Attention Scores Research Articles

Decreased frontal theta frequency during the presence of smartphone among children: an EEG study.

Smart devices have become an integral part of our lives. However, research has highlighted the potential implications of smartphone presence on task performance, particularly in young children. This study aimed to determine the effect of a smartphone presence on brainwaves associated with cognitive interruption in children. EEG data were collected from 5.3 to 8.5-year-old children performing a simple reaction time task with and without the presence of a smartphone. Theta and alpha bands were calculated, and repeated measure analysis of variance was performed to assess the impact of two conditions on alpha and theta bands: 1) with the presence and; 2) without the presence of a smartphone. EEG waveforms were also correlated with standardized cognitive measures evaluating attention abilities using Pearson correlation. Theta and alpha activity values were higher in the absence vs the presence of a smartphone, with a significant difference between theta bands for the two study conditions. Moreover, the difference between theta bands in the two conditions was significantly correlated with lower scores on an auditory attention test. The existence of an interactive electronic device during cognitive tasks is associated with alterations in brain activity related to cognitive control. The presence of a smartphone during a simple reaction time task in young children was associated with a significant decrease in frontal theta frequency. A trend of a decreased alpha band in the presence of a smartphone. The differences in theta and alpha frequencies between conditions were significantly correlated with lower scores in auditory and visual attention and inhibition tests.

Study on correlation between perioperative cognitive function and nutritional status in elderly patients with gastric cancer

Objective: To investigate the cognitive function and nutritional status of elderly patients with gastric cancer during perioperative period, and to analyze their correlation. Methods: Aged patients undergoing gastric cancer surgery in The Affiliated Cancer Hospital of Shandong First Medical University from March to October 2021 were selected as the subjects of this study. The monitoring data of cognitive function and nutritional status were retrospectively analyzed from 1 to 3 days before surgery, 1 and 3 days after surgery, 7 days after surgery (before discharge) and 30 days after surgery to analyze the correlation between cognitive function and nutritional status in elderly patients with gastric cancer. Results: the incidence of mild cognitive impairment in elderly patients with gastric cancer was 52.43 %, the visual space of the two groups' (mild cognitive impairment) ability of execution, name, attention, language, abstract thinking, delayed memory and cognitive function scores were lower than 1 set of directional force (cognitive function in normal group), statistically significant difference (P < 0.05). The nutritional status of elderly patients with gastric cancer was lower than that of healthy elderly group at the same period (P < 0.05). The scores of visual spatial executive function, name, attention, delayed memory, orientation and total score of cognitive function in elderly gastric cancer patients were positively correlated with nutritional status (P < 0.05). Conclusions: The cognitive function and nutritional status of elderly patients with gastric cancer are both in a low state during treatment and a higher level of cognitive function can help patients maintain a more correct nutritional cognition, and the nutritional status of patients will be relatively better. There is a positive correlation between cognitive function and nutritional status in elderly patients with gastric cancer, which should be paid attention to in the treatment.

The 100 Most Cited Androgenetic Alopecia Articles: An Analysis of Altmetrics Data from 2015 to 2022

Introduction: Androgenetic alopecia is the most common type of hair loss, and with increasing media integration in medicine, understanding social media consumption of literature is invaluable. Altmetric Attention Score analysis can quantify factors impacting article distribution on media platforms. Methods: To determine factors influencing literature dissemination and reader demographics, a bibliometric analysis was performed on the 100 most cited androgenetic alopecia articles. Results: Articles with top 25th percentile Altmetric Attention Scores were cited more frequently (41.76 vs. 24.59, p < 0.05). Open-access articles had lower odds of being read by healthcare professionals (aOR = 0.16, p < 0.05), while funded studies and journal impact factor increased odds of readership (aOR = 5.80; aOR = 1.55; p < 0.05 for both). Scientists and healthcare professionals showed interest in publications addressing 5α-reductase inhibitors (aOR = 26.08; aOR = 6.13; p < 0.05 for both). Articles with high social media viewership were also highly cited in academic literature. Conclusion: Healthcare professionals appeared more discerning about article readership compared to the public. With many outlets for consumption of media, members of the public not involved in dermatology may have difficulty in identifying reliable sources of material. Overall, Altmetrics can help quantify readership trends and public interest in dermatology research.

Effect of Sleep Restriction on Adolescent Cognition by Adiposity

Pediatric obesity is associated with impaired cognitive function; however, the mechanisms underlying this association demand assessment. Sleep may be a relevant moderator, as poor sleep predicts both increased adiposity and impaired cognitive function. To determine the effects of adiposity and sleep on adolescent cognitive function. This single-blind randomized crossover trial was conducted from September 2020 to October 2022. Parents or caregivers provided demographic information for adolescent participants. Body mass index percentile and bioelectrical impedance analysis assessed adiposity. Adolescents completed 2 actigraphy-confirmed sleep conditions, adequate and restricted, followed by in-person cognitive assessment. No additional follow-up was provided. Data collection for this population-based study took place in a behavioral medicine clinic in Birmingham, Alabama. A total of 323 participants were assessed for eligibility (ages 14-19 years and healthy). Of the 244 eligible adolescents, 157 declined participation. Eighty-seven were randomized and 26 dropped out postenrollment. The final sample included 61 adolescents, 31 with healthy weight and 30 with overweight or obesity. Data were analyzed from April to October 2023. Following a 2-day washout period of adequate sleep, adolescents completed 2 sleep conditions: adequate (mean [SD] duration, 8 hours, 54 minutes [58.0 minutes]) and restricted (mean [SD] duration, 4 hours, 12 minutes [50.7 minutes]). The National Institutes of Health Cognitive Toolbox assessed global and fluid cognition, cognitive flexibility, working and episodic memory, attention, and processing speed. The Stroop Task assessed inhibition. The final sample included 61 adolescents (mean [SD] age, 16.3 [1.6] years; 35 [57.4%] female). Restricted sleep predicted poorer global cognition scores (restricted mean [SD], 98.0 [2.8]; adequate mean [SD], 103.2 [2.9]), fluid cognition scores (restricted mean [SD], 94.5 [3.2]; adequate mean [SD], 102.0 [3.6]), and cognitive flexibility scores (restricted mean [SD], 84.8 [3.0]; adequate mean [SD], 92.8 [3.0]) for adolescents with overweight or obesity. No differences emerged for adolescents with healthy weight. Adolescents with overweight or obesity also had poorer attention scores (mean [SD], 80.0 [2.3]) compared to adolescents with healthy weight (mean [SD], 88.4 [SD, 2.3]) following restricted sleep. No differences emerged following adequate sleep. Findings were similar for total body fat percentage (TBF%); however, for adolescents with TBF% above 42, restricted sleep also predicted poorer processing speed, and the association between sleep and attention did not vary based on TBF%. Adolescents with overweight or obesity may be more vulnerable to negative cognitive effects following sleep restriction. Improved sleep hygiene and duration in this group may positively impact their cognitive health. ClinicalTrials.gov Identifier: NCT04346433.

Predicting drug-Protein interaction with deep learning framework for molecular graphs and sequences: Potential candidates against SAR-CoV-2.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused the COVID-19 disease, which represents a new life-threatening disaster. Regarding viral infection, many therapeutics have been investigated to alleviate the epidemiology such as vaccines and receptor decoys. However, the continuous mutating coronavirus, especially the variants of Delta and Omicron, are tended to invalidate the therapeutic biological product. Thus, it is necessary to develop molecular entities as broad-spectrum antiviral drugs. Coronavirus replication is controlled by the viral 3-chymotrypsin-like cysteine protease (3CLpro) enzyme, which is required for the virus's life cycle. In the cases of severe acute respiratory syndrome coronavirus (SARS-CoV) and middle east respiratory syndrome coronavirus (MERS-CoV), 3CLpro has been shown to be a promising therapeutic development target. Here we proposed an attention-based deep learning framework for molecular graphs and sequences, training from the BindingDB 3CLpro dataset (114,555 compounds). After construction of such model, we conducted large-scale screening the in vivo/vitro dataset (276,003 compounds) from Zinc Database and visualize the candidate compounds with attention score. geometric-based affinity prediction was employed for validation. Finally, we established a 3CLpro-specific deep learning framework, namely GraphDPI-3CL (AUROC: 0.958) achieved superior performance beyond the existing state of the art model and discovered 10 molecules with a high binding affinity of 3CLpro and superior binding mode.

The Top Ranked 101 Articles in Pediatric Surgical Journals from an Altmetric Perspective.

In the era of scientific digitalization, online media platforms gain increasing popularity to accomplish research output awareness. The Altmetric Attention Score AAS weights these online mentions based on a privy algorithm. We aimed to characterize the top 100 articles with the highest (AAS) published in pediatric surgery journals. Publications from six core pediatric surgery journals were retrieved from www.altmetric.com in January 2023 and ranked by their AAS. The top 101 publications were analyzed for their bibliometric measures, study design, and quality as well as online media mentions. The top 101 AAS articles were published between 1974 and 2022, preferentially from the United States (64%) and mainly in Journal of Pediatric Surgery (73%), followed by Journal of Pediatric Surgery Case Reports, Pediatric Surgery International, Seminars in Pediatric Surgery, and European Journal of Pediatric Surgery. Their AAS ranged between 21 and 389 (median: 33), with Twitter/X being mostly responsible for online mentions (n = 2,189; 75%). The number of citations in peer-reviewed journals ranged between 0 and 358 (median: 16) and did not correlate to AAS. Retrospective study design (33%) with low evidence level IV (43%) dominated. The Journal of Pediatric Surgery is the main source of high-profile AAS publications in pediatric surgery. The altmetric popularity of articles is predominantly achieved by their propagation via X, irrespective of the study quality and recognition in the scientific community. Thus, active "twitterism" may play the key role to reach high AAS scores.

Poor subjective sleep quality and trait impulsivity in patients with bipolar disorder.

Sleep disturbance and impulsivity are key components of mood vulnerability in bipolar disorder (BD), but few studies have assessed the association between these two symptoms among patients with BD. Forty-seven euthymic patients with bipolar I disorder (BDI) or bipolar II disorder (BDII) and 58 age- and sex-matched healthy controls were enrolled in this cross-sectional study. Trait impulsivity was measured using the Barratt Impulsiveness Scale Version 11 (BIS-11), which yielded 3 second-order factors: attention, motor, and non-planning. Subjective sleep quality was assessed using the self-reported Pittsburgh Sleep Quality Index (PSQI). General linear models (GLMs) were used to assess the associations between subjective poor sleep and trait impulsivity with multiple testing corrections. Patients with BD scored higher in BIS-11 and PSQI than healthy controls. PSQI total scores positively correlated with BIS-11 total scores, while sleep disturbance and daytime dysfunction were associated with attentional impulsiveness after controlling for covariates. Participants with higher PSQI total scores (>10) had higher scores in BIS-11 total, attention, and non-planning than those with low PSQI scores (≤5). These findings support the hypothesis that poor sleep quality might lead to impulsivity and add to the growing evidence that improving sleep quality may be a therapeutic target for patients with BD.

Assessing the Impact of Overactive Bladder Medications on Cognition.

Emerging literature has associated the use of anticholinergic medications to cognitive decline. The aim of this study was to evaluate the association of overactive bladder medications on cognitive function with prospective longitudinal cognitive assessments. A population-based cohort of individuals 50 years and older who had serial validated cognitive assessment, in accordance with the Mayo Clinic Study of Aging, was evaluated from October 2004 through December 2021. Anticholinergic overactive bladder medications were grouped by traditional anticholinergic medications and central nervous system (CNS)- sparing anticholinergic medications and compared to no medication exposure. A linear mixed effects model with time-dependent exposures evaluated the association between overactive bladder anticholinergic medication exposure and subsequent trajectories of cognitive z-scores. We included 5,872 participants with a median follow-up of 6.4 years. Four hundred forty-three were exposed to traditional anticholinergic medications, 60 to CNS-sparing medications, and 5,369 had no exposure. On multivariable analyses, exposure to any anticholinergic overactive bladder medication was significantly associated with deterioration in longitudinal cognitive scores in the language and attention assessments compared to the control cohort. Traditional anticholinergic medication exposure was associated with worse attention scores than nonexposed participants. Exposure to CNS-sparing anticholinergic medications was associated with a deterioration in the language domain compared to those unexposed. Among women, traditional anticholinergic medication exposure was associated with worse global and visuospatial scores than nonexposed participants, but this association was not identified in the CNS-sparing group. Exposure to anticholinergic overactive bladder medications was associated with small but significantly worse decline in cognitive scoring in the language and attention domains when compared to nonexposed individuals.

25 years of Clinical Implant Dentistry and Related Research (CIDRR): A modern bibliometric and Altmetrics network analysis.

Since its establishment in 1999, the journal of Clinical Implant Dentistry and Related Research (CIDRR) has consistently disseminated notable clinical and translational research within the domain of oral implantology. As the journal approaches its milestone 25th anniversary, this study endeavors to systematically delineate the publication trends, level of evidence, and bibliometric indices characterizing the initial quarter-century of CIDRR's scholarly activity. Notably, the investigation adopts a contemporary methodology by incorporating Altmetric analysis, thereby enriching the evaluation with an assessment of the broader societal and online impact of the published research. A comprehensive search was performed in SCOPUS and PubMed to access the bibliographic data of all articles published in the journal from 1999 to 2024. Additionally, Altmetric database was used to obtain social media attention scores (AAS). Journal's overall performance via impact factor and quartile range was assessed. Most cited papers were identified and the most prolific authors, institutions and countries and the collaboration networks among those were assessed. The level of evidence of all articles was determined based on Oxford level of evidence scale. All articles were categorized based on their major topic in the field of implant dentistry. Throughout its first 25 years of activity, CIDRR published 1912 articles with an annual growth rate of 2.67% and consistently being ranked at Q1 quartile in "Dentistry (miscellaneous)" and "Oral Surgery" journal categories. When clinical studies are considered, level I and II evidence constituted 22.82% and 11.82% of all articles, respectively. Sweden, the USA, and Italy as well as Göteborgs Universitet, Sahlgrenska Akademin. and Malmö Högskola were the most prolific countries and institutions respectively. "Implant system/design/characteristics," "Bone Augmentation," and "Implant Prosthesis" were the top most investigated topics. The examination of the journal's initial 25 years highlighted that CIDRR has surpassed similar dental research journals in publishing a greater number of high-level evidence articles. It also showcased diverse country- and author-collaboration networks. However, the journal's social media presence is still evolving. This article, presenting a comprehensive overview of the journal's scientometric and bibliographic activities, serves as a valuable reference for researchers, clinicians, and stakeholders, offering insights into both traditional and contemporary perspectives.

The Impact of Online Game Addiction on Student’s Attention

Generally, research on online game addiction only focuses on children or adolescents whose learning patterns still need to be better organized. However, this research focuses on students expected to have a more regular learning pattern. This is because not all students have academic achievements that are as expected. Some students who enter the class play online games with laptops or gadgets. This study aimed to determine online game addiction among santri students, determine the level of attention among santri students, and the effect of online game addiction on attention among santri students. This study uses a quantitative approach. The subjects of this study were santri students with active status in Islamic boarding schools based on Islamic boarding schools. Data collection in this study used an online game addiction scale and a Stroop test to measure attention. The analysis test in this study used the help of the R program. Based on the hypothesis test using the R program, it shows that online game addiction significantly affects the attention of santri students. The results of the research data analysis show that students who get high online game addiction scores have low attention scores. Conversely, students who have low online game addiction scores have high attention scores. This proves that there is an influence of online game addiction on attention . One way to increase attention so that students do not experience addiction to online games, namely by replacing student energy or energy substitution , for example, with sports activity programs.

SiET: Spatial information enhanced transformer for multivariate time series anomaly detection

Anomaly detection in a multivariate time series using unsupervised methods presents a formidable challenge. The existing strategies focused on delineating intrinsic patterns over a temporal dimension and outputting a better representation of the input series. Generally, anomaly detecting model derives a criterion, which is mostly the distance between the representations and the original data, for distinguishing anomalies. Anomaly Transformer is a recent model that achieves substantial advancements by introducing its proprietary criterion of association discrepancy. This new criterion leverages the fact that time points focus on their adjacent neighbors if normal; however, they lose this characteristic if they are anomalous. Anomaly Transformer focuses only on the association between time points and neglects the association between the sensors. In addition, the association discrepancy calculated by the attention score between time points and Gaussian distribution can sometimes be insufficient. To achieve better performance, we propose a spatial information enhanced transformer (SiET), which is a novel paradigm that integrates graph neural networks into the original Anomaly Transformer framework, engendering a high-dimensional association discrepancy. Theoretical proofs are provided to verify the reliability of our model. Further, SiET achieved results comparable to the state-of-the-art results on five unsupervised time-series anomaly detection benchmarks.

Evaluating Effectiveness of Group Intervention Working on Executive Function for Children with Attention Deficit Hyperactivity Disorder: A Prospective Observational Cohort Study

Introduction: The objective of this study is to evaluate the effectiveness of Simon says program (SSP), a strategy-based group intervention program working on executive function (EF) for children with attention deficit hyperactivity disorder (ADHD). Methods: A prospective observational cohort study was conducted from December 2021 to July 2022 recruiting 21 SSP participants, either they were on stimulant or not on stimulants, and 12 other ADHD patients who are on stimulant medication only without prior participation in SSP, using convenience sampling method, from Child Development Clinic Hospital Sultan Ismail. NICHQ Vanderbilt Assessment Follow Up Scales (VAS) were used to measure its effectiveness and the significance of score differences before and after SSP were assessed using paired sample t-test of Statistical Package for Social Science (SPSS) version 28.0 software. Results: Total of 33 children participated in the study. From our study, only those participants on behavioural therapy alone showed statistically significant reduction in inattentive score, hyperactivity score and total symptoms score at the third month and sixth month after joining SSP from parents-rated VAS. There were no statistically significant differences in the average VAS performance score for both groups. Conclusion: SSP could be an effective behavioral intervention for children with ADHD children. Limitations included lacking clear generalizability due to the convenience sampling method and potential inter-rater variability.

Examining the effects of attention and concentration levels on reaction time in fencing

Background and Study Aim. Attention and concentration, fundamental psychological skills, are crucial in situations where the opponent moves rapidly and incessantly. Reaction time is also of paramount importance in winning a game in fencing, which requires both offensive and defensive actions. Understanding the factors that affect reaction time is essential for improving performance. This study aimed to investigate the impact of disruptions in attention and concentration on reaction time in fencing. Material and Methods. Thirty-four healthy male and female fencers participated in two testing sessions. In the initial session, participants filled out a personal information form and took the d2 Attention Test to determine their attention levels. They also completed items representing the concentration disruption subscale of the Sport Anxiety Scale-2 (SAS-2) to measure concentration levels. In the second session, participants underwent the Favero Electronic Fencing Target (EFT-1) test to measure their reaction times. To analyze the obtained data, SPSS 20 was used. The Pearson correlation coefficient between attention, concentration disruption, and participants' reaction times was calculated. Then, linear regression analysis was employed to test whether attention and concentration scores could predict the reaction times. Results. The findings indicated that there is a significant positive relationship between E (r = .603, p &lt; .01), E% (r = .628, p &lt; .01), E1 (r = .584, p &lt; .01), E2 (r = .533, p &lt; .01), and reaction time. Additionally, a significant negative relationship was revealed between concentration performance and reaction times (r = -.456, p &lt; .01). A significant positive correlation was observed between fencers' concentration disruption and reaction times (r = .416, p &lt; .05). Conclusions. Our study results emphasize the importance of attention and concentration in disciplines that require quick reactions. These cognitive factors need to be considered in the development of sports performance.

Stranger things: the vanishing of the Altmetric Attention Score values in information and library science

AbstractThis study investigates the Altmetric Attention Score (AAS) fluctuations and altmetrics source stability in Information Science &amp; Library Sciences publications, analyzing 26,474 documents from 2012 to 2021. It finds that 23.7% of these publications experienced AAS fluctuations over a year. Significant influences on AAS variability include Twitter mentions and policy documents, with Twitter mentions showing high volatility, affecting nearly 30% of papers. The removal of the Analysis &amp; Policy Observatory as a policy source led to a notable drop in policy document mentions. Various types of mention vanishing are identified, such as administrative decisions by altmetrics aggregators, technological issues, user actions on digital platforms, and natural changes on platforms like Wikipedia. In response, the study proposes modifications in the tracking and monitoring system of mentions to not overlook these vanishings. This aims to enhance the reliability and stability of altmetrics at a time when there is a call for their use in the research evaluation.

Association of objective sleep duration with cognition and brain aging biomarkers in older adults.

The neuropathological mechanisms underlying the association between sleep duration and mild cognitive impairment remain poorly understood. This population-based study included 2032 dementia-free people (age ≥ 60 years; 55.1% women) derived from participants in the Multimodal Interventions to Delay Dementia and Disability in Rural China; of these, data were available in 841 participants for Alzheimer's plasma biomarkers (e.g. amyloid-β, total tau and neurofilament light chain), 1044 for serum microvascular biomarkers (e.g. soluble adhesion molecules) and 834 for brain MRI biomarkers (e.g. whiter matter, grey matter, hippocampus, lacunes, enlarged perivascular spaces and white matter hyperintensity WMH). We used electrocardiogram-based cardiopulmonary coupling analysis to measure sleep duration, a neuropsychological test battery to assess cognitive function and the Petersen's criteria to define mild cognitive impairment. Data were analysed with multivariable logistic and general linear models. In the total sample (n = 2032), 510 participants were defined with mild cognitive impairment, including 438 with amnestic mild cognitive impairment and 72 with non-amnestic mild cognitive impairment. Long sleep duration (>8 versus 6-8 h) was significantly associated with increased likelihoods of mild cognitive impairment and non-amnestic mild cognitive impairment and lower scores in global cognition, verbal fluency, attention and executive function (Bonferroni-corrected P < 0.05). In the subsamples, long sleep duration was associated with higher plasma amyloid-β40 and total tau, a lower amyloid-β42/amyloid-β40 ratio and smaller grey matter volume (Bonferroni-corrected P < 0.05). Sleep duration was not significantly associated with serum-soluble adhesion molecules, white matter hyperintensity volume, global enlarged perivascular spaces and lacunes (P > 0.05). Alzheimer's and neurodegenerative pathologies may represent common pathways linking long sleep duration with mild cognitive impairment and low cognition in older adults.

Effects of chronic aerobic exercise on attentional bias among women with methamphetamine addiction

ObjectiveTo explore the effects of chronic exercise on attentional bias toward drug-related stimuli and on brain electrophysiological characteristics among women with methamphetamine addiction. MethodsIn total, 63 women with methamphetamine addiction were randomized to participate in a dance (n = 21; mean age, 32.16 ± 2.07 years), bicycle (n = 21; mean age, 32.59 ± 2.12 years), or control (maintained regular activities with little exercise; n = 21; mean age, 30.95 ± 2.81 years) group for 12 weeks. The participants in the three groups were not significantly different in terms of methamphetamine use or detoxification. Before and after the intervention, attentional bias was assessed using the dot-probe task, and event-related potentials were recorded during the task. ResultsThe mean attentional bias scores decreased significantly after the intervention in both exercise groups but not in the control group. After 12 weeks of dance exercise, the amplitudes of the N170, N2, P2, and P3 components of the event-related potentials decreased significantly during attentional bias processing. In addition, differences in N170 amplitudes for congruent vs. incongruent conditions in the dot-probe task were no longer observed. After 12 weeks of cycling exercise, N2 and P2 amplitudes decreased significantly. By contrast, there were no significant differences in N170, N2, P2, and P3 amplitudes in the control group before vs. after the intervention. ConclusionsChronic (12 weeks of) aerobic exercise reduced attentional bias toward drug-related cues by improving attentional inhibition and reducing the maintenance of extra attention to drug-related cues among women with methamphetamine addiction. Both dance and bicycle exercise improved the early recognition of drug-related cues, weakened the influence of the memory of previous drug use, and improved attentional bias behavior by strengthening attention control. Dance exercise, but not bicycling, also regulated emotional control and improved the attention selection process. These results provide theoretical and empirical evidence that chronic aerobic exercise may reduce the attentional bias toward drug-related cues to assist in the recovery of women with methamphetamine addiction.

A compound framework for short-term gas load forecasting combining time-enhanced perception transformer and two-stage feature extraction

The development of accurate and reliable gas load forecasting models is critical to residential safety and gas company economics. However, since the seq2seq neural network conveys information by sequentially updating the hidden states, when processing gas load data, the information needs to be passed several times before it can affect the prediction results at subsequent time steps. This can lead to a lack of ability of the model to capture long-term dependencies. To address the above issues, we propose a novel compound framework. Time-enhanced perception transformer (TEPT) in the framework achieves parallel computation of historical data and stronger location awareness through convolutional self-attention and improved attention scores. This results in better capture of local patterns and long-term dependencies in gas loads. In addition, the framework proposes two-stage feature extraction (TSFE) for decomposing the important parts of the original information and extracting more refined features based on them. We constructed a real gas load data set from Wuxi, China to verify the effectiveness. The results show that MAE, MAPE, and RMSE of the proposed method are 3.45, 1.07%, and 4.68, which provide higher accuracy compared to other prediction methods.

Understanding the role of self-attention in a Transformer model for the discrimination of SCD from MCI using resting-state EEG.

The identification of EEG biomarkers to discriminate Subjective Cognitive Decline (SCD) from Mild Cognitive Impairment (MCI) conditions is a complex task which requires great clinical effort and expertise. We exploit the self-attention component of the Transformer architecture to obtain physiological explanations of the model's decisions in the discrimination of 56 SCD and 45 MCI patients using resting-state EEG. Specifically, an interpretability workflow leveraging attention scores and time-frequency analysis of EEG epochs through Continuous Wavelet Transform is proposed. In the classification framework, models are trained and validated with 5-fold cross-validation and evaluated on a test set obtained by selecting 20% of the total subjects. Ablation studies and hyperparameter tuning tests are conducted to identify the optimal model configuration. Results show that the best performing model, which achieves acceptable results both on epochs' and patients' classification, is capable of finding specific EEG patterns that highlight changes in the brain activity between the two conditions. We demonstrate the potential of attention weights as tools to guide experts in understanding which disease-relevant EEG features could be discriminative of SCD and MCI.

Seasonality and regional disparity in attention to homelessness in UK newspapers between 2001 and 2020

ABSTRACT This research examined the amount of media attention to homelessness in 11 UK newspapers with two main research questions: (1) Does the media coverage exhibit seasonal cyclical patterns in their attention to homelessness? (2) Do England's nine regions differ in the attention they receive after adjusting for their relative homelessness levels? Time series of all 4105 news reports with the keyword “homeless*” in their headline between 2001 and 2020 were tested for meteorological and monthly seasonal effects, revealing significantly greater attention in winter but decreased coverage in spring and summer. Contrary to expectation, further analysis suggested that the increased winter coverage was not related to the colder months but to the Christmas period. Regarding regional differences, London received the highest mentions in the news but after adjusting for the relative burden of homelessness, the North West emerged as receiving the most relative coverage. The East Midlands and East of England had the lowest adjusted attention scores. As suggested by the public arenas model, the findings of this research suggest that media focus on social problems like homelessness be culturally patterned with key events like Christmas shaping issue-prominence. Similarly, regional imbalances in attention may reflect a systemic bias in news reporting.

TransGEM: a molecule generation model based on Transformer with gene expression data.

It is difficult to generate new molecules with desirable bioactivity through ligand-based de novo drug design, and receptor-based de novo drug design is constrained by disease target information availability. The combination of artificial intelligence and phenotype-based de novo drug design can generate new bioactive molecules, independent from disease target information. Gene expression profiles can be used to characterize biological phenotypes. The Transformer model can be utilized to capture the associations between gene expression profiles and molecular structures due to its remarkable ability in processing contextual information. We propose TransGEM (Transformer-based model from gene expression to molecules), which is a phenotype-based de novo drug design model. A specialized gene expression encoder is used to embed gene expression difference values between diseased cell lines and their corresponding normal tissue cells into TransGEM model. The results demonstrate that the TransGEM model can generate molecules with desirable evaluation metrics and property distributions. Case studies illustrate that TransGEM model can generate structurally novel molecules with good binding affinity to disease target proteins. The majority of genes with high attention scores obtained from TransGEM model are associated with the onset of the disease, indicating the potential of these genes as disease targets. Therefore, this study provides a new paradigm for de novo drug design, and it will promote phenotype-based drug discovery. The code is available at https://github.com/hzauzqy/TransGEM.