bluuebunny/crossref_metadata_2025_split huggingface dataset:
Microencapsulation of antioxidant phenolics from tamarind seed peels using chia gum and maltodextrin
Authors: Abdel-Aty Azza M. , Gad Abdul Aziz M. , Barakat Amal Z. , Mohamed Saleh A. 
Published: February 2025

Abstract

Tamarindus indica seeds/seed peels (TSP) are the main waste products from the tamarind industry and contain valuable bioactive antioxidant-phenolic compounds that promote human health; however, their application is limited due to their instability and poor solubility. Encapsulation is becoming more important in several industries due to its potential for preserving and delivering valuable and delicate bioactive compounds. This study targets the microencapsulation of TSP-phenolic compounds for incorporation into functional food formulations. By employing the freeze-drying method, three microcapsule formulations were developed using chia gum (CG), maltodextrin (M), and a mixture of the two (M/CG) as coating materials. The formed M-, M/CG-, and CG-microcapsules showed remarkable encapsulation efficiency of 88.0, 90.0, and 95.0%, respectively. They preserved most of the TSP-phenolic content (87.5–96.3%) and antioxidant activity (86.0-98.8%). They demonstrated higher digestibility percentages in the intestinal media (53.0–70.0%) than in the gastric media (29.0–36.0%), especially the microcapsules coated with CG. They kept the TSP-antioxidant-phenolic content safe at 40 °C for 2 months. The microcapsules demonstrated improved microstructures, swelling, solubility, and moisture content. Crosslinking and enhanced thermal stability were also proven for microcapsules via FTIR and thermogravimetric studies. In addition, the prepared microcapsules displayed better antimicrobial activity against the examined bacterial strains, with minimum bactericidal concentrations ranging from 0.61 to 1.4 mg/mL. In conclusion, the encapsulation improved the stability, bioavailability, and antibacterial properties of TSP-phenolic compounds, making them suitable for food and pharmaceutical applications.
A spatial transcriptomic signature of 26 genes resolved at single-cell resolution characterizes high-risk gastric cancer precursors
Authors: Huang Robert J. , Wichmann Ignacio A. , Su Andrew , Sathe Anuja , Shum Miranda V. , Grimes Susan M. , Meka Rithika , Almeda Alison , Bai Xiangqi , Shen Jeanne , Nguyen Quan , Luo Ingrid , Han Summer S. , Amieva Manuel R. , Hwang Joo Ha , Ji Hanlee P. 
Published: February 2025

Abstract
Gastric cancer precursors demonstrate highly-variable rates of progression toward neoplasia. Certain high-risk precursors, such as gastric intestinal metaplasia with advanced histologic features, may be at up to 30-fold increased risk for progression compared to lower-risk intestinal metaplasia. The biological differences between high- and low-risk lesions have been incompletely explored. In this study, we use several clinical cohorts to characterize the microenvironment of advanced gastric cancer precursors relative to low-risk lesions using bulk, spatial, and single-cell gene expression assays. We identified a 26-gene panel which is associated with advanced lesions, localizes to metaplastic glands on histopathology, and is expressed in aberrant mature and immature intestinal cells not normally present in the healthy stomach. This gene expression signature suggests an important role of the immature intestinal lineages in promoting carcinogenesis in the metaplastic microenvironment. These findings may help to inform future biomarker development and strategies of gastric cancer prevention.
Evaluating feature extraction in ovarian cancer cell line co-cultures using deep neural networks
Authors: Sharma Osheen , Gudoityte Greta , Minozada Rezan , Kallioniemi Olli P. , Turkki Riku , Paavolainen Lassi , Seashore-Ludlow Brinton 
Published: February 2025

Abstract
Single-cell image analysis is crucial for studying drug effects on cellular morphology and phenotypic changes. Most studies focus on single cell types, overlooking the complexity of cellular interactions. Here, we establish an analysis pipeline to extract phenotypic features of cancer cells cultured with fibroblasts. Using high-content imaging, we analyze an oncology drug library across five cancer and fibroblast cell line co-culture combinations, generating 61,440 images and ∼170 million single-cell objects. Traditional phenotyping with CellProfiler achieves an average enrichment score of 62.6% for mechanisms of action, while pre-trained neural networks (EfficientNetB0 and MobileNetV2) reach 61.0% and 62.0%, respectively. Variability in enrichment scores may reflect the use of multiple drug concentrations since not all induce significant morphological changes, as well as the cellular and genetic context of the treatment. Our study highlights nuanced drug-induced phenotypic variations and underscores the morphological heterogeneity of ovarian cancer cell lines and their response to complex co-culture environments.
Integrated evidence reveals a new subspecies of the genus Seuratascaris (Nematoda: Ascaridomorpha), with characterization of the complete mitochondrial genome
Authors: Gu Xiao-Hong , Mu Jia-Tong , Chen Hui-Xia , Li Liang 
Published: February 2025

Species of Seuratascaris Sprent, 1985 are a rarely reported group of ascaridoid nematodes, parasitising various frogs and toads. In the present study, a new subspecies of Seuratascaris, S. physalis bazhaiensis n. subsp. was described using integrated taxonomic methods, based on specimens collected from Odorrana graminea (Anura: Ranidae) in Guangxi Zhuang Autonomous Region, China. Results of the Assemble Species by Automatic Partitioning (ASAP) and Bayesian inference based on the mitochondrial cox1, cox2 and rrnS data all supported S. physalis bazhaiensis representing a distinct taxon from the nominate subspecies S. physalis physalis. Supplementary morphometric and genetic data of S. phy. physalis are presented based on newly collected material from Odorrana tiannanensis (Anura: Ranidae) and Rhacophorus sp. (Anura: Rhacophoridae) in Yunnan Province, China. A key to species of Seuratascaris is provided. The complete mitochondrial genome of S. physalis bazhaiensis was sequenced and annotated, and represents the first mitogenomic data for the genus Seuratascaris. This mitogenome has only 13,628 bp (including 12 protein-coding genes, 22 tRNA genes, 2 ribosomal RNAs, and only 1 non-coding region), and is the smallest of the reported ascaridoid mitogenomes so far.
Prediction of hydration energies of adsorbates at Pt(111) and liquid water interfaces using machine learning
Authors: Shi Jiexin , Zhang Xiaohong , Punyapu Venkata Rohit , Getman Rachel B. 
Published: February 2025

Aqueous phase heterogeneous catalysis is important to various industrial processes, including biomass conversion, Fischer–Tropsch synthesis, and electrocatalysis. Accurate calculation of solvation thermodynamic properties is essential for modeling the performance of catalysts for these processes. Explicit solvation methods employing multiscale modeling, e.g., involving density functional theory and molecular dynamics have emerged for this purpose. Although accurate, these methods are computationally intensive. This study introduces machine learning (ML) models to predict solvation thermodynamics for adsorbates on a Pt(111) surface, aiming to enhance computational efficiency without compromising accuracy. In particular, ML models are developed using a combination of molecular descriptors and fingerprints and trained on previously published water–adsorbate interaction energies, energies of solvation, and free energies of solvation of adsorbates bound to Pt(111). These models achieve root mean square error values of 0.09 eV for interaction energies, 0.04 eV for energies of solvation, and 0.06 eV for free energies of solvation, demonstrating accuracy within the standard error of multiscale modeling. Feature importance analysis reveals that hydrogen bonding, van der Waals interactions, and solvent density, together with the properties of the adsorbate, are critical factors influencing solvation thermodynamics. These findings suggest that ML models can provide rapid and reliable predictions of solvation properties. This approach not only reduces computational costs but also offers insights into the solvation characteristics of adsorbates at Pt(111)–water interfaces.
Research on PVDF/BNNSs/MXene multilayer films with high energy density and thermal conductivity for dielectric capacitors
Authors: Meng Shuo , Zhao Tong , Wang Zhijuan , Wang Xiaosong , Wang Xiaolong , Zhang Yuantao 
Published: February 2025

Polyvinylidene fluoride (PVDF) has promising applications in the field of dielectric capacitors. However, its low dielectric constant and thermal conductivity limit energy storage density. To address this, three multilayer composite topologies were designed with PVDF/boron nitride nanosheets as insulation and PVDF/MXene as polarization layers. A performance evaluation framework based on the analytic hierarchy process technique for order preference by similarity to the ideal solution method identified the insulation–polarization–polarization–insulation topology as the optimal configuration. This structure enhanced the dielectric performance (εr/tan δ) by 239.44% over pure PVDF at 103 Hz, increased thermal conductivity by 60.45%, and improved breakdown field strength. In addition, charge–discharge efficiency at 300 MV/m reached 75%, with a discharge density of 6.3 J/cm3, which is 152% higher than PVDF. The multilayer design effectively integrates the strengths of each layer to significantly enhance the overall performance, demonstrating that operational research methods are practical for evaluating dielectric materials and guiding design.
Simulating nonadiabatic dynamics in benzophenone: Tracing internal conversion through photoelectron spectra
Authors: Restaino Lorenzo , Schnappinger Thomas , Kowalewski Markus 
Published: February 2025

Benzophenone serves as a prototype chromophore for studying the photochemistry of aromatic ketones, with applications ranging from biochemistry to organic light-emitting diodes. In particular, its intersystem crossing from the first singlet excited state to triplet states has been extensively studied, but experimental or theoretical studies on the preceding internal conversion within the singlet manifold are very rare. This relaxation mechanism is particularly important because direct population transfer of the first singlet excited state from the ground state is inefficient due to its low oscillator strength. In this work, our aim is to fill this gap by employing mixed quantum-classical and full quantum dynamics simulations and time-resolved photoelectron spectroscopy for gas-phase benzophenone and meta-methyl benzophenone. Our results show that nonadiabatic relaxation via conical intersections leads to an increase in the population of the first singlet excited state, which appears linear within the simulation time of 500 fs. This population transfer due to conical intersections can be directly detected by a bifurcation of the photoelectron signal. In addition, we discuss to clarify the role of the third singlet excited state degenerate to the second excited state—a topic that remains largely unexplored in the existing literature on benzophenone.
A novel 22-bp InDel in the intron 1 of the IGF1 gene is associated with slaughtering performance of Chinese Jiaji duck
Authors: Wu Fanghu , Gu Lihong , Shang Yuanyuan , Zhang Xiaohui , Xu Zixin , Xu Tieshan 
Published: February 2025

Context Insertion/deletion can affect poultry growth traits and slaughter performance. Poultry performance can be progressively improved by selecting poultry individuals carrying favorable variants for breeding. Aims The aim of this study was to analyze the correlation between insertion/deletion (InDel) polymorphisms in insulin-like growth factor 1 (IGF1) gene and slaughter performance and growth traits of Jiaji ducks. Methods We measured the growth traits and slaughter performance of 102 Jiaji ducks randomly selected at 90 days of age. The polymerase chain reaction products of Jiaji duck were genotyped using 2% agarose gel electrophoresis. One 22-bp InDel variant was found in the intron 1 of the IGF1 gene. General linear-model (GLM) procedures were used to determine the growth traits and slaughter performances with different InDel genotypes. Key results This 22-bp InDel variant exerted a significant influence on pre-slaughter bodyweight, carcass weight, eviscerated weight, percentage of skin fat, percentage of lean meat and percentage of leg muscle. The 22-bp InDel was adjacent to the transcription start site of the IGF1 gene and predicted to be nearby the core promoter of the IGF1 gene. The InDel mutation resulted in the loss of four transcription factor binding sites. The expression level of IGF1 mRNA was significantly reduced in the breast muscle of mutant individuals. Conclusions The results showed that the 22-bp InDel of the IGF1 gene had a significant effect on the slaughtering performance. Among the growth traits, the bodyweight showed significant effects, whereas no significant impacts were observed on other traits. Implications The InDel locus of the IGF1 gene can be used as a useful molecular marker for genetic breeding of Jiaji ducks.
A UDL blended curriculum metamodel for proficiency-oriented Chinese instruction
Authors: Yu Qiaona , Lei Yuyun , Lu Lu 
Published: February 2025

Abstract
With its evident need in a globalized era, world language education has nonetheless faced a precipitous enrollment decline in the U.S. This study responds to such challenges by proposing a Universal Design for Learning (UDL) Blended Curriculum Metamodel. The Metamodel aims to provide proficiency-oriented instruction for learners across levels with diverse backgrounds, abilities, and needs. At the novice-intermediate level, a technology-enriched asynchronous series was designed as an integral or supplementary part of a face-to-face class with the aim to provide multiple means of representation and action & expression. At the intermediate-advanced level, a self-guided project was designed to provide students with multiple means of engagement. The study examined the effectiveness of the proposed Metamodel via students’ perceptions and discussed implications for its further implementations.
Predicate nominals in Tshila
Authors: Storment John David 
Published: February 2025

Abstract
Tshila /tshílà/ is a Kalahari Khoe language spoken in central-southeastern Botswana by approximately
300 people (Schwab & Collins 2024). It is an SOV language. Tshila has a copular
predicate nominal construction with the word order [Noun Noun COP]. The nouns in this language can vary in size according to
factors such as the projection of phi-feature morphology and the presence of constituent negation and focus. Also possible in
Tshila is predicate inversion. The interaction of the size of the DPs along with the presence of inversion shows interesting
constraints on nominative Case assignment and phi-agreement. The analysis of this construction supports a universal hierarchy of
phi-features (Harley & Ritter 2002; Béjar 2003), not only within nominals but also
on phi-probes. This analysis unifies Case assignment and phi-agreement as a single operation (Chomsky 2000; 2001; Platzack
2006; Legate 2008; Georgi 2017),
which supports the view that Case assignment is not postsyntactic.
An atomistic K-test framework for general grain boundaries and triclinic single crystals
Authors: Brunner Florian , Andric Predrag , Maresca Francesco 
Published: February 2025

Abstract
In the present study, an atomistic K-test framework for the fracture toughness assessment of generally oriented grain boundaries (tilt, twist, mixed) and triclinic single crystals is investigated. Boundary conditions for the modelling of cracks along the interfaces of bicrystals are derived based on the 6th-order Stroh formalism and compared with established approaches. Thereby, especially the oscillations in the relevant field quantities due to mode I loading are critically assessed. It is found that for engineering applications, these oscillations do not compromise the validity of the employed approach since they are confined to a negligibly small region at the crack tip. Next, the 6th-order Stroh approach is used to investigate crack propagation along grain boundaries under mode I loading. A crack identification and crack tip tracing scheme is included to update the imposed boundary conditions during the simulations. Lastly, a physically-motivated method is discussed and incorporated, which allows for the unambiguous determination of the fracture toughness, including challenging setups such as generally oriented grain boundaries. The so-established K-test setup is validated with a series of numerical examples.
Equilibrium and nonequilibrium Gibbs states on sofic groups
Authors: Shriver Christopher 
Published: February 2025

Abstract
Recent work of Barbieri and Meyerovitch has shown that, for very general spin systems indexed by sofic groups, equilibrium (i.e. pressure-maximizing) states are Gibbs. The main goal of this paper is to show that the converse fails in an interesting way: for the Ising model on a free group, the free-boundary state typically fails to be equilibrium as long as it is not the only Gibbs state. For every temperature between the uniqueness and reconstruction thresholds a typical sofic approximation gives this state finite but non-maximal pressure, and for every lower temperature the pressure is non-maximal over every sofic approximation. We also show that, for more general interactions on sofic groups, the local on average limit of Gibbs states over a sofic approximation Σ, if it exists, is a mixture of Σ-equilibrium states. We use this to show that the plus- and minus-boundary-condition Ising states are Σ-equilibrium if Σ is any sofic approximation to a free group. Combined with a result of Dembo and Montanari, this implies that these states have the same entropy over every sofic approximation.
Enhanced phase extraction in optical coherence elastography using discrete cosine transform for localized tissue characterization
Authors: Satpathy Sweta , Poddar Raju 
Published: February 2025

Abstract
We develop a novel enhanced laser-based elastography technique that utilizes an optical coherence tomography (OCT) imaging system. This enhancement combines the capabilities of OCT with an advanced phase extraction technique, aiming to increase the precision of biomechanical measurements in soft tissues. Our approach utilizes the discrete cosine transform (DCT) for phase extraction, overcoming the limitations of vector-based methods in handling complex geometries and large displacements. Unlike fast Fourier transform-based unwrapping, DCT ensures thar the result is artifact-free. This advancement refines spatial detail in optical coherence elastography (OCE), enabling accurate mapping of tissue elasticity and structural variations. By eliminating windowing constraints, our method offers a faster, more robust solution for biomechanical diagnostics. In this study, we introduce a micro-elastography system that utilizes a 4 ohm speaker as a mechanical excitation source to apply controlled, quasi-static compressions. This system, combined with a high-speed, 100 kHz swept-source OCT laser, enables rapid data acquisition and straightforward phase-to-strain conversion. Our findings demonstrate the system’s capability of providing accurate strain mapping across a range of samples, delivering reliable elastic information despite the challenges posed by non-linear and non-uniform tissue boundaries. This study showcases the potential of DCT-based OCE to enhance clinical diagnostics and improve the characterization of diseased and tumor boundaries in soft tissues.
Finite element analysis of the impact of graphene filler dispersion on local hotspots in HMX-Based PBX explosives
Authors: Yang Xuanyi , Huang Xin , Zhang Chaoyang , Wang Yanqing , Ni Yuxiang 
Published: February 2025

Abstract
The incorporation of graphene fillers into polymer matrices has been recognized for its potential to enhance thermal conductivity, which is particularly beneficial for applications in thermal management. The uniformity of graphene dispersion is pivotal to achieving optimal thermal conductivity, thereby directly influencing the effectiveness of thermal management, including the mitigation of local hot-spot temperatures. This research employs a quantitative approach to assess the distribution of graphene fillers within a PBX (plastic-bonded explosive) matrix, focusing specifically on the thermal management of hot spots. Through finite element method (FEM) simulations, we have explored the impact of graphene filler orientation, proximity to the central heat source, and spatial clustering on heat transfer. Our findings indicate that the strategic distribution of graphene fillers can create efficient thermal conduction channels, which significantly reduce the temperatures at local hot spots. In a model containing 0.336% graphene by volume, the central hotspot temperature was reduced by approximately 60K compared to a pure PBX material, under a heat flux of 600W/m2. This study offers valuable insights into the optimization of the spatial arrangement of low-concentration graphene fillers, aiming to improve the thermal management capabilities of HMX-based PBX explosives.
Relativistic Non-Fermi Liquid Fixed Point in 2+1 Dimensional Birefringent Dirac Fermions Interacting with Electromagnetic Fields
Authors: Sun Wan-Zi , Liu Kai , Liu Wu-Ming , Li Cheng-Xi 
Published: February 2025

Abstract
The system consisting of 2+1 dimensional quasirelativistic birefringent Dirac fermions with Coulomb interactions and retarded current-current interactions is described by a quantum field theory similar to reduced quantum electrodynamics. We used the perturbative renormalization group method to study the low-energy behavior of the system and found that it flows to a fixed point of the non-Fermi liquid composed of relativistic pseudospin-1/2 Dirac fermions in the deep infrared limit. At the fixed point, the fermion Green function exhibits a finite anomalous dimension, and the residue of the quasiparticle pole vanishes in a power-law fashion. Our research provides new theoretical perspectives for understanding the origin of spin-1/2 fermions in the Standard Model.
Deep-UV-photo-excited synaptic Ga2O3 nano-device with low-energy consumption for neuromorphic computing
Authors: Yang Liubin , Gu Xiushuo , Zhou Min , Zhang Jianya , Huang Yonglin , Zhao Yukun 
Published: February 2025

Abstract
Synaptic nano-devices have powerful capabilities in logic, memory and learning, making them essential components for constructing brain-like neuromorphic computing systems. Here, we have successfully developed and demonstrated a synaptic nano-device based on Ga2O3 nanowires with low energy consumption. Under 255 nm light stimulation, the biomimetic synaptic nano-device can stimulate various functionalities of biological synapses, including pulse facilitation, peak time-dependent plasticity and memory learning ability. It is found that the artificial synaptic device based on Ga2O3 nanowires can achieve an excellent "learning−forgetting−relearning" functionality. The transition from short-term memory to long-term memory and retention of the memory level after the stepwise learning can attribute to the great relearning functionality of Ga2O3 nanowires. Furthermore, the energy consumption of the synaptic nano-device can be lower than 2.39 × 10‒11 J for a synaptic event. Moreover, our device demonstrates exceptional stability in long-term stimulation and storage. In the application of neural morphological computation, the accuracy of digit recognition exceeds 90% after 12 training sessions, indicating the strong learning capability of the cognitive system composed of this synaptic nano-device. Therefore, our work paves an effective way for advancing hardware-based neural morphological computation and artificial intelligence systems requiring low power consumption.