bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research on the Combination Technology of Smart Meter Status Evaluation and Acquisition Function Based on Big Data Technology
Authors: Xie Guorong , Zheng Xiaohui , Zhuang Dahai , Zheng Hong , Chen Yuanting , Gao Qiangqiang , Zhen Weishan 
Published: September 2020

Abstract
In order to study the key technologies suitable for large-scale intelligent electric energy meter automatic verification, the discrete verification mode is discussed from three aspects of data interaction, scheduling control, and intelligent diagnosis. First, build an application architecture for automated verification data from the perspective of multi-dimensional perception, use WCF and MQ communication modes to build a data interaction architecture, and propose a feedforward feedback integrated control mechanism; second, based on the automated verification control architecture, establish a space-time vertical and horizontal scheduling control strategy; finally. According to the category of automatic verification equipment, classify abnormal / fault categories and establish a fault knowledge base. Based on the intelligent diagnosis process of “alarm-discovery-diagnosis-processing-learning” mechanism, build an intelligent diagnosis application framework. The proposed method effectively guarantees the accuracy and reliability of the interactive data, realizes the automatic verification of space-time cooperative operation, and can effectively improve the daily operation and maintenance efficiency of large-scale automated verification.
Study on thermodynamics and kinetics of chemical vapor deposition of silicon nitride
Authors: Wang Fuyuan , Cheng Laifei , Liang Shuhua 
Published: September 2020

Abstract
The thermodynamics and kinetics methods had been applied to study the effects of the deposition temperature, the reaction gas ratio and the dilution gas on Si3N4 formation in the SiCl4-NH3-H2 system. The studies revealed that raising the deposition temperature would accelerate the chemical reaction and increase Si3N4 yield below 1400 K, higher temperature prompted the side reactions. With the increase of NH3 concentration, the content of Si3N4 in the reaction products also increased. As the diluent gas, H2 could accelerate the reaction and the deposition of Si3N4. However, the excess dilution gas would carry away the reaction gas and inhibit the reaction. The comprehensive effect of temperature and gas ratio on Si3N4 deposition were also analyzed by the three-dimensional figures. Finally, the optimal conditions for Si3N4 preparation were suggested.
Effect of nano-WC content on microstructures and wear resistance of laser cladding Fe-based alloy coatings
Authors: Gao Zhongtang , Ren Haibo , Yu Yuan , Guo Wei , Zhang Chuanwei , Gao Zhiming 
Published: September 2020

Abstracts
Three kinds of Fe-based power with different content of nano-WC were successfully prepared on 35CrMoV steel using laser cladding technique. The influence of nano-WC on the macro-morphology, microstructure and wear resistance of Fe-based coatings under different wear conditions was investigated by scanning electron microscopy and three-dimensional non-contact surface mapping. It has been found that a lot of fine grains and equiaxed grains synthesized with the addition of nano-WC. Both the volume fraction of eutectics and wear resistance of Fe-based coatings are greatly increased with a moderate addition of nano-WC, which is attributed to the exist of the partial dissolution of hard and high temperature WC phase in the composite coating. The wear rates increase more than 2–3 times with the addition of nano-WC range from 5 wt% WC to 10 wt%WC. Hence the addition of nano-WC strengthening phase is an effective and feasible way to improve the mechanical properties, especial for the tribological properties.
Ising model with variable spin/agent strengths
Authors: Krasnytska M , Berche B , Holovatch Yu , Kenna R 
Published: September 2020

Abstract
We introduce varying spin strengths to the Ising model, a central pillar of statistical physics. With inhomogeneous physical systems in mind, but also anticipating interdisciplinary applications, we present the model on network structures of varying degrees of complexity. This allows us explore the interplay of two types of randomness: individual strengths of spins or agents and collective connectivity between them. We solve the model for the generic case of power-law spin strength and find that, with a self-averaging free energy, it has a rich phase diagram with new universality classes. Indeed, the degree of complexity added by quenched variable spins is on a par to that added by endowing simple networks with increasingly realistic geometries. The model is suitable for investigating emergent phenomena in many-body systems in contexts where non-identicality of spins or agents plays an essential role and for exporting statistical physics concepts beyond physics.
Laboratory Workup of Lymphoma in Adults
Authors: Kroft Steven H , Sever Cordelia E , Bagg Adam , Billman Brooke , Diefenbach Catherine , Dorfman David M , Finn William G , Gratzinger Dita A , Gregg Patricia A , Leonard John P , Smith Sonali , Souter Lesley , Weiss Ronald L , Ventura Christina B , Cheung Matthew C 
Published: September 2020

Abstract

Objectives
The diagnostic workup of lymphoma continues to evolve rapidly as experience and discovery lead to the addition of new clinicopathologic entities and techniques to differentiate them. The optimal clinically effective, efficient, and cost-effective approach to diagnosis that is safe for patients can be elusive, in both community-based and academic practice. Studies suggest that there is variation in practice in both settings.

The aim of this review is to
develop an evidence-based guideline for the preanalytic phase of testing, focusing on specimen requirements for the diagnostic evaluation of lymphoma.

Methods
The American Society for Clinical Pathology, the College of American Pathologists, and the American Society of Hematology convened a panel of experts in the laboratory workup of lymphoma to develop evidence-based recommendations. The panel conducted a systematic review of the literature to address key questions. Using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach, recommendations were derived based on the available evidence, the strength of that evidence, and key judgments as defined in the GRADE Evidence to Decision framework.

Results
Thirteen guideline statements were established to optimize specimen selection, ancillary diagnostic testing, and appropriate follow-up for safe and accurate diagnosis of indolent and aggressive lymphoma.

Conclusions
Primary diagnosis and classification of lymphoma can be achieved with a variety of specimens. Application of the recommendations can guide decisions about specimen suitability, diagnostic capabilities, and correct utilization of ancillary testing. Disease prevalence in patient populations, availability of ancillary testing, and diagnostic goals should be incorporated into algorithms tailored to each practice environment.
The role of individual variation in flowering and pollination in the reproductive success of a crepuscular buzz-pollinated plant
Authors: Soares Natalia Costa , Maruyama Pietro Kiyoshi , Staggemeier Vanessa Graziele , Morellato Leonor Patrícia Cerdeira , Araújo Márcio Silva 
Published: September 2020

AbstractBackground and AimsPlant individuals within a population differ in their phenology and interactions with pollinators. However, it is still unknown how individual differences affect the reproductive success of plants that have functionally specialized pollination systems. Here, we evaluated whether plant individual specialization in phenology (temporal specialization) and in pollination (pollinator specialization) affect the reproductive success of the crepuscular-bee-pollinated plant Trembleya laniflora (Melastomataceae).MethodsWe quantified flowering activity (amplitude, duration and overlap), plant–pollinator interactions (number of flowers visited by pollinators) and reproductive success (fruit set) of T. laniflora individuals from three distinct locations in rupestrian grasslands of southeastern Brazil. We estimated the degree of individual temporal specialization in flowering phenology and of individual specialization in plant–pollinator interactions, and tested their relationship with plant reproductive success.Key ResultsTrembleya laniflora presented overlapping flowering, a temporal generalization and specialized pollinator interactions. Flowering overlap among individuals and populations was higher than expected by chance but did not affect the individual interactions with pollinators and nor their reproductive success. In contrast, higher individual generalization in the interactions with pollinators was related to higher individual reproductive success.ConclusionsOur findings suggest that individual generalization in plant–pollinator interaction reduces the potential costs of specialization at the species level, ensuring reproductive success. Altogether, our results highlight the complexity of specialization/generalization of plant–pollinator interactions at distinct levels of organization, from individuals to populations, to species.
Difference between emergent aquatic and terrestrial monocotyledonous herbs in relation to the coordination of leaf stomata with vein traits
Authors: Zhao Wanli , Fu Peili , Liu Guolan , Zhao Ping 
Published: September 2020

Abstract
Emergent aquatic plants mostly occur in shallow waters and root in bottom substrates, but their leaves emerge from the water surface and are thus exposed to air, similar to the leaves of terrestrial plants. Previous studies have found coordination between leaf water supply and demand in terrestrial plants; however, whether such a coordination exists in emergent aquatic plants remains unknown. In this study, we analysed leaf veins and stomatal characteristics of 14 emergent aquatic and 13 terrestrial monocotyledonous herb species (EMH and TMH), with 5 EMH and 8 TMH belonging to Poaceae. We found that EMH had significantly higher mean leaf area, leaf thickness, stomatal density, stomatal number per vein length and major vein diameter, but lower mean major vein length per area (VLA) and total VLA than TMH. There was no significant difference in stomatal length, minor VLA and minor vein diameter between the two groups. Stomatal density and total VLA were positively correlated among the EMH, TMH, as well as the 8 Poaceae TMH species, but this correlation became non-significant when data from both the groups were pooled. Our results showed that the differences in water supply between emergent aquatic and terrestrial plants modify the coordination of their leaf veins and stomatal traits.
Contrasting growth responses to aluminium addition among populations of the aluminium accumulator Melastoma malabathricum
Authors: Mahmud Khairil , Burslem David F R P 
Published: September 2020

Abstract
Aluminium (Al) hyper-accumulation is a common trait expressed by tropical woody plants growing on acidic soils. Studies on Al accumulators have suggested that Al addition may enhance plant growth rates, but the functional significance of this trait and the mechanistic basis of the growth response are uncertain. This study aimed to test the hypothesis that differential growth responses to Al among populations of an Al accumulator species are associated with variation in biomass allocation and nutrient uptake. We conducted two experiments to test differential responses to the presence of Al in the growth medium for seedlings of the Al accumulator shrub Melastoma malabathricum collected from 18 populations across Peninsular Malaysia. Total dry mass and relative growth rate of dry mass were significantly greater for seedlings that had received Al in the growth medium than for control plants that did not receive Al, but growth declined in response to 5.0 mM Al addition. The increase in growth rate in response to Al addition was greater for a fast-growing than a slow-growing population. The increase in growth rate in response to Al addition occurred despite a reduction in dry mass allocation to leaves, at the expense of higher allocation to roots and stems, for plants grown with Al. Foliar concentrations of P, K, Mg and Ca increased in response to Al addition and the first axis of a PCA summarizing foliar nutrient concentrations among populations was correlated positively with seedling relative growth rates. Some populations of the Al hyper-accumulator M. malabathricum express a physiological response to Al addition which leads to a stimulation of growth up to an optimum value of Al in the growth medium, beyond which growth declines. This was associated with enhanced nutrient concentrations in leaves, which suggests that Al accumulation functions to optimize elemental stoichiometry and growth rate.
RBANS Validity Measures and the TOMM in Veterans Undergoing Seizure Monitoring
Authors: Binder Laurence , Salinsky Martin C , Storzbach Daniel , Tadrous-Furnanz Sandy K 
Published: September 2020

Abstract

Objective
To assess the validity of embedded measures of performance validity, the effort index (EI) and effort scale (ES) of the repeatable battery for the assessment of neuropsychological status (RBANS), in Veterans with seizures; to compare the frequency of failure on the test of memory malingering (TOMM) in patients with epileptic versus psychogenic nonepileptic seizures (PNES).

Methods
Seizure diagnosis was established for 309 participants in epilepsy monitoring units using conventional diagnostic criteria who completed both the TOMM and RBANS. The criterion for performance invalidity was failure on any trial of the TOMM. We examined multiple EI and ES cutoffs to establish optimal sensitivity and specificity.

Results
An RBANS EI cutoff score of greater than three was optimal with specificity of .98, sensitivity of.19, and positive Likelihood Ratio of 10 but was not useful when below this cutoff. Confidence intervals indicate the need for confirmation of a failed EI with another performance validity test (PVT). No ES cutoff had sufficient specificity for clinical use. Invalid TOMM performance but not invalid RBANS performance was significantly more common in persons with PNES than in persons with epileptic seizures.

Conclusions
In Veterans undergoing seizure monitoring, the RBANS EI was useful as a screen when positive that requires confirmation with another PVT. The RBANS ES was not useful. Invalid performance on the TOMM was more common in persons with PNES than in persons with epileptic seizures.
Filler Migration to the Orbit
Authors: Hamed-Azzam Shirin , Burkat Cat , Mukari Abed , Briscoe Daniel , Joshi Narish , Scawn Richard , Alon Eran , Hartstein Morris 
Published: September 2020

Abstract

Background
Dermal filler injections continue to grow in popularity as a method of facial rejuvenation. This increase in the number of injections performed has resulted in an increasing number of types of filler-related complications.

Objectives
We report a series of cases where dermal filler injected in the face migrated to the orbit. Treatment methods and possible mechanisms of this newly reported complication are discussed.

Methods
A retrospective, multicenter analysis was performed on patients with dermal filler migration to the orbit after facial filler injections.

Results
Seven patients (6 females, 1 male; age range, 42-67 years) presented with orbital symptoms after filler injection and were subsequently found to have dermal filler in the orbit. Four out of 7 patients underwent orbitotomy surgery, 1 patient underwent lacrimal surgery, 1 patient had strabismus surgery, and 1 patient was treated with hyalurodinase injections. All patients have remained stable postoperatively.

Conclusions
Orbital complications secondary to migrated filler may occur long after the initial procedure. Because the site of the complication is distant from the injection site, patients and physicians may not immediately make the connection. Furthermore, this may lead to unnecessary examinations and a delay in diagnosis while looking for standard orbital masses. Dermal fillers should therefore be considered in the differential diagnosis of patients presenting with new-onset orbital masses.

Level of Evidence: 4
New mixture models for decoy-free false discovery rate estimation in mass spectrometry proteomics
Authors: Peng Yisu , Jain Shantanu , Li Yong Fuga , Greguš Michal , Ivanov Alexander R. , Vitek Olga , Radivojac Predrag 
Published: September 2020

AbstractMotivationAccurate estimation of false discovery rate (FDR) of spectral identification is a central problem in mass spectrometry-based proteomics. Over the past two decades, target-decoy approaches (TDAs) and decoy-free approaches (DFAs) have been widely used to estimate FDR. TDAs use a database of decoy species to faithfully model score distributions of incorrect peptide-spectrum matches (PSMs). DFAs, on the other hand, fit two-component mixture models to learn the parameters of correct and incorrect PSM score distributions. While conceptually straightforward, both approaches lead to problems in practice, particularly in experiments that push instrumentation to the limit and generate low fragmentation-efficiency and low signal-to-noise-ratio spectra.ResultsWe introduce a new decoy-free framework for FDR estimation that generalizes present DFAs while exploiting more search data in a manner similar to TDAs. Our approach relies on multi-component mixtures, in which score distributions corresponding to the correct PSMs, best incorrect PSMs and second-best incorrect PSMs are modeled by the skew normal family. We derive EM algorithms to estimate parameters of these distributions from the scores of best and second-best PSMs associated with each experimental spectrum. We evaluate our models on multiple proteomics datasets and a HeLa cell digest case study consisting of more than a million spectra in total. We provide evidence of improved performance over existing DFAs and improved stability and speed over TDAs without any performance degradation. We propose that the new strategy has the potential to extend beyond peptide identification and reduce the need for TDA on all analytical platforms.Availabilityand implementationhttps://github.com/shawn-peng/FDR-estimation.Supplementary informationSupplementary data are available at Bioinformatics online.
A novel sequence alignment algorithm based on deep learning of the protein folding code
Authors: Gao Mu , Skolnick Jeffrey 
Published: September 2020

Abstract

Motivation
From evolutionary interference, function annotation to structural prediction, protein sequence comparison has provided crucial biological insights. While many sequence alignment algorithms have been developed, existing approaches often cannot detect hidden structural relationships in the ‘twilight zone’ of low sequence identity. To address this critical problem, we introduce a computational algorithm that performs protein Sequence Alignments from deep-Learning of Structural Alignments (SAdLSA, silent ‘d’). The key idea is to implicitly learn the protein folding code from many thousands of structural alignments using experimentally determined protein structures.

Results
To demonstrate that the folding code was learned, we first show that SAdLSA trained on pure α-helical proteins successfully recognizes pairs of structurally related pure β-sheet protein domains. Subsequent training and benchmarking on larger, highly challenging datasets show significant improvement over established approaches. For challenging cases, SAdLSA is ∼150% better than HHsearch for generating pairwise alignments and ∼50% better for identifying the proteins with the best alignments in a sequence library. The time complexity of SAdLSA is O(N) thanks to GPU acceleration.

Availability and implementation
Datasets and source codes of SAdLSA are available free of charge for academic users at http://sites.gatech.edu/cssb/sadlsa/.

Supplementary information
Supplementary data are available at Bioinformatics online.
Probabilistic graphlets capture biological function in probabilistic molecular networks
Authors: Doria-Belenguer Sergio , Youssef Markus K. , Böttcher René , Malod-Dognin Noël , Pržulj Nataša 
Published: September 2020

AbstractMotivationMolecular interactions have been successfully modeled and analyzed as networks, where nodes represent molecules and edges represent the interactions between them. These networks revealed that molecules with similar local network structure also have similar biological functions. The most sensitive measures of network structure are based on graphlets. However, graphlet-based methods thus far are only applicable to unweighted networks, whereas real-world molecular networks may have weighted edges that can represent the probability of an interaction occurring in the cell. This information is commonly discarded when applying thresholds to generate unweighted networks, which may lead to information loss.ResultsWe introduce probabilistic graphlets as a tool for analyzing the local wiring patterns of probabilistic networks. To assess their performance compared to unweighted graphlets, we generate synthetic networks based on different well-known random network models and edge probability distributions and demonstrate that probabilistic graphlets outperform their unweighted counterparts in distinguishing network structures. Then we model different real-world molecular interaction networks as weighted graphs with probabilities as weights on edges and we analyze them with our new weighted graphlets-based methods. We show that due to their probabilistic nature, probabilistic graphlet-based methods more robustly capture biological information in these data, while simultaneously showing a higher sensitivity to identify condition-specific functions compared to their unweighted graphlet-based method counterparts.Availabilityand implementationOur implementation of probabilistic graphlets is available at https://github.com/Serdobe/Probabilistic_Graphlets.Supplementary informationSupplementary data are available at Bioinformatics online.
Dementia key gene identification with multi-layered SNP-gene-disease network
Authors: Lee Dong-gi , Kim Myungjun , Son Sang Joon , Hong Chang Hyung , Shin Hyunjung 
Published: September 2020

Abstract

Motivation
Recently, various approaches for diagnosing and treating dementia have received significant attention, especially in identifying key genes that are crucial for dementia. If the mutations of such key genes could be tracked, it would be possible to predict the time of onset of dementia and significantly aid in developing drugs to treat dementia. However, gene finding involves tremendous cost, time and effort. To alleviate these problems, research on utilizing computational biology to decrease the search space of candidate genes is actively conducted.

In this study, we propose a framework in which diseases, genes and single-nucleotide polymorphisms are represented by a layered network, and key genes are predicted by a machine learning algorithm. The algorithm utilizes a network-based semi-supervised learning model that can be applied to layered data structures.

Results
The proposed method was applied to a dataset extracted from public databases related to diseases and genes with data collected from 186 patients. A portion of key genes obtained using the proposed method was verified in silico through PubMed literature, and the remaining genes were left as possible candidate genes.

Availability and implementation
The code for the framework will be available at http://www.alphaminers.net/.

Supplementary information
Supplementary data are available at Bioinformatics online.