Vacancy Ordering in Ultrathin Copper Oxide Films on Cu(111).

Oxide thin films grown on metal surfaces have wide applications in catalysis and beyond owing to their unique surface structures compared to their bulk counterparts. Despite extensive studies, the atomic structures of copper surface oxides on Cu(111), commonly referred to as "44" and "29", have remained elusive. In this work, we demonstrated an approach for the structural determination of oxide surfaces using element-specific scanning tunneling microscopy (STM) imaging enhanced by functionalized tips. This approach enabled us to resolve the atomic structures of "44" and "29" surface oxides, which were further corroborated by noncontact atomic force microscopy (nc-AFM) measurements and Monte Carlo (MC) simulations. The stoichiometry of the "44" and "29" frameworks was identified as Cu23O16 and Cu16O11, respectively. Contrary to the conventional hypothesis, we observed ordered Cu vacancies within the "44" structure manifesting as peanut-shaped cavities in the hexagonal lattice. Similarly, a combination of Cu and O vacancies within the "29" structure leads to bean-shaped cavities within the pentagonal lattice. Our study has thus resolved the decades-long controversy on the atomic structures of "44" and "29" surface oxides, advancing our understanding of copper oxidation processes and introducing a robust framework for the analysis of complex oxide surfaces.

[Newborn screening, clinical features and genetic analysis for Citrin deficiency in Henan province].

OBJECTIVE: To explore the prevalence, clinical features, genetic characteristics and prognosis of Citrin deficiency in Henan province of China. METHODS: A total of 986 565 neonates screened by tandem mass spectrometry at the Third Affiliated Hospital of Zhengzhou University from January 2013 to December 2021 were retrospectively analyzed. Analysis of SLC25A13 gene variants and parental verification were carried out for neonates suspected for Citrin deficiency by next-generation sequencing. The clinical, biochemical and genetic characteristics of Citrin deficiency patients were integrated to guide the diet treatment and follow up the growth and development. Paired-t test was used to compare the amino acid levels in the peripheral blood samples before and after the treatment. RESULTS: Nine cases of Citrin deficiency were diagnosed among the 986 565 neonates. Specific elevation of citrulline was observed in all of the 9 cases. Six variants were detected by genetic sequencing, among which c.852_855delTATG, c.615+5G>A, c.550C>T and IVS16ins3kb were known pathogenic variants, whilst c.1111_1112delAT and c.837T>A were unreported previously. The detection rate for c. 852_855delTATG was the highest (61.6%, 11/18), followed by IVS16ins3kb (16.7%, 3/18). The clinical symptoms of all patients were relieved after the treatment, and the blood amino acid profile and biochemical parameters were significantly improved by gradually falling within the normal range. By June 2022, all patients had shown a good prognosis. CONCLUSION: The prevalence of Citrin deficiency among neonates from Henan Province by tandem mass spectrometry is 1/109 618, and the carrier rate for the pathogenic variants of the SLC25A13 gene was 1/166. The c.852_855delTATG may be a hot spot variant among the patients. Discovery of the novel variants has enriched the mutational spectrum of the SLC25A13 gene. Above results have provided a basis for the early diagnosis, treatment, prognosis and genetic counseling for the affected families.

Protocol for automated N-glycan sequencing using mass spectrometry and computer-assisted intelligent fragmentation.

Biological functions of glycans are intimately linked to fine details in branches and linkages, which make structural identification extremely challenging. Here, we present a protocol for automated N-glycan sequencing using multi-stage mass spectrometry (MSn). We describe steps for release/purification and derivation of glycans and procedures for MSn scanning. We then detail "glycan intelligent precursor selection" to computationally guide MSn experiments. The protocol can be used for both discrete individual glycans and isomeric glycan mixtures. For complete details on the use and execution of this protocol, please refer to Sun et al.,1 Huang et al.,2 and Huang et al.3.

Analysis of the external acoustic meatus for ergonomic design: part II - anthropometric variations of the external acoustic meatus by sex, age and side in Chinese population.

For devices worn inside the ear, detailed anthropometric data of the external acoustic meatus (EAM) is needed, yet lacking due to the complex and costly methodology associated with attaining such measurements. The purpose of this study was to provide the anthropometric characteristics of the EAM including variations by age group, sex, and side (right/left). 1400 external ears (700 Chinese subjects) were casted and scanned. A total of 23 EAM dimensions of length, width, angle, circumference and area were measured, most of which changed by age group, sex and side. 19 measurements were larger in males and 17 measurements were larger in left-side ears. Except the entrance length and circumference, measurements were not statistically significant between left- and right-side ears. This study provides key anthropometric measurements of the EAM in a Chinese population which can be used for ergonomic design purposes. Practitioner summary: This study provides an available source for anthropometric variations of the external acoustic meatus by age, gender and side in the Chinese population, which can be used as a reference to improve the fit, comfort and function of in-ear wearable devices.

PRS-Net: Planar Reflective Symmetry Detection Net for 3D Models.

In geometry processing, symmetry is a universal type of high-level structural information of 3D models and benefits many geometry processing tasks including shape segmentation, alignment, matching, and completion. Thus it is an important problem to analyze various symmetry forms of 3D shapes. Planar reflective symmetry is the most fundamental one. Traditional methods based on spatial sampling can be time-consuming and may not be able to identify all the symmetry planes. In this article, we present a novel learning framework to automatically discover global planar reflective symmetry of a 3D shape. Our framework trains an unsupervised 3D convolutional neural network to extract global model features and then outputs possible global symmetry parameters, where input shapes are represented using voxels. We introduce a dedicated symmetry distance loss along with a regularization loss to avoid generating duplicated symmetry planes. Our network can also identify generalized cylinders by predicting their rotation axes. We further provide a method to remove invalid and duplicated planes and axes. We demonstrate that our method is able to produce reliable and accurate results. Our neural network based method is hundreds of times faster than the state-of-the-art methods, which are based on sampling. Our method is also robust even with noisy or incomplete input surfaces.

Data analysis and modeling pipelines for controlled networked social science experiments.

There is large interest in networked social science experiments for understanding human behavior at-scale. Significant effort is required to perform data analytics on experimental outputs and for computational modeling of custom experiments. Moreover, experiments and modeling are often performed in a cycle, enabling iterative experimental refinement and data modeling to uncover interesting insights and to generate/refute hypotheses about social behaviors. The current practice for social analysts is to develop tailor-made computer programs and analytical scripts for experiments and modeling. This often leads to inefficiencies and duplication of effort. In this work, we propose a pipeline framework to take a significant step towards overcoming these challenges. Our contribution is to describe the design and implementation of a software system to automate many of the steps involved in analyzing social science experimental data, building models to capture the behavior of human subjects, and providing data to test hypotheses. The proposed pipeline framework consists of formal models, formal algorithms, and theoretical models as the basis for the design and implementation. We propose a formal data model, such that if an experiment can be described in terms of this model, then our pipeline software can be used to analyze data efficiently. The merits of the proposed pipeline framework is elaborated by several case studies of networked social science experiments.

Genetic contexts related to the diffusion of plasmid-mediated CTX-M-55 extended-spectrum beta-lactamase isolated from Enterobacteriaceae in China.

BACKGROUND: CTX-M-55 extended-spectrum beta-lactamases are being rapidly disseminated and transmitted in clinical practices around the world. The genetic contexts of the transferable plasmid-mediated blaCTX-M-55 gene in Enterobacteriaceae were detected and characterized in this study. METHODS: Isolates were obtained from the First Affiliated Hospital of Zhengzhou University between September 2015 and March 2016. Based on polymerase chain reaction and BLAST analysis, resistance genes and genetic context of the blaCTX-M-55 gene were investigated. Conjugation experiments and multilocus sequence typing were performed to demonstrate plasmid-mediated blaCTX-M-55 transmission. RESULTS: Thirteen blaCTX-M-55-positive isolates of Enterobacteriaceae were obtained. Seven isolates were Escherichia coli, 3 were Klebsiella pneumoniae, 1 was Citrobacter freundii, 1 was Morganella morganii and 1 was Serratia marcescens. The blaCTX-M-55 gene has not previously been identified from C. freundii and M. morganii. Four different blaCTX-M-55 genetic contexts were identified, and all of them harbored ISEcp1 in the region upstream of blaCTX-M-55 (in two cases, ISEcp1 was truncated by IS26, and in one case, it was truncated by IS1294), whereas ORF477 was detected downstream of the blaCTX-M-55 gene from 12 of 13 strains. The novel genetic context of ISEcp1∆-blaCTX-M-55-∆IS903 was firstly detected the IS903 element which was identified downstream of blaCTX-M-55. A conjugation assay revealed that all blaCTX-M-55 plasmids were quickly and easily transferable to recipient E. coli, which then presented resistance to multiple antibiotics. CONCLUSIONS: Numerous blaCTX-M-55-positive strains were isolated in a short period of 7 months. The findings indicate that blaCTX-M-55 was rapidly disseminated. The genetic context and conjugative transfer found in this study demonstrate that there is active transmission of blaCTX-M-55 among strains of Enterobacteriaceae in China, which could give rise to an urgent global public health threat.

Determining whether a class of random graphs is consistent with an observed contact network.

We demonstrate a general method to analyze the sensitivity of attack rate in a network model of infectious disease epidemiology to the structure of the network. We use Moore and Shannon's "network reliability" statistic to measure the epidemic potential of a network. A number of networks are generated using exponential random graph models based on the properties of the contact network structure of one of the Add Health surveys. The expected number of infections on the original Add Health network is significantly different from that on any of the models derived from it. Because individual-level transmissibility and network structure are not separately identifiable parameters given population-level attack rate data it is possible to re-calibrate the transmissibility to fix this difference. However, the temporal behavior of the outbreak remains significantly different. Hence any estimates of the effectiveness of time dependent interventions on one network are unlikely to generalize to the other. Moreover, we show that in one case even a small perturbation to the network spoils the re-calibration. Unfortunately, the set of sufficient statistics for specifying a contact network model is not yet known. Until it is, estimates of the outcome of a dynamical process on a particular network obtained from simulations on a different network are not reliable.

Antimicrobial Susceptibility and Molecular Epidemiology of Multidrug-Resistant Klebsiella pneumoniae in Central China.

Extended-spectrum-beta-lactamase-producing and carbapenemase-producing Klebsiella pneumoniae strains have rapidly spread through clinical units worldwide. This study investigated the epidemiology and resistance profiles of K. pneumoniae strains isolated in central China between 2009 and 2014. Antimicrobial susceptibility testing and polymerase chain reaction were used to investigate the prevalence of extended-spectrum beta-lactamases (ESBL) and carbapenemase production by these K. pneumoniae strains, and the prevalence of K. pneumoniae carbapenemase (KPC)-producing K. pneumoniae was investigated by multilocus sequence typing. Carbapenem resistance has emerged as a major concern in K. pneumoniae infections, as phenotype testing has detected carbapenemases in nearly 20% of isolates. KPC-producing isolates in a local epidemic were clonally related, with ST11 being the reservoir for the blaKPC-2 gene and ESBL genes. During the 6-year collection period, the prevalence of ESBLs was dynamic, and suggested that blaCTX-M-55 might become prevalent in the future. Our findings demonstrate the high prevalence of carbapenemase- and ESBL-producing K. pneumoniae in central China and predict a future local epidemic of KPC-2 and CTX-M-55.

From network reliability to the Ising model: A parallel scheme for estimating the joint density of states.

Network reliability is the probability that a dynamical system composed of discrete elements interacting on a network will be found in a configuration that satisfies a particular property. We introduce a reliability property, Ising feasibility, for which the network reliability is the Ising model's partition function. As shown by Moore and Shannon, the network reliability can be separated into two factors: structural, solely determined by the network topology, and dynamical, determined by the underlying dynamics. In this case, the structural factor is known as the joint density of states. Using methods developed to approximate the structural factor for other reliability properties, we simulate the joint density of states, yielding an approximation for the partition function. Based on a detailed examination of why naïve Monte Carlo sampling gives a poor approximation, we introduce a parallel scheme for estimating the joint density of states using a Markov-chain Monte Carlo method with a spin-exchange random walk. This parallel scheme makes simulating the Ising model in the presence of an external field practical on small computer clusters for networks with arbitrary topology with ∼10^{6} energy levels and more than 10^{308} microstates.

Predicting commuter flows in spatial networks using a radiation model based on temporal ranges.

Understanding network flows such as commuter traffic in large transportation networks is an ongoing challenge due to the complex nature of the transportation infrastructure and human mobility. Here we show a first-principles based method for traffic prediction using a cost-based generalization of the radiation model for human mobility, coupled with a cost-minimizing algorithm for efficient distribution of the mobility fluxes through the network. Using US census and highway traffic data, we show that traffic can efficiently and accurately be computed from a range-limited, network betweenness type calculation. The model based on travel time costs captures the log-normal distribution of the traffic and attains a high Pearson correlation coefficient (0.75) when compared with real traffic. Because of its principled nature, this method can inform many applications related to human mobility driven flows in spatial networks, ranging from transportation, through urban planning to mitigation of the effects of catastrophic events.