bluuebunny/crossref_metadata_2025_split huggingface dataset:
Predicting stable crystalline compounds using chemical similarity
Authors: Wang Hai-Chen , Botti Silvana , Marques Miguel A. L. 
Published: January 2021

AbstractWe propose an efficient high-throughput scheme for the discovery of stable crystalline phases. Our approach is based on the transmutation of known compounds, through the substitution of atoms in the crystal structure with chemically similar ones. The concept of similarity is defined quantitatively using a measure of chemical replaceability, extracted by data-mining experimental databases. In this way we build 189,981 possible crystal phases, including 18,479 that are on the convex hull of stability. The resulting success rate of 9.72% is at least one order of magnitude better than the usual success rate of systematic high-throughput calculations for a specific family of materials, and comparable with speed-up factors of machine learning filtering procedures. As a characterization of the set of 18,479 stable compounds, we calculate their electronic band gaps, magnetic moments, and hardness. Our approach, that can be used as a filter on top of any high-throughput scheme, enables us to efficiently extract stable compounds from tremendously large initial sets, without any initial assumption on their crystal structures or chemical compositions.
The complementary graphene growth and etching revealed by large-scale kinetic Monte Carlo simulation
Authors: Kong Xiao , Zhuang Jianing , Zhu Liyan , Ding Feng 
Published: January 2021

AbstractTo fully understand the kinetics of graphene growth, large-scale atomic simulations of graphene islands evolution up to macro sizes (i.e., graphene islands of a few micrometers or with billions of carbon atoms) during growth and etching is essential, but remains a great challenge. In this paper, we developed a low computational cost large-scale kinetic Monte Carlo (KMC) algorithm, which includes all possible events of carbon attachments and detachments on various edge sites of graphene islands. Such a method allows us to simulate the evolution of graphene islands with sizes up to tens of micrometers during either growth or etching with a single CPU core. With this approach and the carefully fitted parameters, we have reproduced the experimentally observed evolution of graphene islands during both growth or etching on Pt(111) surface, and revealed more atomic details of graphene growth and etching. Based on the atomic simulations, we discovered a complementary relationship of graphene growth and etching—the route of graphene island shape evolution during growth is exactly the same as that of the etching of a hole in graphene and that of graphene island etching is exactly same as that of hole growth. The complementary relation brings us a basic principle to understand the growth and etching of graphene, and other 2D materials from atomic scale to macro size and the KMC algorithm is expected to be further developed into a standard simulation package for investigating the growth mechanism of 2D materials on various substrates.
A deep learning-based model for screening and staging pneumoconiosis
Authors: Zhang Liuzhuo , Rong Ruichen , Li Qiwei , Yang Donghan M. , Yao Bo , Luo Danni , Zhang Xiong , Zhu Xianfeng , Luo Jun , Liu Yongquan , Yang Xinyue , Ji Xiang , Liu Zhidong , Xie Yang , Sha Yan , Li Zhimin , Xiao Guanghua 
Published: January 2021

AbstractThis study aims to develop an artificial intelligence (AI)-based model to assist radiologists in pneumoconiosis screening and staging using chest radiographs. The model, based on chest radiographs, was developed using a training cohort and validated using an independent test cohort. Every image in the training and test datasets were labeled by experienced radiologists in a double-blinded fashion. The computational model started by segmenting the lung field into six subregions. Then, convolutional neural network classification model was used to predict the opacity level for each subregion respectively. Finally, the diagnosis for each subject (normal, stage I, II, or III pneumoconiosis) was determined by summarizing the subregion-based prediction results. For the independent test cohort, pneumoconiosis screening accuracy was 0.973, with both sensitivity and specificity greater than 0.97. The accuracy for pneumoconiosis staging was 0.927, better than that achieved by two groups of radiologists (0.87 and 0.84, respectively). This study develops a deep learning-based model for screening and staging of pneumoconiosis using man-annotated chest radiographs. The model outperformed two groups of radiologists in the accuracy of pneumoconiosis staging. This pioneer work demonstrates the feasibility and efficiency of AI-assisted radiography screening and diagnosis in occupational lung diseases.
Enhanced laser-driven proton acceleration using nanowire targets
Authors: Vallières S. , Salvadori M. , Permogorov A. , Cantono G. , Svendsen K. , Chen Z. , Sun S. , Consoli F. , d’Humières E. , Wahlström C.-G. , Antici P. 
Published: January 2021

AbstractLaser-driven proton acceleration is a growing field of interest in the high-power laser community. One of the big challenges related to the most routinely used laser-driven ion acceleration mechanism, Target-Normal Sheath Acceleration (TNSA), is to enhance the laser-to-proton energy transfer such as to maximize the proton kinetic energy and number. A way to achieve this is using nanostructured target surfaces in the laser-matter interaction. In this paper, we show that nanowire structures can increase the maximum proton energy by a factor of two, triple the proton temperature and boost the proton numbers, in a campaign performed on the ultra-high contrast 10 TW laser at the Lund Laser Center (LLC). The optimal nanowire length, generating maximum proton energies around 6 MeV, is around 1–2 $$\upmu$$
μ
m. This nanowire length is sufficient to form well-defined highly-absorptive NW forests and short enough to minimize the energy loss of hot electrons going through the target bulk. Results are further supported by Particle-In-Cell simulations. Systematically analyzing nanowire length, diameter and gap size, we examine the underlying physical mechanisms that are provoking the enhancement of the longitudinal accelerating electric field. The parameter scan analysis shows that optimizing the spatial gap between the nanowires leads to larger enhancement than by the nanowire diameter and length, through increased electron heating.
Role of subnetworks mediated by $$\hbox {TNF}\alpha$$, IL-23/IL-17 and IL-15 in a network involved in the pathogenesis of psoriasis
Authors: Pandey Rakesh , Al-Nuaimi Yusur , Mishra Rajiv Kumar , Spurgeon Sarah K. , Goodfellow Marc 
Published: January 2021

AbstractPsoriasis is a chronic inflammatory skin disease clinically characterized by the appearance of red colored, well-demarcated plaques with thickened skin and with silvery scales. Recent studies have established the involvement of a complex signalling network of interactions between cytokines, immune cells and skin cells called keratinocytes. Keratinocytes form the cells of the outermost layer of the skin (epidermis). Visible plaques in psoriasis are developed due to the fast proliferation and unusual differentiation of keratinocyte cells. Despite that, the exact mechanism of the appearance of these plaques in the cytokine-immune cell network is not clear. A mathematical model embodying interactions between key immune cells believed to be involved in psoriasis, keratinocytes and relevant cytokines has been developed. The complex network formed of these interactions poses several challenges. Here, we choose to study subnetworks of this complex network and initially focus on interactions involving $$\hbox {TNF}_{\alpha }$$

TNF
α

, IL-23/IL-17, and IL-15. These are chosen based on known evidence of their therapeutic efficacy. In addition, we explore the role of IL-15 in the pathogenesis of psoriasis and its potential as a future drug target for a novel treatment option. We perform steady state analyses for these subnetworks and demonstrate that the interactions between cells, driven by cytokines could cause the emergence of a psoriasis state (hyper-proliferation of keratinocytes) when levels of $$\hbox {TNF}_{\alpha }$$

TNF
α

, IL-23/IL-17 or IL-15 are increased. The model results explain and support the clinical potentiality of anti-cytokine treatments. Interestingly, our results suggest different dynamic scenarios underpin the pathogenesis of psoriasis, depending upon the dominant cytokines of subnetworks. We observed that the increase in the level of IL-23/IL-17 and IL-15 could lead to psoriasis via a bistable route, whereas an increase in the level of $$\hbox {TNF}_{\alpha }$$

TNF
α

would lead to a monotonic and gradual disease progression. Further, we demonstrate how this insight, bistability, could be exploited to improve the current therapies and develop novel treatment strategies for psoriasis.
Wettability of semispherical droplets on layered elastic gradient soft substrates
Authors: Yang Yonglin , Li Xing , Wang Wenshuai 
Published: January 2021

AbstractResearch on the wettability of soft matter is one of the most urgently needed studies in the frontier domains, of which the wetting phenomenon of droplets on soft substrates is a hot subject. Scholars have done considerable studies on the wetting phenomenon of single-layer structure, but it is noted that the wetting phenomenon of stratified structure is ubiquitous in nature, such as oil exploitation from geological structural layers and shale gas recovery from shale formations. Therefore, the wettability of droplets on layered elastic gradient soft substrate is studied in this paper. Firstly, considering capillary force, elastic force and surface tension, the constitutive equation of the substrate in the vector function system is derived by using the vector function system in cylindrical coordinates, and the transfer relation of layered structure is obtained. Further, the integral expressions of displacement and stress of double Bessel function are given. Secondly, the numerical results of displacement and stress are obtained by using the numerical formula of double Bessel function integral. The results show that the deformation of the substrate weakens with the increase of the elastic modulus, also the displacement and stress change dramatically near the contact line, while the variation is flat when the contact radius is far away from the droplet radius.
Early production of table olives at a mid-7th millennium BP submerged site off the Carmel coast (Israel)
Authors: Galili E. , Langgut D. , Terral J. F. , Barazani O. , Dag A. , Kolska Horwitz L. , Ogloblin Ramirez I. , Rosen B. , Weinstein-Evron M. , Chaim S. , Kremer E. , Lev-Yadun S. , Boaretto E. , Ben-Barak-Zelas Z. , Fishman A. 
Published: January 2021

AbstractWe present here the earliest evidence for large-scale table olive production from the mid-7thmillennium BP inundated site of Hishuley Carmel on the northern Mediterranean coast of Israel. Olive pit size and fragmentation patterns, pollen as well as the architecture of installations associated with pits from this site, were compared to finds from the nearby and slightly earlier submerged Kfar Samir site. Results indicate that at Kfar Samir olive oil was extracted, while at Hishuley Carmel the data showed that large quantities of table olives, the oldest reported to date, were prepared. This process was most probably facilitated by the site’s proximity to the Mediterranean Sea, which served as a source of both sea water and salt required for debittering/pickling/salting the fruit, as experimentally demonstrated in this study. Comparison of pit morphometry from modern cultivars, wild-growing trees and the archaeological sites, intimates that in pit morphology the ancient pits resemble wild olives, but we cannot totally exclude the possibility that they derive from early cultivated trees. Our findings demonstrate that in this region, olive oil production may have predated table olive preparation, with each development serving as a milestone in the early exploitation of the olive.
High sensitivity rate-integrating hemispherical resonator gyroscope with dead area compensation for damping asymmetry
Authors: Zhao Wanliang , Yang Hao , Liu Fucheng , Su Yan , Li Chong 
Published: January 2021

AbstractThe rate-integrating gyroscope (RIG) operation is considered as the next generation architecture for hemispherical resonator gyroscopes (HRGs) with advantages of direct angle measurement and unlimited dynamic range. However, this RIG operation requires high symmetry for the HRG device and the damping mismatch of the two gyroscopic modes will result in a dead area problem. This work analyzes the error mechanism of the damping asymmetry induced dead area and proposed a novel virtual procession compensation method for HRG RIG. The simulation proves the existence of the dead area as the theory predicted. More importantly, the experimental HRG RIG platform with the proposed compensation method can significantly expand the dynamic range with accurate angle measurement and overcome the problem of dead area. The earth rotation is accurate measured which is the first time that captured by a RIG scheme as a state-of-the-art result.
Chronic BDNF simultaneously inhibits and unmasks superficial dorsal horn neuronal activity
Authors: Alles Sascha R. A. , Odem Max A. , Lu Van B. , Cassidy Ryan M. , Smith Peter A. 
Published: January 2021

AbstractBrain-derived neurotrophic factor (BDNF) is critically involved in the pathophysiology of chronic pain. However, the mechanisms of BDNF action on specific neuronal populations in the spinal superficial dorsal horn (SDH) requires further study. We used chronic BDNF treatment (200 ng/ml, 5–6 days) of defined-medium, serum-free spinal organotypic cultures to study intracellular calcium ([Ca2+]i) fluctuations. A detailed quantitative analysis of these fluctuations using the Frequency-independent biological signal identification (FIBSI) program revealed that BDNF simultaneously depressed activity in some SDH neurons while it unmasked a particular subpopulation of ‘silent’ neurons causing them to become spontaneously active. Blockade of gap junctions disinhibited a subpopulation of SDH neurons and reduced BDNF-induced synchrony in BDNF-treated cultures. BDNF reduced neuronal excitability assessed by measuring spontaneous excitatory postsynaptic currents. This was similar to the depressive effect of BDNF on the [Ca2+]i fluctuations. This study reveals novel regulatory mechanisms of SDH neuronal excitability in response to BDNF.
Reduction of pTau and APP levels in mammalian brain after low-dose radiation
Authors: Iacono Diego , Murphy Erin K. , Avantsa Soundarya S. , Perl Daniel P. , Day Regina M. 
Published: January 2021

AbstractBrain radiation can occur from treatment of brain tumors or accidental exposures. Brain radiation has been rarely considered, though, as a possible tool to alter protein levels involved in neurodegenerative disorders. We analyzed possible molecular and neuropathology changes of phosphorylated-Tau (pTau), all-Tau forms, β-tubulin, amyloid precursor protein (APP), glial fibrillary acidic protein (GFAP), ionized calcium binding adaptor molecule 1 (IBA-1), myelin basic protein (MBP), and GAP43 in Frontal Cortex (FC), Hippocampus (H) and Cerebellum (CRB) of swine brains following total-body low-dose radiation (1.79 Gy). Our data show that radiated-animals had lower levels of pTau in FC and H, APP in H and CRB, GAP43 in CRB, and higher level of GFAP in H versus sham-animals. These molecular changes were not accompanied by obvious neurohistological changes, except for astrogliosis in the H. These findings are novel, and might open new perspectives on brain radiation as a potential tool to interfere with the accumulation of specific proteins linked to the pathogenesis of various neurodegenerative disorders.
Towards bio-inspired artificial muscle: a mechanism based on electro-osmotic flow simulated using dissipative particle dynamics
Authors: Zakeri Ramin 
Published: January 2021

AbstractOne of the unresolved issues in physiology is how exactly myosin moves in a filament as the smallest responsible organ for contracting of a natural muscle. In this research, inspired by nature, a model is presented consisting of DPD (dissipative particle dynamics) particles driven by electro-osmotic flow (EOF) in micro channel that a thin movable impermeable polymer membrane has been attached across channel width, thus momentum of fluid can directly transfer to myosin stem. At the first, by validation of electro-osmotic flow in micro channel in different conditions with accuracy of less than 10 percentage error compared to analytical results, the DPD results have been developed to displacement of an impermeable polymer membrane in EOF. It has been shown that by the presence of electric field of 250 V/m and Zeta potential − 25 mV and the dimensionless ratio of the channel width to the thickness of the electric double layer or kH = 8, about 15% displacement in 8 s time will be obtained compared to channel width. The influential parameters on the displacement of the polymer membrane from DPD particles in EOF such as changes in electric field, ion concentration, zeta potential effect, polymer material and the amount of membrane elasticity have been investigated which in each cases, the radius of gyration and auto correlation velocity of different polymer membrane cases have been compared together. This simulation method in addition of probably helping understand natural myosin displacement mechanism, can be extended to design the contraction of an artificial muscle tissue close to nature.
Best influential spreaders identification using network global structural properties
Authors: Namtirtha Amrita , Dutta Animesh , Dutta Biswanath , Sundararajan Amritha , Simmhan Yogesh 
Published: January 2021

AbstractInfluential spreaders are the crucial nodes in a complex network that can act as a controller or a maximizer of a spreading process. For example, we can control the virus propagation in an epidemiological network by controlling the behavior of such influential nodes, and amplify the information propagation in a social network by using them as a maximizer. Many indexing methods have been proposed in the literature to identify the influential spreaders in a network. Nevertheless, we have notice that each individual network holds different connectivity structures that we classify as complete, incomplete, or in-between based on their components and density. These affect the accuracy of existing indexing methods in the identification of the best influential spreaders. Thus, no single indexing strategy is sufficient from all varieties of network connectivity structures. This article proposes a new indexing methodNetwork Global Structure-based Centrality(ngsc) which intelligently combines existing kshell and sum of neighbors’ degree methods with knowledge of the network’s global structural properties, such as the giant component, average degree, and percolation threshold. The experimental results show that our proposed method yields a better spreading performance of the seed spreaders over a large variety of network connectivity structures, and correlates well with ranking based on an SIR model used as ground truth. It also out-performs contemporary techniques and is competitive with more sophisticated approaches that are computationally cost.
Transmission of Metarhizium anisopliae and Beauveria bassiana to adults of Kuschelorhynchus macadamiae (Coleoptera: Curculionidae) from infected adults and conidiated cadavers
Authors: Khun Kim Khuy , Ash Gavin J. , Stevens Mark M. , Huwer Ruth K. , Wilson Bree A. L. 
Published: January 2021

AbstractKuschelorhynchus macadamiae is a major pest of macadamias in Australia, causing yield losses of up to 15%. Our previous studies have shown the weevil is susceptible to Beauveria bassiana and Metarhizium anisopliae. The aim of this study was to investigate horizontal transmission of both fungal species to healthy weevils from both infected adults and weevil cadavers. In a confined environment the mortality of healthy adults caused by the transmission of conidia from live fungus-infected adults was < 50%. Under similar experimental conditions, the mortality of healthy adults reached 100% when exposed to conidiated cadavers. However, when conidiated cadavers were used in more spacious environments (insect cages), the mortality of adults was < 80%. Using scanning electron microscopy, it was observed that all healthy adults had conidia attached to all external parts of the body. This suggests that although the conidia were readily transferred to the adults, the lower mortality in the larger insect cages could be the result of an unfavourable environmental factor such as low humidity. The presence of conidia attached to all the adults indicated that they did not show any discriminatory behaviour such as avoidance of conidiated cadavers infected by these two fungal species. The results from this study show that there is potential for enhanced control of adult K. macadamiae via transmission from either fungus-infected adults or conidiated cadavers and this could strengthen sustainable pest management in macadamias.
Impact on genetic differences among various chicken breeds on free amino acid contents of egg yolk and albumen
Authors: Goto Tatsuhiko , Shimamoto Saki , Takaya Masahiro , Sato Shun , Takahashi Kanna , Nishimura Kenji , Morii Yasuko , Kunishige Kyoko , Ohtsuka Akira , Ijiri Daichi 
Published: January 2021

AbstractEggs play important roles as food resources and nutraceuticals, to alleviate malnutrition and to improve health status in the world. Since free amino acids contribute to the nutritional values and food tastes, we investigated a total of 81 eggs from five chicken breeds, which are Australorp, Nagoya (NGY), Rhode Island Red (RIR), Shamo (SHA), Ukokkei, and two F1 hybrids (NGYxRIR and SHAxRIR) to test impact on genetic differences in 10 egg traits, 20 yolk amino acid traits, and 18 albumen amino acid traits. One-way ANOVA revealed significant breed effects on 10 egg traits, 20 yolk amino acid traits, and 15 albumen amino acid traits. Moreover, a significant heterosis effect on yolk aspartic acid was identified. In addition, positive correlations were found broadly among traits within each trait category (egg traits, yolk amino acid traits, and albumen amino acid traits), whereas there were basically no or weak correlations among the trait categories. These results suggest that almost all traits can be dramatically modified by genetic factor, and there will be partially independent production systems of amino acids into yolk and albumen. Since there will be typical quantitative genetic architecture of egg contents, further genetic analyses will be needed.