bluuebunny/crossref_metadata_2025_split huggingface dataset:
Eight-element liquid crystal based 32 GHz phased array antenna with improved time response
Authors: Nobles Jason E. , Smiley K. , Bueno Baques D. , Economou E. , Herman Jakub , Harward Ian , Glushchenko Anatoliy (Tolya) , Camley Robert E , Celinski Z 
Published: November 2021

Abstract
Phased array radar systems are used for a wide variety of applications including the precise tracking of airborne craft for air traffic control and providing accurate atmospheric condition information important in weather forecasting. Reducing the cost and size of these radar systems will open new fields to the use of this technology. Using phase control implemented through liquid crystal materials we have created a compact, phased array radar system operating in the microwave range. We report on the construction and testing of a linear, eight element phased array antenna system operating at 32 GHz with element phase controlled by a dual frequency nematic liquid crystal media used as a tunable dielectric. The system was designed using CST Design Studios and Ansys HFSS software. Dual frequency liquid crystals are used to improve beam steering response times. We demonstrate 42 millisecond beam switching times, defined as the time to change the beam focus from one point to another point, controllable beam formation, and beam steering profiles consistent with analytical results and simulation models. The device footprint is a square with sides 9.5 cm long and a thickness less than 2.5 mm. Such a module is easily stackable to create an 8 × 8 phased array system. Our design incorporates a modular construction using PCB for the antennas and input circuitry and a liquid crystal phase control cell with microwave glass substrates. This design simplifies design, construction, and testing as compared to on-glass designs. The device shows an improvement in point-to-point scanning speeds by a factor of 3 as compared to similar liquid crystal based devices and provides continuously variable tuning. Such a device can be used in a system for reduced visibility, directional range finding suitable for automobile collision avoidance systems and rotary wing aircraft landing aids.
316L WAAM and pressure machining influence
Authors: Kan Xinfeng , Yang Dengcui , Zhao Zhengzhi , Sun Jiquan 
Published: November 2021

ABSTRACT
Wire arc additive manufacture (WAAM) technology has a good development prospect, and can be used to manufacture large metal components with complex shapes in combination with traditional machining equipment. This paper adjusts the parameters from the perspective of heat input and arc control. It is found that the stacking quality of 316L stainless steel is the best when the arc voltage is 40V and the arc current is 360A. It is proposed to obtain the flat layers by pressure machining after every layer is stacked, which can create favorable conditions for manufacturing large-size components. And through the hot rolling experiment, it is proved that pressure machining can improve the density and uniformity of the microstructure, and thus enhance the comprehensive mechanical properties of components built by WAAM.
Statistically-informed deep learning for gravitational wave parameter estimation
Authors: Shen Hongyu , Huerta E A , O’Shea Eamonn , Kumar Prayush , Zhao Zhizhen 
Published: November 2021

AbstractWe introduce deep learning models to estimate the masses of the binary components of black hole mergers,(m1,m2), and three astrophysical properties of the post-merger compact remnant, namely, the final spin,af, and the frequency and damping time of the ringdown oscillations of the fundamentalℓ=m=2bar mode,(ωR,ωI). Our neural networks combine a modifiedWaveNetarchitecture with contrastive learning and normalizing flow. We validate these models against a Gaussian conjugate prior family whose posterior distribution is described by a closed analytical expression. Upon confirming that our models produce statistically consistent results, we used them to estimate the astrophysical parameters(m1,m2,af,ωR,ωI)of five binary black holes:GW150914,GW170104,GW170814,GW190521andGW190630. We usePyCBC Inferenceto directly compare traditional Bayesian methodologies for parameter estimation with our deep learning based posterior distributions. Our results show that our neural network models predict posterior distributions that encode physical correlations, and that our data-driven median results and 90% confidence intervals are similar to those produced with gravitational wave Bayesian analyses. This methodology requires a single V100NVIDIAGPU to produce median values and posterior distributions within two milliseconds for each event. This neural network, and a tutorial for its use, are available at theData and Learning Hub for Science.
LR-GNN: a graph neural network based on link representation for predicting molecular associations
Authors: Kang Chuanze , Zhang Han , Liu Zhuo , Huang Shenwei , Yin Yanbin 
Published: November 2021

AbstractIn biomedical networks, molecular associations are important to understand biological processes and functions. Many computational methods, such as link prediction methods based on graph neural networks (GNNs), have been successfully applied in discovering molecular relationships with biological significance. However, it remains a challenge to explore a method that relies on representation learning of links for accurately predicting molecular associations. In this paper, we present a novel GNN based on link representation (LR-GNN) to identify potential molecular associations. LR-GNN applies a graph convolutional network (GCN)-encoder to obtain node embedding. To represent associations between molecules, we design a propagation rule that captures the node embedding of each GCN-encoder layer to construct the LR. Furthermore, the LRs of all layers are fused in output by a designed layer-wise fusing rule, which enables LR-GNN to output more accurate results. Experiments on four biomedical network data, including lncRNA-disease association, miRNA-disease association, protein–protein interaction and drug–drug interaction, show that LR-GNN outperforms state-of-the-art methods and achieves robust performance. Case studies are also presented on two datasets to verify the ability to predict unknown associations. Finally, we validate the effectiveness of the LR by visualization.
Efficient Parameter Server Placement for Distributed Deep Learning in Edge Computing
Authors: Wu Yalan , Yan Jiaquan , Chen Long , Wu Jigang , Li Yidong 
Published: November 2021

AbstractParameter servers (PSs) placement is one of the most important factors for global model training on distributed deep learning. This paper formulates a novel problem for placement strategy of PSs in the dynamic available storage capacity, with the objective of minimizing the training time of the distributed deep learning under the constraints of storage capacity and the number of local PSs. Then, we provide the proof for the NP-hardness of the proposed problem. The whole training epochs are divided into two parts, i.e. the first epoch and the other epochs. For the first epoch, an approximation algorithm and a rounding algorithm are proposed in this paper, to solve the proposed problem. For the other epochs, an adjustment algorithm is proposed, by continuously adjusting the decisions for placement strategy of PSs to decrease the training time of the global model. Simulation results show that the proposed approximation algorithm and rounding algorithm perform better than existing works for all cases, in terms of the training time of global model. Meanwhile, the training time of global model for the proposed approximation algorithm is very close to that for optimal solution generated by the brute-force approach for all cases. Besides, the integrated algorithm outperforms the existing works when the available storage capacity varies during the training.
Attaining the Exponent 5/4 for the Sum-Product Problem in Finite Fields
Authors: Mohammadi Ali , Stevens Sophie 
Published: November 2021

AbstractWe improve the exponent in the finite field sum-product problem from $11/9$ to $5/4$, improving the results of Rudnev et al. [16]. That is, we show that if $A\subset \mathbb {F}_p$ has cardinality $|A|\ll p^{1/2}$, then $ \max \{|A\pm A|,|AA|\} \gtrsim |A|^\frac 54 $ and $ \max \{|A\pm A|,|A/A|\}\gtrsim |A|^\frac 54 $.
BSAC Vanguard Series: Are we finally finding our voice on antimicrobial resistance?
Authors: Davies Dame Sally 
Published: November 2021

Abstract
Modern medicine is a miracle, as recently demonstrated by the successful delivery of COVID-19 vaccines. However, the sad reality is that antimicrobial resistance (AMR) is simultaneously undermining our progress. We need to take urgent action to prevent devastating effects on lives, poverty and global development. Late last year, the heads of the World Health Organization, Organisation for Animal Health and the Food and Agriculture Organization came together to launch a new group of global leaders and experts from right across the world. I’m honoured to be a member of their Global Leaders Group. Many feel powerless in the face of AMR, but the truth is there are many things we can do. I outline some here, from simple but very effective steps such as proper handwashing, right through to putting consumer pressure on food suppliers to reduce reliance on antibiotics in the food supply chain. Change won’t happen overnight, but we can and must make a difference.
Analysis of Genetic Diversity in the American Standardbred Horse Utilizing Short Tandem Repeats and Single Nucleotide Polymorphisms
Authors: Esdaile Elizabeth , Avila Felipe , Bellone Rebecca R 
Published: November 2021

AbstractAmerican Standardbreds were developed as a harness racing horse breed. The United States Trotting Association closed the studbook in 1973 and implemented a book size cap in 2009. This study aimed to investigate genetic diversity in the American Standardbred after the studbook cap was introduced using short tandem repeats (STRs) and single-nucleotide polymorphisms (SNPs). Sixteen STRs from horses foaled from 2010 to 2015 and their sires and dams (n = 50 621) were utilized to examine allelic richness (Ar), expected heterozygosity (HE), observed heterozygosity (HO), unbiased heterozygosity (HU), inbreeding coefficient (FIS), and fixation index (FST). These analyses found that trotting and pacing sires were less genetically diverse than dams (HEPBonferroni = 0.029 and 6.3 × 10−5, respectively) and their offspring (ArPBonferroni = 0.034 and 6.9 × 10-6, respectively), and pacing offspring were significantly less diverse than their dams (HEPBonferroni = 2 × 10-3). Inbreeding coefficients for trotters (FIS = −0.014) and pacers (FIS = −0.012) suggest that breeding practices have maintained diversity. Moderate levels of genetic differentiation (0.066 &lt; FST &lt; 0.11) were found between pacing and trotting groups. Additionally, 10 of the most prolific trotting sires and their male offspring (n = 84) were genotyped on the 670K Axiom Equine HD Array. HO values higher than HE (P &lt; 0.001), low inbreeding coefficients (mean F = −0.064), and mean FROH = 21% indicate relatively high levels of diversity in this cohort, further supporting the STR data. However, in contrast, HO values were higher for trotting sires (0.41) than their offspring (0.36). This observation warrants further monitoring of diversity over time. These data provide an updated foundation of diversity indices for further, long-term analysis in the breed.
Electoral Sentencing Cycles
Authors: Abrams David , Galbiati Roberto , Henry Emeric , Philippe Arnaud 
Published: November 2021

Abstract
We add to our understanding of the optimal method of judicial selection by exploiting an unusual feature in North Carolina: judges rotate location every 6 months. This allows us to identify the existence and source of sentencing variation over the electoral cycle. We show that when elections approach, felony sentences rise. This increase is found exclusively when judges are sentencing in their district of election, and only when elections are contested. When judges hear cases outside their home district, sentences do not significantly vary over the electoral cycle. Our results show that electoral sentencing cycles can be explained by strategic sentencing by judges in an attempt to please voters. The unique setting allows us to reject alternative behavioral or contextual explanations for the rise in sentences as elections approach. (JEL K42).
Flow, form, and force: methods and frameworks for field studies of macroalgal biomechanics
Authors: Burnett Nicholas P , Gaylord Brian 
Published: November 2021

Abstract
Macroalgae are ecologically important organisms that often inhabit locations with physically challenging water motion. The biomechanical traits that permit their survival in these conditions have been of interest to biologists and engineers alike, but logistical and technical challenges of conducting investigations in macroalgal habitats have often prevented optimal study of these traits. Here, we review field methods for quantifying three major components of macroalgal biomechanics in moving water: fluid flow, macroalgal form, and hydrodynamic force. The implementation of some methodologies is limited due to the current state and accessibility of technology, but many of these limitations can be remedied by custom-built devices, borrowing techniques from other systems, or shifting lab-based approaches to the field. We also describe several frameworks for integrating flow, form, and force data that can facilitate comparisons of macroalgal biomechanics in field settings with predictions from theory and lab-based experiments, or comparisons between flow conditions, habitats, and species. These methods and frameworks, when used on scales that are relevant to the examined processes, can reveal mechanistic information about the functional traits that permit macroalgae to withstand physically challenging water motion in their habitats, using the actual fluid flows, macroalgal forms, and physical forces that occur in nature.
Transcriptional Analysis in the Arabidopsis Roots Reveals New Regulators that Linkrac-GR24 Treatment with Changes in Flavonol Accumulation, Root Hair Elongation and Lateral Root Density
Authors: Struk Sylwia , Braem Lukas , Matthys Cedrick , Walton Alan , Vangheluwe Nick , Van Praet Stan , Jiang Lingxiang , Baster Pawel , De Cuyper Carolien , Boyer François-Didier , Stes Elisabeth , Beeckman Tom , Friml Jiří , Gevaert Kris , Goormachtig Sofie 
Published: November 2021

AbstractThe synthetic strigolactone (SL) analog, rac-GR24, has been instrumental in studying the role of SLs as well as karrikins because it activates the receptors DWARF14 (D14) and KARRIKIN INSENSITIVE 2 (KAI2) of their signaling pathways, respectively. Treatment with rac-GR24 modifies the root architecture at different levels, such as decreasing the lateral root density (LRD), while promoting root hair elongation or flavonol accumulation. Previously, we have shown that the flavonol biosynthesis is transcriptionally activated in the root by rac-GR24 treatment, but, thus far, the molecular players involved in that response have remained unknown. To get an in-depth insight into the changes that occur after the compound is perceived by the roots, we compared the root transcriptomes of the wild type and the more axillary growth2 (max2) mutant, affected in both SL and karrikin signaling pathways, with and without rac-GR24 treatment. Quantitative reverse transcription (qRT)-PCR, reporter line analysis and mutant phenotyping indicated that the flavonol response and the root hair elongation are controlled by the ELONGATED HYPOCOTYL 5 (HY5) and MYB12 transcription factors, but HY5, in contrast to MYB12, affects the LRD as well. Furthermore, we identified the transcription factors TARGET OF MONOPTEROS 5 (TMO5) and TMO5 LIKE1 as negative and the Mediator complex as positive regulators of the rac-GR24 effect on LRD. Altogether, hereby, we get closer toward understanding the molecular mechanisms that underlay the rac-GR24 responses in the root.
Generation of a nanobody against HER2 tyrosine kinase using phage display library screening for HER2-positive breast cancer therapy development
Authors: Lamtha Thomanai , Tabtimmai Lueacha , Bangphoomi Kunan , Kiriwan Duangnapa , Malik Aijaz A , Chaicumpa Wanpen , van Bergen en Henegouwen Paul M P , Choowongkomon Kiattawee 
Published: November 2021

Abstract
Human epidermal growth factor receptor 2 (HER2) protein overexpression is found in ~30% of invasive breast carcinomas and in a high proportion of noninvasive ductal carcinomas in situ. Targeted cancer therapy is based on monoclonal antibodies and kinase inhibitors and reflects a new era of cancer therapy. However, delivery to tumor cells in vivo is hampered by the large size (150 kDa) of conventional antibodies. Furthermore, there are many disadvantages with the current anti-HER2 drug, including drug resistance and adverse effects. Nanobodies (15 kDa), single-domain antibody (sdAb) fragments, can overcome these limitations. This study produced the recombinant sdAb against the HER2-tyrosine kinase (HER2-TK) domain using phage display technology. Three specific anti-HER2-TK sdAbs were selected for further characterization. Hallmark VHH residue identification and amino acid sequence analysis revealed that clone numbers 4 and 22 were VH antibodies, whereas clone number 17 was a VH H antibody (nanobody). The half-maximal inhibitory concentration of VHH17 exhibited significantly greater HER2 kinase-inhibition activity than the other clones. Consistent with these results, several charges and polar residues of the HER2-TK activation loop that were predicted based on mimotope analysis also appeared in the docking result and interacted via the CDR1, CDR2 and CDR3 loops of VHH17. Furthermore, the cell-penetrable VHH17 (R9 VHH17) showed cell-penetrability and significantly decreased HER2-positive cancer cell viability. Thus, the VH H17 could be developed as an effective therapeutic agent to treat HER2-positive breast cancer.
Hyperconnectivity and altered dynamic interactions of a nucleus accumbens network in post-stroke depression
Authors: Oestreich Lena KL , Wright Paul , O’Sullivan Michael J 
Published: November 2021

ABSTRACTObjectivesPost-stroke depression (PSD) is a common complication after stroke. To date, no consistent locus of injury is associated with this complication. Here, we probed network dynamics in four functional circuits tightly linked to major depressive disorder and investigated structural alterations within these networks in PSD.MethodsForty-four participants with recent stroke and 16 healthy volunteers were imaged with 3T structural, diffusion and resting-state functional MRI and completed the Geriatric Depression Scale (GDS). Associations between GDS and functional connectivity were investigated within networks seeded from nucleus accumbens (NAc), amygdala and dorsolateral prefrontal cortex. In addition, the default mode network (DMN) was identified by connectivity with medial prefrontal cortex (mPFC) and posterior cingulate cortex (PCC). Circuits that exhibited altered activity associated with GDS were further investigated by extracting within-network volumetric and microstructural measures from structural images.ResultsFunctional connectivity within the NAc-seeded network and DMN correlated positively with depressive symptoms. Normal anticorrelations between these two networks were absent in patients with PSD. PCC grey matter volume as well as microstructural measures in mPFC and the medial forebrain bundle, a major projection pathway interconnecting the NAc-seeded network and links to mPFC, were associated with GDS scores.ConclusionsDepression after stroke is marked by reduced mutual inhibition between functional circuits involving NAc and DMN as well as volumetric and microstructural changes within these networks. Aberrant network dynamics present in patients with PSD are therefore likely to be influenced by secondary, pervasive alterations in grey and white matter, remote from the site of injury.
Variance-quantitative trait loci enable systematic discovery of gene-environment interactions for cardiometabolic serum biomarkers
Authors: Westerman Kenneth E. , Majarian Timothy D. , Giulianini Franco , Jang Dong-Keun , Florez Jose C. , Chen Han , Chasman Daniel I. , Udler Miriam S. , Manning Alisa K. , Cole Joanne B. 
Published: November 2021

ABSTRACTGene-environment interactions (GEIs) represent the modification of genetic effects by environmental exposures and are critical for understanding disease and informing personalized medicine. GEIs often induce differential phenotypic variance across genotypes; these variance-quantitative trait loci (vQTLs) can be prioritized in a two-stage GEI detection strategy to greatly reduce the computational and statistical burden and enable testing of a broader range of exposures. We performed genome-wide vQTL analysis for 20 serum cardiometabolic biomarkers by multi-ancestry meta-analysis of 350,016 unrelated participants in the UK Biobank, identifying 182 independent locus-biomarker pairs (p < 4.5×10−9). Most vQTLs were concentrated in a small subset (4%) of loci with genome-wide significant main effects, and 44% replicated (p < 0.05) in the Women’s Genome Health Study (N = 23,294). Next, we tested each vQTL for interaction across 2,380 exposures, identifying 846 significant GEIs (p < 2.4×10−7). Specific examples demonstrated interaction of triglyceride-associated variants with distinct body mass-versus body fat-related exposures as well as genotype-specific associations between alcohol consumption and liver stress at the ADH1B gene. Our catalog of vQTLs and GEIs is publicly available in an online portal.
Bone marrow mesenchymal stem cells stimulated by tumor necrosis factor-α can promote the repair of fatty liver cell oxidative stress injury and fatty liver ischemia-reperfusion injury
Authors: Tan Yuying , Qiu Jiali , Zhang Weiqi , Xie Yan , Chen Chiyi , Li Junjie , Li Jiang , Jiang Wentao 
Published: November 2021

AbstractMesenchymal stem cells (MSCs) have great prospects for the treatment of ischemia-reperfusion injury (IRI) after liver transplantation. At this stage, the main factor limiting MSCs in the treatment of fatty liver IRI of the donor liver is the residence time of stem cells at the site of inflammatory injury. This study investigated whether bone marrow mesenchymal stem cells (BMSCs) stimulated by tumor necrosis factor-α (TNF-α) can promote the repair of fatty liver cell oxidative stress injury and fatty liver IRI in rats. The results indicated the BMSCs treatment group stimulated by TNF-α had lower indexes and significantly improved oxidative stress damage in vitro through Transwell chamber co-culture experiment, compared with the control group. In vivo, compared with the PBS group and the BMSCs group, the indexes of the BMSCs treatment group stimulated by TNF-α were reduced, and the degree of tissue damage was significantly reduced. BMSCs can repair fatty liver cell oxidative stress injury and fatty liver IRI, however, BMSCs stimulated by TNF-α can promote the repair of tissues and cells.