bluuebunny/crossref_metadata_2025_split huggingface dataset:
Majority logic based area-delay efficient 1-bit approximate adder for error-tolerant applications
Authors: Parameshwara M C , Maroof Naeem , Khan Angshuman 
Published: May 2022

Abstract
The complementary metal oxide semiconductor (CMOS) technology is approaching its physical limits due to lithographic issues and diminishing benefits of scaling. The new technologies such as quantum dot cellular automata (QCA), tunneling phase logic (TPL), nonmagnetic logic (NML), single electron tunneling (SET), etc are emerging as an alternative and may supersede the conventional CMOS technologies in the near future. Now days, the design of approximate computing based on QCA technologies has gaining much of recent interest. In this paper, a majority-logic (ML) based area-delay efficient novel approximate full adder (AFA) is presented. The QCA layout of proposed AFA is designed and simulated using QCADesigner tool. Further, the proposed AFA is analyzed and compared against the state-of-the-art approximate adders referred to as ‘reported AFAs’ (RAAs), in terms of error metrics (EMs), area, and time complexity. Also, analyzed its efficacy for error-tolerant applications such as image processing.
Performance and mechanism of new silicone polymer as filtrate reducer with inhibitory effect for water-based drilling fluid
Authors: Ban Guo , Xu Jiang , Zeng Jia , Zhou Shu-sheng 
Published: May 2022

Abstract
An organic silicon filtrate reducer (AATN) with inhibitory effect, which can resist temperature up to 180 °C, was synthesized by using acrylamide (AM), vinyl trimethoxysilane (A-171), allyltrimethylammonium chloride (TM) and N-vinyl pyrrolidone (NVP) as monomers. AATN can effectively reduce the filtration loss of drilling fluid and inhibit the hydration expansion and hydration dispersion of the clay, which was beneficial to wellbore stability. Experimental results showed that the API filtration loss (FLAPI) of the drilling fluid containing 2 wt% AATN was only 7.8 ml. The siloxane groups of AATN were hydrolyzed in aqueous solution to generate Si–OH bonds, which can react with Si–OH bonds on hydrated clay surface to form a strong chemical adsorption. It was conducive to maintaining the dispersion of clay particles in the drilling fluid. The stable grid structure was formed by AATN and clay particles to reduce mud cake permeability, which can reduce the damage of drilling fluid filtrates to borehole stability. In addition, AATN can adsorb on the surface of sodium bentonite, thus forming a hydrophobic adsorption film on its surface, which effectively enveloped bentonite and inhibited the hydration expansion of bentonite.
WDM equipped universal linear optics for programmable neuromorphic photonic processors
Authors: Totovic Angelina , Pappas Christos , Kirtas Manos , Tsakyridis Apostolos , Giamougiannis George , Passalis Nikolaos , Moralis-Pegios Miltiadis , Tefas Anastasios , Pleros Nikos 
Published: May 2022

Abstract
Non-von-Neumann computing architectures and deep learning training models have sparked a new computational era where neurons are forming the main architectural backbone and vector, matrix and tensor multiplications comprise the basic mathematical toolbox. This paradigm shift has triggered a new race among hardware technology candidates; within this frame, the field of neuromorphic photonics promises to convolve the targeted algebraic portfolio along a computational circuitry with unique speed, parallelization, and energy efficiency advantages. Fueled by the inherent energy efficient analog matrix multiply operations of optics, the staggering advances of photonic integration and the enhanced multiplexing degrees offered by light, neuromorphic photonics has stamped the resurgence of optical computing brining a unique perspective in low-energy and ultra-fast linear algebra functions. However, the field of neuromorphic photonics has relied so far on two basic architectural schemes, i.e., coherent linear optical circuits and incoherent WDM approaches, where wavelengths have still not been exploited as a new mathematical dimension. In this paper, we present a radically new approach for promoting the synergy of WDM with universal linear optics and demonstrate a new, high-fidelity crossbar-based neuromorphic photonic platform, able to support matmul with multidimensional operands. Going a step further, we introduce the concept of programmable input and weight banks, supporting in situ reconfigurability, forming in this way the first WDM-equipped universal linear optical operator and demonstrating different operational modes like matrix-by-matrix and vector-by-tensor multiplication. The benefits of our platform are highlighted in a fully convolutional neural network layout that is responsible for parity identification in the MNIST handwritten digit dataset, with physical layer simulations revealing an accuracy of ∼94%, degraded by only 2% compared to respective results obtained when executed entirely by software. Finally, our in-depth analysis provides the guidelines for neuromorphic photonic processor performance improvement, revealing along the way that 4 bit quantization is sufficient for inputs, whereas the weights can be implemented with as low as 2 bits of precision, offering substantial benefits in terms of driving circuitry complexity and energy savings.
HelixADMET: a robust and endpoint extensible ADMET system incorporating self-supervised knowledge transfer
Authors: Zhang Shanzhuo , Yan Zhiyuan , Huang Yueyang , Liu Lihang , He Donglong , Wang Wei , Fang Xiaomin , Zhang Xiaonan , Wang Fan , Wu Hua , Wang Haifeng 
Published: May 2022

AbstractMotivationAccurate ADMET (an abbreviation for ‘absorption, distribution, metabolism, excretion and toxicity’) predictions can efficiently screen out undesirable drug candidates in the early stage of drug discovery. In recent years, multiple comprehensive ADMET systems that adopt advanced machine learning models have been developed, providing services to estimate multiple endpoints. However, those ADMET systems usually suffer from weak extrapolation ability. First, due to the lack of labelled data for each endpoint, typical machine learning models perform frail for the molecules with unobserved scaffolds. Second, most systems only provide fixed built-in endpoints and cannot be customized to satisfy various research requirements. To this end, we develop a robust and endpoint extensible ADMET system, HelixADMET (H-ADMET). H-ADMET incorporates the concept of self-supervised learning to produce a robust pre-trained model. The model is then fine-tuned with a multi-task and multi-stage framework to transfer knowledge between ADMET endpoints, auxiliary tasks and self-supervised tasks.ResultsOur results demonstrate that H-ADMET achieves an overall improvement of 4%, compared with existing ADMET systems on comparable endpoints. Additionally, the pre-trained model provided by H-ADMET can be fine-tuned to generate new and customized ADMET endpoints, meeting various demands of drug research and development requirements.Availability and implementationH-ADMET is freely accessible at https://paddlehelix.baidu.com/app/drug/admet/train.Supplementary informationSupplementary data are available at Bioinformatics online.
Predicting protein–peptide binding residues via interpretable deep learning
Authors: Wang Ruheng , Jin Junru , Zou Quan , Nakai Kenta , Wei Leyi 
Published: May 2022

AbstractSummaryIdentifying the protein–peptide binding residues is fundamentally important to understand the mechanisms of protein functions and explore drug discovery. Although several computational methods have been developed, most of them highly rely on third-party tools or complex data preprocessing for feature design, easily resulting in low computational efficacy and suffering from low predictive performance. To address the limitations, we propose PepBCL, a novel BERT (Bidirectional Encoder Representation from Transformers) -based contrastive learning framework to predict the protein–peptide binding residues based on protein sequences only. PepBCL is an end-to-end predictive model that is independent of feature engineering. Specifically, we introduce a well pre-trained protein language model that can automatically extract and learn high-latent representations of protein sequences relevant for protein structures and functions. Further, we design a novel contrastive learning module to optimize the feature representations of binding residues underlying the imbalanced dataset. We demonstrate that our proposed method significantly outperforms the state-of-the-art methods under benchmarking comparison, and achieves more robust performance. Moreover, we found that we further improve the performance via the integration of traditional features and our learnt features. Interestingly, the interpretable analysis of our model highlights the flexibility and adaptability of deep learning-based protein language model to capture both conserved and non-conserved sequential characteristics of peptide-binding residues. Finally, to facilitate the use of our method, we establish an online predictive platform as the implementation of the proposed PepBCL, which is now available at http://server.wei-group.net/PepBCL/.Availability and implementationhttps://github.com/Ruheng-W/PepBCL.Supplementary informationSupplementary data are available at Bioinformatics online.
PSMA5 contributes to progression of lung adenocarcinoma in association with the JAK/STAT pathway
Authors: Lu Feng , Zhou Jing , Chen Qing , Zhu Jianling , Zheng Xiaowei , Fang Na , Qiao Ling 
Published: May 2022

Abstract
Proteasome dysregulation is a common feature of cancer and a critical risk for tumorigenesis. However, the characteristics of proteasome components in tumor development and metastasis are poorly understood. PSMA5, an α5 subunit of the 20S core proteasome, is associated with the degradation of intracellular proteins. Increasing evidence indicated that it is involved in tumor development, but the underlying mechanism has remained unknown. Here, we show that PSMA5 is upregulated in lung adenocarcinoma (LUAD) cells and clinical LUAD tissues. Moreover, its upregulation is positively associated with lymph node metastasis and the poor prognosis of LUAD patients. PSMA5 knockdown inhibited the proliferation, invasion and metastasis of LUAD cells in vitro and in vivo, induced apoptosis of LUAD cells and sensitized LUAD cells to cisplatin. Furthermore, investigations revealed that PSMA5 overexpression inhibited cell apoptosis by activating the janus kinase (JAK)/signal transducer and activator of transcription (STAT) signaling pathway in LUAD cells. In total, our results demonstrate that PSMA5 may function as a prognostic factor in LUAD. In addition, PSMA5 is a promising therapeutic target for LUAD, as its depletion induces cell apoptosis by inhibiting the JAK/STAT pathway.
Multimodal deep learning enhances diagnostic precision in left ventricular hypertrophy
Authors: Soto Jessica Torres , Weston Hughes J , Sanchez Pablo Amador , Perez Marco , Ouyang David , Ashley Euan A 
Published: May 2022

Abstract

Aims
Determining the aetiology of left ventricular hypertrophy (LVH) can be challenging due to the similarity in clinical presentation and cardiac morphological features of diverse causes of disease. In particular, distinguishing individuals with hypertrophic cardiomyopathy (HCM) from the much larger set of individuals with manifest or occult hypertension (HTN) is of major importance for family screening and the prevention of sudden death. We hypothesized that an artificial intelligence method based joint interpretation of 12-lead electrocardiograms and echocardiogram videos could augment physician interpretation.

Methods and results
We chose not to train on proximate data labels such as physician over-reads of ECGs or echocardiograms but instead took advantage of electronic health record derived clinical blood pressure measurements and diagnostic consensus (often including molecular testing) among physicians in an HCM centre of excellence. Using more than 18 000 combined instances of electrocardiograms and echocardiograms from 2728 patients, we developed LVH-fusion. On held-out test data, LVH-fusion achieved an F1-score of 0.71 in predicting HCM, and 0.96 in predicting HTN. In head-to-head comparison with human readers LVH-fusion had higher sensitivity and specificity rates than its human counterparts. Finally, we use explainability techniques to investigate local and global features that positively and negatively impact LVH-fusion prediction estimates providing confirmation from unsupervised analysis the diagnostic power of lateral T-wave inversion on the ECG and proximal septal hypertrophy on the echocardiogram for HCM.

Conclusion
These results show that deep learning can provide effective physician augmentation in the face of a common diagnostic dilemma with far reaching implications for the prevention of sudden cardiac death.
Mastigocoleidae fam. nov., a New Mesozoic Beetle Family and the Early Evolution of Dryopoidea (Coleoptera)
Authors: Tihelka Erik , Jäch Manfred A , Kundrata Robin , Li Yan-Da , Engel Michael S , Lozano-Fernandez Jesus , Huang Diying , Cai Chenyang 
Published: May 2022

AbstractWith some 3,700 described species, Dryopoidea are a moderately diverse superfamily of beetles whose position within basal Polyphaga has been historically difficult to elucidate. Members of most extant dryopoid families are set apart from the majority of other polyphagans by their association with aquatic habitats, but little is known about the origin of these derived life habits and the phylogeny of the superfamily. Here we describe Mastigocoleidae Tihelka, Jäch, Kundrata & Cai fam. nov., a new family of Mesozoic dryopoids represented by fossils from the Cretaceous Yixian Formation in northeastern China (undescribed species; ~125 Ma), Crato Formation in northeastern Brazil (Mastigocoleus rhinoceros Tihelka & Cai gen. et sp. nov.; ~113 Ma), and amber from northern Myanmar (Mastigocoleus resinicola Tihelka & Cai gen. et sp. nov. and Cretaceocoleus saetosus Tihelka, Kundrata & Cai gen. et sp. nov.; ~99 Ma). Integrating the findings of recent molecular and morphological phylogenetic analyses, we recover Mastigocoleidae as an early-diverging dryopoid clade sister to the families Lutrochidae and Dryopidae, or less likely as a group of putative stem-dryopoids. Mastigocoleidae are most distinctly separated from all other dryopoid families by their whip-like antennae, with 11 antennomeres, reaching to the pronotal base, and with the scape broadest and longest, a short pedicel, and antennomeres II–XI more or less distinctively gradually tapering toward the apex. Mastigocoleidae indicate that the last common ancestor of Dryopoidea was likely terrestrial in the adult stage, and document character acquisitions associated with a specialization for aquatic life.
Detection of Common Copy Number of Variants Underlying Selection Pressure in Middle Eastern Horse Breeds Using Whole-Genome Sequence Data
Authors: Zandi Mohammad Bagher , Salek Ardestani Siavash , Vahedi Seyed Milad , Mahboudi Hossein , Mahboudi Fereidoun , Meskoob Ardeshir 
Published: May 2022

AbstractDareshouri, Arabian, and Akhal-Teke are 3 Middle Eastern horse breeds that have been selected for endurance and adaptation to harsh climates. Deciphering the genetic characteristics of these horses by tracing selection footprints and copy number of variations will be helpful in improving our understanding of equine breeds’ development and adaptation. For this purpose, we sequenced the whole genome of 4 Dareshouri horses using Illumina Hiseq panels and compared them with publicly available whole-genome sequences of Arabian (n = 3) and Akhal-Teke (n = 3) horses. Three tests of FLK, hapFLK, and pooled heterozygosity were applied using a sliding window (window size = 100 kb, step size = 50 kb) approach to detect putative selection signals. Copy number variation analysis was applied to investigate copy number of variants (CNVs), and the results were used to suggest selection signatures involving CNVs. Whole-genome sequencing demonstrated 8 837 950 single-nucleotide polymorphisms (SNPs) in autosomal chromosomes. We suggested 58 genes and 3 quantitative trait loci, including some related to horse gait, insect bite hypersensitivity, and withers height, based on selective signals detected by adjusted P-value of Mahalanobis distance based on the rank-based P-values (Md-rank-P) method. We proposed 12 genomic regions under selection pressure involving CNVs that were previously reported to be associated with metabolism energy (SLC5A8), champagne dilution in horses (SLC36A1), and synthesis of polyunsaturated fatty acids (FAT2). Only 10 Middle Eastern horses were tested in this study; therefore, the conclusions are speculative. Our findings are useful to better understanding the evolution and adaptation of Middle Eastern horse breeds.
Plant cell division from the perspective of polarity
Authors: Glanc Matouš 
Published: May 2022

AbstractThe orientation of cell division is a major determinant of plant morphogenesis. In spite of considerable efforts over the past decades, the precise mechanism of division plane selection remains elusive. The majority of studies on the topic have addressed division orientation from either a predominantly developmental or a cell biological perspective. Thus, mechanistic insights into the links between developmental and cellular factors affecting division orientation are particularly lacking. Here, I review recent progress in the understanding of cell division orientation in the embryo and primary root meristem of Arabidopsis from both developmental and cell biological standpoints. I offer a view of multilevel polarity as a central aspect of cell division: on the one hand, the division plane is a readout of tissue- and organism-wide polarities; on the other hand, the cortical division zone can be seen as a transient polar subcellular plasma membrane domain. Finally, I argue that a polarity-focused conceptual framework and the integration of developmental and cell biological approaches hold great promise to unravel the mechanistic basis of plant cell division orientation in the near future.
Precipitation and local environment shape the geographic variation of seed size across natural populations of sand rice (Agriophyllum squarrosum)
Authors: Zhao Pengshan , Li Xiaofeng , Ran Ruilan , Sun Hong , Zhao Jiecai , Chen Guoxiong 
Published: May 2022

Abstract
Sand rice (Agriophyllum squarrosum) is widely distributed on dunes in the Asian interior arid zone, and its large intraspecific trait variation makes it a very good model for investigating the ecological processes underlying its adaptation to the desert environment. In this study, seed size variation across 68 natural populations was used to establish geographic patterns and to quantify the effects of the climate, soil, and collection-year weather variables. The length of the seed major axis and thousand seed weight (TSW) both showed significant longitudinal patterns. Long-term climate variables accounted for most of the explained variances for seed major axis (57.20%) and TSW (91.54%). Specifically, annual precipitation and minimum monthly precipitation had the most significantly positive and negative effects, indicating that longitudinal clines are driven by a precipitation gradient across the species’ distribution range. A substantial unique effect of soil variables (27.27%) was found for seed major axis variation, but only 3.64% of TSW variation was explained by soil variables. Two extreme groups were selected to evaluate the genetic and plastic effects on seed size in a common garden experiment. Large-seeded individuals were more competitive in semi-arid regions, and had stronger adaptive plasticity as well as better performance in early seedling establishment, and hence they have potential for use in future domestication projects.
Turbulent dynamo in the two-phase interstellar medium
Authors: Seta Amit , Federrath Christoph 
Published: May 2022

ABSTRACTMagnetic fields are a dynamically important component of the turbulent interstellar medium (ISM) of star-forming galaxies. These magnetic fields are due to a dynamo action, which is a process of converting turbulent kinetic energy to magnetic energy. A dynamo that acts at scales less than the turbulent driving scale is known as the turbulent dynamo. The ISM is a multiphase medium and observations suggest that the properties of magnetic fields differ with the phase. Here, we aim to study how the properties of the turbulent dynamo depend on the phase. We simulate the non-isothermal turbulent dynamo in a two-phase medium (most previous work assumes an isothermal gas). We show that the warm phase (T ≥ 103 K) is transsonic and the cold phase (T &lt; 103 K) is supersonic. We find that the growth rate of magnetic fields in the exponentially growing stage is similar in both phases. We compute the terms responsible for amplification and destruction of vorticity and show that in both phases vorticity is amplified due to turbulent motions, further amplified by the baroclinic term in the warm phase, and destroyed by the term for viscous interactions in the presence of logarithmic density gradients in the cold phase. We find that the final ratio of magnetic to turbulent kinetic energy is lower in the cold phase due to a stronger Lorentz force. We show that the non-isothermal turbulent dynamo is significantly different from its isothermal counterpart and this demonstrates the need for studying the turbulent dynamo in a multiphase medium.
Disc instability and bar formation: view from the IllustrisTNG simulations
Authors: Izquierdo-Villalba David , Bonoli Silvia , Rosas-Guevara Yetli , Springel Volker , White Simon D M , Zana Tommaso , Dotti Massimo , Spinoso Daniele , Bonetti Matteo , Lupi Alessandro 
Published: May 2022

ABSTRACT
We make use of $z\, {=}\, 0$ samples of strongly barred and unbarred disc galaxies from the TNG100 and TNG50 cosmological hydrodynamical simulations to assess the performance of the simple disc instability criterion proposed by Efstathiou, Lake & Negroponte (1982) (ELN-criterion). We find that strongly barred galaxies generally assemble earlier, are more star dominated in their central regions, and have more massive and more compact discs than unbarred galaxies. The ELN-criterion successfully identifies ${\sim }\, 75$ and ${\sim }\, 80{{ per\ cent}}$ of the strongly barred and the unbarred galaxies, respectively. Strongly barred galaxies that the criterion fails to identify tend to have more extended discs, higher spin values and bars that assembled later than is typical for the bulk of the barred population. The bars in many of these cases appear to be produced by an interaction with a close neighbour (i.e. to be externally triggered) rather than to result from secular growth in the disc. On the other hand, we find that unbarred galaxies misclassified as barred by the ELN-criterion typically have stellar discs similar to those of barred galaxies, although more extended in the vertical direction and less star-dominated in their central regions, possibly reflecting later formation times. In addition, the bulge component of these galaxies is significantly more prominent at early times than in the strongly barred sample. Thus, the ELN-criterion robustly identifies secular bar instabilities in most simulated disc galaxies, but additional environmental criteria are needed to account for interaction-induced bar formation.