The attention network test (ANT) is a tool for assessing the executive, alerting, and orienting components of attention. However, conflicting findings exist regarding the nature and correlation ...between attention networks. This study aims to investigate the influence of eye movement time on the assessment of attention network efficiency. Forty male students, with an average age of 20.8 ± 1.3 years, participated in the study. The revised attention network test was conducted concurrently with the recording of the electrooculogram signal. The electrooculogram signal was used to estimate eye placement time on target stimuli. Considering eye movement time for calculating the score of each network was proposed as a novel method. The study explored the nature of attention networks and their relationships, and revealed significant effects for attention networks with and without considering the eye movement time. Additionally, a significant correlation is observed between the alerting and orienting networks. However, no significant correlation is found between attention networks using the proposed method. Considering eye movement time alters the assessment of attention network efficiency and modifies the correlation among attention networks.
This study aimed to use Event-Related Potential (ERP) data to investigate how multiple attentional networks might contribute to vigilance decrement, based on Petersen and Posner's (2012) model of ...networks for executive control, alerting, and spatial orienting. The networks may differ in their sensitivity to effects of time on task. Based on the theory of attentional networks and previous findings, it was hypothesized that temporal decrements would be found in executive control and alerting networks. 102 participants (53 females) performed a version of the Attention Network Test (ANT) that was modified to require a prolonged period of continuous performance of approximately 70 min during electroencephalogram (EEG) recording. ERP amplitudes were measured in task conditions associated with executive control, alerting, and spatial orienting networks were measured across three consecutive task stages. N100 and P300 amplitudes were used to assess early selective attention and later target discrimination, respectively. Results largely replicated previous findings on ERP responses to the ANT. Amplitudes of the N100 wave and P300 declined over time in multiple conditions, consistent with increasing vulnerability to vigilance decrement. Evidence from cue × stage interactions suggested a temporal decrement in alerting processes, indicated by N100 amplitude, but behavioral data did not show any impairment specific to alerting. By contrast, there was a correspondence between a modest decline in frontal P300 amplitude seen in a no cue condition and slowing of response in this condition. A full explanation for vigilance decrement in terms of attention networks remains elusive. However, the current data suggest that parietal N100 and frontal P300 index two distinct processes that may contribute to loss of alertness and vigilance, depending on task demands.
The incomplete understanding of mild traumatic brain injury (MTBI)-related cognitive impairment in the acute stage and the low cognitive needs of patients in the later stage might be the main reasons ...for the neglect of clinical symptoms in patients with MTBI. Patients often experience attention deficits; however, it is unclear whether these patients suffer from general deficits or selective impairment of the brain attention network. Therefore, we investigated deficits in the attention function of patients with mild brain traumatic injury. Patients (n = 50) and matched healthy controls (n = 49) completed a general neuropsychological background test and the Attention Network Test, which provided an independent assessment of the three attention networks (alerting, orienting, and executive control). We found that patients had significant deficits in the orienting network but none in the alerting and executive control networks. Furthermore, patients’ cognitive task scores in attention, memory, and information processing tasks were significantly lower than the scores of the controls. Our results demonstrated that patients with MTBI had selective impairment in the orienting network and extensive cognitive impairments, including those related to general attention, memory, and information processing speed.
•Extensive cognitive impairment is observed in patients with mild traumatic brain injury.•Cognitive impairment is in attention, memory, and information processing speed.•Selective impairment of the orienting network is observed.•There is a normal function of alerting and executive networks.
•An auto-monitoring and anomaly alerting method for group-housed Pigs.•A pig segmentation model based on Mask R-CNN to monitor group-housed pigs.•Use frame difference method to quantify the activity ...level of group-housed pigs.•Adopt K-means clustering algorithm to explore pigs’ daily behaviors.•Use SARIMA model to forecast potential shifts in activity levels proactively.
The activity level of group-housed pigs can reflect their daily behavioral patterns and health conditions. Currently, most pig farms mainly rely on manual daily patrols to monitor the activities of group-housed pigs, which is labor-intensive and inaccurate. In this paper, we propose a computer vision-based method for the automatic monitoring and alerting of group-housed pigs activity anomaly. We established a pig segmentation model based on an improved Mask R-CNN incorporating the CBAM attention mechanism and CIoU loss function for segmenting pigs from video frames. The CBAM attention mechanism enables the model to focus more effectively on target regions, while CIoU loss function guides precise learning of object boundaries, outperforming the traditional IoU loss. Grounded on the segmentation results, we invocated a frame difference method to quantify the activity level of group-housed pigs. Subsequently, we adopted the K-means clustering algorithm to explore the daily behaviors of these pigs. Furthermore, we constructed a SARIMA model using historical data to proactively forecast potential shifts in activity levels. The experimental results demonstrated that the accuracy and recall rate of the pig instance segmentation model were 98.7% and 97.9%, respectively. The SARIMA model performed well in predicting activity levels of group-housed pigs with differing health status. For the pig herds under healthy status, the Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) were 6.01 and 7.67 respectively, while for the pig herds under unhealthy status, the MAE and RMSE were 6.41 and 9.30 respectively. We proposed an effectively method to monitor daily behavioral patterns and anomalies of group-housed pigs, providing valuable references for pig farm management.
The biobehavioral study of aggression has implications for expanding our understanding of transdiagnostic processes that increase risk for disinhibited behaviors. Toward this end, our study tested ...tenets from the process model of aggression (Verona & Bresin, 2015). First, we expected that the predictability of threat would differentially alter cognitive networks, including attentional alerting and executive control. Second, we examined the moderating effects of self- and informant reports of aggression on threat-related changes in cognitive functioning. Using event-related potential (ERP) measures of cognitive-attentional processes, 143 community individuals participated in a well-validated and translational threat manipulation (NPU) task (Schmitz & Grillon, 2012) while completing the Attention Network Test (Fan et al., 2002). Analyses revealed that relatively unpredictable threat quickened alerting-related reaction time, whereas predictable threat interfered with processing of flanker task stimuli. The results, however, failed to show reliable relationships between aggression proneness and threat-related cognitive alterations. The findings fit with a broader literature on cognitive and behavioral outputs of threat activation and provide fruitful avenues for better understanding threat-related aggression.
Alerting for imminent earthquakes is particularly challenging due to the high nonlinearity and nonstationarity of geodynamical phenomena. In this study, based on spatiotemporal information (STI) ...transformation for high-dimensional real-time data, we developed a model-free framework, i.e., real-time spatiotemporal information transformation learning (RSIT), for extending the nonlinear and nonstationary time series. Specifically, by transforming high-dimensional information of the global navigation satellite system into one-dimensional dynamics via the STI strategy, RSIT efficiently utilizes two criteria of the transformed one-dimensional dynamics, i.e., unpredictability and instability. Such two criteria contemporaneously signal a potential critical transition of the geodynamical system, thereby providing early-warning signals of possible upcoming earthquakes. RSIT explores both the spatial and temporal dynamics of real-world data on the basis of a solid theoretical background in nonlinear dynamics and delay-embedding theory. The effectiveness of RSIT was demonstrated on geodynamical data of recent earthquakes from a number of regions across at least 4 y and through further comparison with existing methods.
•Implementing high-risk DDIAS at the point of prescribing in ICUs improves adherence to alerts.•Our systems alert leads to decreased overridden rates of DDIAS in the ICU.•The performance of the DDIAS ...in other educational hospitals at the Iran country level seems to be feasible.•The usability of the DDIASs was found to be at a reasonable level, suggesting that users prefer safe and usable warning systems for potential drug-drug interactions (pDDIs).
The override rate of Drug-Drug Interaction Alerts (DDIA) in Intensive Care Units (ICUs) is very high. Therefore, this study aimed to design, develop, implement, and evaluate a severe Drug-Drug Alert System (DDIAS) in a system of ICUs and measure the override rate of this system.
This is a cross-sectional study that details the design, development, implementation, and evaluation of a DDIAS for severe interactions into a Computerized Provider Order Entry (CPOE) system in the ICUs of Nemazee general teaching hospitals in 2021. The patients exposed to the volume of DDIAS, acceptance and overridden of DDIAS, and usability of DDIAS have been collected. The study was approved by the local Institutional Review Board (IRB) and; the ethics committee of Shiraz University of Medical Science on date: 2019-11-23 (Approval ID: IR.SUMS.REC.1398.1046).
The knowledge base of the DDIAS contains 9,809 severe potential drug-drug interactions (pDDIs). A total of 2672 medications were prescribed in the population study. The volume and acceptance rate for the DDIAS were 81 % and 97.5 %, respectively. The override rate was 2.5 %. The mean System Usability Scale (SUS) score of the DDIAS was 75.
This study demonstrates that implementing high-risk DDIAS at the point of prescribing in ICUs improves adherence to alerts. In addition, the usability of the DDIAS was reasonable. Further studies are needed to investigate the establishment of severe DDIAS and measure the prescribers’ response to DDIAS on a larger scale.
What determines how much one encodes into visual working memory? Traditionally, encoding depth is considered to be indexed by spatiotemporal properties of gaze, such as gaze position and dwell time. ...Although these properties inform about where and how long one looks, they do not necessarily inform about the current arousal state or how strongly attention is deployed to facilitate encoding. Here, we found that two types of pupillary dynamics predict how much information is encoded during a copy task. The task involved encoding a spatial pattern of multiple items for later reproduction. Results showed that smaller baseline pupil sizes preceding and stronger pupil orienting responses during encoding predicted that more information was encoded into visual working memory. Additionally, we show that pupil size reflects not only how much but also how precisely material is encoded. We argue that a smaller pupil size preceding encoding is related to increased exploitation, whereas larger pupil constrictions signal stronger attentional (re)orienting to the to-be-encoded pattern. Our findings support the notion that the depth of visual working memory encoding is the integrative outcome of differential aspects of attention: how alert one is, how much attention one deploys, and how long it is deployed. Together, these factors determine how much information is encoded into visual working memory.
During an emergency, it is necessary to quickly disseminate messages to the public. These communications often provide information about the emergency as well as guidance or advice aimed at ensuring ...the safety of the population. Successful emergency communication depends upon how rapidly and reliably a message can be disseminated, but also on how people respond to the message that they receive. To assist emergency planners tasked with developing message sets for future incidents, in this paper we report a systematic review of all studies that assessed the impact of mobile telephone alerting systems on intended and actual behaviour, to identify factors that affect their likely impact. We searched multiple databases and conferred with topic experts, resulting in a total of 22 studies which met the inclusion criteria. Our results indicate that limited data exist on how people respond to text‐based warning messages and that much of the data is poor quality, indicating a need for more real‐world studies.
