Unique Correlation Research Articles

Longitudinal patterns of alcohol and cannabis use among US young adults: Correlates and implications for problematic health outcomes.

Alcohol and cannabis use are common during young adulthood. Less is known regarding correlates of alcohol-cannabis use patterns and related problematic health outcomes. Using longitudinal survey data (Fall 2018, 2019, 2020) from 2,194 young adults (YAs; ages 18-34), bivariate analyses and multivariable logistic regressions examined: (1) Wave 1 (W1) sociodemographics and psychosocial factors (i.e., adverse childhood experiences [ACEs], depressive symptoms, personality traits, parent and peer alcohol and cannabis use) in relation to W3 past-month use group (i.e., use of neither, alcohol only, cannabis only, both/co-use); and (2) W3 use group in relation to W5 problematic alcohol use (Alcohol Use Disorder Identification Test), problematic cannabis use (Cannabis Use Disorder Identification Test), and depressive/anxiety symptoms (Patient Health Questionnaire - 4 item). Overall, 42.3% reported W3 alcohol-only use, 34.9% co-use, 17.8% no use, and 5.0% cannabis-only use. Those reporting W3 co-use reported greater W1 extraversion, openness, friend alcohol/cannabis use, and were more likely to report parent cannabis use (vs. no use); reported less conscientiousness, greater friend cannabis use, and were more likely to report depressive symptoms and parent cannabis use (vs. alcohol-only use); and reported greater friend alcohol use, and were more likely to report parent alcohol use (vs. cannabis-only use). W3 co-use was associated with higher odds of W5 problematic alcohol use (vs. alcohol-only use) and problematic cannabis use (vs. cannabis-only use). Substance use messaging and interventions should consider YAs' alcohol-cannabis co-use and the unique correlates of such use.

Adolescent social stress alters the role of orexin innervation in the hindbrain in male hamsters.

Juvenile male hamsters exposed to chronic social stress eat more, gain weight, and have larger fat pads. The purpose of the present study was to address possible changes in food hoarding and orexin/hypocretin innervation in response to social stress. Male hamsters in early adolescence were exposed to a resident-intruder social stress paradigm or control condition daily for 2 weeks. Metabolism-related physiological measures and behaviors were tracked, and brains were immunocytochemically labeled for orexin-A. Our data confirm our previous observations on appetite, weight gain, and obesity, and showed a strong trend toward enhanced food hoarding as in prior studies. In addition, there were no statistically significant differences in orexin innervation in any brain area analyzed. However, unique correlation patterns were observed between orexin innervation and appetite or metabolic outcome. In particular, opposite correlations were observed between groups within the dorsal raphe nucleus, lateral parabrachial nucleus, and nucleus of the solitary tract. These opposite patterns of correlations suggest chronic social stress causes site-specific alterations in synaptic activity in relation with these behaviors.

Variable Presence of an Evolutionarily New Brain Structure is Related to Trait Impulsivity.

Impulsivity is a multidimensional construct reflecting poor constraint over one's behaviors. Clinical psychology research identifies separable impulsivity dimensions that are each unique transdiagnostic indicators for psychopathology. Yet, despite this apparent clinical importance, the shared and unique neuroanatomical correlates of these factors remain largely unknown. Concomitantly, neuroimaging research identifies variably present human brain structures implicated in cognition and disorder: the folds (sulci) of the cerebral cortex located in the latest developing and most evolutionarily expanded hominoid-specific association cortices. We tethered these two fields to test whether variability in one such structure in anterior cingulate cortex (ACC)-the paracingulate sulcus (PCGS)-was related to individual differences in trait impulsivity. 120 adult participants with internalizing or externalizing psychopathology completed a magnetic resonance imaging scan and the Three-Factor Impulsivity Index. Using precision imaging techniques, we manually identified the PCGS, when present, and acquired quantitative folding metrics (PCGS length and ACC local gyrification index). Neuroanatomical-behavioral analyses revealed that participants with leftward or symmetrical PCGS patterns had greater severity of Lack of Follow Through (LFT)-which captures inattention and lack of perseverance-than those with rightward asymmetry. Neuroanatomical-functional analyses identified that the PCGS co-localized with a focal locus found in a neuroimaging meta-analysis on a feature underlying LFT. Both quantitative folding metrics did not relate to any impulsivity dimension. This study advances understanding of the neuroanatomical correlates of impulsivity and establishes the notion that the topographical organization of distinct, hominoid-specific cortical expanses underlie separable impulsivity dimensions with robust, transdiagnostic implications for psychopathology.

Insights into the plankton community seasonal variations in a finer scale of the Bohai Sea: biodiversity, trophic linkage, and biotic-abiotic interplay

Plankton play an indispensable role in the biogeochemical processes of marine ecosystem. However, unraveling the intricate interactions among biodiversity, trophic linkages, and biotic-abiotic interplay between phytoplankton-zooplankton remains a significant challenge. Here, we conducted field studies in the neritic area of the Bohai Sea during autumn 2023 and spring 2024 to explore seasonal variations of both phytoplankton and zooplankton through microscope. Our analysis revealed a sharp decline in trophic interactions across phytoplankton and zooplankton, with an abundance ratio in autumn 2023 being 5.5 times higher than in spring 2024. Additionally, dominant plankton species (Y ≥ 0.02) exhibited obvious differences between the two seasons, with higher species diversity observed in autumn. Moreover, each dominant zooplankton species had distinct preferred food items in both seasons, with Rhizosolenia setigera being favored by Noctiluca scintillans and Acartia pacifica. Furthermore, a multivariate biota-environment analysis indicated that each dominant plankton species had unique correlation with specific environmental parameters, highlighting how plankton can fully exploit external environmental conditions to survive in seasonal variations. Ultimately, our findings emphasize significant seasonal dynamics and provide a solid foundation for assessing the potential impacts of environmental changes on plankton in coastal marine realm.

Prospects of universal influenza virus vaccine and the current challenges of new antiviral drugs

The profound impact of influenza viruses on human health persists as a significant burden, given their potent capacity to cause morbidity and mortality. Despite efforts to mitigate the annual burden of influenza, the effectiveness of current seasonal vaccines in providing substantial protection falls short, leaving undesirable pandemic of influenza viruses. The challenges posed by the influenza pandemic lies from the constant changes inherent in the virus itself, as well as the limitations of current immunization approaches in achieving sufficient immunogenicity. Influenza viruses exhibit antigenic drift and shift, undergoing antigenic evolution by altering the surface glycoproteins. These changes contribute to the persistent and dynamic nature of the influenza virus, posing formidable challenges to effective prevention and control strategies. Currently, there is growing recognition of unique viral targets that hold promise development of broad-protective vaccines against influenza. These targets are distinct from traditional vaccine targets and offer the potential for more comprehension protection against diverse strains of the virus. Here, we present a review about the novel drugs and vaccines that target the influenza virus would signify the unique immune correlates of protection that need to be initiated to accelerate the vaccine efficacy.

The Relationship Between Racial Attitudes and Disordered Eating Behaviors in Black Men and Black Women.

Black individuals remain underrepresented in disordered eating research, despite evidence that both Black men and women present with disordered eating behaviors. Culturally-informed theoretical frameworks suggest that these behaviors may be linked to race-related sociocultural experiences, such as aspects of racial identity. While studies have focused on racial identity commitment, the association between attitudes toward one's racial identity and disordered eating remains underexplored. The present study examines whether positive attitudes toward one's Blackness and Black culture are associated with disordered eating. In a cross-sectional online sample of Black men and women (N = 458), we measured self-reported attitudes toward Blackness (i.e., centrality and private regard) and disordered eating behaviors (i.e., purging, binge eating, excessive exercise, and drive for thinness). In pre-registered linear regression models, private regard was negatively associated with purging and binge eating. Across all models, centrality was not associated with disordered eating. On average, Black women reported greater drive for thinness whereas Black men reported higher excessive exercise scores. This is the first study to demonstrate associations between racial attitudes and disordered eating among Black men and women. Our findings affirm unique correlates of disordered eating among Black people and suggest that positive attitudes toward one's Blackness and Black culture may be a protective factor against the development of disordered eating.

Categorizing E-cigarette-related tweets using BERT topic modeling

BackgroundSocial media platforms are critical channels for promoting e-cigarettes, particularly among youth, making analysis of their vast and diverse content essential for public health interventions. Prevalence rates of e-cigarette use are high and evidence suggests that social media are popular forums that promote e-cigarette use through direct and indirect marketing techniques. The volume and diverse nature of e-cigarette-related information on social media is challenging and may obfuscate public health prevention messaging. Traditional hand-coding methods are labor-intensive and limit scalability. In contrast, unsupervised machine learning approaches, such as topic modeling, allow for efficient analysis of large datasets, uncovering patterns and trends that manual methods cannot achieve at scale. The present study focused on ascertaining the extent to which themes and topics in tweets related to e-cigarettes can be successfully rendered into useful homogenous units using machine learning. A better understanding of current depictions and discussions around e-cigarette products and use on social media can inform public health counter messaging and policy interventions. MethodsWe used topic modeling (BERTopic) to iteratively derive vape-related tweet clusters and calculate the importance of particular words to these groupings. We conducted a qualitative content analysis to study clustered tweets. We also sought to determine the geographic locations of e-cigarette conversations using automated geoparsing methods, which translate toponyms in textual data into geographic identifiers, to attempt to infer the location of tweets. ResultsWe were able to successfully identify >100,000 tweets in broad thematic categories in English and Spanish. Our correlation and inter-topic map analysis of the machine-derived topics, which examines the relationships between topics, indicated that most of the topics were unique (correlation value < 0.5) and did not overlap with each other. We identified six topics: Flavors and Disposable Vapes, Cannabis, Vape Shops and Refillable Vapes, Vape Culture, Anti-vaping and Quitting, and Spanish Tweets and Vaping Nicotine. Further analysis of these topics using qualitative methods identified themes within each topic. For example, Category 6 (Spanish Tweets and Vaping Nicotine) included four topics focused on the health risks of vaping, personal motivations for vaping, and the regulation of vaping products. Using geoparsing, which automatically detects location information, we found that the United States had the highest number of tweets related to vaping. Discussion/conclusionResults underscore the possibility of leveraging BERTopic modeling to reduce large quantities of data to comprehensively describe and categorize myriad e-cigarette related messages to which social media users are exposed. This data reduction approach can be applied to various social media platforms to describe and categorize e-cigarette posts and thereby triangulate and validate findings. Thematic content analysis of the topics identified through this technique requires supervision and human inputs. Our approach provides a comprehensive understanding of the evolving e-cigarette discourse, informing public health counter-messaging and policy interventions. Moreover, findings support the need for regulation, such as reducing appealing flavors and suggest that social media can be used effectively to support public health messaging (i.e., quitting messages).

Correlates of Sexting Coercion Victimization

In an online sample of adults aged 18 to 30 (n = 2,828), we examined if experiencing sexting coercion victimization was correlated with demographic (e.g., sexual orientation), relationship domain variables (e.g., number and length of relationships), prior victimization, sexuality domain variables (e.g., pornography use), and sexting behaviour (e.g., frequency). Approximately 1 in 5 participants reported being pressured (22%; 620/2,828; Nmen = 125, Nwomen = 495), threatened (5%; 144/2,828; Nmen = 19, Nwomen = 125), or coerced (22%; 629/2,828; Nmen = 127, Nwomen = 502) into sending a sext. Prior victimization, greater mating effort (e.g., multiple partners, infidelity) were unique correlates of experiencing sexting coercion victimization. Alternatively, greater pornography consumption among females was associated with a reduction in the likelihood of experiencing sexting coercion victimization. The study highlights correlates that increase an individual’s susceptibility to coercive sexting. Our findings can inform interventions and future research directions.

Liquefaction behavior and shear strain-based pore pressure model of fiber reinforced calcareous sand

The generation mechanism of pore pressure plays an essential role in understanding the liquefaction behavior of sand under cyclic loading. Extensive undrained simple shear tests were undertaken to study the pore pressure and shear strain development characteristics of calcareous sand reinforced by fibers. The results show that the deformation patterns of the tested calcareous sand gradually shift from brittle to ductile failure as fiber content increases. The mechanism of pore pressure generation in calcareous sand subjected to cyclic loading is quite distinct from that of siliceous sand, exhibiting more pronounced accumulation in the initial stage of cyclic loading. Fiber reinforced calcareous sand exhibits reverse shear contraction behavior when liquefaction is imminent. A remarkable finding is the establishment of a unique correlation between pore pressure ratio and shear strain, irrespective of the fiber reinforcement. Consequently, a shear strain-based pore pressure generation model of reinforced calcareous sand is then developed to predict the pore pressure built-up trend under varying fiber content and length conditions. This model is also applicable to various testing conditions and soil types.

Visualization of hydraulic fracturing in compacted bentonite: The roles of dry density, water content, and pressurization rate

Deep geological repository is typically situated at depths ranging from several hundred to 1000 m below ground, making bentonite engineered barrier potentially vulnerable to high water pressure and even inducing hydraulic fracturing. This study conducted injection tests on compacted GMZ (Gaomiaozi) bentonite with a self-developed visualization set-up. The objective was to unveil the roles of dry density, water content, and pressurization rate in hydraulic fracturing from the perspective of fracturing macro-morphological dynamics and breakthrough characteristics. Moreover, the relationships between breakthrough characteristics and microstructure were examined by MIP (mercury intrusion porosimetry) analysis. Results showed that the fracturing dynamics were characterized by three stages: hydration, cracking, and fracturing stages. Compared to water content and pressurization rate, dry density exerted more pronounced effects on these stages. Increasing dry density can lead to an expansion of circular hydration zone, a more complex cracking network, and a change in fracturing patterns from long and clear to short and fuzzy. In terms of breakthrough characteristics, the breakthrough pressure was positively correlated with dry density and negatively correlated with water content. Interestingly, there is a good and unique logarithmic correlation between the breakthrough pressure and the ratio eM/em of inter-aggregate void ratio and intra-aggregate void ratio, regardless of dry density and water content. Within a certain range (i.e. 200-50 kPa/min), breakthrough pressure showed slight dependency on pressurization rate. Nevertheless, an extremely low pressurization rate of 20 kPa/min caused a transition for the specimen from quasi-brittle to plastic state owning to more water infiltration, thereby hindering fracture initiation and propagation.

Hexokinase HK3-mediated O-GlcNAcylation of EP300: a key regulator of PD-L1 expression and immune evasion in ccRCC

Clear cell renal cell carcinoma (ccRCC) demonstrates enhanced glycolysis, critically contributing to tumor development. Programmed death-ligand 1 (PD-L1) aids tumor cells in evading T-cell-mediated immune surveillance. Yet, the specific mechanism by which glycolysis influences PD-L1 expression in ccRCC is not fully understood. Our research identified that the glycolysis-related gene (GRG) HK3 has a unique correlation with PD-L1 expression. HK3 has been identified as a key regulator of O-GlcNAcylation in ccRCC. O-GlcNAcylation exists on the serine 900 (Ser900) site of EP300 and can enhance its stability and oncogenic activity by preventing ubiquitination. Stably expressed EP300 works together with TFAP2A as a co-transcription factor to promote PD-L1 transcription and as an acetyltransferase to stabilize PD-L1 protein. Furthermore, ccRCC exhibits interactive dynamics with tumor-associated macrophages (TAMs). The uridine 5′-diphospho-N-acetylglucosamine (UDP-GlcNAc), which serves as a critical substrate for the O-GlcNAcylation process, facilitates TAMs polarization. In ccRCC cells, HK3 expression is influenced by IL-10 secreted by M2 TAMs. Our study elucidates that HK3-mediated O-GlcNAcylation of EP300 is involved in tumor immune evasion. This finding suggests potential strategies to enhance the efficacy of immune checkpoint blockade therapy.

Dimensions of parenting during infancy: Testing a latent bifactor model

AbstractIn the current paper, we examined the dimensional structure of parenting using a bifactor model of observed parenting domains during infancy. We validated our parenting dimensions by examining correlations with indicators of family well‐being and child development. Data come from a longitudinal cohort that recruited a diverse sample of mothers (56.5% White) and their newborn child (50.7% males). Parenting was assessed using multiple indicators at an average of 18 months (N = 397). Bifactor modelling revealed a general latent dimension of sensitivity and two unique dimensions indexing emotional input and cognitive input. We found a pattern of shared and unique correlations of the three parenting dimensions with family and child well‐being. The most robust correlations were with the general sensitivity dimension, which we argue cuts across parentings behaviors and is fundamental to development.

Unique versus shared neural correlates of externalizing psychopathology in late childhood.

Childhood externalizing psychopathology is heterogeneous. Symptom variability in conduct disorder (CD), oppositional defiant disorder (ODD), attention-deficit/hyperactivity disorder (ADHD), and callous-unemotional (CU) traits designate different subgroups of children with externalizing problems who have specific treatment needs. However, CD, ODD, ADHD, and CU traits are highly comorbid. Studies need to generate insights into shared versus unique risk mechanisms, including through the use of functional magnetic resonance imaging (fMRI). In this study, we tested whether symptoms of CD, ODD, ADHD, and CU traits were best represented within a bifactor framework, simultaneously modeling shared (i.e., general externalizing problems) and unique (i.e., symptom-specific) variance, or through a four-correlated factor or second-order factor model. Participants (N = 11,878, age, M = 9 years) were from the Adolescent Brain and Cognitive Development Study. We used questionnaire and functional magnetic resonance imaging data (emotional N-back task) from the baseline assessment. A bifactor model specifying a general externalizing and specific CD, ODD, ADHD, and CU traits factors demonstrated the best fit. The four-correlated and second-order factor models both fit the data well and were retained for analyses. Across models, reduced right amygdala activity to fearful faces was associated with more general externalizing problems and reduced dorsolateral prefrontal cortex activity to fearful faces was associated with higher CU traits. ADHD scores were related to greater right nucleus accumbens activation to fearful and happy faces. Results give insights into risk mechanisms underlying comorbidity and heterogeneity within externalizing psychopathology. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Data-driven prediction of rail neutral temperature for continuously welded rails using impulse-based vibration frequencies

Continuously welded rails (CWR) are prone to the development of high thermal-induced load along the axial direction. Excessive levels of load lead to risk of rail buckling and potential for derailment. Knowledge of the in situ rail axial load in CWRs is therefore important to ensure safe rail management. Field-deployable, nondestructive evaluation techniques for measuring the rail load, or a widely adopted alternative called rail neutral temperature (RNT), are desired. This study uses a data-driven approach to investigate if rail dynamic response data, collected in a non-destructive fashion, can be used to predict RNT. The study is based on a data set comprising rail equivalent strain, temperature and vibration resonance frequencies that was collected from a revenue-service rail over a period of nearly two years. All excited vibration resonance peaks are identified from other peaks caused by noise using spectral amplitude variance. Among these resonance peaks, potentially useful resonances are identified with respect to stacked spectra collected across a testing day using an assumed temperature-frequency relation. A subset of the identified useful resonances is then identified based on their consistent appearance across both testing locations and all testing days, strong correlation to effective strain, and strong correlation to each other. Three particular vibration resonances (or vibration modes -- these terms will be used interchangeably throughout this paper unless specified otherwise. The term mode does not necessarily indicate mode shapes or mode families.) emerge from this process as best candidates. A classic feature selection technique, Lasso linear regression, is then employed to identify critical power combinations of the three resonant mode frequencies. Two power combinations exhibit unique correlation to the measured equivalent axial strain at both test locations across all testing days, and thus show particular ability to predict RNT. The RNT is predicted at one test location using different models based on the power combination data from the other location, and vice versa, where the predictions satisfy standard RNT measurement accuracy expectations.

Osmotic gradient ektacytometry - a novel diagnostic approach for neuroacanthocytosis syndromes.

The unique red blood cell (RBC) properties that characterize the rare neuroacanthocytosis syndromes (NAS) have prompted the exploration of osmotic gradient ektacytometry (Osmoscan) as a diagnostic tool for these disorders. In this exploratory study, we assessed if Osmoscans can discriminate NAS from other neurodegenerative diseases. A comprehensive assessment was conducted using Osmoscan on a diverse group of patients, including healthy controls (n = 9), neuroacanthocytosis syndrome patients (n = 6, 2 VPS13A and 4 XK disease), Parkinson's disease patients (n = 6), Huntington's disease patients (n = 5), and amyotrophic lateral sclerosis patients (n = 4). Concurrently, we collected and analyzed RBC indices and patients' characteristics. Statistically significant changes were observed in NAS patients compared to healthy controls and other conditions, specifically in osmolality at minimal elongation index (Omin), maximal elongation index (EImax), the osmolality at half maximal elongation index in the hyperosmotic part of the curve (Ohyper), and the width of the curve close to the osmolality at maximal elongation index (Omax-width). This study represents an initial exploration of RBC properties from NAS patients using osmotic gradient ektacytometry. While specific parameters exhibited differences, only Ohyper and Omax-width yielded 100% specificity for other neurodegenerative diseases. Moreover, unique correlations between Osmoscan parameters and RBC indices in NAS versus controls were identified, such as osmolality at maximal elongation index (Omax) vs. mean cellular hemoglobin content (MCH) and minimal elongation index (EImin) vs. red blood cell distribution width (RDW). Given the limited sample size, further studies are essential to establish diagnostic guidelines based on these findings.

Quantity and Distribution of Muscle Spindles in Animal and Human Muscles.

Muscle spindles have unique anatomical characteristics that can be directly affected by the surrounding tissues under physiological and pathological conditions. Understanding their spatial distribution and density in different muscles is imperative to unravel the complexity of motor function. In the present study, the distribution and number/density of muscle spindles in human and animal muscles were reviewed. We identified 56 articles focusing on muscle spindle distribution; 13 articles focused on human muscles and 43 focused on animal muscles. The results demonstrate that spindles are located at the nerve entry points and along distributed vessels and they relate to the intramuscular connective tissue. Muscles' deep layers and middle segments are the main topographic distribution areas. Eleven articles on humans and thirty-three articles on animals (totaling forty-four articles) focusing on muscle spindle quantity and density were identified. Hand and head muscles, such as the pronator teres/medial pterygoid muscle/masseter/flexor digitorum, were most commonly studied in the human studies. For animals, whole-body musculature was studied. The present study summarized the spindle quantity in 77 human and 189 animal muscles. We identified well-studied muscles and any as-yet unfound data. The current data fail to clarify the relationship between quantity/density and muscle characteristics. The intricate distribution of the muscle spindles and their density and quantity throughout the body present some unique patterns or correlations, according to the current data. However, it remains unclear whether muscles with fine motor control have more muscle spindles since the study standards are inconsistent and data on numerous muscles are missing. This study provides a comprehensive and exhaustive approach for clinicians and researchers to determine muscle spindle status.

Examining the neurostructural architecture of intelligence: The Lothian Birth Cohort 1936 study

Examining underlying neurostructural correlates of specific cognitive abilities is practically and theoretically complicated by the existence of the positive manifold (all cognitive tests positively correlate): if a brain structure is associated with a cognitive task, how much of this is uniquely related to the cognitive domain, and how much is due to covariance with all other tests across domains (captured by general cognitive functioning, also known as general intelligence, or ‘g’)? We quantitatively address this question by examining associations between brain structural and diffusion MRI measures (global tissue volumes, white matter hyperintensities, global white matter diffusion fractional anisotropy and mean diffusivity, and FreeSurfer processed vertex-wise cortical volumes, smoothed at 20mm fwhm) with g and cognitive domains (processing speed, crystallised ability, memory, visuospatial ability). The cognitive domains were modelled using confirmatory factor analysis to derive both hierarchical and bifactor solutions using 13 cognitive tests in 697 participants from the Lothian Birth Cohort 1936 study (mean age 72.5 years; SD = .7). Associations between the extracted cognitive factor scores for each domain and g were computed for each brain measure covarying for age, sex and intracranial volume, and corrected for false discovery rate.There were a range of significant associations between cognitive domains and global MRI brain structural measures (r range .008 to .269, p < .05). Regions implicated by vertex-wise regional cortical volume included a widespread number of medial and lateral areas of the frontal, temporal and parietal lobes. However, at both global and regional level, much of the domain-MRI associations were shared (statistically accounted for by g). Removing g-related variance from cognitive domains attenuated association magnitudes with global brain MRI measures by 27.9–59.7% (M = 46.2%), with only processing speed retaining all significant associations. At the regional cortical level, g appeared to account for the majority (range 22.1–88.4%; M = 52.8% across cognitive domains) of regional domain-specific associations. Crystallised and memory domains had almost no unique cortical correlates, whereas processing speed and visuospatial ability retained limited cortical volumetric associations. The greatest spatial overlaps across cognitive domains (as denoted by g) were present in the medial and lateral temporal, lateral parietal and lateral frontal areas.

EEG correlates to perceived urgency elicited by vibration stimulation of the upper body

Conveying information effectively while minimizing user distraction is critical to human–computer interaction. As the proliferation of audio–visual communication pushes human information processing capabilities to the limit, researchers are turning their attention to haptic interfaces. Haptic feedback has the potential to create a desirable sense of urgency that allows users to selectively focus on events/tasks or process presented information with minimal distraction or annoyance. There is a growing interest in understanding the neural mechanisms associated with haptic stimulation. In this study, we aim to investigate the EEG correlates associated with the perceived urgency elicited by vibration stimuli on the upper body using a haptic vest. A total of 31 participants enrolled in this experiment and were exposed to three conditions: no vibration pattern (NVP), urgent vibration pattern (UVP), and very urgent vibration pattern (VUVP). Through self-reporting, participants confirmed that the vibration patterns elicited significantly different levels of perceived urgency (Friedman test, Holm–Bonferroni correction, p < 0.01). Furthermore, neural analysis revealed that the power spectral density of the delta, theta, and alpha frequency bands in the middle central area (C1, Cz, and C2) significantly increased for the UVP and VUVP conditions as compared to the NVP condition (One-way ANOVA test, Holm–Bonferroni correction, p < 0.01). While the perceptual experience of haptic-induced urgency is well studied with self-reporting and behavioral evidence, this is the first effort to evaluate the neural correlates to haptic-induced urgency using EEG. Further research is warranted to identify unique correlates to the cognitive processes associated with urgency from sensory feedback correlates.

Experimental investigation on methane hydrate-bearing sediment permeability under a wide range of conditions

Depressurization exploitation of hydrate in methane hydrate-bearing sediments (MHBS) causes changes in sediment effective stress, deformation, and hydrate content, often resulting in decreased permeability which reduces gas production efficiency. To investigate the evolution of MHBS permeability subjected to these changing conditions, permeability tests on MHBS of different methane hydrate saturation level were performed during isotropic compression and drained triaxial shearing under a wide range of effective stress conditions. The results obtained from compression tests indicate that with increasing effective stress, MHBS permeability first decreases rapidly and then tends to stabilize, and the influence of hydrate saturation on permeability gradually reduces. The permeability during the triaxial shear process is closely related to volumetric deformation, with shear-contraction specimen exhibiting continuous decrease in permeability and shear-dilation specimens experiencing an increase in permeability. Unique correlation between permeability with effective void ratio (affected by hydrate saturation) was observed at low confining pressure and early stage of shear. However, this relationship becomes nonunique under increased pressure and shear strain. Thus, a unified MHBS permeability model for a range of conditions is established based on the observed relationship between MHBS permeability and effective void ratio, considering the influence of confining stress, shear strain, and the breakage of sediment particles.

A temporal prediction model for ship maneuvering motion based on multi-head attention mechanism

In real-world maritime conditions, accurately predicting ship maneuvering motion over ultrashort periods can enhance the development of more precise vessel control algorithms. This study proposes a prediction model for ship maneuvering that utilizes a multi-head attention mechanism. To form a basis for this data-driven approach, we gathered training data from turning and zigzag tests of a ship conducted in natural sea environments. The model's predictive capability is assessed by comparing two strategies over a fixed 30-time-step forecast horizon: iterative multi-step forecasting (IMS) and direct multi-step forecasting (DMS). Notably, the model employs distinct attention layers to examine the temporal relationships among various motion variables across the three degrees of freedom in the output. Moreover, it uses separate attention layers to explore the distinct time response traits of the input motion states and control signals. The results demonstrate that different motion state variables display unique temporal correlations under different signal sequences, and the proposed network architecture effectively captures these temporal response traits.