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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]

Background: Nursing professionals are key to providing safe care that improves patient outcomes. Hence, it is essential to focus on developing nurses' patient safety competencies and principles. Purpose: This review examined the effectiveness of educational interventions in developing patient safety knowledge, skills, behaviors, and attitudes in undergraduate nursing students. Methods: The search strategy aimed to identify published and unpublished studies in databases and grey literature. Studies were assessed using the Joanna Briggs Institute critical appraisal tools. Results: A total of 36 studies met the inclusion criteria. The teaching methods employed single or combined interventions and the educational interventions suggested either improvements in outcomes or no impact. Conclusion: The effectiveness of educational interventions to develop patient safety competencies in undergraduate nursing students, either as a single or combined strategy, was mixed. Further research is needed to provide more robust evidence on which teaching method for patient safety is most effective. [ABSTRACT FROM AUTHOR]

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Underground topographic bases are of particular importance in the design and management of underground mining works. They can be dependent on the geodetic and topographic system on the surface, but they can also be independent in relation to a particular reference system. In the case of dependent topographic bases, it is preferable, from the point of view of the precisions required for the drawing of mining works in safe conditions, that they are related to two points known by their x, y (fixed) coordinates. The quantities measured in such situations are angles and distances. Measurement errors are transmitted to the determined quantities and consequently it is necessary to analyze the factors with which such a process can be evaluated. The necessary scientific approach is presented below. [ABSTRACT FROM AUTHOR]

Monitoring deformations in mining pillars in salt mines is crucial for detecting spalling, cracks, and distortions caused by internal pressures, with the aim of preventing mining accidents and maintaining structural integrity. At Salina Ocna Dej, annual measurements have not utilized drone technology, which was recently introduced in Romania. The measurements conducted with the DJI Phantom 4 Pro Plus drone in 2020 and 2024 provided essential data on changes in the mining pillar. In 2020, difficulties caused by air currents slightly affected the measurements, but by 2024, improved conditions allowed for more accurate results. The horizontal sections taken at various elevations revealed significant spalling and distortions, particularly on the eastern and western sides, with substantial rupture in the northwest corner and displacements on the northern side. Comparing the data from the two measurement sets showed a significant difference in precision, highlighting the need for regular inspections to prevent premature erosion and avoid accidents. [ABSTRACT FROM AUTHOR]

Low-cost air quality sensors are a promising supplement to current reference methods for air quality monitoring but can suffer from issues that affect their measurement quality. Interferences from environmental conditions such as temperature, humidity, cross-sensitivities with other gases and a low signal-to-noise ratio make them difficult to use in air quality monitoring without significant time investment in calibrating and correcting their output. Many studies have approached these problems utilising a variety of techniques to correct for these biases. Some use physical methods, removing the variability in environmental conditions, whereas most adopt software corrections. However, these approaches are often not standardised, varying in study duration, measurement frequency, averaging period, average concentration of the target pollutant and the biases that are corrected. Some go further and include features with no direct connection to the measurement such as the level of traffic nearby, converting the initial measurement into a modelled value. Though overall trends in performance can be derived when aggregating the results from multiple studies, they do not always match observations from individual studies, a phenomenon observed across many different academic fields and known as "Simpson's Paradox". The preference of performance metrics which utilise the square of the error, such as root mean squared error (RMSE) and r2, over ones which use the absolute error, such as mean absolute error (MAE), makes comparing results between models and studies difficult. Ultimately, comparisons between studies are either difficult or unwise depending on the metrics used, and this literature review recommends that efforts are made to standardise the reporting of calibration and correction studies. By utilising metrics which do not use the square of the error (e.g., MAE), models can be more easily compared within and between studies. By not only reporting the raw error but also the error normalised by multiple factors (including the reference mean and reference absolute deviation), the variabilities induced by environmental factors such as proximity to pollution sources can be minimised. [ABSTRACT FROM AUTHOR]

• Despite prevalent role of human factors, police-reported pedestrian-involved crash data often have gaps in crash details. • The Pedestrian and Bicycle Crash Data Tool (PBCAT) provides an inclusive high-quality database capturing sequence of events. • Unobserved factors (e.g., pedestrian conspicuity or driver riskiness) can have significant influence on pedestrian injuries. • Ordered probit model and its finite mixture version are applied to address unobserved heterogeneity in pedestrian injuries. • Results suggest sufficient heterogeneity in pedestrian injuries and parameters of related factors across two latent groups. Introduction: Human factors are often major contributors to pedestrian crashes. However, police-reported pedestrian-involved crash data often have gaps in crash details. Overcoming this limitation, the Pedestrian and Bicycle Crash Data Tool (PBCAT) provides a more comprehensive high-quality database capturing the sequence of events. Methods: In addition to human and roadway environmental factors, there could be unobserved factors (e.g., pedestrian conspicuity, impact speed, or riskiness by a driver) that could be either unavailable or not used in the analysis; however, these unobserved factors could have a significant influence on pedestrian injuries. This study applies finite mixture models to address unobserved heterogeneity in pedestrian injuries which is usually overlooked. As a result, the associations of one or more of the observed factors with pedestrian injuries across different latent (unobserved) classes can be different. Results: Harnessing this unique database for North Carolina reveals that in most (95%) of the crashes (N=24,886) occurring between 2009 and 2019, pedestrians were either killed or injured. Risky behaviors by drivers and pedestrians contributed to 7.91% and 50.59% of these crashes, respectively. Recognition errors (e.g., dash or dart-out) and violations (e.g., failure to yield) by pedestrians contributed to 22.08% and 28.58% of crashes, respectively. Recognition errors and violations by drivers contributed to only 2.12% and 3.11% of crashes respectively each of which is significantly lower than those by pedestrians. Results of the ordered Probit model indicate that the chance of pedestrian fatality is significantly higher if a pedestrian makes recognition errors and violations, a driver makes performance errors, and either the pedestrian or driver is impaired. Conclusions and practical implications: The finite mixture model shows that pedestrians belong to two latent groups across which there is significant heterogeneity in pedestrian injuries and variations in the associations of observed factors with pedestrian injuries. The practical implications are discussed in the paper. [ABSTRACT FROM AUTHOR]

Background: Manual objective assessment of skill and errors in minimally invasive surgery have been validated with correlation to surgical expertise and patient outcomes. However, assessment and error annotation can be subjective and are time-consuming processes, often precluding their use. Recent years have seen the development of artificial intelligence models to work towards automating the process to allow reduction of errors and truly objective assessment. This study aimed to validate surgical skill rating and error annotations in suturing gestures to inform the development and evaluation of AI models. Methods: SAR-RARP50 open data set was blindly, independently annotated at the gesture level in Robotic-Assisted Radical Prostatectomy (RARP) suturing. Manual objective assessment tools and error annotation methodology, Objective Clinical Human Reliability Analysis (OCHRA), were used as ground truth to train and test vision-based deep learning methods to estimate skill and errors. Analysis included descriptive statistics plus tool validity and reliability. Results: Fifty-four RARP videos (266 min) were analysed. Strong/excellent inter-rater reliability (range r = 0.70–0.89, p < 0.001) and very strong correlation (r = 0.92, p < 0.001) between objective assessment tools was demonstrated. Skill estimation of OSATS and M-GEARS had a Spearman's Correlation Coefficient 0.37 and 0.36, respectively, with normalised mean absolute error representing a prediction error of 17.92% (inverted "accuracy" 82.08%) and 20.6% (inverted "accuracy" 79.4%) respectively. The best performing models in error prediction achieved mean absolute precision of 37.14%, area under the curve 65.10% and Macro-F1 58.97%. Conclusions: This is the first study to employ detailed error detection methodology and deep learning models within real robotic surgical video. This benchmark evaluation of AI models sets a foundation and promising approach for future advancements in automated technical skill assessment. [ABSTRACT FROM AUTHOR]

The concept of the "lumberjack effect" addresses important concerns regarding the role of automation (and impact of automation failure) in complex engineering systems such as aviation, power plant control rooms, and others. Conflicts between "narrow" and "broad" definitions of automation failures uncover logical inconsistencies regarding human-automation interactions processes in maintaining system performance. However, the "lumberjack effect" debate obscures essential considerations that automation tools exist as components in complex systems with multiple levels of abstraction hierarchies (Rasmussen). A sole focus on automation failure conflates the automation components with the overall system function. Elaborating operating conditions associated with human-automation interaction conflicts and failures supports an improved approach to failure mode and effects analysis techniques for improving system safety. Detecting system failure modes and operating conditions, poorly quantified in other risk priority determinations, are important contributions at the overall system analysis level, not as an isolated emphasis on the automation itself. [ABSTRACT FROM AUTHOR]

The implementation of automation in many domains has led to well-documented accidents and incidents, resulting from reduced situation awareness that occurs when operators are out-of-loop (OOTL), automation confusion, and automation interaction difficulties. Wickens coined the term lumberjack effect to summarize the finding that while automation works well most of the time in typical or normal situations, the performance problems that occur in novel or unexpected situations also increase the likelihood of catastrophic errors. Skraaning and Jamieson have criticized the lumberjack effect due to a study in which they failed to find it. I show that this claim is unsupported due to a number of methodological limitations in their study and conceptual errors. They also provide a model of automation failure that fails to clearly delineate the many barriers to accidents that are available, instead emphasizing the ways in which automation can fail technically and different types of human error. An alternate automation failure model is presented that provides a broader socio-technical perspective emphasizing the design features, processes, capabilities, organizational policies, and training that support people in improving system safety when automation fails. [ABSTRACT FROM AUTHOR]

This study aims to examine the errors that students made when using the APOS (Action-Process-Object-Schema) theory to create their knowledge of partial derivatives. Design/Methodology/Approach: The method used was descriptive-qualitative including data collection through tests, interviews and documentation. Triangulation techniques were used in data validity procedures to ensure the reliability of the data. Findings: The results showed that high, medium and low ability students had an understanding of the action, process and object stages in determining the partial derivatives. However, medium-ability students experienced a deficiency in understanding the object stage while low-ability students showed shortcomings in understanding the process and object stages. Several mistakes were made in determining partial derivatives of algebraic and trigonometric functions including incorrectly selecting and using the procedures of addition, subtraction, multiplication, division and chain rules as well as writing conclusions. Conclusion: The dominant types of errors in determining partial derivatives were executive (ExE) and process skill (PE). Recommendations: Future studies were expected to modify the genetic decomposition of partial derivatives and expand the classification of errors in data analysis. [ABSTRACT FROM AUTHOR]

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]

Background. Attack efficiency in the game of volleyball is of paramount importance in winning competitions. Objectives. The study aimed to analyse the differences in attack efficiency between teams of varying value levels, according to their position in the ranking. Materials and methods. All 12 teams participating in the men's national first league championship were analysed using the Data Volley software. The attack parameters were compared between teams in the first half of the ranking vs teams in the second half. Another comparison was performed for 3 value levels of the top teams (top, middle, and low). Results. The Mann-Whitney U test (used to assess the differences between teams in the first half vs. teams in the second half of the ranking) indicates Z values associated with statistically significant thresholds (p < 0.05) for most of the attack indicators, except Blocked but recovered% (p > 0.05). The situation is similar also for the Kruskal-Wallis test, where χ² values indicate significant differences between the three levels of the teams for most of the parameters, except Blocked but recovered%. Conclusions. The findings reveal the higher values of attack efficiency and its parameters for the teams placed in the top positions of the ranking. The teams in the first half of the ranking have better percentage values on the executions associated with Winning% and Positive%. The attacking players of these teams also demonstrate lower percentage scores on the executions associated with Error%, Blocked attack% and Poor%, thus committing fewer mistakes. The situation is similar when comparing the top vs low and middle vs low pairs, where only for Blocked but recovered% no significant differences have been identified. These results support the need to focus on making the volley attack more efficient as a decisive factor in competitive success. [ABSTRACT FROM AUTHOR]

This paper discusses the replacement of manual processes and the way in which the possibility of human errors in plant care is eliminated. The benefits that the intelligent system brings are the reduction of human errors, the reduction of time for plant care such as watering the flowers, checking the humidity of the plants, moving them to a brighter place. [ABSTRACT FROM AUTHOR]

The study investigates the types and sources of errors that English as a Foreign Language (EFL) learners at Albanian High School in the Republic of North Macedonia make in their writing due to firstlanguage interference. The study used a mixed-method research design, with a structured questionnaire and a writing task. As revealed by the findings of this study, the most prevalent types of errors were grammatical and lexical, with syntactic errors being less common. The leading causes of these errors were found to be the transfer of first-language structures, a lack of knowledge of English grammar, incorrect translation of single words, and a misuse of English grammar. The findings of the study can be utilized to develop instructional materials and teaching strategies that target specific varieties of errors caused by firstlanguage interference. Additionally, the findings of the study can contribute to a better understanding of how learners learn a foreign language and the cognitive processes involved in language learning. The findings can be integrated to help develop instructional materials that target specific categories of errors caused by first-language interference. Finally, the study is envisaged to contribute to a better understanding of first-language interference in EFL writing and to inform the development of effective teaching practices and materials that address this challenge for EFL learners. [ABSTRACT FROM AUTHOR]

Constructing the correct mathematical model is the main key to solving mathematical modeling problems, but students most often fail at this process. Understanding the failure characteristics of constructing a model can be used to correct student errors. This study aims to discuss the characteristics of failures in constructing mathematical models carried out by the students in algebra subject matter. This study used an exploratory descriptive design approach and involves 41 mathematics education students to solve mathematical modeling test questions. The results showed four types of failure characteristics in constructing the model. First, misunderstand type is characterized by disability in capturing important facts from the problem and compiling a model only procedurally. Second, misconnection type is marked by incompetence in making connections between important facts. Third, missspeculation type is noted by the incapacity in making speculations about important facts. Fourth, misslogic type is signed by the inability to use logical facts. Therefore, lecturers or teachers must be more careful to improve the teaching process to be more comprehensive and carry out appropriate scaffolding to overcome the students' difficulties in solving mathematical modeling problems, especially in constructing mathematical models. The appearance of each error indicates the need for certain repairs. Error correction should be handled based on the characteristics that arise. [ABSTRACT FROM AUTHOR]

Le terme d'évènement recouvre un large éventail de situations concrètes en oncologie radiothérapie, de l'effet secondaire particulièrement intense en lien avec l'irradiation à la possibilité d'une erreur technique ou humaine. Si les démarches qualité font désormais partie intégrante du fonctionnement des services d'oncologie radiothérapie pour l'analyse et la prévention de ces évènements, leur survenue au cours d'une irradiation conserve un impact significatif sur les personnes soignées et leur vécu du parcours de soin, mais aussi sur les professionnels de santé. Ces impacts pratiques, émotionnels et symboliques sont d'autant plus importants quand l'évènement survient dans les suites d'une erreur. La démarche éthique comprend alors trois temps essentiels : reconnaître l'évènement en tant que tel, informer les personnes impliquées de l'évènement et enfin créer les conditions favorables au maintien du soin. Chacune de ses étapes est marquée d'enjeux et de questionnements spécifiques nécessitant une approche éthique complexe amenant à considérer constamment la conciliation de perceptives parfois divergentes entre personnes soignées et professionnels de santé. La survenue d'un évènement peut aussi déboucher sur une authentique crise de confiance aux multiples dimensions que les professionnels de santé auront aussi à accompagner. Enfin, la survenue d'un évènement interroge notre responsabilité vis-à-vis des personnes que nous prenons en soin, mais aussi notre idéal de maîtrise. Critiquer notre culture de la performance, repenser profondément notre approche de l'évènement et de l'erreur pour y voir aussi une opportunité d'évolution positive sont autant de pistes à déployer au sein de nos unités de soin. The term "event" covers a wide range of concrete situations in radiation oncology, from particularly intense radiation-related side effects to the possibility of technical or human error. Although quality procedures are an integral part of radiotherapy oncology department operations ensuring the analysis and prevention of such events, their occurrence during radiation treatment still has a significant impact on patients and their experience of the treatment process, as well as on health professionals. These practical, emotional and symbolic impacts are all the greater when the event occurs in the aftermath of an error. The ethical approach therefore comprises three essential stages: recognizing the event as such, informing those involved of the event and, finally, creating conditions for the continuation of care. Each of these stages is marked by specific issues and questions, requiring a complex ethical approach that constantly involves reconciling the possible divergent perceptions of patients and health professionals. The occurrence of an event can also lead to a genuine crisis of confidence with multiple dimensions, which health professionals will also have to face and to support. Finally, the occurrence of an event calls into question not only our responsibility towards patients, but also our ideal of control. We need to criticize our culture of performance, rethink our approach to events and errors, and see them also as opportunities for positive change. [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]

Introduction: This article aimed at digging deep into distractors used for mathematics multiple-choice items. The quality of distractors may be more important than their number and the stem in a multiple-choice question. Little attention is given to this aspect of item writing especially, mathematics multiple-choice questions. This article provides an engaging but succinct literature review on the development of plausible distractors for mathematics multiple choice items. Methods: A literature review was conducted on developing effective distractors for mathematics tests. The review explored potential strategies for generating distractors that effectively assess students' understanding and problem-solving skills in mathematics. Results: Alternative sources of distractors other than students' misconceptions are provided to aid the development of plausible distractors for mathematics multiple-choice items. Discussion: Practical guidelines for judging distractors fit for mathematics questions are provided to help teachers improve their item writing skills based on literature and experience as a mathematics teacher. Common pitfalls in distractor development were identified to enable mathematics teachers to have a clear path for their work. Limitations: This article focused on the development of plausible distractors specifically for mathematics multiple choice questions. Conclusions: Test constructors must ensure aligning the distractors with the objectives of each lesson in order to make the distractors relevant to the demands of the item. [ABSTRACT FROM AUTHOR]

This study answers the following research questions: 1) What types of mathematical errors do future teachers identify when they reflect on their practice? and 2) Which levels of development of the didactic suitability assessment competence for the "errors" component can be inferred when they reflect on their practice? To answer these questions, we explain the Didactic Suitability Criteria construct and describe the associated training cycle structure in the theoretical and methodological framework sections. We followed a qualitative research methodology that mainly consists of thematic analysis. The study conducted allows finding inductive categories of types of mathematical errors, such as error in the task instructions, error of proposition, procedural error, error in the representation, error in the definition and error in the argument. It also enables establishing levels of development of the didactic suitability assessment competence of future teachers for the "errors" component. The main conclusion of this research is the importance of the context to decide what a mathematical error is. The need to further examine the notion of mathematical error in the training of future mathematics teachers is also stressed. Another conclusion is the development of a rubric that allows for more accurate and deeper reflections of future teachers on the errors made. [ABSTRACT FROM AUTHOR]

Industry 5.0 is defined by the connection between technology and human skills, enhancing the field of accounting through the integration of artificial intelligence (AI), automation, and advanced data analytics solutions. In this new industrial stage, the focus is not only on automation but also on supporting human activity through the personalization of processes and technology [14]. In this context, accounting professionals are challenged to expand their traditional roles, becoming involved in predictive analysis, strategic advisory, and risk assessment, supported by digital tools. A core element of Industry 5.0 in accounting is the use of AI to simplify complex operations. Through these technologies, financial data is processed quickly, enabling anomaly detection and improving the accuracy of reports[8]. For automating routine tasks, robots and software are used, such as account reconciliation, invoice management, and transaction auditing, freeing up human resources for higher-value activities. In this way, AI helps increase efficiency and reduce errors in accounting processes [10]. The collaboration between humans and machines, characteristic of Industry 5.0, opens new perspectives for accounting, supporting in-depth analysis and decision-making based on precise information. Accountants can use advanced digital platforms to assess risks, optimize cost structures, and anticipate market fluctuations, relying on data and advanced analytical models [6].

Shu-Wah Ng,1 Maggie PK Lit,2 Agnes YK Lai3 1Division of Respiratory Medicine, Department of Medicine and Geriatrics, United Christian Hospital, Hong Kong Special Administrative Region, People’s Republic of China; 2Division of Respiratory Medicine, Department of Medicine, Queen Elizabeth Hospital, Hong Kong Special Administrative Region, People’s Republic of China; 3School of Nursing and Health Sciences Hong Kong Metropolitan University, Hong Kong Special Administrative Region, People’s Republic of ChinaCorrespondence: Agnes YK Lai, School of Nursing and Health Sciences, 11th Floor, Jockey Club Institute of Healthcare, Hong Kong Metropolitan University, 1 Sheung Shing Street, Homantin, Kowloon, Hong Kong, Tel +852-3970-2917, Email ayklai@hkmu.edu.hkBackground: Persistently high rates of inhaler errors and poor adherence among Chronic Obstructive Pulmonary Disease (COPD) patients contribute to ineffective symptomatic control, high care burdens, and increased healthcare resource utilization.Objective: This study aimed to report (i) nurses-identified common problems and errors of inhaler use in COPD patients, (ii) nurses’ attitudes, practices, training needs and required support in inhaler education.Methods: An online questionnaire survey was conducted with nurses working in Hong Kong from May to June 2023 using an exponential, non-discriminative snowball sampling strategy.Results: Of 156 nurses (67.3% female, 41% aged 40 or above), 37.2% and 62.8% of them had more than 10 years of experience in medical units and received respiratory-related specialist training, respectively. About 86% and 82% perceived that their patients did not have adequate basic knowledge and had incorrect use of their inhaled medications. High rates of inhaler use errors were observed by nurses across all phases: preparation (50%– 92%), pre-inhalation (45%– 89%), inhalation (69%– 89%), and aftercare (66%– 85%). Nurses with ≥ 10 years of working experience in medical units or specialist training showed significantly more confidence in educating on inhaler use, engaging in more discussion with patients about inhaler use, and assessing patient inhaler use techniques more frequently than those with less experience or no respiratory-related specialist training with small effect size (Cohens’d: 0.26– 0.33).Conclusion: Inhaler use errors were common issues among COPD patients in Hong Kong. Enhanced professional training and support in inhaler education could improve nurses’ confidence and practices in conducting patient education on inhaler use.Keywords: chronic obstructive pulmonary disease, nurses’ experience, inhaler, errors, clinical experience

Background. Attack efficiency in the game of volleyball is of paramount importance in winning competitions. Objectives. The study aimed to analyse the differences in attack efficiency between teams of varying value levels, according to their position in the ranking. Materials and methods. All 12 teams participating in the men’s national first league championship were analysed using the Data Volley software. The attack parameters were compared between teams in the first half of the ranking vs teams in the second half. Another comparison was performed for 3 value levels of the top teams (top, middle, and low). Results. The Mann-Whitney U test (used to assess the differences between teams in the first half vs. teams in the second half of the ranking) indicates Z values associated with statistically significant thresholds (p < 0.05) for most of the attack indicators, except Blocked but recovered% (p > 0.05). The situation is similar also for the Kruskal-Wallis test, where χ² values indicate significant differences between the three levels of the teams for most of the parameters, except Blocked but recovered%. Conclusions. The findings reveal the higher values of attack efficiency and its parameters for the teams placed in the top positions of the ranking. The teams in the first half of the ranking have better percentage values on the executions associated with Winning% and Positive%. The attacking players of these teams also demonstrate lower percentage scores on the executions associated with Error%, Blocked attack% and Poor%, thus committing fewer mistakes. The situation is similar when comparing the top vs low and middle vs low pairs, where only for Blocked but recovered% no significant differences have been identified. These results support the need to focus on making the volley attack more efficient as a decisive factor in competitive success.

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.

Trustworthy literature is an essential part of knowledge, evidence-based information, and science. However, publications can contain mistakes or have results from unreliable research, which may compromise their integrity. In this review, we discuss publication integrity, with a focus on our field of biomedicine, and how it could be improved. In our experience, compromised publication integrity is frequently poorly handled, and we, and others, have reported that responses to publication integrity concerns can be inefficient, inconsistent, slow, opaque, and incomplete. Checklists and tools are now available to assist in the assessment of publication integrity, but systemic changes are needed. However, this requires many of the key parties involved (journals, publishers, institutions, academic societies, and regulators) to acknowledge and engage with the problem. There is little evidence of a willingness to do this. We conclude that it has been recognised for many years that the system for dealing with publication integrity is broken, but currently, there appears little interest in trying to improve it. [ABSTRACT FROM AUTHOR]

Objective: to study the causes of fatal outcomes in patients with generalized forms of meningococcal infection (GFMI). Materials and methods: a retrospective analysis of case histories and pathological examination results of 10 children with GFMI who died in the intensive care unit of the infectious diseases hospital of the Krasnoyarsk City Children's Clinical Hospital No. 1 in Krasnoyarsk for the period 2012-2022 is presented. Results. The most important risk factor for the development of an unfavorable outcome of GFMI is age; 90% of the deaths were children in the first three years of life. The leading clinical form of MI was meningococcemia (80 ± 12.6%) with the development of septic shock (80 ± 12.6%), disseminated intravascular coagulation (60 ± 15.5%), acute adrenal insufficiency (90 ± 9.5%). Despite the timely request of parents for medical help, only 30 ± 14.5% (4/10) of patients were hospitalized in the hospital after the first visit, most of the children were hospitalized in the hospital after 3—4 calls with an erroneous diagnosis (50 ± 15.8%), underestimation of the severity of the condition and the degree of septic shock, without providing emergency medical care at the prehospital stage (60 ± 15.5%), which contributed to the development of a tragic outcome.

The aim of this research is to analyze errors in writing Arabic vocabulary of students at the STKIP Muhammadiyah Kalabahi Center for Foreign Language Studies (PSBA) for the 2023-2024 academic year. Using the qualitative descriptive analysis method. Meanwhile, the data collection technique in this research is observation, namely direct observation, interview activities are carried out with PSBA students and documentation is the process of collecting data and processing data in the form of student worksheet results. Meanwhile, data analysis in this research is using the Corner data analysis model, namely 1) determining the sample size and data media. The researcher took sample data, namely 2023/2024 PSBA Tapel students using written vocabulary data as a medium in Arabic. 2) identify errors. Researchers collected PSBA students' vocabulary writing errors from the final semester exam results. 3) classify errors. Researchers classified vocabulary writing errors written by PSBA students. 4) evaluate errors. In this study, researchers gave a serious assessment of every PSBA student's vocabulary writing errors. The results of this research were that errors were found from 4 aspects, namely: 1) errors based on adding letters. 2) errors based on removing some letters. 3) errors based on omission of characters (punctuation). 4) errors based on letter errors. The cause of these errors is that students do not pay attention to writing vocabulary properly when memorizing, so that it affects when writing and students do not practice writing vocabulary continuously. Analysis of each error has been presented, so that improvement or evaluation efforts emerge to minimize these errors, namely 1) choosing a learning method. 2) providing examples related to writing rules. 3) Practice repeatedly (tadribat). [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]

Copyright of Duzce University Journal of Science & Technology is the property of Duzce University Journal of Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Stable operation of large industrial equipment with rotating components depends on constant monitoring to ensure correct geometric shape. Aerial laser scanning is considered in relation to existing methods of shape measurement. Sample results of field research on shape monitoring are presented for a rotary furnace. [ABSTRACT FROM AUTHOR]

This article assesses Nietzsche's engagement with the sublime in Dawn to shed light on an aspect thereof that has so far been overlooked: Nietzsche's deployment of the sublime as a philosophical framework for coming to terms with epistemic limits and transcendental errors. By engaging with the sublime both descriptively and methodologically, Nietzsche promotes an awareness of cognitive limits that fosters, instead of impeding, the pursuit of knowledge and the accomplishment of philosophical endeavors. While complicating the minimal existing literature on the topic, this article highlights Nietzsche's philosophically unique use of the sublime in navigating a characteristically post-Kantian epistemic issue (the awareness of epistemic partiality and inadequacy) and in mitigating an illusory faith in reason. [ABSTRACT FROM AUTHOR]

This essay gives a literary account of "overthinking" women in the autofictional forms of the Brexlit era. In Patricia Lockwood's No One Is Talking About This and Helen Macdonald's H is for Hawk the protagonists both avatars for the authors frequently find themselves having imperfect or even failed political conversations with strangers and then ruminating on their sense of their own mistakes. But rather than dismissing their sometimes cringe-inducing self-indictments this essay suggests that overthinking as a literary mode is a reparative experiment in counterfactual thought. [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]

Tintin comics, as one of the most popular comics of the 20th century in the world, has been translated and read by different age groups in Iran as well. Translating comics is a difficult task. The purpose of the present study is to assess the quality of translations of seven series of this collection, translated by Masume Razapour, from both verbal and nonverbal aspects considering four challenging areas of idiom, slang, onomatopoeia, and equivalence. Thus, English and Persian texts were compared with each other. To examine the verbal part Waddington’s (2001) type A model and for the nonverbal part, Kress and van Luween’s (2006) model have been used for examining the three metameanings of multimodal texts and determining the violation of imagetext relations. The result of the study shows that the translator acted the most successfully in The Black Island (7.45) and the least successfully in The Broken Ear (-1.36). The changes in metameanings have happened in compositional meaning due to changes in font type/size or discontinuities of color. There are some cases of violation of image-text relation due to cultural differences and differences in writing direction. Examining the two verbal and non-verbal parts shows that the translator in a few cases of domesticating the texts due to cultural differences has caused some violations in meaning and image-text relation. The results of study can be used in teaching translation, informing translators about the more challenging areas of comic translation, and considerate use of localization to save image-text relations. [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]

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]

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]