Decision Time Research Articles

Configuration and optimisation of a green closed-loop supply chain with delivery time and green investment considering government subsidy under meta-heuristics algorithms

Consumers' environment consciousness, together with the fierce rivalries among companies, has attracted increasing attention from scholars and industries to the configuration and optimisation of green closed-loop supply chain. However, current studies of closed-loop supply chains rarely consider both the uncertainty from the market and the quality from the recycled used products. Therefore, this article constructs a green closed-loop supply chain total profit model that considers government subsidies, delivery times, green investment and the above uncertainties. Fuzzy chance constraint method is used to solve the uncertain demand; genetic and particle swarm optimisation algorithms are adopted to calculate the model. This study finds (1) enterprises can formulate flexible and adaptable strategies based on different demands; (2) their delivery time decisions rely on both consumer demand and their logistics development levels; (3) enterprises should adjust their delivery times and green investment decisions according to consumers' different sensitivities; (4) enterprises can increase profits by recycling products within a certain range of greenness; (5) for improving recycling and remanufacturing rates, the government can provide secondary subsidies to enterprises for product recycling within the green range of 0.35 ∼ 0.40. This study contributes to the optimisation of strategies developed by enterprises under conditions of subsidies and multiple uncertainties.

Transforming Agriculture with Advanced Robotic Decision Systems via Deep Recurrent Learning

Global farming methods have improved owing to supply demand, human resource shortages, and seasonal fluctuations. Integrating automated mechanics, smart controllers, and artificial intelligence has become imperative to tackle these problems. Through self-learning and wise decision-making, this integration speeds up processing and encourages sustainability. To help modern farming techniques become more efficient and environmentally friendly, this paper presents a Pliant Decision System (PDS) specifically made for Farming Robots (FRs). The FRs are designed to be time-synchronized and multi-operational, which allows for guided agricultural practices that provide sustainable results. The robotic operations are planned to finish the agricultural processes with individual sustainability verification once they are first classified according to traditional techniques. Two layers of deep recurrent learning are used to evaluate sustainability. Verifying individual completion and sustainability via timely execution and cumulative effect is the primary emphasis of the first layer. In the second layer, the seasonal consistency of production improvements is compared using dual analyses. By training the learning model to synchronize and complete robotic activities promptly, people can execute judgments and synchronize successive agricultural operations throughout the year. The proposed method outwits the existing methods by leveraging sustainable factors by 8.24%, completion by 11.1%, promptness by 7.79%, synchronization by 6.75%, and reducing decision time by 12.07% for the varying process times.

Age added to MELD or ACLF predicts survival in patients with alcohol-associated hepatitis declined for liver transplantation.

Severe alcohol-associated hepatitis (AH) that is nonresponsive to corticosteroids is associated with high mortality, particularly with concomitant acute-on-chronic liver failure (ACLF). Most patients will not be candidates for liver transplantation (LT) and their outcomes are largely unknown. Our aim was to determine the outcomes of these declined candidates and to derive practical prediction models for transplant-free survival applicable at the time of the waitlist decision. We analyzed a database of patients with severe AH who were hospitalized at a LT center from January 2012 to July 2021, using the National Death Index for those lacking follow-up. Clinical variables were analyzed based on the endpoints of mortality at 30, 60, 90, and 180 days. Logistic and Cox regression analyses were used for model derivation. Over 9.5 years, 206 patients with severe AH were declined for LT, mostly for unfavorable psychosocial profiles, with a mean MELD of 33 (±8), and 61% with ACLF. Over a median follow-up of 521 (17.5-1368) days, 58% (119/206) died at a median of 21 (9-124) days. Of 32 variables, only age added prognostic value to MELD and ACLF grade. CLIF-C ACLF score and 2 new models, MELD-Age and ACLF-Age, had similar predictability (AUROC: 0.73, 0.73, 0.72, respectively), outperforming Lille and Maddrey's (AUROC: 0.63, 0.62). In internal cross-validation, the average AUROC was 0.74. ACLF grade ≥2, MELD score >35, and age >45 years were useful cutoffs for predicting increased 90-day mortality from waitlist decision. Only two patients initially declined for LT for AH subsequently underwent LT (1%). Patients with severe AH declined for LT have high short-term mortality and rare rates of subsequent LT. Age added to MELD or ACLF grade enhances survival prediction at the time of waitlist decision in patients with severe AH declined for LT.

Understanding the Role of Eye Movement Pattern and Consistency in Isolated English Word Reading Through Hidden Markov Modeling.

In isolated English word reading, readers have the optimal performance when their initial eye fixation is directed to the area between the beginning and word center, that is, the optimal viewing position (OVP). Thus, how well readers voluntarily direct eye gaze to this OVP during isolated word reading may be associated with reading performance. Using Eye Movement analysis with Hidden Markov Models, we discovered two representative eye movement patterns during lexical decisions through clustering, which focused at the OVP and the word center, respectively. Higher eye movement similarity to the OVP-focusing pattern predicted faster lexical decision time in addition to cognitive abilities and lexical knowledge. However, the OVP-focusing pattern was associated with longer isolated single letter naming time, suggesting conflicting visual abilities required for identifying isolated letters and multi-letter words. In contrast, in both word and pseudoword naming, although clustering did not reveal an OVP-focused pattern, higher consistency of the first fixation as measured in entropy predicted faster naming time in addition to cognitive abilities and lexical knowledge. Thus, developing a consistent eye movement pattern focusing on the OVP is essential for word orthographic processing and reading fluency. This finding has important implications for interventions for reading difficulties.

The effects of SNAP emergency allotments on state-level SNAP benefits and enrollment during the COVID-19 pandemic.

During the COVID-19 pandemic, all US states provided emergency allotments (EA) to enrollees of the Supplemental Nutrition Assistance Program (SNAP) to alleviate rising food insecurity. However, 18 states opted out of the SNAP-EA program before its official expiration in February 2023. Using a staggered difference-in-differences model to account for state-level variation in the timing of the SNAP-EA opt-out decisions, we analyzed SNAP and SNAP-EA data from the US Department of Agriculture Food and Nutrition Service to quantify the impact of state opt-out decisions on SNAP benefit size and enrollment. We found that the average SNAP monthly benefit among 18 SNAP opt-out states was reduced by $183 (95% confidence interval [CI]: -$214, -$152) per beneficiary. The percentage of the state population enrolled in the SNAP program among the opt-out states modestly decreased by 0.35 (95% CI: -0.61, -0.10) percentage points. Additionally, we employed logistic regression models to associate state opt-out decisions with state-level characteristics. We found that the state governor's political party being Republican was the only significant predictor for the state's opt-out decisions. Our findings help explain why opting out of SNAP-EA has been associated with higher food insufficiency and shed light on the impact of political decisions to opt out of SNAP-EA on the lives of millions of Americans.

Real-Time Optimal Scheduling of a Water Diversion System Using an Improved Wolf-Pack Algorithm and Scheme Library

A water diversion system (WDS) with cascade pumping stations (CPSs) plays an important role in the application of water resources. However, high energy consumption is reported due to unreasonable scheduling schemes and long decision times. Herein, this paper presents a new method to achieve optimal scheduling schemes effectively, including the head allocation of CPSs, the number of running pumps, and pump blade angles. A double-layer mathematical model for a WDS was established with the goal of achieving minimal energy consumption, considering the constraints of flow rate, water level, and the characteristics of pump units. The inner-layer model was used to obtain scheduling schemes of single-stage pumping stations, as well as the water levels and flow rates of water channels, while the outer-layer model was used to optimize inter-stage head allocation. An improved wolf-pack algorithm (IWPA) was proposed to solve the model, using a Halton sequence to obtain the uniform initial population distribution and introducing simulated annealing (SA) to improve the global searchability. Moreover, an idea for a pre-established scheme library was suggested for inner-layer models to obtain the solutions in real time with less calculation workload. Taking an actual project as a case, in contrast with the actual schemes, the optimal scheduling method could result in energy savings of 14.37–20.39%, a CO2 emission reduction of 13–32 tons per day, and water savings of 0.14–18.34%. Moreover, the time complexity decreased to square order, and the CPU time of the optimal method was about 1% that of the traditional method. This study provides an efficient method for the high-value utilization of energy and water resources for a WDS.

A Methodological Approach to Assembly Time Standard Estimation Based on Incomplete Characteristics of the Production Process and Using Small Databases

The problem solved in this article concerns assembly planning, which is time-consuming, but crucial in the development of mechanical products. At the product design stage there is no complete information about the manufacturing process, so it is necessary to develop an approach to help process the uncertain and incomplete information. In order to compare different product variants, the assembly time standard has to be estimated on the basis of the incomplete product and production process characteristics. This paper presents a method for estimating the assembly time standard using time classes, decision tree and evidence theory.

A dual-channel multimodal sentiment analysis framework based on three-way decision

In the exploration of human–computer interaction, accurately identifying and understanding the user’s sentimental state helps enhance the user experience. Multimodal sentiment analysis aims to identify sentiments through various signals. However, inconsistencies in sentiments between text and visual–audio signals pose a challenge, as models often struggle to capture these differences adequately. To alleviate this issue, we propose a dual-channel sentiment analysis framework based on three-way decision. This framework includes a multimodal model, a visual–audio model, and a three-way decision module. Specifically, the multimodal model and visual–audio model generate predictions, and the three-way decision module selects an appropriate prediction. We improve the binary cross-entropy loss function for the visual–audio model to integrate the three-way decision module better and improve sentiment prediction accuracy. Additionally, we introduce an adversarial training task to ensure differences in predictions between the two models, thereby enhancing the influence of the visual–audio model. Experimental results on four public datasets demonstrate that our framework significantly improves the accuracy of sentiment recognition and reduces the average decision time.

Open Abdominal Management for Damage Control in Liver Transplantation: A Single-center Experience.

Patients undergoing liver transplantation are in a state of coagulopathy before surgery because of liver failure. Intraoperative hemorrhage, massive transfusions, and post-reperfusion syndrome further contribute to coagulopathy, acidosis, and hypothermia. In such situations, temporary cessation of surgery with open abdominal management and resuscitation in the intensive care unit (ICU), which is commonly used as a damage control strategy in trauma care, may be effective. We assessed the outcomes of open abdominal management in liver transplantation and the corresponding complication rates. We retrospectively reviewed the outcomes of patients undergoing open abdominal management among 250 consecutive liver transplantation cases performed at our institution from 2009 to 2022. Open abdominal management was indicated in 16 patients. The open abdomen management group had higher Model for End-stage Liver Disease scores (24 versus 16, P < 0.01), a higher incidence of previous upper abdominal surgery (50% versus 18%, P < 0.01), more pretransplant ICU treatment (31% versus 10%, P = 0.03), and more renal replacement therapy (38% versus 12%, P = 0.01). At the time of the damage control decision, coagulopathy (81%), acidosis (38%), hypothermia (31%), and a high-dose noradrenaline requirement (75%) were observed. The abdominal wall was closed in the second operation in 75% of patients, in the third operation in 19%, and in the fourth operation in 6%. Postoperatively, the frequency of early allograft dysfunction was predominantly higher in the open abdominal management group (69%), whereas the frequency of vascular complications and intra-abdominal infection was the same as in other patients. Open abdominal management can be a crucial option in cases of complex liver transplant complicated by conditions such as hypothermia, acidosis, coagulopathy, and hemodynamic instability. Damage control management minimizes deterioration of the patient's condition during surgery, allowing completion of the planned procedure after stabilizing the patient's overall condition in the ICU.

Progress Decisions Involving Time: Sunk Cost or Completion Effects

ABSTRACTFive studies involving seven samples were conducted to examine the effects of sunk time in progress decisions. Previous research on sunk time in progress decisions has failed to control for completion effects. Studies 1a and 1b found strong evidence for completion effects and weaker effects for sunk time effects on probability of continuing. In Studies 2a and 2b, we expanded our sunk time scenarios to use multiple types. We found evidence for sunk time and completion effects on probability of continuing. An additional analysis, however, found that the sunk time effect was larger when the progress decision involved a goal focused on the accomplishment of a project (e.g., writing a paper for class), as opposed to a goal focused on enjoyment (e.g., watching a television show). Study 3 found that both sunk time and completion effects were present in progress decisions focused on the accomplishment of a project. These effects were present even when participants were informed that there was sufficient time to complete an alternative project. Study 4 failed to find a sunk time effect in a behavioral study, and Study 5 replicated Study 4 using a vignette format. Overall, these results provide some evidence of sunk time effects in progress decisions, but the effect appears to be small and may be due, at least partially, to completion effects.

Research on Train Loading and Unloading Mode and Scheduling Optimization in Automated Container Terminals

In some automated container terminals, railway lines have been implemented into the port, saving container transfer time. However, the equipment scheduling level of the railway yard needs to be improved for managers. In the equipment scheduling of loading and unloading containers for railway trains, the operation modes “full unloading and full loading” and “synchronous loading and unloading” are often adopted. Due to the long length of the railway yard and the line of one train, there are two ways to arrange loading and unloading tasks for automated rail-mounted gantry cranes (ARMGs): one is to pre-assign tasks for ARMGs, and the other is to not pre-assign tasks for ARMGs. To investigate the efficacy of these different operation modes and methods of assigning tasks, this study formulated three mixed-integer linear programming (MILP) models with the goal of minimizing the ARMG task completion time. An adaptive large neighborhood search algorithm was used to tackle the scheduling problem. The scheduling effects of different operation modes and methods for assignment tasks were compared in terms of their calculation time and the completion time of ARMG tasks. Notably, the findings reveal that, with an increase in the number of tasks, the “pre-assign” task arrangement had a limited effect on the completion time of the ARMG tasks, made the calculation time shorter, and reduced the complexity of the problem. From the perspective of the completion time of ARMG tasks, the time under the “synchronous loading and unloading” operation mode was less than that of the “full unloading and full loading” operation mode. Therefore, it is recommended that the managers of the railway yard in an automated container terminal adopt the “synchronous loading and unloading” operation mode but determine the task assignment method according to decision time requirements. In addition, when the number of tasks is large, to decrease the time to complete ARMG tasks, the manager can adopt the “non-pre-assign” task distribution method.

Evaluation of drug litigation against the Campinas municipal health system from 2017 to 2021

In Brazil, the judicialization of public health for access to medications has resulted in significant challenges to the management of public policies, especially at the municipal level. To evaluate the profile of drug litigations against the Campinas municipal health system from 2017 to 2021, this study analyzed the characteristics of litigants, medicine dispensation, and the timing of court decisions. A quantitative, analytical, and comparative cross-sectional study was conducted using data on the dispensation of 506 types of medications and 493 court cases. The analysis included sociodemographic, procedural, medical–sanitary, and pharmaceutical assistance management variables. The time of court decisions was assessed using the Kruskal‒Wallis test complemented by the Dunn test. The plaintiffs were predominantly adults, females, and self-declared students, and some cases involved nonresidents. Most of the lawsuits were represented by private lawyers, gratuitousness of justice and with decisions favorable to the plaintiff. However, only 43% of the patients obtained a preliminary injunction or early tutelage. The median time needed for a court decision from the date of case filing was 12 days until the granting of a preliminary injunction or early tutelage and 6.5 months until a judgment or dismissal without a decision on the merits. Approximately 32.4% of the medications dispensed by the judicial pharmacy already belonged to the list of the Brazil’s Unified Health System in 2020; 46.3% were prescribed by their generic name; 75.5% had therapeutic equivalents, and 94.9% had marketing authorization from the Brazilian National Health Surveillance Agency. Judicialization in Campinas is an alternative way of accessing medications, but it is time-consuming and benefits only a small portion of the population (0.068%). The characteristics of the plaintiffs and judicialized medicines highlight the need to review health policies to promote equitable and efficient access to essential treatments for the population.

Differential games in the supply chain of innovative products with consumer purchase regret induced returns.

Innovative products entering the market will cause dynamic changes in market demand, and consumers' purchase regret and their return behavior make the market environment more and more complex, which in turn affects the dynamic decision-making in the supply chain. In this paper, under the situation of discrete decision time, combining with the objective reality, we make discrete modification to the classical Bass diffusion model (Bass model), construct a manufacturer-led, retailer-followed supply chain differential game model, analyze the optimal decision-making of the manufacturer and the retailer by combining with the theory of discrete optimal control, and then verify the conclusions by numerical simulation. The results show that: when retailers purchase directly from the manufacturer and sell in the market, the optimal pricing of the innovative product can make the supply chain as a whole, realizing Pareto optimality; consumer's purchase regret will increase the amount of returns, which will lead to the decrease of product sales and the profits of the manufacturer and the retailer; when the innovative product accounts for a different share of the market, the impact of purchase regret on the wholesale price and the retail price are also different. Therefore, manufacturers need to have an extensive comprehension of the market to minimize the negative effects of consumer regret and returns, and to formulate a reasonable pricing strategy for their products to gain as much profit as possible.

Effect of Bedside Ultrasound-Guided Versus Fluoroscopy-Guided Transvenous Cardiac Temporary Pacing in Children with Bradyarrhythmia.

To compare the efficacy and safety of bedside ultrasound-guided and fluoroscopy-guided transvenous cardiac temporary pacing in the treatment of bradyarrhythmia in children. Children treated by temporary intravenous cardiac pacing from January 2016 to June 2023 in Hunan Provincial Children's Hospital were enrolled, and the characteristics and data of the cases were summarized. Patients were divided into bedside ultrasound-guided group (ultrasound group) and fluoroscopy-guided group (fluoroscopy group) according to the implantation guidance methods. The efficacy, safety, and incidence of complications in children were compared, and follow-up analysis was carried out. A total of 30 children were enrolled, including 18 males and 12 females, with a median age of 5.5 (2.9, 10.0) years and a median weight of 18.7 (12.7, 32.7) kg. The most common primary diseases were fulminant myocarditis (13/30 cases) and congenital high-grade AVB (10/30 cases). Among them, the proportion of congenital high AVB in the fluoroscopy group was significantly higher than that in the ultrasound group, and the difference was statistically significant (p = 0.007). The implantation process was successful in all 30 children. From the time of pacing decision to implantation, the median time of ultrasound group was 56 (30, 60) min and that of fluoroscopy group was 154 (78,180) min, with a statistically significant difference (P < 0.001). A total of 5 cases developed complications. There was no statistically significant difference between the two groups (P > 0.05). Compared with traditional fluoroscopic temporary pacing, bedside ultrasound-guided temporary pacing technology can effectively shorten the operation time and reduce the occurrence of complications and has become a better choice for children's emergency and critical care treatment. The right internal jugular vein is preferred for intravenous implantation.

Execution of decisions of the Constitutional Court of Ukraine: separate doctrinal approaches

It is indicated that the key problem in the activity of the Constitutional Court of Ukraine is ensuring the implementation of its decisions. Without solving this issue, it is impossible to guarantee the supremacy of the Constitution, the principle of separation of powers and the existence of an independent judicial branch of government as a separate institution. Ignoring the decisions of the constitutional control body undermines the very system of checks and balances, the authority of the Basic Law and the constitutional order in the country in general. These principles underlie the implementation of decisions of constitutional courts, the purpose of which is to ensure constitutional legality. In Ukraine, the mechanism for the implementation of the decisions of the Central Committee of Ukraine has already been developed in general, but there are problems related to the non-implementation of some of its decisions for a long time. Therefore, the task of further improvement of this mechanism and its proper legislative regulation remains relevant. The authors claim that Ukraine has already developed a mechanism for implementing decisions of the Constitutional Court. However, this system is not perfect, which is evidenced by the fact of non-execution of individual court decisions. Therefore, the issue of continuing the work on improving the existing mechanism for implementing decisions of the body of constitutional jurisdiction, securing it properly at the legislative level, remains urgent. At the same time, the problem of the quality of such execution comes to the fore, for the solution of which it is necessary to develop criteria for the effectiveness of the execution of court decisions, which will allow to assess the quality of the legal acts that are introduced and the work of the responsible entities. Both outlined problems definitely need further thorough scientific research. In addition, according to the authors, it should be noted that the issues of the legal nature of the legal positions of the Constitutional Court of Ukraine and the criteria for the effective implementation of its decisions remain interacting categories and, therefore, require thorough scientific study. At the same time, clarifying the legal force of the Court’s legal positions is complicated by the lack of their legislative definition, by a certain difficulty in understanding the role and place of the body of constitutional jurisdiction in the system of state power. At the same time, the legal positions have a normative and mandatory character, reflected in the acts of the KSU. The need to ensure their immutability follows from the principles of legal certainty and stability of the Constitution. However, the possibility of revising some legal positions in connection with the change in the socio-political structure of the state is gaining relevance.

The SEER Program's evolution: supporting clinically meaningful population-level research.

Although the Surveillance, Epidemiology, and End Results (SEER) Program has maintained high standards of quality and completeness, the traditional data captured through population-based cancer surveillance are no longer sufficient to understand the impact of cancer and its outcomes. Therefore, in recent years, the SEER Program has expanded the population it covers and enhanced the types of data that are being collected. Traditionally, surveillance systems collected data characterizing the patient and their cancer at the time of diagnosis, as well as limited information on the initial course of therapy. SEER performs active follow-up on cancer patients from diagnosis until death, ascertaining critical information on mortality and survival over time. With the growth of precision oncology and rapid development and dissemination of new diagnostics and treatments, the limited data that registries have traditionally captured around the time of diagnosis-although useful for characterizing the cancer-are insufficient for understanding why similar patients may have different outcomes. The molecular composition of the tumor and genetic factors such as BRCA status affect the patient's treatment response and outcomes. Capturing and stratifying by these critical risk factors are essential if we are to understand differences in outcomes among patients who may be demographically similar, have the same cancer, be diagnosed at the same stage, and receive the same treatment. In addition to the tumor characteristics, it is essential to understand all the therapies that a patient receives over time, not only for the initial treatment period but also if the cancer recurs or progresses. Capturing this subsequent therapy is critical not only for research but also to help patients understand their risk at the time of therapeutic decision making. This article serves as an introduction and foundation for a JNCI Monograph with specific articles focusing on innovative new methods and processes implemented or under development for the SEER Program. The following sections describe the need to evaluate the SEER Program and provide a summary or introduction of those key enhancements that have been or are in the process of being implemented for SEER.

A Novel Method of 3D Lyapunov Guidance Vector Field to Avoid Intercepting Satellite Based on Reinforcement Learning

This paper proposes a new 3D Lyapunov guidance vector field(3D-LGV) avoidance strategy based on reinforcement learning for the satellite evasion and interception problem. Combining it with the interfered fluid dynamical system (IFDS) enables the satellite to evade and smoothly enter orbit according to the state of the intercepting satellite in real time. 3D-LGV provides an initial flow field approaching an elliptical orbit, while IFDS provides a perturbed flow field based on the intercepting satellite position. The combined potential field of the initial flow field and the disturbed flow field is the planned velocity direction of the satellite. As a decision-making layer, the proximal policy optimization (PPO) dynamically adjusts the perturbed flow field in the IFDS to increase the avoidance success rate in different scenarios. The experimental results show that, compared with the particle swarm optimization with rolling horizon control algorithm, the algorithm proposed in this paper has a shorter decision time and a higher avoidance success rate. At the same time, Monte Carlo simulation shows that the evasion success rate of the proposed algorithm reaches 98%.

Effect of COVID-19 Shelter-In-Place Orders on Visual Outcomes of Ophthalmic Surgical Emergencies

ABSTRACT Purpose To compare the outcomes of ophthalmic surgical emergencies during shelter-in-place (SIP) order with the corresponding period in 2019. Methods This retrospective cohort study compared patients presenting to the Bascom Palmer Eye Institute (BPEI) emergency department (ED) who underwent urgent surgery during the SIP period (March 23–May 17, 2020), compared to the same weeks in 2019 (non-SIP). Main outcome measures included symptom-to-ED time, ED-to-surgical decision time, surgical decision-to-operating room (OR) time, ED-to-OR time, and postoperative follow-up time. Secondary outcome measures included travel distance, visual acuity (VA), intraocular pressure (IOP), and number of glaucoma medications. Results Seventy-six and 148 patients presented with ophthalmic surgical emergencies in the SIP and non-SIP study periods, respectively. Retinal detachment (RD), acute glaucoma, and open globe injury were the most common diagnoses in both periods. Symptom-to-ED and surgical decision-to-OR times were shorter during the SIP period. SIP patients had comparable preoperative VA but worse postoperative VA compared to non-SIP patients. During the SIP period, RD patients experienced postoperative VA reduction rather than improvement (+0.09 vs. −0.23 logMAR, p = 0.03); glaucoma patients were less likely to reach surgical decision within 24 h (OR 0.16 [95% CI 0.03–0.95]); and globe injuries had longer ED-to-surgical decision time and ED-to-OR time compared to the non-SIP period. Other outcomes were similar between both study periods. Conclusion There was reduced volume of ophthalmic surgical emergencies and worse postoperative vision during SIP compared to the non-SIP period, despite shorter symptom-to-ED and surgical decision-to-OR times suggesting minimal delays in seeking or receiving care.

An Original Remote Digital Serious Game for Neonatal Resuscitation Training: New Opportunities from COVID-19 Era.

Background: The social restrictions imposed by the COVID-19 pandemic have disrupted traditional teaching methods and encouraged the development of innovative and safer approaches based on distance learning. Among these novel techniques, digital game-based learning (DGBL) is a method that facilitates learning through the efficient use of interactive software tailored to the user. Methods: In this work, we investigated the effectiveness of the DGBL methodology for remote training using a game-based digital learning software designed about remote neonatal resuscitation. The DGBL approach was validated in 52 anesthesiologist trainees and compared to a homogenous retrospective control group of pediatric trainees with the same prior knowledge, who followed an in-person training course using the digital serious game. Scores obtained during each game session are recorded and used to assess progress in knowledge of the flowchart, decision time, timing of assisted ventilation, and ability to check equipment. Results: The results confirmed the effectiveness of the remote training mode for each of the analyzed features, whereas no statistically significant advantages of using a supervised DGBL were found. Conclusion: In conclusion, the DGBL remote training approach is a valuable tool that can provide users with an interactive, effective, and enjoyable learning experience. Future developments will concern the implementation of multiplayer versions to stimulate interaction between users for the development of inter-professional and teamwork skills.

Confidence Is Influenced by Evidence Accumulation Time in Dynamical Decision Models

Confidence judgments are closely correlated with response times across a wide range of decision tasks. Sequential sampling models offer two competing explanations for the relationship between confidence and response time: According to some models, decision time directly influences confidence. Other models explain the correlation by linking subjective confidence computation to the decision process dynamics. In previous model comparisons, drift diffusion-based confidence models that do not explicitly consider decision time in the computation of confidence provided superior model fits compared to race models that directly included decision time in the internal computation of confidence. In the present study, we present support for the assumption that confidence explicitly takes decision time and post-decisional accumulation time into account. We propose the dynamical visibility, time, and evidence (dynaViTE) model, an extension of the dynamical weighted evidence and visibility (dynWEV) model. DynaViTE assumes that confidence is not solely based on the final amount of accumulated evidence but explicitly includes time in the computation of confidence. Model comparisons using four previously published data sets with different perceptual decision tasks showed a good model fit of dynaViTE, indicating that the relationship between confidence and response time is not only due to the close link in the accumulation process but also to an explicit inclusion of time in the computation of confidence.