SpecParam (formally known as FOOOF) allows for the refined measurements of electroencephalography periodic and aperiodic activity, and potentially provides a non-invasive measurement of excitation: inhibition balance. However, little is known about the psychometric properties of this technique. This is integral for understanding the usefulness of SpecParam as a tool to determine differences in measurements of cognitive function, and electroencephalography activity. We used intraclass correlation coefficients to examine the test-retest reliability of parameterized activity across three sessions (90 minutes apart and 30 days later) in 49 healthy young adults at rest with eyes open, eyes closed, and during three eyes closed cognitive tasks including subtraction (Math), music recall (Music), and episodic memory (Memory). Intraclass correlation coefficients were good for the aperiodic exponent and offset (intraclass correlation coefficients > 0.70) and parameterized periodic activity (intraclass correlation coefficients > 0.66 for alpha and beta power, central frequency, and bandwidth) across conditions. Across all three sessions, SpecParam performed poorly in eyes open (40% of participants had poor fits over non-central sites) and had poor test-retest reliability for parameterized periodic activity. SpecParam mostly provides reliable metrics of individual differences in parameterized neural activity. More work is needed to understand the suitability of eyes open resting data for parameterization using SpecParam.

In an urban environment, traffic congestion, automobile emissions, and road safety are significant problems that lead to financial losses and environmental deterioration. Vehicle detection, counting, speed estimation, and pollution monitoring are frequently handled inconsistently by current traffic monitoring systems. This research closes this gap by applying the cutting-edge YOLOv8 deep learning architecture to create an extensive real-time vehicle recognition and counting system. In addition to calculating vehicle speeds and detecting five different types of vehicles and pedestrians, the system also estimates emission rates in real time using traffic data. After evaluation of two YOLOv8 variants (YOLOv8n and YOLOv8s), it was found that YOLOv8s performed better, with 0.936 precision, 0.822 recall, and 0.930 mAP50 for CNG automobiles. With an emission factor ranging from 0.6 to 0.8, real-time pollution monitoring was made possible by calculating vehicle emissions based on both type and speed. In addition, the system has a web application developed with the Flask framework and allows real-time traffic data display, including emission rates, vehicle counts, and speed calculations. The method is effective, as evidenced by the results, where YOLOv8s exceed YOLOv8n in essential metrics, including the miss-classification rate (as low as 0.112) and F1-score (0.875 for CNG). With its unique method of simultaneous vehicle identification, counting, speed estimation, and pollution monitoring, this research could lead to advancements in road safety, traffic management, and emission reduction. Doi: 10.28991/ESJ-2025-09-02-023 Full Text: PDF

Neuroprotective factors are essential to successful ageing. As such, digital device use was proposed as an easily accessible and stimulating available cognitive activity to enhance brain function. Nonetheless, there was a lack of studies inspecting the connection between digital device use and cognitive reserve, the risk of cognitive impairment, and cognition. This study aims to investigate the potential mediator and moderator of the association between digital device use, cognitive reserve, the risk of cognitive impairment, and cognition among healthy older adults. A quantitative cross-sectional study was conducted to investigate the relationship between digital device use and cognitive reserve, the risk of cognitive impairment, and cognition. A total of 210 healthy older adults were recruited through purposive sampling. The results obtained from this study revealed that there was a significant difference in cognitive reserve and cognition between healthy older adults who use a digital device for communication purpose only and who use a digital device for multiple purposes. A significant relationship was also found between cognitive reserve, the risk of cognitive impairment, and cognition. Although digital device use was found to be significantly associated with cognitive reserve and cognition, it was not significantly associated with the risk of cognitive impairment. Cognitive reserve partially mediated the relationship between digital device use and cognition, supporting the notion that cognitive reserve acts as an underlying mechanism in the relationship between digital device use and cognition. Hence, digital device use was suggested to be a good daily intervention for healthy older adults to build on their cognitive reserve and potentially protect their cognition from declining. Nevertheless, relying on digital device use alone is not sufficient, and other activities should be explored to enhance cognitive reserve among healthy older adults.

Schizophrenia is a debilitating mental health disorder that imposes profound economic, societal, and personal burdens. The negative symptoms of schizophrenia (i.e., blunted affect, alogia, anhedonia, asociality, and avolition) are highly prevalent and pervasive in the psychotic disorder and pose significant resistance to available treatment options. Traumatic childhood experiences are strongly linked with the risk of developing schizophrenia. Most prior studies have primarily focused on positive symptoms of schizophrenia (e.g., hallucinations and delusions), whereas less attention has been given to negative symptoms. The current study investigated the relationship between childhood trauma (i.e., physical abuse, sexual abuse, and emotional abuse and neglect) and negative symptoms in a sample of schizophrenia outpatients and healthy controls (n = 159 participants, including 99 patients with schizophrenia). The observations from the current study revealed that schizophrenia patients experienced a significantly greater degree of childhood trauma and negative symptoms than the control individuals. The results of the current study also indicated that more severe experiences of total childhood trauma (i.e., summation of all trauma types), physical abuse, and emotional neglect may increase the risk of schizophrenia patients reporting negative symptoms. However, childhood sexual and emotional abuse was found to have no impact on the degree of negative symptoms experienced by schizophrenia patients. Implications and limitations of the current study are discussed. In conclusion, we found that the severity of overall childhood trauma, physical abuse, and emotional neglect may play an important role in increasing the likelihood of schizophrenia patients reporting negative symptoms.

Protein and peptide aggregation has become a prominent focus in biomedical research due to its critical role in the development of neurodegenerative diseases (NDs) and its relevance to industrial applications. Neurodegenerative disorders such as Alzheimer’s disease (AD), Parkinson’s disease (PD), Huntington’s disease (HD), and Amyotrophic Lateral Sclerosis (ALS) are closely associated with abnormal aggregation processes, highlighting the need for a deeper understanding of their molecular mechanisms. In recent years, a wide range of computational methods, bioinformatics tools, and curated databases have been developed to predict and analyze sequences and structures that are prone to aggregation. These in silico approaches offer valuable insights into the underlying principles of aggregation and contribute to the identification of potential therapeutic targets. This review provides a concise overview of the current bioinformatics resources and computational techniques available for studying protein and peptide aggregation, intending to guide future research efforts in the field of neurodegenerative disease modeling and drug discovery.

Destination memory, which is the ability to remember to whom one has sent information, is intimately associated with social cognition. We assessed whether processing attributes of destinations would improve destination memory in patients with traumatic brain injury (TBI). In this cross-sectional study, we tested the destination memory of 24 patients with TBI and 25 control participants in two conditions. On the first one (control condition), we invited participants to tell proverbs to celebrities’ faces in order to decide, on a subsequent recognition test, whether they previously told that proverb to that celebrity or not. On the second condition (experimental introspection condition), the same procedures were repeated. However, after telling the proverbs, we invited participants to introspect about what the destination might believe about the proverbs (e.g., “What do you think that the celebrities would think about the proverbs?”). Group comparisons demonstrated better destination memory after the introspection than when no introspection was implemented in control participants, but there were no significant differences between the two conditions in patients with TBI. However, analyses of individual profiles demonstrated that more than half (n = 13) of the patients with TBI demonstrated better destination memory after introspection. While these results demonstrate a beneficial effect of introspection on destination memory for some cases of patients with TBI, more research is needed to reveal how introspection may influence patients’ memory in social interactions.