Individual Variation Research Articles

Correlation of palatal anatomic characteristics with dermatoglyphic heterogeneity in different growth patterns

The study aimed to explore the correlation between dermatoglyphic patterns and quantitative palatal anatomic variables in individuals with different growth patterns. A cross-sectional study was conducted involving 126 healthy patients aged 17-25 years. Participants were divided into three groups based on growth patterns: average, vertical, and horizontal. Dermatoglyphic patterns were recorded using an optical fingerprint sensor, and palatal characteristics were measured using digital software. Palatal characteristics, including intercanine width, intermolar width, and palatal depth, were measured using digital software. The results were statistically analyzed. Significant differences were observed in ridge counts among the three growth patterns. The average growth pattern showed lower ridge counts compared to the vertical and horizontal growth patterns. Dermatoglyphic patterns, such as double loops and tented arches, were significantly higher in the horizontal growth pattern. Weak correlations were found between certain dermatoglyphic patterns and palatal characteristics, with simple arch patterns showing a negative correlation with inter-canine width and symmetrical whorl patterns showing a positive correlation with palatal depth. Loop patterns, spiral patterns, double loop patterns, symmetrical whorl, and simple arch patterns were significant predictors of growth patterns. This study revealed distinct dermatoglyphic patterns and ridge counts among individuals with different growth patterns. Weak correlations were observed between dermatoglyphic patterns and palatal characteristics. However, the predictive value of dermatoglyphics for skeletal malocclusion requires further investigation. Understanding the relationships between dermatoglyphic patterns and craniofacial growth can provide valuable insights into genetic and developmental factors affecting dental and orthodontic conditions.

Development of SSR markers related to agarwood production and genetic diversity of Aquilaria sinensis (Lour.) Spreng wild populations

Aquilaria sinensis (Lour.) Spreng is an economically important tree that produces agarwood when it is subjected to mechanical wounding. However, the information regarding its heredity is limited. The breeding of A. sinensis has been hindered due to ambiguity in the sources of germplasm, genetic background, and varietal information. Simple sequence repeat (SSR) markers are ideal for studying genetic diversity and germplasm identification in plants. They offer the advantages of high polymorphism, good reproducibility, and co–dominance. Here, we mined SSR markers within agarwood–inducing genes and used them to explore the genetic diversity among A. sinensis natural germplasm. A total of 407 SSR loci were identified within 92 genes. We designed 96 primer pairs, among which 16 showed polymorphism and were subsequently used to analyze the genetic diversity and population structure of 179A. sinensis individuals. A total of 107 alleles were identified, with an average of 7 alleles per locus, and their polymorphism information content ranged between 0.424 to 0.769, with an average of 0.569. The analysis of molecular variance revealed that genetic variation within the individuals accounted for 94% of the total variation, indicating that the variation of A. sinensis is derived from individual variation. Furthermore, the structure analysis indicated that the natural populations of A. sinensis could be theoretically divided into 16 subgroups. The 16 polymorphic SSRs had strong cross–species transferability and distinguished individuals of A. agallochum (Lour.) Roxb. ex Finl. and A. malaccensis Lam. Taken together, these findings provide a useful resource for germplasm identification and molecular marker–assisted breeding of A. sinensis.

Occupational self-efficacy scale: Validity in teachers

Occupational self-efficacy has gained attention because of its importance in understanding the effects of psychosocial factors at work, but because of its relevance, it is necessary to study it in the context of the COVID-19 pandemic. The Occupational Self-Efficacy Short Scale Form (OSS-SF) is a measure of individual variability in self-efficacy within the work context and has been used in some studies in Latin America. The aim of this study was to obtain evidence of the validity of the OSS-SF for 214 Peruvian teachers and to evaluate its internal structure and associations with other constructs. The sample, composed of 214 teachers (Mage = 44, SDage = 10), was selected using nonprobabilistic convenience sampling and evaluated via online forms. Nonparametric item response theory was used. Among the results, a unidimensional structure and high scalability at the item and scale levels were obtained (>0.70). The reliability was approximately 0.90. There was moderate convergence with job satisfaction (0.39) and slight convergence with the perception of the management of virtual tools (0.18). The OSS-SF is a scale with adequate evidence of validity and reliability for Peruvian teachers who work remotely. Therefore, it can be used as a diagnostic measure of intervention and training needs to benefit teachers and students.

Investigating the Prevalence and Predictors of Apathy among the Canadian Long-Term Care Residents: A Secondary Data Analysis.

In long-term care facilities (LTCF), apathy is a prevalent issue, leading to cognitive decline, functional impairment, and increased mortality risk. Despite its significance, apathy often remains underrecognized and undermanaged in these settings. Recognizing and addressing the predictors of apathy is critical for early intervention and improved care outcomes. This study aims to assess the prevalence of apathy and identify its associated risk factors among newly admitted residents in the Canadian LTCF, using the InterRAI Minimum Data Set (MDS 2.0). We conducted a cross-sectional analysis of MDS 2.0 admission assessment data between 2015 and 2019, covering 157,596 residents across six Canadian provinces and one territory. Apathy was measured using the Apathy Index of the MDS 2.0, with the biopsychosocial model guiding the analysis. The prevalence of apathy was 12.5% (19,758 individuals). The most significant predictors include cognitive impairments, specific age groups, hearing impairments, vision impairments, facility size and location. The findings of this study underscore the need for tailored strategies in LTCF to address apathy, considering individual, institutional, and regional variations. Emphasis on environmental and personal factors is crucial in the management and prevention of apathy in these settings.

Use of weather types to analyze the simultaneous abundance of ozone, PM2.5 and allergenic tree pollen: focusing on the potential impact on asthma hospitalization in Montreal, Canada

AbstractAir pollution, aeroallergens, and weather conditions can worsen health symptoms such as asthma. While studying the impact of these factors, the use of weather types (WTs) rather than individual meteorological variables (such as temperature, relative humidity, wind, cloudiness, or precipitation) is more appropriate since it is holistic and integrative. Moreover, several studies have shown that the human body responds to WTs, rather than to individual meteorological variables. In this study, the use of Sheridan’s WTs is adopted and compared with a so-called “In-House” WTs. The analysis presented here deals with the links between asthma hospitalization and the synergy among air pollution, birch tree pollen and WTs. Knowing the daily WT in a region can provide valuable information for health planning and management of asthma hospitalization, emergency visits and sub-clinical symptoms in the population. This is because air pollution and birch pollen both occur within only a few specific WTs, such as the TROWAL (trough of warm air aloft) or tropical airmasses. These specific WTs need to be more scrutinized since, in Montreal, these are often linked with higher daily mean hospitalization. The findings of this study emphasize the importance of specific WTs in determining the maximum daily concentrations of ozone, fine particles, Betula pollen concentrations and health effects such as asthma hospitalization. Moreover, the use of data filters in the analysis (for temperature and total count of hospitalization) also reveals new insights in the complex nature of asthma disease and its relationship with environmental factors.

The Ubiquitous External Ejaculation: Examining Perceptions of Sexual Images Across Cultures.

The persistent debates over pornography have often focused on differences between males and females, not only in the frequency of consumption or the type of material consumed, but also on the different ways that individuals may perceive sexually explicit images and respond to them. Some of these differences may be due to sex differences in a number of factors including sexual strategies, pathogen or sexual disgust, and own mate value as well as within sex differences in these factors. Previous studies have demonstrated that perceptions of sexually explicit images are influenced by the sex of the target in the image and the target's emotional affect, as well as sex of the respondent, their sexual orientation, short-term mating orientation, and disgust measures. However, these previous studies were conducted with participants from the United States alone. This study compared the findings from these US samples to those from non-Western ones (Philippines and Brazil) in order to examine the replicability across cultures of the US results as well as whether some variables (religiosity, for example) account for more or less of the variance in perceptions in different populations. Results indicated that there were some differences in terms of the amount of variance in perceptions explained by different variables across populations. Participant and stimuli related variables explained more variance in the Philippines while individual difference variables accounted for more variance in Brazil.

TS-AI: A deep learning pipeline for multimodal subject-specific parcellation with task contrasts synthesis

Accurate mapping of brain functional subregions at an individual level is crucial. Task-based functional MRI (tfMRI) captures subject-specific activation patterns during various functions and behaviors, facilitating the individual localization of functionally distinct subregions. However, acquiring high-quality tfMRI is time-consuming and resource-intensive in both scientific and clinical settings. The present study proposes a two-stage network model, TS-AI, to individualize an atlas on cortical surfaces through the prediction of tfMRI data. TS-AI first synthesizes a battery of task contrast maps for each individual by leveraging tract-wise anatomical connectivity and resting-state networks. These synthesized maps, along with feature maps of tract-wise anatomical connectivity and resting-state networks, are then fed into an end-to-end deep neural network to individualize an atlas. TS-AI enables the synthesized task contrast maps to be used in individual parcellation without the acquisition of actual task fMRI scans. In addition, a novel feature consistency loss is designed to assign vertices with similar features to the same parcel, which increases individual specificity and mitigates overfitting risks caused by the absence of individual parcellation ground truth. The individualized parcellations were validated by assessing test-retest reliability, homogeneity, and cognitive behavior prediction using diverse reference atlases and datasets, demonstrating the superior performance and generalizability of TS-AI. Sensitivity analysis yielded insights into region-specific features influencing individual variation in functional regionalization. In addition, TS-AI identified accelerated shrinkage in the medial temporal and cingulate parcels during the progression of Alzheimer's disease, suggesting its potential in clinical research and applications.

A mixed-methods longitudinal examination of weight-related self-monitoring and disordered eating among a population-based sample of emerging adults

BackgroundWeight-related self-monitoring (WRSM) apps are used by millions, but the effects of their use remain unclear. This study examined longitudinal relationships between WRSM and disordered eating among a population-based sample of emerging adults.MethodsParticipants (n = 138) were recruited from EAT 2010–2018 (Eating and Activity over Time study) to participate in a mixed-methods (quantitative and qualitative) longitudinal study to understand the impacts of WRSM. In 2018, participants (Mage=21.7 ± 1.9 years) reported motivations for use and types of WRSM apps used. Dependent variables collected in 2022 (Mage=25.7 ± 1.9 years) included past year total number of disordered weight control behaviors, disordered muscle building behaviors, compulsive exercise, and binge eating. Linear and logistic regressions were used adjusting for sociodemographics, body mass index, and baseline disordered eating. Semi-structured interviews (n = 25) were analyzed using inductive thematic analysis.ResultsParticipants using WRSM apps for weight management demonstrated an increase in disordered weight control behaviors over time (β = 0.894, p = .012). Using WRSM apps for “healthy” eating was marginally associated with an increase in disordered weight control behaviors. (β = 0.673, p = .052). Qualitatively, participants reported varied temporality between WRSM and disordered eating, but believed that app use encouraged restriction/binge cycles and normalized disordered eating.ConclusionsFindings suggest there may be individual variation in the relationships between WRSM and disordered eating, but that using WRSM apps with the motivation of managing eating or weight may increase disordered eating in some. Additionally, WRSM apps may normalize or encourage disordered eating. Therefore, safeguards, including screening and monitoring, are needed to ensure WRSM does not cause or escalate harm among WRSM users.

Crossing borders, casting votes: examining migrant electoral turnout in Chile (2012–2020)

ABSTRACT Our analysis focuses on the determinants of electoral participation among migrants, considering individual factors—gender and age—and variables from their countries of origin, such as economic, political, and institutional aspects. We specifically look at Chile, where migrants are allowed to vote in all elections after acquiring five years of permanent residency. Utilizing a comprehensive administrative census covering over 70 million voters, including 1.2 million migrants, from 2012 to 2020, our findings reveal several key patterns: Gender and age significantly influence voting behavior, with higher turnout among women and older migrants. Additionally, migrants from wealthier nations tend to vote less compared to those from poorer countries. Furthermore, the presence of compulsory voting in the origin country significantly increases participation among migrants, especially those from less democratic or non-democratic countries. This study bridges theoretical models that focus on individual variables and those that emphasize the impact of origin country characteristics on migrant electoral behavior.

The developing of prosody in infants: a longitudinal study over the first 16 months of infant life

Background The acquisition and development of prosodic aspects of vocal intonation are of special interest within the larger context of language acquisition. Method The present study explored the developmental trajectories of infant prosodic abilities from 4 to 16 months of life with an intensive time points assessment. Several aspects were considered: an acoustic analysis of infant vocal productions with specific software, the analyses of all the prosodic variables associated with the fundamental frequency (F0 mean, F0 range, and F0 final contours), the individual variability and the complexity of the vocal productions of the infants. Results The multi-level analysis evidenced specific prosodic developmental trajectories that differ for the different kind of vocal productions since the first months of life. Conclusions The findings suggest that in the second half of the first year of life infants show an intonational repertoire that may help manage interactions with their caregiver and that individual variability has to be taken in consideration when assessing infants’ prosody.

The impact of internet usage preferences on labor income: Evidence from China.

The widespread application and iterative updating of computers and Internet communication technologies have not only increased productivity and enhanced intra- and inter-enterprise collaboration, but have also led to significant changes in the labor market and residents' labor income. In the digital era, accepting digital technology and possessing a certain degree of digital literacy have become the necessary abilities for people to survive and develop. However, the differences in digital literacy caused by individual differences will inevitably bring about a series of chain reactions. Therefore, it is necessary to study the subtle impact of Internet usage preference on residents' labor income in the context of digital transformation to promote digital equity. This study aims to empirically analyze micro-level survey data to reveal the impact of individual differences in internet usage preferences on their labor income. The findings provide theoretical references for government policy formulation and individual development. A function model was established to analyze the impact of individual internet usage preferences on labor income. Relevant data from the authoritative Chinese General Social Survey (CGSS2017) were selected, and empirical analyses for significance, heterogeneity, and robustness were conducted using the ZINB and CMP models in the Stata statistical software. (1) Higher Internet Usage Frequency (IUF) increases the likelihood of higher income. (2) Engaging in Online Social Networking (OSN) helps in accumulating social capital, leading to higher labor income. Meanwhile, participating in Online Entertainment (OE) relieves work and life stresses, thereby increasing labor income. Proficiency in Accessing Online Information (AOI) is associated with higher labor income, while frequent involvement in Online Business (OB) is correlated with higher personal income. Additionally, the Marginal utility of these internet usage preferences indicate that OB > AOI > OSN > OE. (3) Individual variations in physical, psychological, and social characteristics significantly influence the labor income effects of internet usage preferences. (4) There are substantial differences in the labor income effects of internet usage preferences between urban and rural areas and across different regions. (5) Education attainment has a positive mediating effect on the labour income effect of individual Internet use preferences, and enhancing residents' digital literacy has a positive effect on increasing their labour income and alleviating inequality in digital gains. (6) The popularity of Internet technology is the background that triggers an individual's Internet use, and the acceptance of a particular Internet technology is catalyzed by an individual's perception of the value and difficulty of mastering that technology; an individual's biased learning or proficiency in a particular Internet technology in order to gain higher competitiveness and value in the labour market is an important internal driving force.

The Relationship between Functional Movement Quality and Speed, Agility, and Jump Performance in Elite Female Youth Football Players

The association between movement screening and physical fitness testing in athletes is conflicting, and therefore, this study aimed to examine the relationship between Functional Movement Screen (FMS) performance and physical performance in elite female youth football players. Twenty-two players from the national U16 team of Bosnia and Herzegovina underwent FMS and physical performance tests, including speed, agility, and jump assessments. Jump and speed performance score correlated well with ASLR, while the overall FMS score was not associated with any of the performance variables. These findings suggest that while certain movement patterns may impact athletic performance, the relationship between movement screening and physical performance is delicate. Coaches and practitioners should consider individual variations and sport-specific demands when interpreting FMS results in order to optimize and maximize athlete performance and reduce injury risks.

Green lizards (Squamata, Lacertidae) from ?Pliocene deposits of Węże I in southern Poland, with comments on cranial features for selected lacertids

AbstractI here describe lacertids from the classic Węże I locality in southern Poland (?Pliocene deposits) based on six previously undescribed jaws: an incomplete left maxilla, two dentaries and three mandibles. These jaws collectively provide considerable data on the morphology of the maxilla, dentary, teeth, coronoid, splenial, angular, surangular and prearticular. All six jaws can be unequivocally allocated to Lacertidae and five of those are allocated to European green lizards of the Lacerta viridis group. Currently, La. viridis has regionally extinct or probably extinct status in Poland. The material from Węże I provides evidence that European green lizards had a large geographic distribution in Europe, including Poland during the ?Pliocene. One mandible fragment appears to be slightly different and is allocated to Lacertidae indet. That mandible might point to a higher taxonomic diversity of lacertids in this locality. However, that interpretation needs to be viewed with caution, because based on such limited material, individual and/or ontogenetic variation cannot be ruled out. To reveal the real taxonomic palaeodiversity of lacertids in Węże I, new and more complete cranial material is needed. In addition, this article provides insights into the comparative osteology of skulls and selected cranial elements in lacertids.

Hysterectomy with sentinel lymph node dissection in the setting of preoperative endometrial intraepithelial neoplasia and an endometrial stripe ≥20 mm: a cost-effectiveness analysis

ObjectivesRoutine lymph node assessment in patients with endometrial intraepithelial neoplasia is institution and surgeon-dependent without clear guidelines. We sought to determine if routine sentinel lymph node (SLN) dissection at the...

Cortical and Subjective Measures of Individual Noise Tolerance Predict Hearing Outcomes with Varying Noise Reduction Strength

Noise reduction (NR) algorithms are employed in nearly all commercially available hearing aids to attenuate background noise. However, NR processing also involves undesirable speech distortions, leading to variability in hearing outcomes among individuals with different noise tolerance. Leveraging 30 participants with normal hearing engaged in speech-in-noise tasks, the present study examined whether the cortical measure of neural signal-to-noise ratio (SNR)—the amplitude ratio of auditory evoked responses to target speech onset and noise onset—could predict individual variability in NR outcomes with varying strength, thus serving as a reliable indicator of individual noise tolerance. In addition, we also measured subjective ratings of noise tolerance to see if these measures could capture different perspectives on individual noise tolerance. Results indicated a significant correlation between neural SNR and NR outcomes that intensified with increasing strength of NR processing. While subjective ratings of noise tolerance were not correlated with the neural SNR, noise-tolerance ratings could predict outcomes with stronger NR processing and account for additional variance in the regression model, although the effect was limited. Our findings underscore the importance of accurately assessing an individual’s noise tolerance characteristics in predicting perceptual benefits from various NR processing methods and suggest the advantage of incorporating both cortical and subjective measures in the relevant methodologies.

Heatmap-Based Active Shape Model for Landmark Detection in Lumbar X-ray Images.

Medical staff inspect lumbar X-ray images to diagnose lumbar spine diseases, and the analysis process is currently automated using deep-learning techniques. The detection of landmarks is necessary in the automatic process of localizing the position and identifying the morphological features of the vertebrae. However, detection errors may occur owing to the noise and ambiguity of images, as well as individual variations in the shape of the lumbar vertebrae. This study proposes a method to improve the robustness of landmark detection results. This method assumes that landmarks are detected by a convolutional neural network-based two-step model consisting of Pose-Net and M-Net. The model generates a heatmap response to indicate the probable landmark positions. The proposed method then corrects the landmark positions using the heatmap response and active shape model, which employs statistical information on the landmark distribution. Experiments were conducted using 3600 lumbar X-ray images, and the results showed that the landmark detection error was reduced by the proposed method. The average value of maximum errors decreased by 5.58% after applying the proposed method, which combines the outstanding image analysis capabilities of deep learning with statistical shape constraints on landmark distribution. The proposed method could also be easily integrated with other techniques to increase the robustness of landmark detection results such as CoordConv layers and non-directional part affinity field. This resulted in a further enhancement in the landmark detection performance. These advantages can improve the reliability of automatic systems used to inspect lumbar X-ray images. This will benefit both patients and medical staff by reducing medical expenses and increasing diagnostic efficiency.

Meditation training and enduring changes in psychological functioning: a 7-year longitudinal study

ABSTRACT Considerable research has now documented the beneficial effects of mindfulness-based practices on psychological functioning. Less is known about the long-term durability of such changes following formal meditation training. In a sample of adults (N = 67, 52% female, ages 22–70 years), we examined changes in 16 measures of psychological adaptive functioning across a 3-month residential meditation intervention and across a subsequent 7-year period. We observed general training-related improvements followed by multi-year returns toward pre-training levels. However, beneficial changes in two personality attributes (agreeableness and neuroticism) were of moderate effect size (d = 0.51 and d = 0.45, respectively) and were retained across the 7-year follow-up. We further found that individual variation in changes was represented by three latent attributes: (Changes related to) Mindful Well-being, Resilient Extraversion, and Self-Compassionate Openness. These results suggest that intensive meditation training is associated with improved adaptive functioning and enduring changes in aspects of personality.

Do the best of all together: Hierarchical spatial-frequency fusion transformers for animal re-identification

Animal re-identification is fundamental in the ecology and ethology community for understanding the Earth’s ecosystems. Due to the uncertainty of photographing animals in the wild, such as the position and angle of capture and the variations in animal individuals as well as in their poses and habitats, building image-based visual models for re-identifying animal individuals is a challenging task. We propose a novel framework, hierarchical spatial-frequency fusion transformers, to address animal re-identification. We first use spatial and frequency representation learning to capture effective deep features and then employ hierarchical transformer-based representation learning to consolidate low-level detailed information into high-level semantic information from a global perspective. Through this process, we construct a deeply supervised nonlinear aggregation method to enhance finer multi-scale, multi-level and cross-domain features. Our method illustrates the case of “do the best of all together”, meaning that only when both the frequency and spatial domains are combined can we achieve the best performance. The experimental results demonstrate that our approach achieves significantly higher performance than other state-of-the-art methods.

Integrated line-field optical coherence tomography and scheimpflug imaging for corneal imaging

Previously we demonstrated a combined scanning-point optical coherence tomography (OCT) and Scheimpflug Imaging (SI) system, to provide cross-section images of the corneal layers and the whole anterior segment of the eye simultaneously. However, to fully realise the benefits of this dual imaging modality concept towards clinical practice, it is required that the OCT part of the system can achieve ultra-high axial resolution (<3 µm in air) and faster imaging speeds, without using prohibitively expensive components. To achieve this, a new imaging device integrating line-field OCT and SI, using a supercontinuum light source, is demonstrated. This line-field configuration enables both OCT and SI B-scan to be captured using the same light illumination in a single shot, which is the most significant improvement over single point scanning. This achieves an OCT axial resolution down to 2.1 µm in air (1.6 µm in corneal tissue) and an imaging speed up to 213 kA-Scans/s. Since the OCT and SI capture the identical corneal position and serve as cross-validation, this technique offers a great method for accurately determining the individual corneal thickness and refractive index, thereby minimizing individual variations, which can help determine the extent of cutting or correction needed in vision correction. Moreover, the precise measurement of corneal thickness provided by this technique allows for a better understanding of the biomechanical properties of the cornea. We demonstrate the efficacy of the proposed system by evaluating porcine and bovine eyes ex-vivo for determining the corneal refractive index and thickness.

A dependency distance approach to the syntactic complexity variation in the connected speech of Alzheimer’s disease

Previous research on the syntax complexity variation in individuals with Alzheimer’s disease primarily focuses on isolated language features like sentence length or syntactic structure, with limited exploration of their connection to memory and cognitive deficits. This study investigated the syntactic complexity variation in AD by associating working memory load with fine-grained syntactic features adopting a dependency distance approach. The findings include: (1) AD patients had shorter mean dependency distances (MDD) and more head-final dependencies compared to the HC group; (2) The patients still produced their speech under the DDM tendency but exhibited a stronger preference for simple syntactic structures; (3) Sentences produced by AD patients were statistically shorter than the HC group, and the patients exhibited greater difficulty handling syntactic structures as sentence length increases; (4) The patients could employ different syntactic structures but perform worse in extending them, particularly in nominal groups and hypotactic constructions; (5) The patients showed stronger reliance on sentence-initial adjuncts and inverted constructions. These findings suggest that syntactic impairments in AD exhibit a potential hierarchical decline along the continuum of syntactic complexity, with working memory deficits being a critical factor.