bluuebunny/crossref_metadata_2025_split huggingface dataset:
Multi-exponential error extrapolation and combining error mitigation techniques for NISQ applications
Authors: Cai Zhenyu 
Published: May 2021

AbstractNoise in quantum hardware remains the biggest roadblock for the implementation of quantum computers. To fight the noise in the practical application of near-term quantum computers, instead of relying on quantum error correction which requires large qubit overhead, we turn to quantum error mitigation, in which we make use of extra measurements. Error extrapolation is an error mitigation technique that has been successfully implemented experimentally. Numerical simulation and heuristic arguments have indicated that exponential curves are effective for extrapolation in the large circuit limit with an expected circuit error count around unity. In this Article, we extend this to multi-exponential error extrapolation and provide more rigorous proof for its effectiveness under Pauli noise. This is further validated via our numerical simulations, showing orders of magnitude improvements in the estimation accuracy over single-exponential extrapolation. Moreover, we develop methods to combine error extrapolation with two other error mitigation techniques: quasi-probability and symmetry verification, through exploiting features of these individual techniques. As shown in our simulation, our combined method can achieve low estimation bias with a sampling cost multiple times smaller than quasi-probability while without needing to be able to adjust the hardware error rate as required in canonical error extrapolation.
Quantum nonlocality without entanglement: explicit dependence on prior probabilities of nonorthogonal mirror-symmetric states
Authors: Ha Donghoon , Kwon Younghun 
Published: May 2021

AbstractIn the case of a multi-party system, through local operations and classical communication (LOCC), each party may not perform perfect discrimination of quantum states that are separable and orthogonal. This property of quantum ensemble is called “nonlocality without entanglement” since each local party has a limit to full information of given quantum states. When this property is extended to the case of minimum-error discrimination, one can see that it is revealed when a nonlocal measurement provides more information about the unentangled states than LOCC does. One may infer the fact that the property depends on quantum states composing the quantum ensemble. However, an essential but unsettled question about the property is whether an explicit dependence on prior probabilities in terms of minimum-error discrimination could be shown in nonlocality without entanglement. In a simple term, one can ask whether different quantum ensembles made of the same separable quantum states could exhibit explicitly different behavior of the nonlocality. We answer this question in the positive, and we furthermore provide the explicit functional dependence of guessing probability on prior probabilities for the mirror-symmetric ensemble.
Critical charge fluctuations and emergent coherence in a strongly correlated excitonic insulator
Authors: Volkov P. A. , Ye Mai , Lohani H. , Feldman I. , Kanigel A. , Blumberg G. 
Published: May 2021

AbstractExcitonic insulator is a coherent electronic phase that results from the formation of a macroscopic population of bound particle-hole pairs—excitons. With only a few candidate materials known, the collective excitonic behavior is challenging to observe, being obscured by crystalline lattice effects. Here we use polarization-resolved Raman spectroscopy to reveal the quadrupolar excitonic mode in the candidate zero-gap semiconductor Ta2NiSe5 disentangling it from the lattice phonons. The excitonic mode pronouncedly softens close to the phase transition, showing its electronic character, while its coupling to noncritical lattice modes is shown to enhance the transition temperature. On cooling, we observe the gradual emergence of coherent superpositions of band states at the correlated insulator gap edge, with strong departures from mean-field theory predictions. Our results demonstrate the realization of a strongly correlated excitonic state in an equilibrium bulk material.
Heterogeneity in patterns of helminth infections across populations of mountain gorillas (Gorilla beringei beringei)
Authors: Petrželková Klara J. , Uwamahoro Carine , Pafčo Barbora , Červená Barbora , Samaš Peter , Mudakikwa Antoine , Muvunyi Richard , Uwingeli Prosper , Gilardi Kirsten , Nziza Julius , Noheri Jean Bosco , Eckardt Winnie , Ndagijimana Felix , Ssebide Benard , Okwirokello Ricky , Nizeyimana Fred , Syaluha Eddy Kambale , Nzayisenga Gaspard , Flores Girón Luis , Bahizi Méthode , Ntwari Adrien Emile , Lukusa Jean-Paul , Tumushime Jean Claude , Mangura Damien , Mapilanga Jeff , Kalonji Arthur , Aruho Robert , Stryková Anna , Tehlarová Zuzana , Cameira Rita , Lowenstine Linda , Šlapeta Jan , Romportl Dušan , Ferrari Nicola , Cranfield Michael , Modrý David 
Published: May 2021

AbstractConservation efforts have led to the recovery of the endangered mountain gorilla populations. Due to their limited potential for spatial expansion, population densities increased, which may alter the epidemiology of infectious diseases. Recently, clinical gastrointestinal illnesses linked to helminth infections have been recorded in both gorilla populations. To understand drivers and patterns of helminth infections we quantified strongylid and tapeworm infections across both Virunga Massif and Bwindi populations using fecal egg counts. We assessed the impact of age, sex, group size, season and spatial differences used as a proxy, which reflects observed variation in the occurrence of gastrointestinal problems, vegetation types, gorilla subpopulation growth and associated social structure on helminth infections. We revealed striking geographic differences in strongylid infections with higher egg counts mostly in areas with high occurrences of gastrointestinal disease. Increased helminth egg counts were also associated with decreasing group size in some areas. Observed spatial differences may reflect mutual effects of variations in subpopulation growth rates, gorilla social structure, and vegetation associated with altitude across mountain gorilla habitat. Helminth infection intensities in Virunga gorillas were lowest in the youngest and the oldest animals. Elucidating parasite infection patterns of endangered species with low genetic diversity is crucial for their conservation management.
Assessment of axillary node status by ultrasound after neoadjuvant chemotherapy in patients with clinically node-positive breast cancer according to breast cancer subtype
Authors: Maeshima Yurina , Sakai Takehiko , Ogiya Akiko , Takahashi Yoko , Miyagi Yumi , Kokubu Yumi , Osako Tomo , Ito Yoshinori , Takahashi Shunji , Ohno Shinji , Ueno Takayuki 
Published: May 2021

AbstractThe use of sentinel node biopsy (SNB) following neoadjuvant chemotherapy (NAC) for patients with cN1 breast cancer is controversial. Improvements of negative predictive value (NPV) by axillary ultrasound (AUS), which corresponds to the accurate prediction rate of node-negative status after NAC, would lead to decreased FNR of SNB following NAC. In this study, we retrospectively investigated the accurate prediction rate of NPV by AUS after NAC in patients with cytologically node-positive breast cancer treated between January 2012 and December 2016. Of 279 eligible patients, the NPV was 49.2% in all patients, but varied significantly by tumor subtype (p < 0.001) and tumor response determined by magnetic resonance imaging (MRI) (p = 0.0003). Of the 23 patients with clinically node negative (ycN0) by AUS and clinical complete response in primary lesion by MRI, the NPV was 100% in patients with HR±/HER2+ or HR−/HER2− breast cancer. In conclusion, regarding FNR reduction post-NAC, it will be of clinical value to take tumor subtype and primary tumor response using MRI into account to identify patients for SNB after NAC.
The modulatory effects of alfalfa polysaccharide on intestinal microbiota and systemic health of Salmonella serotype (ser.) Enteritidis-challenged broilers
Authors: Li Zemin , Zhang Chongyu , Li Bo , Zhang Shimin , Haj Fawaz G. , Zhang Guiguo , Lee Yunkyoung 
Published: May 2021

AbstractSalmonella serotype (ser.) Enteritidis infection in broilers is a main foodborne illness that substantially threatens food security. This study aimed to examine the effects of a novel polysaccharide isolated from alfalfa (APS) on the intestinal microbiome and systemic health of S. ser. Enteritidis-infected broilers. The results indicated that broilers receiving the APS-supplemented diet had the improved (P < 0.05) growth performance and gut health than those fed no APS-supplemented diet. Supplementation with APS enhanced (P < 0.05) the richness of gut beneficial microbes such as Bacteroidetes, Barnesiella, Parabacteroides, Butyricimonas, and Prevotellaceae, while decreased (P < 0.05) the abundance of facultative anaerobic bacteria including Proteobacteria, Actinobacteria, Ruminococcaceae, Lachnospiraceae, and Burkholderiaceae in the S. ser. Enteritidis-infected broilers. The Bacteroides and Odoribacter were identified as the two core microbes across all treatments and combined with their syntrophic microbes formed the hub in co-occurrence networks linking microbiome structure to performance of broilers. Taken together, dietary APS supplementation improved the systemic health of broilers by reshaping the intestinal microbiome regardless of whether S. ser. Enteritidis infection was present. Therefore, APS can be employed as a potential functional additives to inhibit the S. ser. Enteritidis and enhance the food safety in poultry farming.
A comparative study of synthetic winged peptides for absolute protein quantification
Authors: Benesova Eliska , Vidova Veronika , Spacil Zdenek 
Published: May 2021

AbstractA proper internal standard choice is critical for accurate, precise, and reproducible mass spectrometry-based proteomics assays. Synthetic isotopically labeled (SIL) proteins are currently considered the gold standard. However, they are costly and challenging to obtain. An alternative approach uses SIL peptides or SIL "winged" peptides extended at C- or/and N-terminus with an amino acid sequence or a tag cleaved during enzymatic proteolysis. However, a consensus on the design of a winged peptide for absolute quantification is missing. In this study, we used human serum albumin as a model system to compare the quantitative performance of reference SIL protein with four different designs of SIL winged peptides: (i) commercially available SIL peptides with a proprietary trypsin cleavable tag at C-terminus, (ii) SIL peptides extended with five amino acid residues at C-terminus, (iii) SIL peptides extended with three and (iv) with five amino acid residues at both C- and N-termini. Our results demonstrate properties of various SIL extended peptides designs, e.g., water solubility and efficiency of trypsin enzymatic cleavage with primary influence on quantitative performance. SIL winged peptides extended with three amino acids at both C- and N-termini demonstrated optimal quantitative performance, equivalent to the SIL protein.
Semantic and spatial congruency mould audiovisual integration depending on perceptual awareness
Authors: Delong Patrycja , Noppeney Uta 
Published: May 2021

AbstractInformation integration is considered a hallmark of human consciousness. Recent research has challenged this tenet by showing multisensory interactions in the absence of awareness. This psychophysics study assessed the impact of spatial and semantic correspondences on audiovisual binding in the presence and absence of visual awareness by combining forward–backward masking with spatial ventriloquism. Observers were presented with object pictures and synchronous sounds that were spatially and/or semantically congruent or incongruent. On each trial observers located the sound, identified the picture and rated the picture’s visibility. We observed a robust ventriloquist effect for subjectively visible and invisible pictures indicating that pictures that evade our perceptual awareness influence where we perceive sounds. Critically, semantic congruency enhanced these visual biases on perceived sound location only when the picture entered observers’ awareness. Our results demonstrate that crossmodal influences operating from vision to audition and vice versa are interactively controlled by spatial and semantic congruency in the presence of awareness. However, when visual processing is disrupted by masking procedures audiovisual interactions no longer depend on semantic correspondences.
COVID-19 infection data encode a dynamic reproduction number in response to policy decisions with secondary wave implications
Authors: Rowland Michael A. , Swannack Todd M. , Mayo Michael L. , Parno Matthew , Farthing Matthew , Dettwiller Ian , George Glover , England William , Reif Molly , Cegan Jeffrey , Trump Benjamin , Linkov Igor , Lafferty Brandon , Bridges Todd 
Published: May 2021

AbstractThe SARS-CoV-2 virus is responsible for the novel coronavirus disease 2019 (COVID-19), which has spread to populations throughout the continental United States. Most state and local governments have adopted some level of “social distancing” policy, but infections have continued to spread despite these efforts. Absent a vaccine, authorities have few other tools by which to mitigate further spread of the virus. This begs the question of how effective social policy really is at reducing new infections that, left alone, could potentially overwhelm the existing hospitalization capacity of many states. We developed a mathematical model that captures correlations between some state-level “social distancing” policies and infection kinetics for all U.S. states, and use it to illustrate the link between social policy decisions, disease dynamics, and an effective reproduction number that changes over time, for case studies of Massachusetts, New Jersey, and Washington states. In general, our findings indicate that the potential for second waves of infection, which result after reopening states without an increase to immunity, can be mitigated by a return of social distancing policies as soon as possible after the waves are detected.
A predictive model for vertebrate bone identification from collagen using proteomic mass spectrometry
Authors: Yang Heyi , Butler Erin R. , Monier Samantha A. , Teubl Jennifer , Fenyö David , Ueberheide Beatrix , Siegel Donald 
Published: May 2021

AbstractProteogenomics is an increasingly common method for species identification as it allows for rapid and inexpensive interrogation of an unknown organism’s proteome—even when the proteome is partially degraded. The proteomic method typically uses tandem mass spectrometry to survey all peptides detectable in a sample that frequently contains hundreds or thousands of proteins. Species identification is based on detection of a small numbers of species-specific peptides. Genetic analysis of proteins by mass spectrometry, however, is a developing field, and the bone proteome, typically consisting of only two proteins, pushes the limits of this technology. Nearly 20% of highly confident spectra from modern human bone samples identify non-human species when searched against a vertebrate database—as would be necessary with a fragment of unknown bone. These non-human peptides are often the result of current limitations in mass spectrometry or algorithm interpretation errors. Consequently, it is difficult to know if a “species-specific” peptide used to identify a sample is actually present in that sample. Here we evaluate the causes of peptide sequence errors and propose an unbiased, probabilistic approach to determine the likelihood that a species is correctly identified from bone without relying on species-specific peptides.
Modular barcode beads for microfluidic single cell genomics
Authors: Delley Cyrille L. , Abate Adam R. 
Published: May 2021

AbstractBarcode beads allow efficient nucleic acid tagging in single cell genomics. Current barcode designs, however, are fabricated with a particular application in mind. Repurposing to novel targets, or altering to add additional targets as information is obtained is possible but the result is suboptimal. Here, we describe a modular framework that simplifies generation of multifunctional beads and allows their easy extension to new targets.
Identification of hepatic fibrosis inhibitors through morphometry analysis of a hepatic multicellular spheroids model
Authors: Song Yeonhwa , Kim Sanghwa , Heo Jinyeong , Shum David , Lee Su-Yeon , Lee Minji , Kim A-Ram , Seo Haeng Ran 
Published: May 2021

AbstractA chronic, local inflammatory milieu can cause tissue fibrosis that results in epithelial-to-mesenchymal transition (EMT), endothelial-to-mesenchymal transition (EndMT), increased abundance of fibroblasts, and further acceleration of fibrosis. In this study, we aimed to identify potential mechanisms and inhibitors of fibrosis using 3D model-based phenotypic screening. We established liver fibrosis models using multicellular tumor spheroids (MCTSs) composed of hepatocellular carcinoma (HCC) and stromal cells such as fibroblasts (WI38), hepatic stellate cells (LX2), and endothelial cells (HUVEC) seeded at constant ratios. Through high-throughput screening of FDA-approved drugs, we identified retinoic acid and forskolin as candidates to attenuate the compactness of MCTSs as well as inhibit the expression of ECM-related proteins. Additionally, retinoic acid and forskolin induced reprogramming of fibroblast and cancer stem cells in the HCC microenvironment. Of interest, retinoic acid and forskolin had anti-fibrosis effects by decreasing expression of α-SMA and F-actin in LX2 cells and HUVEC cells. Moreover, when sorafenib was added along with retinoic acid and forskolin, apoptosis was increased, suggesting that anti-fibrosis drugs may improve tissue penetration to support the efficacy of anti-cancer drugs. Collectively, these findings support the potential utility of morphometric analyses of hepatic multicellular spheroid models in the development of new drugs with novel mechanisms for the treatment of hepatic fibrosis and HCCs.
Effects of elevated temperature on the corrosion resistance of silver–cobalt oxide–titanium dioxide (Ag/Co3O4/TiO2) nanocomposites coating on AISI 1020
Authors: Ibrahim Mohammed , Agboola Joseph B. , Abdulkareem Saka A. , Adedipe Oyewole , Tijani Jimoh O. 
Published: May 2021

AbstractThe effects of temperature on corrosion resistance of Silver–Cobalt oxide and Titanium Dioxide (Ag/Co3O4/TiO2) nanocomposite coated AISI 1020 in a high-temperature environment was investigated. The Ag, Co3O4and TiO2nanoparticles were individually produced by mixing the salt precursors with extract ofPiptadeniastrum Africanaleaf under the optimized synthesis conditions. The nanocomposite was produced by mixing Ag, Co3O4and TiO2nanoparticles (NPs) in equal proportions to constitute 75 wt% of the composite. 10 wt% epoxy resin and its hardener in the ratio (1:1) were added to serve as the binder, while 15 wt% of CNT was introduced to serve as support. The produced Ag/Co3O4/TiO2nanocomposite was coated on the surface of mild steel (AISI 1020) by the dipping method. The coated samples were heated in a muffle furnace to 35, 100, 200, and 300 °C. Microstructural evolution of the coatings was investigated using X-ray diffraction, scanning electron microscopy and energy dispersive spectrometer. The corrosion resistance of the coated and heated and un-heated steel samples was determined using the potentiodynamic polarization method. The results show that Ag/Co3O4/TiO2nanocomposite coated sample cured at 100 °C exhibited the highest corrosion resistance of 195.12 Ω.
Identification of novel source of salt tolerance in local bread wheat germplasm using morpho-physiological and biochemical attributes
Authors: Hussain Nadeem , Ghaffar Abdul , Zafar Zafar Ullah , Javed Muhammad , Shah Kausar Hussain , Noreen Sibgha , Manzoor Hamid , Iqbal Muhammad , Hassan Islam Frahat Zaky , Bano Hussan , Gul Hafiza Saima , Aamir Misbah , Khalid Ayesha , Sohail Younas , Ashraf Muhammad , Athar Habib-ur-Rehman 
Published: May 2021

AbstractSalt tolerant wheat cultivars may be used as genetic resource for wheat breeding to ensure yield stability in future. The study was aimed to select salt tolerant cultivar(s) to identify novel source of salt tolerance in local wheat germplasm. Initially, 40 local wheat cultivars were screened at 150 mM NaCl stress at seedling stage. Selected salt-tolerant (three; S-24, LU-26S and Pasban-90) and salt-sensitive (four; MH-97, Kohistan-97, Inqilab-91 and Iqbal-2000) wheat cultivars were further evaluated using growth, yield, biochemical and physiological attributes. Growth and yield of selected cultivars were reduced under salt stress due to decline in plant water status, limited uptake of macronutrients (N, P and K), reduced K+/Na+ratio, photosynthetic pigments and quantum yield of PSII. Wheat plants tried to acclimate salt stress by osmotic adjustment (accumulation of total soluble sugars, proline and free amino acids). Degree of salinity tolerance in cvs. S-24 and LU-26S found to be associated with maintenance of K+/Na+ratio, osmo-protectant and photosynthetic activity and can be used as donor for salt tolerance in wheat breeding program at least in Pakistan. These cultivars can be further characterized using molecular techniques to identify QTLs/genes for salt exclusion, osmo-protectant and photosynthetic activity for molecular breeding.
Protein model accuracy estimation empowered by deep learning and inter-residue distance prediction in CASP14
Authors: Chen Xiao , Liu Jian , Guo Zhiye , Wu Tianqi , Hou Jie , Cheng Jianlin 
Published: May 2021

AbstractThe inter-residue contact prediction and deep learning showed the promise to improve the estimation of protein model accuracy (EMA) in the 13th Critical Assessment of Protein Structure Prediction (CASP13). To further leverage the improved inter-residue distance predictions to enhance EMA, during the 2020 CASP14 experiment, we integrated several new inter-residue distance features with the existing model quality assessment features in several deep learning methods to predict the quality of protein structural models. According to the evaluation of performance in selecting the best model from the models of CASP14 targets, our three multi-model predictors of estimating model accuracy (MULTICOM-CONSTRUCT, MULTICOM-AI, and MULTICOM-CLUSTER) achieve the averaged loss of 0.073, 0.079, and 0.081, respectively, in terms of the global distance test score (GDT-TS). The three methods are ranked first, second, and third out of all 68 CASP14 predictors. MULTICOM-DEEP, the single-model predictor of estimating model accuracy (EMA), is ranked within top 10 among all the single-model EMA methods according to GDT-TS score loss. The results demonstrate that inter-residue distance features are valuable inputs for deep learning to predict the quality of protein structural models. However, larger training datasets and better ways of leveraging inter-residue distance information are needed to fully explore its potentials.