Severe Mistakes Research Articles

An ISM-MICMAC approach for analyzing the relationship between blockchain adoption criteria in a pharmaceutical supply chain: Tunisian case

Purpose In the context of digitalizing the supply chain of different sectors, the blockchain technology (BT) is emerged and becomes one of the most interesting and debated research topics. A few years ago, this technology was implemented for the first time in the financial sector, which is currently extended to be used in many other areas, mainly the health-care sector. The success of this technology stems from its ability to enhance the performance, security, consistency of sharing medical data within the whole system and the analysis of medical records. Technically, the BT is defined as a decentralized digital ledger that records transactions between the stakeholders in a supply chain. Thus, they could gain better control and find severe mistakes and the unsafe ones in the medical field. The purpose of this paper is to address a preliminary study of the BT adoption in a real pharmaceutical supply chain (PSC) of the Tunisian case. Design/methodology/approach Indeed, the authors propose an interpretive structural modeling (ISM) combined with the cross-impact matrix multiplication applied to classification (MICMAC) analysis. This methodology is known as an effective one used to identify the criteria that influence the implementation of the BT, analyze the relationships between them and delighting the most impactful ones. Findings The readiness criteria for the adoption of the BT for the considered system are identified which are 10 ones and the structural relationship between them is uncovered through many interviews with experts. Hence, the found results define the most crucial criteria that should be valorized amongst the other criteria. Originality/value The originality of this study stems from its theoretical and practical relevance regarding the potential of the pharmaceutical system and the importance of the integration of new technologies as the BT. The ISM-MICMAC approach seems to be very performant for such preliminary study of the BT adoption in the Tunisian pharmaceutical system.

Do Mistakes Provoke New Mistakes? Evidence From Chess

We investigate how the mistakes of professional chess players affect the quality of their further moves in the same game. Using a database of games played by top chess players, Stockfish chess engine evaluations, and an ordered probit regression analysis, we found clear evidence that small inaccuracies lead to less accurate play in future, while more severe mistakes have a weaker effect on the quality of play in the same direction.

A quantitative framework for security assurance evaluation and selection of cloud services: a case study

Due to the high adoption of cloud services, the protection of data and information is critical. Cloud service customers (CSCs) need help to obtain the authoritative assurances required for the cloud services and negotiate the cloud service contract based on the terms and conditions set by cloud service providers (CSPs). Several standards and guidelines are available for assessing cloud security. However, most of these standards and guidelines are complex and time-consuming to select a service or make an informed decision for CSCs. Moreover, the existing methods are insufficient to solve this problem because they are process-oriented, neglect the importance of stakeholder requirements, and lack a comprehensive and rigid analytic method that can aid decision-makers in making the right decisions. In this paper, we developed two evaluation techniques: (i) a quantitative cloud security assurance method to assess the security level of cloud services by measuring the critical security properties and (ii) a novel and rigid categorical analytical method that enables CSPs to identify the major problems in the system and assess how much gain can be achieved by solving each of them. The cloud security assurance method is based on two important metrics: security requirement and vulnerability. It assists CSCs in avoiding severe mistakes and making informed decisions while selecting a cloud service. Moreover, these methods support CSPs in improving the security level of cloud services and meet customer requirements. The proposed methods are validated using different case scenarios on a private cloud platform.

BUILDING AN IDEAL INDUSTRIAL RELATIONSHIP IN INDONESIA POST-DECISION OF THE CONSTITUTIONAL COURT

The terms of termination of employment due to gross misconduct by workers have been canceled. The ruler can no longer perform unilateral termination of employment. The determination of gross misconduct awaits the verdict of a court that has the force of law remains. The purpose of the study was to review the decision of the working relationship of gross misconduct after the decision of the Constitutional Court and to examine the working relationship between workers and the ideal ruler in the future. This study uses a philosophical approach, which is to examine the working relationships of workers and ideal rulers in the future. The results of this study showed that termination of employment among others because workers make severe mistakes that have the effect of not getting severance money and without any prior warning. The provision has been overturned by the Constitutional Court. Workers who commit gross misconduct must be proven first through criminal proceedings and there is a court ruling that has a fixed legal force. The pattern of worker and employer relationships is expected to create a mutually beneficial working relationship between the two parties in the future. The employment relationship of workers and employers is supposed to be a partnership relationship so that there is no discrimination, intimidation, and exploitation. Industrial relations ideally refers to Pancasila. With the source of Pancasila as a philosophical basis, and the 1945 Constitution all the rules of law governing Industrial Relations as its implementation. With this relationship, it is expected that the nuances of worker and employer relationships in the future can be harmonious, there is a positive syntactic relationship.

Do Public-Private Partnerships Still Have a Future?

Public Private Partnerships (PPP) are under discussion because of the mixed results achieved and the deteriorated trust between public and private actors. However, abandoning PPP could represent a severe mistake in public policy. Based on the recent Italian experience, the authors argue that a new approach to PPP, based on the ESG/SDGs and Impact Investing agenda, could represent an opportunity, both for the public and the private sectors, to contribute to solving wicked problems while generating societal value. This Commentary paves the way for a reflection on this renewed approach to PPP and the need for a new set of skills in the public and private sectors to support the transition.

A deep neural network based framework for restoring the damaged persian pottery via digital inpainting

Conservation of the historical artworks involves carefully planning interventions to prolong the material, historical, and design integrity of humanity's-built heritage. Among which, restoration of the destroyed parts of the artworks via inpainting is one of the most critical stages in the restorative conservation.Indeed, one of the significant assets of any art-historical work is its aesthetic aspects. However, usually due to the visual complexity and the diversity of the motifs, the number of patterns that a restorer artist can have in mind when repairing them, are limited. Also, the inpainting process of such artworks might be very slow and prone to errors; a slight error can cause severe mistakes for the aesthetic aspects of the artifact. Therefore, the need to develop an intelligent system to provide an image of the refurbished artifact before to the restoration operation, is undeniable. Motivated by the idea that the computer-vision-based image inpainting process could be an efficient solution for this purpose, in this paper, for the first time, we propose a framework that employs a deep artificial neural network-based approach to inpaint the images of Persian pottery for restoring their damaged parts. The framework can repair irregular structures that usually exist in Persian pottery and inpaints relatively large missing parts. Besides, the restored parts were seamlessly integrated with the rest of the image without the need for any further postprocessing. To evaluate the proposed framework, we have collected 677 images from different Kubachi ware (known as Persian pottery) to study the inpainting results. The provided dataset is available free for the research community. Quantitative and qualitative evaluations of the results show that the proposed framework performs well, where the inpainted parts are visually and semantically plausible, and the details of the predicted colors in the damaged areas are very satisfying.

ESTABLISHMENT OF BIG DATA ANALYTICS APPLICATION MODEL FOR MALAYSIAN PUBLIC SECTOR: AN EXPERT VALIDATION

These days, Big Data (BD) and Big Data Analytics (BDA) applications have increased intensively among public and private organisations. Most organisations are aware that BDA has an enormous potential in aiding them to better understand their business environments and their customers’ needs. Nevertheless, many organisations have yet to implement BD as they are concerned that poor quality of data will have an adverse impact on establishing worthful insight, and leading to severe mistakes during their decision-making process. In addition, the different BD characteristics or traits could affect data quality. Therefore, to determine the value of data generated from BD, the collected data must be analysed for accuracy and quality. This paper aims to present findings to better understand quality requirements for BDA implementation in the public sector, specifically in Malaysia. This study explored the influence of Data Quality Dimensions (DQD) on BDA application, identified the influence of Big Data Traits (BDT) on DQD, and evaluated the integration of BDT and DQD in BDA applications using expert validation approach. A conceptual model that incorporates DQD and BDT for BDA application in the public sector was proposed as the study outcome. The conceptual model was developed based on eight BDT (variety, velocity, veracity, validity, volume, value, volatility, and variability) and four data quality categories (intrinsic, contextual, representational, and accessibility). The expert validation results showed that five out of eight BDT are important. The outcomes from this study would deliver important knowledge to the current body of studies that may prove useful for potential use in the future.

Training improves the handling of inhaler devices and reduces the severity of symptoms in geriatric patients suffering from chronic-obstructive pulmonary disease

PurposeElderly patients with impaired vision, cognitive decline or motor/sensory disturbances of their fingers suffering from chronic-obstructive pulmonary disease (COPD) encounter difficulties in handling inhaler devices used as the cornerstones of treatment of pulmonary obstruction. Many elderly patients make severe mistakes which impede adequate drug delivery to the bronchioles. This multimodal training program was designed to reduce the number of handling mistakes of inhaler devices.MethodsFrom October 1, 2016 to September 30, 2017, a prospective intervention study was conducted in 38 in-patients > 65 years (median age 79 years) with previously diagnosed COPD. The effect of an 8-day intervention comprising daily counselling and video demonstration according to the recommendations of the German Airway League on the frequency of mistakes during handling of inhaler devices, the forced expiratory volume in 1 s (FEV1), the forced vital capacity (FVC) and the perception of symptoms (COPD Assessment Test, CAT) were studied. Measurements on days 1 and 8 were compared by Wilcoxon signed rank test.ResultsThe number of handling mistakes per patient decreased as a consequence of the intervention from 3.0 (0–7) to 0.5 (0–6) [median (minimum-maximum; p < 0.0001)]. The CAT Score decreased from 19.5 (14/24) to 14.5 (10.75/21) [median (25./75. percentile; p < 0.0001) indicating a substantial reduction of clinical symptoms. Conversely, FEV1 and FVC only slightly increased (difference statistically not significant). At study entry, the number of handling mistakes was inversely correlated with the Mini Mental Status Test (MMST) score (p = 0.01). The reduction of the number of handling mistakes during the intervention was not correlated with the MMST.ConclusionIn COPD, intensive training for 8 days improved the handling of inhalers and reduced clinical symptoms in geriatric patients. Patients with cognitive abnormalities also benefitted from this intervention.Trial registrationGerman Clinical Trials Registry DRKS00023196, date of registration September 29, 2020 (retrospectively registered).

Monte Carlo SEM-EDS Nano-Microanalysis Strategy of Historical Mineral Pigments: The Simulation of the Egyptian Blue from Pompeii (Italy) as an Example

A correct determination of the mineral and chemical composition of specimens is of the utmost importance to answer questions regarding the Cultural Heritage field. Because of the preciousness and often very low quantity of sample available, with textures and sizes in the nano-to-micrometric range, scanning electron microscopy (SEM) combined with energy-dispersive X-ray spectroscopy (EDS) is one of the most suited and exploited nano-microanalytical techniques. In these cases, to avoid severe mistakes and quantification errors in SEM-EDS, it is mandatory to consider several effects related to the transport of electrons and X-rays in the material, which in turn are dependent on the SEM-EDS setup. In the present work, a Monte Carlo SEM-EDS nano-microanalytical simulation strategy is proposed and applied to a practical selected case. The Egyptian blue mineral pigment, which is found in Pompeian murals, is used here as an example and model system to show the effects of real size variations (0.1–10 µm), basic geometrical shapes of the pigment (prismatic and spherical) and typical SEM setups, sample holders and substrates. The simulations showed a great—sometimes not intuitive—dependence of the X-ray intensity on the thickness and shape of the samples and SEM-EDS parameters, thereby influencing the analysis and quantification. The critical overview of the results allowed the determination of the correct procedure and technical SEM-EDS parameters and indicated how to apply the Monte Carlo simulation strategy to other Cultural Heritage cases.

La comunicación de los efectos adversos en un servicio de urgencias

Objective: to review the communication barriers in healthcare professionals when faced with an adverse event. Method: a qualitative phenomenological study conducted at the Emergency Unit from the Hospital de Tortosa Virgen de la Cinta (Tarragona) between October and December, 2018, through convenience sampling. Two focus groups were set up, with six-seven healthcare professionals grouped by time of professional experience (over or below three years). The participants were differentiated by age, gender and professional category. The Atlas.Ti program was used for analysis. Three analytical categories and 14 subcategories were identified. Results: the study included 13 professionals in two focus groups. The categories emerging from their speech were: definition of adverse event, information and improvements. The frequency of errors was normalized. They mentioned mild and severe mistakes, differentiating their action and feelings. They reported that part of their learning consists in trial-error during practice. They expressed fear to report in severe situations. The recording system is underused. They coincided in reporting as a team, after consensus, and they expressed lack of institutional protection. They proposed implementing debriefings, positive identification, communication between hospital units, information technologies, and a structured change of shift. Conclusion: fear of answers, loss of reputation, and lack of institutional support appeared as the main barriers at the time of acknowledging and reporting incidents. There was wide consensus about lack of responsibiility in communication and excuse for adverse events, and about the need to provide support and training to professionals.

Fall back proper equilibrium

Proper equilibrium plays a prominent role in the literature on non-cooperative games. The underlying thought experiment in which the players play a passive role is, however, unsatisfying, as it gives no justification for its fundamental idea that severe mistakes are made with a significantly smaller probability than innocuous ones. In this paper, we introduce a more active role for the players, leading to the refinement of fall back proper equilibrium.

A comparative analysis of common mistakes in achievement tests prepared by school teachers and corporate trainers

Test development has been an important part of measurement and evaluation in any educational setting, whether its purpose is instruction or training. Both teachers and trainers are expected to have certain level of mastery in developing reliable and valid tests for assessing performance of learners adequately. However, it has often been reported that teachers and trainers are not competent enough to develop such tests. Most teachers have taken at least one university course on educational measurement and evaluation during their undergraduate education. Similarly, a considerable number of corporate trainers attend at least one in-service training seminar on measurement and evaluation as a part of their professional training program. However, teachers and trainers still make serious mistakes in preparing tests for assessing the level of learning and performance properly. This study compares their mistakes based on basic principles of test development. More specifically, the researcher wanted to assess whether the mistakes of teachers and trainers are similar or different. Toward this purpose, a total of 120 instructors (62 teachers and 58 trainers) were selected as participants of the study. A total of 6450 test items in various fields of learning were analysed to make comparisons. Results generally suggest that school teachers and corporate trainers make similar mistakes, although their level of knowledge and skills in measurement and evaluation are different due to prior learning. There is also no difference regarding the subject matter area and the level of education for which the tests were developed. Approximately 60% of items need revisions, half of which appear to have severe mistakes. The most common problems are related to easy test items, route learning, implausible distractors, use of negative questions, hidden cues, illogical order of alternatives, length of sentences for correct answers, disturbing sequence of items, single-mode (text-based) questions, and subjective items. These results, along with some others, have serious implications for programs on teacher education and training of trainers.

Retracted: Direct Allylation of In Situ Generated Aldehyde Acyl Anions by Synergistic NHC and Palladium Catalysis.

The above article from Angewandte Chemie International Edition, published online on May 21, 2014 in Wiley Online Library (www.onlinelibrary.wiley.com, DOI: 10.1002/anie.201400623) and in print,1 has been retracted by agreement between the corresponding author, the journal Editor, Dr. Peter Gölitz, and Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim. The retraction has been agreed upon because by performing additional characterization data analyses, the authors discovered that the structures of the products (table 1) were incorrectly assigned: A double-check of the data revealed that the major isolated products were allyl esters and not the expected allyl ketones. The authors acknowledge this severe mistake and its potential impact on the community.

Zurückziehung: Direct Allylation of In Situ Generated Aldehyde Acyl Anions by Synergistic NHC and Palladium Catalysis

The above article from Angewandte Chemie International Edition, published online on May 21, 2014 in Wiley Online Library (www.onlinelibrary.wiley.com, DOI: 10.1002/ange.201400623) and in print,1 has been retracted by agreement between the corresponding author, the journal Editor, Dr. Peter Gölitz, and Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim. The retraction has been agreed upon because by performing additional characterization data analyses, the authors discovered that the structures of the products (table 1) were incorrectly assigned: A double-check of the data revealed that the major isolated products were allyl esters and not the expected allyl ketones. The authors acknowledge this severe mistake and its potential impact on the community.

Statistical sensor fusion of ECG data using automotive-grade sensors

Abstract. Driver states such as fatigue, stress, aggression, distraction or even medical emergencies continue to be yield to severe mistakes in driving and promote accidents. A pathway towards improving driver state assessment can be found in psycho-physiological measures to directly quantify the driver's state from physiological recordings. Although heart rate is a well-established physiological variable that reflects cognitive stress, obtaining heart rate contactless and reliably is a challenging task in an automotive environment. Our aim was to investigate, how sensory fusion of two automotive grade sensors would influence the accuracy of automatic classification of cognitive stress levels. We induced cognitive stress in subjects and estimated levels from their heart rate signals, acquired from automotive ready ECG sensors. Using signal quality indices and Kalman filters, we were able to decrease Root Mean Squared Error (RMSE) of heart rate recordings by 10 beats per minute. We then trained a neural network to classify the cognitive workload state of subjects from heart rate and compared classification performance for ground truth, the individual sensors and the fused heart rate signal. We obtained an increase of 5 % higher correct classification by fusing signals as compared to individual sensors, staying only 4 % below the maximally possible classification accuracy from ground truth. These results are a first step towards real world applications of psycho-physiological measurements in vehicle settings. Future implementations of driver state modeling will be able to draw from a larger pool of data sources, such as additional physiological values or vehicle related data, which can be expected to drive classification to significantly higher values.

Report of improved performance in Talbot-Lau phase-contrast computed tomography.

Many expectations have been raised since the use of conventional x-ray tubes on grating-based x-ray phase-contrast imaging. Despite a reported increase in contrast-to-noise ratio (CNR) in many publications, there is doubt on whether phase-contrast computed tomography (CT) is advantageous in clinical CT scanners in vivo. The aim of this paper is to contribute to this discussion by analyzing the performance of a phase-contrast CT laboratory setup. A phase-contrast CT performance analysis was done. Projection images of a phantom were recorded, and image slices were reconstructed using standard filtered back projection methods. The resulting image slices were analyzed by determining the CNRs in the attenuation and phase image. These results were compared to analytically calculated expectations according to the already published phase-contrast CT performance analysis by Raupach and Flohr [Med. Phys. 39, 4761-4774 (2012)]. There, a severe mistake was found leading to wrong predictions of the performance of phase-contrast CT. The error was corrected and with the new formulae, the experimentally obtained results matched the analytical calculations. The squared ratios of the phase-contrast CNR and the attenuation CNR obtained in the authors' experiment are five- to ten-fold higher than predicted by Raupach and Flohr [Med. Phys. 39, 4761-4774 (2012)]. The effective lateral spatial coherence length deduced outnumbers the already optimistic assumption of Raupach and Flohr [Med. Phys. 39, 4761-4774 (2012)] by a factor of 3. The authors' results indicate that the assumptions made in former performance analyses are pessimistic. The break-even point, when phase-contrast CT outperforms attenuation CT, is within reach even with realistic, nonperfect gratings. Further improvements to state-of-the-art clinical CT scanners, like increasing the spatial resolution, could change the balance in favor of phase-contrast computed tomography even more. This could be done by, e.g., quantum-counting pixel detectors with four-fold smaller pixel pitches.

Exploring Driver Error at Intersections

A large portion of crashes occur at intersections, and most such crashes are associated with driver mistakes. Severe mistakes may lead to serious injuries; therefore, it is necessary to investigate the factors that contribute to driver error and how those factors influence driver behavior. More information on these contributing factors can help researchers develop cost-effective countermeasures that might help mitigate driver error. The primary objective of this study was to examine key contributors to driver error that took place at uncontrolled, sign-controlled, and signalized intersections. An ordered-probit statistical model and a data-mining technique called “association rules” were implemented to explore these relationships. The results of both approaches were consistent. Association rules were found to be capable of discovering patterns in the data that could not be found in the ordered-probit statistical model. The secondary objective of this study was to provide new insights on how to improve intersection safety by adding to the knowledge regarding the contributing factors of those driver errors. Most, if not all, errors are related to human factors; thus, they can effectively be corrected through a holistic approach that involves engineering, enforcement, and education.

Unexpected Consequences of Ricardian Expectations—Erratum

AbstractThis note identifies a severe mistake in my article ‘Unexpected Consequences of Ricardian Expectations’ that appeared in this journal in the July 2013 issue.

Editorial: What Matters?

Editorial: What Matters?

“Reverse” nested lottery contests

This paper proposes a multi-prize “reverse” nested lottery contest model, which can be viewed as the “mirror image” of the conventional nested lottery contest of Clark and Riis (1996a). The reverse-lottery contest model determines winners by selecting losers based on contestants’ one-shot effort through a hypothetical sequence of lotteries. We provide a microfoundation for the reverse-lottery contest from a perspective of (simultaneous) noisy performance ranking and establish that the model is underpinned by a unique performance evaluation rule. We further demonstrate that the noisy-ranking model can be interpreted intuitively as a “worst-shot” contest, in which contestants’ performances are evaluated based on their most severe mistakes. The reverse-lottery contest model thus depicts a great variety of widely observed competitive activities of this nature. A handy closed-form solution for a symmetric equilibrium of the reverse-lottery contest is obtained. We show that the winner-take-all principle continues to hold in reverse-lottery contests. Moreover, we find that a reverse-lottery contest elicits more effort than a conventional lottery contest whenever the prizes available to contestants are relatively scarce.