bluuebunny/crossref_metadata_2025_split huggingface dataset:
Modeling Aerosol Effects on Liquid Clouds in the Summertime Arctic
Authors: Ghahreman Roya , Gong Wanmin , Beagley Stephen R. , Akingunola Ayodeji , Makar Paul A. , Leaitch W. Richard 
Published: December 2021

AbstractAn investigation of aerosol effects on the Arctic summer clouds is carried out by using a fully‐coupled version of GEM‐MACH, an online air quality forecast model. Model simulations are carried out for the July 2014 NETCARE field campaign based from Resolute, Nunavut, Canada. For a pristine period, the model simulated thin water clouds, with liquid water path <50 g m−2, at relatively low altitudes (<200 m). The model simulated more and smaller droplets with higher liquid water content (LWC) during a polluted period. Further sensitivity analysis indicates that the increased aerosol loading from long‐range transport during the polluted period is responsible for the increase in CDNC and decreased droplet size, which also led to an increase in cloud liquid water content (LWC), a decrease in precipitation, and increased cloudiness in the area. The model agrees with observation showing that aerosols smaller than 100 nm are commonly activated in the summer Arctic, with even smaller aerosols (<50 nm) being activated during the pristine period. The impact of atmospheric dimethyl sulfide (DMS) upon the Arctic summer cloud microphysics was also investigated. The inclusion of DMS leads to an increase in CDNC and smaller droplet sizes. It also improves the modeled aerosol size distribution considerably compared to the observation, particularly in the size range between 60 and 200 nm. The enhancement of CDNC due to DMS is more significant (e.g., >50%) in the regions with higher DMS(g) mixing ratios, resulting in higher sulphate mass increases in these regions.
Improving Surface PM2.5 Forecasts in the United States Using an Ensemble of Chemical Transport Model Outputs: 2. Bias Correction With Satellite Data for Rural Areas
Authors: Zhang Huanxin , Wang Jun , García Lorena Castro , Zhou Meng , Ge Cui , Plessel Todd , Szykman James , Levy Robert C. , Murphy Benjamin , Spero Tanya L. 
Published: December 2021

AbstractThis work serves as the second of a two‐part study to improve surface PM2.5 forecasts in the continental U.S. through the integrated use of multisatellite aerosol optical depth (AOD) products (MODIS Terra/Aqua and VIIRS DT/DB), multichemical transport model (CTM) (GEOS‐Chem, WRF‐Chem, and CMAQ) outputs, and ground observations. In Part I of the study, an ensemble Kalman filter (KF) technique using three CTM outputs and ground observations was developed to correct forecast bias and generate a single best forecast of PM2.5 for next day over nonrural areas that have surface PM2.5 measurements in the proximity of 125 km. Here, with AOD data, we extended the bias correction into rural areas where the closest air quality monitoring station is at least 125–300 km away. First, we ensembled all of satellite AOD products to yield the single best AOD. Second, we corrected daily PM2.5 in rural areas from multiple models through the AOD spatial pattern between these areas and nonrural areas, referred to as “extended ground truth” or EGT, for the present day. Lastly, we applied the KF technique to reduce the forecast bias for next day using the EGT. Our results find that the ensemble of bias‐corrected daily PM2.5 from three CTMs for both today and next day show the best performance. Together, the two‐part study develops a multimodel and multi‐AOD bias‐correction technique that has the potential to improve PM2.5 forecasts in both rural and nonrural areas in near real time, and be readily implemented at state levels.
Congenital heart disease in school-aged children: Cognition, education, and participation in leisure activities
Authors: Spillmann Rebecca , Polentarutti Susanne , Ehrler Melanie , Kretschmar Oliver , Wehrle Flavia M. , Latal Beatrice 
Published: December 2021

Abstract
Background
Children with congenital heart disease (CHD) are at risk for neurodevelopmental deficits. This study aimed to investigate the impact of cognitive deficits on educational outcome and participation in leisure activities.

Methods
A prospective cohort of 134 children with CHD who underwent cardiopulmonary bypass surgery (CPB) was examined at 10 years of age. IQ was assessed with the WISC-IV and executive functions with the BRIEF (parent- and teacher-report). Parents reported on type and level of education and educational support, and leisure activity participation. Ordinal regression analyses assessed the association between cognitive deficits and educational outcome and participation.

Results
Total IQ (P = 0.023), working memory (P < 0.001), processing speed (P = 0.008), and teacher-reported metacognition (P = 0.022) were lower than norms. Regular school was attended by 82.4% of children with CHD compared to 97% of the general Swiss population (P < 0.001). Seventy-five percent of children participated in leisure activities. Lower total IQ and teacher-rated global executive functions were associated with more educational support and lower IQ was associated with less participation.

Conclusion
As school-aged children with CHD experience cognitive deficits, follow-up is required to provide optimal support with regard to educational outcome and participation in leisure activities.

Impact

Contemporary cohorts of children with congenital heart disease undergoing cardiopulmonary bypass surgery remain at increased risk for cognitive deficits.

Cognitive deficits affect educational outcome and leisure activities.

These findings underline the importance of early detection of cognitive deficits and recommend support with respect to cognitive functioning.
Fis1 phosphorylation by Met promotes mitochondrial fission and hepatocellular carcinoma metastasis
Authors: Yu Yan , Peng Xiao-Dan , Qian Xiao-Jun , Zhang Kai-Ming , Huang Xiang , Chen Yu-Hong , Li Yun-Tian , Feng Gong-Kan , Zhang Hai-Liang , Xu Xue-Lian , Li Shun , Li Xuan , Mai Jia , Li Zhi-Ling , Huang Yun , Yang Dong , Zhou Li-Huan , Zhong Zhuo-Yan , Li Jun-Dong , Deng Rong , Zhu Xiao-Feng 
Published: December 2021

AbstractMet tyrosine kinase, a receptor for a hepatocyte growth factor (HGF), plays a critical role in tumor growth, metastasis, and drug resistance. Mitochondria are highly dynamic and undergo fission and fusion to maintain a functional mitochondrial network. Dysregulated mitochondrial dynamics are responsible for the progression and metastasis of many cancers. Here, using structured illumination microscopy (SIM) and high spatial and temporal resolution live cell imaging, we identified mitochondrial trafficking of receptor tyrosine kinase Met. The contacts between activated Met kinase and mitochondria formed dramatically, and an intact HGF/Met axis was necessary for dysregulated mitochondrial fission and cancer cell movements. Mechanically, we found that Met directly phosphorylated outer mitochondrial membrane protein Fis1 at Tyr38 (Fis1 pY38). Fis1 pY38 promoted mitochondrial fission by recruiting the mitochondrial fission GTPase dynamin-related protein-1 (Drp1) to mitochondria. Fragmented mitochondria fueled actin filament remodeling and lamellipodia or invadopodia formation to facilitate cell metastasis in hepatocellular carcinoma (HCC) cells both in vitro and in vivo. These findings reveal a novel and noncanonical pathway of Met receptor tyrosine kinase in the regulation of mitochondrial activities, which may provide a therapeutic target for metastatic HCC.
A 2.09 Mb fragment translocation on chromosome 6 causes abnormalities during meiosis and leads to less seed watermelon
Authors: Tian Shujuan , Ge Jie , Ai Gongli , Jiang Jiao , Liu Qiyan , Chen Xiner , Liu Man , Yang Jianqiang , Zhang Xian , Yuan Li 
Published: December 2021

AbstractSeedlessness is a valuable agronomic trait in watermelon (Citrullus lanatus) breeding. Conventional less seed watermelons are mainly triploid, which has many disadvantages due to unbalanced genome content. Less seed watermelon can be achieved at the diploid level when certain reproductive genes are mutated or by chromosome translocation, which leads to defects during meiosis. However, the formation mechanism of diploid less seed watermelons remains largely unknown. Here, we identified a spontaneous mutant line, watermelon line “148”, which can set seeds normally when self-pollinated. A total of 148 × JM F1hybrid plants exhibited seed number reductions to 50.3% and 47.3% of those of the two parental lines, respectively, which are considered to be less seed. Examination of pollen viability and hybridization experiments revealed that F1hybrids produce semisterile pollen and ovules. Further cytological observations indicated that semisterility was a result of a reciprocal translocation of chromosomes, which exhibited one quadrivalent ring of four chromosomes at prometaphase I during meiosis. RT-qPCR analysis indirectly confirmed that the semisterile phenotype is caused by chromosome translocation rather than disruption of specific meiotic gene expression. F2population genetic analysis indicated that the “148” watermelon line is a homozygous translocation and that the less seed phenotype of the F1hybrid is prompted by one chromosome fragment translocation. The translocated fragment was further fine mapped to a 2.09 Mb region on chromosome 6 by whole-genome resequencing and genetic map cloning procedures. Our work revealed that a 2.09 Mb chromosome fragment translocation on chromosome 6, causing meiotic defects at metaphase I during meiosis, leads to diploid less seed watermelon. Our findings provide a new promising method for less seed watermelon breeding at the diploid level, as well as a fragment size reference for breeding less seed watermelon through artificially induced chromosome translocation.
Dissecting the membrane-microtubule sensor in grapevine defence
Authors: Guan Pingyin , Shi Wenjing , Riemann Michael , Nick Peter 
Published: December 2021

AbstractSpecific populations of plant microtubules cooperate with the plasma membrane to sense and process abiotic stress signals, such as cold stress. The current study derived from the question, to what extent this perception system is active in biotic stress signalling. The experimental system consisted of grapevine cell lines, where microtubules or actin filaments are visualised by GFP, such that their response became visible in vivo. We used the bacterial elicitors harpin (inducing cell-death related defence), or flg22 (inducing basal immunity) in combination with modulators of membrane fluidity, or microtubules. We show that DMSO, a membrane rigidifier, can cause microtubule bundling and trigger defence responses, including activation of phytoalexin transcripts. However, DMSO inhibited the gene expression in response to harpin, while promoting the gene expression in response to flg22. Treatment with DMSO also rendered microtubules more persistent to harpin. Paradoxically, Benzylalcohol (BA), a membrane fluidiser, acted in the same way as DMSO. Neither GdCl3, nor diphenylene iodonium were able to block the inhibitory effect of membrane rigidification on harpin-induced gene expression. Treatment with taxol stabilised microtubule against harpin but amplified the response of PAL transcripts. Therefore, the data support implications of a model that deploys specific responses to pathogen-derived signals.
Regulatory circuits involving bud dormancy factor PpeDAM6
Authors: Lloret Alba , Quesada-Traver Carles , Conejero Ana , Arbona Vicent , Gómez-Mena Concepción , Petri César , Sánchez-Navarro Jesús A. , Zuriaga Elena , Leida Carmen , Badenes María Luisa , Ríos Gabino 
Published: December 2021

AbstractDORMANCY-ASSOCIATED MADS-BOX (DAM) genes have recently emerged as key potential regulators of the dormancy cycle and climate adaptation in perennial species. Particularly, PpeDAM6 has been proposed to act as a major repressor of bud dormancy release and bud break in peach (Prunus persica). PpeDAM6 expression is downregulated concomitantly with the perception of a given genotype-dependent accumulation of winter chilling time, and the coincident enrichment in H3K27me3 chromatin modification at a specific genomic region. We have identified three peach BASIC PENTACYSTEINE PROTEINs (PpeBPCs) interacting with two GA-repeat motifs present in this H3K27me3-enriched region. Moreover, PpeBPC1 represses PpeDAM6 promoter activity by transient expression experiments. On the other hand, the heterologous overexpression of PpeDAM6 in European plum (Prunus domestica) alters plant vegetative growth, resulting in dwarf plants tending toward shoot meristem collapse. These alterations in vegetative growth of transgenic lines associate with impaired hormone homeostasis due to the modulation of genes involved in jasmonic acid, cytokinin, abscisic acid, and gibberellin pathways, and the downregulation of shoot meristem factors, specifically in transgenic leaf and apical tissues. The expression of many of these genes is also modified in flower buds of peach concomitantly with PpeDAM6 downregulation, which suggests a role of hormone homeostasis mechanisms in PpeDAM6-dependent maintenance of floral bud dormancy and growth repression.
An integrated metagenomic and metabolite profiling study of hydrocarbon biodegradation and corrosion in navy ships
Authors: Marks Christopher R. , Duncan Kathleen E. , Nanny Mark A. , Harriman Brian H. , Avci Recep , Oldham Athenia L. , Suflita Joseph M. 
Published: December 2021

AbstractNaval vessels regularly mix fuel and seawater as ballast, a practice that might exacerbate fuel biodegradation and metal biocorrosion. To investigate, a metagenomic characterization and metabolite profiling of ballast from U.S. Navy vessels with residence times of 1-, ~20-, and 31 weeks was conducted and compared with the seawater used to fill the tanks. Aerobic Gammaproteobacteria differentially proliferated in the youngest ballast tank and aerobic-specific hydrocarbon degradation genes were quantitatively more important compared to seawater or the other ballast tanks. In contrast, the anaerobic Deltaproteobacteria dominated in the eldest ballast fluid with anaerobic-specific hydrocarbon activation genes being far more prominent. Gene activity was corroborated by detection of diagnostic metabolites and corrosion was evident by elevated levels of Fe, Mn, Ni and Cu in all ballast samples relative to seawater. The findings argue that marine microbial communities rapidly shift from aerobic to anaerobic hydrocarbonoclastic-dominated assemblages that accelerate fuel and infrastructure deterioration.
Advancing mathematics by guiding human intuition with AI
Authors: Davies Alex , Veličković Petar , Buesing Lars , Blackwell Sam , Zheng Daniel , Tomašev Nenad , Tanburn Richard , Battaglia Peter , Blundell Charles , Juhász András , Lackenby Marc , Williamson Geordie , Hassabis Demis , Kohli Pushmeet 
Published: December 2021

AbstractThe practice of mathematics involves discovering patterns and using these to formulate and prove conjectures, resulting in theorems. Since the 1960s, mathematicians have used computers to assist in the discovery of patterns and formulation of conjectures1, most famously in the Birch and Swinnerton-Dyer conjecture2, a Millennium Prize Problem3. Here we provide examples of new fundamental results in pure mathematics that have been discovered with the assistance of machine learning—demonstrating a method by which machine learning can aid mathematicians in discovering new conjectures and theorems. We propose a process of using machine learning to discover potential patterns and relations between mathematical objects, understanding them with attribution techniques and using these observations to guide intuition and propose conjectures. We outline this machine-learning-guided framework and demonstrate its successful application to current research questions in distinct areas of pure mathematics, in each case showing how it led to meaningful mathematical contributions on important open problems: a new connection between the algebraic and geometric structure of knots, and a candidate algorithm predicted by the combinatorial invariance conjecture for symmetric groups4. Our work may serve as a model for collaboration between the fields of mathematics and artificial intelligence (AI) that can achieve surprising results by leveraging the respective strengths of mathematicians and machine learning.
Validation of expert system enhanced deep learning algorithm for automated screening for COVID-Pneumonia on chest X-rays
Authors: Gidde Prashant Sadashiv , Prasad Shyam Sunder , Singh Ajay Pratap , Bhatheja Nitin , Prakash Satyartha , Singh Prateek , Saboo Aakash , Takhar Rohit , Gupta Salil , Saurav Sumeet , M. V. Raghunandanan , Singh Amritpal , Sardana Viren , Mahajan Harsh , Kalyanpur Arjun , Mandal Atanendu Shekhar , Mahajan Vidur , Agrawal Anurag , Agrawal Anjali , Venugopal Vasantha Kumar , Singh Sanjay , Dash Debasis 
Published: December 2021

AbstractSARS-CoV2 pandemic exposed the limitations of artificial intelligence based medical imaging systems. Earlier in the pandemic, the absence of sufficient training data prevented effective deep learning (DL) solutions for the diagnosis of COVID-19 based on X-Ray data. Here, addressing the lacunae in existing literature and algorithms with the paucity of initial training data; we describe CovBaseAI, an explainable tool using an ensemble of three DL models and an expert decision system (EDS) for COVID-Pneumonia diagnosis, trained entirely on pre-COVID-19 datasets. The performance and explainability of CovBaseAI was primarily validated on two independent datasets. Firstly, 1401 randomly selected CxR from an Indian quarantine center to assess effectiveness in excluding radiological COVID-Pneumonia requiring higher care. Second, curated dataset; 434 RT-PCR positive cases and 471 non-COVID/Normal historical scans, to assess performance in advanced medical settings. CovBaseAI had an accuracy of 87% with a negative predictive value of 98% in the quarantine-center data. However, sensitivity was 0.66–0.90 taking RT-PCR/radiologist opinion as ground truth. This work provides new insights on the usage of EDS with DL methods and the ability of algorithms to confidently predict COVID-Pneumonia while reinforcing the established learning; that benchmarking based on RT-PCR may not serve as reliable ground truth in radiological diagnosis. Such tools can pave the path for multi-modal high throughput detection of COVID-Pneumonia in screening and referral.
Alternative negative weight for simpler hardware implementation of synapse device based neuromorphic system
Authors: Han Geonhui , Lee Chuljun , Lee Jae-Eun , Seo Jongseon , Kim Myungjun , Song Yubin , Seo Young-Ho , Lee Daeseok 
Published: December 2021

AbstractLately, there has been a rapid increase in the use of software-based deep learning neural networks (S-DNN) for the analysis of unstructured data consumption. For implementation of the S-DNN, synapse-device-based hardware DNN (H-DNN) has been proposed as an alternative to typical Von-Neumann structural computing systems. In the H-DNN, various numerical values such as the synaptic weight, activation function, and etc., have to be realized through electrical device or circuit. Among them, the synaptic weight that should have both positive and negative numerical values needs to be implemented in a simpler way. Because the synaptic weight has been expressed by conductance value of the synapse device, it always has a positive value. Therefore, typically, a pair of synapse devices is required to realize the negative weight values, which leads to additional hardware resources such as more devices, higher power consumption, larger area, and increased circuit complexity. Herein, we propose an alternative simpler method to realize the negative weight (named weight shifter) and its hardware implementation. To demonstrate the weight shifter, we investigated its theoretical, numerical, and circuit-related aspects, following which the H-DNN circuit was successfully implemented on a printed circuit board.
Associations of the oral microbiota and Candida with taste, smell, appetite and undernutrition in older adults
Authors: Fluitman Kristina S. , van den Broek Tim J. , Nieuwdorp Max , Visser Marjolein , IJzerman Richard G. , Keijser Bart J. F. 
Published: December 2021

AbstractPoor taste and smell function are widely thought to contribute to the development of poor appetite and undernutrition in older adults. It has been hypothesized that the oral microbiota play a role as well, but evidence is scarce. In a cross-sectional cohort of 356 older adults, we performed taste and smell tests, collected anthropometric measurements and tongue swabs for analysis of microbial composition (16S rRNA sequencing) and Candida albicans abundance (qPCR). Older age, edentation, poor smell and poor appetite were associated with lower alpha diversity and explained a significant amount of beta diversity. Moreover, a lower Streptococcus salivarius abundance was associated with poor smell identification score, whereas high C. albicans abundance seemed to be associated with poor smell discrimination score. In our population, neither the tongue microbiota, nor C. albicans were associated with poor taste or directly with undernutrition. Our findings do suggest a host-microbe interaction with regard to smell perception and appetite.
Radiological hazard assessments of radionuclides in building materials, soils and sands from the Gaza Strip and the north of Sinai Peninsula
Authors: Abd Elkader Mona M. , Shinonaga Taeko , Sherif Mohamed M. 
Published: December 2021

AbstractRadiological hazards to the residents of the Gaza Strip, Palestine and the north of the Sinai Peninsula, Egypt, were determined using the naturally occurring radionuclides (226Ra, 232Th and 40K) in 69 samples of building materials (demolition debris, plasters, concretes, from recycling plants and raw cements from suppliers), soils and sands collected in the field. The radiological hazard indices and dose rates calculated with the activity concentrations of radionuclides in those materials determined by gamma-ray spectrometry indicate that the values are all within the global limits recommended by the United Nations Scientific Committee on the Effects of Atomic Radiation 2000 and European Commission 1999. The results of Spearman's correlation and hierarchical cluster analysis for 210Pb in the building materials, soils and sands suggest that the samples include 210Pb from the atmospheric fallout. The medium correlation between 232Th and 40K in demolition debris implies that their activity concentrations are characteristic of the building materials and constituents of the demolition debris. Non-natural ratio of 238U/235U was found in the soil and sand samples collected in the Gaza Strip. Furthermore, 137Cs and 241Am were detected in some soil, sand and demolition debris samples analyzed in this study. The origins of those anthropogenic radionuclides were considered.