Potential Sources Of Error Research Articles

Method of Assessing the Logistics Process as Regards Information Flow Unreliability on the Example of a Container Terminal

The reliability of logistics processes is most often considered in the context of the correct flow of materials. The information that accompanies the logistic flow is usually not considered a potential source of errors or disruptions to the correct operation of the logistic chain. The article presents literature studies in this field and presents a model for evaluating the logistics process, taking into account the quality of information. An example of process evaluation based on a container terminal was presented.

Broader Estimates of Gastrocnemius Activity Generated a More Representative Cocontraction Index: A Study in Pediatric Population.

The electromyography (EMG) cocontraction index (CCI) given by the antagonistic/agonistic Root Mean Square (RMS) amplitude ratio of the same muscle is a qualified biomarker used for spastic cocontraction quantification and management in cerebral palsy children. However, this normative EMG ratio is likely subject to a potential source of errors with biased estimates when measuring the gastrocnemius plantar flexors activity. Due to the uneven distribution of electrical activity within the muscle volume, cocontraction levels can be misestimated, if EMGs are obtained from the sole traditional bipolar sensor location recommended by SENIAM. This preliminary study, on 10 healthy children (mean age 10 yr), investigated whether surface EMG detected proximally and distally via two pairs of bipolar electrodes, within the medial gastrocnemius (MG), provides a significant difference in CCI estimates during non-dynamic (isometric dorsiflexion) and dynamic (swing phases of gait) conditions. Gait cycles were extracted from Inertial Measurement Unit sensors. Medial gastrocnemius activity was greater distally than proximally during plantar flexion when it acts as an agonist (~24±18%) and it was greater proximally during dorsiflexion (~23±9%) when it is acting as an antagonist. As a direct consequence, CCI estimates from the conventional sensor location were significantly different (~36%) from the CCIs computed by considering broader MG regions. This difference arose in all subjects during isometric efforts and in two of 10 healthy children during the swing phase of gait who presented cocontraction patterns (p<0.05). EMG bipolar sampling encompassing proximal and distal gastrocnemius muscle regions may reduce bias in CCI computation and provide a more representative and accurate cocontraction index that is especially important for comparisons to the diseased state.

Sample Preparation Biases in Automated Quantitative Mineralogical Analysis of Mine Wastes

Abstract Mineralogical information is becoming increasingly important for the interpretation and prediction of the long-term leaching behavior of mine waste rock and tailings, yet the collection of quantitative mineralogical data for these materials is complicated by biases introduced during sample preparation. Here, we present experiments with synthetic reference materials, soluble mineral (gypsum) and pulverized weathered waste rock samples to investigate potential artifacts that can be introduced during the preparation of granular sample specimen for quantitative mineralogical analysis. Our results show that, during epoxy-molding, particle segregation due to size is more important than that due to density, both of which can be effectively circumvented by cutting molds perpendicular to the orientation of settling. We also determine that sacrificing sample polish to avoid phase alteration need not impede phase attribution as long as surface roughness and slope are calibrated with sample-internal contrast references. Finally, bootstrapping analysis shows that variability in geometric and mineralogical particle parameters due to unresolved sample heterogeneity is small compared with other biases, even at particle numbers &amp;lt;25,000 at sizes &amp;gt;150 µm. Our results demonstrate the importance of quantifying potential sources of error during sample preparation in quantitative mineralogical studies on mine wastes.

A metabarcoding framework for wild bee assessment in Luxembourg

Wild bees are crucial organisms for terrestrial environments. Their ongoing decline could cause irreparable damage to ecosystem services vital to plant reproduction and human food production. The importance of taking swift action to prevent further declines is widely acknowledged, but the current deficit of reliable taxonomic information complicates the development of efficient conservation strategies targeting wild bees. DNA metabarcoding can help to improve this situation by providing rapid and standardized mass identification. This technique allows the analysis of large numbers of specimens without the need for specialized taxonomic knowledge by matching high-throughput sequencing reads against public DNA barcode reference libraries. However, the validation of this approach for wild bees requires the evaluation of potential error sources on a regional scale. Here we analyzed the effects of three potential error sources on a metabarcoding pipeline customized for the wild bee fauna of Luxembourg. In an in silico study, we checked the completeness of the BOLD reference library for 349 species found in the country, the correspondence between molecular and morphological species delimitation for these taxa, and the amplification efficiency of three commonly used metabarcoding primer pairs (mlCOlintF/HCO2198, LepF1/MLepF1-Rev and BF2/BR2). The detection power of the pipeline was evaluated based on the species recovery rates from mock communities of known composition under variable DNA concentration treatments. The reference barcode library evaluation results show that 97% of the species have at least a single barcode in BOLD Systems (minimal length 196 bp) and that 85% of species have ≥ 5 barcodes in the public domain. The mlCOlintF/HCO2198 target fragment presented the highest coverage (77.94% of the species with full barcode sequences), followed by the target fragments of LepF1/MLepF1-Rev (77.65%) and BF2/BR2 (68.48%). Only 60% of the morphospecies presented a complete coverage of the prominent Folmer region (658 bp). The in silico amplification efficiency analysis shows that the BF2/BR2 primer pair has the best-predicted amplification performance, but none of the primer combinations evaluated can be expected to efficiently amplify all local wild bee genera. Finally, all species detection rates in the mock communities, except for the sample with the most discrepant DNA concentrations, were above 97%, with no significant differences found among treatments. These results indicate that the detection capacity of the pipeline is robust enough to be used for the reliable assessment of local wild bee biodiversity, even if species from various size categories are pooled together. Primer bias has a major effect on species detection, which can be acknowledged with a preliminary assessment of primer-template mismatch and sophisticated methodological designs (e.g. mock community controls, replicates). Overall, the metabarcoding pipeline here described provides a suitable tool for quick and reliable taxonomic identification of the regional wild bee fauna to aid conservation initiatives in Luxembourg – and beyond.

Magnetic pair distribution function data using polarized neutrons and ad hoc corrections

We report the first example of magnetic pair distribution function (mPDF) data obtained through the use of neutron polarization analysis. Using the antiferromagnetic semiconductor MnTe as a test case, we present high-quality mPDF data collected on the HYSPEC instrument at the Spallation Neutron Source using longitudinal polarization analysis to isolate the magnetic scattering cross section. Clean mPDF patterns are obtained for MnTe in both the magnetically ordered state and the correlated paramagnet state, where only short-range magnetic order is present. We also demonstrate significant improvement in the quality of high-resolution mPDF data through the application of ad hoc corrections that require only minimal human input, minimizing potential sources of error in the data processing procedure. We briefly discuss the current limitations and future outlook of mPDF analysis using polarized neutrons. Overall, this work provides a useful benchmark for mPDF analysis using polarized neutrons and provides an encouraging picture of the potential for routine collection of high-quality mPDF data.

Models Used to Predict Chemical Bioaccumulation in Fish from in Vitro Biotransformation Rates Require Accurate Estimates of Blood-Water Partitioning and Chemical Volume of Distribution.

Methods for extrapolating measured in vitro intrinsic clearance to a whole-body biotransformation rate constant (kB ) have been developed to support modeled bioaccumulation assessments for fish. The inclusion of extrapolated kB values into existing bioaccumulation models improves the prediction of chemical bioconcentration factors (BCFs), but there remains a tendency for these methods to overestimate BCFs relative to measured values. Therefore, a need exists to evaluate the extrapolation procedure to assess potential sources of error in predicted kB values. We examined how three different approaches (empirically based, composition based, and polyparameter linear free energy relationships [ppLFERs]) used to predict chemical partitioning in vitro (liver S9 system; KS9W ), in blood (KBW ), and in whole fish tissues (KFW ) impact the prediction of a chemical's hepatic clearance binding term (fU ) and apparent volume of distribution (VD ), both of which factor into the calculation of kB and the BCF. Each approach yielded different KS9W , KBW , and KFW values, but resulted in fU values that were of similar magnitude and remained relatively constant at log octanol-water partition ratios (KOW ) greater than 4. This is because KBW and KS9W values predicted by any given approach exhibit a similar dependence on log KOW (i.e., regression slope), which results in a cancelation of "errors" when fU is calculated. In contrast, differences in KBW values predicted by the three approaches translate to differences in VD , and by extension kB and the BCF, which become most apparent at log KOW greater than 6. There is a need to collect KBW and VD data for hydrophobic chemicals in fish that can be used to evaluate and improve existing partitioning prediction approaches in extrapolation models for fish. Environ Toxicol Chem 2023;42:33-45. © 2022 SETAC.

Electrical Shorting of Thermocouples in Flexible Thermal Protection System Materials

The flexible thermal protection system (FTPS) on NASA’s Low-Earth Orbit Flight Test of an Inflatable Decelerator (LOFTID) vehicle will be instrumented with thermocouples to measure the in-depth thermal response during entry into Earth’s atmosphere. Accurate flight temperature measurements are critical for verifying vehicle performance during the flight test and reducing uncertainties in the thermal models, but the deployable nature of inflatable decelerator technology presents challenges. The thermocouples need to be compactable, cannot damage the FTPS or the inflatable structure, and need to be able to withstand high temperatures and large thermal gradients. The present paper details the developmental testing that was performed using a tube furnace to examine the potential error sources associated with instrumenting NASA’s FTPS with thermocouples insulated with either glass braid or ceramic braid. Large measurement errors occurred with both thermocouple insulation materials due to conductive deposits on the insulation electrically shorting the thermocouple leads. Two mechanisms were identified that contribute to this phenomenon: 1) the organic binder on the thermocouple insulation carbonizes in a high-temperature, low-oxygen environment and 2) decomposition products from the FTPS are able to permeate the braided insulation. The effect of heat cleaning the thermocouples to eliminate the first mechanism is presented, and the possibility of using a mica wrap as an impermeable barrier to mitigate the second mechanism is explored. Finally, the applicability of the ground-based tube furnace test results to the flight environment is discussed.

Position of Correct Option and Distractors Impacts Responses to Multiple-Choice Items: Evidence From a National Test.

Even though the impact of the position of response options on answers to multiple-choice items has been investigated for decades, it remains debated. Research on this topic is inconclusive, perhaps because too few studies have obtained experimental data from large-sized samples in a real-world context and have manipulated the position of both correct response and distractors. Since multiple-choice tests' outcomes can be strikingly consequential and option position effects constitute a potential source of measurement error, these effects should be clarified. In this study, two experiments in which the position of correct response and distractors was carefully manipulated were performed within a Chilean national high-stakes standardized test, responded by 195,715 examinees. Results show small but clear and systematic effects of options position on examinees' responses in both experiments. They consistently indicate that a five-option item is slightly easier when the correct response is in A rather than E and when the most attractive distractor is after and far away from the correct response. They clarify and extend previous findings, showing that the appeal of all options is influenced by position. The existence and nature of a potential interference phenomenon between the options' processing are discussed, and implications for test development are considered.

Genotyping‐by‐sequencing for biogeography

AbstractAimGenotyping‐by‐sequencing (GBS) and similar reduced‐representation sequencing methods, such as restriction site‐associated DNA sequencing (RADseq), have been revolutionary for genetic analyses in biogeography. However, navigating the many different methodological and analytical approaches and numerous sources of potential error can be overwhelming. We provide an overview of key considerations for biogeographical research using GBS, from sample design through data filtering to the sharing of data, which should particularly assist new users.TaxonAll taxa.LocationWorldwide.MethodsWe review recent advances for GBS and compare differences among GBS methods and analytical approaches. We highlight the concerns most relevant for biogeographical research, and emphasise practical limitations for studies on non‐model organisms.ResultsGBS methods vary substantially and recent literature demonstrates the need for careful study design and data filtering relevant to the study organism and hypothesis under investigation. Biogeographical research using non‐model organisms or long‐term sampling are likely to face some practical limitations compared to ideal GBS study designs. The methodological information recorded in published manuscripts often varies. We outline a general framework for planning and undertaking biogeographical research using GBS.Main conclusionsGBS and similar approaches have grown rapidly in popularity for biogeographical research. Evaluating, recording and justifying decisions throughout a GBS workflow—across sampling, library preparation and sequencing, identifying and filtering samples and loci, biogeographical analyses, and sharing data—is crucial for improving scientific reproducibility and compatibility among GBS datasets. This review outlines ways to improve and simplify GBS research, thereby enhancing our capacity to use genomic data to address broad‐scale biogeographical questions.

Determination of five positive control drugs in hERG external solution (buffer) by LC-MS/MS to support in vitro hERG assay as recommended by ICH S7B

ICH S7B recommends screening for hERG channel block using patch clamp recordings to assess a drug's proarrhythmic risk. Block of the hERG channel has been associated with clinical QTC prolongation as well as the rare, but potentially fatal ventricular tachyarrhythmia Torsade de Pointes (TdP). During recording, drug concentrations perfused to the cells can deviate from nominal concentrations due to molecule-specific properties (such as non-specific binding), thereby introducing error when assessing drug potency. To account for this potential source of error, both the original ICH S7B and the newly released ICH E14/S7B Q&As guidelines call for verifying drug solutions' concentrations. Dofetilide, cisapride, terfenadine, sotalol and E-4031 are hERG blockers commonly used as positive controls to illustrate hERG assay sensitivity. The first four compounds are also clinical drugs associated with high TdP risk; therefore, their safety margins may be useful comparators to better understand an investigational product's TdP risk. Having analytical methods to quantify these five compounds in the hERG external solution that will be used for patch clamp recordings is important from a regulatory science research perspective. However, a literature search revealed no analytical methods or stability information for these molecules in the high salt, serum-free matrix that constitutes the hERG external solution. This study was conducted to develop and validate LC-MS/MS methods to quantify these 5 molecules in hERG external solution. The bioanalytical methods for these positive controls were validated as per the FDA's bioanalytical method validation guidance along with various stabilities.

Using Stochastically Perturbed Parameterizations to Represent Model Uncertainty. Part I: Implementation and Parameter Sensitivity

Abstract Accurately representing model-based sources of uncertainty is essential for the development of reliable ensemble prediction systems for NWP applications. Uncertainties in discretizations, algorithmic approximations, and diabatic and unresolved processes combine to influence forecast skill in a flow-dependent way. An emerging approach designed to provide a process-level representation of these potential error sources, stochastically perturbed parameterizations (SPP), is introduced into the Canadian operational Global Ensemble Prediction System. This implementation extends the SPP technique beyond its typical application to free parameters in the physics suite by sampling uncertainty both within the dynamical core and at the formulation level using “error models” when multiple physical closures are available. Because SPP perturbs components within the model, internal consistency is ensured and conservation properties are not affected. The full SPP scheme is shown to increase ensemble spread to keep pace with error growth on a global scale. The sensitivity of the ensemble to each independently perturbed “element” is then assessed, with those responsible for the bulk of the response analyzed in more detail. Perturbations to surface exchange coefficients and the turbulent mixing length have a leading impact on near-surface statistics. Aloft, a tropically focused error model representing uncertainty in the advection scheme is found to initiate growing perturbations on the subtropical jet that lead to forecast improvements at higher latitudes. The results of Part I suggest that SPP has the potential to serve as a reliable representation of model uncertainty for ensemble NWP applications. Significance Statement Ensemble systems account for the negative impact that uncertainties in prediction models have on forecasts. Here, uncertain model parameters and algorithms are subjected to perturbations representing impact on forecast errors. By initiating error growth within the model calculations, the equally skillful members of the ensemble remain physically realistic and self-consistent, which is not guaranteed by other depictions of model error. This “stochastically perturbed parameterization” technique (SPP) comprises many small error sources, each analyzed in isolation. Each source is related to a limited set of processes, making it possible to determine how the individual perturbations affect the forecast. We conclude that SPP in the Canadian Global Ensemble Forecasting System produces realistic estimates of the impact of model uncertainties on forecast skill.

Daily runoff and its potential error sources reconstructed using individual satellite hydrological variables at the basin upstream

Basin-scale hydropower operation and water resource allocation rely on in situ river discharge measured at a river mouth, which is referred to as runoff. Due to labor intensiveness and tight financial constraints, satellite hydrological variables have been advocated for reconstructing monthly runoff via regressing with nearby measured monthly river discharge over the past two decades. Nevertheless, daily runoff reconstruction by regressing with upstream satellite hydrological variables on a daily scale has yet to be examined. A data standardization approach is proposed for daily runoff reconstructed using satellite hydrological data upstream of the Mekong Basin. It was found that the accuracy of reconstructed and predicted daily runoff against in situ runoff was substantially increased, in particular, the troughs (peaks) during dry (wet) seasons, respectively, when compared to that of the direct linear regression. The backwater impact on the runoff accuracy is negligible after standardization, implying the possibility of choosing the basin exit at the entrance of the river delta. Results generated from the data standardization via neural network–based models do not improve consistently or even a bit worse than that of the linear regression. The best forecasted runoff, yielding the lowest relative error of 8.6%, was obtained from the upstream standardized water storage index. Detrended cross-correlation analysis indicated that the reconstructed and forecasted runoff from the data standardization yielded a cross-correlation larger than 0.8 against in situ data within most window sizes. Further improvement lies in the methodology for mitigating the influence due to climate variability and extreme events.

Toward high-accuracy and high-efficiency battery electrothermal modeling: A general approach to tackling modeling errors

An accurate control-oriented electrothermal model is a prerequisite for efficient thermal management of battery-powered applications. Despite the great efforts made to pursue high-accuracy modeling of the heat generation and transfer processes inside lithium-ion batteries for control purposes, little work has shed light on the error sources in such electrothermal modeling for obtaining an optimal model. In this article, we propose a practical and general framework for investigating the potential error sources in computationally efficient electrothermal modeling of large-format lithium-ion batteries. The results demonstrate that the high-accuracy modeling of the thermal interplay between two tabs and the cell body and the optimization of the temperature sensor placements should be given high priority. Further, the overpotential-based method is preferred to calculate the local generation rates of the battery body for accuracy and generalizability. This study provides important insights into accurate and computationally efficient electrothermal modeling for large-format energy storage batteries.

The effect of the immunoassay curve fitting routine on bias in troponin.

Unlike many dose-response curves used in clinical chemistry, the immunoassay curve used to quantitate measurands is often sigmoidal rather than linear. Consequently, a more complex curve fitting model is required. Various models are available, but they can introduce bias, and there can be little awareness of why this error can be introduced. These curve-fitting models include those based on the law of mass-action, empirical models such as splines or linearization models such as the log/logit function. All these models involve assumptions, which can introduce bias as the dose-response curve is 'forced' to fit or minimize the distance between the standard concentration points to the theoretical curve. The most common curve fitting model is the four or five parameter model, which uses four or five parameters to fit a sigmoidal curve to a set of standard points. Measurement of cardiac troponin is an important element in establishing a diagnosis of acute myocardial infarction. We use troponin, a cardiac biomarker, to demonstrate the potential effect of the bias that the curve fit could introduce. Troponin is used for both rule-in and rule-out decisions at different concentrations and at either end of the dose-response curve. The curve fitting process can cause lot-to-lot reagent (and calibrator) variation in immunoassay. However, laboratory staff need to be aware of this potential source of error and why it occurs. Understanding how the error occurs leads to a greater awareness of the importance of validating new reagent/calibrator assessment using patient samples with concentrations at crucial decision points.

The impact of improved spatial and temporal resolution of reanalysis data on Lagrangian studies of the tropical tropopause layer

Abstract. Lagrangian trajectories are frequently used to trace air parcels from the troposphere to the stratosphere through the tropical tropopause layer (TTL), and the coldest temperatures of these trajectories have been used to reconstruct water vapor variability in the lower stratosphere, where water vapor's radiative impact on Earth's surface is strongest. As such, the ability of these trajectories to accurately capture temperatures encountered by parcels in the TTL is crucial to water vapor reconstructions and calculations of water vapor's radiative forcing. A potential source of error for trajectory calculations is the resolution of the input data. Here, we explore how improving the spatial and temporal resolution of model input data impacts the temperatures measured by Lagrangian trajectories that cross the TTL during boreal winter using ERA5 reanalysis data. We do so by comparing the temperature distribution of trajectories computed with data downsampled in either space or time to those computed with ERA5's maximum resolution. We find that improvements in temporal resolution from 6 to 3 and 1 h lower the cold point temperature distribution, with the mean cold point temperature decreasing from 185.9 to 185.0 and 184.5 K for reverse trajectories initialized at the end of February for each year from 2010 to 2019, while improvements to vertical resolution from that of MERRA2 data (the GEOS5 model grid) to full ERA5 resolution also lower the distribution but are of secondary importance, and improvements in horizontal resolution from 1∘ × 1∘ to 0.5∘ × 0.5∘ or 0.25∘ × 0.25∘ have negligible impacts to trajectory cold points. We suggest that this is caused by excess vertical dispersion near the tropopause when temporal resolution is degraded, which allows trajectories to cross the TTL without passing through the coldest regions, and by undersampling of the four-dimensional temperature field when either temporal or vertical resolution is reduced.

Classification of body postures using smart workwear

BackgroundDespite advancing automation, employees in many industrial and service occupations still have to perform physically intensive work that may have negative effects on the health of the musculoskeletal system. For targeted preventive measures, precise knowledge of the work postures and movements performed is necessary.MethodsPrototype smart work clothes equipped with 15 inertial sensors were used to record reference body postures of 20 subjects. These reference postures were used to create a software-based posture classifier according to the Ovako Working Posture Analysing System (OWAS) by means of an evolutionary training algorithm.ResultsA total of 111,275 posture shots were recorded and used for training the classifier. The results show that smart workwear, with the help of evolutionary trained software classifiers, is in principle capable of detecting harmful postures of its wearer. The detection rate of the evolutionary trained classifier (bar{a}_{ccr} = 0.35 for the postures of the back, bar{a}_{ccr} = 0.64 for the arms, and bar{a}_{ccr} = 0.25 for the legs) outperforms that of a TensorFlow trained classifying neural network.ConclusionsIn principle, smart workwear – as prototypically shown in this paper – can be a helpful tool for assessing an individual’s risk for work-related musculoskeletal disorders. Numerous potential sources of error have been identified that can affect the detection accuracy of software classifiers required for this purpose.

How to Read and Determine the Specific Surface Area of Inorganic Materials using the Brunauer-Emmett-Teller (BET) Method

The specific surface area of inorganic materials is a crucial parameter that influences their performance in various applications. The Brunauer-Emmett-Teller (BET) method is widely used for accurately determining the surface area of porous materials. This study presents a comprehensive guide to determining the specific surface area of inorganic materials using the BET method. The paper outlines the theoretical background of the BET method, the experimental procedures involved, and the data analysis techniques. Additionally, we discuss the limitations and potential sources of errors in the BET method. The proposed guide aims to provide researchers and practitioners with a systematic approach to accurately measure the specific surface area of inorganic materials, enabling informed decision-making and enhancing material design and optimization processes.

Automated enumeration of Eimeria oocysts in feces for rapid coccidiosis monitoring

Coccidiosis represents a major driver in the economic performance of poultry operations, as coccidia control is expensive, and infections can result in increased feed conversion ratios, uneven growth rates, increased co-morbidities with pathogens such as Salmonella, and mortality within flocks. Shifts in broiler production to antibiotic-free strategies, increased attention on pre-harvest food safety, and growing incidence of anti-coccidial drug resistance has created a need for increased understanding of interventional efficacy and methods of coccidia control. Conventional methods to quantify coccidia oocysts in fecal samples involve manual microscopy processes that are time and labor intensive and subject to operator error, limiting their use as a diagnostic and monitoring tool in animal parasite control. To address the need for a high-throughput, robust, and reliable method to enumerate coccidia oocysts from poultry fecal samples, a novel diagnostic tool was developed. Utilizing the PIPER instrument and MagDrive technology, the diagnostic eliminates the requirement for extensive training and manual counting which currently limits the application of conventional microscopic methods of oocysts per gram (OPG) measurement. Automated microscopy to identify and count oocysts and report OPG simplifies analysis and removes potential sources of operator error. Morphometric analysis on identified oocysts allows for the oocyst counts to be separated into 3 size categories, which were shown to discriminate the 3 most common Eimeria species in commercial broilers, E. acervulina, E. tenella, and E. maxima. For 75% of the samples tested, the counts obtained by the PIPER and hemocytometer methods were within 2-fold of each other. Additionally, the PIPER method showed less variability than the hemocytometer counting method when OPG levels were below 100,000. By automated identification and counting of oocysts from 12 individual fecal samples in less than one hour, this tool could enable routine, noninvasive diagnostic monitoring of coccidia in poultry operations. This approach can generate large, uniform, and accurate data sets that create new opportunities for understanding the epidemiology and economics of coccidia infections and interventional efficacy.

Quantifying antisite defect concentrations in yttrium aluminum garnet by high-precision density analysis

Quantifying the nature and density of lattice defects in high-quality crystals is often difficult or impossible with commonly employed material characterization techniques. In many cases, even the density of intentionally doped impurities present in a grown crystal must be inferred indirectly using methods such as mapping spatial variations in crystal properties or, when the defects are optically active, interpreting optical absorption with imprecisely known oscillator strengths. In this work we explore gravimetric techniques to obtain absolute defect densities in crystals, a powerful approach often overlooked in modern materials science. A hydrostatic weighing apparatus based on Archimedes’ principle was constructed, tested, and refined to enable high-precision density measurements of small crystal samples. Application of this system is illustrated by determining the density of Yttrium Aluminum Garnet (YAG) relative to a high-purity silicon crystal density reference, minimizing traditional difficulties in correcting for the variations in surface tension and the water and air density due to small changes in ambient temperature, pressure, and solution composition. This method, using a relatively simple apparatus and small samples, is effective in measuring the intrinsic concentration of Y–Al antisite lattice defects in YAG, agreeing with results from far more elaborate high-resolution optical laser spectroscopy at cryogenic temperatures. Furthermore, we quantitatively analyze the effects of several potential sources for error, including natural variations in isotope distributions, residual surface contamination, and ambient temperature or pressure variations. Subsequently, we find that the density analysis method is a promising technique for characterizing new and modified materials being developed for applications ranging from solid-state lasers and scintillators to quantum information.

Clinical decision making in acute medicine.

Clinical decision-making is a core skill for the practice of medicine and yet during training there is often little formal analysis of the process of clinical reasoning or instruction about how to do it better. This paper reviews the process of clinical decision-making with a particular focus on diagnostic reasoning. Aspects of psychology and philosophy are applied to the process along with consideration of potential sources of error and the steps that can be taken to minimize this.