Run Size Research Articles

Integrating moving average control procedures into the risk-based quality control plan in small-volume medical laboratories

IntroductionThe modern approach to quality control (QC) in medical laboratories implies the development of a risk-based control plan. This paper aims to develop a risk-based QC plan for a laboratory with a small daily testing volume and to integrate the already optimized moving average (MA) control procedures into this plan.Materials and methodsA multistage bracketed QC plan for ten clinical chemistry analytes was made using a Westgard QC frequency calculator. Previously, MA procedures were optimized by the bias detection simulation method.ResultsAspartate aminotransferase, HDL-cholesterol and potassium had patient-risk sigma metrics greater than 6, albumin and cholesterol greater than 5, creatinine, chlorides, calcium and total proteins between 4 and 5, and sodium less than 4. Based on the calculated run sizes and characteristics of optimized MA procedures, for 6 tests, it was possible to replace the monitoring QC procedure with an MA procedure. For the remaining 4 tests, it was necessary to keep the monitoring QC procedure and introduce MA control for added security.ConclusionThis study showed that even in a laboratory with a small volume of daily testing, it is possible to make a risk-based QC plan and integrate MA control procedures into that plan.

A new and flexible design construction for orthogonal arrays for modern applications

Orthogonal array, a classical and effective tool for collecting data, has been flourished with its applications in modern computer experiments and engineering statistics. Driven by the wide use of computer experiments with both qualitative and quantitative factors, multiple computer experiments, multifidelity computer experiments, cross-validation and stochastic optimization, orthogonal arrays with certain structures have been introduced. Sliced orthogonal arrays and nested orthogonal arrays are examples of such arrays. This article introduces a flexible, fresh construction method, which uses smaller arrays and a special structure. The method uncovers the hidden structure of many existing fixed-level orthogonal arrays of given run sizes, possibly with more columns. It also allows fixed-level orthogonal arrays of nearly strength three to be constructed, which are useful as there are not many construction methods for fixed-level orthogonal arrays of strength three, and also helpful for generating Latin hypercube designs with desirable low-dimensional projections. Theoretical properties of the proposed method are explored. As by-products, several theoretical results on orthogonal arrays are obtained.

Production sequence determination to minimize the required storage space for the multiple items production system

Purpose: The research studies the production system having multiple items being processed on the same production line. The objectives are to (1) investigate the influence of production sequence on the optimal value of production run size, (2) explore the effect of production sequence on the maximum inventory level, which can affect the storage space required, and (3) propose a method to determine the proper production sequence in order to minimize the required storage space.Design/methodology/approach: Finding that the optimal production sequence, which yields the lowest storage space required, is independent of the production run size, the research problem is divided into two independent subproblems. The first subproblem is to determine the optimal production run size to minimize the total variable cost. Here, the solution obtained from the classical multiple items EPQ model still holds. The second subproblem is to explore the proper production sequence in order to minimize the storage space required. The relationship between the production sequence and the value of maximum inventory level is determined and formulated. To explore the proper production sequence, a genetic algorithm is developed. For the performance evaluation, two experimental studies are conducted. The first experiment is to compare the solution obtained from the proposed method with the optimal solution yielded from the enumeration method on 360 small size problems. The second experiment is conducted on 180 large size problems. The result obtained from the proposed method is compared with the result yielded from the Largest Rho First (LRF) heuristic constructed by arranging the production of each item according to the ratio between the demand rate and production rate.Findings: It has been found that the optimal production sequence is independent of the production run size. Nonetheless, different production sequences yield different required storage spaces. With the proper production sequence, the manufacturer can reduce the total space required to keep its inventory. The proposed genetic algorithm can be applied to determine the proper production sequence in a reasonable amount of time. For the small size problem of 8 and 10 production items, the proposed genetic algorithm provides the solution with the maximum percentage deviation of 0.307 percent from the optimal solution. For the large size problem of 15 production items, the proposed genetic algorithm outperforms the LRF heuristic for all 180 problems. This result is more pronounced when the slack proportion is getting smaller.Research limitations/implications: According to the research model, no shortages are allowed. Therefore, the model is applicable for the production system having the summation value of the ratio between demand rate and production rate for all items not greater than one.Originality/value: Those traditional research involving the determination of optimal production run size and production sequence in the system having multiple items being produced on the same production line differs from each other in their production environments. However, most of them still have the objective function of minimizing the total system cost incurred. To the best of our literature searching, none of them discussed the influence of production sequence on the total inventory level, which directly affects the required storage space, one of the critical issues facing by many manufacturers. The originality of this work is to show that different production sequence yields different total storage space required and proposed the method to determine proper production sequence.

Using nonregular designs to generate space-filling designs

Strong orthogonal arrays are a class of space-filling designs suitable for computer experiments. Among this class of designs, those of strength two plus are most attractive as they aim at better space-filling properties in two-dimensions and hence have most economical run sizes. Most of previous work on strong orthogonal arrays of strength two plus focuses on the use of regular designs. In this paper, we develop a method of constructing space-filling designs using nonregular designs. Designs so constructed have very flexible run sizes compared to those constructed from regular designs. Apart from some theoretical results, computer searches are conducted to find space-filling designs using two-level nonregular designs of up to 40 runs and three-level nonregular designs of 27 and 54 runs.

Labor Markets and Sustainability: Short-Run Dynamics and Long-Run Equilibrium

Many of the world’s economies experienced rapid structural changes due to globalization and other forces over the past 50 years. During this period, developing countries were the recipients of massive foreign direct investment, and their industrialization was accompanied by urbanization, city gigantism, and related environmental issues, such as pollution. Over time, investments in the education of the urban poor allowed their move from the industrial sector to the service sector. This growth of the service sector came at the expense of the industrial sector, which implied structural changes in cities and massive cleaning efforts. The objective of this study is to model these transitions in a simple dynamic framework. The economic model indicates that in the short run, urban growth is negatively impacted by environmental degradation and agglomeration costs, while service sector growth is negatively impacted by environmental cleaning costs. In the long run, optimal city and service sizes are both decreasing functions of environmental degradation and agglomeration and cleaning costs. Thus, sustainability ultimately determines the optimal city size.

Order-of-Addition Orthogonal Arrays with High Strength

In order-of-addition experiments, the full order-of-addition designs are often unaffordable due to their large run sizes. The problem of finding efficient fractional OofA designs arises. The order-of-addition orthogonal arrays are a class of optimal fractional order-of-addition designs for the prevalent pair-wise ordering model, under a variety of widely used design criteria. In the literature, the studies on order-of-addition orthogonal arrays focused on strength 2 while the order-of-addition orthogonal arrays of higher strength have not been investigated yet. In this paper, we focus on order-of-addition orthogonal arrays of strength 3. First, the method of constructing order-of-addition orthogonal arrays of strength 3 is proposed. Second, a theoretical result that states that the order-of-addition orthogonal arrays of strength 3 have better balance properties than those of strength 2 is developed. Third, we provide thorough simulation studies which show that the constructed order-of-addition orthogonal arrays of strength 3 have desirable performance for estimating optimal orders of addition.

The impact of the COVID-19 pandemic on a recreational rainbow trout (Oncorhynchus mykiss) fishery.

There has been a recent flurry of publications describing the potential effects of the COVID-19 pandemic on both commercial and recreational fisheries. As of yet, studies have only provided insights from researchers or industry experts detailing perceived consequences, or from survey data indicating modifications in angler activity levels and behaviours. Using real recreational fisheries data from an ongoing radio telemetry study (2018–present), we explored changes in the relative exploitation rates of rainbow trout (Oncorhynchus mykiss; Walbaum 1792) in the Saugeen River, Ontario, a tributary to Lake Huron, before compared to during the pandemic. Restrictions on site access that affected the implementation of important management activities that usually support this popular fishery are also discussed. During the initial phase of complete public lock-downs imposed during spring 2020, angler exploitation rates decreased to half that reported prior to the pandemic. Fishway operations were temporarily suspended and hatchery efforts were interrupted. Once restrictions began to ease in fall 2020, there was an eight-fold increase in overall exploitation rate and a four and a half-fold increase in harvest rate compared to seasons prior to the pandemic. While the full impact of the ongoing pandemic on the Lake Huron fishery is not likely to be fully realized for several years, the potential effects on future return run sizes may need to be considered by fisheries managers monitoring trends in population escapement.

Uniform order-of-addition designs

The order-of-addition (OofA) experiment, whose response is affected by the addition order of components or materials, has received much attention recently. In this paper, based on suitable Hamming distance, we first establish the discrete discrepancy for any order-of-addition experiments from the viewpoint of uniformity and similarity. The lower bound of the discrete discrepancy under U-type designs is derived to serve as a benchmark of design optimality.In addition, we propose a new type of designs, called uniform order-of-addition (UOofA) designs, that achieve the lower bound of the discrete discrepancy. Some methods are provided to construct UOofA designs. The resulting designs have flexible run sizes and are suitable for sequential experiments. Furthermore, these designs under column permutations are efficient under the pairwise-order model.Such efficient UOofA designs, as well as their balance 性质 and projection 性质, are displayed in the S materials.

A study of the moving rate of positive results for use in a patient-based real-time quality control program on a procalcitonin point-of-care testing analyzer.

ObjectiveTo establish an applicable and highly sensitive patient‐based real‐time quality control (PBRTQC) program based on a data model constructed with patients’ results of a procalcitonin point‐of‐care testing (POCT) analyzer.MethodsPatients’ results were retrospectively collected within one year. The Excel software was used to establish quality control (QC) programs of the moving average (MA) and the moving rate of positive results (MR). A Monte Carlo simulation was used to introduce positive and negative biases between 0.01 and 1 ng/ml at random points of the testing data set. Different parameters were used to detect the biases, and the detection efficiency was expressed using the median number of patient samples affected until error detection (MNPed). After comparing the MNPeds of different programs, MA and MR programs with appropriate parameters were selected, and validation plots were generated using MNPeds and maximum number of the patient samples affected (MAX). β curves were generated using the power function of the programs, the performances were compared with that of the conventional QC program.ResultsNeither the conventional QC nor MA program was sensitive to small bias, While MR program can detect the minimum positive bias of 0.06 ng/ml and negative of 0.4 ng/ml at an average daily run size of 10 specimens, with FRs < 1.0%, βs < 1%.ConclusionThe MR program, which is more sensitive to small biases than conventional QC and MA programs, with low FR and β. As such, it can be used as a PBRTQC program with high performance.

Phenological Variation in Spring Migration Timing of Adult Alewife in Coastal Massachusetts

AbstractThe timing of biological events in plants and animals, such as migration and reproduction, is shifting due to climate change. Anadromous fishes are particularly susceptible to these shifts as they are subject to strong seasonal cycles when transitioning between marine and freshwater habitats to spawn. We used linear models to determine the extent of phenological shifts in adult AlewifeAlosa pseudoharengusas they migrated from ocean to freshwater environments during spring to spawn at 12 sites along the northeastern USA. We also evaluated broadscale oceanic and atmospheric drivers that trigger their movements from offshore to inland habitats, including sea surface temperature, North Atlantic Oscillation index, and Gulf Stream index. Run timing metrics of initiation, median (an indicator of peak run timing), end, and duration were found to vary among sites. Although most sites showed negligible shifts towards earlier timing, statistically significant changes were detected in three systems. Overall, winter sea surface temperature, spring and fall transition dates, and annual run size were the strongest predictors of run initiation and median dates, while a combination of within‐season and seasonal‐lag effects influenced run end and duration timing. Disparate results observed across the 12 spawning runs suggest that regional environmental processes were not consistent drivers of phenology and local environmental and ecological conditions may be more important. Additional years of data to extend time series and monitoring of Alewife timing and movements in nearshore habitats may provide important information about staging behaviors just before adults transition between ocean and freshwater habitats.

High egg retention in Chinook Salmon Oncorhynchus tshawytscha carcasses sampled downstream of a migratory barrier.

Barriers in rivers have the potential to severely decrease functional connectivity between habitats. Failure to pass barriers and reach natal spawning habitat may compromise individual reproductive success, particularly for semelparous, philopatric species that rely on free-flowing rivers to reach natal habitat during their once-in-a-lifetime spawning migrations. To investigate the consequences of in-river barriers on fish spawning success, we quantified egg retention and spawning effort (caudal fin wear) in female Chinook Salmon Oncorhynchus tshawytscha carcasses collected downstream of the Whitehorse Hydro Plant on the upper Yukon River and at a nearby free-flowing tributary (Teslin River) from 2018 to 2020 (~2900 km migrations). Previous studies have demonstrated that a large proportion of fish attempting to reach spawning locations upstream of the hydro plant fail to pass the associated fishway. We estimated nearly all female salmon failing to pass the hydro plant attempted spawning in non-natal habitat downstream, but that these females retained ~34% of their total fecundity compared to ~6% in females from the free-flowing river. Females downstream of the hydro plant also had lower wear on their caudal fin, a characteristic that was correlated with increased egg deposition. Egg retention did not vary across years with different run sizes, and we propose that egg retention downstream of the hydro plant was not driven by density-dependent mechanisms. Findings from this work indicate that female Chinook Salmon can still deposit eggs following failed fish passage and failure to reach natal spawning sites, though egg retention rates are considerably higher and uncertainties remain about reproductive success. We encourage researchers to incorporate carcass surveys into fish passage evaluations for semelparous species to fully account for consequences of failed passage.

Lower bounds of the average mixture discrepancy for row augmented designs with mixed four- and five-level

Follow-up experimental designs are widely used in various scientific investigations and industrial applications to discuss the relationship between inputs and outputs at various stages. Due to the limitation of run size, the desired experimental purpose may not be achieved through one stage of the experiment, so additional runs should be considered in the follow-up stage. By taking all possible level permutation of the factors into consideration, the uniformity of row augmented designs with mixed four- and five-level is discussed under the average mixture discrepancy, and new lower bounds of average mixture discrepancy for row augmented designs with mixed four- and five-level are obtained in this paper. Accordingly, the algorithm for the construction of uniform row augmented designs with mixed four- and five-level is proposed. Numerical examples show that the constructed uniform row augmented designs with mixed four- and five-level are highly efficient and can be used in practice.

A New Practical Tool for Assessing the Analytical Performance and Designing Risk-Based Statistical Quality Control Procedures in Laboratories

We developed a new practical tool and applied it to assess the performance of 14 biochemical assays and designed risk-based statistical quality control (SQC) procedures. Two graphs were combined to develop the new tool. Data points of assays were plotted on the tool to determine their sigma performance and the risk-based SQC procedures. The quality goal index (QGI) was also calculated for quality improvement. Among 14 assays, total bilirubin, direct bilirubin, alanine aminotransferase, creatine kinase, and gammaglutamyl transferase achieved 6-sigma performance, the recommended SQC procedure was 13s rule (n = 2) with a run size of 1,000 patient samples. Triglycerides was 5-sigma quality and could be controlled with 13s/22s/R4s multi-rule procedure (n = 2) with a run size of 450. Uric acid, creatinine, total cholesterol, and aspartate aminotransferase obtained 4-sigma quality and could be controlled using 13s/22s/R4s/41s multi-rule procedure (n = 4) with run size of 200. The performance for urea, alkaline phosphatase, amylase, and lactate dehydrogenase was 3-sigma and 13s/22s/R4s/41s/6X multi-rule procedure (n = 6) with run size of 45 was recommended. The QGI for assays with sigma quality below 6.0 were all less than 0.8. The developed tool can be used to simplify laboratory practices in assessing analytical performance and designing SQC procedures.

Moving Targets: Assessing Fraser River Pink Salmon Run Size during a Period of Change and Uncertainty

Moving Targets: Assessing Fraser River Pink Salmon Run Size during a Period of Change and Uncertainty

A systematic construction of compromise designs under baseline parameterization

Karunanayaka and Tang (2017) introduced a class of compromise designs for estimating main effects under the baseline parameterization. Their approach is to add some runs to the basic one-factor-at-a-time design, and its implementation requires computer search except for the case of adding one run where a theoretical result is available. The reliance on computer search only allowed them to find the limited results from adding up to four runs to the basic one-factor-at-a-time design. In this paper, we provide a systematic construction of compromise designs, without computer search and without restriction on the run size and the number of factors. Closed-form expressions of the bias and efficiency criteria are obtained for the new designs. Both theoretical and empirical studies show that our designs outperform those of Karunanayaka and Tang (2017) saving small-sized problems.

EVALUATION OF TRAWL SAMPLING FOR THREATENED EULACHON (THALEICHTHYS PACIFICUS) IN THE LOWER COLUMBIA RIVER DURING JANUARY–MARCH 2013

The population of Eulachon (Thaleicthys pacificus) spawning in the Columbia River and its tributaries is thought to be the largest in the world. Eulachon historically supported indigenous, commercial, and sport harvests, but were listed as threatened under the US Endangered Species Act in 2010. This study tested the use of a small research trawl and 38-kHz echosounder to provide new, fishery-independent data for Columbia River Eulachon. During January–March 2013, we used a semi-balloon shrimp trawl and an uncalibrated 38-kHz downward-looking echosounder to sample estuarine and tidal freshwater habitats. Eulachon were present in the estuary on every sampling day. Direct mortality in the trawl was very low (<0.1%). We observed sex ratios closer to 1:1 than previously reported for the Columbia River, and trawl-caught Eulachon were longer and heavier than Eulachon caught with the same gear in the same season during 1980–1981. The largest catches occurred after 11 February 2013, when midwater estuary temperature warmed and remained above 5.5°C. Tributary spawning began in mid-March after estuary warming and continued for at least 2 wk. Observations suggested that Eulachon occurred in low densities and remained dispersed in deeper waters of the estuary for at least 2 mo before upstream migration. The estuary may therefore serve as an important staging area prior to upstream migration and subsequent spawning. Catch data and qualitative acoustic images suggest that a combination of trawl and acoustic surveys could provide direct estimates of adult biomass. If Eulachon populations are to recover from the threat of extinction, additional data will be needed to resolve uncertainties regarding spawner condition, adult spawning-stock biomass, and variation in run timing relative to river and estuary conditions. We recommend implementation of systematic surveys for adult Eulachon in the Columbia River to further understand how environmental factors drive variation in run size and run timing for this species.

Generating optimal order-of-addition designs with flexible run sizes

A series of optimal designs with flexible run sizes is proposed in this paper for designing order-of-addition experiments. Because the full design can be partitioned into several isotopic Latin squares, a fractional design can be obtained by juxtaposing some selected Latin squares according to a particular optimality criterion. A computer-assisted search procedure is first implemented to generate optimal designs with small to moderate run sizes. Based on the computer-generated designs, a recursive method is then used to construct optimal designs with large run sizes. In addition, two practical techniques are introduced to obtain new optimal or near-optimal designs via existing optimal designs. The proposed designs are compared with competing designs generated by conventional software. The results show that the proposed designs are often more efficient for estimating the unknown parameters. A catalogue of optimal designs and near-optimal designs is provided as a reference for future work.

Application of a six sigma model to evaluate the analytical performance of urinary biochemical analytes and design a risk‐based statistical quality control strategy for these assays: A multicenter study

BackgroundThe six sigma model has been widely used in clinical laboratory quality management. In this study, we first applied the six sigma model to (a) evaluate the analytical performance of urinary biochemical analytes across five laboratories, (b) design risk‐based statistical quality control (SQC) strategies, and (c) formulate improvement measures for each of the analytes when needed.MethodsInternal quality control (IQC) and external quality assessment (EQA) data for urinary biochemical analytes were collected from five laboratories, and the sigma value of each analyte was calculated based on coefficients of variation, bias, and total allowable error (TEa). Normalized sigma method decision charts for these urinary biochemical analytes were then generated. Risk‐based SQC strategies and improvement measures were formulated for each laboratory according to the flowchart of Westgard sigma rules, including run sizes and the quality goal index (QGI).ResultsSigma values of urinary biochemical analytes were significantly different at different quality control levels. Although identical detection platforms with matching reagents were used, differences in these analytes were also observed between laboratories. Risk‐based SQC strategies for urinary biochemical analytes were formulated based on the flowchart of Westgard sigma rules, including run size and analytical performance. Appropriate improvement measures were implemented for urinary biochemical analytes with analytical performance lower than six sigma according to the QGI calculation.ConclusionsIn multilocation laboratory systems, a six sigma model is an excellent quality management tool and can quantitatively evaluate analytical performance and guide risk‐based SQC strategy development and improvement measure implementation.

Utilizing individual clear effects for intelligent factor allocations and design selections

Extensive studies have been conducted on how to select efficient designs with respect to a criterion. Most design criteria aim to capture the overall efficiency of the design across all columns. When prior information indicated that a small number of factors and their two-factor interactions (2fi’s) are likely to be more significant than other effects, commonly used minimum aberration designs may no longer be the best choice. Motivated by a real-life experiment, we propose a new class of regular fractional factorial designs that focus on estimating a subset of columns and their corresponding 2fi’s clear of other important effects. After introducing the concept of individual clear effects (iCE) to describe clear 2fi’s involving a specific factor, we define the clear effect pattern criterion to characterize the distribution of iCE’s over all columns. We then obtain a new class of designs that sequentially maximize the clear effect pattern. These newly constructed designs are often different from existing optimal designs. We develop a series of theoretical results that can be particularly useful for constructing designs with large run sizes, for which algorithmic construction becomes computationally challenging. We also provide some practical guidelines on how to choose appropriate designs with respect to different run size, the number of factors, and the number of 2fi’s that need to be clear.

Sliced symmetrical Latin hypercube designs

A main goal in computer experiments is to estimate the expected model output. This article proposes a new type of space-filling design, called a sliced symmetrical Latin hypercube, intended for solving this integration problem when multiple computer models are run in batches. Such a design is a special Latin hypercube that can be partitioned into slices of smaller Latin hypercubes, with some slices being also symmetrical designs. Compared with an ordinary sliced Latin Hypercube, the proposed design has the following advantages: (i) the group symmetry of models can be detected by the first slice of the design, which leads to a decline in the experimental cost, (ii) the design structure inherits efficient variance reduction ability for the estimation from the sliced Latin Hypercubes, and (iii) each slice of the design is flexible in run size. Finally, numerical illustrations are provided to corroborate the theoretical results.