bluuebunny/crossref_metadata_2025_split huggingface dataset:
Novel Sulfonamide‐Sydnone Hybrids: Complementary Insight into Anti‐Inflammatory Action, Anti‐SARS‐CoV‐2 Activity, Human Serum Albumin Interaction, and in silico Analysis
Authors: Resendes Barbosa Igor , Alves Amorim Mayara , de Souza Oliveira Vitor Hélio , André Eunice , Pereira Guedes Guilherme , Augusto Chaves Otávio , Serpa Carlos , Fintelman‐Rodrigues Natalia , Sacramento Carolina Q. , Moreno L. Souza Thiago , Sant'Anna Carlos Mauricio R. , Echevarria Aurea 
Published: February 2025

AbstractAcute lung injury (ALI) is a severe condition often seen in intensive care unit patients. Due to limited treatment options, ALI is linked to high rates of mortality and morbidity. Bacterial and viral infections are significant contributors to ALI. For instance, severe acute respiratory syndrome‐coronavirus‐2 (SARS‐CoV‐2) infection can lead to a strong inflammatory response that may progress to ALI, a leading cause of death in COVID‐19 cases. Prior research has demonstrated that sulfonamides and sydnones exhibit anti‐inflammatory and antiviral properties, which has led us to develop compounds containing both scaffolds. Most of the new sulfonamide‐sydnone hybrids are expected to be orally bioavailable based on in silico ADME predictions. They effectively suppressed the development of ALI in lipopolysaccharide (LPS)‐challenged mice and inhibited viral replication in Calu‐3 cells, with minimal cytotoxicity in non‐infected Calu‐3 and Vero E6 cells. Molecular docking investigations indicated some possible viral targets for the action of the sydnones, highlighting the possible interaction with non‐structural proteins of SARS‐CoV‐2. Additionally, combined experimental and theoretical studies indicated that the new compounds can strongly interact with human serum albumin, suggesting a possible extended residence time in the human bloodstream.
ARTransformer: An Architecture of Resolution Representation Learning for Cross‐Resolution Person Re‐Identification
Authors: Lu Xing , Lai Fengshan , Cao Zhixiang , Xia Daoxun 
Published: February 2025

ABSTRACTCross‐resolution person re‐identification (CR‐ReID) seeks to overcome the challenge of retrieving and matching specific person images across cameras with varying resolutions. Numerous existing studies utilize established CNNs and ViTs to resize captured low‐resolution (LR) images and align them with high‐resolution (HR) image features or construct common feature spaces to match between images of different resolutions. However, these methods ignore the potential feature connection between the LR and HR images of the same pedestrian identity. Besides, the CNNs or ViTs usually obtain outliers within the attention maps of LR images; this inclination to excessively concentrate on anomalous information may obscure the genuine and anticipated characteristics between images, which makes it challenging to extract meaningful information from the images. In this work, we propose the abnormal feature elimination and reconfiguration Transformer (ARTransformer), a novel network architecture for robust cross‐resolution person re‐identification tasks. This method uses a resolution feature discriminator to learn resolution‐invariant features and output feature matrices of images with different resolutions. It then calculates the potential feature relationships between images of pedestrians with the same identity but different resolutions through a new cross‐resolution landmark agent attention (CR‐LAA) mechanism. Conclusively, it utilizes output feature matrices to model LR and HR image interactions by mitigating abnormal image features and prioritizing attention on the target person by learning representations from input images of various resolutions. Experimental results show that ARTransformer performs well in matching images with different resolutions, even with unseen resolution, and extensive evaluations on four real‐world datasets confirm the excellent results of our approach.
Identification of Adsorption Sites for CO2 in a Series of Rare‐Earth and Zr‐Based Metal‐Organic Frameworks
Authors: Tassé Dylan , Quezada-Novoa Victor , Copeman Christopher , Howarth Ashlee J , Rochefort Alain 
Published: February 2025

The adsorption of CO2 in MOF‐808, NU‐1000 and a series of rare‐earth CU‐10 analogues has been studied with first principles DFT and classical Monte‐Carlo methods. DFT calculations describe the interaction of CO2 with the different metal‐organic frameworks (MOFs) as physisorption, but where we can distinguish several adsorption sites in the vicinity of the metal nodes. Beyond the identification of adsorption sites, the MOFs were synthesized, activated, and characterized to evaluate their experimental N2 and CO2 adsorption capacity. Classical Grand Canonical Monte‐Carlo (GCMC) simulations for the adsorption of CO2 are in very good agreement with DFT results for identifying the most favored adsorption sites in the MOFs. In contrast, a rather mixed agreement between GCMC simulations and experimental results is found for the estimation of adsorption capacity {of several MOFs studied toward N2 and CO2.
A User‐Centric Approach to Reliable Automated Flow Cytometry Data Analysis for Biomedical Applications
Authors: Popp Georg , Jöckel Lisa , Kläs Michael , Wiener Thomas , Hilger Nadja , Stumpf Nils , Groß Janek , Dünkel Anna , Blache Ulrich , Fricke Stephan , Franz Paul 
Published: February 2025

ABSTRACTAutomation and the increased number of measurable parameters in flow cytometry (FCM) have strongly increased the volume and complexity of phenotyping immune cell populations. Despite numerous automated gating methods for FCM analysis, their adoption in routine practice remains challenging due to accessibility barriers for users and potential model failures. Here, we propose a user‐centered solution that combines elements of supervised machine learning (SML), rapid application development (RAD), systematic quality assurance guided by structured argumentation, and uncertainty estimation to address these challenges. We implement a data‐driven model for event classification and use RAD to generate software prototypes, allowing FCM users to apply the model for automated gating. Considering concepts for structured argumentation from assurance cases (ACs), we derived and justified quality analyses that inform users about the quality of the model. We propose guiding the model operation phase using uncertainty estimation to provide users with a clear understanding of the model's confidence in its predictions. We aim to overcome barriers to the routine application of automated gating and contribute to more reliable and efficient FCM data analysis. Our approach is based on the application of phenotyping for human immune cells. We encourage future research to investigate the potential of SML, ACs, and uncertainty estimation to address dependability of data‐driven models (DDMs) supporting diagnostic decision making in the medical domain, including FCM in clinical applications and highly regulated areas such as pharmaceutical research.
Frequency and Predictors of Shape/Weight Concerns and Objective Binge Eating in Avoidant/Restrictive Food Intake Disorder (ARFID)
Authors: Kambanis P. Evelyna , Palmer Lilian P. , Jhe Grace , McPherson Iman , Graver Haley , Dalton Abigail G. , Ji Chunni , Asanza Elisa , Shabazian Lauren , Dunford Ashley , Breithaupt Lauren , Freizinger Melissa , Eddy Kamryn T. , Misra Madhusmita , Micali Nadia , Holsen Laura , Lawson Elizabeth A. , Becker Kendra R. , Thomas Jennifer J. 
Published: February 2025

ABSTRACTObjectiveDSM‐5 prohibits the diagnosis of avoidant/restrictive food intake disorder (ARFID) in the context of clinically significant shape/weight concerns. However, emerging data suggest that ARFID and shape/weight concerns may co‐occur, and DSM‐5‐TR now permits comorbid binge‐eating disorder alongside ARFID. We compared shape/weight concerns in adults with ARFID to healthy controls (HCs) and nonclinical norms; assessed the frequency of clinical‐level shape/weight concerns and past‐month objective binge episodes (OBE); and identified ARFID characteristics linked to elevated shape/weight concerns and OBEs. We hypothesized that individuals with ARFID would exhibit lower shape/weight concerns than HCs and nonclinical norms, that none would exhibit clinical‐level shape/weight concerns, and that higher weight would predict greater shape/weight concerns. Our examination of OBEs was exploratory.MethodParticipants with ARFID (N = 83) and HCs (N = 41) completed the Eating Disorder Examination—Questionnaire (EDE‐Q).ResultsAdults with ARFID scored significantly higher than HCs but significantly lower than nonclinical norms on shape/weight concerns. Two percent exhibited clinical‐level shape/weight concerns, and 15% reported past‐month OBEs. Higher weight uniquely predicted shape/weight concerns.DiscussionShape/weight concerns are lower in ARFID than in the general population, and a small proportion of adults with ARFID—particularly those at higher weights—may experience clinical‐level shape/weight concerns and OBEs.
Deeply Diverged but Morphologically Conserved Lineages in Tornier's Cat Snake (Crotaphopeltis tornieri) of the Eastern Arc Mountains
Authors: Nielsen Tejs L. , Nielsen Sofie Holdflod , Novosolov Maria , Gravlund Peter , Allentoft Morten E. 
Published: February 2025

ABSTRACTThe Eastern Arc Mountain (EAM) forests in Tanzania have remarkably high endemism. Closely‐related forest‐adapted species are found isolated on different “sky islands” testifying to allopatry as a major driver for speciation in this region. However, some species defy this pattern. Tornier's cat snake (Crotaphopeltis tornieri) occupies most of the isolated mountain rainforest, despite presumably not being able to move across the arid savannah landscape that separates them. To test contrasting hypotheses of recent dispersal vs morphological conservatism we examined scale characters of 218 C. tornieri individuals and sequenced 80 full mitochondrial genomes covering populations from eight mountain blocks across the EAM and Southern Highlands of Tanzania (SHT). The morphological examination revealed no differentiation between populations except the Usambara Mountain populations showing significant differences in some scale characters. This was in stark contrast to the genetic analyses showing very high divergence between mountain populations. On average the mitochondrial genome showed > 12% genetic differentiation with cytB and COI showing interpopulation distances of up to 28.5% and 15.1%, respectively. Both Bayesian coalescent and maximum‐likelihood based phylogenies, uncovered a highly distinct clade structure in C. tornieri defined by the mountains. Divergence times were estimated at c. 21 million years for the split between the EAM and SHT populations and 5.4–1.4 millions years for population splits within EAM. Our results point towards old isolation events but with a highly conserved morphology resulting in just one recognized species. By including presumed outgroups of C. degeni and C. hotamboeia in the phylogeny we found C. tornieri to be paraphyletic. These results have implications for understanding evolution in the EAM and warrant a revision of the number of species in this genus.
Two Novel Species of Genus Melanoleuca (Agaricales) From Indian Himalaya
Authors: Choudhary Shikha , Mehmood Tahir , Sharma Yash Pal , Uniyal Priyanka 
Published: February 2025

ABSTRACTTwo interesting taxa of genus Melanoleuca have been reported from cultivated lands of temperate regions in Uttarakhand Himalaya and Ladakh Himalaya. These taxa are proposed here as Melanoleuca deothalensis sp. nov. and Melanoleuca drassina sp. nov. The novel taxa are presented in present communication with detailed taxonomic descriptions, photomicrographs, illustrations, and nrITS‐based phylogeny.
Finite Element Numerical Simulation of Free Convection Heat Transfer in a Square Cavity Containing an Inclined Prismatic Obstacle With Machine Learning Optimization
Authors: Rajarajeswari Perepi , Arasukumar Thilagavathi , Anwar Bég O. , Bég Tasveer A. , Kuharat S. , Bala Anki Reddy P. , Ramachandra Prasad V. 
Published: February 2025

ABSTRACTThe present work describes a numerical simulation of free convection heat transfer inside a square cavity containing a prismatic obstacle at various angles of inclination. The nondimensional governing equations are discretized by the finite element method and solved in the commercial software “COMSOL Multiphysics 6.1” with appropriate boundary conditions. The effect of prominent parameters on streamline, isotherm contours, and local Nusselt number profiles are depicted graphically. The control parameters are the Prandtl number and Rayleigh number (103 ≤ Ra ≤ 106). The study considers air as the circulating fluid with the Prandtl number, Pr = 0.71. The computations are conducted for the prismatic shape at four different orientations of , and . The inclination angle of the prismatic obstacle is observed to exert a significant role in the distribution of heat and momentum inside the square cavity. Furthermore, neural network approaches are used for optimizing the thermal performance of the system, via Bayesian regularization machine learning analysis and Levenberg–Marquardt algorithms. The study finds applications in solar collectors, fuel cells, and so forth.
Optimal Irrigation Water Allocation for Enhanced Productivity of Pepper (Capsicum annuum L.) and Economic Gain: Evidence From the Semi‐Arid Region of Ethiopia
Authors: Negash Tatek Wondimu , Tesfaye Tefera Abera , Awlachew Tigist Worku , Denku Aynalem Gurms , Bayisa Gobena Dirirsa , Bizuneh Ketema Tezera , Bikila Gebeyehu Ashami 
Published: February 2025

ABSTRACTThis study was conducted to assess the effects of different irrigation levels on pepper yield and related attributes. The experiment included five irrigation levels: 60%, 80%, 100%, 120% and 140% management‐allowed depletion (MAD). The highest pepper yield was observed under the 120% MAD, with yields of 2.09 and 2.10 t/ha during the 2017 and 2019 experimental years, respectively. Conversely, the lowest pepper yield was recorded under the 60% MAD, with yields of 1.66 and 1.71 t/ha during the 2017 and 2019 experimental seasons, respectively. In terms of water productivity, the lowest values of 0.3 (2017) and 0.33 kg/m3 (2019) were obtained under 60% MAD, whereas the highest values of 0.39 (2017) and 0.42 kg/m3 (2019) were recorded under the 120% MAD. The 120% MAD yielded the highest economic gain of $12,127. On the basis of these findings, applying 120% MAD is more favourable for pepper production in semi‐arid areas of Ethiopia and similar environments. This approach balances water availability and plant needs by allowing slightly greater soil moisture depletion, enhancing its ability to withstand water stress and reducing the frequency and volume of irrigation. This lowers labour and water costs, contributing to greater economic efficiency.
Edge Computing Enables Assessment of Student Community Building: An Emotion Recognition Method Based on TinyML
Authors: Liu Shuo 
Published: February 2025

ABSTRACTDeep network‐based video sentiment analysis is crucial for online evaluation tasks. However, these deep models are difficult to run on intelligent edge devices with limited computing resources. In addition, video data are susceptible to lighting interference, distortion, and background noise, which severely limits the performance of facial expression recognition. To relieve these issues, we develop an effective multi‐scale semantic fusion tiny machine learning (TinyML) model based on a spatiotemporal graph convolutional network (ST‐GCN) which enables robust expression recognition from facial landmark sequences. Specifically, we construct regional‐connected graph data based on facial landmarks which are collected from cameras on different mobile devices. In existing spatiotemporal graph convolutional networks, we leverage the multi‐scale semantic fusion mechanism to mine the hierarchical structure of facial landmarks. The experimental results on CK+ and online student community assessment sentiment analysis (OSCASA) dataset confirm that our approach yields comparable results.
Magnetic Resonance Imaging and Anatomical Correlation of Human Temporal Lobe Landmarks in 3D Euclidean Space: A Study of Control and Epilepsy Disease Subjects
Authors: Delgado‐González José‐Carlos , Delgado‐Gandía Carmen , Delgado‐Gandía Carlos , Cebada‐Sánchez Sandra , De‐La‐Rosa‐Prieto Carlos , Artacho‐Pérula Emilio 
Published: February 2025

ABSTRACTEpilepsy is a common neurological disorder of great importance to patients and society. Sclerosis is associated with neuronal loss and neurodegeneration in specific regions of the hippocampal formation. The hippocampal formation and temporal lobe are not the only regions affected; the chronicity of the disease extends the involvement to other brain regions. Our aim is to investigate the spatial relationship of anatomical structures in both control (CO) and epileptic (EP) subjects using magnetic resonance imaging (MRI) in order to determine changes in epileptic patients compared to healthy anatomical structures. Anatomical landmarks are identified and registered in 3D space to provide a reference for the brain structures; the 3D network is described quantitatively using planar distances, as well as measuring rostrocaudal and Euclidean distances. The planar and rostrocaudal distances are the most remarkable discriminators between CO and EP groups, especially between structures located in and outside the temporal lobe. The study achieves a 100% discrimination between the control group and the epileptic group with the discriminant use of two distances: D_PL, Hpe/Cde and D_RC, As/cae. Finally, discriminates 100% between the three study groups, control group CO, extratemporal lobe epilepsy ETLE and temporal lobe epilepsy TLE, with a total of 12 distances distributed in the three axes of space. This study allows us to hope for a future application, its clinical utility may allow us not only to identify processes (in our case, epilepsy), but also to obtain parameters of the evolution of the disease.
Comparison of key floral components between two Tilia species and among different processing technologies as revealed by widely targeted metabolomic profiling
Authors: Yuan Xiao , Wang Huanli , Yan Lingjun , Huang Xi , Tang Shijie 
Published: February 2025

AbstractBACKGROUNDTilia has a long history of cultivation and holds high ornamental and economic value. The volatile aroma compounds of Tilia flowers have significant characteristics that contribute to their ornamental appeal, and affect the flavor of floral tea. Here, widely targeted metabolomic analyses were conducted to investigate the aroma active compounds in the fresh inflorescences of Tilia cordata Mill. (Tc) and Tilia miqueliana Maxim. (Tm), and in samples prepared by freeze drying, air drying, and oven drying.RESULTSWe identified 442 volatile organic compounds by headspace solid‐phase microextraction gas chromatography–mass spectrometry. Terpenoids were the most abundant and diverse group, while heterocyclic compounds were the main contributors to the aroma profile. Notably, 46 aroma compounds were identified as primary contributors to the characteristic aroma of Tilia, including abhexon, 2‐isobutyl‐3‐methoxypyrazine, (Z)‐6‐nonenal, methyl benzoate, (E)‐2‐hexenal, 1‐hexanol, 2‐thiophenemethanethiol, p‐cymene, furaneol, and (Z)‐4‐heptenal. The concentration of volatile organic compounds was higher in Tc than in Tm, indicating a more pronounced aroma character of Tc. For both Tc and Tm, the aroma compounds were better preserved and present at higher concentrations in freeze‐dried samples than in air‐dried and oven‐dried samples.CONCLUSIONThese results provide a foundation for further research on the molecular mechanisms of aroma formation in Tilia flowers and on aroma as a cue for insect pollination. Furthermore, the results provide a basis for the development and commercialization of Tilia floral teas and other related products. © 2025 Society of Chemical Industry.
Vascularized Deep Femoral Periosteal Flap: Anatomical Study and Clinical Application in Congenital Pseudarthrosis of the Tibia in Two Cases
Authors: da Costa Antonio Carlos , Romero‐Larrauri Pablo , Rojas‐Neira Juliana , Gonzalez‐Morgado Diego , Fouad Amr , Alves Cristina , Soldado Francisco 
Published: February 2025

ABSTRACTBackgroundVascularized periosteal transplants have proven to be highly effective and rapid in promoting bone healing in biologically complex nonunions in children, with several reported donor sites. This study aimed to assess the feasibility of harvesting a vascularized diaphyseal femoral periosteal flap (VDFPF) from cadavers and evaluate its clinical application in two cases of bilateral congenital pseudarthrosis of the tibia.MethodsThis study investigated the periosteal branches of the deep femoral vessels (DFV) supplying the femoral diaphysis in 19 previously latex‐injected cadavers. The femur was divided into four segments. The distance from the midpoint of the inguinal ligament to the origin of the DFV and the number of periosteal branches were recorded. The vascularized diaphyseal femoral periosteal flap (VDFPF) was used to treat one side in two patients with bilateral congenital pseudarthrosis of the tibia (aged 14 and 2 years).ResultsThe DFV's origin was located at a mean of 4.2 cm (range 2.8–8.5 cm) distal to the midpoint of the inguinal ligament. In 15 cases, the DFV coursed adjacent to the second and third quarters of the femoral shaft, providing a mean number of 5 (range 4–8) periosteal branches, allowing for the harvesting of a new pure vascularized periosteal flap. Healing of congenital pseudarthrosis of the tibia occurred within 3 months in both patients, with no donor or recipient site complications at the final follow‐up of 13 months.ConclusionsThe VDFPF may be an effective periosteal transplant and a viable alternative to other large free periosteal transplants used in children for treating complex non‐unions, especially when tibial and fibular donors are not available. Bone union was fast compared to other techniques used to treat these challenging cases.
Efficient Optimization of Engineering Problems With A Particular Focus on High‐Order IIR Modeling for System Identification Using Modified Dandelion Optimizer
Authors: Izci Davut , Hashim Fatma A. , Mostafa Reham R. , Ekinci Serdar , Smerat Aseel , Migdady Hazem , Abualigah Laith 
Published: February 2025

ABSTRACTThis paper introduces the modified dandelion optimizer (mDO), a novel adaptive metaheuristic algorithm designed to address complex engineering optimization challenges, with a focus on infinite impulse response (IIR) system identification. The proposed mDO incorporates three key advancements: an enhanced descending phase to improve global exploration, a novel exploration‐exploitation phase that balances search intensity and breadth, and a self‐adaptive crossover operator that refines solutions dynamically. These innovations specifically target the challenges associated with high‐order IIR modeling, enabling mDO to deliver more precise and efficient system identification. To validate its performance, mDO was rigorously evaluated across diverse testing environments, including the CEC2017 and CEC2022 benchmark functions, various IIR model identification scenarios, and real‐world engineering design problems such as multi‐product batch plant design, multiple disk clutch brake design, and speed reducer design. Comparative analyses reveal that mDO consistently outperforms leading optimization algorithms in terms of accuracy, robustness, and computational efficiency, particularly in complex, high‐dimensional landscapes. Statistical assessments further confirm mDO's superior capability in accurately identifying IIR system parameters even under noise and varying model orders. This study positions mDO as a competitive and versatile tool for engineering applications, offering significant improvements in optimization accuracy and adaptability for advanced system modeling and real‐world problem‐solving.