Error Avoidance Research Articles

Pitfalls and Traps in Neuropathology

Abstract Impediments to making a correct diagnosis are avoided, and complex administrative efforts are used to make those impediments less frequent. There are quality control procedures, patient safety initiatives, and endless meetings attempting to lessen medical errors. Pitfalls and traps are encountered daily by pathologists, and most are avoided. Artifacts produce traps created by cautery, physical crush, thick sections, and drying and are well known. Appropriate deferral, recuts, stains, and collegial consultations aid in error avoidance in these instances. Neuropathology has some pitfalls and traps that are encountered infrequently especially in the low neuropathology case load environment. Those traps are unfamiliar and treacherous for the unwary pathologist. This review describes five cases each with its special trap.

Third assessment on impacts of climate change on tropical cyclones in the Typhoon Committee Region – Part I: Observed changes, detection and attribution

Published findings on climate change impacts on tropical cyclones (TCs) in the ESCAP/WMO Typhoon Committee Region are assessed. We focus on observed TC changes in the western North Pacific (WNP) basin, including frequency, intensity, precipitation, track pattern, and storm surge. Results from an updated survey of impacts of past TC activity on various Members of the Typhoon Committee are also reported. Existing TC datasets continue to show substantial interdecadal variations in basin-wide TC frequency and intensity in the WNP. There has been encouraging progress in improving the consensus between different datasets concerning intensity trends. A statistically significant northwestward shift in WNP TC tracks since the 1980s has been documented. There is low-to-medium confidence in a detectable poleward shift since the 1940s in the average latitude where TCs reach their peak intensity in the WNP. A worsening of storm inundation levels is believed to be occurring due to sea level rise-due in part to anthropogenic influence-assuming all other factors equal. However, we are not aware that any TC climate change signal has been convincingly detected in WNP sea level extremes data. We also consider detection and attribution of observed changes based on an alternative Type II error avoidance perspective.

Learning Climate and Innovative Work Behavior, the Mediating Role of the Learning Potential of the Workplace

This study aims to explore the relationship between learning climate, in the dimensions of learning facilitation and error avoidance, learning potential of the workplace (task-related and interactional) and innovative work behavior. Survey data were collected from a sample of 374 employees and their supervisors from an automatic food distribution company in central Italy. Structural equation models have been conducted to empirically test the hypotheses. Results showed that both dimensions of learning climate were related interactional and task-related learning potential and that task-related learning potential mediated the relationship between climate and innovative behavior. Furthermore, the climatic dimension of learning facilitation had a direct relationship with innovative work behavior. Advancing from existing organizational behavior and individual learning literature, this article contributes to extend knowledge about the role of learning climate and workplace learning potential in innovative work behavior. The findings offer guidance for organizations that aim to strengthen employee-driven innovation, highlighting the importance of learning climate and potential.

The Efficacy of Normal Saline (N/S 0.9%) Versus Heparin Solution in Maintaining Patency of Peripheral Venous Catheter and Avoiding Complications: a Systematic Review.

Introduction:Heparin is a sulfated polysaccharide belonging to the glycosaminoglycan family with strong anticoagulant activity. It has been widely used to maintain intravascular catheters in patients requiring intravenous medication. It is believed that heparin prevents thrombus formation in the intravascular catheter, but since the 1980s, the necessity of the heparin solution for peripheral intravenous catheter (PIVC) flushing has been questioned in several clinical trials. According to the Institute for Safe Medication Practices (ISMP), there are four special categories of High Alert Medications (HAMs), including heparin.Aim:The aim of this systematic review was to investigate the efficacy of normal saline versus heparin solution in maintaining the patency and functionality of the PIVC and avoiding complications.Methodology:A systematic review using PubMed and Cochrane Library databases was conducted. Original research studies of hospitalized patients with PIVC, regardless of age, published in English, over the last decade (2009-2019) were eligible for inclusion.Results:The review concluded in 10 studies that met the inclusion criteria. From these studies, it appears that it is not fully documented whether the normal saline (N/S 0,9%) is superior to heparin solution (H/S) in the flushing of the PIVC for maintaining its patency and prevent complications. Researchers tend to support the use of N/S 0,9% due to safety, error avoidance, efficiency, ease of use and cost-effectiveness. Concern about the possible complications of the heparin solution was the cause of guidelines development for N/S 0,9% in countries such as Australia.Conclusions:The use of normal saline seems to outweigh the heparin solution in maintaining the patency of PIVC.

Use of human-robot collaboration to enhance process monitoring of mechanical joining

This paper presents a new form of setting process monitoring for mechanical joining implemented into a human-robot collaboration. The used lightweight robot can be manipulated in an intuitive way. We developed an easy to use hand guiding opportunity for cobots from Universal Robots by providing an URCap. This way such a cobot can be manipulated quickly and precisely with ease by any operator new to the system within minutes. It enables an economic use of hand guiding with an additional hand guiding device. With this device the teach pendant is not needed during the regular operations which simplifies the usage of the cobot. The integrated sensors (primarily a force-torque sensor) collect data, which gives information about the setting process. Several errors (e.g. no rivet head support, angle offset, gap between the sheets) were carried out on a test setup while recording the data for evaluation. The resulting force/torque-time graphs give indication of the occurring error. As a result the classified error can be immediately displayed to the operator for recognizing the need for reworking. In combination with an error avoidance algorithm the overall quality of the product can be sustainably improved.

CeSR + Assisted LDPC: A Holistic Strategy to Improve MLC NAND Flash Reliability

NAND flash suffers from program interference and retention errors, which negatively affect its reliability. Existing schemes preprocess raw data before writing them to reduce Raw Bit Error Rate (RBER) and leverage ECCs (such as LDPC codes) to reduce Uncorrectable Bit Error Rate (UBER). Prior arts failed to take into account the counteractions between the program interference and retention errors.Thus, they may lead to sub-optimal error avoidance. Besides, after the preprocessing procedure, data randomness may be affected. Since NAND flash shows numerical-correlated error characteristics, there's a potential to provide such information to LDPC codes to further improve performance. In this article, we propose a holistic strategy consisting of two coupled procedures to enhance flash reliability. First, we use our previously proposed CeSR strategy to reduce RBER. Second, we improve the existing LDPC codes and name it Assisted LDPC strategy to reduce UBER. The Assisted LDPC is deeply coupled with CeSR. It leverages the data pattern after CeSR to improve the decoding success rate and accelerate the decoding procedure. The evaluation shows that compared with the state-of-the-art NRC strategy, CeSR can reduce the RBER of hot and cold data by up to 20.30% and 85.13%, respectively. Besides, compared with the traditional LDPC, the Assisted LDPC decoding strategy can increase the decoding success rate by up to 97% for cold data and reduce the average decoding iteration number of MSB pages for hot and cold data by up to 31.6% and 73.9%, respectively.

DVFS Based Error Avoidance Strategy in Wireless Network-on-Chip

In wireless on-chip network, the reliability of data packet transmission in the link faces great challenges due to crosstalk between lines, noise and transient faults, which seriously affects the overall performance of the network. Therefore, fault tolerance becomes critical in link design. In addition, the traditional fault-tolerant solution based on the error recovery strategy brings a lot of retransmission overhead under high failure rate. Hence, in this paper we propose a new fault-tolerant scheme based on DVFS error avoidance strategy, which dynamically adjusts the voltage and frequency in the network based on the real-time status of the network, thereby reducing the occurrence of faults. Experiments indicate that compared with the traditional fault-tolerant scheme based on error recovery strategy, this paper achieves a huge performance improvement with less power consumption and area overhead.

Medication error encouragement training: A quasi-experimental study

BackgroundMedication errors are the most common clinical errors in healthcare practice and can lead to serious consequences. Medication error encouragement training (MEET) brings students face-to-face with potential errors in the medication process, in a safe environment where they are encouraged to understand both the error and the context in which it occurred. ObjectivesThe study aimed to examine the effects of a MEET intervention on medication safety confidence among nursing undergraduates. DesignThis was a quasi-experimental study with a nonequivalent control group design. ParticipantsOur sample was recruited from the nursing education department of a university, with 47 participants randomly assigned to the experimental group, and 50 to the control group. MethodsBoth groups received theoretical training, followed by applied training. The experimental group received the MEET intervention developed specifically for this study, while the control group received traditional error avoidance training. Participants' medication administration confidence was measured pre- and post-intervention. ResultsFollowing training, the experimental group's confidence was significantly higher than that of the control group. With regard to individual medication administration procedures, the experimental groups' medication safety confidence increased significantly after training compared to the control group in patient identification, drug information confirmation, and drug preparation. ConclusionsIntroducing MEET into nursing curricula could reduce medication errors and related complications in healthcare institutions. Further studies are needed to investigate the long-term effects of MEET interventions, as well as the generalizability of our findings.

Innovative accuracy design of in-site precise automatic inspecting machine of valve sleeve bore of aeronautical precision coupling

The diameter accuracy and geometric accuracy of the valve sleeve bore of aeronautical precision coupling are both high. It is necessary to inspect the bore diameter and cylindricity error frequently in machining, but there is a lack of in-site high accuracy and low cost automatic inspection methods currently. The scheme and accuracy design of a precise automatic inspecting machine (PAIM) of valve sleeve bore is carried out. Accuracy design of PAIM by traditional error distribution method fails to meet the requirement of measurement accuracy. Based on the idea of error avoidance and TRIZ technology system evolution theory, an innovative accuracy design method by using automatic dynamic disconnected measuring chain is proposed and realized. Accuracy analysis and experiment prove the correctness and validity of the proposed method.

A Dynamic Timing Error Avoidance Technique Using Prediction Logic in High-Performance Designs

Time borrowing techniques have been widely used to mitigate the timing errors in high-performance designs. A new dynamic flip-flop conversion technique is introduced by Ahmadi et al. (2015) which dynamically converts flip-flops into transparent latches to grant the time borrowing from the next stage and prevent setup time violation. However, it is not able to prevent the timing violation in the successive critical path (SCP) and critical feedback path (CFP) structures. In this brief, we introduce a novel idea of using the output of fast prediction logic of the critical path along with dynamic clock stretching in SCP and CFP structures. The results show that our technique, on average, is able to improve the performance by 20.2% and 14.8% during the prelayout and postlayout simulations, respectively. Furthermore, the proposed technique is almost 7.7% more effective in terms of the performance improvement with only 0.1% area overhead in comparison with the best existing technique.

Automatic 3D cephalometric annotation system using shadowed 2D image-based machine learning

This paper presents a new approach to automatic three-dimensional (3D) cephalometric annotation for diagnosis, surgical planning, and treatment evaluation. There has long been considerable demand for automated cephalometric landmarking, since manual landmarking requires considerable time and experience as well as objectivity and scrupulous error avoidance. Due to the inherent limitation of two-dimensional (2D) cephalometry and the 3D nature of surgical simulation, there is a trend away from current 2D to 3D cephalometry. Deep learning approaches to cephalometric landmarking seem highly promising, but there exist serious difficulties in handling high dimensional 3D CT data, dimension referring to the number of voxels. To address this issue of dimensionality, this paper proposes a shadowed 2D image-based machine learning method which uses multiple shadowed 2D images with various lighting and view directions to capture 3D geometric cues. The proposed method using VGG-net was trained and tested using 2700 shadowed 2D images and corresponding manual landmarkings. Test data evaluation shows that our method achieved an average point-to-point error of 1.5 mm for the seven major landmarks.

Is the new ASNM intraoperative neuromonitoring supervision \u201cguideline\u201d a trustworthy guideline? A commentary

The new ASNM intraoperative neuromonitoring (IONM) supervision guideline [1] attempts to justify current remote IONM practices.1 Contrary to ordinary clinical practice guideline development, it is provider-centered, not patient-centered. The new guideline could have embraced recent scholarship that indicates the need to provide robust teamwork and medical error avoidance. It could have moved in the direction of improved patient safety and outcomes. Instead, key words are repeated (“communicate,” “collaborate,” “team”) many times, but with no meaningful strategy to achieve their patient safety potential. In fact, within this new guideline, an IONM remote provider’s communication with in-room physician peers and co-practitioners is defined as: “… at minimum, direct voice access (via ‘land-line’ or cellular network) for perioperative communication with the surgical team”.

Effectiveness of error management training in the hospitality industry: Impact on perceived fairness and service recovery performance

Hospitality employees make errors given the characteristics of the service product. The way employees handle errors is largely determined by the training they receive. This research examined the impact of three training types on employees’ service recovery performance: errorless training, error avoidance training, and error management training. The mediating effect of perceived fairness between training types and service recovery performance was also examined. A scenario-based experimental research design in a restaurant setting was used in this study. The data was collected from 109 frontline hospitality employees in the United States (in Study 1) and from 155 foodservice professionals in China (in Study 2). Results indicated that error management training has a stronger impact on service recovery performance and perceived fairness compared to errorless and error avoidance training. The mediation effect of perceived fairness was also found. All hypotheses were supported and the findings were consistent in both studies.

The Error Dilemma in Teams: Goal Orientations, Information Elaboration, and Team Errors

A team composition including two types of individuals – one focused on error avoidance and the other on learning – has been assumed to be optimal for minimizing team errors. We, however, propose th...

Punched belt hole position deviation analysis of float type water level gauge

The key parts of the float type water level gauge instrument is perforated belt, The size and tolerance requirements of its aperture is: (1) alternation of 100+0.2 and 100-0.2, (2) 200±0.1, (3) 1000±0.15, (4) 10000±0.2. The single hole position: alternation of 100+0.2 and 100-0.2; double: 200±0.1, and ensure the best hole position error avoidance tends to be one-way, that is to say: when the punched belt combined with a water wheel rotating line moving, The hole position error to single direction increase or decrease, caused the water level nail gradually and close to the edge of the hole, and then edge and final punched belt was lifted. This paper uses the laser drilling process of steel strip for data collection and analysis. It is found that this method cannot meet the tolerance requirements and the double stamping processing method with adjustable cylindrical pin is feasible.

Medical Error Avoidance in Intraoperative Neurophysiological Monitoring: The Communication Imperative.

Error avoidance in medicine follows similar rules that apply within the design and operation of other complex systems. The error-reduction concepts that best fit the conduct of testing during intraoperative neuromonitoring are forgiving design (reversibility of signal loss to avoid/prevent injury) and system redundancy (reduction of false reports by the multiplication of the error rate of tests independently assessing the same structure). However, error reduction in intraoperative neuromonitoring is complicated by the dichotomous roles (and biases) of the neurophysiologist (test recording and interpretation) and surgeon (intervention). This "interventional cascade" can be given as follows: test → interpretation → communication → intervention → outcome. Observational and controlled trials within operating rooms demonstrate that optimized communication, collaboration, and situational awareness result in fewer errors. Well-functioning operating room collaboration depends on familiarity and trust among colleagues. Checklists represent one method to initially enhance communication and avoid obvious errors. All intraoperative neuromonitoring supervisors should strive to use sufficient means to secure situational awareness and trusted communication/collaboration. Face-to-face audiovisual teleconnections may help repair deficiencies when a particular practice model disallows personal operating room availability. All supervising intraoperative neurophysiologists need to reject an insular or deferential or distant mindset.

Tool wear induced error avoidance on dental prosthesis manufacturing

During the manufacturing of dental prostheses, tight tolerances have to be obtained in order to ensure the correct fitting of the prosthesis seats to the implants located on the patient’s jaw. However, the wearing of the tool can generate errors during precision milling processes that lead to unacceptable geometrical deviations, producing a high cost due to the waste of resources and machine time. The present paper introduces a procedure for the avoidance of these defects during the precision milling processes employed for the machining of dental prostheses. By the use of geometrical models, the deviations generated on the machined surfaces by a worn tool can be calculated in comparison to a fresh tool. Once the deviations are calculated, it is possible to avoid them by the use of 2D tool radius compensation techniques. The capability of the solution presented here was validated by machining prosthesis seats and evaluating their assembly to a fitting part. The obtained results show that the developed solution is capable of eliminating the fitting strains generated when machining dental prosthesis seats with a worn tool.

Development of an adaptive, self-learning control concept for an additive manufacturing process

Error avoidance in high-precision manufacturing processes becomes more important for numerous state-of-the-art technologies. Selective laser melting is one of these technologies offering large potentials in the production of complex and flexible metal products. As the technology is relatively new, it is vulnerable for errors, given that the process parameters are not measured yet. A novel multilevel control concept, incorporating several sensors, has the potential to reduce errors significantly. For inner cascade control, the laser power will be adjusted by measurements with an intensity sensor for wavelengths in the visible range. This sensor is integrated into the optical path of the laser beam. An adapted self-learning strategy supports the stability of the process by updating the parameters of the used multidimensional model in order to attenuate environmental influences or shifts within the process. This work presents the concept of the control approach, first measurement results and the required relations between measurement, process and control parameters.

Eliminating Timing Errors Through Collaborative Design to Maximize the Throughput

In advanced technology nodes, large timing margins must be added to allow for worse process, voltage, temperature, and aging variations. The error detection and correction (EDAC) technique effectively eliminates these margins by timing speculation, but the high design complexity and large hardware cost make many existing EDAC systems unsuitable for commercial processors. Based on the instruction-level locality of timing errors, a collaborative EDAC approach is proposed to address this issue. The hardware layer adopts simple and low cost EDAC circuits to ensure correct operation when timing error occurs, while a runtime software layer prevents recurring errors of the same instruction by sending timing error alarms to the hardware layer. Cooperation of both layers, accompanied with the proposed profile-guided timing error avoidance algorithm, eliminates more than 95% of errors with small runtime overhead. This significantly improves overall performance and alleviates pressure on the EDAC circuits. Experimental results based on the three-stage commercial CK802 processor in SMIC 40LL process present that the approach has improved the peak performance of the baseline EDAC system (Razor-Lite + half-frequency replay) by 8% and reduced the energy consumption by 25%, with less than 1.4% area overhead.

Imperfect practice makes perfect: error management training improves transfer of learning.

Traditionally, trainees are instructed to practise with as few errors as possible during simulation-based training. However, transfer of learning may improve if trainees are encouraged to commit errors. The aim of this study was to assess the effects of error management instructions compared with error avoidance instructions during simulation-based ultrasound training. Medical students (n = 60) with no prior ultrasound experience were randomised to error management training (EMT) (n = 32) or error avoidance training (EAT) (n = 28). The EMT group was instructed to deliberately make errors during training. The EAT group was instructed to follow the simulator instructions and to commit as few errors as possible. Training consisted of 3 hours of simulation-based ultrasound training focusing on fetal weight estimation. Simulation-based tests were administered before and after training. Transfer tests were performed on real patients 7-10 days after the completion of training. Primary outcomes were transfer test performance scores and diagnostic accuracy. Secondary outcomes included performance scores and diagnostic accuracy during the simulation-based pre- and post-tests. A total of 56 participants completed the study. On the transfer test, EMT group participants attained higher performance scores (mean score: 67.7%, 95% confidence interval [CI]: 62.4-72.9%) than EAT group members (mean score: 51.7%, 95% CI: 45.8-57.6%) (p < 0.001; Cohen's d = 1.1, 95% CI: 0.5-1.7). There was a moderate improvement in diagnostic accuracy in the EMT group compared with the EAT group (16.7%, 95% CI: 10.2-23.3% weight deviation versus 26.6%, 95% CI: 16.5-36.7% weight deviation [p = 0.082; Cohen's d = 0.46, 95% CI: -0.06 to 1.0]). No significant interaction effects between group and performance improvements between the pre- and post-tests were found in either performance scores (p = 0.25) or diagnostic accuracy (p = 0.09). The provision of error management instructions during simulation-based training improves the transfer of learning to the clinical setting compared with error avoidance instructions. Rather than teaching to avoid errors, the use of errors for learning should be explored further in medical education theory and practice.