Incorrect Size Research Articles

A systematic approach to adaptive sequential design for clinical trials: using simulations to select a design with desired operating characteristics

ABSTRACT The failure rates of phase 3 trials are high. Incorrect sample size due to uncertainty of effect size could be a critical contributing factor. Adaptive sequential design (ASD), which may include one or more sample size re-estimations (SSR), has been a popular approach for dealing with such uncertainties. The operating characteristics (OCs) of ASD, including the unconditional power and mean sample size, can be substantially affected by many factors, including the planned sample size, the interim analysis schedule and choice of critical boundaries and rules for interim analysis. We propose a systematic, comprehensive strategy which uses iterative simulations to investigate the operating characteristics of adaptive designs and help achieve adequate unconditional power and cost-effective mean sample size if the effect size is in a pre-identified range.

Consumers' interaction with online fashion retailers' body measurement guidance

PurposeOnline fashion retailers offer body measurement guidance, alongside their target consumer body size charts and fit information, to help consumers select the right size garment as the garment cannot be tried on. Its use by retailers suggests it can act as a means of mitigating garment returns as there has been a noted increase in returns due to incorrect size selection even though body measurement instructions are provided online. The purpose of this research is to determine how consumers interact with body measurement guidance, how they interpret it and use it, thereby interrogating its efficacy.Design/methodology/approachAn exploratory investigation was undertaken. Thirty participants were recruited and given a choice of fashion retailers' body measurement guidance and a tape measure. They took their body measurements over their clothes. A technician repeated the task, thereby providing two sets of body measurements. A paired t-test determined if there was a significant difference in both values in terms of their mean. Technicians also documented their observations of how the participants interacted with the task. The content of the fashion retailer measurement guidance was then compared to that of published anthropometric guidance for surveys.FindingsParticipants were familiar with the guidance and tape-measure; they were able to self-measure. The fashion retailer measurement guidance, however, lacked detail/clarity in visuals and written content when compared to anthropometric guidance. Interpretation of the guidance differed between participant and technician. This resulted in a significant difference in circumference measurements for the bust/chest and hips, yet no significant difference in waist and inside-leg measurements. For measurements that were difficult to take unaided, participants devised novel practices which resulted in little divergence from the technician taken body measurements. The results question the guidance efficacy in its current form.Originality/valueThere has been no study which addresses how consumers interpret and interact with fashion retailers' online measurement guidance. This is important as this can mitigate garment returns. This research provides insight to influence fashion retailers' measurement guidance policy. It also adds to the existing body of knowledge surrounding anthropometric practice for clothing.Research limitations/implicationsThe findings indicated that fashion retailers need to revise their body measurement guidance content. The content needs to be more comprehensive but still use accessible language and visuals. The broader implications of this study highlight that traditional anthropometrics for self-taken body measurement needs developing as an emerging concept through clothing-related academic study.Practical implicationsFashion retailers' measurement guidance needs to be more comprehensive but still use accessible language and visuals. The broader implications of this study highlight that traditional anthropometrics for self-taken body measurement needs further investigation and documentation as an emerging concept through clothing-related academic study.

Hypoxia delays steroid-induced developmental maturation in Drosophila by suppressing EGF signaling.

Animals often grow and develop in unpredictable environments where factors like food availability, temperature, and oxygen levels can fluctuate dramatically. To ensure proper sexual maturation into adulthood, juvenile animals need to adapt their growth and developmental rates to these fluctuating environmental conditions. Failure to do so can result in impaired maturation and incorrect body size. Here we describe a mechanism by which Drosophila larvae adapt their development in low oxygen (hypoxia). During normal development, larvae grow and increase in mass until they reach critical weight (CW), after which point a neuroendocrine circuit triggers the production of the steroid hormone ecdysone from the prothoracic gland (PG), which promotes maturation to the pupal stage. However, when raised in hypoxia (5% oxygen), larvae slow their growth and delay their maturation to the pupal stage. We find that, although hypoxia delays the attainment of CW, the maturation delay occurs mainly because of hypoxia acting late in development to suppress ecdysone production. This suppression operates through a distinct mechanism from nutrient deprivation, occurs independently of HIF-1 alpha and does not involve dilp8 or modulation of Ptth, the main neuropeptide that initiates ecdysone production in the PG. Instead, we find that hypoxia lowers the expression of the EGF ligand, spitz, and that the delay in maturation occurs due to reduced EGFR/ERK signaling in the PG. Our study sheds light on how animals can adjust their development rate in response to changing oxygen levels in their environment. Given that hypoxia is a feature of both normal physiology and many diseases, our findings have important implications for understanding how low oxygen levels may impact animal development in both normal and pathological situations.

Impact of PSF misestimation and galaxy population bias on precision shear measurement using a CNN

ABSTRACT Weak gravitational lensing of distant galaxies provides a powerful probe of dark energy. The aim of this study is to investigate the application of convolutional neural networks (CNNs) to precision shear estimation. In particular, using a shallow CNN, we explore the impact of point spread function (PSF) misestimation and ‘galaxy population bias’ (including ‘distribution bias’ and ‘morphology bias’), focusing on the accuracy requirements of next generation surveys. We simulate a population of noisy disc and elliptical galaxies and adopt a PSF that is representative of a Euclid-like survey. We quantify the accuracy achieved by the CNN, assuming a linear relationship between the estimated and true shears and measure the multiplicative (m) and additive (c) biases. We make use of an unconventional loss function to mitigate the effects of noise bias and measure m and c when we use either: (i) an incorrect galaxy ellipticity distribution or size–magnitude relation, or the wrong ratio of morphological types, to describe the population of galaxies (distribution bias); (ii) an incorrect galaxy light profile (morphology bias); or (iii) a PSF with size or ellipticity offset from its true value (PSF misestimation). We compare our results to the Euclid requirements on the knowledge of the PSF model shape and size. Finally, we outline further work to build on the promising potential of CNNs in precision shear estimation.

Quadrat misuse: Confessions of a cover crop researcher's biomass sampling journey

AbstractRectangular quadrats (1 m2 or less) are commonly used in cover crop research to sample shoot biomass in fields where the cover crops are planted in narrow rows. However, in drilled cover crops, quadrats do not accurately estimate cover crop biomass unless the width dimension of the quadrat, that runs perpendicular to the rows, is a multiple of the cover crop row spacing. Illustrations are provided with correctly sized and placed quadrats for sampling drilled cover crops along with calculations to convert sampled biomass to field‐scale units. Examples with various quadrat sizes, row spacings, and quadrat placements are used to illustrate how researchers can inadvertently underestimate or overestimate biomass by up to 49% and 27%, respectively. A survey of 92 articles with cover crop biomass data published in the Agronomy Journal and Weed Technology from 2017 to 2021 found that many studies used an incorrect quadrat size, which suggests that they may have inaccurately estimated cover crop biomass. However, assumptions were made to reach this conclusion because only a few papers provided the dimensions, orientation, and shape of the quadrat used. These results (1) raise important questions about possible errors made in papers reporting cover crop biomass data and associated metrics (nitrogen uptake, weed biomass, etc.), and (2) highlight the need for describing sampling methods in greater detail to ensure that accurate data and analysis are published in the literature. Approaches to correct possible errors in published research are described along with biomass sampling suggestions for future cover crop research.

The application of human reliability analysis to carpal tunnel decompression.

Many surgical procedures are prone to human error, particularly in the learning phase of skills acquisition. Task standardisation has been suggested as an approach to reducing errors, but it fails to account for the human factors associated with learning. Human reliability analysis (HRA) is a structured approach to assess human error during surgery. This study used HRA methodologies to examine skills acquisition associated with carpal tunnel decompression. The individual steps or subtasks required to complete a carpal tunnel decompression were identified using hierarchical task analysis (HTA). The systematic human error reduction and prediction approach (SHERPA) was carried out by consensus of subject matter experts. This identified the potential human errors at each subgoal, the level of risk associated with each task and how these potential errors could be prevented. Carpal tunnel decompression was broken down into 46 subtasks, of which 21 (45%) were medium risk and 25 (55%) were low risk. Of the 46 subtasks, 4 (9%) were assigned high probability and 18 (39%) were assigned medium probability. High probability errors (>1/50 cases) included selecting incorrect tourniquet size, failure to infiltrate local anaesthetic in a proximal-to-distal direction and completion of the World Health Organization (WHO) surgical sign-out. Three (6%) of the subtasks were assigned high criticality, which included failure to aspirate before anaesthetic injection, whereas 21 (45%) were assigned medium criticality. Remedial strategies for each potential error were devised. The use of HRA techniques provides surgeons with a platform to identify critical steps that are prone to error. This approach may improve surgical training and enhance patient safety.

Bayesian sample size calculations for comparing two strategies in SMART studies.

In the management of most chronic conditions characterized by the lack of universally effective treatments, adaptive treatment strategies (ATSs) have grown in popularity as they offer a more individualized approach. As a result, sequential multiple assignment randomized trials (SMARTs) have gained attention as the most suitable clinical trial design to formalize the study of these strategies. While the number of SMARTs has increased in recent years, sample size and design considerations have generally been carried out in frequentist settings. However, standard frequentist formulae require assumptions on interim response rates and variance components. Misspecifying these can lead to incorrect sample size calculations and correspondingly inadequate levels of power. The Bayesian framework offers a straightforward path to alleviate some of these concerns. In this paper, we provide calculations in a Bayesian setting to allow more realistic and robust estimates that account for uncertainty in inputs through the 'two priors' approach. Additionally, compared to the standard frequentist formulae, this methodology allows us to rely on fewer assumptions, integrate pre-trial knowledge, and switch the focus from the standardized effect size to the MDD. The proposed methodology is evaluated in a thorough simulation study and is implemented to estimate the sample size for a full-scale SMART of an internet-based adaptive stress management intervention on cardiovascular disease patients using data from its pilot study conducted in two Canadianprovinces.

Evaluation Of Relationship Causes Of The Return Process In The Supply Chain Of The Textile Industry

This research focuses on the return process, the process where consumers decide to return the product after receiving an order or after making a purchase. This incident is not desired by the company, because it has the potential to reduce profits and consumer loyalty. However, the company is aware that the return process cannot be avoided. So this research aims to evaluate the factors that have the potential to cause the return process by using the Interpretive Structural Modeling (ISM) Methodology. This research case study was conducted on a textile company that serves orders for school uniforms, office uniforms, moslem clothes, etc. Nine factors were identified, that are: off-season, overstock, delivery error, incorrect size, incorrect color, quality issue, change mind, damaged item, and incorrect product, which are the reasons consumers carry out the return process. The results of the ISM-based model and MICMAC analysis mapping show that the quality issue factor is the key reason for consumers to make the return process. The strategy of handling presses return in connection with these factors is carried out by developing a system that supports customer support work to maintain consumer loyalty. Through the ISM methodology, companies can simplify complex problems, so they focus on the factors that are the root of the problem to be able to design strategies to deal with them.

Comprehensive detection method for multi-contaminants in hydraulic oil based on inductance-resistance-capacitance analysis

Oil condition monitoring technology is a practical method for mechanical fault diagnosis, because oil contamination can directly reflect the lubrication and wear state. A comprehensive detection method based on integrated sensor consisting of an inductance-resistance sensing unit and a capacitance sensing unit is introduced in this article. Inductance parameter differentiates metallic debris, and the coil-based resistance parameter can detect smaller non-ferromagnetic metallic debris. Capacitance parameter is used to measure air bubbles and moisture, and the moisture measurement is not interfered by solid impurities. The simulation analysis showed that annular channel reduces the instability of inductive-resistive detection caused by position effect. The experimental results proved that the integrated inductive-resistive-capacitive sensor detects air bubbles, moisture, ferromagnetic debris and non-ferromagnetic debris by comparing multi-parameter signals. This method expands the detection range for oil contamination, and reduces the probability of incorrect particle counting and incorrect size measurement, which provides technical support for the intelligent operation and maintenance of mechanical equipment.

Efficiency and Optimal size of Italian Public Hospitals: Results from Data Envelopment Analysis

Background: One of the major issues discussed in the literature about hospital efficiency is the impact of hospital size on technical efficiency. Many studies have observed that in some cases, hospital technical inefficiency is correlated with an incorrect size. This paper addresses this topic. In particular, we attempt to identify an optimal size of hospitals in terms of beds.
 Methods: The study is organized as follow: first, we performed the Data Envelopment Analysis in order to calculate the technical and scale efficiency scores for a sample of 41 Italian public hospitals during the period 2010-2013; second, we investigated the impact of size on hospital efficiency, identifying the magnitudes of input reductions needed to make inefficient public hospitals efficient. Finally, we calculated the most productive scale size for each hospital in the sample. According to these results, through an overall observation, we attempted to identify an optimal size for hospitals in terms of beds.
 Results: Most of the hospitals were inefficient and most of the inefficiency was the results of the presence of waste in terms of input resources. During the period considered, we found that inputs could be reduced by 22% on average. Economies of scale were found around 200 beds for 20.000 discharges per year.
 Conclusions: The identification of an optimal size of hospitals in terms of beds still requires further efforts in the literature. However, this study contributes to support hospital managers in resource allocation choices through a quantitative approach.

Periodic Resuscitation Cart Checks and Nurse Situational Awareness: An Observational Study

IntroductionThe periodic check of the function and integrity of the resuscitation cart is very important to ensure that the cart is prepared for use to provide emergency care to critical patients. Little is known about situational awareness during the periodic inspection of resuscitation carts. The purpose of this study was to measure hospital clinical nurses’ situational awareness immediately after completion of a check of the resuscitation cart content and to directly observe and assess the resuscitation cart readiness in the selected hospitals. MethodsAn observational correlational study with a self-report measure design was used in which the Situation Awareness Rating Technique was collected immediately after the completion of checking of the resuscitation cart. ResultsAmong the 332 nurse participants, the mean situational awareness score was 16.42 (standard deviation 5.26), reflecting an average situational awareness during the task of checking and inspection of the resuscitation cart. Knowing the policies and guidelines relating to resuscitation and the resuscitation cart is associated with the participants’ situational awareness (F3,33 = 3.70, P = .04). In addition, working in critical areas and the number of years of working experience are associated with the participants’ situational awareness (F2,33 = 3.24, P = .04 and F3,33 = 3.00, P = .02, respectively). Assessing the resuscitation cart readiness revealed several issues such as empty oxygen tanks (32%); drained batteries and equipment failure (16%); incorrect size of equipment (16%); and missing, expired, and unavailable equipment (15%). Some of these issues were noted even though the carts were checked several times by different participants. DiscussionMuch work needs to be done, because inadequate situational awareness during the periodic check of the resuscitation cart content can affect patient safety in life-threatening emergencies.

Enhancement of Imperfection Detection Capabilities in TIG Welding of the Infrared Monitoring System

For a low cost, there are industrial infrared monitoring systems used for imperfection detection and identification in welded joints. The key drawback that impedes real life industrial applications is the low spatial resolution, as well as the temporal resolution of low-cost infrared (IR) cameras. This is also the case in tungsten inert gas (TIG) welding. Taking into consideration the influence of voltage on the arc energy and heat input, high frequency sampled voltage was used to evaluate the interpolated temporal resolution of IR sequences. Additionally, a reflected temperature correction method was proposed to reduce the uncertainty of absolute temperature measurement with a thermographic camera. The proposed method was applied to detect several imperfection types, such as lack of or incomplete penetration as well as incorrect weld shape and size (including burnouts). Results obtained for different interpolation factors were compared. The obtained results emphasize the validity of reflected temperature correction method. For the weld defects detection task, the smallest detectable defect was found for various interpolation factors. Moreover, the correspondence of arc voltage and the joint temperature was checked. Additionally, a set of decision rules was elaborated on and applied to distinguish between various joint conditions. It was found that defects that do not have symmetrical temperature distribution with respect to the joint axis are harder to identify.

Mastering the scientific peer review process: tips for young authors from a young senior editor

Are you a student at a higher institution or an early-career researcher who is striving to understand and master the peer review process so to increase the odds of getting a paper published in the Journal of Forestry Research or another reputable, peer-reviewed, scientific journal? In this paper, a young, senior editor provides a handbook of the peer review process based on his decadal experience in scientific publishing. He covers major information you need to know during the entire process, from selecting journals to completing the proofing of your accepted paper. He introduces key points for consideration, such as avoidance of predatory journals, dubious research practices and ethics, interaction with peers, reviewers, and editors, and the pursuit of aretê. Finally, he points out some common statistical errors and misconceptions, such as P hacking and incorrect effect size inference. He hopes that this paper will enhance your understanding and knowledge of the peer-review process.

Factors associated with inaccurate size estimation of colorectal polyps: A multicenter cross-sectional study.

Accurate polyp size estimation is essential in deciding the therapeutic strategy of colorectal polyps and endoscopic surveillance intervals. However, many endoscopists frequently make incorrect size estimations without being aware of their errors. This cross-sectional study aimed to clarify the characteristics of endoscopists associated with inaccurate estimation. We previously conducted a web trial involving 261 endoscopists in 51 institutions in Japan to assess their ability to estimate polyp size. Participants answered questions about polyp size using visual estimates in a test involving images of 30 polyps. Here, we investigated the relationships between inaccurate size estimation and the backgrounds of participants. The rates of overestimation and underestimation of polyp size were also compared to clarify any trends in the answers of participants with low accuracy (<50%). Multivariable logistic regression analysis revealed that the number of colonoscopic procedures in the past year was the only factor associated with a low accuracy of polyp size estimation (odds ratio 0.750, 95% confidence interval 0.609-0.925; P=0.007). Endoscopists with low accuracy had a greater tendency to overestimate polyp size (42.3% overestimation and 21.2% underestimation, P<0.001) compared with other endoscopists (16.6% overestimation and 17.9% underestimation, P=0.951). Endoscopists with limited experience of colonoscopy in the past year were more likely to make frequent errors in size estimation. Furthermore, endoscopists making inaccurate size estimations had a propensity to overestimate polyp size.

Sample size, power and effect size revisited: simplified and practical approaches in pre-clinical, clinical and laboratory studies.

Calculating the sample size in scientific studies is one of the critical issues as regards the scientific contribution of the study. The sample size critically affects the hypothesis and the study design, and there is no straightforward way of calculating the effective sample size for reaching an accurate conclusion. Use of a statistically incorrect sample size may lead to inadequate results in both clinical and laboratory studies as well as resulting in time loss, cost, and ethical problems. This review holds two main aims. The first aim is to explain the importance of sample size and its relationship to effect size (ES) and statistical significance. The second aim is to assist researchers planning to perform sample size estimations by suggesting and elucidating available alternative software, guidelines and references that will serve different scientific purposes.

Perceptions and experiences of healthcare workers during the COVID-19 pandemic in the UK

ObjectiveThe COVID-19 pandemic has set unprecedented demand on the healthcare workforce around the world. The UK has been one of the most affected countries in Europe. The aim of this...

Error detection and classification in patient-specific IMRT QA with dual neural networks.

Despite being the standard metric in patient-specific quality assurance (QA) for intensity-modulated radiotherapy (IMRT), gamma analysis has two shortcomings: (a) it lacks sensitivity to small but clinically relevant errors (b) it does not provide efficient means to classify the error sources. The purpose of this work is to propose a dual neural network method to achieve simultaneous error detection and classification in patient-specific IMRT QA. For a pair of dose distributions, we extracted the dose difference histogram (DDH) for the low dose gradient region and two signed distance-to-agreement (sDTA) maps (one in x direction and one in y direction) for the high dose gradient region. An artificial neural network (ANN) and a convolutional neural network (CNN) were designed to analyze the DDH and the two sDTA maps, respectively. The ANN was trained to detect and classify six classes of dosimetric errors: incorrect multileaf collimator (MLC) transmission (±1%) and four types of monitor unit (MU) scaling errors (±1% and ±2%). The CNN was trained to detect and classify seven classes of spatial errors: incorrect effective source size, 1mm MLC leaf bank overtravel or undertravel, 2mm single MLC leaf overtravel or undertravel, and device misalignment errors (1mm in x- or y direction). An in-house planar dose calculation software was used to simulate measurements with errors and noise introduced. Both networks were trained and validated with 13 IMRT plans (totaling 88 fields). A fivefold cross-validation technique was used to evaluate their accuracy. Distinct features were found in the DDH and the sDTA maps. The ANN perfectly identified all four types of MU scaling errors and the specific accuracies for the classes of no error, MLC transmission increase, MLC transmission decrease were 98.9%, 96.6%, and 94.3%, respectively. For the CNN, the largest confusion occurred between the 1-mm-MLC bank overtravel class and the 1-mm-device alignment error in x-direction class, which brought the specific accuracies down to 90.9% and 92.0%, respectively. The specific accuracy for the 2-mm-single MLC leaf undertravel class was 93.2% as it misclassified 5.7% of the class as being error free (false negative). Otherwise, the specific accuracy was above 95%. The overall accuracies across the fivefold were 98.3±0.7% and 95.6%±1.5% for the ANN and the CNN, respectively. Both the DDH and the sDTA maps are suitable features for error classification in IMRT QA. The proposed dual neural network method achieved simultaneous error detection and classification with excellent accuracy. It could be used in complement with the gamma analysis to potentially shift the IMRT QA paradigm from passive pass/fail analysis to active error detection and root cause identification.

Numerical simulation of compression corner flows at Mach number 9

A hypersonic vehicle encounters a wide range of conditions during its complete flight regime. These flight conditions may vary from low to high Mach numbers with varying angles of attack. The near-wall viscous dissipation associated with flows at combined high Mach and Reynolds numbers leads to significant wall heat transfer rates and shear stresses. The shock wave/boundary-layer interaction results in a flow separation region, which commonly augments total pressure losses in the flow and lowers the efficiency of aerodynamic control surfaces such as fins installed on a vehicle. The standard turbulence models, when used to resolve such flows, result in incorrect separation bubble size for large separated flows. Therefore, it results in an inaccurate aerodynamic load, such as the wall pressures, skin friction distribution, and heat transfer rate. In previous studies, the application of the shock-unsteadiness correction to the standard two-equation k-ω turbulence model improved the separation bubble size leading to an accurate pressure prediction and shock definition with the assumption of constant Prandtl number. In the present work, the new shock-unsteadiness modification to the k-ω turbulence model is applied to the hypersonic compression corner flows. This new model with variable Prandtl number is based on the model parameter, which depends upon the local density ratio. The computed wall pressures, heat flux and flow field are compared to the experimental data. A parametric study is carried out by varying compression deflection angles, free stream Reynolds number and wall temperatures to compute the flow field and wall data accurately, particularly in the shock boundary layer interaction region. The new shock-unsteadiness modified k-ω model with variable Prandtl number shows an accurate prediction of initial pressure rise location, pressure distribution in the plateau region and heat flux in comparison to the standard k-ω model.

Novel Technique for Optimal Placement and Sizing of DG in 3-Phase Unbalanced Radial Secondary Distribution System

The optimum position and volume of the Distributed Generation to be planned in the unbalanced radial distribution network (URDN) is critical to minimize power losses. Incorrect size and location may enhance the power losses and voltage regulation. This paper investigates the operations of the distribution system and aims to develop a new technique to solve the problem of placement and sizing distributed generation to minimize power loss, improving the profile of voltage. A Novel Sensitivity Analysis is used to estimate the optimal position and volume of DG units to be installed in a URDN. The proposed technique is validated on the 25 bus test system to illustrate and evaluate the correctness. The results are confronted with the results of distinct methods available in the literature. The performance of the proposed method is considered to be better in terms of the quality of the solutions than the other classical techniques..

Comparisons of day-time and night-time hydroacoustic surveys in temperate lakes

In recent years, due to an increased need for non-intrusive sampling techniques, hydroacoustics has attracted attention in fishery science and management. Efforts to promote standardisation are increasing the accuracy, efficiency, and comparability of this method. The European Water Framework Directive and the Standard Operating Procedures for Fisheries Hydroacoustic Surveys in North American Great Lakes has recommended that surveys be conducted at night. At night, fish usually disperse in the water column, thus allowing for single echo detection and subsequent accurate fish size estimation, while day-time schooling behaviour hampers the estimation of fish size. However, sampling during the day would often be safer and cheaper. This study analyses how fisheries hydroacoustic results differ between day-time and night-time surveys, using data from 14 natural temperate lakes of various size. Data collected during the day and night at two depth layers linked to thermal stratification were compared in terms of acoustic scattering strength, target strength, and biomass estimates. The results showed a significant correlation between day-time and night-time estimates, though biomass in the upper layer was biased for day-time surveys, mainly due to incorrect fish size estimates resulting from rare single echo detections and schooling behaviour. Biomass estimates for the lower depth layer did not significantly differ between the two diel periods. Thus, this study confirms that hydroacoustic sampling in temperate lakes should be performed at night for accurate fish stock biomass estimates.