bluuebunny/crossref_metadata_2025_split huggingface dataset:
Production and performance of commercial beef breeding females in northern Australia. 4. Factors influencing the occurrence of lactating cows becoming pregnant within 4 months of calving
Authors: McCosker K. D. , Perkins N. R. , Fordyce G. , O’Rourke P. K. , McGowan M. R. 
Published: March 2022

Context Sound reproductive efficiency is a key determinant for the overall productivity of a beef breeding business. For beef breeding herds to obtain high levels of reproductive productivity, breeding females need to efficiently become pregnant while lactating. Aims This study aimed to determine and quantify the major factors associated with lactating cows becoming pregnant within 4 months of calving (P4M) in commercial beef breeding herds of northern Australia. Methods A prospective epidemiological study was conducted using 78 commercial northern Australian beef breeding herds and involved 78 000 cattle that were monitored for 3–4 years. A multivariable model-building process was employed to scrutinise the resulting dataset to identify what herd-management practices, and nutritional, environmental and individual cow factors were major determinants of lactating cows becoming pregnant within 4 months of calving (P4M) and to estimate their magnitudes of effect. Key results Overall, 41.6% of cows per production year were successful for P4M. Country type was strongly associated with 65.4%, 57.5%, 61.8% and 16.4% P4M for the Southern Forest, Central Forest, Northern Downs, and Northern Forest respectively. Between-year variability ranged between 3.3 and 11.7 percentage points. Cows calving in December–January (61%) had a substantially higher occurrence of P4M than did cows calving between July and September (15%). The difference in P4M when comparing availability of wet-season pasture protein and phosphorus was 12.7 and 20.3 percentage points respectively. Modelling of the impact of group seroprevalence and management group prevalence of recent infection with several infectious diseases was estimated, with a large negative association between group bovine viral diarrhoea seroprevalence and P4M suggested. Conclusions This study further demonstrated the substantial impact that environment, herd management practices, nutrition and disease factors can have on the reproductive performance of females. Implications To optimise the performance of females (through increasing the occurrence of cows contributing calves in consecutive years) under commercial conditions in northern Australia, herd managers should focus on maximising the proportion of cows within a herd calving at the desired time of the year, ensuring that any nutritional deficiencies and herd health issues are managed, and that cows are managed such that they are of good body condition score at the time of calving.
Evolutionary dynamics, evolutionary forces, and robustness: A nonequilibrium statistical mechanics perspective
Authors: Rao Riccardo , Leibler Stanislas 
Published: March 2022

SignificanceEvolution through natural selection is an overwhelmingly complex process, and it is not surprising that theoretical approaches are strongly simplifying it. For instance, population genetics considers mainly dynamics of gene allele frequencies. Here, we develop a complementary approach to evolutionary dynamics based on three elements—organism reproduction, variations, and selection—that are essential for any evolutionary theory. By considering such general dynamics as a stochastic thermodynamic process, we clarify the nature and action of the evolutionary forces. We show that some of the forces cannot be described solely in terms of fitness landscapes. We also find that one force contribution can make organism reproduction insensitive (robust) to variations.
Behavioral responses to predatory sounds predict sensitivity of cetaceans to anthropogenic noise within a soundscape of fear
Authors: Miller Patrick J. O. , Isojunno Saana , Siegal Eilidh , Lam Frans-Peter A. , Kvadsheim Petter H. , Curé Charlotte 
Published: March 2022

Significance
Acoustic signals travel efficiently in the marine environment, allowing soniferous predators and prey to eavesdrop on each other. Our results with four cetacean species indicate that they use acoustic information to assess predation risk and have evolved mechanisms to reduce predation risk by ceasing foraging. Species that more readily gave up foraging in response to predatory sounds of killer whales also decreased foraging more during 1- to 4-kHz sonar exposures, indicating that species exhibiting costly antipredator responses also have stronger behavioral reactions to anthropogenic noise. This advance in our understanding of the drivers of disturbance helps us to predict what species and habitats are likely to be most severely impacted by underwater noise pollution in oceans undergoing increasing anthropogenic activities.
Enhancement of speech-in-noise comprehension through vibrotactile stimulation at the syllabic rate
Authors: Guilleminot Pierre , Reichenbach Tobias 
Published: March 2022

SignificanceSyllables are important building blocks of speech. They occur at a rate between 4 and 8 Hz, corresponding to the theta frequency range of neural activity in the cerebral cortex. When listening to speech, the theta activity becomes aligned to the syllabic rhythm, presumably aiding in parsing a speech signal into distinct syllables. However, this neural activity cannot only be influenced by sound, but also by somatosensory information. Here, we show that the presentation of vibrotactile signals at the syllabic rate can enhance the comprehension of speech in background noise. We further provide evidence that this multisensory enhancement of speech comprehension reflects the multisensory integration of auditory and tactile information in the auditory cortex.
Spherical nucleic acids as an infectious disease vaccine platform
Authors: Teplensky Michelle H. , Distler Max E. , Kusmierz Caroline D. , Evangelopoulos Michael , Gula Haley , Elli Derek , Tomatsidou Anastasia , Nicolaescu Vlad , Gelarden Ian , Yeldandi Anjana , Batlle Daniel , Missiakas Dominique , Mirkin Chad A. 
Published: March 2022

Significance
Using SARS-CoV-2 as a relevant case study for infectious disease, we investigate the structure–function relationships that dictate antiviral spherical nucleic acid (SNA) vaccine efficacy. We show that the SNA architecture can be rapidly employed to target COVID-19 through incorporation of the receptor-binding domain, and that the resulting vaccine potently activates human cells in vitro and mice in vivo. Furthermore, when challenged with a lethal viral infection, only mice treated with the SNA vaccine survived. Taken together, this work underscores the importance of rational vaccine design for infectious disease to yield vaccines that elicit more potent immune responses to effectively fight disease.
Massive perturbations to atmospheric sulfur in the aftermath of the Chicxulub impact
Authors: Junium Christopher K. , Zerkle Aubrey L. , Witts James D. , Ivany Linda C. , Yancey Thomas E. , Liu Chengjie , Claire Mark W. 
Published: March 2022

Significance
Sulfur isotopes confirm a key role for atmospheric sulfur gases in climatic cooling, mass extinction, and the demise of dinosaurs and other global biota after the Chicxulub bolide impact at the Cretaceous–Paleogene boundary. The sulfur isotope anomalies are confined to beds containing ejecta and, in the immediately overlying sediments, are temporally unrelated to known episodes of volcanism that also bracket this event, further addressing the controversial role of the Deccan Traps in the extinction.
Functional enzyme–polymer complexes
Authors: Waltmann Curt , Mills Carolyn E. , Wang Jeremy , Qiao Baofu , Torkelson John M. , Tullman-Ercek Danielle , Olvera de la Cruz Monica 
Published: March 2022

Significance
The use of biological enzyme catalysts could have huge ramifications for chemical industries. However, these enzymes are often inactive in nonbiological conditions, such as high temperatures, present in industrial settings. Here, we show that the enzyme PETase (polyethylene terephthalate [PET]), with potential application in plastic recycling, is stabilized at elevated temperature through complexation with random copolymers. We demonstrate this through simulations and experiments on different types of substrates. Our simulations also provide strategies for designing more enzymatically active complexes by altering polymer composition and enzyme charge distribution.
Biochemical and structural characterization of an aromatic ring–hydroxylating dioxygenase for terephthalic acid catabolism
Authors: Kincannon William M. , Zahn Michael , Clare Rita , Lusty Beech Jessica , Romberg Ari , Larson James , Bothner Brian , Beckham Gregg T. , McGeehan John E. , DuBois Jennifer L. 
Published: March 2022

Significance
More than 400 million tons of plastic waste is produced each year, the overwhelming majority of which ends up in landfills. Bioconversion strategies aimed at plastics have emerged as important components of enabling a circular economy for synthetic plastics, especially those that exhibit chemically similar linkages to those found in nature, such as polyesters. The enzyme system described in this work is essential for mineralization of the xenobiotic components of poly(ethylene terephthalate) (PET) in the biosphere. Our description of its structure and substrate preferences lays the groundwork for in vivo or ex vivo engineering of this system for PET upcycling.
Characterisation of Sn–3.5Ag solder/Cu joint under various reflow conditions
Authors: Georgy K. , Tikale Sanjay , Prabhu K. Narayan 
Published: March 2022

The effect of reflow time and reflow temperatures on wettability and bond shear strength of Sn–3.5Ag solder alloy on a Cu substrate is assessed for reflow times of 10 s, 100 s, 300 s, 500 s and reflow temperatures of 250 °C, 270 °C, 290 °C, 320 °C. The wetting regime was found to have capillary, gravity, and viscous regimes. A microstructural study using a scanning electron microscope (SEM) with energydispersive spectroscopy revealed the presence of intermetallic compounds at the interface between the substrate and solder droplet. The bond strength of the solder joint is maximum at a reflow temperature of 250  °C and a reflow time of 10 s. Bond shear strength decreased with an increase in reflow time from 10 s to 500 s. The effect of different cooling conditions on the solder–substrate joint is also investigated.
Integrable nonlocal derivative nonlinear Schrödinger equations
Authors: Ablowitz Mark J , Luo Xu-Dan , Musslimani Ziad H , Zhu Yi 
Published: March 2022

Abstract
Integrable standard and nonlocal derivative nonlinear Schrödinger equations are investigated. The direct and inverse scattering are constructed for these equations; included are both the Riemann–Hilbert and Gel’fand–Levitan–Marchenko approaches and soliton solutions. As a typical application, it is shown how these derivative NLS equations can be obtained as asymptotic limits from a nonlinear Klein–Gordon equation.
Adaptively sketched Bregman projection methods for linear systems
Authors: Yuan Zi-Yang , Zhang Lu , Wang Hongxia , Zhang Hui 
Published: March 2022

Abstract
The sketch-and-project, as a general archetypal algorithm for solving linear systems, unifies a variety of randomized iterative methods such as the randomized Kaczmarz and randomized coordinate descent. However, since it aims to find a least-norm solution from a linear system, the randomized sparse Kaczmarz can not be included. This motivates us to propose a more general framework, called sketched Bregman projection (SBP) method, in which we are able to find solutions with certain structures from linear systems. To generalize the concept of adaptive sampling to the SBP method, we show how the progress, measured by Bregman distance, of single step depends directly on a sketched loss function. Theoretically, we provide detailed global convergence results for the SBP method with different adaptive sampling rules. At last, for the (sparse) Kaczmarz methods, a group of numerical simulations are tested, with which we verify that the methods utilizing sampling Kaczmarz–Motzkin rule demands the fewest computational costs to achieve a given error bound comparing to the corresponding methods with other sampling rules.
Maximum reweighted-kurtosis deconvolution: a fully blind and adaptive method for restoration of gear fault impulse trains
Authors: Wu Lei , Wang Jiaxu , Zhang Xin , Liu Zhiwen 
Published: March 2022

Abstract
Deconvolution based on vibration signals has been proven to be an effective tool in gear fault diagnosis. However, for many common methods, precisely restoring the fault impulse train is still a challenging task due to the great dependence on prior knowledge and the empirical determination of filter parameters. In this paper, a fully blind and adaptive method termed maximum reweighted-kurtosis deconvolution (MRKD) is proposed. A new deconvolution criterion, i.e., reweighted-kurtosis, is defined. This criterion possesses great robustness to impulse interferencesand thus has great potential to solve the problem of previous kurtosis-based methods in which a single dominant impulse is deconvolved instead of the impulse train induced by a localized fault. Furthermore, a parameter-adaptive strategy is developed to adaptively determine the appropriate filter parameters. As such, the proposed method does not require any prior knowledge of the target fault impulse train and addresses the critical issue of many common methods specifying filter parameters empirically. The proposed method is validated through simulated and real vibration signals. Comparison with the most popular deconvolution methods indicates that MRKD outperforms other methods for the restoration of a gear fault impulse train.
Constructing van der Waals heterostructures by dry-transfer assembly for novel optoelectronic device
Authors: Li Huihan , Xiong Xiaolu , Hui Fei , Yang Dongliang , Jiang Jinbao , Feng Wanxiang , Han Junfeng , Duan Junxi , Wang Zhongrui , Sun Linfeng 
Published: March 2022

Abstract
Since the first successful exfoliation of graphene, the superior physical and chemical properties of two-dimensional (2D) materials, such as atomic thickness, strong in-plane bonding energy and weak inter-layer van der Waals (vdW) force have attracted wide attention. Meanwhile, there is a surge of interest in novel physics which is absent in bulk materials. Thus, vertical stacking of 2D materials could be critical to discover such physics and develop novel optoelectronic applications. Although vdW heterostructures have been grown by chemical vapor deposition, the available choices of materials for stacking is limited and the device yield is yet to be improved. Another approach to build vdW heterostructure relies on wet/dry transfer techniques like stacking Lego bricks. Although previous reviews have surveyed various wet transfer techniques, novel dry transfer techniques have been recently been demonstrated, featuring clean and sharp interfaces, which also gets rid of contamination, wrinkles, bubbles formed during wet transfer. This review summarizes the optimized dry transfer methods, which paves the way towards high-quality 2D material heterostructures with optimized interfaces. Such transfer techniques also lead to new physical phenomena while enable novel optoelectronic applications on artificial vdW heterostructures, which are discussed in the last part of this review.
Design of polysaccharidic Aloe vera gel incorporated PVA/tetracycline electrospun cell culture scaffolds for biomedical applications
Authors: Allafchian Alireza , Fathi Mohammad , Jalali Seyed Amir Hossein 
Published: March 2022

Abstract
In this study, hybrid nanofibrous 3D scaffolds containing Aloe vera (AV), polyvinyl alcohol (PVA) and tetracycline hydrochloride (TCH) are fabricated by electrospinning for cell culture applications. The role of polysaccharides present in AV gel is found to enhance the biocompatibility of the nanofibrous scaffolds. Different combinations of the polymers were selected to produce homogenous nanofibers with favorable mean fiber diameter and tensile strength. The surface morphology of the products was studied by SEM and it is found that the mean fiber diameter is decreased to about 188 nm upon addition of the AV component. The electrospun scaffolds were investigated by FT-IR spectroscopy to reveal the chemical structure of the samples and their crystallinity was studied by XRD. The hydrophilicity of the scaffolds was tested by optical contact angle measurements and their mechanical strength was examined by tensile strength tests. It is found that PVA is the main component contributing the mechanical stability of the scaffold structure. The fabricated scaffolds presented a more pronounced inhibitory effect against Gram-positive bacterial strains of S. aureus and B. cereus. Cell culture experiments using fibroblast L929 murine cells reveals that the AV/PVA/TCH scaffolds are promising for cell growth and the cells are capable of achieving a proper cell adhesion and proliferation. The cell viability experiment by MTT assay exhibits the contributing role of AV gel to L929 cell viability on the AV/PVA/TCH scaffolds.
Cooperative effect of bimetallic MOF-derived CoNi(OH)2@NiCo2S4 nanocomposite electrocatalysts with boosted oxygen evolution activity
Authors: Zheng Lingxia , Wang Shibin , Wang Yongzhi , Zhao Zhefei , Yang Pengju , Song Jianlan , Shi Xiaowei , Zheng Huajun 
Published: March 2022

Abstract
Highly efficient and inexpensive electrocatalysts for oxygen evolution reaction (OER) are extensively studied for water splitting. Herein, a unique bimetallic nanocomposite CoNi(OH)2@NiCo2S4 nanosheet arrays derived from metal-organic-frameworks (MOFs, CoNi-ZIF) is simply fabricated on Ni foam, endowing large specific surface area and outstanding electrical conductivity. Compared with their single-metallic counterparts, the bimetallic composite displays dramatically low overpotential and small Tafel slope as well as outstanding catalytic stability. The overpoptential at 20 mA cm−2 for CoNi(OH)2@NiCo2S4 is only 230 mV in comparison with Ni(OH)2@Ni3S2 (266 mV), Co(OH)2@Co3S4 (294 mV) and RuO2 (η = 302 mV). First-principle calculations based on density functional theory (DFT) are carried out and reveal that the introduction of Ni in Co(OH)2 helps lowered the energy difference of ΔG
OOH*–ΔG
O*, and thereby boosting the OER reactivity. This study provides an effective approach for the rational construction of low-cost metal hybrids.
Patient-specific deep learning model to enhance 4D-CBCT image for radiomics analysis
Authors: Zhang Zeyu , Huang Mi , Jiang Zhuoran , Chang Yushi , Lu Ke , Yin Fang-Fang , Tran Phuoc , Wu Dapeng , Beltran Chris , Ren Lei 
Published: March 2022

Abstract

Objective. 4D-CBCT provides phase-resolved images valuable for radiomics analysis for outcome prediction throughout treatment courses. However, 4D-CBCT suffers from streak artifacts caused by under-sampling, which severely degrades the accuracy of radiomic features. Previously we developed group-patient-trained deep learning methods to enhance the 4D-CBCT quality for radiomics analysis, which was not optimized for individual patients. In this study, a patient-specific model was developed to further improve the accuracy of 4D-CBCT based radiomics analysis for individual patients. Approach. This patient-specific model was trained with intra-patient data. Specifically, patient planning 4D-CT was augmented through image translation, rotation, and deformation to generate 305 CT volumes from 10 volumes to simulate possible patient positions during the onboard image acquisition. 72 projections were simulated from 4D-CT for each phase and were used to reconstruct 4D-CBCT using FDK back-projection algorithm. The patient-specific model was trained using these 305 paired sets of patient-specific 4D-CT and 4D-CBCT data to enhance the 4D-CBCT image to match with 4D-CT images as ground truth. For model testing, 4D-CBCT were simulated from a separate set of 4D-CT scan images acquired from the same patient and were then enhanced by this patient-specific model. Radiomics features were then extracted from the testing 4D-CT, 4D-CBCT, and enhanced 4D-CBCT image sets for comparison. The patient-specific model was tested using 4 lung-SBRT patients’ data and compared with the performance of the group-based model. The impact of model dimensionality, region of interest (ROI) selection, and loss function on the model accuracy was also investigated. Main results. Compared with a group-based model, the patient-specific training model further improved the accuracy of radiomic features, especially for features with large errors in the group-based model. For example, the 3D whole-body and ROI loss-based patient-specific model reduces the errors of the first-order median feature by 83.67%, the wavelet LLL feature maximum by 91.98%, and the wavelet HLL skewness feature by 15.0% on average for the four patients tested. In addition, the patient-specific models with different dimensionality (2D versus 3D) or loss functions (L1 versus L1 + VGG + GAN) achieved comparable results for improving the radiomics accuracy. Using whole-body or whole-body+ROI L1 loss for the model achieved better results than using the ROI L1 loss alone as the loss function. Significance. This study demonstrated that the patient-specific model is more effective than the group-based model on improving the accuracy of the 4D-CBCT radiomic features analysis, which could potentially improve the precision for outcome prediction in radiotherapy.
Boosting transducer matrix sensitivity for 3D large field ultrasound localization microscopy using a multi-lens diffracting layer: a simulation study
Authors: Favre Hugues , Pernot Mathieu , Tanter Mickael , Papadacci Clément 
Published: March 2022

Abstract
Mapping blood microflows of the whole brain is crucial for early diagnosis of cerebral diseases. Ultrasound localization microscopy (ULM) was recently applied to map and quantify blood microflows in 2D in the brain of adult patients down to the micron scale. Whole brain 3D clinical ULM remains challenging due to the transcranial energy loss which significantly reduces the imaging sensitivity. Large aperture probes with a large surface can increase both resolution and sensitivity. However, a large active surface implies thousands of acoustic elements, with limited clinical translation. In this study, we investigate via simulations a new high-sensitive 3D imaging approach based on large diverging elements, combined with an adapted beamforming with corrected delay laws, to increase sensitivity. First, pressure fields from single elements with different sizes and shapes were simulated. High directivity was measured for curved element while maintaining high transmit pressure. Matrix arrays of 256 elements with a dimension of 10 × 10 cm with small (λ/2), large (4λ), and curved elements (4λ) were compared through point spread functions analysis. A large synthetic microvessel phantom filled with 100 microbubbles per frame was imaged using the matrix arrays in a transcranial configuration. 93% of the bubbles were detected with the proposed approach demonstrating that the multi-lens diffracting layer has a strong potential to enable 3D ULM over a large field of view through the bones.