bluuebunny/crossref_metadata_2025_split huggingface dataset:
Exploring the potential of electric weed control: a review
Authors: Slaven Miranda J. , Koch Maximilian , Borger Catherine P. D. 
Published: August 2023

AbstractWeed management is a significant challenge that must be addressed both globally and in Australia, where traditional methods of control have become limited. The avoidance of mechanical practices has resulted in reduced erosion but has also led to an increased reliance on chemicals and a subsequent increase in rates of herbicide resistance. To address this challenge, alternative forms of weed management, such as electric weed control (electro-weeding), need to be considered. Electric weed control functions by transferring electrical current through the target plant following electrode contact, causing the plant’s cells to burst and either killing the plant or suppressing its growth. However, a multitude of variables, such as electrical power and speed of application, weed morphology, and site-specific environmental conditions, can impact the use of electric weed control and its efficacy. While electric weed control holds promise, and despite its recent global popularity with numerous companies producing machinery, the applicability, efficacy, and risks of using electric weed control internationally and in Australia have yet to be thoroughly analyzed. Given the existing knowledge gaps, this review provides a comprehensive overview of the theory and recent advances in electric weed control. Additionally, the review discusses the potential for resistance development and safety risks associated with electric weed control and presents an overview of modern machines and their application in various settings. It also highlights the need for further research to determine the applicability and efficacy of implementing this new weed control method before widespread adoption and integration into pest management strategies.
Connecting Large‐Scale Meteorological Patterns to Extratropical Cyclones in CMIP6 Climate Models Using Self‐Organizing Maps
Authors: Gore Michelle J. , Zarzycki Colin M. , Gervais Melissa M. 
Published: August 2023

AbstractExtratropical cyclones (ETCs) are responsible for the majority of cool‐season extreme events in the northeastern United States (NEUS), often leading to high‐impact weather conditions that can have wide‐ranging socioeconomic impacts. Evaluating the ability of climate models to adequately simulate ETC dynamics is essential for improving model performance and increasing confidence in future projections used by stakeholders and policymakers. ETCs are traditionally studied using techniques such as case studies and synoptic typing, however, these approaches can be time‐consuming, require subjective analysis, and do not necessarily identify the coincident large‐scale meteorological patterns (LSMPs). Here, we apply self‐organizing maps (SOMs) as an automated machine‐learning approach to characterize the LSMPs and associated frequency and intensity of discrete ETC events over NEUS. The dominant patterns of geopotential height variability are identified through SOM analysis of five reanalysis products during the last four decades. ETC events are tracked using TempestExtremes and are integrated with SOMs to classify the accumulated cyclone activity (ACA) associated with each pattern. We then evaluate the skill of CMIP6 historical experiments in simulating the LSMPs and ETC events identified in the SOM. Our results identify a robust bias toward more zonal patterns, with models struggling to reproduce the more amplified patterns typically associated with the highest cyclone activity. While model resolution has some impact on simulation credibility, model configuration appears to be more important in LSMP representation. The vast majority of CMIP6 models produce too few ETCs, although model errors are distributed around historical reanalyses when ACA is normalized by storm frequency.
Evaluating European ECOSTRESS Hub Evapotranspiration Products Across a Range of Soil‐Atmospheric Aridity and Biomes Over Europe
Authors: Hu Tian , Mallick Kaniska , Hitzelberger Patrik , Didry Yoanne , Boulet Gilles , Szantoi Zoltan , Koetz Benjamin , Alonso Itziar , Pascolini‐Campbell Madeleine , Halverson Gregory , Cawse‐Nicholson Kerry , Hulley Glynn C. , Hook Simon , Bhattarai Nishan , Olioso Albert , Roujean Jean‐Louis , Gamet Philippe , Su Bob 
Published: August 2023

AbstractThe ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) is a scientific mission that collects high spatio‐temporal resolution (∼70 m, 1–5 days average revisit time) thermal images since its launch on 29 June 2018. As a predecessor of future missions, one of the main objectives of ECOSTRESS is to retrieve and understand the spatio‐temporal variations in terrestrial evapotranspiration (ET) and its responses to soil water availability and atmospheric aridity. In the European ECOSTRESS Hub (EEH), by taking advantage of land surface temperature (LST) retrievals, we generated ECOSTRESS ET products over Europe and Africa using three models with different structures and parameterization schemes, namely Surface Energy Balance System (SEBS) and Two Source Energy Balance (TSEB) parametric models, as well as the non‐parametric Surface Temperature Initiated Closure (STIC) model. A comprehensive evaluation of the EEH ET products was conducted with respect to flux measurements from 19 eddy covariance sites in Europe over six different biomes with diverse aridity levels. Results revealed comparable performances of STIC and SEBS (RMSE of ∼70 W m−2). However, the relatively complex TSEB model produced a higher RMSE of ∼90 W m−2. Comparison between STIC ET estimates and the operational ECOSTRESS ET product from NASA PT‐JPL model showed a larger RMSE (around 50 W m−2 higher) for the PT‐JPL ET estimates. Substantial overestimation (>80 W m−2) in PT‐JPL ET estimates was evident over shrublands and savannas, presumably due to weak constraint of LST in the model. Overall, the EEH supports ET retrieval for the future high‐resolution thermal missions.
Carbon Storage in Earth's Deep Interior Implied by Carbonate‐Silicate‐Iron Melt Miscibility
Authors: Davis A. H. , Solomatova N. V. , Caracas R. , Campbell A. J. 
Published: August 2023

AbstractCarbonate melts have been proposed to exist in the lower mantle, but their interaction with other lower mantle melt compositions is poorly understood. To understand miscibility in the carbonate‐silicate‐metal melt system, we simulate endmember, binary, and ternary melt mixtures and study how their Gibbs free energies of mixing evolve with pressure. We find that carbonate‐metal and carbonate‐silicate melts have miscibility gaps that close with increasing pressure, while silicate‐metal melts are immiscible at all lower‐mantle pressures. Extending this analysis to the core‐mantle boundary, we suggest three miscible melt fields near the endmember carbonate, silicate, and iron melt compositions. Analysis of the densities of these miscible melt compositions indicates that some carbonate‐rich and some silicate‐rich melt compositions are gravitationally stable at the core‐mantle boundary and could be candidate compositions to explain ultra‐low velocity zones. Additionally, we evaluate the speciation of an example immiscible melt composition at various pressures throughout the mantle and identify reduced carbon species that would be expected to form in the melt. Our analysis reveals that a majority of Earth's carbon could have been transported to the core during core‐mantle differentiation and that much of Earth's carbon may be stored in the deep interior today.
Smooth muscle liver kinase B1 inhibits foam cell formation and atherosclerosis via direct phosphorylation and activation of SIRT6
Authors: Deng Qiming , Li Hongxuan , Yue Xiaolin , Guo Chenghu , Sun Yuanyuan , Ma Chang , Gao Jiangang , Wu Yue , Du Bin , Yang Jianmin , Zhang Cheng , Zhang Wencheng 
Published: August 2023

AbstractFoam cell formation is a hallmark of the early phase of atherosclerosis. Growing evidence has demonstrated that vascular smooth muscle cells (VSMCs) comprise a considerable proportion of foam cells. Liver kinase B1 (LKB1) plays a crucial part in cardiovascular diseases. However, the role of LKB1 in VSMC-derived foam cell formation and atherosclerosis remains unclear. To explore the effects of LKB1 on VSMC-derived foam cell formation and atherosclerosis, we generated smooth muscle-specific LKB1 knockout (LKB1SMKO) mice by crossbreeding LKB1flox/flox mice with SM22α-CreERT2 mice. LKB1 expression decreased in plaque-loaded aortas and oxidized low-density lipoprotein (oxLDL)-treated VSMCs. Compared with controls, atherosclerosis development was exacerbated in LKB1SMKO mice via the promotion of VSMC-derived foam cell formation. Conversely, LKB1 overexpression inhibited lipid uptake and foam cell formation in VSMCs. Mechanistically, LKB1 binds to SIRT6 and directly phosphorylates and activates it, thereby reducing lectin-like oxLDL receptor-1 (LOX-1) via SIRT6-dependent histone deacetylation. Finally, adeno-associated virus (AAV)-mediated LOX-1 deficiency in smooth muscle ameliorated atherosclerosis in LKB1SMKO mice. Our findings suggest that LKB1 may modulate VSMC-derived foam cell formation and atherosclerosis via the phosphorylation and activation of SIRT6.
Super-resolution multicolor fluorescence microscopy enabled by an apochromatic super-oscillatory lens with extended depth-of-focus
Authors: Li Wenli , He Pei , Lei Dangyuan , Fan Yulong , Du Yangtao , Gao Bo , Chu Zhiqin , Li Longqiu , Liu Kaipeng , An Chengxu , Yuan Weizheng , Yu Yiting 
Published: August 2023

AbstractPlanar super-oscillatory lens (SOL), a far-field subwavelength-focusing diffractive device, holds great potential for achieving sub-diffraction-limit imaging at multiple wavelengths. However, conventional SOL devices suffer from a numerical-aperture-related intrinsic tradeoff among the depth of focus (DoF), chromatic dispersion and focusing spot size. Here, we apply a multi-objective genetic algorithm (GA) optimization approach to design an apochromatic binary-phase SOL having a prolonged DoF, customized working distance (WD), minimized main-lobe size, and suppressed side-lobe intensity. Experimental implementation demonstrates simultaneous focusing of blue, green and red light beams into an optical needle of ~0.5λ in diameter and DOF > 10λ at WD = 428 μm. By integrating this SOL device with a commercial fluorescence microscope, we perform, for the first time, three-dimensional super-resolution multicolor fluorescence imaging of the “unseen” fine structures of neurons. The present study provides not only a practical route to far-field multicolor super-resolution imaging but also a viable approach for constructing imaging systems avoiding complex sample positioning and unfavorable photobleaching.
SYPL1 defines a vesicular pathway essential for sperm cytoplasmic droplet formation and male fertility
Authors: Liu Jiali , Hermo Louis , Ding Deqiang , Wei Chao , Mann Jeffrey M. , Yan Xiaoyuan , Melnick Ashley F. , Wu Yingjie , Withrow Alicia , Cibelli Jose , Hess Rex A. , Chen Chen 
Published: August 2023

AbstractThe cytoplasmic droplet is a conserved dilated area of cytoplasm situated at the neck of the sperm flagellum. Viewed as residual cytoplasm inherited from late spermatids, the cytoplasmic droplet contains numerous saccular elements as its key content. However, the origin of these saccules and the function of the cytoplasmic droplet have long been speculative. Here, we identify the molecular origin of these cytoplasmic droplet components by uncovering a vesicle pathway essential for formation and sequestration of saccules within the cytoplasmic droplet. This process is governed by a transmembrane protein SYPL1 and its interaction with VAMP3. Genetic ablation of SYPL1 in mice reveals that SYPL1 dictates the formation and accumulation of saccular elements in the forming cytoplasmic droplet. Derived from the Golgi, SYPL1 vesicles are critical for segregation of key metabolic enzymes within the forming cytoplasmic droplet of late spermatids and epididymal sperm, which are required for sperm development and male fertility. Our results uncover a mechanism to actively form and segregate saccules within the cytoplasmic droplet to promote sperm fertility.
Thermodynamical framework for effective mitigation of high aerosol loading in the Indo-Gangetic Plain during winter
Authors: Acharja Prodip , Ghude Sachin D. , Sinha Baerbel , Barth Mary , Govardhan Gaurav , Kulkarni Rachana , Sinha Vinayak , Kumar Rajesh , Ali Kaushar , Gultepe Ismail , Petit Jean-Eudes , Rajeevan Madhavan Nair 
Published: August 2023

AbstractThe Indo-Gangetic Plain (IGP) experiences severe air pollution every winter, with ammonium chloride and ammonium nitrate as the major inorganic fractions of fine aerosols. Many past attempts to tackle air pollution in the IGP were inadequate, as they targeted a subset of the primary pollutants in an environment where the majority of the particulate matter burden is secondary in nature. Here, we provide new mechanistic insight into aerosol mitigation by integrating the ISORROPIA-II thermodynamical model with high-resolution simultaneous measurements of precursor gases and aerosols. A mathematical framework is explored to investigate the complex interaction between hydrochloric acid (HCl), nitrogen oxides (NOx), ammonia (NH3), and aerosol liquid water content (ALWC). Aerosol acidity (pH) and ALWC emerge as governing factors that modulate the gas-to-particle phase partitioning and mass loading of fine aerosols. Six "sensitivity regimes" were defined, where PM1 and PM2.5 fall in the "HCl and HNO3 sensitive regime", emphasizing that HCl and HNO3 reductions would be the most effective pathway for aerosol mitigation in the IGP, which is ammonia-rich during winter. This study provides evidence that precursor abatement for aerosol mitigation should not be based on their descending mass concentrations but instead on their sensitivity to high aerosol loading.
A separable temporal convolutional networks based deep learning technique for discovering antiviral medicines
Authors: Singh Vishakha , Singh Sanjay Kumar 
Published: August 2023

AbstractAn alarming number of fatalities caused by the COVID-19 pandemic has forced the scientific community to accelerate the process of therapeutic drug discovery. In this regard, the collaboration between biomedical scientists and experts in artificial intelligence (AI) has led to a number of in silico tools being developed for the initial screening of therapeutic molecules. All living organisms produce antiviral peptides (AVPs) as a part of their first line of defense against invading viruses. The Deep-AVPiden model proposed in this paper and its corresponding web app, deployed at https://deep-avpiden.anvil.app, is an effort toward discovering novel AVPs in proteomes of living organisms. Apart from Deep-AVPiden, a computationally efficient model called Deep-AVPiden (DS) has also been developed using the same underlying network but with point-wise separable convolutions. The Deep-AVPiden and Deep-AVPiden (DS) models show an accuracy of 90% and 88%, respectively, and both have a precision of 90%. Also, the proposed models were statistically compared using the Student’s t-test. On comparing the proposed models with the state-of-the-art classifiers, it was found that they are much better than them. To test the proposed model, we identified some AVPs in the natural defense proteins of plants, mammals, and fishes and found them to have appreciable sequence similarity with some experimentally validated antimicrobial peptides. These AVPs can be chemically synthesized and tested for their antiviral activity.
Influence of knee flexion angle on graft bending angle during anterior cruciate ligament reconstruction using the transportal technique
Authors: Chung Kwangho , Choi Chong Hyuk , Kim Sung-Hwan , Kim Sung-Jae , Choi Hee Chan , Jung Min 
Published: August 2023

AbstractThis study aimed to examine change in the graft bending angle (GBA) according to various knee flexion angles in creating femoral tunnel by the transportal technique in ACL reconstruction, and to reveal knee flexion angle minimizing GBA while maintaining stable femoral tunnel characteristics. Patients who underwent ACL reconstruction using the transportal technique between January 2017 and December 2018 were retrospectively reviewed. Patients were classified into three groups according to knee flexion angle when creating femoral tunnel (group 1: < 120° (n = 19); group 2: 120–129° (n = 32); group 3: ≥ 130° (n = 33). GBA was measured on three-dimensional knee model reconstructed from postoperative computed tomography images. The length of the femoral tunnel and posterior wall blow-out were also checked. There was significant difference of GBA between the groups (group 1 = 112.1°; group 2 = 106.4°; group 3 = 101.4°, p < 0.001). The knee flexion angle in creating femoral tunnel was negatively correlated with GBA (r = − 0.733, p < 0.001). Five patients in group 1 had short femoral tunnel. GBA was influenced by knee flexion angle in creating femoral tunnel and got more acute as the knee flexion angle increased. Considering length and risk of wall blow-out in femoral tunnel, and GBA, knee flexion angle between 120 and 130° could be recommended as appropriate angle to create optimal femoral tunnel in ACL reconstruction using the transportal technique.
Sensing nucleotide composition in virus RNA
Authors: Lo Raymon , Gonçalves-Carneiro Daniel 
Published: August 2023

Abstract
Nucleotide composition plays a crucial role in the structure, function and recognition of RNA molecules. During infection, virus RNA is exposed to multiple endogenous proteins that detect local or global compositional biases and interfere with virus replication. Recent advancements in RNA:protein mapping technologies have enabled the identification of general RNA-binding preferences in the human proteome at basal level and in the context of virus infection. In this review, we explore how cellular proteins recognise nucleotide composition in virus RNA and the impact these interactions have on virus replication. Protein-binding G-rich and C-rich sequences are common examples of how host factors detect and limit infection, and, in contrast, viruses may have evolved to purge their genomes from such motifs. We also give examples of how human RNA-binding proteins inhibit virus replication, not only by destabilising virus RNA, but also by interfering with viral protein translation and genome encapsidation. Understanding the interplay between cellular proteins and virus RNA composition can provide insights into host–virus interactions and uncover potential targets for antiviral strategies.
Longitudinal Grammaticality Judgments of Tense Marking in Complex Questions in Children With and Without Specific Language Impairment, Ages 5–18 Years
Authors: Rice Mabel L. , Earnest Kathleen Kelsey , Hoffman Lesa 
Published: August 2023

Purpose:
Identification of children with specific language impairment (SLI) can be difficult even though their language can lag that of age peers throughout childhood. A clinical grammar marker featuring tense marking in simple clauses is valid and reliable for young children but is limited by ceiling effects around the age of 8 years. This study evaluated a new, more grammatically challenging complex sentence task in children affected or unaffected with SLI in longitudinal data, ages 5–18 years.

Method:
Four hundred eighty-three children (213 unaffected, 270 affected) between 5 and 18 years of age participated, following a rolling recruitment longitudinal design encompassing a total of 4,148 observations. The new experimental grammaticality judgment task followed linguistic concepts of syntactic sites for finiteness and movement within complex clauses. Growth modeling methods evaluated group differences over time for four different outcomes; three were hypothesized to evaluate optional omissions of overt finiteness forms in authorized sentence sites, and one evaluated an overt error of tense marking.

Results:
As in earlier studies of younger children, growth models for the SLI group were consistently lower than the unaffected group, although the growth trajectories across groups did not differ. The results replicated across four item types defined by omissions with minor differences for an item with an overt error of tense marking. Covariates of child nonverbal IQ, mother's education, and child sex did not significantly moderate these effects.

Conclusion:
The outcomes support the task as having potential screening value for identification of children with SLI and are consistent with linguistic interpretations of task demands.
Short‐term prediction of behind‐the‐meter PV power based on attention‐LSTM and transfer learning
Authors: Zhang Jinjiang , Hong Liqing , Ibrahim Shamsuddeen Nyako , He Yuanru 
Published: August 2023

AbstractDistributed photovoltaic (PV) systems often lack adequate measurements due to cost considerations, which makes it very difficult to predict them accurately. Here, an approach is proposed for behind‐the‐meter (BTM) PV power prediction using attention‐LSTM neural network and transfer learning. First, the weather is classified into four types based on the deviation ratio β. Second, the correlation analysis algorithm identifies the weather factors that contribute the most to PV power generation as GHI, DNI, humidity, and temperature. Then, attention‐LSTM pre‐trained model is constructed, in which the LSTM network fully extracts the temporal characteristics of PV power generation, while the attention mechanism enhances the attention to the important information in the input. Finally, a novel BTM PV short‐term power prediction method using transfer learning that the upper layer parameters of the pre‐trained model were frozen, and a small amount of DP‐NB data was used to fine‐tune the model. The proposed methodology has higher prediction accuracy compared with other benchmark methods under four weather types, and the time cost is saved by freezing the parameters of the first layer of the network by 37.2%.
An immune‐related multi‐omics analysis of dolichyl‐diphosphooligosaccharide protein glycosyltransferase in glioma: Prognostic value exploration and competitive endogenous RNA network identification
Authors: Liu Jie , Feng Chao , Liu Min , Zhou Yan , Shen Yuezhen , Li Jianxin , Wei Xiangyang 
Published: August 2023

AbstractDolichyl‐diphosphooligosaccharide protein glycosyltransferase (DDOST) plays a pivotal role in the glycosylation of asparagine residues on nascent polypeptides. However, the biological role of DDOST in glioma remains unclear. The mRNA expression of DDOST in glioma was identified using TCGA, CGGA, GEO and Rembrandt datasets. Immunohistochemistry assay was conducted to examine the protein level of DDOST. Cox regression analysis, nomograms and calibration plots were used to evaluate the prognostic value of DDOST. The association between DDOST and immune cell infiltration was evaluated using CIBERSORT algorithm. Additionally, DNA methylation and ceRNA regulatory network of DDOST expression were investigated using the LinkedOmics and ENCORI databases. The authors found that DDOST was substantially expressed at the mRNA and protein levels. Functional enrichment analysis revealed close associations between DDOST and immune‐related pathways, as well as immune cell infiltration. In addition, DDOST exhibited synergistic effects with tumour mutational burden (TMB) and other immune checkpoints. For expression regulation mechanisms, DDOST had low DNA methylation levels in high‐grade gliomas and may be involved in multiple ceRNA networks in glioma. Thus, DDOST may serve as an unfavourable biomarker for gliomas. DNA methylation and ceRNA regulatory networks of DDOST expression were identified for the first time in this multi‐omics study.