bluuebunny/crossref_metadata_2025_split huggingface dataset:
Improvement of the aerodynamic behavior of a sport utility vehicle numerically by using some modifications and aerodynamic devices
Authors: Al-Saadi Ahmed , Al-Farhany Khaled , Idan Al-Chlaihawi Kadhim K. , Jamshed Wasim , Eid Mohamed R. , Tag El Din El Sayed M. , Raizah Zehba 
Published: November 2022

AbstractThe present study proposes aerodynamically optimized exterior designs of a sport utility vehicle using computational fluid dynamics analysis based on steady-state Reynolds-averaged Navier–Stokes turbulence models. To achieve an optimal design, modifications of the outer shape and adding some aerodynamic devices are investigated. This study focuses on modifying this vehicle model’s upper and front parts. At the same time, the rear diffuser and spare tire on the back door as a fairing are used as aerodynamic devices for improving streamlines. All these modifications and add-on devices are simulated individually or in combination to achieve the best exterior design. A variety of Reynolds numbers are used for determining the optimization variables. Tetrahedral cells are used throughout the global domain because of the sharp edges in the geometry of the Discovery car model. At the same time, prism cells around car surfaces are adopted to improve the accuracy of the results. A good agreement between the numerical drag coefficient in the present study for the baseline models and the experimental data has been achieved. Changes in the drag and lift coefficients are calculated for all models. It is clear from the numerical results that the use of combined modifications and add-on devices has a significant effect in improving the overall aerodynamic behavior. As a result, the drag coefficient for the optimal design of the Discovery 4th generation is reduced from 0.4 to 0.352 by about 12% compared to the benchmark. Simultaneously, the lift coefficient is 0.037 for optimal design, and it is an acceptable value. It is found that combining all optimal modified configurations can improve both CD and CL simultaneously.
Comparative metabolite profiling of four polyphenol rich Morus leaves extracts in relation to their antibiofilm activity against Enterococcus faecalis
Authors: Salem Mohamed A. , Salama Maha M. , Ezzat Shahira M. , Hashem Yomna A. 
Published: November 2022

AbstractEnterococci are a common cause of urinary tract infections. The severity of enterococcal infections is associated with their ability to form biofilms. Morus leaves are known as a natural antibacterial, however, their antibiofilm activity against Enterococcus remains unveiled. This study aimed to evaluate the ability of four polyphenol-rich Morus leaves extracts (Morus nigra,M.rubra,M.macroura,andM.alba)to inhibit biofilm formed by enterococcal clinical isolates in relation to their metabolic profiling. Results revealed that 48% of the isolates formed strong biofilm, 28% formed moderate biofilm, 20% formed weak biofilm, and only 4% did not form a biofilm. The strong biofilm-forming isolates wereE. faecalis,and hence were chosen for this study.The antibiofilm activity of the four polyphenol-rich Morus leaves extracts revealed that theM.nigraextract exhibited the highest percentage of biofilm inhibition followed byM.rubrathenM.macrouraand the least inhibition was detected inM.alba,and these results were in accordance with the phenolic and flavonoid contents of each extract.UPLC-ESI-MS/MS identified 61 polyphenolic compounds in the four extracts. Further, multivariate analysis confirmed clear segregation ofM. nigrafrom the other species suggesting disparity in its metabolome, with accumulation of flavonoids, anthocyanidins, phenolic acids and coumarin derivatives. Quercetin and kaempferol glycosides were found to be positively and significantly correlated to the antibiofilm activity. In conclusion,M. nigraethanolic extracts showed the highest phenolic content and antibiofilm activity and they could be developed as a complementary treatment for the development of antimicrobial agents.
The 3D ultrastructure of the chordotonal organs in the antenna of a microwasp remains complex although simplified
Authors: Diakova Anna V. , Makarova Anastasia A. , Pang Song , Xu C. Shan , Hess Harald , Polilov Alexey A. 
Published: November 2022

AbstractInsect antennae are astonishingly versatile and have multiple sensory modalities. Audition, detection of airflow, and graviception are combined in the antennal chordotonal organs. The miniaturization of these complex multisensory organs has never been investigated. Here we present a comprehensive study of the structure and scaling of the antennal chordotonal organs of the extremely miniaturized parasitoid waspMegaphragma viggianiibased on 3D electron microscopy. Johnston’s organ ofM. viggianiiconsists of 19 amphinematic scolopidia (95 cells); the central organ consists of five scolopidia (20 cells). Plesiomorphic composition includes one accessory cell per scolopidium, but inM. viggianiithis ratio is only 0.3. Scolopale rods in Johnston’s organ have a unique structure. Allometric analyses demonstrate the effects of scaling on the antennal chordotonal organs in insects. Our results not only shed light on the universal principles of miniaturization of sense organs, but also provide context for future interpretation of theM. viggianiiconnectome.
Eye movement behavior in a real-world virtual reality task reveals ADHD in children
Authors: Merzon Liya , Pettersson Kati , Aronen Eeva T. , Huhdanpää Hanna , Seesjärvi Erik , Henriksson Linda , MacInnes W. Joseph , Mannerkoski Minna , Macaluso Emiliano , Salmi Juha 
Published: November 2022

AbstractEye movements and other rich data obtained in virtual reality (VR) environments resembling situations where symptoms are manifested could help in the objective detection of various symptoms in clinical conditions. In the present study, 37 children with attention deficit hyperactivity disorder and 36 typically developing controls (9–13 y.o) played a lifelike prospective memory game using head-mounted display with inbuilt 90 Hz eye tracker. Eye movement patterns had prominent group differences, but they were dispersed across the full performance time rather than associated with specific events or stimulus features. A support vector machine classifier trained on eye movement data showed excellent discrimination ability with 0.92 area under curve, which was significantly higher than for task performance measures or for eye movements obtained in a visual search task. We demonstrated that a naturalistic VR task combined with eye tracking allows accurate prediction of attention deficits, paving the way for precision diagnostics.
Epigenome-wide association study of physical activity and physiological parameters in discordant monozygotic twins
Authors: Duncan Glen E. , Avery Ally , Thorson Jennifer L. M. , Nilsson Eric E. , Beck Daniel , Skinner Michael K. 
Published: November 2022

AbstractAn epigenome-wide association study (EWAS) was performed on buccal cells from monozygotic-twins (MZ) reared together as children, but who live apart as adults. Cohorts of twin pairs were used to investigate associations between neighborhood walkability and objectively measured physical activity (PA) levels. Due to dramatic cellular epigenetic sex differences, male and female MZ twin pairs were analyzed separately to identify differential DNA methylation regions (DMRs). A priori comparisons were made on MZ twin pairs discordant on body mass index (BMI), PA levels, and neighborhood walkability. In addition to direct comparative analysis to identify specific DMRs, a weighted genome coexpression network analysis (WGCNA) was performed to identify DNA methylation sites associated with the physiological traits of interest. The pairs discordant in PA levels had epigenetic alterations that correlated with reduced metabolic parameters (i.e., BMI and waist circumference). The DNA methylation sites are associated with over fifty genes previously found to be specific to vigorous PA, metabolic risk factors, and sex. Combined observations demonstrate that behavioral factors, such as physical activity, appear to promote systemic epigenetic alterations that impact metabolic risk factors. The epigenetic DNA methylation sites and associated genes identified provide insight into PA impacts on metabolic parameters and the etiology of obesity.
Long-term body tactile stimulation reduces aggression and improves productive performance in Nile tilapia groups
Authors: dos Santos Gauy Ana Carolina , Bolognesi Marcela Cesar , Gonçalves-de-Freitas Eliane 
Published: November 2022

AbstractOne concern of the Anthropocene is the effects of human activities on animal welfare, revealing the urgency to mitigate impacts of rearing environments. Body tactile stimulation (TS), like massage therapy, has emerged as an enrichment method to counteract stress and anxiety in vertebrates. In the current study, we evaluated the effects of long-term TS on four-member groups of male Nile tilapia, a worldwide reared species whose socially aggressive behavior is an essential source of stress. We placed a rectangular PVC frame fitted with vertical plastic sticks sided with silicone bristles in the center of aquarium to enable the fish to receive body TS when passing through the bristles. A similar apparatus without bristles was used as the control. Fish subjected to TS for 21 days showed a gradual lowering of overt fights over time, but with no reduction in cortisol or androgen levels. Nevertheless, TS improved the specific growth rate, maintained balanced length/weight gain, and increased feed efficiency, probably owing to the lowered energy expenditure during fights. Thus, we show for the first time that long-term TS provided by a simple device can be used as a tool to improve the welfare and productive performance of territorial fish.
Multi-scale fusion for RGB-D indoor semantic segmentation
Authors: Jiang Shiyi , Xu Yang , Li Danyang , Fan Runze 
Published: November 2022

AbstractIn computer vision, convolution and pooling operations tend to lose high-frequency information, and the contour details will also disappear with the deepening of the network, especially in image semantic segmentation. For RGB-D image semantic segmentation, all the effective information of RGB and depth image can not be used effectively, while the form of wavelet transform can retain the low and high frequency information of the original image perfectly. In order to solve the information losing problems, we proposed an RGB-D indoor semantic segmentation network based on multi-scale fusion: designed a wavelet transform fusion module to retain contour details, a nonsubsampled contourlet transform to replace the pooling operation, and a multiple pyramid module to aggregate multi-scale information and context global information. The proposed method can retain the characteristics of multi-scale information with the help of wavelet transform, and make full use of the complementarity of high and low frequency information. As the depth of the convolutional neural network increases without losing the multi-frequency characteristics, the segmentation accuracy of image edge contour details is also improved. We evaluated our proposed efficient method on commonly used indoor datasets NYUv2 and SUNRGB-D, and the results showed that we achieved state-of-the-art performance and real-time inference.
Predicting visual difference maps for computer‐generated images by integrating human visual system model and deep learning
Authors: Li Ling , Chen Chunyi , Peng Jun , Zhang Ripei 
Published: November 2022

AbstractThe quality of images generated by computer graphics rendering algorithms is mainly affected by visible distortion at some pixel locations. Image quality assessment (IQA) metrics are commonly utilized to assess the quality of rendered images, but their results are a global difference value, which does not provide pixel‐wise differences to optimize the renderings. In contrast, visibility difference models including visual perception models and deep learning models can calculate pixel‐wise visibility difference between distorted images and reference images. However, they either are only applied to a single type of visible distortion or are seriously dependent on datasets. To this end, the authors propose a novel model, dubbed Human Visual Perception and Deep Learning Image Difference Metric (HPDL‐IDM), which combines the Human Visual System (HVS) model and deep learning. HPDL‐IDM primarily consists of two modules: (i) the visual perception feature calculation module, which calculates difference maps between various kinds of features extracted from the reference image and the distorted image according to the visual characteristics of human eyes and concatenates them, and (ii) the deep learning module, which utilizes a neural network of encoder–decoder structure to train on the LocvisVC and VisTexRes datasets whose input and output are these concatenated feature difference maps and the final image distortion visibility difference map respectively. Additionally, the authors pool the final difference map into a global difference value between 0 and 1 to apply their model to many image processing tasks related to Image quality metrics (IQMs). Experimental results show that HPDL‐IDM's generalization capacity and accuracy are improved by a large margin compared to other models.
A reweighted matrix completion algorithm for sparse inverse synthetic aperture radar imaging
Authors: Lv Mingjiu , Chen Wenfeng , Ma Jianchao , Yang Jun , Ma Xiaoyan , Cheng Qi 
Published: November 2022

AbstractSparse inverse synthetic aperture radar (ISAR) imaging can be generally achieved by compressed sensing (CS) methods because sparse sampling disables the approach of conventional range Doppler. However, the CS‐based methods have to convert the matrix into a vector when the random sampling is adopted, which results in huge memory usage and high computational complexity. Note that matrix completion (MC) is suitable for matrix operations, which can recover random sparse data directly based on the low‐rank property of the echo matrix. In order to improve the performance of the conventional MC approaches, a novel reweighted matrix completion method for sparse ISAR imaging is proposed in this paper. To avoid using the same singular value thresholding of the traditional MC method to achieve a low‐rank solution, the reweighted scheme for singular values is applied to restrain the rank. Furthermore, the weights of the current iteration are updated with their singular values obtained in the former iteration, rather than using a fixed value. Then, the alternating direction method of multipliers is utilised to alternatively optimise the proposed model, which has an improved computational efficiency. Once the full data is recovered, the ISAR image can be achieved via the conventional 2D inverse fast Fourier transform. Experimental results based on measured data validate the proposed approach that can result in improving imaging performance within several seconds, which is tens of times faster than some reported low‐rank‐based methods.
A Case Series of Stereotactic Biopsy of Brainstem Lesions through the Transfrontal Approach
Authors: Escobar-Vidarte Oscar Andrés , Griswold Dylan Paul , Orozco-Mera Javier , Mier-Garcia Juan Felipe , Peralta Pizza Fernando 
Published: November 2022

Abstract
Background and Importance Brainstem lesions may be unresectable or unapproachable. Regardless, the histopathological diagnosis is fundamental to determine the most appropriate treatment. We present our experience with transfrontal stereotactic biopsy technique for brainstem lesions as a safe and effective surgical route even when contralateral transhemispheric approach is required for preservation of eloquent tissue.
Clinical Presentation Twenty-five patients underwent surgery by transfrontal approach. Medical records were reviewed for establishing the number of patients who had postoperative histopathological diagnosis and postoperative complications. Twenty-four patients (18 adults and 7 children) had histopathological diagnosis. There were 18 astrocytomas documented, of which 12 were high grade and 6 low grade. The other diagnoses included viral encephalitis, post–renal transplant lymphoproliferative disorder, nonspecific chronic inflammation, Langerhans cell histiocytosis, and two metastases. No case was hindered by cerebrospinal fluid loss or ventricular entry. Complications included a case of mesencephalic hemorrhage with upper limb monoparesis and a case of a partially compromised third cranial nerve in another patient without associated bleeding.
Conclusion Stereotactic biopsy of brainstem lesions by transfrontal ipsilateral or transfrontal transhemispheric contralateral approaches is a safe and effective surgical approach in achieving a histopathological diagnosis in both pediatric and adult populations.
4 Organocatalytic Dynamic Kinetic Asymmetric Transformations
Authors: Córdova A. , Zhang K. , Deiana L. 
Published: November 2022

AbstractDynamic kinetic asymmetric transformations (DYKAT) are an important way of converting simple organic molecules into complex small molecules as single diastereo- and enantiomers. Herein we describe selected examples that are catalyzed by small organic molecules, which utilize activation mechanisms similar to enzymes for accomplishing the high stereoselectivity. The research area of DYKAT is growing and remarkable examples for producing important organic molecules and pharmaceuticals are demonstrated. In this context, organocatalysis will play an important role.
5 Chemoenzymatic Dynamic Kinetic Resolution of Amines
Authors: Adriaensen K. , De Vos D. 
Published: November 2022

AbstractEnantiopure amines are valuable intermediates in the fine-chemical industry but can be challenging to obtain. The combination of racemization techniques with enzymatic resolution into a chemoenzymatic dynamic kinetic resolution yields an invaluable and efficient method to achieve enantiopure amines. This chapter discusses the main differences between the recent dynamic kinetic resolution approaches, as well as their respective (dis)advantages, with a focus on the overall applicability to a wide substrate scope. Additionally, various industrially relevant examples cement the value of the chemoenzymatic dynamic kinetic resolution of amines.
Preaching to the Choir and Beyond
Authors: Zeng Ruoyan , Winner Ellen 
Published: November 2022

Abstract
Do narratives about suffering enhance empathy? Readers experience empathy for story characters, but does that
empathy spill over into the “real” world? We investigated whether a narrative in the form of a memoir by an undocumented immigrant
in the United States (compared to an expository account about undocumented immigrants) softens attitudes towards this group.
Across three studies, the narrative yielded greater attitude change in the direction of empathy than did the expository reading,
with this effect in some cases still visible one month later. We conclude that, compared to an expository account, a narrative
about the suffering of an individual in a marginalized group renders attitudes towards members of this group more positive for
those already sympathetic (Study 1) and for those initially unsympathetic (Studies 2 and 3). Study 3 demonstrated that this effect
generalized to attitudes about Black Americans despite no mention of race relations in the narrative.
Gene editing to improve drought tolerance
Authors: Núñez-Muñoz Leandro , Calderón-Pérez Berenice , Ruiz-Medrano Roberto , Xoconostle-Cázares Beatriz 
Published: November 2022

Abstract
Drought is by far one of the main agricultural problems affecting crop production worldwide, generating even more economic losses than all biotic factors combined. Humankind has pursued the improvement of crops to enhance plant productivity under water-limiting conditions since the dawn of agriculture, initially through conventional breeding and more recently, using tools such as transgenesis and gene editing. Among gene editing techniques, the clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated (Cas) system has seen a boom in plant breeding, thus, contributing to improve tolerance to biotic and abiotic stresses. This review provides a broad view of drought tolerance mechanisms. The molecular factors mediating this complex quantitative trait and biochemical mechanisms related to drought-tolerant phenotypes are described. Likewise, gene editing tools to confer drought tolerance, limitations, and further direction of gene editing technique with CRISPR/Cas are discussed. Considerations about epigenetics of drought tolerance are mentioned as a new emerging mechanism to understand memory to stress and its possible application to obtain stress-tolerant crops via genome editing.
Observation of charge density wave in layered hexagonal Cu1.89Te single crystal
Authors: Gao Wenshuai , Chen Zheng , Wei Wensen , Yan Chao , Wang Shasha , Tang Jin , Zhang Ranran , Cheng Lixun , Nan Pengfei , Wang Jie , Han Yuyan , Xi Chuanying , Ge Binghui , He Lin , Du Haifeng , Ning Wei , Zhu Xiangde , Tian Mingliang 
Published: November 2022

Abstract
We report comprehensive transport, electron microscopy and Raman spectroscopy studies on the transition-metal chalcogenides Cu1.89Te single crystals. The metallic Cu1.89Te displays successive metal-semiconductor transitions at low temperatures and almost ideal linear MR when magnetic field up to 33T. Through the electron diffraction patterns, the stable room temperature phase is identified as a 3×3×2 modulated superstructure based on Nowotny hexagonal structure. The superlattice spots of Transmission electron microscopy and Scanning tunneling microscopy clearly show the structural transitions from the room temperature Commensurate Ⅰ (C-Ⅰ) phase to the low temperature Commensurate Ⅱ (C-Ⅱ) phase. All the results can be understood in term of charge density wave (CDW) instability, yielding intuitive evidences for the CDW formations in Cu1.89Te. The additional Raman modes below room temperature further reveal that the zone-folded phonon modes may play an important role on the CDW transitions. Our research sheds light on the novel electron features of Cu1.89Te at low temperature, and may provide potential applications for future nano-devices.