Desired Error Research Articles

Analytical performance of feline plasma on current Heska and IDEXX point-of-care biochemistry analyzers compared with a commercial laboratory analyzer.

Point-of-care (POC) biochemistry analyzers are widely used in small animal clinical practice but infrequently independently assessed for performance. To assess the performance of two current model point-of-care biochemistry analyzers (Heska Element DC and IDEXX Catalyst) compared with a commercial laboratory analyzer (Cobas 8000). One hundred twenty-one cats from a feline hospital population were sampled with plasma results from a single lithium heparin tube assessed on all three analyzers. Plasma biochemistry results from each POC analyzer were compared with the commercial laboratory analyzer using Bland-Altman difference plots and by determining whether the limits of agreement (LOAs) (95% of differences) fell within various quality goals after correcting for inherent bias. Only 7 of 14 analytes on the Heska analyzer and 2 analytes on the IDEXX analyzer attained the most stringent LOA quality goal, which was being within desirable total error based on biologic variation (TEdes). The number of analytes achieving quality goals increased with less stringent standards such as American Society of Veterinary Clinical Pathologists allowable total error (ASVCP TEA) guidelines or if <95% of clinical comparisons reaching these quality goals is considered acceptable. Widespread bias was found between both POC analyzers and the commercial laboratory analyzer. The performance of both POC biochemistry analyzers was variable compared with a commercial laboratory analyzer. Performance goals were only able to be attained after the bias for each analyzer was accounted for by offsetting the LOAs and quality goals set by the mean bias for each analyte on each analyzer.

Anxiety-Related Factors Associated With Symptom Severity in Irritable Bowel Syndrome in Jazan, Saudi Arabia.

This study in Jazan, Saudi Arabia aims to identify anxiety-related factors associated with symptom severity in irritable bowel syndrome (IBS). IBS is a common gastrointestinal disorder causing abdominal pain and altered bowel habits. The prevalence of IBS in Saudi Arabia is estimated to be 10%-20% among the general population. Therefore, the present study aimed todetermine anxiety-related factors associated with symptom severity in irritable bowel syndrome in Jazan, Saudi Arabia. Understanding these factors will provide insights into the overall impact of IBS on patients' quality of life. The study utilized a cross-sectional, descriptive observational design to examine the general population in Jazan, Saudi Arabia. The sample size of 385 individuals was calculated based on the population size and desired error margin. A convenience sampling technique was employed to select participants who met the inclusion criteria. A validated anonymous self-administered electronic survey was distributed through social media channels. The survey consisted of four sections gathering demographic information, personal risk factors, IBS types with anxiety and risk factors, and a questionnaire to determine the level of anxiety. A pilot study was conducted to improve the survey's clarity. Ethical considerations were followed, and data were analyzed using Statistical Package for Social Sciences (SPSS; IBM Corp., Armonk, NY, USA). Descriptive statistics and significance tests were performed. A study with 637 participants found a 31.08% prevalence of IBS, which was more common in females. Participants with IBS had a higher rate of chronic disease. There were no significant differences in demographic factors between IBS and non-IBS participants. The duration of IBS diagnosis varied, with the majority of IBS with diarrhea (IBS-D) sufferers being diagnosed five years prior. Symptom severity differed among IBS types, with those with an unspecified type reporting the highest percentage of severe symptoms. IBS types were also correlated with anxiety levels, with IBS-D sufferers reporting moderate anxiety and those with an unspecified type reporting severe anxiety. A study with 637 participants found the prevalence of IBS to be 31.08%, with higher rates in females. IBS was associated with chronic diseases and higher anxiety levels. The findings emphasize the need for comprehensive management of IBS, including psychological interventions and dietary modifications, to improve patients' overall health and quality of life. Further research on genetic and modifiable risk factors is needed.

Compression of electrical code violation recognition data using the improved swinging door trending algorithm

Abstract Aiming at the challenge of storing massive power grid data, this paper proposes an improved swing gate trend algorithm to effectively compress 5G data. The algorithm first performs least squares smoothing on the original data to reduce noise interference on the SDT algorithm, which enables the data compression process to more accurately determine the data trend. Further, the shortcomings of the original SDT algorithm are improved, including adaptive frequency conversion data processing, dynamic threshold adjustment, and anomaly recording strategy, to enhance the practicality and efficiency of the algorithm. Through simulation analysis and example data validation, the study shows that the data compression ratio can be stabilized at about 23.98 when the data compression time reaches 1.6 minutes, and the actual error is very close to the desired error. The time overhead of the improved SDT algorithm is only 0.225 seconds, indicating that the algorithm is efficient and reliable. Combined with different data compression storage strategies, the algorithm can further reduce the data compression time. This study provides an adequate data compression method for electric code violation identification, which offers a practical solution for processing and storing large-scale grid data.

A new error estimates of finite element method for (2+1)-dimensional nonlinear advection-diffusion model

This paper designs, analyzes, and implements a finite element analysis for the simulation of the nonlinear advection-diffusion model. The key feature of the proposed work is to provide novel a priori error estimates in Bôchner norms L2(0,T;H01(Ω)) and L∞(0,T;H01(Ω)) simultaneously. To achieve the desired error estimates for both semidiscrete and fully discrete schemes, our idea is to introduce the Ritz projection operator that allows us to enforce the known estimates for P1 and P2 finite elements in the formulation of the desired results. Further, this paper establishes the stability, existence, and uniqueness in the precise normed spaces. Finally, we prove the fully discrete error estimates using the Backward Euler and Crank-Nicolson's schemes which are corroborated by numerical experiments to validate the developed theory on various domains for both schemes. To the best of author's knowledge, this is the first finite element simulation that provides the estimates in the L2 Bôchner norm for any such types of time-dependent problems.

Six-minute, in vivo MRI quantification of proximal femur trabecular bone 3D microstructure.

Assessment of proximal femur trabecular bone microstructure in vivo by magnetic resonance imaging has recently been validated for acquiring information independent of bone mineral density in osteoporotic patients. However, the requisite signal-to-noise ratio (SNR) and resolution for interrogation of the trabecular microstructure at this anatomical location prolongs the scan duration and renders the imaging protocol clinically infeasible. Parallel imaging and compressed sensing (PICS) techniques can reduce the scan duration of the imaging protocol without substantially compromising image quality. The present work investigates the limits of acceleration for a commonly used PICS technique, ℓ1-ESPIRiT, for the purpose of quantifying measures of trabecular bone microarchitecture. Based on a desired error tolerance, a six-minute, prospectively accelerated variant of the imaging protocol was developed and assessed for intersession reproducibility and agreement with the longer reference scan. To investigate the limits of acceleration for MRI-based trabecular bone quantification by parallel imaging and compressed sensing reconstruction, and to develop a prototypical imaging protocol for assessing the proximal femur microstructure in a clinically practical scan time. Healthy participants (n=11) were scanned by a 3D balanced steady-state free precession (bSSFP) sequence satisfying the Nyquist criterion with a scan duration of about 18min. The raw data were retrospectively undersampled and reconstructed to mimic various acceleration factors ranging from 2 to 6. Trabecular volumes-of-interest in four major femoral regions (greater trochanter, intertrochanteric region, femoral neck, and femoral head) were analyzed and six relevant measures of trabecular bone microarchitecture (bone volume fraction, surface-to-curve ratio, erosion index, elastic modulus, trabecular thickness, plates-to-rods ratio) were obtained for images of all accelerations. To assess agreement, median percent error and intraclass correlation coefficients (ICCs) were computed using the fully-sampled data as reference. Based on this analysis, a prospectively 3-fold accelerated sequence with a duration of about 6min was developed and the analysis was repeated. A prospective acceleration factor of 3 demonstrated comparable performance in reproducibility and absolute agreement to the fully-sampled scan. The median CoV over all image-derived metrics was generally <6% and ICCs >0.70. Also, measurements from prospectively 3-fold accelerated scans demonstrated in general median percent errors of <7% and ICCs >0.70. The present work proposes a method to make in vivo quantitative assessment of proximal femur trabecular microstructure with a clinically practical scan duration of about 6min.

A Comprehensive Model for Efficient Design Space Exploration of Imprecise Computational Blocks

After almost a decade of research, development of more efficient imprecise computational blocks is still a major concern in imprecise computing domain. There are many instances of the introduced imprecise components of different types, while their main difference is that they propose different precision-cost-performance trade-offs. In this paper, a novel comprehensive model for the imprecise components is introduced, which can be exploited to cover a wide range of precision-cost-performance trade-offs, for different types of imprecise components. The model helps to find the suitable imprecise component based on any desired error criterion. Therefore, the most significant advantage of the proposed model is that it can be simply exploited for design space exploration of different imprecise components to extract the suitable components, with the desired precision-cost-performance trade-off for any specific application. To demonstrate the efficiency of the proposed model, two novel families of Lowest-cost Imprecise Adders (LIAs) and Lowest-cost Imprecise Multipliers (LIMs) are introduced in the paper, which are systematically extracted based on exploration of the design space provided by the proposed model. A wide range of simulation and synthesis results are also presented in the paper to prove the comparable efficiency of the systematically extracted LIA/LIM structures with respect to the most efficient existing human-made imprecise components both individually and in a Multiply-Accumulate application.

Evaluation of equivalent linearization methods of MDOF isolated structures in response spectrum analysis

In the seismic design of isolated structures, equivalent linearization of the hysteretic isolators is normally considered. There exist many equivalent linearization methods and evaluation of these methods has been widely studied. However, most of the previous studies concern a single degree of freedom system only, and the used analysis method is time history analysis. In such a case, the evaluation heavily depends on the ground motions selected. Note that the response spectrum analysis is a commonly used method for seismic design of structures. Therefore, it is more valuable to evaluate these equivalent linearization methods based on the response spectrum analysis. In this study, a multiple degree of freedom model is adopted due to the contribution of higher modes of the superstructure to the seismic responses, and the procedure of the response spectrum analysis in conjunction with the equivalent linearization method is presented in detail. Then, considering a series of parameters of isolators, a statistical study is performed to evaluate the accuracy of these equivalent linearization methods by comparing with the nonlinear time history analysis. Moreover, the effect of the damping reduction factor for the response spectrum on the accuracy of the equivalent linearization methods is discussed in terms of probability in a desirable error range. The analytical results show that the accuracy of the equivalent linearization methods is associated with the earthquake intensity. Meanwhile, for different response quantities the accuracy of each equivalent linearization method varies significantly. In addition, to estimate the seismic responses with a better accuracy in the response spectrum analysis, a suitable damping reduction factor should be considered.

A New Receiver Design for Protograph-Coded Reference Reused DCSK Systems

In this letter, we investigate the performance of protograph-coded reference reused differential chaos shift keying (DCSK) systems to improve the transmission reliability. The traditional protograph-coded DCSK receiver does not take full advantage of the reused chaotic reference signals and hence cannot obtain desirable error performance. To solve this problem, we design a new receiver architecture called <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">weighted reference estimation and iterative decoding (WRE-ID)</i> , which can universally improve the performance of protograph-coded reference reused DCSK systems over both multipath Rayleigh fading and additive white Gaussian noise channels. In particular, we put forward the WRE algorithm to estimate reference signal in order to calculate log-likelihood ratio (LLR) more precisely. Furthermore, extrinsic information output from the decoder is utilized to iteratively recalculate the weight of the WRE algorithm. As a further illustration, we derive the LLR expressions of the proposed WRE-ID-aided receiver of a typical protograph-coded reference reused DCSK (i.e., high-efficiency DCSK) system. Analytical and simulated results show that the proposed WRE-ID-aided receiver can always overtake the traditional receivers in reference reused DCSK systems. Hence, the protograph-based reference reused DCSK systems with the proposed receiver are very promising for high-rate high-reliability wireless applications.

Admixed high-performance concrete property prediction by novel regression-based models

High-performance concrete (HPC) is one of the most important elements in constructing bridges, skyscrapers, and dams. This concrete additive plays a very important role in performance and response to inflow loads such as earthquakes and dead loads. Fly ash (Fa) and Micro-silica (Ms) are additives added to concrete by cement to reduce water to cement. Increase the ratio and increase the hardening of the cement. This will improve the compressive strength (Cs) of the concrete. Modeling is required for this type of structure. The radial basis function (RBF) is one of the models that can produce better and more rational results. This model combines two optimizers, the Sine Cosine Algorithm (SCA) and the Artificial hummingbird algorithm (AHA), in the framework of RBF-SCA and RBF-AHA, which are considered to be new and effective initiatives in the field of algorithms. The lowest amount of error parameters contains: (RMSE = 2.58), (NMSE = 6.59), and (U95 = 7.16) for RBF-AHA in the train section and the test section (MBE = – 0.1929). The (Tstate = 0.285) in the train section of the RBF-SCA has the lowest compared to another section. RBF-AHA has the highest R2 value of 97.15% in the training area. Both hybrid models can have the desired error and the correct percentage based on the given output. However, the RBF-AHA model may look more powerful in this modeling.

A Wireless Channel Equalization Method Based on Hybrid Whale Optimization: For Constant Modulus Blind Equalization System

This paper proposes a wireless channel equalization method applied to the constant modulus blind equalization system, which addresses the slow convergence and strong randomness in the initialization of equalizer weights in the constant modulus blind equalization algorithm (CMA) by introducing a hybrid arithmetic whale optimization algorithm (HAWOA). The mean square error in the CMA is utilized as the cost function for the HAWOA to obtain a more effective initial weights for the equalizer. To validate the superiority of the hybrid arithmetic whale constant modulus blind equalization algorithm, tests are conducted on the equalization system using 16QAM and 64QAM signals. The simulation results demonstrate that the proposed algorithm achieved better initial weights compared to the CMA and the constant modulus blind equalization algorithm based on the whale optimization algorithm. It can obtain the desired mean square error with a lower symbol error rate in fewer iterations. Furthermore, the hybrid arithmetic whale constant modulus blind equalization algorithm exhibited faster convergence in optimizing initial weights, effectively enhancing the equalization performance of the CMA in wireless channels while ensuring timeliness.

The stability of C-peptide and insulin in plasma and serum samples under different storage conditions.

C-peptide and insulin are peptide hormones and their stability is affected by a number of pre-analytical factors. The study aimed to investigate the impact of sample type, storage temperature and time delays before centrifugation and analysis on the stability of C-peptide and insulin. Ten healthy non-diabetic adults in fasting and non-fasting state were enrolled. 40 mL of blood was collected from each participant into SST and dipotassium EDTA tubes. Samples were centrifuged immediately or at timed intervals (8, 12, 48 and 72 h). After baseline measurements on the Roche Cobas e602 analyzer using electrochemiluminescence immunoassays, aliquots were stored at room temperature (RT), 2-8 and-20 °C for 4 h to 30 days. The percentage deviation (PD) from baseline was calculated and a change greater than desirable biological variation total error was considered clinically significant. C-peptide was more stable in separated serum than plasma (PD of-5 vs.-13 %) samples stored at 2-8 °C for 7 days and was most unstable at RT when centrifugation was delayed (PD-46 % in plasma and-74 % in serum after 48 h). Insulin was more stable in plasma than in serum under the different storage conditions with a minimum PD of-1% when stored at-20 °C for 30 days. When samples were kept unspun at RT for 72 h, PD was-23 and-80 % in plasma and serum, respectively. C-peptide was more stable in serum provided the sample was centrifuged immediately and stored in the fridge or freezer while insulin was found to be more stable in EDTA plasma.

An Experimental Study on Trajectory Tracking Control of Torpedo-like AUVs Using Coupled Error Dynamics

In this paper, we propose a trajectory tracking controller with experimental verification for torpedo-like autonomous underwater vehicles (AUVs) with underactuation characteristics. The proposed controller overcomes the underactuation problem by designing the desired error dynamics in a coupled form using state variables in body-fixed and world coordinates. Unlike the back-stepping control requiring high-order derivatives of state variables, the proposed controller only requires the first derivatives of the states, which can alleviate noise magnification issues due to differentiation. We adopt time delay estimation to estimate the dynamics indirectly using control inputs and vehicle outputs, making the proposed controller relatively easy to apply without requiring the all of the vehicle dynamics. We also address some practical issues that commonly arise in experimental environments: handling measurement noises and actuation limits. To mitigate the effects of noise on the controller, a filtering technique using a moving window average is employed. Additionally, to account for the actuation limits, we design an anti-windup structure that takes into consideration the nonlinearity between the thrusting force and rotating speed of the thruster. We verify the tracking performance of the proposed controller through experimentation using an AUV. The experimental results show that the 3D motion control of the proposed controller exhibits an RMS error of 0.3216 m and demonstrate that the proposed controller achieves accurate tracking performance, making it suitable for survey missions that require tracking errors of less than one meter.

Proximal Stochastic Recursive Momentum Methods for Nonconvex Composite Decentralized Optimization

Consider a network of N decentralized computing agents collaboratively solving a nonconvex stochastic composite problem. In this work, we propose a single-loop algorithm, called DEEPSTORM, that achieves optimal sample complexity for this setting. Unlike double-loop algorithms that require a large batch size to compute the (stochastic) gradient once in a while, DEEPSTORM uses a small batch size, creating advantages in occasions such as streaming data and online learning. This is the first method achieving optimal sample complexity for decentralized nonconvex stochastic composite problems, requiring O(1) batch size. We conduct convergence analysis for DEEPSTORM with both constant and diminishing step sizes. Additionally, under proper initialization and a small enough desired solution error, we show that DEEPSTORM with a constant step size achieves a network-independent sample complexity, with an additional linear speed-up with respect to N over centralized methods. All codes are made available at https://github.com/gmancino/DEEPSTORM.

Half-plane point retrieval queries with independent and dependent geometric uncertainties

This paper addresses a family of geometric half-plane retrieval queries of points in the plane in the presence of geometric uncertainty. The problems include exact and uncertain point sets and half-plane queries defined by an exact or uncertain line whose location uncertainties are independent or dependent and are defined by k real-valued parameters. Point coordinate uncertainties are modeled with the Linear Parametric Geometric Uncertainty Model (LPGUM), an expressive and computationally efficient worst-case, first order linear approximation of geometric uncertainty that supports parametric dependencies between point locations. We present an efficient O(k2) time and space algorithm for computing the envelope of the LPGUM line that defines the half-plane query. For an exact line and an LPGUM n points set, we present an O(log⁡nk+mk) time query and O(nk) space algorithm, where m is the number of LPGUM points on or above the half-plane line. For a LPGUM line and an exact points set, we present a O(k2+(klog⁡nlog⁡log⁡n)ε+m) time and O(n2log⁡n+kε) space approximation algorithm, where 0<ε≤1 is the desired approximation error. For a LPGUM line and an LPGUM points set, we present two O(k2+(klog⁡nklog⁡log⁡nk)ε+mk) and O(mk2+(klog⁡nklog⁡log⁡nk)ε) time query and O((nk)2log⁡nk+kε) space approximation algorithms for the independent and dependent case, respectively.

Robust superdirective beamforming for arbitrary sensor arrays

This paper presents a method of designing robust superdirective beamformers for arbitrary sensor arrays. First, the optimal weighting vector is transformed into an equivalent form based on the eigen–decomposition of the noise correlation matrix in an isotropic uniform noise field, and its entries will be indexed using mode orders instead of element numbers. Second, a parameter is weighted at the maximum–order entry in the modified weighting vector. The beampattern, directivity factor, and error sensitivity function can be expressed as functions of the parameter. Adjusting the parameter will achieve arbitrary–order superdirective beampatterns with different directivity factors or error sensitivity functions. Third, the closed–form expression of the parameter can be derived given a desired directivity factor or error sensitivity function. The final robust broadband superdirective beampatterns can then be readily synthesized. The proposed method, which is an extension of that previously proposed for circular sensor arrays, provides flexible schemes to designing robust broadband superdirective beamformers for arbitrary arrays in simulations and experiments.

Low-Resolution MMSE Equalization for Massive MU-MIMO Systems

Finite-alphabet equalization that represents a spatial equalization matrix with low-resolution coefficients is a promising technique to reduce the power consumption, processing delay, and circuit area of baseband processing in the context of all-digital massive multiuser multiple-input multiple-output uplink systems. However, to minimize the performance loss caused by a coarse-resolution spatial equalization matrix, its coefficients must be carefully designed in the minimum mean-square error sense to achieve the desired bit error rate (BER) performance, which unfortunately constitutes an NP-hard optimization problem. To tackle this problem, we first reformulate the finite-alphabet equalization design problem as an unconstrained optimization on a smooth Riemannian manifold. Then we propose an algorithm based on Riemannian manifold optimization (RMO) to solve the reformulated problem. Based on simulation results, the proposed 2-bit RMO-assisted equalizer outperforms its state-of-the-art counterparts while maintaining the same asymptotic complexity. In addition, the proposed 2-bit RMOassisted equalizer exhibits a loss of only 1.47 dB at a BER of 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-4</sup> compared to an unquantized linear minimum mean squared error equalizer.

Stability and comparison of complete blood count parameters between capillary and venous blood samples.

This study assessed the comparability of complete blood count (CBC) parameters between capillary and venous samples, and extended previous research by examining the influence of different storage temperatures on CBC stability up to 7 days after sample collection. Venous and capillary blood samples were collected from 93 adult patients. Hemoglobin (Hb), hematocrit (Ht), mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC), mean platelet volume (MPV), leukocytes, lymphocytes, basophils, eosinophils, erythrocytes, red cell distribution width (RDW), immature granulocytes (IG), immature reticulocyte fraction (IRF), monocytes, neutrophils, platelets, and reticulocytes were measured. Deming regression and mean relative differences between venous and capillary measurements were contrasted with desirable total allowable error (TEa). Stability was assessed in 20-27 venous blood samples stored at 4, 21-22, or 30°C, and analyzed at 0, 24, 48, 72, 96, 120, 144, and 168 h. Mean relative change with respect to baseline measurements was compared to the desirable TEa to determine acceptable stability. Deming regression demonstrated strong linear correlations and acceptable variation between venous and capillary measurements. Erythrocytes, Hb, Ht, MCH, MCV, RDW, reticulocytes, and platelets showed acceptable stability for at least 96 h at 4°C. Mean relative change exceeded desirable TEa after 24 h at 30°C for all parameters, except erythrocytes, Hb, leukocytes, and MCH. Clinical laboratory specialists and clinicians should be aware of potential differences between venous and capillary measurements, and the influence of storage conditions. Clinical validity of delayed CBC analysis depends on the clinical situation and required precision of the result.

Optimized performance analysis of nonrecursive low-density parity-check-coded Gaussian minimum shift keying in 5G-application

We present the low-density parity-check-coded nonrecursive Gaussian minimum shift keying-based hybrid modulation scheme for free-space optical (FSO) communications under optimal signal-to-noise ratio, limited power, and spectrum resources to support 5G and beyond applications with high-throughput efficiency. Our work investigates and approximates the error rate of the proposed scheme across a negative exponential stochastic FSO channel model with misalignment-induced fading. Using the Meijer-G function over the combined channel probability density function, we develop a unique closed-form formulation of outage probability. The potential benefits of utilizing the normalized beamwidth to achieve the desired error rate ( ≈ 10 − 12 ) is discussed. An improvement of 88.64% in the case of narrow beamwidth is perceived which collaborates with the proposed analytical expressions. The precision of our study is supported by numerical data from Monte Carlo simulation.

Non-linearity in lipase assays: A multicentric comparison on different analysers

ObjectivesNon-linearity in lipase assays and the ensuing gaps in results distribution have been described on Roche analysers, but have yet to be studied on other analysers. Design and methodsEighteen lithium-heparinized plasma pools of lipase activities decreasing from 1700 to <4 U/L were prepared for multicentric evaluation on several analysers. Non-linearity was modelled as the difference between the polynomial regression of lipase activities depending on relative dilutions over the primary measuring range, and the linear regression of the same variables above the manufacturer’s limit of linearity (MLL). Gaps in lipase distribution resulting from non-linearity were graphically evidenced through histograms. Upper limits of gaps were calculated, which are lipase activities where non-linearity biases no longer impact the diluted lipase results. ResultsMLLs and lipase (U/L) calculated at MLL (%biases versus MLL) were respectively: 1200 and 1124 (−6.3%) on the Architect C16000 (Abbott); 300 and 248 (−17.3%) on the Cobas c503 (Roche); 1500 and 1458 (−2.8%) on the Dimension Vista (Siemens); and 700 and 659 (−5.9%) on the Atellica CH930 (Siemens). Using Sentinel Lipase reagents on Abbott analysers, these measurements were respectively: 300 and 294 (−2.0%) on the Architect C16000, and 300 and 298 (−0.7%) on the Alinity. Setting Randox Lipase reagents on the Alinity, MLL and lipase at MLL were 953 and 776 (−18.6%), respectively. ConclusionsConsidering the desirable (±14.2 %) and optimal (±7.1 %) allowable total error for lipase (EFLM/EuBIVAS), biases at manufacturer’s limit of linearity were acceptable, except for Roche Cobas c503 method and Randox method on Abbott Alinity.

An augmented interface approach in fictitious domain methods

We introduce a new type of fictitious domain method to solve elliptic problems defined over curved complicated domains. In fictitious domain methods with a penalty approach, given domain Ω is embedded into a rectangular domain R and a penalty is applied over the whole fictitious part R ﹨ Ω . We apply the L 2 penalty over a small strip Ω δ around ∂Ω in R ﹨ Ω and present a priori estimates with the sharp convergence of the penalized problem's solution to the original problem's solution. We use the linear finite element method to solve the penalized problem and attain the desired error estimates. Numerical experiments ensure the theoretical estimations and forecast the optimal convergence irrespective of the shape and convexity of the domain.