bluuebunny/crossref_metadata_2025_split huggingface dataset:
RETRACTED ARTICLE: Enhanced approach using trust based decision making for secured wireless streaming video sensor networks
Authors: Ramesh S. , Yaashuwanth C. 
Published: April 2019

AbstractThe advances in the expanse of image sensors have made it conceivable to make high-resolution picture sensors easily accessible. The amelioration of wireless interactive media sensor networks are found to be greatly increased due to the day to day usage of cameras, microphones and smart devices. A secured multi-hop routing mechanism is addressed in surveillance areas which could be incorporated to the multimedia sensors that are capable of peruse the detected data comprises of recorded images and videos. Also, malevolent sensor hubs could be interjected into the vigilance area in an untrusted environment. In this contemplated venture, a novel lightweight trust decision-making framework is accomplished for QoS clustering to give secure routing in both intercluster and intracluster communication. A quantifiable aberrant trust value is the variable determined by the Cluster Head (CH) for its Cluster Member (CM) inside the cluster. The LEACH (Low Energy Adaptive Clustering Hierarchy) protocol is adopted for group formation and also for the exchange of the trust values among the master nodes, member nodes and Base station. In this way, the correspondence overhead, likelihood of dynamic assaults for example sinkhole and black hole assaults mount by eavesdroppers can be reduced by maintenance of trust values by cluster heads rather than cluster members. Besides, in wireless streaming video sensor networks this approach authorizes us to predict and counteract malicious untrusted and flawed nodes. Simulation results using NS-2 is examined and the suggested trust decision-making model escalates the dependability, elasticity and low memory aloft in comparison with the current trust models adopted for wireless video sensor network security.
Colonial America Today: U.S. Empire and the Political Status of Native American Nations
Authors: Bacon J. M. , Norton Matthew 
Published: April 2019

AbstractThe article systematically assesses U.S.-Native relations today and their historical foundations in light of a narrow, empirical definition of colonial empire. Examining three core elements of colonial empire—the formal impairment of sovereignty, the intensive practical impairment of sovereignty through practices of governance and administration, and the continuing otherness of the dominated and dominant groups—we compare contemporary U.S.-Native political relations to canonical instances of formal colonial indirect rule empires. Based on this analysis, we argue that the United States today is a paradigmatic case of formal colonial empire in the narrow, traditional sense, one that should be better integrated into the comparative, historical, and sociological study of such formal empires. Furthermore, this prominent contemporary case stands against the idea that the era of formal colonial empire is over.
Predictive models and abstract argumentation: the case of high-complexity semantics
Authors: Vallati Mauro , Cerutti Federico , Giacomin Massimiliano 
Published: April 2019

AbstractIn this paper, we describe how predictive models can be positively exploited in abstract argumentation. In particular, we present two main sets of results. On one side, we show that predictive models are effective for performing algorithm selection in order to determine which approach is better to enumerate the preferred extensions of a given argumentation framework. On the other side, we show that predictive models predict significant aspects of the solution to the preferred extensions enumeration problem. By exploiting an extensive set of argumentation framework features—that is, values that summarize a potentially important property of a framework—the proposed approach is able to provide an accurate prediction about which algorithm would be faster on a given problem instance, as well as of the structure of the solution, where the complete knowledge of such structure would require a computationally hard problem to be solved. Improving the ability of existing argumentation-based systems to support human sense-making and decision processes is just one of the possible exploitations of such knowledge obtained in an inexpensive way.
Numerical Modeling of the Propagation of Infrasonic Acoustic Waves Through the Turbulent Field Generated by the Breaking of Mountain Gravity Waves
Authors: Sabatini R. , Snively J. B. , Bailly C. , Hickey M. P. , Garrison J. L. 
Published: April 2019

AbstractThe nonlinear propagation of low‐frequency acoustic waves through the turbulent fluctuations induced by breaking mountain gravity waves is investigated via 2‐D numerical simulations of the Navier‐Stokes equations, to understand the effects of atmospheric dynamics on ground‐based infrasound measurements. Emphasis is placed on acoustic signals of frequency around 0.1 Hz, traveling through tens‐of‐kilometers‐scale gravity waves and subkilometer‐scale turbulence. The sensitivity of the infrasonic phases to small‐scale fluctuations is found to depend on the altitudes through which they are refracted toward the Earth. For the considered cases, the dynamics in the stratosphere impact the refracting acoustic waves to a greater extent than those in the thermosphere. This work clearly demonstrates the need for accurate descriptions of the effects of atmospheric dynamics on acoustic propagation, such as here captured by the full set of fluid dynamic equations, as well as of the subsequent effects on measured signals.
Nicotinamide mononucleotide promotes osteogenesis and reduces adipogenesis by regulating mesenchymal stromal cells via the SIRT1 pathway in aged bone marrow
Authors: Song Jie , Li Jing , Yang Fangji , Ning Gang , Zhen Limin , Wu Lina , Zheng Yongyuan , Zhang Qi , Lin Dongjun , Xie Chan , Peng Liang 
Published: April 2019

AbstractMesenchymal stromal cells (MSCs) can differentiate to various cell types including osteoblasts, chondrocytes, and adipocytes. This cellular flexibility contributes to widespread clinical use of MSCs in tissue repair. However, challenges remain in efficient cellular expansion of MSCs for stem cell therapy. Current MSC culture methods have resulted in reduced self-renewal of MSCs and compromised therapeutic outcomes. This study identifies that nicotinamide mononucleotide (NMN), a key natural NAD+ intermediate, effectively encourages MSC expansion in vitro and in vivo. The in vitro expanded MSCs had heightened osteogenesis, but reduced adipogenesis. Furthermore, NMN supplementation stimulated osteogenesis of endogenous MSCs, and protected bone from aging and irradiation induced damage in mice. Mechanistically, we found that NMN treatment upregulated SIRT1. Genetically overexpressing SIRT1 in MSCs by using Prx1 cre; ColA1flox-stop-flox-SIRT1 mice promoted osteogenesis and reduced adipogenesis in aged mice. Overall, our data demonstrate that NMN promoted MSC self-renewal with strengthened osteogenesis and reduced adipogenesis via upregulating SIRT1 in aged mice.
Unusual substrate and halide versatility of phenolic halogenase PltM
Authors: Mori Shogo , Pang Allan H. , Thamban Chandrika Nishad , Garneau-Tsodikova Sylvie , Tsodikov Oleg V. 
Published: April 2019

AbstractControlled halogenation of chemically versatile substrates is difficult to achieve. Here we describe a unique flavin-dependent halogenase, PltM, which is capable of utilizing a wide range of halides for installation on a diverse array of phenolic compounds, including FDA-approved drugs and natural products, such as terbutaline, fenoterol, resveratrol, and catechin. Crystal structures of PltM in complex with phloroglucinol and FAD in different states yield insight into substrate recognition and the FAD recycling mechanism of this halogenase.
Author Correction: Environment-responsive nanophores for therapy and treatment monitoring via molecular MRI quenching
Authors: Kaittanis Charalambos , Shaffer Travis M. , Ogirala Anuja , Santra Santimukul , Perez J. Manuel , Chiosis Gabriela , Li Yueming , Josephson Lee , Grimm Jan 
Published: April 2019

This Article contains an error in Figure 6. In panel b, the left-hand image is mistakenly described as showing fluorescence before treatment, while it in fact shows the same white light image as the right-hand panel without fluorescent overlay to better visualize the tumour location. A correct version of Figure 6b is presented in the accompanying Author Correction. The error has not been corrected in the original version of the Article.
Measuring social, environmental and health inequalities using deep learning and street imagery
Authors: Suel Esra , Polak John W. , Bennett James E. , Ezzati Majid 
Published: April 2019

AbstractCities are home to an increasing majority of the world’s population. Currently, it is difficult to track social, economic, environmental and health outcomes in cities with high spatial and temporal resolution, needed to evaluate policies regarding urban inequalities. We applied a deep learning approach to street images for measuring spatial distributions of income, education, unemployment, housing, living environment, health and crime. Our model predicts different outcomes directly from raw images without extracting intermediate user-defined features. To evaluate the performance of the approach, we first trained neural networks on a subset of images from London using ground truth data at high spatial resolution from official statistics. We then compared how trained networks separated the best-off from worst-off deciles for different outcomes in images not used in training. The best performance was achieved for quality of the living environment and mean income. Allocation was least successful for crime and self-reported health (but not objectively measured health). We also evaluated how networks trained in London predict outcomes three other major cities in the UK: Birmingham, Manchester, and Leeds. The transferability analysis showed that networks trained in London, fine-tuned with only 1% of images in other cities, achieved performances similar to ones from trained on data from target cities themselves. Our findings demonstrate that street imagery has the potential complement traditional survey-based and administrative data sources for high-resolution urban surveillance to measure inequalities and monitor the impacts of policies that aim to address them.
Maternal DCAF13 Regulates Chromatin Tightness to Contribute to Embryonic Development
Authors: Liu Yang , Zhao Long-Wen , Shen Jing-Ling , Fan Heng-Yu , Jin Yan 
Published: April 2019

AbstractMaternal-zygotic transition (MZT) is critical for the developmental control handed from maternal products to newly synthesized zygotic genome in the earliest stage of embryogenesis. However, the spatiotemporal dynamic regulation of MZT by maternal factors is largely unknown. Here, we reported a novel maternal factor, DCAF13, which was highly expressed in growing oocyte nucleolus and had key maternal effects on oocyte and zygotic chromatin tightness during maternal to zygotic transition. DCAF13 specifically deleted in oocytes resulted in loose chromatin structure in fully grown germinal vesicle oocytes. Despite normal nuclear maturation in maternal DCAF13-deleted oocytes, the chromosomes at MII stage were not properly condensed. Consequently, the nuclear and nucleolar structure reorganized abnormally, and transcription was inactive in zygotic embryos. RNA-seq analysis of MII oocytes and 2-cell embryos demonstrated that the transcriptomes between knockout and control oocyte were similar, but the maternal DCAF13 deleted two-cell embryos showed a significant decrease in transcription. In addition, the maternal DCAF13-deleted embryos displayed arrest at the two-cell stage, which could not be rescued by injecting flag-Dcaf13 mRNA in the zygote. This revealed that DCAF13 was a unique maternal effect factor regulating the nucleolus.
Universality of size-energy ratio in four-body systems
Authors: Stipanović Petar , Vranješ Markić Leandra , Gudyma Andrii , Boronat Jordi 
Published: April 2019

AbstractUniversal relationship of scaled size and scaled energy, which was previously established for two- and three-body systems in their ground state, is examined for four-body systems, using Quantum Monte Carlo simulations. We study in detail the halo region, in which systems are extremely weakly bound. Strengthening the interparticle interaction we extend the exploration all the way to classical systems. Universal size-energy law is found for homogeneous tetramers in the case of interaction potentials decaying predominantly as r−6. In the case of mixed tetramers, we also show under which conditions the universal line can approximately describe the size-energy ratio. The universal law can be used to extract ground-state energy from experimentally measurable structural characteristics, as well as for evaluation of theoretical interaction models.
Identifying A- and P-site locations on ribosome-protected mRNA fragments using Integer Programming
Authors: Ahmed Nabeel , Sormanni Pietro , Ciryam Prajwal , Vendruscolo Michele , Dobson Christopher M. , O’Brien Edward P. 
Published: April 2019

AbstractIdentifying the A- and P-site locations on ribosome-protected mRNA fragments from Ribo-Seq experiments is a fundamental step in the quantitative analysis of transcriptome-wide translation properties at the codon level. Many analyses of Ribo-Seq data have utilized heuristic approaches applied to a narrow range of fragment sizes to identify the A-site. In this study, we use Integer Programming to identify the A-site by maximizing an objective function that reflects the fact that the ribosome’s A-site on ribosome-protected fragments must reside between the second and stop codons of an mRNA. This identifies the A-site location as a function of the fragment’s size and its 5′ end reading frame in Ribo-Seq data generated from S. cerevisiae and mouse embryonic stem cells. The correctness of the identified A-site locations is demonstrated by showing that this method, as compared to others, yields the largest ribosome density at established stalling sites. By providing greater accuracy and utilization of a wider range of fragment sizes, our approach increases the signal-to-noise ratio of underlying biological signals associated with translation elongation at the codon length scale.
Efficient Deep Network Architectures for Fast Chest X-Ray Tuberculosis Screening and Visualization
Authors: Pasa F. , Golkov V. , Pfeiffer F. , Cremers D. , Pfeiffer D. 
Published: April 2019

AbstractAutomated diagnosis of tuberculosis (TB) from chest X-Rays (CXR) has been tackled with either hand-crafted algorithms or machine learning approaches such as support vector machines (SVMs) and convolutional neural networks (CNNs). Most deep neural network applied to the task of tuberculosis diagnosis have been adapted from natural image classification. These models have a large number of parameters as well as high hardware requirements, which makes them prone to overfitting and harder to deploy in mobile settings. We propose a simple convolutional neural network optimized for the problem which is faster and more efficient than previous models but preserves their accuracy. Moreover, the visualization capabilities of CNNs have not been fully investigated. We test saliency maps and grad-CAMs as tuberculosis visualization methods, and discuss them from a radiological perspective.
Alternative paths to realize Majorana Fermions in Superconductor-Ferromagnet Heterostructures
Authors: Livanas G. , Sigrist M. , Varelogiannis G. 
Published: April 2019

AbstractA fundamental obstacle for achieving quantum computation is local decoherence. One way to circumvent this problem rests on the concepts of topological quantum computation using non-local information storage, for example on pairs of Majorana fermions (MFs). The arguably most promising way to generate MFs relies at present on spin-triplet p-wave states of superconductors (SC), which are not abundant in nature, unfortunately. Thus, proposals for their engineering in devices, usually via proximity effect from a conventional SC into materials with strong spin-orbit coupling (SOC), are intensively investigated nowadays. Here we take an alternative path, exploiting the different connections between fields based on a quartet coupling rule for fields introduced by one of us, we demonstrate that, for instance, coexisting Zeeman field with a charge current would provide the conditions to induce p-wave pairing in the presence of singlet superconductivity. This opens new avenues for the engineering of robust MFs in various, not necessarily (quasi-)one-dimensional, superconductor-ferromagnet heterostructures, including such motivated by recent pioneering experiments that report MFs, in particular, without the need of any exotic materials or special structures of intrinsic SOC.
Elevated carbon dioxide levels lead to proteome-wide alterations for optimal growth of a fast-growing cyanobacterium, Synechococcus elongatus PCC 11801
Authors: Mehta Kanika , Jaiswal Damini , Nayak Monalisha , Prasannan Charulata B. , Wangikar Pramod P. , Srivastava Sanjeeva 
Published: April 2019

AbstractThe environmental considerations attributing to the escalation of carbon dioxide emissions have raised alarmingly. Consequently, the concept of sequestration and biological conversion of CO2 by photosynthetic microorganisms is gaining enormous recognition. In this study, in an attempt to discern the synergistic CO2 tolerance mechanisms, metabolic responses to increasing CO2 concentrations were determined for Synechococcus elongatus PCC 11801, a fast-growing, novel freshwater strain, using quantitative proteomics. The protein expression data revealed that the organism responded to elevated CO2 by not only regulating the cellular transporters involved in carbon-nitrogen uptake and assimilation but also by inducing photosynthesis, carbon fixation and glycolysis. Several components of photosynthetic machinery like photosystem reaction centers, phycobilisomes, cytochromes, etc. showed a marked up-regulation with a concomitant downshift in proteins involved in photoprotection and redox maintenance. Additionally, enzymes belonging to the TCA cycle and oxidative pentose phosphate pathway exhibited a decline in their expression, further highlighting that the demand for reduced cofactors was fulfilled primarily through photosynthesis. The present study brings the first-ever comprehensive assessment of intricate molecular changes in this novel strain while shifting from carbon-limited to carbon-sufficient conditions and may pave the path for future host and pathway engineering for production of sustainable fuels through efficient CO2 capture.
Elevated Glycemic Gap Predicts Acute Respiratory Failure and In-hospital Mortality in Acute Heart Failure Patients with Diabetes
Authors: Liao Wen-I , Wang Jen-Chun , Lin Chin-Sheng , Yang Chih-Jen , Hsu Chia-Ching , Chu Shi-Jye , Chu Chi-Ming , Tsai Shih-Hung 
Published: April 2019

AbstractDiabetes is a common comorbidity in patients hospitalized for acute heart failure (AHF), but the relationship between admission glucose level, glycemic gap, and in-hospital mortality in patients with both conditions has not been investigated thoroughly. Clinical data for admission glucose, glycemic gap and in-hospital death in 425 diabetic patients hospitalized because of AHF were collected retrospectively. Glycemic gap was calculated as the A1c-derived average glucose subtracted from the admission plasma glucose level. Receiver operating characteristic (ROC) curves were used to determine the optimal cutoff value for glycemic gap to predict all-cause mortality. Patients with glycemic gap levels >43 mg/dL had higher rates of all-cause death (adjusted hazard ratio, 7.225, 95% confidence interval, 1.355–38.520) than those with glycemic gap levels ≤43 mg/dL. The B-type natriuretic peptide levels incorporated with glycemic gap could increase the predictive capacity for in-hospital mortality and increase the area under the ROC from 0.764 to 0.805 (net reclassification improvement = 9.9%, p < 0.05). In conclusion, glycemic gap may be considered a useful parameter for predicting the disease severity and prognosis of patients with diabetes hospitalized for AHF.
Fungal hydrophobins render stones impermeable for water but keep them permeable for vapor
Authors: Winandy Lex , Schlebusch Olexandra , Fischer Reinhard 
Published: April 2019

AbstractThe conservation of architectural heritage is a big challenge in times with increasing air pollution with aggressive gases. A second major threat to buildings is the combination of water and air contaminants which may be used by microorganisms for their metabolism. Hence, myriads of different bacteria and fungi populate stone surfaces and penetrate into the fine pores and cracks. Whereas epoxid-based paintings (or other paintings) may protect the coated surfaces from water and aggressive gases, these chemicals seal the stone surface and prevent also the evaporation of vapor from the inside of the buildings. Here, we tested a natural, fungal protein-based coating method. Fungi use small, amphiphilic proteins to turn their surfaces hydrophobic. We found that Aspergillus nidulans hydrophobin DewA and Trichoderma reesei HFBI confer hydrophobicity to stones but keep their pores open. The effect resembles “Gore-tex” fabric material.
Abiotic and biotic stresses induce a core transcriptome response in rice
Authors: Cohen Stephen P. , Leach Jan E. 
Published: April 2019

AbstractEnvironmental stresses greatly limit crop yield. With the increase in extreme weather events due to climate change and the constant pressure of diseases and pests, there is an urgent need to develop crop varieties that can tolerate multiple stresses. However, our knowledge of how plants broadly respond to stress is limited. Here, we explore the rice core stress response via meta-analysis of publicly available rice transcriptome data. Our results confirm that rice universally down-regulates photosynthesis in response to both abiotic and biotic stress. Rice also generally up-regulates hormone-responsive genes during stress response, most notably genes in the abscisic acid, jasmonic acid and salicylic acid pathways. We identified several promoter motifs that are likely involved in stress-responsive regulatory mechanisms in rice. With this work, we provide a list of candidate genes to study for improving rice stress tolerance in light of environmental stresses. This work also serves as a proof of concept to show that meta-analysis of diverse transcriptome data is a valid approach to develop robust hypotheses for how plants respond to stress.