bluuebunny/crossref_metadata_2025_split huggingface dataset:
Sex classification of 3D skull images using deep neural networks
Authors: Noel Lake , Fat Shelby Chun , Causey Jason L. , Dong Wei , Stubblefield Jonathan , Szymanski Kathryn , Chang Jui-Hsuan , Wang Paul Zhiping , Moore Jason H. , Ray Edward , Huang Xiuzhen 
Published: June 2024

AbstractDetermining the fundamental characteristics that define a face as "feminine" or "masculine" has long fascinated anatomists and plastic surgeons, particularly those involved in aesthetic and gender-affirming surgery. Previous studies in this area have relied on manual measurements, comparative anatomy, and heuristic landmark-based feature extraction. In this study, we collected retrospectively at Cedars Sinai Medical Center (CSMC) a dataset of 98 skull samples, which is the first dataset of this kind of 3D medical imaging. We then evaluated the accuracy of multiple deep learning neural network architectures on sex classification with this dataset. Specifically, we evaluated methods representing three different 3D data modeling approaches: Resnet3D, PointNet++, and MeshNet. Despite the limited number of imaging samples, our testing results show that all three approaches achieve AUC scores above 0.9 after convergence. PointNet++ exhibits the highest accuracy, while MeshNet has the lowest. Our findings suggest that accuracy is not solely dependent on the sparsity of data representation but also on the architecture design, with MeshNet's lower accuracy likely due to the lack of a hierarchical structure for progressive data abstraction. Furthermore, we studied a problem related to sex determination, which is the analysis of the various morphological features that affect sex classification. We proposed and developed a new method based on morphological gradients to visualize features that influence model decision making. The method based on morphological gradients is an alternative to the standard saliency map, and the new method provides better visualization of feature importance. Our study is the first to develop and evaluate deep learning models for analyzing 3D facial skull images to identify imaging feature differences between individuals assigned male or female at birth. These findings may be useful for planning and evaluating craniofacial surgery, particularly gender-affirming procedures, such as facial feminization surgery.
Improved predictions of total kidney volume growth rate in ADPKD using two-parameter least squares fitting
Authors: Hu Zhongxiu , Sharbatdaran Arman , He Xinzi , Zhu Chenglin , Blumenfeld Jon D. , Rennert Hanna , Zhang Zhengmao , Ramnauth Andrew , Shimonov Daniil , Chevalier James M. , Prince Martin R. 
Published: June 2024

AbstractMayo Imaging Classification (MIC) for predicting future kidney growth in autosomal dominant polycystic kidney disease (ADPKD) patients is calculated from a single MRI/CT scan assuming exponential kidney volume growth and height-adjusted total kidney volume at birth to be 150 mL/m. However, when multiple scans are available, how this information should be combined to improve prediction accuracy is unclear. Herein, we studied ADPKD subjects ($$n = 36$$

n
=
36

) with 8+ years imaging follow-up (mean = 11 years) to establish ground truth kidney growth trajectory. MIC annual kidney growth rate predictions were compared to ground truth as well as 1- and 2-parameter least squares fitting. The annualized mean absolute error in MIC for predicting total kidney volume growth rate was $$2.1\% \pm 2\%$$

2.1
%
±
2
%

compared to $$1.1\% \pm 1\%$$

1.1
%
±
1
%

($$p = 0.002$$

p
=
0.002

) for a 2-parameter fit to the same exponential growth curve used for MIC when 4 measurements were available or $$1.4\% \pm 1\%$$

1.4
%
±
1
%

($$p = 0.01$$

p
=
0.01

) with 3 measurements averaging together with MIC. On univariate analysis, male sex ($$p = 0.05$$

p
=
0.05

) and PKD2 mutation ($$p = 0.04$$

p
=
0.04

) were associated with poorer MIC performance. In ADPKD patients with 3 or more CT/MRI scans, 2-parameter least squares fitting predicted kidney volume growth rate better than MIC, especially in males and with PKD2 mutations where MIC was less accurate.
A novel algorithm to differentiate between primary lung tumors and distant liver metastasis in lung cancers using an exosome based multi gene biomarker panel
Authors: Shah Kanisha A. , Rawal Rakesh M. 
Published: June 2024

AbstractThe lack of non-invasive methods for detection of early metastasis is a crucial reason for the poor prognosis of lung cancer (LC) liver metastasis (LM) patients. In this study, the goal was to identify circulating biomarkers based on a biomarker model for the early diagnosis and monitoring of patients with LCLM. An 8-gene panel identified in our previous study was validated in CTC, cfRNA and exosomes isolated from primary lung cancer with & without metastasis. Further multivariate analysis including PCA & ROC was performed to determine the sensitivity and specificity of the biomarker panel. Model validation cohort (n = 79) was used to verify the stability of the constructed predictive model. Further, clinic-pathological factors, survival analysis and immune infiltration correlations were also performed. In comparison to our previous tissue data, exosomes demonstrated a good discriminative value with an AUC of 0.7247, specificity (72.48%) and sensitivity (96.87%) for the 8-gene panel. Further individual gene patterns led us to a 5- gene panel that showed an AUC of 0.9488 (p =  < 0.001) and 0.9924 (p =  < 0.001) respectively for tissue and exosomes. Additionally, on validating the model in a larger cohort a risk score was obtained (RS > 0.2) for prediction of liver metastasis with an accuracy of 95%. Survival analysis and immune filtration markers suggested that four exosomal markers were independently associated with poor overall survival. We report a novel blood-based exosomal biomarker panel for early diagnosis, monitoring of therapeutic response, and prognostic evaluation of patients with LCLM.
Study of the mechanical properties and propagation mechanisms of non-coplanar and discontinuous joints via numerical simulation experiments
Authors: Liu Yuanming , Ya Lankai , Wang Wei , Chen Qingzhi , Wang Zhongxing , Teng Zhaolei , Cheng Jiajun 
Published: June 2024

AbstractNon-coplanar and discontinuously jointed rock masses are more complex than coplanar and discontinuously jointed rock masses. The mechanical properties and propagation mechanisms of non-coplanar and discontinuous joints were studied via direct shear tests with microscopic numerical simulation experiments. The numerical simulation tests were performed under different normal stresses, joint inclination angles, and shear rates. The numerical experimental results show that the microscale failure of non-coplanar and discontinuously jointed rock masses is mainly caused by tensile cracks. Additionally, when the peak shear stress is reached, the growth rate of cracks increases rapidly, and the number of cracks increases with increasing normal stress. The shear strength of non-coplanar and discontinuously jointed rock masses increases with increasing normal stress. Under the same normal stress, the variation curves of the shear strength of non-coplanar and discontinuously jointed rock masses with respect to the dip angle exhibit an “S”-shaped nonlinear pattern. Rock masses with joint inclination angles of approximately 15° and 65° have minimum and maximum shear strengths, respectively. The joint dip angle has a significant impact on the final failure mode of rock bridges in the rock mass. As the joint dip angle increases, the final failure modes of rock bridges change from “end-to-end” connection to a combination of “head-to-head” and “tail-to-tail” connections. The shear rate has a certain impact on the peak shear stress, but the impact is not significant. The spatial distribution of the tensile force chains changes as shearing progresses, and stress concentration occurs at the tips of the original joints, which is the reason for the development of long tensile cracks in the deeper parts.
Ratiometric fluorescence nanoscopy and lifetime imaging of novel Nile Red analogs for analysis of membrane packing in living cells
Authors: Lauritsen Line , Szomek Maria , Hornum Mick , Reinholdt Peter , Kongsted Jacob , Nielsen Poul , Brewer Jonathan R. , Wüstner Daniel 
Published: June 2024

AbstractSubcellular membranes have complex lipid and protein compositions, which give rise to organelle-specific membrane packing, fluidity, and permeability. Due to its exquisite solvent sensitivity, the lipophilic fluorescence dye Nile Red has been used extensively to study membrane packing and polarity. Further improvement of Nile Red can be achieved by introducing electron-donating or withdrawing functional groups. Here, we compare the potential of derivatives of Nile Red with such functional substitutions for super-resolution fluorescence microscopy of lipid packing in model membranes and living cells. All studied Nile Red derivatives exhibit cholesterol-dependent fluorescence changes in model membranes, as shown by spectrally resolved stimulated emission depletion (STED) microscopy. STED imaging of Nile Red probes in cells reveals lower membrane packing in fibroblasts from healthy subjects compared to those from patients suffering from Niemann Pick type C1 (NPC1) disease, a lysosomal storage disorder with accumulation of cholesterol and sphingolipids in late endosomes and lysosomes. We also find small but consistent changes in the fluorescence lifetime of the Nile Red derivatives in NPC1 cells, suggesting altered hydrogen-bonding capacity in their membranes. All Nile Red derivatives are essentially non-fluorescent in water but increase their brightness in membranes, allowing for their use in MINFLUX single molecule tracking experiments. Our study uncovers the potential of Nile Red probes with functional substitutions for nanoscopic membrane imaging.
Rhinoceros horn mineral and metal concentrations vary by sample location, depth, and color
Authors: Roth Terri L. , Rebolloso Sarah L. , Donelan Elizabeth M. , Rispoli Louisa A. , Buchweitz John P. 
Published: June 2024

AbstractPoaching is again driving rhinos to the brink of extinction due to the demand for rhino horn products consumed for cultural, medicinal, and social purposes. Paradoxically, the same horn for which rhinos are killed may contain valuable clues about the species’ health. Analyses of horn composition could reveal such useful bioindicators while elucidating what people actually ingest when they consume horn derivatives. Our goals were to quantify minerals (including metals) in rhino horn and investigate sampling factors potentially impacting results. Horns (n = 22) obtained during necropsies of white (n = 3) and black (n = 13) zoo rhinos were sampled in several locations yielding 182 specimens for analysis. Initial data exposed environmental (soil) contamination in the horn’s exterior layer, but also confirmed that deep (≥ 1 cm), contaminant-free samples contained measurable concentrations of numerous minerals (n = 18). Of the factors examined in deep samples, color-associated mineral differences were the most profound with dark samples higher in zinc, copper, lead, and barium (p < 0.05). Our data demonstrate that rhino horns contain both essential and potentially toxic minerals that could be relevant to rhino health status, but low concentrations make their human health benefits or risks unlikely following consumption.
Rapid, equipment-free extraction of DNA from skin biopsies for point-of-care diagnostics
Authors: Manning Jason Cade , Boza Juan Manuel , Cesarman Ethel , Erickson David 
Published: June 2024

AbstractKaposi’s sarcoma (KS) is a cancer affecting skin and internal organs for which the Kaposi’s sarcoma associated herpesvirus (KSHV) is a necessary cause. Previous work has pursued KS diagnosis by quantifying KSHV DNA in skin biopsies using a point-of-care (POC) device which performs quantitative loop-mediated isothermal amplification (LAMP). These previous studies revealed that extracting DNA from patient biopsies was the rate limiting step in an otherwise rapid process. In this study, a simplified, POC-compatible alkaline DNA extraction, ColdSHOT, was optimized for 0.75 mm human skin punch biopsies. The optimized ColdSHOT extraction consistently produced 40,000+ copies of DNA per 5 µl reaction from 3 mg samples—a yield comparable to standard spin column extractions—within 1 h without significant equipment. The DNA yield was estimated sufficient for KSHV detection from KS-positive patient biopsies, and the LAMP assay was not affected by non-target tissue in the unpurified samples. Furthermore, the yields achieved via ColdSHOT were robust to sample storage in phosphate-buffered saline (PBS) or Tris-EDTA (TE) buffer prior to DNA extraction, and the DNA sample was stable after extraction. The results presented in this study indicate that the ColdSHOT DNA extraction could be implemented to simplify and accelerate the LAMP-based diagnosis of Kaposi’s sarcoma using submillimeter biopsy samples.
Environmental exposures to organophosphorus flame retardants in early pregnancy and risks of gestational diabetes mellitus: a nested case–control study
Authors: Lang Qi , Sun Jiali , Yu Xiangyuan , Wei Shudan , Wei Jinyan , Zhang Min , Zhao Chaochao , Zhang Jun , Zeng Dingyuan , Huang Bo 
Published: June 2024

AbstractOPFRs are emerging environmental pollutants with reproductive and endocrine toxicity. This study aimed to examine the association between environmental exposure to OPFRs during early pregnancy and GDM. This nested case–control study was based on a birth cohort that was constructed at a maternal and child health hospital, including 74 cases of GDM among 512 pregnant women. The OPFRs, including TBP, TBEP, TCEP, TDCPP, TMCP, TOCP, and TPHP during 10–14 weeks of pregnancy were determined using GC–MS. The association between the OPFRs and GDM was assessed using WQS and BKMR models. The levels of OPFRs were significantly elevated in GDM patients (60) compared with the controls (90). The WQS analysis showed that mixtures of the OPFRs were significantly associated with GDM (OR 1.370, 95% CI 1.036–1.810, P = 0.027), and TBP, TPHP, and TMCP were the major contributors to the mixed exposure effect. In the BKMR model, individual exposure to TBP, TPHP, and TMCP, and the interaction of TMCP with TBP and TPHP were significantly associated with GDM. Environmental exposure to OPFRs is positively associated with GDM. These findings provide evidence for the adverse effects of OPFR exposure on the health of pregnant women.
Off-season survival and life history of beet armyworm, Spodoptera exigua (Hubner) on various host plants
Authors: Rajesh Chowdary L. , Suneel Kumar G. V. , Bharathi S. , Sarada O. , Nagaraju Yalavarthi , Manikyanahalli Chandrashekara Keerthi , Naga Harish Giri 
Published: June 2024

AbstractThe beet armyworm, Spodoptera exigua (Hubner) (Lepidoptera: Noctuidae), has become a significant pest of chickpea in recent years. The polyphagous nature allows it to survive on various hosts during the off-season, creating a great menace to the crop in the following season. To assess the incidence and document the alternate hosts of S. exigua, a rapid roving survey was conducted in 11 chickpea-growing areas of Prakasam district, Andhra Pradesh, India. Additionally, the life history traits of S. exigua were studied on major alternate host plants under laboratory conditions (27 ± 1 °C and 70 ± 2% RH) to understand the survival, life expectancy and potential contribution to future populations. The results show that, among the different crops surveyed, the maximum larval incidence was noticed in maize (1.93 larvae/plant), cowpea (1.73 larvae/plant), and sunflower (1.68 larvae/plant) during the off-season. Life history studies of S. exigua showed that highest larval survival percentage was observed on chickpea (83.6%), while the lowest was on maize (44.5%). The mean developmental time for larvae was longest on maize (27.1 days) and shortest on chickpea (14.9 days). Larvae did not develop beyond the third instar when fed with chilli. The growth index statistics showed chickpea (9.2) was the most suitable host plant, whereas maize (0.9) was the least suitable host. The age-stage-specific survival rate (Sxj) varied across developmental stages, and the survival curves overlapped, indicating different growth rates among individuals. The life expectancy (exj) at age zero was highest on groundnut (37.06 days). The intrinsic rate of increase (r) of S. exigua was lowest on maize (0.10 ± 0.0013) and highest on chickpea (0.22 ± 0.0010). Similarly, the net reproductive rate (R0) was highest on chickpea (846.39 ± 18.22) and lowest on maize (59.50 ± 2.06). The population doubled every 3.08 ± 0.011 days on chickpea compared to 7.22 ± 0.80 days on maize. The study conclusively indicates that chickpea and sunflower, primarily cultivated during the rabi season in India, are the most preferred hosts for S. exigua. In contrast, maize and cotton, mainly grown during the kharif season, are less preferred and merely support the pest's survival. Consequently, S. exigua switches hosts between different crops growing seasons, so effective management of S. exigua during the kharif season can help prevent pest outbreaks during the rabi season.
Residents’ future residential preference and its affecting factors in the rapid urbanization zone of rural China from a family life cycle perspective
Authors: Zhang Mengke , Tong Yan , Ge Yuhang , Guo Jin , Nie Hanlin , Wang Zhijun , Fan Liangxin 
Published: June 2024

AbstractUnderstanding farmers’ future residential preferences and the factors affecting these choices is crucial for tackling the issues related to hollow village management and rural planning. Despite limited research on the role of the family life cycle, this study explores how the family life cycle, characteristics of the household head, livelihood strategies, and resource availability shape farmers’ future residential preferences. Data were collected from 777 households in China’s main grain-producing area. The findings reveal that 52.90% of households prefer to stay in their current rural residences. Other favored options are elderly care facilities (13.90%), living with children in the village (12.36%), and ancestral homes (11.68%). The family life cycle significantly affects these preferences (p < 0.01), with changes in family structure and age leading to different living choices. Specifically, households in the initial (71.29%), burden (70.32%), and stable stages (40.14%) prefer their current rural residences, while those in the maintenance and empty-nest stages opt for living with their children’s residences (22.22% and 16.96%, respectively) or in elderly care facilities (30.00% and 33.93%). Meanwhile, age, health, income, livelihood strategies, and land ownership also markedly influence the choice of residence. Recommendations include educational programs for elderly rural residents, improving older individuals’ adaptability to rural changes, creating more rural employment opportunities, and enhancing medical and infrastructural services for the sustainable rural development.
Exploring the impact of fabrication parameters in organic solar cells with PM6:Y6 using machine learning
Authors: Zhao Xiaojie , Lei Min , Wang Kuo , Peng Xinyu , Li Zhennan , Zhou Haixin , Peng Zhiyan , Chen Ziye , Deng Jiahao , Zhang Kang , Huang Di , Liang Jiaojiao 
Published: June 2024

The preparation parameters of PM6:Y6 non-fullerene organic solar cells (OSCs) have significant influence on the power conversion efficiency (PCE). Herein, machine learning (ML) models are applied for analyzing the quantitative effects of the PCE on PM6:Y6 non-fullerene OSCs from the perspective of fabrication parameters. Random Forest (RF) model has the best evaluation performance and is considered as the best model among the six different algorithms. The Pearson correlation coefficient, coefficient of determination, root mean square error, mean absolute error, and mean absolute percentage error of the test set in the RF model are 0.836, 0.668, 0.695, 0.538, and 0.035, respectively. In addition, the most important preparation parameters for PCE are the effective area of OSCs, type of solvent and solvent additives, spin-coating speed, total concentration, annealing temperature, annealing time from SHAP analysis. The optimized PCE can be obtained in PM6:Y6 non-fullerene OSCs when the effective area is between 4 and 6 mm2, the spin-coating speed is 3000 rpm, and the total concentration is 18 mg ml−1, respectively. The contour map further reflects that the optimal annealing temperature are 80 or 105 °C, and the corresponding annealing time are 5 or 9 min, respectively. Based on the above preparation conditions, we verified through the experimental design that the optimal PCE is 16.91%, and the relative error with the ML prediction is only 1.24%. Our research provides low time and cost guidance on preparation parameter matching for the development of high-performance the PM6:Y6 non-fullerene OSCs.
Doubly warped product manifolds: Investigations through the projective curvature tensor and relativistic applications
Authors: Syied Abdallah Abdelhameed , Chand De Uday , Turki Nasser Bin , Kumar Rajesh 
Published: June 2024

This paper introduces a description of a doubly warped product manifold, taking into account certain conditions related to the projective curvature tensor. We demonstrate that the factor manifolds of a projectively flat (symmetric) doubly warped product manifold possess constant sectional curvature. In the flatness scenario, a doubly warped product manifold reduces to a singly warped product manifold. We establish that the factor manifolds of a doubly warped product manifold with harmonic projective curvature tensor are Einstein manifolds and exhibit harmonic projective curvature tensor. In Sec. VI, we provide evidence that a projectively flat (symmetric) generalized Robertson–Walker space-time is both a perfect fluid and static.
Introduction to solids
Authors: Nitzan Abraham 
Published: June 2024

Abstract
This chapter reviews essential concept of solid-state physics. (1) Lattice periodicity. (2) Lattice vibrations (normal modes of harmonic systems, simple harmonic crystal in one dimension, density of modes, phonons in higher dimensions and the heat capacity of solids). (3) Electronic structure of solids (the free electron theory of metals: energetics and motion, electronic structure of periodic solids: Bloch theory, the one-dimensional tight binding model, the nearly free particle model, intermediate summary: Free electrons versus non-interacting electrons in a periodic potential, dynamical implications of the electronic band structure of solids, semiconductors). (4) The work function. (5). Surface potential and screening (general considerations, the Thomas–Fermi theory of screening by metallic electrons, semiconductor interfaces, interfacial potential distributions).
Time-correlation functions
Authors: Nitzan Abraham 
Published: June 2024

Abstract
This chapter discusses classical and quantum correlation functions and the use of harmonic representations of thermal environments. (1) Time correlation functions in stationary systems. (2) Simple examples (the diffusion coefficient, golden rule rates). (3) Classical time correlation functions. (4) Quantum time-correlation functions. (5) Harmonic reservoir (classical bath, the spectral density, quantum bath, instantaneous normal modes).
Vibrational energy relaxation
Authors: Abraham Nitzan 
Published: June 2024

Abstract
This chapter describe the applications of quantum and classical relaxation theory to vibrational relaxation of molecules interacting with their thermal environments. (1) A model Hamiltonian for a molecule undergoing vibrational relaxation process. (2) Evaluation of vibrational relaxation rates for different model interactions (the bilinear interaction model, nonlinear interaction models, the independent binary collision (IBC) model, multi-phonon theory of vibrational relaxation). (3) Effect of supporting modes. (4) Numerical simulations of vibrational relaxation.