 5.9 dB is fully compensated to a minor loss of 0.3 dB in 441 ms.

Meso-scale transport in sticky granular fluids

Fluid mechanics and rheology involve many unsolved challenges related to the transport mechanisms of mass, momentum and energy – especially when it comes to realistic, industrially relevant materials. Very interesting are suspensions or granular fluids with solid, particulate ingredients that feature contact mechanics on the micro-scale, which affect the transport properties on the continuum- or macro-scale. Their unique ability to behave as either fluid, or solid or both, can be quantified by non-Newtonian rheological rules, and results in interesting mechanisms such as super-diffusion, shear thickening, fluid–solid transitions (jamming) or relaxation/creep. Focusing on the steady state flow of a granular fluid, one can attempt to answer a long-standing question: how do realistic material properties such as dissipation, stiffness, friction or cohesion influence the rheology of a granular fluid? In a recent paper Macaulay & Rognon (J. Fluid Mech., vol. 858, 2019, R2) shed new light on the effect cohesion can have on mass transport in sheared, sticky granular fluids. On top of the usual diffusive, stochastic modes of transport, cohesion can create and stabilise clusters of particles into bigger agglomerates that carry particles over large distances – either ballistically in the dilute regime, or by their rotation in the dense regime. Importantly, these clusters must not only be larger than the particles (defining the intermediate, meso-scale), but they must also have a finite lifetime, in order to be able to exchange mass with each other, which can seriously enhance transport in sticky granular fluids by rotection, i.e. a combination of rotation and convection.

Derandomisation-based multiple frequency control for stochastic Markov jump systems

ABSTRACTUnder the framework of derandomisation approach, the state feedback control issues for both continuous-time and discrete-time Markov jump linear systems (MJLSs) are investigated to meet multiple performance objectives over multiple frequency ranges. Because of the stochastic jumping among different modes, the generalised Kalman–Yakubovic–Popov lemma-based finite-frequency controller design approach cannot be directly applied to MJLSs. To overcome this limitation, a derandomisation approach is established by transforming the original stochastic multiple modes systems to deterministic ones. Then the multiple frequency controllers for both discrete-time and continuous-time MJLSs are designed to guarantee the multiple performances of the closed-loop systems. To verify the effectiveness of the developed algorithms, examples are presented, where the performance requirements include specifications in low-frequency and high-frequency ranges, respectively.

Agricultural tractors of the fifth generation

The article deals with the problem of substantiation of mobile power units (MPU) – tractors for agriculture of the fifth generation. This issue is quite relevant. The main purpose of the work is to analyze agricultural tractors of the fifth generation. The authors formulated the main requirements for the ecological balance of the technogenic interaction of MPUs with production processes in agro-ecosystems of grain production in the zonal conditions of South-Russian arid agriculture. Proposals for the creation of new MPUs have been developed; the technological structures of machine aggregates based on the MPU of the fifth generation of classes 3, 5-6 and 8 that determined the technical schemes of the named MPU were determined. Analytical models for calculating the power characteristics of MPU of the named classes in deterministic and stochastic modes in relation to the most energy-intensive operations with definitions of the mathematical expectations of MTA’s power and performance. Also, an analysis of the MTAs effectiveness based on new MPUs upon criterion of the time spent on cultivating crop rotations on the examples of peasant farms and agricultural organizations (APC, CAE, etc.)

Dual Dynamically Orthogonal approximation of incompressible Navier Stokes equations with random boundary conditions

In this paper we propose a method for the strong imposition of random Dirichlet boundary conditions in the Dynamical Low Rank (DLR) approximation of parabolic PDEs and, in particular, incompressible Navier Stokes equations. We show that the DLR variational principle can be set in the constrained manifold of all S rank random fields with a prescribed value on the boundary, expressed in low rank format, with rank smaller then S. We characterize the tangent space to the constrained manifold by means of a Dual Dynamically Orthogonal (Dual DO) formulation, in which the stochastic modes are kept orthonormal and the deterministic modes satisfy suitable boundary conditions, consistent with the original problem. The Dual DO formulation is also convenient to include the incompressibility constraint, when dealing with incompressible Navier Stokes equations. We show the performance of the proposed Dual DO approximation on two numerical test cases: the classical benchmark of a laminar flow around a cylinder with random inflow velocity, and a biomedical application for simulating blood flow in realistic carotid artery reconstructed from MRI data with random inflow conditions coming from Doppler measurements.

Improving industrial pipeline transport using research of regularities of flow of mixtures in material pipeline

Highly efficient energy-saving methods of pipeline transport have been developed on the basis of modern scientific approaches. A general concept and its implementation on the synergetic basis have been proposed. It is shown that stochastic motion modes arise while passing through intermittence, i.e. they are the result of collision of asymptotically stable and unstable motion states. It has been established that flow of air-fuel mixtures with inner weaves and inner portion turbulent motions is considered as a process of self-organization with collective flows. At the same time, effective coefficients of transfer of momentum, force and mass of the moving material flow are determined. The hypothesis of emergence of stochastic motion modes that arise during transition through intermittency has been justified, which makes it possible to derive the regularity of collision of asymptotically stable and unstable flows of air-fuel mixtures. The rheological model for flow of non-Newtonian fluids is proposed that takes into account the flow features, which makes it possible to determine the shear stress and viscosity of CWF at different values of the shear velocity. The mathematical model takes into account independent rheological parameters of the suspension, which depend on concentration and granulometric composition of coal, as well as on high-speed transportation modes. It has been established that the process of self-organization of mass transfer in the pneumatic transport pipeline is carried out by additional energy supply of the moving material flow and provides creation of additional vorticity of the flow. There have been determined the main tasks solved by intensification of the processes in the transport pipeline, which makes it possible to increase efficiency of its operation.

Stochastic modelling and diffusion modes for proper orthogonal decomposition models and small-scale flow analysis

We present here a new stochastic modelling approach in the constitution of fluid flow reduced-order models. This framework introduces a spatially inhomogeneous random field to represent the unresolved small-scale velocity component. Such a decomposition of the velocity in terms of a smooth large-scale velocity component and a rough, highly oscillating component gives rise, without any supplementary assumption, to a large-scale flow dynamics that includes a modified advection term together with an inhomogeneous diffusion term. Both of those terms, related respectively to turbophoresis and mixing effects, depend on the variance of the unresolved small-scale velocity component. They bring an explicit subgrid term to the reduced system which enables us to take into account the action of the truncated modes. Besides, a decomposition of the variance tensor in terms of diffusion modes provides a meaningful statistical representation of the stationary or non-stationary structuration of the small-scale velocity and of its action on the resolved modes. This supplies a useful tool for turbulent fluid flow data analysis. We apply this methodology to circular cylinder wake flow at Reynolds numbers $Re=100$ and $Re=3900$. The finite-dimensional models of the wake flows reveal the energy and the anisotropy distributions of the small-scale diffusion modes. These distributions identify critical regions where corrective advection effects, as well as structured energy dissipation effects, take place. In providing rigorously derived subgrid terms, the proposed approach yields accurate and robust temporal reconstruction of the low-dimensional models.

Stochastic model order reduction in randomly parametered linear dynamical systems

• Stochastic model order reduction for randomly parametered linear dynamical structures. • Reduction in state-space dimension using SEREP. • Development of surrogate model in the reduced state space using PCE. • Significant savings in computational costs for reliability analysis of large systems. • Proposed methodology enables using existing commercial FE softwares. This study focuses on the development of reduced order models for stochastic analysis of complex large ordered linear dynamical systems with parametric uncertainties, with an aim to reduce the computational costs without compromising on the accuracy of the solution. Here, a twin approach to model order reduction is adopted. A reduction in the state space dimension is first achieved through system equivalent reduction expansion process which involves linear transformations that couple the effects of state space truncation in conjunction with normal mode approximations. These developments are subsequently extended to the stochastic case by projecting the uncertain parameters into the Hilbert subspace and obtaining a solution of the random eigenvalue problem using polynomial chaos expansion. Reduction in the stochastic dimension is achieved by retaining only the dominant stochastic modes in the basis space. The proposed developments enable building surrogate models for complex large ordered stochastically parametered dynamical systems which lead to accurate predictions at significantly reduced computational costs.

Intrusive Galerkin Projection for Model Order Reduction of Uncertain Linear Dynamic Systems

This paper deals with model order reduction of random parameter-dependent (RPD) linear time invariant (LTI) systems by using the RPD-balanced realization (BR), recently developed by the same authors. A novel way to deal with this crucial issue is presented. It is based on the intrusive Galerkin projection of the RPD-BR. Indeed, it is shown, through numerical simulations, that the intrusive Galerkin projection of the RPD-BR into the generalized polynomial chaos (GPC) space enables to generate a deterministic realization preserving stability properties for the original RPD-model. Moreover, the new deterministic state variables, which are the stochastic modes of the RPD-balanced state variables, are ordered with respect to their sub-contributions to the RPD-input/output behaviour, measured by deterministic Hankel values. Hence, a deterministic reduced order model is derived by deleting the state variables with small Hankel values and the complete RPD-reduced order model is then obtained. The feasibility of the proposed method is analyzed while its accuracy is compared to the RPD-truncated balanced realization (RPD-TBR).

Stabilization of stochastic operating modes in the flow reactor

A conceptual multistable model of the flow reactor proposed by Volter and Salnikov is studied in the presence of random disturbances. A stochastic excitability of this system, even in a zone of stable equilibria, is explained by the high stochastic sensitivity. Such high stochastic sensitivity of the equilibrium can be a basic reason of the noise-induced destruction of the operating mode. For the stabilization of the stochastic flow reactor, a theory of the synthesis of the assigned low stochastic sensitivity is suggested. It is shown how to use this control approach and construct an appropriate regulator which suppresses unwanted large-amplitude stochastic oscillations and provide a proper operation of the flow reactor.

Wave scattering method for dynamic response analysis of structures with stochastic parameters

ABSTRACTThe wave scattering method is presented to analyze dynamic response of frameworks with stochastic parameters. First, with the uncertain physical, geometric, and loading properties in consideration, the stochastic waveguide equations containing the axial, torsional and flexural wave modes are established. Second, the stochastic wave scattering equation and wave translation matrix are derived to obtain the wave modes. Third, the methodology to extract the generalized displacements and forces from stochastic wave modes is proposed. Finally, a cantilever beam, a planar framework, and a space framework have been presented as numerical examples to illustrate the efficiency of the proposed method. It is found that the results obtained by the proposed method with higher computational efficiency show an excellent agreement with those by Monte Carlo simulation method. Furthermore, the influences of stochastic parameters on dynamic response are revealed.

Starquakes spring stellar surprises

Don Kurtz, Simon Jeffrey and Conny Aerts describe discoveries in the new era of precision asteroseismology. We call it the “Tychonic Principle”: a revolutionary improvement in observational precision inevitably leads to discovery. For Tycho Brahe, the improvement was in precision of astromet- ric position; for us, over the decades since we were students, it has been orders of magnitude improvement in the precision of radial velocity and photometric measure- ments for stars. Three decades ago, stellar radial velocities were measured to 1 kms–1 precision; now, in the best cases they are measured to 10s of cms–1. Three decades ago, stellar light variability was measured to mmag precision (one part per thousand); now in the best cases it is measured to better than µmag precision (one part per million). Stellar astrophysics is being revo- lutionized by this new ultra-high precision. The driving force has been the search for exoplanets. The two main techniques for exoplanet searches – radial velocity and transit measurements – require exquisite precision to detect either the tiny perturba- tive motion of a star being tugged about by a planet, or the slight drop in stellar bright- ness as a planet transits its star. The improvement in radial velocity preci- sion came about from brilliant engineering: 1 Luminosity– effective temperature (Hertzsprung–Russell) diagram showing locations of major pulsating variables coloured roughly by spectral type, the zero- age main sequence and horizontal branch, the Cepheid instability strip, and evolution tracks for model stars of various masses, indicated by small numbers (M⊙). Shadings represent heat-engine p modes (\\\), g modes (///) and strange modes (|||) and acoustically driven stochastic modes (≡). Rough spectral types are shown on the top axis. (Based on figures by J Christensen-Dalsgaard and then by CS Jeffery. See Jeffery & Saio 2016) of stellar apparent brightnesses – the µmag revolution – came with space missions that took photometers above the Earth’s atmos- phere. The highest precision ground-based photometry of one particular star reached 14 µmag – 14 parts per million (Kurtz et al. 2005) – in pulsation amplitude, but typically 1 mmag has been considered old photoelectric photometers, or dozens with CCDs on the ground. The third – and for some purposes the most important – benefit is the nearly continuous observa- tions for four years of about 150000 stars. For decades, groups of astronomers have organized campaigns to observe pulsating stars contemporaneously ground-based spectrographs have been placed in temperature-stabilized vacuums on vibrationally stable platforms with the light from the telescope fibre-fed to the ultra-stable spectrographs. For exoplanet good. With the advent of the French-led ESA CoRoT mis- sion and the NASA Kepler mission, it has become pos- sible to reach µmag precision “Stellar astrophysics is being revolutionized by this new ultra-high precision” from observatories around the world to try to get con- tinuous measurement of the changes in stellar brightness; one project for this is called searches the spectroscopic measurements have to provide true radial velocities to feed into Newton’s form of Kepler’s third law to determine the planets’ masses. This carries its own difficulties; at radial velocity preci- sion better than 1 ms–1 even the definition of radial velocity is interestingly complex (Lindegren & Dravins 2003). But, for astero- seismology, the fundamental data are the pulsation frequencies, with only secondary information coming from the amplitudes of the radial velocity excursions. The improvement in the measurement for thousands of stars simultaneously. The planet hunters have built beautifully stable spectrographs and ultra-precise photometers in their search for exoplanets; we asteroseismologists have used those precision data for new stellar astrophysics. Here, we are primarily showing results from the Kepler mission. For asteroseismol- ogy this mission provided multifold ben- efits over ground-based observations. The obvious one is the µmag precision; another is the observation of 200000 stars simulta- neously, instead of just one at a time with the “Whole Earth Telescope”, (WET; see Provencal et al. 2014). But where WET can observe a single target, or a few targets, for several weeks with duty cycles (fraction of time observing out of the full time possible) of, say, 50%, Kepler observations have bet- ter than 90% duty cycles for four years for 150000 stars. For many asteroseismic tar- gets this unprecedented length of observing time has been the key to discovery. So the planet hunters drove the technol- ogy development. We asteroseismologists have put that technology to excellent use. In

Influence of household air-conditioning use modes on the energy performance of residential district cooling systems

During technical evaluations of cooling systems in residential buildings, it is necessary to consider the influence of the household air-conditioning (AC) use modes. In other words, how the occupants control the AC, for instance, when it is turned on, what the temperature setting is, and how long it is used. Field measurements and spot interviews indicate that AC usage by residents should be environmental, event and random related. A reduced-order AC conditional probability (CP) model was developed in this study to describe AC usage. The AC CP model was integrated with a building energy modeling program (BEMP) to reflect the interaction of the AC operation and the indoor environment. With consideration of stochastic AC use modes, the uncertainty of user compositions was studied. Additionally, simulation results revealed that AC use modes and user compositions can cause up to a 4.5-fold difference in the system efficiency of district cooling systems. The Lorenz curve and Gini coefficient were applied in this study to describe the load distribution in a quantitative manner. Through a comparison with the constant schedule definition model, the study also identified inclusion of the stochastic feature of AC use modes and their compositions in simulations as being important to the technical evaluation of district cooling systems.

Recent Advances in Physics of Fluid Parametric Sloshing and Related Problems

Liquid parametric sloshing, known also as Faraday waves, has been a long standing subject of interest. The development of the theory of Faraday waves has witnessed a number of controversies regarding the analytical treatment of sloshing modal equations and modes competition. One of the significant contributions is that the energy is transferred from lower to higher harmonics and the nonlinear coupling generated static components in the temporal Fourier spectrum, leading to a contribution of a nonoscillating permanent sinusoidal deformed surface state. This article presents an overview of different problems of Faraday waves. These include the boundary value problem of liquid parametric sloshing, the influence of damping and surfactants on the stability and response of the free surface, the weakly nonlinear parametric and autoparametric sloshing dynamics, and breaking waves under high parametric excitation level. An overview of the physics of Faraday wave competition together with pattern formation under single-, two-, three-, and multifrequency parametric excitation will be presented. Significant effort was made in order to understand and predict the pattern selection using analytical and numerical tools. Mechanisms for selecting the main frequency responses that are different from the first subharmonic one were identified in the literature. Nontraditional sources of parametric excitation and Faraday waves of ferromagnetic films and ferrofluids will be briefly discussed. Under random parametric excitation and g-jitter, the behavior of Faraday waves is described in terms of stochastic stability modes and spectral density function.

Molecular recognition of HER-1 in whole-blood samples.

Multimode sensing was proposed for molecular screening and recognition of HER-1 in whole blood. The tools used for molecular recognition were platforms based on nanostructured materials such as the complex of Mn(III) with meso-tetra (4-carboxyphenyl) porphyrin, and maltodextrin (dextrose equivalence between 4 and 7), immobilized in diamond paste, graphite paste or C60 fullerene paste. The identification of HER-1 in whole-blood samples, at molecular level, is performed using stochastic mode and is followed by the quantification of it using stochastic and differential pulse voltammetry modes. HER-1 can be identified in the concentration range between 280 fg/ml and 4.86 ng/ml using stochastic mode, this making possible the early detection of cancers such as gastrointestinal, pancreatic and lung cancers. The recovery tests performed using whole-blood samples proved that the platforms can be used for identification and quantification of HER-1 with high sensitivity and reliability in such samples, these making them good molecular screening tools.