Unstable Candidates Research Articles

Biased screening for multi-component materials with Structures of Alloy Generation And Recognition (SAGAR)

Exploring new materials has attracted more and more attention, due to the improvement of technology and industry. Theoretically, the first-principles calculations combined with global optimization have been applied to predicting the properties of materials accurately and accelerate the discovery of new materials. For certain multi-component materials, the atoms are nearly at the lattice sites and the material exploration can be enhanced with biased screening. Based on the space symmetry, the calculations of duplicate structures can be avoided, and the specified constraints are applied to filter the energetically unstable candidates out. To provide the reasonable candidates for the first-principles calculations, we have released a program of Structures of Alloy Generation And Recognition (SAGAR), which can be conveniently used through the website. Herein, we will present several examples to show that the biased screening is practical and efficient, determining structures with high stabilities and novel properties. We have studied the distribution of up to 50% Cl vacancy concentration in NaCl and revealed semiconductor–metal transition in the boron/nitrogen co-doped diamond. The ground state anti-ferrormagnetic configuration of VCl2 is determined, as well as the low-lying hydrogenated-C60 structures with high symmetry. Our results indicate that the biased screening with proper constraint will effectively enhance the material exploration.

A kinematic stability repair algorithm for planar truss topology via geometric decomposition

Topology optimization of trusses is one of the most inviting topics in the structural optimization field. In search for the computational efficiency, researchers have implemented many algorithms for this problem. With the advent of metaheuristic algorithms, structural optimization problems have become simpler to model; however, solution of these problems remains computationally expensive. The design candidates are generated by adding and removing the members heuristically and kinematically unstable candidates are mostly eliminated in metaheuristic truss topology optimization procedures. These procedures have a major flaw that needs to be overcome; metaheuristic algorithms may discard a promising but unstable design candidate although it can be repaired by adding and/or removing a few members. This study presents an algorithm to repair kinematically unstable planar truss design candidates. The algorithm first builds the connectivity matrix of the unstable candidates and identifies the structural components through geometric decomposition. Then, the repair takes place by adding and/or removing as less members as possible systematically in the conditions as absence of a basic truss and existence of unconnected or improperly connected components, supports, forces and/or remaining members. In addition, the presented algorithm gives information on how close is a candidate to a kinematically stable configuration.

Impact of the 2018 Donor Heart Allocation System on Post Transplant Morbidity and Mortality

Introduction The 2018 revised United Network of Organ Sharing (UNOS) heart transplant (HTx) donor allocation system, initiated on October 18, 2018, aimed to minimize waitlist mortality by prioritizing the transplant of more unstable candidates. However, this prioritization could potentially trade lower waitlist mortality for higher post-transplant morbidity and mortality. The purpose of this study was to examine the impact of the revised HTx allocation system on the clinical characteristics and outcomes of HTx recipients from a high-volume transplant center. Methods We identified 169 adult patients undergoing first-time single-organ HTx between October 2017 and October 2019. The cohort was divided into Era 1 (79 patients; 10/18/17-10/17/18) and Era 2 (90 patients; 10/18/18-10/17/19). Demographic and clinical characteristics, waitlist characteristics, and post-transplant morbidity and mortality were compared between eras. Results Patients in Era 2 were younger (55 v. 61 years, p=0.004), were twice as likely to be transplanted on temporary mechanical circulatory support (44% v. 20%, p Conclusion In a high-volume center, the revised HTx allocation system has shortened HTx waitlist time with transplantation of more unstable patients on temporary mechanical support with no impact on post-transplant outcomes. This suggests that, with careful patient selection, the revised allocation system may optimize both waitlist and post-transplant outcomes.

Global Analysis of the Human RNA Degradome Reveals Widespread Decapped and Endonucleolytic Cleaved Transcripts.

RNA decay is an important regulatory mechanism for gene expression at the posttranscriptional level. Although the main pathways and major enzymes that facilitate this process are well defined, global analysis of RNA turnover remains under-investigated. Recent advances in the application of next-generation sequencing technology enable its use in order to examine various RNA decay patterns at the genome-wide scale. In this study, we investigated human RNA decay patterns using parallel analysis of RNA end-sequencing (PARE-seq) data from XRN1-knockdown HeLa cell lines, followed by a comparison of steady state and degraded mRNA levels from RNA-seq and PARE-seq data, respectively. The results revealed 1103 and 1347 transcripts classified as stable and unstable candidates, respectively. Of the unstable candidates, we found that a subset of the replication-dependent histone transcripts was polyadenylated and rapidly degraded. Additionally, we identified 380 endonucleolytically cleaved candidates by analyzing the most abundant PARE sequence on a transcript. Of these, 41.4% of genes were classified as unstable genes, which implied that their endonucleolytic cleavage might affect their mRNA stability. Furthermore, we identified 1877 decapped candidates, including HSP90B1 and SWI5, having the most abundant PARE sequences at the 5′-end positions of the transcripts. These results provide a useful resource for further analysis of RNA decay patterns in human cells.

As Easy as Bojo’s ‘Oven-ready’ Brexit Pie? The Conservative Campaign

Just two years after a disastrous campaign which cost Theresa May her majority in Parliament and annihilated her hope of delivering Brexit, the Conservative Party managed to turn things around and secure a landslide victory. However surprising the result might have been, many factors can actually be used to explain this political success: a weak and disorganized opposition that failed to provide any clear solutions to the political gridlock, a general feeling of Brexit weariness and, of course, an efficient Conservative campaign. This paper will analyse the Conservative campaign to understand how the Tories managed to easily win an election that was considered by many as extremely important and whose result was almost impossible to predict. First, we will deal with the official slogan of the Conservative campaign: “Get Brexit Done”. We will then see that everything was organized around this simple message: making the most of the popularity of a highly unstable candidate, Boris Johnson, and using any means possible online to drive the point home.

Inspection of Imprint Defects in Stamped Metal Surfaces Using Deep Learning and Tracking

This article focuses on the automatic detection and classification of imprint defects on the surface of metal parts. This innovative research had collaboration with a multinational industry, which provided a system to capture images of vehicle parts as well as information about defects, their frequency, and quality requirements. As our main contribution, we propose a framework that combines detection, classification, and tracking in a synergistic way to assist the automotive industry. We use a state-of-the-art convolutional neural network, known as RetinaNet, to detect and classify imprint defects. We explore the temporal coherence in consecutive frames by tracking detected regions so as to reduce false alarms—unstable candidate regions that are rarely (re)detected many times—or to fix the classification of regions that are alternated classified as mild or severe imprint across frames. In our experiments, we achieve a mean average precision of $76\%$ to detect and classify mild and severe defects, outperforming state-of-the-art detectors for static images. For severe imprints only, we achieve precision and recall values of $90\%$ and $92\%$ , respectively. These are promising results that could also benefit other industrial applications such as inspection of fissures, holes, wrinkles, and scratches, that also use image sequences.

Automated Synthesis of Safe Digital Controllers for Sampled-Data Stochastic Nonlinear Systems

We present a new method for the automated synthesis of digital controllers with formal safety guarantees for systems with nonlinear dynamics, noisy output measurements, and stochastic disturbances. Our method derives digital controllers such that the corresponding closed-loop system, modeled as a sampled-data stochastic control system, satisfies a safety specification with probability above a given threshold. Our technique uses a fast solver and an optimization method to search for candidate controllers, which are then formally evaluated in closed-loop with the system in question by a verified solver. Unstable candidate controllers are discarded by efficiently checking a sufficient condition for Lyapunov stability of sampled-data nonlinear systems. We evaluate our technique on three case studies: an artificial pancreas model, a powertrain control model, and a quadruple-tank process.

Predicting the Structure Stability of Layered Heteroanionic Materials Exhibiting Anion Order

We report a workflow for heteroanionic materials discovery using Pauling's second rule to filter for and predict new candidate materials for synthesis with reduced computational overhead. Using oxyfluoride and oxynitride n = 1 Ruddlesden-Popper compounds as a use-case, we show that a minimization scheme based on the global instability index (GII) efficiently filters up to 50% of highly unstable candidate compositions based on crystal-chemistry grounds. We then validate the minimization scheme using density functional theory (DFT) calculations and find that unexpectedly the GII of stable heteroanionic materials is higher than that of homoanionic oxides owing to significant charge redistribution in compounds containing more than one anionic species. Using this workflow, we predict Sr2AlO3F to be stable and describe our attempts to synthesize a phase-pure material.

Existence of Solid Electrolyte Interphase in Mg Batteries: Mg/S Chemistry as an Example.

Magnesium redox chemistry is a very appealing "beyond Li ion chemistry" for realizing high energy density batteries due to the high capacity, low reduction potential, and most importantly, highly reversible and dendrite-free Mg metal anode. However, the progress of rechargeable Mg batteries has been greatly hindered by shortage of electrolytes with wide stability window, high ionic conductivity, and good compatibility with cathode materials. Unlike solid electrolyte interphase on Li metal anode, surface film formed by electrolyte decomposition in Mg batteries was considered to block Mg ion transport and passivate Mg electrode. For this reason, the attention of the community has been mainly focusing on surface layer free electrolytes, while reductively unstable salts/solvents are barely considered, despite many of them possessing all the necessary properties for good electrolytes. Here, for the first time, we demonstrate that the surface film formed by electrolyte decomposition can function as a solid electrolyte interphase (SEI). Using Mg/S chemistry as a model system, the SEI formation mechanism on Mg metal anode was thoroughly examined using electrochemical methods and surface chemistry characterization techniques such as EDX and XPS. On the basis of these results, a comprehensive view of the Mg/electrolyte interface that unifies both the SEI mechanism and the passivation layer mechanism is proposed. This new picture of surface layer on Mg metal anode in Mg batteries not only revolutionizes current understanding of Mg/electrolyte interface but also opens new avenues for electrolyte development by uncovering the potential of those reductively unstable candidates through interface design.

Using NearestGraph QoS Prediction Method for Service Recommendation in the Cloud

With the advent of the mobile network, the fusion of cloud computing and fog computing is becoming feasible to promise lower latency and short‐fat connection. However, there are a lot of redundant cloud‐aware services with identical functionalities but a different quality of service (QoS) in the fog cloud environment. In fact, since QoS information is stored in distributed fog servers rather than remote cloud, it is hard for individuals to make recommendation and selection with sparse QoS information. Collaborative filtering is an important method for the sparsity problems and has been widely adopted on the prediction of missing QoS values. Focusing on the fact that existing researchers often ignore the QoS fluctuation in a wide range in the fog cloud environment, a novel neighbor‐based QoS prediction method is proposed for service recommendation, in which a concept and calculation method is put forward to describe the stable status of services and users with quantifiable QoS values, and a NearestGraph algorithm is further designed to recognize stable or unstable candidate along with their popularity by a nearest neighbor graph structure which can help to make missing QoS values prediction in a certain order to improve final prediction accuracy. Experimental results confirm that the proposed method is effective in predicting unknown QoS values in terms of service recommendation accuracy and efficiency.

Monolayer II-VI semiconductors: A first-principles prediction

A systematic study of 32 honeycomb monolayer II-VI semiconductors is carried out by first-principles methods. While none of the two-dimensional (2D) structures can be energetically stable, it appears that BeO, MgO, CaO, ZnO, CdO, CaS, SrS, SrSe, BaTe, and HgTe honeycomb monolayers have a good dynamic stability. The stability of the five oxides is consistent with the work published by Zhuang et al. [Appl. Phys. Lett. 103, 212102 (2013)]. The rest of the compounds in the form of honeycomb are dynamically unstable, revealed by phonon calculations. In addition, according to the molecular dynamic (MD) simulation evolution from these unstable candidates, we also find two extra monolayers dynamically stable, which are tetragonal BaS $[P4/nmm(129)]$ and orthorhombic HgS $[P{2}_{1}/m(11)]$. The honeycomb monolayers exist in the form of either a planar perfect honeycomb or a low-buckled 2D layer, all of which possess a band gap and most of them are in the ultraviolet region. Interestingly, the dynamically stable SrSe has a gap near visible light, and displays exotic electronic properties with a flat top of the valence band, and hence has a strong spin polarization upon hole doping. The honeycomb HgTe has recently been reported to achieve a topological nontrivial phase under appropriate in-plane tensile strain and spin-orbital coupling (SOC) [J. Li et al., arXiv:1412.2528]. Some II-VI partners with less than $5%$ lattice mismatch may be used to design novel 2D heterojunction devices. If synthesized, potential applications of these 2D II-VI families could include optoelectronics, spintronics, and strong correlated electronics.

Identification of reference genes for quantitative expression analysis of microRNAs and mRNAs in barley under various stress conditions.

For accurate and reliable gene expression analysis using quantitative real-time reverse transcription PCR (qPCR), the selection of appropriate reference genes as an internal control for normalization is crucial. We hypothesized that non-coding, small nucleolar RNAs (snoRNAs) would be stably expressed in different barley varieties and under different experimental treatments, in different tissues and at different developmental stages of plant growth and therefore might prove to be suitable reference genes for expression analysis of both microRNAs (miRNAs) and mRNAs. In this study, we examined the expression stability of ten candidate reference genes in six barley genotypes under five experimental stresses, drought, fungal infection, boron toxicity, nutrient deficiency and salinity. We compared four commonly used housekeeping genes; Actin (ACT), alpha-Tubulin (α-TUB), Glycolytic glyceraldehyde-3-phosphate dehydrogenase (GAPDH), ADP-ribosylation factor 1-like protein (ADP), four snoRNAs; (U18, U61, snoR14 and snoR23) and two microRNAs (miR168, miR159) as candidate reference genes. We found that ADP, snoR14 and snoR23 were ranked as the best of these candidates across diverse samples. For accurate and reliable gene expression analysis using quantitative real-time reverse transcription PCR (qPCR), the selection of appropriate reference genes as an internal control for normalization is crucial. We hypothesized that non-coding, small nucleolar RNAs (snoRNAs) would be stably expressed in different barley varieties and under different experimental treatments, in different tissues and at different developmental stages of plant growth and therefore might prove to be suitable reference genes for expression analysis of both microRNAs (miRNAs) and mRNAs. In this study, we examined the expression stability of ten candidate reference genes in six barley genotypes under five experimental stresses, drought, fungal infection, boron toxicity, nutrient deficiency and salinity. We compared four commonly used housekeeping genes; Actin (ACT), alpha-Tubulin (α-TUB), Glycolytic glyceraldehyde-3-phosphate dehydrogenase (GAPDH), ADP-ribosylation factor 1-like protein (ADP), four snoRNAs; (U18, U61, snoR14 and snoR23) and two microRNAs (miR168, miR159) as candidate reference genes. We found that ADP, snoR14 and snoR23 were ranked as the best of these candidates across diverse samples. Additionally, we found that miR168 was a suitable reference gene for expression analysis in barley. Finally, we validated the performance of our stable and unstable candidate reference genes for both mRNA and miRNA qPCR data normalization under different stress conditions and demonstrated the superiority of the stable candidates. Our data demonstrate the suitability of barley snoRNAs and miRNAs as potential reference genes for miRNA and mRNA qPCR data normalization under different stress treatments.

Promoter methylation and transgene copy numbers predict unstable protein production in recombinant chinese hamster ovary cell lines

Mammalian cell lines for recombinant protein production need to maintain productivity over extended cultivation times. Long-term stability studies are time and resource intensive, but are widely performed to identify and eliminate unstable candidates during cell line development. Production instability of manufacturing cell lines can be associated with methylation and silencing of the heterologous promoter. We have identified CpG dinucleotides within the human cytomegalovirus major immediate early promoter/enhancer (hCMV-MIE) that are frequently methylated in unstable antibody-producing Chinese hamster ovary (CHO) cell lines. We have established methylation-specific real-time qPCR for the rapid and sensitive measurement of hCMV-MIE methylation in multiple cell lines and provide evidence that hCMV-MIE methylation and transgene copy numbers can be used as early markers to predict production instability of recombinant CHO cell lines. These markers should provide the opportunity to enrich stable producers early in cell line development and allow developers to put more emphasis on other criteria, such as product quality and bioprocess robustness.