bluuebunny/crossref_metadata_2025_split huggingface dataset:
Differences between mates at the TLR1Lb locus are associated with lower reproductive success in a long-lived seabird
Authors: Gousy-Leblanc Marianne , Merkling Thomas , Colston-Nepali Lila , Lachance Linklater Emma , Elliott Kyle H. , Friesen Vicki L. 
Published: December 2024

AbstractGenetic diversity can influence fitness components such as survival and reproductive success. Yet the association between genetic diversity and fitness based on neutral loci is sometime very weak and inconsistent, with relationships varying among taxa due to confounding effects of population demography and life history. Fitness-diversity relationships are likely to be stronger and more consistent for genes known to influence phenotypic traits, such as immunity-related genes, and may also depend on the genetic differences between breeding partners. We recorded breeding success of individuals and breeding pairs over 20 years to evaluate the relationships between reproductive success and both neutral genetic variation (using 7,830 single nucleotide polymorphisms) and functional variation (four toll-like receptor [TLRs] loci) with reproductive success in thick-billed murres (Uria lomvia). Individual genetic diversity (both neutral and functional) was unrelated to reproductive success, but surprisingly, successful multi-year reproductive success decreased with the genetic difference between breeding partners at TLR1Lb. This result may be due to an advantage of specific alleles at TLR1Lb. This study is one of few addressing both individual genetic variation and genetic similarity between mates at both neutral and functional variation in a long-lived bird.
A deep transfer learning based convolution neural network framework for air temperature classification using human clothing images
Authors: Ahmed Maqsood , Zhang Xiang , Shen Yonglin , Ali Nafees , Flah Aymen , Kanan Mohammad , Alsharef Mohammad , Ghoneim Sherif S. M. 
Published: December 2024

AbstractWeather recognition is crucial due to its significant impact on various aspects of daily life, such as weather prediction, environmental monitoring, tourism, and energy production. Several studies have already conducted research on image-based weather recognition. However, previous studies have addressed few types of weather phenomena recognition from images with insufficient accuracy. In this paper, we propose a transfer learning CNN framework for classifying air temperature levels from human clothing images. The framework incorporates various deep transfer learning approaches, including DeepLabV3 Plus for semantic segmentation and others for classification such as BigTransfer (BiT), Vision Transformer (ViT), ResNet101, VGG16, VGG19, and DenseNet121. Meanwhile, we have collected a dataset called the Human Clothing Image Dataset (HCID), consisting of 10,000 images with two categories (High and Low air temperature). All the models were evaluated using various classification metrics, such as the confusion matrix, loss, precision, F1-score, recall, accuracy, and AUC-ROC. Additionally, we applied Gradient-weighted Class Activation Mapping (Grad-CAM) to emphasize significant features and regions identified by models during the classification process. The results show that DenseNet121 outperformed other models with an accuracy of 98.13%. Promising experimental results highlight the potential benefits of the proposed framework for detecting air temperature levels, aiding in weather prediction and environmental monitoring.
Assessment of resilient modulus of soil using hybrid extreme gradient boosting models
Authors: Duan Xiangfeng 
Published: December 2024

AbstractAccurate estimation of the soil resilient modulus (MR) is essential for designing and monitoring pavements. However, experimental methods tend to be time-consuming and costly; regression equations and constitutive models usually have limited applications, while the predictive accuracy of some machine learning studies still has room for improvement. To forecast MR efficiently and accurately, a new model named black-winged kite algorithm-extreme gradient boosting (BKA-XGBOOST) is proposed. In BKA-XGBOOST, XGBOOST captures the many-to-one nonlinear relationship between geotechnical factors and MR, while BKA provides the optimal hyperparameters for XGBOOST. By combining them, XGBOOST has stable and accurate predictive capabilities for different combinations of soil data. Comparisons with nine models show that the proposed model outperforms other models in terms of MR prediction accuracy, with a determination coefficient (R2) of 0.995 and a mean absolute error (MAE) of 0.975 MPa. In addition, an efficient MR prediction software is developed based on the model to improve its practicality and interactivity, which is promising for assisting engineers in evaluating pavement properties.
The critical role of emotional communication for motivated reasoning
Authors: Wolf Ingo , Schröder Tobias 
Published: December 2024

AbstractPersuasive appeals frequently prove ineffective or produce unintended outcomes, due to the presence of motivated reasoning. Using the example of electric cars adoption, this research delves into the impact of emotional content, message valence, and the coherence of pre-existing attitudes on biased information evaluation. By conducting a factorial survey (N = 480) and incorporating a computational model of attitude formation, we aim to gain a deeper insight into the cognitive-affective mechanisms driving motivated reasoning. Our experimental findings reveal that motivated reasoning is most pronounced when persuasive appeals employ a combination of emotional and rational elements within a negatively valenced argument. Furthermore, our computational model, which estimates belief and affect adjustments underlying attitude changes, elucidates how message framing influences cognitive-affective processes through emotional coherence. The results provide support for a negative correlation between shifts in coherence in response to new information and the propensity for motivated reasoning. The research contributes to computational models of opinion dynamics and social influence, offering a psychologically realistic framework for exploring the impact of individual reasoning on population-level dynamics, particularly in policy contexts, where it can enhance communication and informed policy discussions.
Surface electromyography evaluation for decoding hand motor intent in children with congenital upper limb deficiency
Authors: Battraw Marcus A. , Fitzgerald Justin , Winslow Eden J. , James Michelle A. , Bagley Anita M. , Joiner Wilsaan M. , Schofield Jonathon S. 
Published: December 2024

AbstractChildren born with congenital upper limb absence exhibit consistent and distinguishable levels of biological control over their affected muscles, assessed through surface electromyography (sEMG). This represents a significant advancement in determining how these children might utilize sEMG-controlled dexterous prostheses. Despite this potential, the efficacy of employing conventional sEMG classification techniques for children born with upper limb absence is uncertain, as these techniques have been optimized for adults with acquired amputations. Tuning sEMG classification algorithms for this population is crucial for facilitating the successful translation of dexterous prostheses. To support this effort, we collected sEMG data from a cohort of N = 9 children with unilateral congenital below-elbow deficiency as they attempted 11 hand movements, including rest. Five classification algorithms were used to decode motor intent, tuned with features from the time, frequency, and time–frequency domains. We derived the congenital feature set (CFS) from the participant-specific tuned feature sets, which exhibited generalizability across our cohort. The CFS offline classification accuracy across participants was 73.8% ± 13.8% for the 11 hand movements and increased to 96.5% ± 6.6% when focusing on a reduced set of five movements. These results highlight the potential efficacy of individuals born with upper limb absence to control dexterous prostheses through sEMG interfaces.
Initial experience of a novel surgical assist robot “Saroa” featuring tactile feedback and a roll-clutch system in radical prostatectomy
Authors: Iwatani Kosuke , Urabe Fumihiko , Saito Shun , Kawano Shota , Yamasaki Tomoya , Kimura Shoji , Otsuki Hideo , Fujio Kei , Kimura Takahiro , Miki Jun 
Published: December 2024

AbstractTo evaluate the safety and efficacy of the Saroa Surgical Robot System in robot-assisted laparoscopic radical prostatectomy (RARP). We enrolled 60 patients who underwent RARP using either the Saroa (n = 9) or da Vinci Xi (n = 51) systems at Jikei University Kashiwa Hospital from January 2022 to March 2024. We compared preoperative characteristics, perioperative outcomes, complications, and postoperative urinary continence at three months between the two groups. No significant differences were found in preoperative characteristics. The Saroa group had a longer median operative time compared to the da Vinci group. Postoperative urinary continence rates were slightly lower in the Saroa group (77.8 % vs. 84.6%), though not statistically significant. When the tactile feedback function was activated, the organs were grasped with less force compared to when it was off. This study is the first to assess the Saroa system’s effectiveness and safety in RARP. While the system shows promise, especially with tactile feedback that aids in delicate tissue handling, further investigation is needed to evaluate long-term oncological and functional outcomes.
Master S-N curve method to fatigue damage assessment of the high-ply cutter body
Authors: Liu Wenfei , Chen Bo , Zhou Chao , Li Wei , Yu Hengji 
Published: December 2024

AbstractAt present, the cutting fabric thickness of the high-ply cutter can reach 100 mm, which requires high vacuum pressure resistance performance, and the fatigue reliability of the cutter body is an important indicator of cutting performance. In this paper, the cutter body was analyzed by finite element simulation, the equivalent structural stress and Von Mises stress at key positions were calculated separately. Then, the master S-N curve method and traditional method were used to evaluate fatigue damages at key locations of the cutter body, which are compared and analyzed with the fatigue damage of measured dynamic stress. The results show that the maximum fatigue damage calculated by the master S-N curve method is 0.223, which is the safest. it verifies the effectiveness and reliability of the master S-N curve method in evaluating the fatigue damage of the cutter body. Meanwhile, the fatigue damage of the three measuring points calculated by the three methods is all below 0.5, and it indicates that the design of the cutter body is reasonable. In addition, the master S-N curve method and equivalent structural stress method were first applied to the fatigue damage assessment of high-ply cutter body, which provides an efficient and high-precision approach for the anti-fatigue design of cutter body.
Detection of fungal sequences in human brain: rDNA locus amplification and deep sequencing
Authors: Leitao Rodrigo , Wan Iam Ut , Chown Harry , Williams Thomas J. , Fisher Matthew C. , Rhodes Johanna 
Published: December 2024

AbstractThe aetiology of Alzheimer’s disease (AD) and Parkinson’s disease (PD) are unknown and tend to manifest at a late stage in life; even though these neurodegenerative diseases are caused by different affected proteins, they are both characterized by neuroinflammation. Links between bacterial and viral infection and AD/PD has been suggested in several studies, however, few have attempted to establish a link between fungal infection and AD/PD. In this study we adopted a nanopore-based sequencing approach to characterise the presence or absence of fungal genera in both human brain tissue and cerebrospinal fluid (CSF). We observed the presence of small fungal burden DNA in two AD brains and a control case (extensive amyloid angiopathy). This approach would be well-placed to investigate potential links between microbial infection and neurodegenerative disease.
Psychometric properties of the English and Hindi versions of the Brief Inventory of Thriving for use among Indian adolescents
Authors: Syed Usama Ghayas , Dixit Shikha , Kern Margaret L. 
Published: December 2024

AbstractThe Brief Inventory of Thriving (BIT) provides a holistic measure of well-being, but has only been validated for adults, and does not have a Hindi version. The present study investigated the unidimensional structure, internal consistency, convergent/discriminant, and criterion validity of both the original English version of the BIT (BIT-E) and its Hindi-translated version (BIT-H) among adolescents in India. Further, we tested measurement invariance across these two language versions, gender, and academic disciplines. A total of 534 adolescents were recruited across two samples (N1 = 224 and N2 = 310) from five schools using convenience sampling. Both versions demonstrated excellent psychometric properties, with unidimensional structure, good internal consistency, convergent/discriminant, and criterion validity with a number of psycho-educational correlates. Partial scalar invariance was achieved across language versions and gender, while strict invariance was established across academic disciplines. The BIT, in both English and Hindi, appears to be an excellent measure of well-being for adolescents. Limitations, directions for future research, and recommendations for using the BIT-E and BIT-H among adolescents in research and applied settings are discussed.
A meta-analytic evaluation of the reliability of work-family and family-work conflict scales
Authors: Ugwu Lawrence Ejike , Idemudia Erhabor Sunday 
Published: December 2024

AbstractIn occupational psychology, measuring the interplay between work and family roles is crucial. The Work-family conflict (WFC) and Family-Work Conflict (FWC) scales are indispensable tools in this endeavour. However, their reliability across diverse geographical locations and work settings, particularly during the global pandemic, requires thorough examination. This meta-analysis evaluates the reliability generalisation of WFC and FWC scales across different studies. Registered with PROSPERO (ID: CRD42024509030), we systematically searched four major databases: EBSCOhost, Web of Science, Scopus, and ScienceDirect, yielding 506 potential studies. After deduplication and screening, 44 studies published between 2000 and 2024 were selected. These studies analysed reliability coefficients (Cronbach’s alpha) and the impact of geographical location, work setting, and events like the COVID-19 pandemic on scale reliability. The analysis showed high reliability for both scales, with a pooled Cronbach’s alpha of 0.91 (95% CI [0.87, 0.95]) indicating strong internal consistency. Test-retest reliability was also high, with a pooled estimate of 0.89 (95% CI: [0.84, 0.93]). Subgroup analyses revealed minimal variability in reliability across sectors, regions, and the pandemic period, with no heterogeneity (I2 = 0.0%), suggesting the scales’ broad applicability. The WFC and FWC scales demonstrate high reliability across various global contexts, underscoring their value in occupational psychology. Their adaptability to different cultural and work scenarios, including during the COVID-19 pandemic, highlights their potential for widespread use. The uniform reliability across studies emphasises their effectiveness in capturing work-family dynamics, supporting their generalizability and relevance for cultural adaptation.
Characterisation of the optical response to seismic waves of submarine telecommunications cables with distributed and integrated fibre-optic sensing
Authors: Fairweather David M. , Tamussino Max , Masoudi Ali , Feng Zitong , Barham Richard , Parkin Neil , Cornelius David , Brambilla Gilberto , Curtis Andrew , Marra Giuseppe 
Published: December 2024

AbstractWe present the first controlled-environment measurements of the optical path-length change response of telecommunication submarine cables to active seismic and acoustic waves. We perform the comparison among integrated (optical interferometry) and distributed (distributed acoustic sensing, DAS) fibre measurements and ground truth data acquired by 58 geophones, 20 three-axis seismometers and 7 microphones. The comparison between different seismic acquisition methods is an essential step towards full validation and calibration of the data acquired using novel cable-based sensing techniques. Our experimental data demonstrates broadside sensitivity of integrated optical phase measurements, in contrast to predictions from the prevailing model for this type of sensing. We also present evidence of a fast-wave arrival, which we attribute to coupled energy propagating through the metal armour of the submarine cables at a considerably faster velocity than the subsurface and acoustic waves measured during our tests. The latter process can greatly affect the detected optical signal. The experimental setup allowed us to also observe how sensing measurements on separate optical fibres within the same cable can lead to significantly different detected waveforms. Constraining the effects of the fibre architecture on recorded signals can identify factors that contribute to the non-linear response of such a sensing system.
Diagnoses of postpartum urinary retention using next-generation non-piezo ultrasound technology: assessing the accuracy and benefits
Authors: Plöger Ruben , Behning Charlotte , Walter Adeline , Gembruch Ulrich , Strizek Brigitte , Recker Florian 
Published: December 2024

AbstractPostpartum urinary retention has a wide range of publicized incidences, likely caused by frequent misdiagnosis of this puerperal complication. Especially covert postpartum urinary retention has a high number of missed diagnoses due to the lack of symptoms and the time-extensive diagnostics via ultrasound, leading to no treatment and no appropriate follow-up. To simplify the diagnosis and establish a screening tool we analyzed the application of portable handheld-ultrasound devices (PUD) as used in Point-of-care diagnostics in comparison to established standard ultrasound devices (SUD). This prospective study aimed to evaluate the reliability of non-piezo, chip-based PUD in comparison to the measurement withSUD, containing a piezo transducer, as golden standard for the ultrasound diagnosis of postpartum urinary retention. Randomly, 100 participants between the first and seventh day after delivery in an obstetric ward underwent ultrasound examinations using a EPIQ 5 W (Philips) as SUD and a Butterfly iQ (Butterfly Network) as PUD to compare the accuracy in bladder size after micturition and the estimated post-void residual volume. Intraclass correlation coefficients, Bland-Altman plots, and Pearson correlation coefficients were used for analyzing the reliability and agreement between the measurements of these devices and were calculated for subgroups as body mass index, mode of delivery and timepoint of delivery. The results show a near-perfect agreement (0.994) and correlation (r = 0.982) for estimated post-void residual volume and for most measurements between the two types of ultrasound devices. The agreement rate for the diagnosis of covert postpartum urinary retention is 100%. Subgroup analyses lack a significant difference reflected by agreement and correlation rates. These findings affirm the high reliability of PUD for the diagnosis of postpartum urinary retention and supports their integration into daily clinical practice, thereby simplifying regular controls of the bladder by physicians during daily rounds on the ward. This technology may allow a higher diagnosis rate so that patient care can be optimized and the long-term impact on continence and quality of life can be studied and analysed.
Surface reconstruction limited magnetism of the nodal loop semimetal Ca$$_3$$P$$_2$$
Authors: Alassaf Assem , Koltai János , García-Fuente Amador , Oroszlány László 
Published: December 2024

AbstractNodal loop semimetals are topological materials with drumhead surface states characterized by reduced kinetic energy. If the Fermi energy of such a system is near these nondispersive states interaction among charge carriers substantially impacts their electronic structure. The emergence of magnetism in these surface states is one of the possible consequences. Ca$$_3$$P$$_2$$ an already synthesized material possesses a remarkably large nodal loop which is situated exactly at the Fermi level of the bulk system. In the present work, we investigate how surface magnetism is impacted by surface reconstruction and lattice termination in finite slabs in this material. We show that a slight deviation from the stoichiometric occupation of Ca sites results in the stabilization of magnetic patterns.
Microscopic changes in the multifidus muscle in people with low back pain associated with lumbar disc herniation
Authors: Purushotham Shilpa , Hodson Nathan , Greig Carolyn , Gardner Adrian , Falla Deborah 
Published: December 2024

AbstractLumbar disc herniation (LDH) is a common degenerative condition causing low back pain (LBP) due to nerve compression. Previous studies show conflicting findings regarding the multifidus (MF) muscle’s microscopic changes in LDH patients. So, this study aimed to compare the affected MF to the adjacent MF on the ipsilateral and contralateral sides in LDH patients and examined correlations with clinical features of LBP. Four muscle biopsies were collected from each of 30 surgical participants. Immunohistochemistry was performed on tissue sections and imaged with an epifluorescence microscope. Data was analysed using a two-way ANOVA for muscle fibre cross-sectional area, perimeter, diameter, and composition, while pathological fibres were analysed using a one-way ANOVA. Pearson’s correlation was employed to examine MF microscopy associations with clinical features. Results revealed no significant differences between the affected MF and MF from other sites, though significantly more pathological fibres were present in the affected MF (p < 0.05). A weak but significant negative correlation was found between type I fibres and LBP clinical features, though no such correlations were observed for type IIA fibres. In conclusion, LDH primarily impacts the pathological status of the MF rather than fibre phenotype or size, and severity of clinical features is associated with the size of type I fibres.
miRNA changes associated with differentiation of human embryonic stem cells into human retinal ganglion cells
Authors: Esmaeili Maryam , Smith Daniel A. , Mead Ben 
Published: December 2024

Abstract
miRNA, short non-coding RNA, are rapidly emerging as important regulators in cell homeostasis, as well as potential players in cellular degeneration. The latter has led to interest in them as both biomarkers and as potential therapeutics. Retinal ganglion cells (RGC), whose axons connect the eye to the brain, are central nervous system cells of great interest, yet their study is largely restricted to animals due to the difficulty in obtaining healthy human RGC. Using a CRISPR/Cas9-based reporter embryonic stem cell line, human RGC were generated and their miRNA profile characterized using NanoString miRNA assays. We identified a variety of retinal specific miRNA upregulated in ESC-derived RGC, with half of the most abundant miRNA also detectable in purified rat RGC. Several miRNA were however identified to be unique to RGC from human. The findings show which miRNA are abundant in RGC and the limited congruence with animal derived RGC. These data could be used to understand miRNA’s role in RGC function, as well as potential biomarkers or therapies in retinal diseases involving RGC degeneration.