Consequences Of Errors Research Articles

Is the plant biostimulant application ameliorative for herbicide-damaged sunflower hybrids?

Sunflower (Helianthus annuus L.) is one of the most economically important field crops grown in Bulgaria. In some cases sunflowers from different systems (IMI-SUN or ExpressSUN) are sprayed by mistake with the unappropriated herbicidal product for the growing system – IMI- or Express SUN and reverse. Then, acute or chronic phytotoxic effects (even death of the plants) may occur. In some situations, the plants mistakenly treated with the wrong herbicidal product may recover completely, or to different extents after ameliorative treatment with plant biostimulants. For this reason, two field trials in three consecutive growing seasons in 2017, 2018, and 2019 were conducted. The experiments were performed in the experimental field of the Department of Agriculture and Herbology at the Agricultural University of Plovdiv, Bulgaria. The experiments aimed to evaluate the ameliorative effect of the plant biostimulant Amino Expert® Impuls after imitation of ”mistaken” herbicide application. In the first experiment the ExpressSUN sunflower hybrid “P 64 LE 25″ was treated with imazamox, and in the second, the IMI-SUN sunflower hybrid “Bacardi” CLP (Clearfield Plus) was sprayed with tribenuron-methyl. The treatments included untreated control plots, application of imazamox (Pulsar Plus – 2.00 l ha−1), or tribenuron-methyl (Express 50 WG (water-soluble granules) - 0.04 kg ha−1 + Trend 90–0.1%) alone and variants with the ameliorative supplication of plant biostimulant four days after the herbicidal intervention. After the application of the plant biostimulant Amino Expert Impuls for ameliorative treatment, the plants from both cropping systems overcome the herbicide stress to different extents. The Chlorophylls (a and b) and carotenoids as well as net photosynthetic rate were higher for the untreated plants from both technologies. For the treatments where plant biostimulant application was used, an increase of the parameters sunflower head diameter, plant height, seed yield, absolute seed mass, as well as seed oil content were recorded. The obtained results showed that the significant results are in favor of ExpressSun technology. In the event of errors in the application of herbicides in these two cropping systems, the consequences are much more corrective in cases where tribenuron-methyl-tolerant sunflower is treated with Pulsar Plus than if IMI-SUN sunflower is treated with the herbicide Express 50 WG + Trend 90.

Deep-Learning-Based Earthquake Detection for Fiber-Optic Distributed Acoustic Sensing

In this paper, deep learning models trained with real seismic data are proposed and proven to detect earthquakes in fiber-optic distributed acoustic sensor (DAS) measurements. The proposed neural network architectures cover the three classical deep learning paradigms: fully connected artificial neural networks (FC-ANNs), convolutional neural networks (CNNs) and recurrent neural networks (RNNs). Results demonstrate that training these networks with seismic waveforms measured by traditional broadband seismometers can extract and learn relevant features of earthquakes, enabling the reliable detection of seismic waves in DAS measurements. The intrinsic differences between DAS and seismograph waveforms, and eventual errors in the labelling of the DAS data, slightly reduce the performance of the models when tested with the distributed acoustic measurements. Despites of that, trained models can still reach up to 96.94% accuracy in the case of CNN and 93.86% in the case of CNN+RNN. The method and results here reported could represent an important contribution to the development of an early warning earthquake system based on DAS technology.

A deep learning approach for direction of arrival estimation using automotive-grade ultrasonic sensors

In this paper, a deep learning approach is presented for direction of arrival estimation using automotive-grade ultrasonic sensors which are used for driving assistance systems such as automatic parking. A study and implementation of the state of the art deterministic direction of arrival estimation algorithms is used as a benchmark for the performance of the proposed approach. Analysis of the performance of the proposed algorithms against the existing algorithms is carried out over simulation data as well as data from a measurement campaign done using automotive-grade ultrasonic sensors. Both sets of results clearly show the superiority of the proposed approach under realistic conditions such as noise from the environment as well as eventual errors in measurements. It is demonstrated as well how the proposed approach can overcome some of the known limitations of the existing algorithms such as precision dilution of triangulation and aliasing.

Error cancellation.

The human cognitive system houses efficient mechanisms to monitor ongoing actions. Upon detecting an erroneous course of action, these mechanisms are commonly assumed to adjust cognitive processing to mitigate the error's consequences and to prevent future action slips. Here, we demonstrate that error detection has far earlier consequences by feeding back directly onto ongoing motor activity, thus cancelling erroneous movements immediately. We tested this prediction of immediate auto-correction by analysing how the force of correct and erroneous keypress actions evolves over time while controlling for cognitive and biomechanical constraints relating to response time and the peak force of a movement. We conclude that the force profiles are indicative of active cancellation by showing indications of shorter response durations for errors already within the first 100 ms, i.e. between the onset and the peak of the response, a timescale that has previously been related solely to error detection. This effect increased in a late phase of responding, i.e. after response force peaked until its offset, further corroborating that it indeed reflects cancellation efforts instead of consequences of planning or initiating the error.

A Statistical Model to Determine Biomechanical Limits for Physically Safe Interactions With Collaborative Robots

Collaborative robots (cobots) provide a wide range of opportunities to improve the ergonomics and efficiency of manual work stations. ISO/TS 15066 defines power and force limiting (PFL) as one of four safeguarding modes for these robots. PFL specifies biomechanical limits for hazardous impacts and pinching contacts that a cobot must not exceed to protect humans from serious injuries. Most of the limits in ISO/TS 15066 are preliminary, since they are based on unverified data from a literature survey. This article presents a human-subject study that provides new and experimentally verified limits for biomechanically safe interactions between humans and cobots. The new limits are specifically tailored to impact and pinching transferred through blunt and semi-sharp surfaces as they can occur in the event of human error or technical failures. Altogether 112 subjects participated in the study and were subjected to tests with emulated impact and pinching loads at 28 different body locations. During the experiments, the contact force was gradually increased until the load evoked a slightly painful feeling on the subject’s body location under test. The results confirm that the pain thresholds of males and females are different in specific body regions. Therefore, when defining biomechanical limits, the gender difference must be taken into account. A regression model was utilized to incorporate the gender effect as a covariate into a conventional statistical distribution model that can be used to calculate individual limits, precisely fitted to a specific percentile of a mixed group of male and female workers which interacting with cobots.

Malpractice Awareness among Surgeons and Surgical Trainees in Ethiopia.

In Ethiopia, a country where seeing medical errors is not rare, there is a lack of data concerning the overall awareness of medical malpractice issues among physicians. A recent study showed that 80% of malpractice claims in Ethiopia are related to some form of surgery or operation room activities. A cross-sectional survey was conducted among surgeons and surgical trainees. Data were collected anonymously by an online survey using Google forms through a 56-items structured questionnaire. Subsequently, the data were analyzed and reported employing nonparametric statistical methods with SPSS software package 26. In our sample, the overall awareness regarding medical malpractice was relatively low. Surgery on a wrong patient (71.1%) was the most commonly reported form of malpractice, whereas unintended damage to adjacent organs (10.8%) was the most frequently disagreed up on form. In the event of a medical error, the majority (59.6%) reported readiness to disclose their error to the patient. The most common mentioned reason for not revealing a mistake was a threat of physical or verbal assault (68%). A significant number of respondents, i.e., 120(59.1%), reported being physically/verbally assaulted by a patient or their attendants at some point in their practice. The findings of our study provided a general picture of surgeons' and surgical trainees' knowledge, attitude, and practice regarding medical malpractice. This study recommends more robust ethics and law training modules to surgical trainees, refresher courses to surgeons, and advanced training programs in ethics and law.

Fault-tolerant control system for the formation of carbon products

The production of carbon products is largely resource- and energy-intensive. That is why increasing the efficiency of this production is an urgent scientific and practical task, especially in modern conditions of constant growth of energy costs. An effective way to solve this problem is to create a modern process control system, taking into account possible failures of system components. A method for the synthesis of a fault-tolerant control system for the cyclic formation of carbon products has been developed, which takes into account control errors that are caused by malfunctions of controllers under conditions of unknown disturbances. According to the cyclic nature of the technological process under consideration, a control method with iterative learning was used in the synthesis of the control system. This method considers cyclic processes based on a two-dimensional model (2D model). The proposed control algorithm ensures the convergence of the control process with the task both in time and in each work cycle in order to promote the required quality of control even in the event of unknown disturbances and errors in the performance of controllers. The synthesis of the control system is based on the solution of a system of linear matrix inequalities. Based on the combination of a control method with iterative learning and a control method that takes into account failures in controllers, a method of constructing a fault-tolerant control system for the cyclic formation of carbon products has been synthesized to ensure acceptable operation of the control object in abnormal conditions. The control system has been synthesized by solving a system of linear matrix inequalities with the MATLAB software. In the future, it is necessary to consider optimal settings of the proposed control system and examine its effectiveness in comparison with conventional fault-tolerant systems for non-cyclic processes.

Design and Development of an Online Smart Monitoring and Diagnosis System for Photovoltaic Distributed Generation

In photovoltaic power plants, fault diagnosis tools are essential for ensuring a high energy yield. These tools should be capable of accurately identifying and quantifying the factors behind the various fault mechanisms commonly found in photovoltaic plants. Considering the aforementioned factors, this article proposes an online smart PV monitoring solution, which is capable of detecting malfunctions that arise from accidental and/or technical causes through the analysis of I-V curves, however, without the necessity to interrupt the operation of the system, thus reducing the maintenance cost. Accidental causes can lead to the reduction of energy productivity due to the excessive accumulation of dirt on the photovoltaic modules, partial shading and eventual errors that occur during its installation. On the other hand, technical causes can be attributed to faults found on the photovoltaic modules, which lead to gradual losses in their electric and material characteristics. Therefore, by using the electric characteristics supplied by the manufacturer of the installed modules, the I-V and P-V curves of the operational photovoltaic strings were obtained in real time, compared to the respective theoretical curves obtained through mathematical modeling. In order to validate the proposed online monitoring system and its potential for predictive maintenance application, a field experimentation was mounted in a 93.8 kWp photovoltaic system.

NTFS Data Tracker: Tracking file data history based on $LogFile

The $LogFile is a file system metafile that stores NTFS (New Technology File System) transaction data. It is used to restore the file system to its normal state in the event of a file system error, such as one caused by sudden power outages. The transaction data recorded in $LogFile contain changes in the metadata of files and directories in the $MFT. By analyzing it, all file operations performed in the file system during a specific period can be identified. Existing research on the $LogFile has focused on finding file-level events including create, delete, move and rename. Research has also been conducted on file data in $LogFile to acquire data location information (data runs) that is initially stored at the time of file creation, or to reconstruct only the final location information of the data. No research, however, has been conducted to date on tracking the entire history of changes in the file data. In this paper, we develop a technique that reproduces changes in the metadata within the $MFT on a file-by-file basis by using transaction data recorded in the $LogFile to overcome the limitations of existing research in the area. We use this technique to track all data on the history of a given file according to changes in it over time from its creation to deletion. An NTFS Data Tracker is also developed based on the results and various example use cases are discussed.

Selection of Optimal Error Recovery Process using Evaluation Standards in Automated Plants

Plant automation has become increasingly popular in various industries. However, errors are more likely to occur in difficult tasks that are often performed in an automated plant. Such tasks are often returned to the previous step, and re-executed in the event of a large-scale error. Therefore, it is important to decide both the past step to which the task needs to return and the recovery step following its return. In this study, various evaluation standards are used to realize the planning of error recovery, while considering these two factors.

Factors associated with medical students’ speaking-up about medical errors: A cross-sectional study

Background Training medical students to speak up when they witness a potential error is an important competency for patient safety, but details regarding the barriers that prevent medical students from effectively communicating are lacking. Therefore, this study aimed at exploring the factors affecting medical students’ willingness to speak up for patient safety when a medical error was observed. Methods This is a cross-sectional study at a medical university in Taiwan, and 151 medical students in clinical clerkship completed a survey including demographic characteristics, conflict of interests/social relationship, personal capability, and personality and characteristics of senior staff domains. Data were analyzed using t-test. Results Three of five items in the conflict of interests/social relationship domain showed statistically significant importance, including ‘I am afraid of being punished’ (Mean difference, MD = 0.37; p < 0.01), ‘I do not want to break unspoken rules’ (MD = 0.55; p < 0.01), and ‘I do not want to have bad team relationship’ (MD = 0.58; p < 0.01). Two items (perception of knowledge/understanding and communication skills) in the personal capability domain were significantly important to speaking up. Six of 10 items in personality and characteristics of senior staff domain were rated significantly important in deciding to speak up. The top three factors of them were senior personnel with ‘Grumpy’ personality (MD = 1.20; p < 0.01), ‘hierarchy gap’ (MD = 1.12; p < 0.01), and senior personnel with ‘Stubborn’ personality (MD = 1.06; p < 0.01). Conclusion Our findings demonstrated medical students’ perspectives on barriers to speaking up in the event of medical error. Some factors related to characteristics of senior staff could compromise medical students’ ability to speak up in the event of medical error. These results might be important for medical educators in designing personalized educational activities related to medical students’ ability to speak up for patient safety.

Investigating Safety Standards and Performance of Emergency Power Diesel Generators in Hospitals of Tabriz, Iran

Background: Power outage risk is one of the serious risks that could be eliminated by supplying electricity through the emergency power system installed in a hospital, such as diesel generators and uninterruptible power supplies (UPSs).&#x0D; Objectives: The present study aimed to investigate the observance of safety and maintenance standards of emergency power diesel generators in the hospitals of Tabriz.&#x0D; Methods: This descriptive-analytical research was cross-sectionally performed in 18 hospitals of Tabriz in 2014. The data collection tools included a questionnaire and a checklist prepared according to the national standards and consisted of 87 questions in 15 categories. Data were analyzed using SPSS version 19.&#x0D; Results: The average rates of observance of safety and maintenance standards of diesel generators in 111-question standards and 87-question standards were equal to 61.4 and 52.8%, respectively. Regarding the observance of the 19 standards, “ventilation” and “daily visits” standards with 28.94 and 96.24, respectively, had the lowest and highest degrees of observance in hospitals. There was a significant direct association between observing the standards defined for diesel generators with the number of hospital beds (P = 0.01) and the total capacity of emergency power generation by generators (P = 0.05).&#x0D; Conclusions: The results of the present study indicate a low level of safety and maintenance for the emergency power systems of hospitals. These scores are not considered favorable for a system called “emergency”, and if the necessary interventions are not made in this regard, in the event of natural disasters and human errors, hospitals will face numerous problems.&#x0D;

Analisis Human Error Pada Surat Penyerahan Petikemas (SP2) Dan Warehouse Management System (WMS)

PT. XYZ is a logistics service company engaged in the shipping service business of sea / air ships (EMKL / EMKU) and warehousing / warehousing. In the operational field of Full Container Load (FCL) at PT XYZ, there are problems, namely Human Error (Human Error) inputting data into the Container Handover Letter (SP2) and Warehouse Management System (WMS) documents. The purpose of this study was to determine the causative factors and to find out the right recommendations for improvement in the event of data input errors in the WMS system and data input errors in the manufacture of SP2. Data collection techniques, namely by observation and interviews. The analysis technique used fishbone diagrams and 5W + 1H analysis. Factors that cause Human Error are lack of training or trainning, the number of other tasks outside the job description, the absence of work shifts, the atmosphere is too busy by EMKL who takes care of documents, and the absence of an RFID Reader. To minimize the occurrence of Human Errors is to hold training and provide motivation so that employees can take part in training in operating the WMS system, socializing and providing additional benefits or money to employees, recruiting new employees at least divided into 2 team work shifts for the WMS operation section, adding service into two parts, will reduce EMKL queues and speed up document input to WMS, conduct socialization to use RFID.

Clinical, epidemiological aspects, and trends of Hepatitis B in Brazil from 2007 to 2018

Hepatitis B virus (HBV) infection is a concern for public health due to its high prevalence, high infectivity, morbidity, and mortality worldwide. Brazil presents a low HBV prevalence, but has considerable heterogeneity among its geographic regions. Here, we describe the epidemiological profile of HBV infection in different regions of Brazil during 2007–2018, as well as the historical trends associated with the infection. We conducted an observational, ecological time-series study using secondary data collected from the National Notifiable Diseases Information System (SINAN). Our findings suggest that HBV infection was more likely to occur in young, sexually active adults. Individuals from Northeast and Midwest regions were more likely to present acute HBV infection, while individuals from South region were more likely to present chronic HBV infection, reinforcing that specific strategies are required for each particular region. Additionally, we observed a general decreasing trend of infection starting in 2014, however there was an increasing trend of infection in men and in individuals over 40 years old. Although we observed a decreasing trend in HBV infection, active surveillance is needed to prevent HBV spread and possible epidemics, as well as encouraging the vaccination of adults, especially young adult males. Our findings can inform the conduct of large-scale observational studies to evaluate clinical, economical, and social impacts of HBV infections, leading to improved social policies. Finally, our results highlight the need to improve data quality and completeness of epidemiological data, minimizing eventual errors that can make prevention and control strategies difficult.

DEVELOPMENT OF A DECISION SUPPORT SYSTEM FOR ANALYSIS OF EMERGENCIES ON URBAN TRANSPORT

The article discusses some aspects of the design of a decision support system (DSS) module during the analysis of major accidents or emergencies in urban transport in large cities, megalopolises, as well as in Smart City. It is shown that the computational core of such a DSS can be based on the methods of cluster analysis (CA). It is shown that the implementation of even basic spacecraft algorithms in the computational core of the DSSS allows an iterative search for optimal solutions to prevent a large number of emergencies in urban transport by establishing characteristic signs of accidents and emergencies and measures of proximity between two objects. It is shown that such a toolkit as DSS can provide all interested parties with a scientifically grounded classification of multidimensional observations, which summarize the set of selected indicators and make it possible to identify internal connections between emergencies in urban transport. The DSS module for analyzing emergencies in urban transport is described. It has been found that to solve such a problem, it is possible to use the "weighted" Euclidean distance in the computational core of the DSS. It is this parameter that makes it possible to take into account the significance of each characteristic of emergency situations in urban transport, which, in turn, will contribute to obtaining reliable analysis results. It is shown that the spacecraft methods can also be in demand when, along with the analysis of emergency situations in urban transport, problems of designing and reconstructing the configurations of urban street-road networks are solved in parallel. This task, in particular, requires an analysis phase (not least using CA methods) in order to minimize unnecessary uncompensated costs in the event of errors in the road network. When solving such a problem, sections of the urban street and road network are analyzed in order to identify problem areas that need reconstruction or redevelopment. The use of CA methods in such conjugate problems is due to the absence of a priori hypotheses regarding the classes that will be obtained as a result.

Simulation-Based Learning: Basics for Anaesthetists.

Simulation training is useful to become familiar with new technology, to practice behaviours and strategies, to acquire routines for specific scenarios, and to reflect on one's behaviour. Processes that have to function almost automatically (e.g., resuscitation) have to be practised repeatedly until they can be reliably executed even under stress or fatigue. Simulators offer the opportunity to acquire these skills without endangering the patient. Various types of simulators (from pig liver to premature baby simulator) are already being used extensively for this purpose. Significant advantages of this learning environment include the freedom from risk in the event of errors, the repeatability of procedures, the possibility of varying conditions, and the possibility of practising processes with different complexities. Simulators are used in a variety of settings, providing valuable training in non-technical skills and creating awareness of other aspects of human factors. In addition, working with simulators through targeted testing of technology and work processes can help to structure work in hospitals more closely based on human factors.

Study and promotion of safety culture using mixed methods research

Abstract Objective With a positive safety culture, institutions offer the best quality and safe care to their patients. The objective of this study was to analyze patient safety culture from the perspective of the multidisciplinary team, to identify factors that influence patient safety culture, and to create/promote—jointly with the study participants—strategies for improving processes of change. Methods The study design represented a mixed methods research approach, with a sequential explanatory design. A multidisciplinary team of workers at a general hospital was eligible for the study. To collect quantitative data, we administered the Safety Attitudes Questionnaire (SAQ). The qualitative phase was accomplished via focus groups (FGs), with participants from the first phase of the study using the principles of deliberative dialogue (DD) as a knowledge-translation strategy. The STROBE guideline was used to develop the study. Results The overall SAQ score was positive (75.1 ± 10.4). Negative scores were found in the fields of Safety Climate, Working Conditions, and Stress Recognition. Focus group discussions identified the aspects that create a negative impact on safety culture, such as ineffective communication, punitive approach in the event of errors, the lack of commitment and adherence to the protocols, and the non-recognition of the stress and the mistakes. Actions for the promotion of safety culture were developed and implemented during the study. Conclusions The use of the principles of DD as a strategy for knowledge translation (KT) made it possible to identify and plan for joint actions to generate improvements in safety culture.

Optimal Location of Sectionners and Distributed Generation Resources to Improve Reliability in Distribution Networks

In traditional distribution networks, due to the radial structure and subscriber power supply, in the event of errors in the main feeders, downstream subscribers experienced a long blackout, which reduced the reliability level of the network. With the expansion of the use of scattered generations, storage resources and the use of load response methods, load retrieval is provided in the downstream area. In this paper, a method is proposed for locating sectionners and distributed generations in distribution networks with the aim of creating flexible micro-grids. By creating an island, disassembling and restoring loads of more importance in the distribution network, on the one hand, it reduces the amount of fines paid by the distribution company to Subscribers and economic interests of the distribution company, and, on the other hand, by improving reliability, provides customer satisfaction.

Time-Dependent System Kinematic Reliability Analysis for Robotic Manipulators

Abstract Time-dependent system kinematic reliability of robotic manipulators, referring to the probability of the end-effector’s pose error falling into the specified safe boundary over the whole motion input, is of significant importance for its work performance. However, investigations regarding this issue are quite limited. Therefore, this work conducts time-dependent system kinematic reliability analysis defined with respect to the pose error for robotic manipulators based on the first-passage method. Central to the proposed method is to calculate the outcrossing rate. Given that the errors in robotic manipulators are very small, the closed-form solution to the covariance of the joint distribution of the pose error and its derivative is first derived by means of the Lie group theory. Then, by decomposing the outcrossing event of the pose error, calculating the outcrossing rate is transformed into a problem of determining the first-order moment of a truncated multivariate Gaussian. Then, based on the independent assumption that the outcrossing events occur independently, the analytical formula of the outcrossing rate is deduced for the stochastic kinematic process of robotic manipulators via taking advantage of the moment generating function of the multivariate Gaussian, accordingly leading to achievement of the time-dependent system kinematic reliability. Finally, a six-degrees-of-freedom (6-DOF) robotic manipulator is used to demonstrate the effectiveness of the proposed method by comparison with the Monte Carlo simulation and finite-difference-based outcrossing rate method.

Assessing perspectives on artificial intelligence applications to gastroenterology

Assessing perspectives on artificial intelligence applications to gastroenterology