mdpi-ai/citelens huggingface dataset:
Development and validation of serological dynamic risk score to predict outcome in gastric cancer with adjuvant chemotherapy: a multicentre, longitudinal, cohort study
Field: ONCOLOGY

Background: Baseline serological biomarkers have the potential to predict the benefits of adjuvant chemotherapy in patients with gastric cancer. However, the fluctuating nature of postoperative recurrence risk makes precise treatment challenging. We aimed to develop a risk score in real-time predicting outcomes for postoperative GC patients using blood chemistry tests.Materials and methods: This was a retrospective, multicentre, longitudinal cohort study from three cancer centres in China, with a total of 2737 GC patients in the pTNM stage Ib to III. Among them, 1651 patients with at least two serological records were assigned to the training cohort. Model validation was carried out using separate testing data with area under curve (AUC). The least absolute shrinkage and selection operator (LASSO) and random forest-recursive feature elimination (RF-RFE) algorithm were used to select the parameters.Results: The Cox regression model derived six risk factors to construct a composite score (low-risk: 0-2 score; high risk: 3-6 score), including CEA, CA125, CA199, haemoglobin, albumin, and neutrophil to lymphocyte ratio. The risk score accurately predicted mortality in 1000-time bootstrap (AUROCs:0.658; 95% CI: 0.645, 0.670), with the highest AUROC (0.767; 95% CI: 0.743, 0.791) after 1 year since the gastrectomy. In validation dataset, the risk score had an AUROC of 0.586 (95% CI 0.544, 0.628). Furthermore, patients with high risk at 1 month derived significant clinical benefits from adjuvant chemotherapy (P for interaction <0.0001). Compared with the low-low-low risk group, the low-low-high risk group of the long-term state chain (risk state at baseline, 6 months, 1 year) had the worse OS (HR, 6.91; 95%CI: 4.27, 11.19) and DFS (HR, 7.27; 95%CI: 4.55, 11.63).Conclusion: The dynamic risk score is an accurate and user-friendly serological risk assessment tool for predicting outcomes and assisting clinical decisions after gastrectomy.
A test of pre-exposure spacing and multiple context pre-exposure on the mechanisms of latent inhibition of dental fear: A study protocol
Field: PSYCHOLOGY

Background: Latent inhibition occurs when exposure to a stimulus prior its direct associative conditioning impairs learning. Results from naturalistic studies suggest that latent inhibition disrupts the learning of dental fear from aversive associative conditioning and thereby reduces the development of dental phobia. Although theory suggests latent inhibition occurs because pre-exposure changes the expected relevance and attention directed to the pre-exposed stimulus, evidence supporting these mechanisms in humans is limited. The aim of this study is to determine if two variables, pre-exposure session spacing and multiple context pre-exposure, potentiate the hypothesized mechanisms of expected relevance and attention and, in turn, increase latent inhibition of dental fear. Methods: In a virtual reality simulation, child and adult community members (ages 6 to 35) will take part in pre-exposure and conditioning trials, followed by short- and long-term tests of learning. A 100ms puff of 60 psi air to a maxillary anterior tooth will serve as the unconditioned stimulus. Pre-exposure session spacing (no spacing vs. sessions spaced) and multiple context pre-exposure (single context vs. multiple contexts) will be between-subject factors. Stimulus type (pre-exposed to-be conditioned stimulus, a non-pre-exposed conditioned stimulus, and an unpaired control stimulus) and trial will serve as within-subject factors. Baseline pain sensitivity will also be measured as a potential moderator. Discussion: It is hypothesized that spaced pre-exposure and pre-exposure in multiple contexts will increase the engagement of the mechanisms of expected relevance and attention and increase the latent inhibition of dental fear. It is expected that the findings will add to theory on fear learning and provide information to aid the design of future interventions that leverage latent inhibition to reduce dental phobia.
Collectivism, face concern and Chinese-style lurking among university students: the moderating role of trait mindfulness
Field: PSYCHOLOGY

Introduction This study focuses on understanding the unique causes and mechanisms of “Chinese-style lurking” on WeChat among university students, within a cultural context that emphasizes collectivism and face concern. The research also looks into the moderating role of trait mindfulness. Methods For the confirmation of these phenomena and to validate the theories, a structural equation model was constructed using the Stress-Strain-Outcome (SSO) theory and mindfulness buffering theory. The model was then tested and validated with data from 1,453 valid online surveys. These data were analyzed using the SmartPLS 4.0 software. Results The results indicate that collectivism increases face concern, which in turn escalates online social anxiety. Face concern completely mediates between collectivism and online social anxiety, creating a serial mediation effect between face concern, online social anxiety, and lurking behavior. Additionally, trait mindfulness was found to negatively modulate the pathways from collectivism to face concern and from online social anxiety to lurking. Discussion The findings underscore the influence of traditional Chinese culture on contemporary students' online behavior and provide a new perspective for understanding social media lurking in an Eastern context. The results suggest that a mindfulness-based approach could be used to mitigate the associated silence and anxiety.
Graph Convolutional Network with Syntactic Dependency for Aspect-Based Sentiment Analysis
Field: AI

Aspect-based sentiment analysis (ABSA) aims to mine the sentiment tendencies expressed by specific aspect terms. The studies of ABSA mainly focus on the attention-based approaches and the graph neural network approaches based on dependency trees. However, the attention-based methods usually face difficulties in capturing long-distance syntactic dependencies. Additionally, existing approaches using graph neural networks have not made sufficient exploit the syntactic dependencies among aspects and opinions. In this paper, we propose a novel Syntactic Dependency Graph Convolutional Network (SD-GCN) model for ABSA. We employ the Biaffine Attention to model the sentence syntactic dependencies and build syntactic dependency graphs from aspects and emotional words. This allows our SD-GCN to learn both the semantic relationships of aspects and the overall semantic meaning. According to these graphs, the long-distance syntactic dependency relationships are captured by GCNs, which facilitates SD-GCN to capture the syntactic dependencies between aspects and viewpoints more comprehensively, and consequently yields enhanced aspect features. We conduct extensive experiments on four aspect-level sentiment datasets. The experimental results show that our SD-GCN outperforms other methodologies. Moreover, ablation experiments and visualization of attention further substantiate the effectiveness of SD-GCN.
Reserve-building as a buffer for depression among individuals living with disability: a longitudinal study of current activities related to brain health
Field: PSYCHOLOGY

Aims This study examined whether reserve-building activities are associated with attenuated reported depression among people who were disabled from work due to a medical condition as compared to employed, retired, and unemployed participants. Methods This secondary analysis included 771 individuals who provided data at three time points: baseline (late Spring 2020), follow-up 1 (Spring 2021), and follow-up 2 (Fall 2021). The DeltaQuest Reserve-Building Measure assessed current activities related to brain health. An analysis of variance and Pearson correlation coefficients assessed group differences in reserve-building activity scores. Classification and regression tree (CART) modeling investigated factors associated with higher and lower reported depression by employment group. The random effects (RE) models tested two buffering hypotheses: (1) comparing all groups to the employed group and (2) examining within-group effects. Results Engaging in outdoor activities, exercise, and religious/spiritual activities was associated with reduced depression over time in the overall sample. While disabled participants endorsed lower levels of being Active in the World, Outdoor activities, and Exercise and higher levels of Inner Life and Passive Media Consumption than the other employment groups, more reserve-building activities distinguished depression levels in the disabled group's CART models compared to the others. Among the disabled, unemployed, and retired participants, engaging in any reserve-building activities was also associated with lower depression scores, which was distinct from the employed participants. In the RE models that used the employed group as the reference category, only the disabled group's level of depression was buffered by engaging in creative activities. In the within-group RE models, the disabled group's engagement in Religious/Spiritual, Outdoors, and Games was associated with substantially reduced within-group depression, which was different from the other employment groups. In contrast, reserve-building activities were not implicated at all as buffers for employed participants. Conclusion This study revealed a beneficial effect of reserve-building activities on buffering depression over time during the COVID-19 pandemic, particularly for disabled people. It documented that even if such individuals engaged in lesser amounts of such activities as compared to other employment groups, the buffering effect was substantial. Given the low-cost and accessible nature of reserve-building activities, it would be worthwhile to encourage such activities for disabled individuals.
Using collaborative autoethnography to investigate mentoring relationships for novice engineering education researchers
Field: EDUCATION

Background: The National Science Foundation Research Initiation in Engineering Formation (RIEF) program aims to increase research capacity in the field by providing funding for technical engineering faculty to learn to conduct engineering education research through mentorship by an experienced social science researcher. We use collaborative autoethnography to study the tripartite RIEF mentoring relationship between Julie, an experienced engineering education researcher, and two novice education researchers who have backgrounds in biomedical engineering—Paul, a biomedical engineering faculty member and major professor to the second novice, Deepthi, a graduate student. We ground our work in the cognitive apprenticeship model and Eby and colleagues’ mentoring model. Results: Using data from written reflections and interviews, we explored the role of instrumental and psychosocial supports in our mentoring relationship. In particular, we noted how elements of cognitive apprenticeship such as scaffolding and gradual fading of instrumental supports helped Paul and Deepthi learn qualitative research skills that differed drastically from their biomedical engineering research expertise. We initially conceptualized our tripartite relationship as one where Julie mentored Paul and Paul subsequently mentored Deepthi. Ultimately, we realized that this model was unrealistic because Paul did not yet possess the social science research expertise to mentor another novice. As a result, we changed our model so that Julie mentored both Paul and Deepthi directly. While our mentoring relationship was overall very positive, it has included many moments of miscommunication and misunderstanding. We draw on Lent and Lopez’s idea of relation-inferred self-efficacy to explain some of these missed opportunities for communication and understanding. Conclusions: This paper contributes to the literature on engineering education capacity building by studying mentoring as a mechanism to support technically trained researchers in learning to conduct engineering education research. Our initial mentoring model failed to take into account how challenging it is for mentees to make the paradigm shift from technical engineering to social science research and how that would affect Paul’s ability to mentor Deepthi. Our experiences have implications for expanding research capacity because they raise practical and conceptual issues for experienced and novice engineering education researchers to consider as they form mentoring relationships.
Systemic advantage has a meaningful relationship with grade outcomes in students’ early STEM courses at six research universities
Field: EDUCATION

Background: Large introductory lecture courses are frequently post-secondary students’ first formal interaction with science, technology, engineering, and mathematics (STEM) disciplines. Grade outcomes in these courses are often disparate across student populations, which, in turn, has implications for student retention. This study positions such disparities as a manifestation of systemic inequities along the dimensions of sex, race/ethnicity, income, and first-generation status and investigates the extent to which they are similar across peer institutions.Results: We examined grade outcomes in a selected set of early STEM courses across six large, public, research-intensive universities in the United States over ten years. In this sample of more than 200,000 STEM course enrollments, we find that course grade benefits increase significantly with the number of systemic advantages students possess at all six institutions. The observed trends in academic outcomes versus advantage are strikingly similar across universities despite the fact that we did not control for differences in grading practices, contexts, and instructor and student populations. The findings are concerning given that these courses are often students’ first post-secondary STEM experiences.Conclusions: STEM course grades are typically lower than those in other disciplines; students taking them often pay grade penalties. The systemic advantages some student groups experience are correlated with significant reductions in these grade penalties at all six institutions. The consistency of these findings across institutions and courses supports the claim that inequities in STEM education are a systemic problem, driven by factors that go beyond specific courses or individual institutions. Our work provides a basis for the exploration of contexts where inequities are exacerbated or reduced and can be used to advocate for structural change within STEM education. To cultivate more equitable learning environments, we must reckon with how pervasive structural barriers in STEM courses negatively shape the experiences of marginalized students.
Psychological Distress and Behavioral Vigilance in Response to Minority Stress and Threat among Members of the Asian American and Pacific Islander Community during the COVID-19 Pandemic
Field: PSYCHOLOGY

Stigmatization, hostility, and violence towards the Asian American and Pacific Islander (AAPI) community have increased sharply during the COVID-19 pandemic. It is important to conduct research to promote understanding of the effects of such stigmatization on the AAPI community. Accordingly, the present study used a combined minority stress and integrated threat framework to examine whether factors related to AAPI identity would moderate the relationship between stigmatization/threat associated with AAPI identity and increased psychological distress and behavioral vigilance. AAPI individuals were recruited online from both Turk Prime and Reddit and completed measures of perceived stigmatization; integrated threat; depression, anxiety, and stress; and behavioral vigilance. Perceptions of stigmatization and threat predicted relevant outcomes both as individual predictors and in multivariate analyses. However, factors relating to the strength of AAPI identification did not moderate the effects of stigmatization and threat on psychological distress and behavioral vigilance, which is a result that failed to support this aspect of the broader conceptual model on which this project was based. Instead, these proposed moderators were themselves predicted by stigmatization and threat variables. The implications of these findings for effective interventions to alleviate the negative consequences of anti-Asian stigmatization are discussed.
Characteristics of Early Pancreatic Cancer: Comparison between Stage 1A and Stage 1B Pancreatic Cancer in Multicenter Clinical Data Warehouse Study
Field: ONCOLOGY

Background: Little is known about the characteristics of early pancreatic cancer. We aimed to identify the characteristics, clues for early detection, and prognostic factors for early pancreatic cancer by analyzing a large number of patients with stage 1 pancreatic cancer. Methods: A clinical data warehouse that includes databases of all the medical records of eight academic institutions was used to select and analyze patients with pancreatic cancer that had been diagnosed from January 2010 to May 2023. Results: In total, 257 stage 1 pancreatic cancer patients were included. There were 134 men (52%), and the average age was 67.2 ± 9.9 years. Compared to patients with stage 1B pancreatic cancer (2–4 cm), patients with stage 1A pancreatic cancer (≤2 cm) had more tumors in the body and tail than in the head (p = 0.028), more new-onset diabetes and less old diabetes (p = 0.010), less jaundice (p = 0.020), more follow-up of IPMN (intraductal papillary mucinous neoplasm, p = 0.029), and more histories of acute pancreatitis (p = 0.013). The pathological findings showed that stage 1A pancreatic cancer involved more IPMNs (p < 0.001) and lower pancreatic intraepithelial neoplasia (p = 0.004). IPMN was present in all 13 pancreatic tumors that were smaller than 1 cm. In multivariate analysis, positive resection margin (odds ratio [OR] 1.536, p = 0.040), venous invasion (OR 1.710, p = 0.010), and perineural invasion (OR 1.968, p = 0.002) were found to be risk factors affecting disease-free survival, while old diabetes (odds ratio [OS] 1.981, p = 0.003) and perineural invasion (OR 2.270, p = 0.003) were found to be risk factors affecting overall survival. Conclusions: IPMN is closely associated with early pancreatic cancer and may provide an opportunity for early detection. The presence of perineural invasion was a crucial prognostic factor for both overall and disease-free survival in patients with stage 1 pancreatic cancer.
“Who’s the Student at Home?”: Parental Help-Giving Orientation in Learning at Home Predicted using a Parent’s Personal Characteristics
Field: EDUCATION

The present study focuses on the involvement of a parent in their child’s learning processes, particularly, their help-giving orientation while learning at home. The main goal of the study was to identify the connection between the parent’s personal characteristics and the help-giving orientation the parent provides to their child: autonomous vs. dependent (parent as student) help-giving. The sample was collected using online participant recruitment surveys in Israel. In total, 306 parents aged 27–59, who had at least one child in elementary school, answered five questionnaires measuring the research variables: the short grit scale; the satisfaction with life scale; the advice/affect management–overparenting subscale; the parenting sense of competence scale; the parental help-giving orientations scale (PHGOs), and a background questionnaire. The findings identified negative associations between parental personal characteristics (grit, advice/affect management, well-being) and parent-as-student orientation and positive associations between the parent’s characteristics and parental autonomous help-giving orientation, with all of these effects at least partially mediated by parental self-efficacy (indirect effects). The results provide greater insight into the relationship between a parent’s personal characteristics and their choice of assistance to their child and contribute to the knowledge regarding parental involvement in learning at home and educational contexts in general.
Intelligent Vehicle Violation Detection System Under Human–Computer Interaction and Computer Vision
Field: AI

In view of the current problems of low detection accuracy, poor stability and slow detection speed of intelligent vehicle violation detection systems, this article will use human–computer interaction and computer vision technology to solve the existing problems. First, the picture data required for the experiment is collected through the Bit Vehicle model dataset, and computer vision technology is used for preprocessing. Then, use Kalman filtering to track and study the vehicle to help better predict the trajectory of the vehicle in the area that needs to be detected; finally, use human–computer interaction technology to build the interactive interface of the system and improve the operability of the system. The violation detection system based on computer vision technology has an accuracy of more than 96.86% for the detection of the eight types of violations extracted, and the average detection is 98%. Through computer vision technology, the system can accurately detect and identify vehicle violations in real time, effectively improving the efficiency and safety of traffic management. In addition, the system also pays special attention to the design of human–computer interaction, provides an intuitive and easy-to-use user interface, and enables traffic managers to easily monitor and manage traffic conditions. This innovative intelligent vehicle violation detection system is expected to help the development of traffic management technology in the future.
No End in Sight; Assessing the Impact of Internet Gaming Disorder on Digital Eye Strain Symptoms and Academic Success
Field: PSYCHOLOGY

Background: Internet Gaming Disorder (IGD) has been associated with symptoms of Digital Eye Strain (DES) and poor academic performance among adolescent students. The purpose of this study is to assess whether a student’s achievement of a specific academic goal within a short period of time can be directly predicted by symptoms of IGD and DES. Methods: This is a cross-sectional survey of 140 high school graduates who received an examination of visual acuity as a pre-requisite for entering the written admission examinations of law enforcement and military academies. The students completed the Digital Eye Strain Questionnaire (DESQ) and the Ten-Item Internet Gaming Disorder Test (IGDT-10) and stated their own evaluation of their chances for success. They were contacted following their admission examinations, and their success or failure to be admitted was recorded. Results: The students with IGD symptomatology were more likely to present with symptoms of DES. They were also more pessimistic about their chances of success in the subsequent written admission examinations; none succeeded, while the rest of the students recorded an expected rate of success. A combination of IGD and complaints related to the prolonged fixation of the upper body in a specific viewing position was the best predictor variable set for future success in admission examinations. Conclusions: IGD is associated with a failure to achieve academic success. Combining a factor for physical discomfort during prolonged sessions of gaming with the typical criteria for IGD may expand the predictive validity of the construct of gaming disorder.