Incorrect Actions Research Articles

СИСТЕМНЫЙ АНАЛИЗ ПРИЧИН И ФАКТОРОВ НЕЖЕЛАТЕЛЬНЫХ РЕАКЦИЙ ПРИМЕНЕНИЯ ОМАЛИЗУМАБА

The article presents a systematic analysis of the causes and factors of adverse reactions to the use of omalizumab. Methods of monitoring appeals, expert assessment, and interviewing medical specialists were applied. The analysis showed that in Russia there is a "declarative passivity" of medical workers and patients in relation to reports of adverse reactions to the use of omalizumab, which is associated with a high workload and reluctance on the part of medical workers to issue a notification, lack of knowledge about the procedure for notification, fear of being punished for possible incorrect actions on the use of the drug; on the part of patients – by not knowing their rights and the procedure for submitting a report, by fear of spoiling relations with the attending physician. Such passivity and closeness hinders the formation of a system for the prevention of drug safety violations. The data obtained in the course of the study (on the frequency and structure of adverse reactions to the use of omalizumab in clinical practice in children and adults; information on the most dangerous combinations of omalizumab with other drugs; The characteristics of the causes and factors of adverse reactions to the use of omalizumab, as well as the untimely submission of notifications about them, have become the theoretical basis for the development of recommendations for improving pharmacovigilance activities to ensure the safety of the use of omalisamab in children and adults, which includes 4 areas: creation of organizational conditions to ensure the safety of the use of omalisamab in children and adults in medical organizations; prevention of adverse reactions to the use of omalizumab at the preclinical stage; optimization of clinical choice and support for decision-making by a medical specialist (doctor) when prescribing omalizumab based on a risk-based approach, taking into account the individual characteristics of the patient and the clinical situation; improving the quality of safety monitoring of the use of omalizumab.

Simulation Strategies to Develop Undergraduate Nurses' Skills to Identify Patient Deterioration: A Quasi-Experimental Study

BackgroundGraduate nurses are unprepared to recognize and respond to patient deterioration. Simulation involving micro-debriefing with feedback and opportunities for repeated performance can improve simulated clinical practice. MethodsA prospective quasi-experimental design evaluating two simulation approaches (Standard simulation versus Rapid Cycle Intentional Simulation) recruited 138 second year undergraduate nursing students. ResultsDuring simulations the intervention groups demonstrated behaviors associated with situational awareness, in context of a deteriorating patient. Conversely control groups initiated incorrect clinical actions throughout the scenario, potentially harming the simulated patient. ConclusionsSimulation that involves interruptions and micro-debriefings has been shown to improve student performance in deteriorating patient simulations.

COLREGs Misunderstood or Ignored?

As various scholarly articles and accident investigation reports indicate, the risk of collisions at sea is still high. The objective of this research is to identify if this is due to misunderstanding of the International Regulations for Preventing Collisions at Sea 1972, as amended (COLREGs), by watchkeeping officers working onboard cargo ships. A total of 76 collisions while navigating officers (OOW) were at the con that occurred during a period of 10 years were analysed.80% of the collisions could have been avoided since one vessel was aware of the presence of the other. The highest number of collisions had taken place in cases of crossing situations. Furthermore, it is also important to note that 52% of the OOWs involved in collisions were sufficiently experienced.No evidence was found to conclude that these accidents occurred due to misinterpretation or misunderstanding of the COLREG’s by the OOW’s onboard the cargo ships, but as incorrect or insufficient action had been taken by experienced OOW’s, this could have been due to complacency and/or overconfidence on their part.Among the measures to be taken to minimize collisions at sea, overconfidence and complacency are two factors that should also require attention by all interested parties.

TA&AT: Enhancing Task-Oriented Dialog with Turn-Level Auxiliary Tasks and Action-Tree Based Scheduled Sampling

Task-oriented dialog systems have witnessed substantial progress due to conversational pre-training techniques. Yet, two significant challenges persist. First, most systems primarily utilize the latest turn's state label for the generator. This practice overlooks the comprehensive value of state labels in boosting the model's understanding for future generations. Second, an overreliance on generated policy often leads to error accumulation, resulting in suboptimal responses when adhering to incorrect actions. To combat these challenges, we propose turn-level multi-task objectives for the encoder. With the guidance of essential information from labeled intermediate states, we establish a more robust representation for both understanding and generation. For the decoder, we introduce an action tree-based scheduled sampling technique. Specifically, we model the hierarchical policy as trees and utilize the similarity between trees to sample negative policy based on scheduled sampling, hoping the model to generate invariant responses under perturbations. This method simulates potential pitfalls by sampling similar negative policy, bridging the gap between task-oriented dialog training and inference. Among methods without continual pre-training, our approach achieved state-of-the-art (SOTA) performance on the MultiWOZ dataset series and was also competitive with pre-trained SOTA methods.

Pretrained Language–Knowledge Graph Model Benefits Both Knowledge Graph Completion and Industrial Tasks: Taking the Blast Furnace Ironmaking Process as an Example

Industrial knowledge graphs (IKGs) have received widespread attention from researchers in recent years; they are intuitive to humans and can be understood and processed by machines. However, how to update the entity triples in the graph based on the continuous production data to cover as much knowledge as possible, while applying a KG to meet the needs of different industrial tasks, are two difficulties. This paper proposes a two-stage model construction strategy to benefit both knowledge graph completion and industrial tasks. Firstly, this paper summarizes the specific forms of multi-source data in industry and provides processing methods for each type of data. The core is to vectorize the data and align it conceptually, thereby achieving the fusion modeling of multi-source data. Secondly, this paper defines two interrelated subtasks to construct a pretrained language–knowledge graph model based on multi-task learning. At the same time, considering the dynamic characteristics of the production process, a dynamic expert network structure is adopted for different tasks combined with the pretrained model. In the knowledge completion task, the proposed model achieved an accuracy of 91.25%, while in the self-healing control task of a blast furnace, the proposed model reduced the incorrect actions rate to 0 and completed self-healing control for low stockline fault in 278 min. The proposed framework has achieved satisfactory results in experiments, which verifies the effectiveness of introducing knowledge into industry.

Mengatasi Siswa Sekolah Dasar yang Kesulitan dalam Mengerjakan Soal Matematika dengan Pendekatan Segitiga Restitusi

The aim of this research is to describe a model for overcoming elementary school students who have difficulty working on mathematics problems using the restitution triangle approach. Difficulty working on math problems is part of the difficulty learning mathematics. Difficulty learning mathematics is generally defined as a condition where students are unable to learn mathematics subjects completely. The restitution triangle was originally a step towards positively disciplining students. The restitution triangle approach contains aspects of a humanist approach for students. There are three steps to the restitution triangle approach, starting from stabilizing identity. This step builds confidence in students that everyone has experienced mistakes in doing questions. So that students do not feel mentally down. The second step is Validation of Incorrect Actions. In this step, students are invited to reflect on any part of the problem they got wrong and are guided to correct it, there is a remedial learning process. The third step asks about beliefs. In this step, students' motivation is increased so that students now know the steps to work on the questions, and tomorrow they will not make any more mistakes when working on the questions. The results of a literature review found that the stages of the restitution triangle in positive discipline can be used to help overcome elementary school students who have difficulty working on mathematics problems.

Abstract PR017: Enabling broad population access to facilitate gut microbiome discoveries

Abstract Microbial associations with colorectal cancer (CRC) are well recognized as well as the potential of using microbiome-based signals for broad-scale, non-invasive screening programs, particularly in underserved communities. Variability within microbiome workflows including sample collection is a contributing factor to inconsistent and non-translatable microbiome results. This limits microbiome discoveries associated with CRC and the development of such screening programs. In addition, ensuring participant and patient adherence can be a challenging prospect with fecal sample collections, and non-adherence (i.e., patient dropout, collection errors) can increasingly strain resources. An intuitively designed sample collection device should increase adherence across the general population while minimizing failed collections. Enabling the at-home collection of gut microbiome samples removes barriers between patients and testing while providing the scalability and flexibility needed for large studies or screening programs. Across two studies, 152 naïve participants were recruited to evaluate comprehension of and adherence to the OMNIgene™•GUT Dx device Instructions for Use (IFU). Both studies were designed with key considerations related to user group selection, sample size, population demographics, education level, and relevant real-world scenarios. In the first study (n=118), each participant was observed collecting one simulated “fecal” sample with representation across the Bristol scale (Type 1 to 7). The study observer conducted a follow-up interview with the participant regarding incorrect actions during collection. In the second study (n=34), participants collected one real fecal sample at home and returned it to the laboratory using standard postal services. Samples were inspected at the laboratory for collection adherence with the IFU by evaluating device closure, sufficient mixing, and DNA yield. DNA was extracted using the QIAamp PowerFecal Pro kit (QIAGEN) and quantified using PicoGreen (Invitrogen). In both studies, participants were asked to complete comprehension questionnaires to test understanding of the IFU used during collection. Participants demonstrated high rates of comprehension by answering the questions correctly 94% of the time. Participants observed collecting simulated samples demonstrated success rates of 87% for all tasks overall. Samples evaluated from the second study demonstrated participant adherence where 100% of samples were correctly returned via standard postal systems supporting at-home direct-to-consumer settings; 100% of participants properly closed the tube ensuring no loss of sample during transport; 97% of participants adequately mixed the sample; and 97% of participant samples provided sufficient DNA (≥ 120 ng) per extraction aliquot for downstream analysis. Results from these usability studies demonstrate that the OMNIgene™•GUT Dx device provides an easy-to-use at-home collection solution for diverse populations, especially at-risk, minority populations without easy access to clinical services. Citation Format: Ashlee Brown, Savannah Colameco, Tara Crawford Parks. Enabling broad population access to facilitate gut microbiome discoveries [abstract]. In: Proceedings of the 16th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2023 Sep 29-Oct 2;Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2023;32(12 Suppl):Abstract nr PR017.

Sensor deception attacks against security in supervisory control systems

This paper investigates the problem of synthesizing sensor deception attacks against security in the context of supervisory control of discrete-event systems (DES). We consider a DES plant controlled by a supervisor, whose security requirement is to maintain the initial-secret of the system undetected, i.e., it does not want to reveal the fact that it was initiated from a secret state. On the other hand, there exists an active attacker that can tamper with the observations received by the supervisor by, e.g., hacking into the communication channel between the sensors and the supervisor. The objective of the attacker is to deceive the supervisor such that the initial-secret is revealed due to incorrect control actions. We investigate the problem from the attacker’s point of view and focus on synthesizing attack strategies that threaten the security of the system. We consider two levels of success of the attacker: one requires that the attacker can detect the initial-secret of the system “almost surely” and the other only requires that the attacker has the possibility to detect the initial-secret of the system. For both cases, we present algorithms for synthesizing successful attack strategies. Our approach is based on the All Attack Structure (AAS) which records state estimates for both the supervisor and the attacker. Structural properties of the security requirements are also leveraged to reduce the synthesis complexity. A running academic example is provided to illustrate the proposed synthesis procedures.

Certain aspects of the civil legal liability of doctors (medical workers)

The article analyzes the relations “medical institution - patient”, “doctor (medical worker) - patient”, it is emphasized that such relations are based on legal equality, that is why they are civil law relations. Peculiarities of the civil liability of doctors (medical workers) for violation of patients’ rights are studied, and attention is paid to the analysis of the reasons for the emergence of civil liability of doctors. The article substantiates that the basis of civil legal liability is the presence in the actions (inaction) of a doctor (medical worker) of the composition of a civil offense, which is expressed in failure to perform, improper performance of one’s duties regarding the prevention, diagnosis, treatment of diseases of persons (patients), who requested medical assistance (service).
 During the investigation the article reveals the content of civil liability of doctors for violation of patients’ rights. Attention is drawn to the absence in the civil legislation of defining the specifics of liability regulation in the provision of the medical assistance.
 The article describes the concept and conditions of responsibility for damage caused to the patient’s health or his death. It is emphasized that civil liability occurs in the presence of illegality of actions (inaction) of a medical institution (doctors, medical workers), the presence of damage (to health, life) and a causal connection between the illegal action and damage. The author also draws attention to the presence of the fault of the medical institution.
 Scientifically based proposals and recommendations for improving the civil legislation of Ukraine in the field of health care are being formed. Legal proceedings are analyzed, the subject of which is compensation for damage caused as a result of incorrect or illegal actions of doctors (medical workers) in the performance of professional activities.

Protection for AC transmission line between DFIG wind farm and MMC station

The characteristics of power electronic controlled sources are reflected at both ends of the AC line applied to the integration of long-distance wind farms into the MMC-HVDC converter station, and the fault characteristics of the system have undergone fundamental changes. For the doubly-fed wind power AC transmission line with a modular multilevel converter, the short-circuit current characteristics provided by the power supply at both ends of the line lead to the inadaptability of longitudinal differential protection. In view of the significant difference in the complexity of the short-circuit current component provided by the doubly-fed wind power and the converter at both ends of the AC transmission line, a line pilot protection idea based on the complexity of the current component is proposed. The complexity of the current component is characterized by singular entropy theory, and then the singular entropy algorithm and its scheme for pilot protection are constructed. A refined electromagnetic transient model of MMC-HVDC for doubly-fed wind farms is built in PSCAD for simulation verification. The simulation results show that the proposed method can quickly and reliably identify various types of internal and external faults, and solve the problem of incorrect action of traditional protection in this scenario. In addition, the scheme is not affected by fault type, location, or transition resistance.

Taijiquan Auxiliary Training and Scoring Based on Motion Capture Technology and DTW Algorithm

Learning Tai Chi requires long-term practice and guidance, which is difficult for beginners. This article proposes a Tai Chi-assisted training and scoring method based on motion capture technology and a dynamic time warping (DTW) algorithm. Firstly, by using motion capture technology, the key point data of Tai Chi movements can be accurately captured. Then, using the DTW algorithm, the learner's action sequence is compared and matched with the standard Tai Chi action sequence in order to evaluate the learner's action accuracy and fluency. Learners can promptly correct incorrect actions and improve the accuracy and fluency of their actions. This method has significant advantages in accuracy and reliability. In summary, the Tai Chi-assisted training and scoring method based on motion capture technology and DTW algorithm provides an effective auxiliary tool for Tai Chi learners, which can help them better master the techniques and essence of Tai Chi. This study is of great significance for promoting the popularization of Tai Chi and improving the learning effectiveness of Tai Chi.

Temporal unpredictability increases error monitoring as revealed by EEG-EMG investigation.

Reacting in an unpredictable context increases error monitoring as evidenced by greater error-related negativity (ERN), an electrophysiological marker linked to an evaluation of response outcomes. We investigated whether ERN also increased when participants evaluated their responses to events that appeared in unpredictable versus predictable moments in time. We complemented electroencephalographic (EEG) analysis of cortical activity by measuring performance monitoring processes at the peripheral level using electromyography (EMG). Specifically, we used EMG data to quantify how temporal unpredictability would affect motor time (MT), the interval between the onset of muscle activity, and the mechanical response. MT increases following errors, indexing online error detection, and an attempt to stop incorrect actions. In our temporally cued version of the stop-signal task, symbolic cues predicted (temporally predictable condition) or not (temporally unpredictable condition) the onset of a target. In 25% of trials, an auditory signal occurred shortly after the target presentation, informing participants that they should inhibit their response completely. Response times were slower, and fewer inhibitory errors were made during temporally unpredictable than predictable trials, indicating enhanced control of unwanted actions when target onset time was unknown. Importantly, the ERN to inhibitory errors was greater in temporally unpredictable relative to temporally predictable conditions. Similarly, EMG data revealed prolonged MT when reactions to temporally unpredictable targets had not been stopped. Taken together, our results show that a temporally unpredictable environment increases the control of unwanted actions, both at cortical and peripheral levels, suggesting a higher subjective cost of maladaptive responses to temporally uncertain events.

The role of impulse and interference control in aversive personality: A comprehensive assessment

Ethically and socially aversive behaviors have been attributed to several personality traits, including characteristics collectively referred to under the umbrella term of impulsivity. It is an open question, however, whether such characteristics are an integral part of ethically and socially aversive personality. Relying on three large samples (total N = 9854) and implementing longitudinal assessments, the present study provides a comprehensive investigation of the role of impulse and interference control in aversive personality. Based on contemporary conceptualizations of the impulsivity domain, a total of 17 dimensions spanning both self-reports and behavioral tasks are assessed. To represent aversive personality, we consider the D Factor of Personality (D), i.e., the basic disposition shared by all aversive traits. Results indicate that D co-occurs with a deficit in inhibiting the incorrect action when multiple actions are available, a preference for immediate rewards while failing to consider the consequences of one's actions, and maladaptive behavior directed towards regulating strong affect. However, most associations between D and dimensions of impulsivity were small or non-significant, thereby disconfirming the notion that characteristics related to a lack of impulse control are an integral feature of aversive personality in general.

Deep Reinforcement Learning DDPG Algorithm with AM based Transferable EMS for FCHEVs

Hydrogen fuel cell is used to run fuel cell hybrid electrical vehicles (FCHEVs). These FCHEVs are more efficient than vehicles based on conventional internal combustion engines due to no tailpipe emissions. FCHEVs emit water vapor and warm air. FCHEVs are demanding fast dynamic responses during acceleration and braking. To balance dynamic responsiveness, develop hybrid electric cars with fuel cell (FC) and auxiliary energy storage source batteries. This research paper discusses the development of an energy management strategy (EMS) for power-split FC-based hybrid electric cars using an algorithm called deep deterministic policy gradient (DDPG) which is based on deep reinforcement learning (DRL). DRL-based energy management techniques lack constraint capacity, learning speed, and convergence stability. To address these limitations proposes an action masking (AM) technique to stop the DDPG-based approach from producing incorrect actions that go against the system's physical limits and prevent them from being generated. In addition, the transfer learning (TL) approach of the DDPG-based strategy was investigated in order to circumvent the need for repetitive neural network training throughout the various driving cycles. The findings demonstrated that the suggested DDPG-based approach in conjunction with the AM method and TL method overcomes the limitations of current DRL-based approaches, providing an effective energy management system for power-split FCHEVs with reduced agent training time.

Use cases also exist for attackers—how to foster the concept of misuse cases

Due to the new digital control structures of cyber-physical energy systems (CPES), where the control interventions no longer take place physically on site but are triggered, released, executed and acknowledged remotely by automated control systems, there is not only the risk of incorrect actions by plants or operators, but also of possible attacks or misuses. In this contribution, we propose an integrated security-by-design approach (on a conceptual level) for testing the interoperability of various heterogeneous systems (e.g., TSO-DSO communications) by combining multiple, but yet separated, state-of-the-art approaches. With the objective of eliminating or minimizing the impact of cyber incidents, best practices from various sectors have been adapted and integrated with well-established methods and standards from the energy sector, such as the IEC 62559‑2 use case template.

Discrimination between internal faults and inrush currents in power transformers based on the discriminative-feature-focused CNN

Overcoming the drawback of the incorrect action of differential protection induced by the inrush current is a crucial issue for transformer protection. This paper proposes a deep learning protection scheme based on a discriminative-feature-focused convolutional neural network to improve the protection accuracy. Considering that internal faults and inrush currents can be reliably distinguished based on the unsaturated part of the differential current, the three-module network and specialized loss function are designed to guide the proposed network to extract the discriminative features of the unsaturated part of the differential current. By focusing on discriminative features with invariance and robustness, the proposed method presents high accuracy and remedies the problem of the limited generalization ability of artificial-intelligence-based protection in engineering applications. Test results on various datasets show that the proposed scheme can accurately identify transformer states with good robustness to noise and generalization to complex scenes, such as CT saturation, overexcitation, and field data. A time-consuming test deployed on hardware shows that this algorithm meets the protection time requirements. The comparison with previous methods confirms the superior reliability and generalization ability of the proposed scheme.

Detection of Pilot's Mental Workload Using a Wireless EEG Headset in Airfield Traffic Pattern Tasks.

Elevated mental workload (MWL) experienced by pilots can result in increased reaction times or incorrect actions, potentially compromising flight safety. This study aims to develop a functional system to assist administrators in identifying and detecting pilots' real-time MWL and evaluate its effectiveness using designed airfield traffic pattern tasks within a realistic flight simulator. The perceived MWL in various situations was assessed and labeled using NASA Task Load Index (NASA-TLX) scores. Physiological features were then extracted using a fast Fourier transformation with 2-s sliding time windows. Feature selection was conducted by comparing the results of the Kruskal-Wallis (K-W) test and Sequential Forward Floating Selection (SFFS). The results proved that the optimal input was all PSD features. Moreover, the study analyzed the effects of electroencephalography (EEG) features from distinct brain regions and PSD changes across different MWL levels to further assess the proposed system's performance. A 10-fold cross-validation was performed on six classifiers, and the optimal accuracy of 87.57% was attained using a multi-class K-Nearest Neighbor (KNN) classifier for classifying different MWL levels. The findings indicate that the wireless headset-based system is reliable and feasible. Consequently, numerous wireless EEG device-based systems can be developed for application in diverse real-driving scenarios. Additionally, the current system contributes to future research on actual flight conditions.

Knowing the Education Business and Politics of Modern Guanxi Confucian Societies In Bengkalis Island

Understanding modern Confucius Guanxi politics and business is a new science for business and politics that focuses on trust and mutual benefit between people. This means that people must maintain relationships, share information, solve problems, and seek opportunities to increase value for themselves and for others. This theory also emphasizes the importance of protecting power and complying with applicable business rules and norms. Writing this article is a review of the science of politics and business of Confucian Guanxi both in terms of good and bad. Theory and its applications are very useful for providing different views and perspectives on how to think and do things. However, the lack of politics and business with Bibliometric Analysis using VOSviewer and Publish or Perish. Confucian Guanxi can lead to incorrect understanding and action. For example, the classical theory of economics provides the view that markets will always move toward equilibrium, but this contradicts the fact that most markets in the world are unstable. This has led economists to develop new, more realistic theories. Another negative side of Confucian Guanxi political and business theories is that they can be misinterpreted. Another negative side of Confucian Guanxi political and business theories is that they can be misinterpreted. For example, some people may use psychological theory to claim that people with certain characteristics have limitations that prevent them from achieving their goals. This can lead to assault and exclusion. This theory also has another negative side. They can limit a person's thinking and limit their way of seeing the world. Some people may use theory to support their unfavorable views on certain political and business subjects.

A review of the possibilities of gene doping in sports focused on the advantages and disadvantages

Introduction and purpose: Gene therapy can be defined as a modification of gene expression in a patient's body. There are two main strategies: the abuse of "classical" gene therapy and strategies of RNA interference with gene transfer. The aim of the study is to analyze scientific literature on gene doping, with a focus on the advantages and disadvantages of using genes related to sports.
 Materials and methods: The literature available on PubMed was reviewed using the words “gene therapy”, “sport”.
 Description of the state of knowledge: 
 The potential modification of genes such as EPO, IGF1/GH, HIF-1, PPAR have been identified as having beneficial effects for athletes. Modifying the EPO gene could lead to an increase in red blood cells and oxygen in the blood, which could increase muscle endurance. Modification of the IGF1/GH gene can lead to muscle hypertrophy, block muscle atrophy. The HIF-1 gene codes proteins involved in the hypoxia process and can increase endurance by facilitating the adaptation of cells to low oxygen conditions. Modifying the PPAR gene can impact carbohydrate and lipid metabolism, regulating body mass. Gene therapy could provide a potential cure for diseases such as acute anemia and muscular dystrophy. However, it is important to consider the ethical and health implications of gene doping.
 Summary: "Gene doping" is a practice that can lead to improved athletic performance but also to serious health problems. The introduction of regulations and doping tests detecting changes in the genome would exclude this practice among athletes who take risky and morally incorrect actions. Increasing the expression of genes such as EPO, IGF-1, HIF-1, PCK1 results in increased muscle endurance and performance. Further research is needed to understand the exact mechanisms and effects of gene therapy. Genetic modification has the potential to bring benefits such as treating diseases such as acute anemia resulting from kidney failure.

A Formal Metareasoning Model of Concurrent Planning and Execution

Agents that plan and act in the real world must deal with the fact that time passes as they are planning. When timing is tight, there may be insufficient time to complete the search for a plan before it is time to act. By commencing execution before search concludes, one gains time to search by making planning and execution concurrent. However, this incurs the risk of making incorrect action choices, especially if actions are irreversible. This tradeoff between opportunity and risk is the problem addressed in this paper. Our main contribution is to formally define this setting as an abstract metareasoning problem. We find that the abstract problem is intractable. However, we identify special cases that are solvable in polynomial time, develop greedy solution algorithms, and, through tests on instances derived from search problems, find several methods that achieve promising practical performance. This work lays the foundation for a principled time-aware executive that concurrently plans and executes.