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This paper presents an evaluation of the usability, functionality, and usefulness of the Warehouse Error Prevention (WEP) tool that consists of seven modules. The WEP tool is framed in a simple yes/no form, which can be used to identify human factors related to sources of pick errors in a warehouse. Thirty-three participants in 27 organisations from three different countries participated in a trial application and evaluation of the tool. The evaluation included a survey study and semi-structured interviews. Survey results show that participants agreed on the usability and functionality of the WEP tool. In the interviews, participants generally reported the WEP tool as being both accurate and functional with the potential to support engineers, ergonomists, and warehouse managers to improve order picking quality. Further quantitative field testing of the WEP tool's potential to identify costly warehouse errors is needed. [ABSTRACT FROM AUTHOR]

A WRF‐based high‐resolution reanalysis of the Irish climate (1981–2010) is used to create proxy daily precipitation observations at the locations of climatological sites used for precipitation monitoring; the data are statistically representative of the real precipitation climate both for mean (over monthly, seasonal and annual periods) and extreme values. The proxy observations are spatially interpolated to the original WRF grid using a typical gridding package and compared against the original data to assess gridding errors. The errors are more complex than the estimates provided by the gridding software; systematic biases are evident which by the inclusion of strategically placed additional observing sites are shown to be greatly reduced. There is also evidence of systematic differences in trend analyses of extreme precipitation over the period. The method provides independent estimates of the errors that arise from actual gridding applications. It also facilitates the testing of the optimality of a network by highlighting possible inadequacies in an existing station layout and suggesting new observing site locations to fill gaps. Uncertainties regarding the errors in real precipitation observations, and possible spurious impacts linked to temporal changes in the real observing network, are avoided by this method. [ABSTRACT FROM AUTHOR]

Turbofan engines exhibit pronounced nonlinearity due to component characteristics and thermal processes, necessitating linearization to connect engine control with linear control theory. Off-equilibrium linearization offers excellent transient tracking and controller performance, making it ideal for military turbofan engines with rapid acceleration and deceleration. Hardware-in-Loop (HIL) experiments are crucial for verifying controller performance, but time delays in the HIL platform can cause oscillations in state variables when using this linearization method. To address this issue, this paper introduces an off-equilibrium linearization-based control strategy. This strategy employs an off-equilibrium linearized model to approximate the nonlinear time-delay system, followed by designing an H8 controller for the linear time-delay system. The effectiveness of this approach applied to turbofan engines, including its antidelay and robust tracking capabilities, is validated through simulations, HIL experiments, and semiphysical experiments. [ABSTRACT FROM AUTHOR]

Early detection is the most effective defense against breast cancer. Mammography is a well-established X-ray-based technique that is used for annual or biennial screening of women above age of 40. Since the dense breast tissue sometimes obscures the cancer in an X-ray image, about 10% of screened women are recalled and undergo additional adjunctive modalities, such as ultrasound, digital breast tomosynthesis, or magnetic resonance imaging. These modalities have drawbacks such as additional radiation dosage, overdiagnosis, and high cost. A new concurrent multispectral imaging approach was recently presented to eliminate the high recall rates by utilizing the breast surface temperature data with an inverse physics-informed neural network algorithm. This method utilizes the bioheat transfer modeling as the governing physics equations and conducted inverse heat transfer modeling using infrared temperatures to predict the presence of a tumor heat source. Validation of the predicted tumor size and location was conducted on a biopsy-proven breast cancer patient using infrared temperature data captured of the breast surface and pathology reports. A regression analysis between the predicted temperatures and infrared temperatures showed a coefficient of determination of 0.98. The absolute error in the predicted tumor size was 0.4 cm and the maximum absolute error in tumor location was 0.3 cm. The proposed approach shows promising results and performance. However, additional testing with more patients is required to quantify the standard deviation in the prediction and establish the sensitivity and specificity of the machine learning technique. [ABSTRACT FROM AUTHOR]

Adverse events have a profound impact on surgeons. This impact extends to physical and mental health, psychological wellbeing, and professional performance. Surgeons are ill prepared for these consequences of adverse events and are under-supported when they inevitably occur. Here we review the data on how adverse events affect surgeons. We explore the efforts made to date to both prepare surgeons before and support them after such events and we make recommendations regarding how this should and could be done better. [ABSTRACT FROM AUTHOR]

Quantum state tomography (QST) aiming at reconstructing the density matrix of a quantum state plays an important role in various emerging quantum technologies. Recognizing the challenges posed by imperfect measurement data, we develop a unified neural network (NN)-based approach for QST under constrained measurement scenarios, including limited measurement copies, incomplete measurements, and noisy measurements. Through comprehensive comparison with other estimation methods, we demonstrate that our method improves the estimation accuracy in scenarios with limited measurement resources, showcasing notable robustness in noisy measurement settings. These findings highlight the capability of NNs to enhance QST with constrained measurements. [ABSTRACT FROM AUTHOR]

This study seeks to ascertain the pronunciation inaccuracies of Kurdish English as a Foreign Language (EFL) students at the university level when articulating English diphthong phonemes. These students grapple with challenges related to the articulation of diphthong sounds in English due to their limited exposure and practice. The primary objective of this research is to identify, categorize, and quantify the total number of pronunciation errors made by Kurdish EFL students in the context of English diphthongs. A sample of thirty undergraduate Kurdish EFL students, who are native speakers of Northern Kirmanci, participated in this descriptive qualitative study. The students were requested to pronounce 40 English words, encompassing the eight diphthong sounds prescribed by Southern Standard British English Received Pronunciation (RP). Their pronunciations were recorded using smartphones. These students, who were in their senior year of undergraduate studies, were selected for the study. The recordings of the students' pronunciations were meticulously examined to discern common mispronunciations of English diphthong sounds. Subsequently, the data were collected, organized, and ranked in order of prevalence, ultimately revealing a total of 405 errors. The prevalence of diphthong errors is presented as follows: (ʊə) at a rate of 93.3%, (ɪə) 58.8%, (əʊ) 42.2%, (eə) 37.3%, (aʊ) 28.6%, (eɪ) 14.7%, (aI) 8%, and (ɔɪ) 5.8%. Kurdish native speakers frequently encounter difficulties in articulating English diphthongs, primarily due to the absence of these sounds in their native language and a dearth of English pronunciation study and practice throughout their academic journey. These diphthong pronunciation errors manifest in eight distinct patterns, contributing to a spectrum of student proficiency levels. Consequently, to enhance their linguistic competence and accurately pronounce English words containing diphthongs, students should engage in sustained diphthong practice during their academic tenure at the university [ABSTRACT FROM AUTHOR]

The analysis of the subsidence cone at Salina Ocna Dej involved modern measurement techniques, including drones, to evaluate terrain changes and generate a detailed 3D model. Data collection occurred in two stages, in 2021 and 2022, utilizing drones to capture a large number of high-resolution images (5472x3648 pixels) [1], resulting in a significant volume of data. These images were processed using specialized software to create a 3D model, employing advanced alignment, data fusion, and interpolation techniques. The results demonstrated that using drones offers considerable benefits over traditional methods, including increased accuracy and reduced time and resource consumption [2], with minimal errors recorded at just 0.7 mm. The project emphasized the importance of adapting initial plans to field conditions and considering weather forecasts to prevent accidents. Post-processing the data enabled clear delineation of the subsidence contour and slope angles, facilitating their integration into the analysis of other mining activities in the region. The generated 3D model serves as a reference for monitoring subsidence evolution and assessing risks to nearby residences. Continuous measurement and constant monitoring of the subsidence cone are essential to prevent potential future damage caused by slope instability and erosion. [ABSTRACT FROM AUTHOR]

Background: Minimizing air aspiration by carefully filling blood gas syringes is crucial to prevent air contamination from causing undesirable variations in gasses and other molecules. While some previous studies investigated this aspect, these are now outdated and only analyzed a limited number of blood gas parameters. Thus, we investigated the effects air contamination in the syringe using a modern blood gas analyzer. Methods: We sampled venous blood from 17 laboratory workers (mean age: 46±11 years; 10 women), filling two consecutive blood gas syringes. The first was filled exactly to its nominal volume (i.e., 1.0 mL), while the second was filled with 0.8 mL of blood and 0.2 mL of ambient air. Blood gas analysis was performed in each syringe using an identical analyzer. Results: In the syringe with the air bubble, we found statistically significant increase in pH (0.1%), pO2 (10.8%), SO2 (11.2%), total hemoglobin (3.0%), and hematocrit (2.7%), while values of pCO2 (-4.8%), sodium (-0.5%), and ionized calcium (-1.3%) were significantly reduced. With exception of pH, all these changes exceeded the performance specifications. Potassium, chloride, glucose, lactate, COHb and MetHb values remained unchanged. Conclusions: These findings confirm that air bubbles must be removed as soon as possible after sampling from blood gas syringes to prevent artifactual test results and misleading clinical judgment and inappropriate treatment. When blood gas syringes are received in the laboratory with air bubbles inside, the most vulnerable parameters (i.e., pO2, SO2, pCO2, sodium, ionized calcium, hematocrit and hemoglobin) should be suppressed. [ABSTRACT FROM AUTHOR]

This essay chronicles my personal journey of uncovering a truth that contradicted my long-held assumptions, resulting in a profound professional reckoning. It began with my discovery of a treasure trove of 350 glass plate negatives, masterpieces captured between 1920 and 1940, which led me to write a biography of the photographer, Benedict Stolz, a German Benedictine monk. A central figure in this biography was Hermann Keller, Stolz's childhood friend and, in his day, a renowned theologian, philosopher, and Hebraist. I portrayed Keller as a Nazi war criminal and associate of SS leader Reinhard Heydrich, based on numerous secondary sources. However, shortly before publication, an interview with a nun who had known Keller challenged this narrative, attributing the "erroneous charges" against him to the mistakes of one historian that were subsequently echoed by others. After years of doubting her claims, I was confronted with evidence proving Keller's innocence, prompting a critical reflection on how historians, including myself, can unwittingly propagate inaccuracies. [ABSTRACT FROM AUTHOR]

The primary goal of this paper is to develop a formal foundation to design an adaptive output feedback predictor for a class of unknown systems where parameters and order are unknown or high-dimensional. We present a reduced-order adaptive output-predictor scheme based on modal reduction and Lyapunov's method. Moreover, the credibility of the proposed reduced-order adaptive output-predictor scheme is validated by mathematical proof and numerical studies. [ABSTRACT FROM AUTHOR]

This article presents serious errors, corrections and omissions in the New York Times coverage of the Israel-Hamas war in Gaza from October 2023 to June 2024. The Times was selected for investigation since it is one of the most influential newspapers in the world. Errors were identified by external sources, corrections were late, vague and evasive. Omissions created false context and reporting, and lacked transparency. Among the explored case studies and issues: Al-Ahli Hospital explosion, civilian casualties, misquoting Israeli leaders, employing questionable journalists, and internal newsroom testimonials. The findings reveal misleading repeated errors, inadequate corrections, significant omissions, and poor editorial supervision. [ABSTRACT FROM AUTHOR]

We examine and benchmark the emerging idea of applying the large eddy simulation (LES) formalism to unconventionally coarse grids where Reynolds-averaged Navier-Stokes (RANS) would be considered more appropriate at first glance. We distinguish this idea from very large eddy simulation and detached eddy simulation, which require switching between RANS and LES formalism. LES on RANS grid is appealing because first, it requires minimal changes to a production code; second, it is more cost-effective than LES; third, it converges to LES; and most importantly, it accurately predicts flows with separation. This work quantifies the benefit of LES on RANS-like grids as compared to RANS on the same grids. Three canonical cases are considered: periodic hill, backward-facing step, and jet in cross flow. We conduct direct numerical simulation (DNS), proper LES on LES grids, LES on RANS-quality grids, and RANS. We show that while the LES solutions on the RANS-quality grids are not grid converged, they are twice as accurate as the RANS on the same grids. [ABSTRACT FROM AUTHOR]

The purpose of this study was to investigate the effects of contamination of venous blood with a lipid-containing solution on parameters measured by a modern blood gas analyzer. We collected venous blood from 17 healthcare workers (46 ± 11 years; 53 % women) into three blood gas syringes containing 0 , 5 and 10 % lipid-containing solution. Blood gas analysis was performed within 15 min from sample collection on GEM Premier 5000, while triglycerides and serum indices were assays on Roche COBAS C702. Triglycerides concentration increased from 1.0 ± 0.3 mmol/L in the uncontaminated blood gas syringe, to 39.4 ± 7.8 and 65.3 ± 14.4 mmol/L (both p<0.001) in syringes with 5 and 10 % final lipid contamination. The lipemic and hemolysis indices increased accordingly. Statistically significant variation was noted for all analytes except hematocrit and COHb in the syringe with 5 % lipids, while only COHb did not vary in the syringe with 10 % lipids. Significant increases were observed from 5 % lipid contamination for pO2, SO2 and lactate, while the values of pH, pCO2, sodium, potassium, chloride, ionized calcium, glucose, hematocrit (10 % contamination), hemoglobin and MetHB decreased. All these changes except lactate and CoHb exceeded their relative performance specifications. Artifactual hyperlipidemia caused by contamination with exogenous lipids can have a clinically significant impact on blood gas analysis. Manufacturers of blood gas analyzers must be persuaded to develop new instruments equipped with serum indices. [ABSTRACT FROM AUTHOR]

As sleep problems can impair quality of work, an online questionnaire was used to examine relationships between sleepiness and decision making while obtaining unobtrusive indices of performance. Participants (N = 344) completed the Insomnia Severity Index, Epworth Sleepiness Scale, and the Melbourne Decision Making Questionnaire in a Qualtrics survey while reporting mobile phone use. Qualtrics recorded the time and the number of clicks required to complete each page of the survey. Multiple regression indicated that insomnia was associated with daytime sleepiness and Hypervigilance, and mobile phone use before bed. Participants with moderate sleepiness required a greater number of clicks to complete the questionnaire. Greater sleepiness was associated with longer times to complete these self-assessment tasks. Clinically significant sleepiness produces changes in performance that can be detected from online responsivity. As sleepy individuals can be appreciably and quantitatively slower in performing subjective self-assessment tasks, this argues for objective measures of sleepiness and automated interventions and the design of systems that allow better quality sleep. Practitioner summary: Work can require processing of electronic messages, but 24/7 accessibility increases workload, causes fatigue and potentially creates security risks. Although most studies use people's self-reports, this study monitors time and clicks required to complete self-assessment rating scales. Sleepiness affected online responsivity, decreasing online accuracy and increasing response times and hypervigilance. [ABSTRACT FROM AUTHOR]

Models of heuristics are often predicated on the desideratum that they should possess no free parameters. As a result, heuristic implementations are usually deterministic and do not allow for any choice errors, as the latter would require a parameter to regulate the magnitude of errors. We discuss the implications of this in light of research that highlights the evidence supporting stochastic choice and its dependence on preferential strength. We argue that, in principle, the existing models of deterministic heuristics should, and can, be quite easily modified to stochastic counterparts through the addition of an errormechanism. This requires a single free parameter in the error mechanism, whilst otherwise retaining the parameter-free cognitive processes in the deterministic component of existing heuristics. We present various types of error mechanisms applicable to heuristics and discuss their comparative virtues and drawbacks, paying particular attention to their impact on model comparisons between heuristics and parameter-rich models. [ABSTRACT FROM AUTHOR]

Radiological interpretations, while essential, are not infallible and are best understood as expert opinions formed through the evaluation of available evidence. Acknowledging the inherent possibility of error is crucial, as it frames the discussion on improving diagnostic accuracy and patient care. A comprehensive review of error classifications highlights the complexity of diagnostic errors, drawing on recent frameworks to categorize them into perceptual and cognitive errors, among others. This classification underpins an analysis of specific error types, their prevalence, and implications for clinical practice. Additionally, we address the psychological impact of radiological practice, including the effects of mental health and burnout on diagnostic accuracy. The potential of artificial intelligence (AI) in mitigating errors is discussed, alongside ethical and regulatory considerations in its application. This research contributes to the body of knowledge on radiological errors, offering insights into preventive strategies and the integration of AI to enhance diagnostic practices. It underscores the importance of a nuanced understanding of errors in radiology, aiming to foster improvements in patient care and radiological accuracy. [ABSTRACT FROM AUTHOR]

The development of proton therapy techniques imposes strict requirements for the accuracy of proton beam delivery. Existing methods for determining the planning target volume allow one to take into account only the influence of patient positioning errors before the start of irradiation. In this paper, the results of work on taking into account proton therapy system beam delivery errors for determining the planning target volume are presented. The technique for measuring the proton beam parameters and analyzing the measurement results is described. The calculation of the minimum required margin from the clinical target volume is carried out to guarantee its irradiation, taking into account the errors in beam delivery by the proton therapy system. [ABSTRACT FROM AUTHOR]

An implicit compact scheme is proposed to approximate the solution of parabolic partial differential equations (PDEs) of Burgers' type in two dimensions. These nonlinear PDEs are essential because they describe various mechanisms in engineering and physics. The nonlinear convective and advective processes are discretized with high-order accuracy on an arbitrary grid, which results in a family of high-resolution discrete replacements of given PDEs. The essence of the new scheme lies in its compact character and two-level single-cell discretization, so that one discrete equation leads to the accuracy of orders three or four, depending upon the choice of the grid network. The scheme is used for solving celebrated nonlinear PDEs, such as the nondegenerate convection–diffusion equation, the generalized Burgers–Huxley equation, the Buckley–Leverett equation, and the Burgers–Fisher equation. Many computational results are presented to demonstrate the high-resolution character of the newly proposed scheme. [ABSTRACT FROM AUTHOR]

Teachers' beliefs about students' errors are influenced by structural factors and by other beliefs towards education and students that teachers may hold. The literature on this topic has provided some evidence and some mixed results. Furthermore, some structural aspects related to errors have not been considered in framing teachers' beliefs about errors, such as the use of grades as a classroom assessment practice, which is strongly related to errors in testing situations. Based on these premises, this study aimed to explore teachers' beliefs about errors and the practices teachers report using to deal with students' errors in the classroom and teachers' beliefs about the interdependence between grades and errors. Italian teachers (N = 33) from primary, middle, and secondary schools had been interviewed and the qualitative data were analysed through reflexive thematic analysis. The results showed that, according to teachers, errors acquire different meanings in the learning process, which are related to the roles they play in fostering or not learning. Furthermore, in describing these roles teachers reported to use specific practices to deal with students' errors. Finally, teachers acknowledged that classroom assessment based on grades has a negative interdependency with errors that makes it difficult to present errors as a fruitful part of learning both in learning and testing situations. Our results reveal the ambivalence of teachers' beliefs about errors and shed light on the challenges the grading evaluation system poses to teachers. [ABSTRACT FROM AUTHOR]

Abstract Triage systems, crucial for Emergency Departments, face unresolved doubts and issues that have not been addressed, coupled with increasing fragmentation due to a growing body of new evidence. International collaboration is essential for evidence-based triage solutions.

The accuracy and reliability of IoT-based sensor networks depend on validating sensed data, including detecting outliers at the node level. This study proposes an online outlier detection approach using Multiple Linear Regression-based adaptive thresholds for real-time IoT/WSN sensor nodes. IoT sensors experience two outlier types: Errors, from sensor malfunctions or low battery, and Events, from sudden environmental changes. The Adaptive Threshold Based Outlier Detection (ATBOD) approach differentiates errors from events using an adaptive threshold that adjusts to real-time data patterns. Unlike existing methods that are used in literature, which lack automated model evolution and suffer from delays and high computational time, ATBOD enhances outlier detection sensitivity without increasing false alarms, which is crucial for efficient IoT sensor board operation. It also improves sensor board lifespan by discarding errors at the node level, preventing energy wastage from transmitting error data to the cloud. ATBOD outperforms existing algorithms, which are referenced for comparison, such as Enhanced Efficient Outlier Detection and Classification Approach (EEODCA), K Nearest Neighbor approximate outlier detection (KNN), and Modified Local Outlier Factor (LOF), in Error Detection Rate, Error False Positive Rate, and Energy Saving Ratio. These advancements represent a significant leap in performance, making ATBOD a superior method for real-time outlier detection in IoT sensor networks.

Introduction: The occurrence of medication errors in hospital settings presents considerable public health challenges, as they significantly affect patient morbidity and mortality, especially with an increasing frequency in critical care units. Material and methods: A prospective before-and-after study conducted in Critical Care Unit 3 at Alexandria Main University Hospital involved 1440 observations of medication errors in 16-bed units over three months, encompassing 181 patients using a checklist. After implementing a sensitization program, a follow-up study was conducted with 1472 observations involving 185 patients over another three months. The comprehensive study focuses on the impact of the sensitization program on medication errors and its reporting, employing a prospective before-after design. Results: No statistically significant difference in mortality was observed between Control and Postintervention groups (p = 0.258). Prescription errors accounted for 52.0%, transcription errors 19.2%, dispensing errors 1.2%, preparation errors 13.9%, and administration errors 13.6% of total medication errors. In the Control group, 38.7% experienced at least one medical error, compared to 21.6% in the Postintervention group (p < 0.001). There were 396 medication errors (27.5% of observations) in the Control group versus 250 errors (17.0% of observations) in the Postintervention group (p < 0.001). Errors reporting increased from 3.8% to 30% (p < 0.001). Conclusions: The non-technological sensitization program effectively reduced medication errors in our resource-limited unit and improved error reporting. [ABSTRACT FROM AUTHOR]

The accuracy and reliability of IoT-based sensor networks depend on validating sensed data, including detecting outliers at the node level. This study proposes an online outlier detection approach using Multiple Linear Regression-based adaptive thresholds for real-time IoT/WSN sensor nodes. IoT sensors experience two outlier types: Errors, from sensor malfunctions or low battery, and Events, from sudden environmental changes. The Adaptive Threshold Based Outlier Detection (ATBOD) approach differentiates errors from events using an adaptive threshold that adjusts to real-time data patterns. Unlike existing methods that are used in literature, which lack automated model evolution and suffer from delays and high computational time, ATBOD enhances outlier detection sensitivity without increasing false alarms, which is crucial for efficient IoT sensor board operation. It also improves sensor board lifespan by discarding errors at the node level, preventing energy wastage from transmitting error data to the cloud. ATBOD outperforms existing algorithms, which are referenced for comparison, such as Enhanced Efficient Outlier Detection and Classification Approach (EEODCA), K Nearest Neighbor approximate outlier detection (KNN), and Modified Local Outlier Factor (LOF), in Error Detection Rate, Error False Positive Rate, and Energy Saving Ratio. These advancements represent a significant leap in performance, making ATBOD a superior method for real-time outlier detection in IoT sensor networks. [ABSTRACT FROM AUTHOR]

The gradual digitization of EU migration policies is turning external borders into AI-driven filters that limit access to fundamental rights for people from third countries according to risk indicators. An unshakeable confidence in the reliability of technological devices and their ability to predict the future behaviour of incoming foreigners is leading towards the datafication of EU external frontiers. What happens if the supposedly infallible algorithms are wrong? The article aims to understand the consequences of algorithmic errors on the lives of migrants, refugees and asylum seekers arriving in the European Union. This contribution investigates the socio-political implications of deploying data-driven solutions at the borders in an attempt to problematize the techno-solutionist approach of EU migratory policies and its fundamental rights impact on affected individuals.

Significant errors often arise when measuring streamflow during high flows and flood events. Such errors conflated by short records of observations may induce bias in the flood frequency estimates, leading to costly engineering design mistakes. This work illustrates how observational (measurement) errors affect the uncertainty of flood frequency estimation. The study used the Bulletin 17 C (US standard) method to estimate flood frequencies of historical peak flows modified to represent the measurement limitations. To perform the modifications, we explored, via Monte Carlo simulation, four hypothetical scenarios that mimic measurement errors, sample size limitations, and their combination. We used a multiplicative noise from a log-normal distribution to simulate the measurement errors and implemented a bootstrap approach to represent the sampling error. Then, we randomly selected M samples from the total N records of the observed peak flows of four gauging stations in Iowa in central USA. The observed data record ranges between 76 and 119 years for watersheds with drainage areas between 500 and 16,000 km2. According to the results, measurement errors lead to more significant differences than sampling limitations. The scenarios exhibited differences with median magnitudes of up to 50%, with some cases reaching differences up to 100% for return periods above 50 years. The results raise a red flag regarding flood frequency estimation that warrants looking for further research on observational errors. [ABSTRACT FROM AUTHOR]

• Medical errors continue to lead to significant mortality and morbidity in healthcare. • Recognition of errors by students is low, and implementing safety recognition into the curricula is imperative. • A "room of errors" study in a small midwestern university effectively increased first-semester students' abilities to recognize common medical errors. Errors in healthcare remain one of the leading causes of death in the United States each year. Nurses are an integral part of the healthcare team and spend the most direct-care time with patients, placing them at the forefront of error mitigation. This study aims to evaluate the beginning nursing students' awareness of safety issues at the bedside. Thirty-four students independently completed a "Room of Errors" simulation in week two of the first semester of a four-year baccalaureate nursing program. A repeat simulation was completed in week 13 with only 25 students participating, and a paired t-test was used to compare the results of those who completed both experiences. Although the average number of errors identified increased from 9.68 to 14.64 out of 42 (p=<0.001), the mean number of errors found per student remained low. While statistical significance is present, the number of errors not identified remains high. Continued research on best practices for implementing safety standards into nursing programs is necessary. [ABSTRACT FROM AUTHOR]

Background. Mistrust of doctors and the desire for compensation are driving a rise in malpractice litigation worldwide. Aim. To estimate the extent to which Italians view birth complications as malpractice in obstetric care, and how widespread this perception is. Method. WhatsApp® and Facebook® contacts of one of the authors were invited to respond to an online questionnaire. The answers of 265 Italian respondents were used to estimate how common the perception of obstetric staff errors is and how this perception spreads over time: the denigration curve. To test if the denigration curve is reliable, the curve has been plotted along with the trend of the rate of litigation in Italy. Results. Almost a 50% of respondents deemed that birth complications are due to obstetric staff errors. The likelihood of the perception that one has experienced a birth complication was 64.5%. The communication of obstetric staff error seemed low overall among the respondents. The denigration curve shape is almost coincident with the curve of claim rates in Italy, proving that it would be reliable. Conclusion. The respondents provided an estimate of the rate of birth complications that was higher than the real occurrence rate, and attributed these complications to obstetric staff errors. The denigration curve could predict whether and when there might be litigation related to any birth complications (both error related and non-error related). [ABSTRACT FROM AUTHOR]

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Microwave holographic measurement technology is a common method used in antenna measurement. This method has high measurement efficiency and high precision. To evaluate and enhance the antenna's performance, it is crucial to precisely determine the surface deformation. In this paper, the effects of feed offset error and scanning error on the antenna microwave holographic measurement results are investigated, and corresponding error compensation methods are proposed. The relationship between the influence of the error sources on the antenna gain loss and surface deformation accuracy is established. The reasons for holographic measurement errors, their characteristics, and their specific impact on system performance can be better understood. In order to improve the accuracy of the measurement, the compensation methods for the different measurement errors are given. They can provide the theoretical basis for maintaining and enhancing the performance of antenna system. [ABSTRACT FROM AUTHOR]

Background: Intracavernosal injection therapy (ICI) is a well-established therapeutic strategy for men with erectile dysfunction. Complications are often related to patient error when performong ICI. Aim: The objective of this study was to examine patient errors in an established patient training program for performing ICI and identify factors that could predict major errors. Methods: Patients enrolled in our ICI program are trained on technical aspects, and dose titration is begun. Patients are given explicit instructions during training, both verbally and in written form. Records were reviewed for men using ICI for ≥6 months. Multivariable analysis was used to define predictors of major errors. Outcomes: Errors were listed as minor (zero-response injection, penile bruising, expired medication) and major (errors potentially leading to priapism: dose self-titration, double injecting). Results: Overall, 1368 patients met the inclusion criteria and were included in the analysis. The mean patient age was 66 ± 22 (range 29-91) years. Regarding education, 41% of patients had graduate-level education, 48% had college education, and 11% high school education. Mean follow-up was 3.2 ± 7.6 (range 0.5-12) years. The agents used were trimix (62%), bimix (35%), papaverine (2%), and prostaglandin E1 monotherapy (1%). At least 1 error occurred during self-administration in 42% of patients during their time in the program. Errors included zero response to medication due to technical error (8% of patients), penile bruising (34%), use of an expired bottle (18%), self-titration (5%), and double injecting (4% of patients); 12% of men committed ≥1 error during their time in the program. On multivariable analysis, independent predictors of the occurrence of a major error included: young age, graduate-level education, and <12 months of injection use. Clinical implications: To the best of our knowledge, this is the first reported study to investigate ICI errors and risk factors. The identification of factors predictive of major errors allows for more tailored and intensive training in this subset of patients. Strengths and limitations: Strengths of this study include a large patient population (1386 men) with a considerable follow-up time. Additionally, the rigorous training, education, and monitoring of the participants, as well as the use of formal definitions, enhances the accuracy and reliability of the results. Despite the strengths of the study, recall bias may be a limitation concern. Conclusion: The majority of patients were error free, and the majority of the errors were minor in nature. Major errors occurred in <10% of patients. Younger age, graduate-level education, and less experience with ICI were independent predictors of major errors. [ABSTRACT FROM AUTHOR]

According to its own description, the biomedical meta-database PubMed exists "with the aim of improving health—both globally and personally." Unfortunately, PubMed contains an increasing amount of low-quality research that may detract from this goal. Currently, PubMed warns its users and protects itself from such problems with a disclaimer stating that the presence of any article, book, or document in PubMed does not imply an endorsement of, or concurrence with, its contents by the NLM, the National Institutes of Health (NIH), or the U.S. Federal Government. However, we are critical of a "disclaimer-only" stance and encourage PubMed to take further action against low-quality research being found and indexed in its database, and thus available for use. To address this problem, we offer two lines of reasoning to argue that PubMed should not function merely as a passive index of health-related research. Instead, we first argue that only trustworthy published research is able to further PubMed's goal of health improvement. Secondly, on the basis of surveys, we argue that researchers place a high level of trust in articles that are referenced in this meta-database. We cannot expect any one set of actors to ensure trustworthy content on PubMed, which requires collective responsibility among authors, peer reviewers, editors, and indexers alike. Instead, we propose a curation-based model that incorporates three mechanisms of collaborative content curation: open expert feedback on indexed content, journal auditing, and constant transparent reassessment of indexed entities. [ABSTRACT FROM AUTHOR]

AbstractObjectivesMethodsResultsConclusionsCognitive and affective factors have been implicated in verbal fluency (VF) performance in Parkinson’s disease (PD). This exploratory study aimed to investigate the relationships between cognitive and affective variables on traditional (“core”) and "process” (error and interval) scores of VF and elucidate unique information these scores may provide regarding mechanisms underlying VF.Sixty-two PD patients without dementia completed clinical neuropsychological examinations consisting of attention, processing speed, language, executive functioning, visuospatial, memory, and mood measures. Hierarchical regression and negative binomial regression analyses were used to evaluate relationships between outcome and predictor variables.Generativity results revealed that processing speed and working memory explained up to 34% of the variance of total letter fluency responses (p = <.001) and processing speed explained 24% of the variance for total semantic fluency (p = .003). For category switching generativity, only age predicted 20% of the variance (p = .01). Two executive functioning measures were negatively associated with error production over the duration (b = −.055, p = .028; b = −.062, p = .004) and final 45-second interval (b = −.072, p = .003; b = −.044, p = .033) of the category switching task. In the initial 15-second task interval, a positive predictive relationship between error production and indifference apathy (b = .616, p = .044) was demonstrated.Findings demonstrate the potential utility of "process” scores in detecting subtle cognitive impairment in Parkinson’s disease patients without dementia and tentatively evidence the role of indifference apathy in task initiation. [ABSTRACT FROM AUTHOR]

The study aims to examine the effectiveness of traditional methods for developing English as a Second Language (L2) writing. None of the studies has focused on L2 writing errors comparing the effectiveness of English language teaching methods in the classrooms. However, the current study investigates the efficacy of Grammar translation (GT) and communicative language teaching (CLT) methods in minimizing first language (L1) transfer errors in (L2) writing for 12th grade students in senior secondary public schools. The study included 180 participants randomly. The participants were divided into four groups: two experimental groups were exposed to GT and CLT methods, and two control groups were treated based on their regular curriculum in Hindi and English medium schools for three weeks. The data was extracted from participants over pre and post-test and analyzed quantitatively. The results of this study indicate students made more L1 transfer errors in Hindi Medium Schools in comparison to the English medium in L2 writing. Furthermore, students made a lesser mean of errors for the post-test rather than the pre-test. Moreover, the GT method performed better in Hindi and English medium classrooms than the CLT method in terms of minimizing L1 transfer errors after attending their pre-designed classes. The importance of the GT method for teaching and learning English in India is explored considering current literature on English teaching methods. [ABSTRACT FROM AUTHOR]

Every language has rules, laws, and systems that govern it. Usually, the more advanced generations establish them automatically. Then circumstances immediately change them for the next generation, and something similar to violating these rules and laws occurs, and the pronunciation of words or their meanings change. If the old system is immune, the change is considered modern. This study uses a descriptive and analytical approach by collecting data presented in the book by Dr. Atef Fadl Muhammad, then describing it, analyzing it, and responding to its errors. Some researchers go too far in this regard and consider what they deny about the change as a common mistake, and perhaps they need to catch the fact that this is true in Arabic because it is a direct standard and a dividing line for truth and error. This study proves that much of what researchers imagine (and the book above is an example of researchers' blogs) is not a common mistake but is true, supported by something that eliminates doubt. Whatever is true about the Arabs is accurate, and whatever contradicts their words is false. The words of the Arabs do not have the same level of power, but we do not judge anything that comes from them as false, regardless of the level of control. From this, we have seen many things recorded as common language mistakes, but they are true, and this is what this study is based on. This study monitors the frequency of researchers describing words and methods as common mistakes, discussing them, and whether all that is observed is an honest mistake or a belief contrary to the truth. This study concluded that these are simply beliefs and not facts, as many things recorded as false are aspects of what is true. [ABSTRACT FROM AUTHOR]

The gradual digitization of EU migration policies is turning external borders into AI-driven filters that limit access to fundamental rights for people from third countries according to risk indicators. An unshakeable confidence in the reliability of technological devices and their ability to predict the future behaviour of incoming foreigners is leading towards the datafication of EU external frontiers. What happens if the supposedly infallible algorithms are wrong? The article aims to understand the consequences of algorithmic errors on the lives of migrants, refugees and asylum seekers arriving in the European Union. This contribution investigates the socio-political implications of deploying data-driven solutions at the borders in an attempt to problematize the techno-solutionist approach of EU migratory policies and its fundamental rights impact on affected individuals. [ABSTRACT FROM AUTHOR]

The prospects are substantiated of using the air data system with one fixed flush-mounted receiver, built-in sensors of incoming flow parameters, and calculator on ultralight and small aircraft. Based on the previously developed analytical models for determining the output signals of this promising system, the study of the instrumental and methodic errors of its measurement channels was carried out. Analytical models are obtained for the instrumental and methodic errors of measurement channels of the air data system with one fixed flush-mounted receiver of incoming air flow parameters. [ABSTRACT FROM AUTHOR]

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Written corrective feedback has been extensively investigated with regard to its effectiveness, comparison of its different types, and perceptions about its effectiveness. However, few studies have addressed the types of errors receiving Corrective Feedback (CF) and still, much fewer have focused on formulaic errors as targets of CF. Thus, the current study compared formulaic and non-formulaic errors as targets of CF in learner writing. In addition, it examined the CF types provided for these errors. Finally, it sought the effect of a teacher awareness-raising program on teachers' attention to formulaic versus non-formulaic errors and on the CF types used to correct these errors. To achieve these purposes, eight English language teachers from four language institutes were selected through convenience sampling. First, during two sessions, the teachers asked the learners to write two compositions on two writing topics. Next, an awareness-raising program for teachers was run to raise the teacher's awareness level about formulaic and non-formulaic errors and CF types for correcting such errors. Then, the learners were asked to write two other compositions each in one session. The results showed that before the treatment, non-formulaic errors received considerably more CF than formulaic errors and that the percentage of direct CF was more than other CF types. In addition, the study showed that the awareness-raising program for teachers influenced their attention to formulaic errors. The findings of this study indicate that teachers need awareness-raising about the importance of formulaic sequences and the need to correct formulaic errors whenever possible. [ABSTRACT FROM AUTHOR]

An early warning method based on Session Initiation Protocol (SIP) concept for generator set electrical control abnormal response is proposed. The first is to clean the electrical data of the generator set by SIP. Using Supervisory Control and Data Acquisition (SCADA) and Generalized Linear Models (GLM) algorithm, a linear model is constructed to analyze the electrical control of generating units. Using the Autoregressive Integrated Moving Average Model (ARIMA), an abnormal response early warning model for electrical control of generating units is established. BP neural network is used to train the abnormal response data of the generator set electrical control. According to the current response data, the model prediction is realized, and the early warning of the abnormal response of the generator set electrical control is effectively realized. The simulation results show that the proposed method can effectively reduce the early‐warning error, false alarm rate, and early‐warning delay of generator electrical control abnormal response. [ABSTRACT FROM AUTHOR]

The study aims to investigate the quality of neural machine translation when translating research paper abstracts from English to Arabic. It performs an error analysis and provides an evaluation of the quality of neural machine translation (NMT) represented by Google Translate and Microsoft Translator. The research team selects 25 English research paper abstracts in education from well-known Scopus scientific journals issued in English speaking countries. These abstracts are then translated into Arabic using both Google Translate and Microsoft Translator. The error analysis is based on the typology of errors introduced by Multidimensional Quality Metrics (MQM). A professional evaluation is also conducted using the Scalar Quality Metric evaluation (SQM) as proposed in Freitag (2021). The study finds that the translation outputs of academic texts like abstracts of education research papers are still not up to standards when translating English educational research abstracts into Arabic. There are various types of translation errors. However, there is a slight difference in translation quality and number of errors in favor of Google Translate compared to Microsoft Translator. However, it is included that NMT system still requires a lot of training, and more Arabic corpora need to be built. [ABSTRACT FROM AUTHOR]

Background Aims Samples and Methods Results Conclusions Interest in the potential of learning from errors to benefit innovation and organizational and personal growth is currently increasing. In practice, individuals frequently do not appear to learn spontaneously from errors and setbacks without support. Based on prior work, this paper considers antecedents and consequences of adaptive responses to errors.Two experiments with undergraduate students aimed to identify the causal link between beliefs and maintained motivation and the adaptation of actions to the end of analysing and effectively correcting errors.In Study 1 (N = 195, 72% female, M = 20.7 years, SD = 3.0), we experimentally manipulated learners' beliefs around the importance of errors to learning, after which they completed a 50‐min learning session on research methods and statistics. In Study 2 (N = 67, 58% female, M = 21.8 years, SD = 3.99), we intertwined the manipulation more closely with the actual learning process by using prompts about adaptive responses to errors immediately after error feedback.In Study 1, those to whom we stressed the negative effects of errors showed significantly fewer adaptive action‐related responses to errors, less persistence, and less use of metacognitive strategies after errors. In Study 2, we found significant positive effects on the learners' persistence, their metacognitive control, and effort investment.Our results support and expand previous, mostly correlational, research findings on individuals' adaptive responses to errors. [ABSTRACT FROM AUTHOR]

Background Aims Sample Method Results and Conclusions Many people fear failure and making mistakes. This fear can be transmitted from parents to children, suggesting that parental communication regarding failures and setbacks may play a critical role in shaping a child's perception of mistakes.In this study, we investigated how everyday parent‐child conversations about setbacks influence children's fear of making mistakes.Drawing on the large pre‐birth Growing Up in New Zealand cohort, we focused on a sub‐sample of 231 mother‐child dyads who engaged in a recorded conversations about a "recent disappointment or setback" when the children were 8 years old.Conversations between mothers and children about the recent disappointments were coded to identify whether parents recognised or acknowledge their child's emotional response, if action plans were discussed, and the types of resources that the child could draw on. The children also completed a questionnaire about their global self‐worth and their fear of making mistakes.The discussion of clear action plans, in the absence of a discussion about collaborative resources, was found to be associated with an increased fear of making mistakes among children. Conversely, when mothers clearly acknowledged their child's emotions and discussed ways to work collaboratively with their child on future problems, there was a notable decrease in the child's fear of mistakes. However, it is noteworthy that many mothers in our study either minimally acknowledged or dismissed their child's emotions(40%), rarely discussed action plans (55%), or collaborative resources (79%)when discussing the recent setback. [ABSTRACT FROM AUTHOR]

The article presents the discussion on Error Analysis in second language learning, which studies learners' mistakes and their underlying reasons. Topics include explores various types of errors, including intralingual and interlingual errors, and highlights S.P. Corder's pioneering role in emphasizing the importance of errors in language learning and the paradigm shift in linguistics towards a more rationalistic view.