Fine-grained fault recognition method for shaft orbit of rotary machine based on convolutional neural network

In the fault diagnosis of the shaft orbit of rotating machinery, there are few prejudgments about the severity of the faults, which is very important for fault repair. Therefore, a fine-grained recognition method is proposed to detect different severity faults by shaft orbit. Since different shaft orbits represent different type and different severity of faults, the convolutional neural network (CNN) is applied for identifying the shaft orbits to recognize the type and severity of the fault. The recognition rate of proposed fine-grained fault identification method is 97.96 % on the simulated shaft orbit database, and it takes only 0.31 milliseconds for the recognition of single sample. Experimental result indicated that the classification performance of the proposed method are better than the traditional machine learning models. Moreover, the method is applied for the identification of the measured shaft orbits of rotor with different degree of imbalance faults, and the testing accuracy of the experiments in measured shaft orbits is 97.14 %, which has verified the effectiveness of the proposed fine-grained fault recognition method

Recent progress in thermoelectric nanocomposites based on solution-synthesized nanoheterostructures

Thermoelectric materials, which can convert waste heat into electricity, have received increasing research interest in recent years. This paper describes the recent progress in thermoelectric nanocomposites based on solution-synthesized nanoheterostructures. We start our discussion with the strategies of improving the power factor of a given material by using nanoheterostructures. Then we discuss the methods of decreasing thermal conductivity. Finally, we highlight a way of decoupling power factor and thermal conductivity, namely, incorporating phase-transition materials into a nanowire heterostructure. We have explored the lead telluride–copper telluride thermoelectric nanowire heterostructure in this work. Future possible ways to improve the figure of merit are discussed at the end of this paper

Geology, U-Pb geochronology and stable isotope geochemistry of the Heihaibei gold deposit in the southern part of the Eastern Kunlun Orogenic Belt, China : A granitic intrusion-related gold deposit?

The Heihaibei gold deposit is a newly discovered gold deposit in the southern part of the Eastern Kunlun Orogenic Belt. Its most distinctive features are that the gold mineralization is hosted in monzogranite, and that the presence of pre-ore (possibly syn-ore) monzogranite and post-ore gabbro allows to constrain the minerali-zation's formation age. Zircons from the monzogranites yield U-Pb ages of 454 +/- 3 Ma, while zircons separated from the gabbro dikes cutting the monzogranites and gold mineralized body yield U-Pb ages of 439 +/- 3 Ma, which is interpreted to be the minimum age of the Au mineralizing event. Combined with the regional geological background, we proposed that the Heihaibei Au mineralization occurred during the subduction stage of the Early Paleozoic Proto-Tethys ocean. The ore assemblage is dominated by pyrite, arsenopyrite and native gold. The hydrothermal alteration that has led to the peculiar enrichment of Au is not systematically distributed and displays no clear concentric zoning pattern. The main mineralization formed during three stages: the K-feldspar-quartz-pyrite (Py1)-arsenopyrite-sericite-epidote stage (I), the quartz-pyrite (Py2)-native gold-chlorite stage (II), and the quartz-carbonate stage (III). The main gold mineralization occurred during stage II. Fluid inclusion homogenization temperature and salinities decrease from stage I (Th., 268-412 C; W., 6.87-16.63 wt% NaCl equiv.) to stage II (Th., 183-288 C; W., 3.69-14.84 wt% NaCl equiv.). The 818O and 8D values (818OH2O = 4.9 to 9.7%o; 8DV-SMOW =-84.1%o to -81.1%o) of quartz samples from stage I and stage II are comparable to a magmatic-hydrothermal ore-forming fluid that possibly underwent fluid-rock interaction with the Nachitai Group metamorphic rocks during the early ore-forming stage. The relatively uniform 834S values (834SV-CDT = 7.7 to 8.5%o) are slightly elevated compared to magmatic 834S values, but could be derived from a magma if a significant crustal melt component is present. Moreover, the 834S values are within the S isotopic composition range of a granitic reservoir, suggesting that they are probably inherited from the Heihaibei monzogranites. The Pb and Hf isotope compositions imply a close genetic association between the gold mineralization and granitic magmatism, which are both the products of the mixing of crustal and mantle sources. The trace element compositions of pyrite provide additional evidence that the gold mineralization in the Heihaibei deposit was related to the magmatism. Compared with the typical characteristics of orogenic gold and intrusion-related gold systems (IRGS) deposits, the Heihaibei gold deposit may instead be classified as a granitic intrusion-related gold deposit.Peer reviewe

Applications of Machine Learning for Atomistic Modeling in Catalysis Informatics

In this era driven by data science and artificial intelligence, traditional computational catalysis has undergone a profound revolution facilitated by a variety of machine learning and deep learning techniques. For the new generation of computational theorists and experts in the field of catalysis and surface science, it is crucial to grasp how data-driven models and workflows can seamlessly integrate into scientific research domain. This dissertation explores two primary categories of studies in modern catalysis informatics. Type I studies are centered around predicting specific physical properties related to and playpivotal roles in governing various aspects of catalyst performance, including reactivity, selectivity, and activity. Type II studies, on the other hand, focus on the development of Machine-learning Potentials (Force Fields). These are meticulously engineered to extend the applicability of computationally intensive ab-initio methods (density functional theory, conventional molecular dynamics, and metadynamics) to larger catalytic systems and longer simulation timeframes for enhanced transferability and scalability. The overarching objective of both studies is to extract valuable structural, thermodynamic, and kinetic insights from catalytic systems that were previously inaccessible or inefficient using traditional simulation methods. This dissertation is organized into 5 chapters. Chapter 1 serves as an extensive review, akin to a concise textbook, covering data-driven research methods in catalysis informatics. It places particular emphasis on multiscale modeling techniques, descriptor (fingerprint) design for complex molecular systems, the foundational theory and typical algorithms of machine learning and deep learning, and the workflow for developing Machine-learning Potentials. Chapters 2 - 4 comprise the papers where I served as the first (or co-first) author, delving into accelerating the research progress in catalysis informatics. The final chapter 5 offers a summary and outlines potential avenues for future research in the field of catalysis informatics

Developing Cheap but Useful Machine Learning based Models for Investigating High-Entropy Alloy Catalysts

This work aims to address the challenge of developing interpretable ML-based models when access to large scale computational resources is limited. Using CoMoFeNiCu high-entropy alloy catalysts as an example, we present a cost-effective workflow that synergistically combines descriptor based approaches, machine learning based force fields and low-cost density functional theory (DFT) calculations to predict high-quality adsorption energies for H, N and NHx (x = 1, 2 and 3) adsorbates. This is achieved using three specific modifications to typical DFT workflows including, (1) using a sequential optimization protocol, (2) developing a new-geometry based descriptor, and (3) re-purposing the already-available low-cost DFT optimization trajectories to develop a ML-FF. Taken together, this study illustrates how cheap DFT calculations and appropriately designed descriptors can be used to develop cheap but useful models for predicting high-quality adsorption energies at significantly lower computational costs. We anticipate that this resource-efficient philosophy may be broadly relevant to the larger surface catalysis community

Developing Cheap but Useful Machine Learning-Based Models for Investigating High-Entropy Alloy Catalysts

This work aims to address the challenge of developing interpretable ML-based models when access to large-scale computational resources is limited. Using CoMoFeNiCu high-entropy alloy catalysts as an example, we present a cost-effective workflow that synergistically combines descriptor-based approaches, machine learning-based force fields, and low-cost density functional theory (DFT) calculations to predict high-quality adsorption energies for H, N, and NHx (x = 1, 2, and 3) adsorbates. This is achieved using three specific modifications to typical DFT workflows including: (1) using a sequential optimization protocol, (2) developing a new geometry-based descriptor, and (3) repurposing the already-available low-cost DFT optimization trajectories to develop a ML-FF. Taken together, this study illustrates how cost-effective DFT calculations and appropriately designed descriptors can be used to develop cheap but useful models for predicting high-quality adsorption energies at significantly lower computational costs. We anticipate that this resource-efficient philosophy may be broadly relevant to the larger surface catalysis community

Identification Method of Shaft Orbit in Rotating Machines Based on Accurate Fourier Height Functions Descriptors

In this paper, an algorithm based on two novel shape descriptors and support vector machine (SVM) is proposed to improve the recognition accuracy and speed of shaft orbits of rotating machines. Firstly, two novel shape descriptors, respectively, named accurate Fourier height functions 1 (AFHF1) and accurate Fourier height functions 2 (AFHF2) are presented based on height function (HF) and Fourier transformation. Both AFHF1 and AFHF2 shape descriptors are constant to similarity transforms and also have intrinsic invariance to the starting point change and are more compacted than HF. Therefore, they perform well on the global or local features of the contours of shaft orbits. Then, the AFHF1 and AFHF2 shape descriptors are utilized to extract features of shaft orbits in the simulated dataset and measured dataset. Taking extracted feature vectors as the input, SVM is adopted in order to classify the fault types according to the shapes of shaft orbits. Finally, a series of descriptors including shape context (SC), inner-distance shape context (IDSC), triangular centroid distances (TCDs), and HF were compared to verify the performance of the proposed AFHF1 and AFHF2 shape descriptors. The average accuracy of our method in simulated dataset and measured dataset are all higher than 99.83%, the average recognition time of each sample is no more than 19 milliseconds. The experiments demonstrate that the proposed method has the best recognition accuracy and real-time and antinoise performance

Prevalence of gestational diabetes mellitus in mainland China: A systematic review and meta‐analysis

Abstract Aims/Introduction Pregnant women with gestational diabetes mellitus (GDM) are at a higher risk of adverse pregnancy outcomes. The aim of the present study was to estimate the pooled prevalence of GDM in mainland China according to International Association of Diabetes and Pregnancy Study Groups criteria. Materials and Methods We carried out a systematic review by searching both English and Chinese literature databases. Random effects models were used to summarize the prevalence of GDM in mainland China. Subgroup and sensitivity analyses were carried out to address heterogeneity. Publication bias was evaluated using Egger's test. Results A total of 25 papers were included in the meta‐analysis, involving 79,064 Chinese participants. The total incidence of GDM in mainland China was 14.8% (95% confidence interval 12.8–16.7%). Subgroup analysis showed that the age, bodyweight and family history of diabetes mellitus could significantly increase the incidence of GDM. Conclusions To the best of our knowledge, this systematic review is the first to estimate the pooled prevalence of GDM among women in mainland China according to International Association of Diabetes and Pregnancy Study Groups criteria. The results of our systematic review suggest a high prevalence of GDM in mainland China, indicating that this country might have the largest number of GDM patients worldwide

Myotis flavus Shamel 1944

<i>Myotis flavus</i> Shamel 1944 <p> <i>Myotis flavus</i> Shamel 1944; type specimen, National Museum of Natural History (NMNH) 239908; adult ♀, remainder in fluid, skull removed. The type specimen was collected under a grove of trees with large leaves and lilac-like flowers in Jul 1923 at Enri in Formosus.The bat hanged head downwards from the stem of a leaf. Its colour was light yellow, the wing being variegated with orange and brown (Shamel 1944).</p> <p> <b>New materials.</b> JX- 07X-20, adult, male, collected at Shiyan cave (114°12΄E, 26°36΄N; 1058 m) in Liping village of Jinggangshan Natural Reserve of Jiangxi Province in mainland China by TingLei Jiang and KePing Sun in September 2006. Fur specimen (No. JX- 07X-20) was deposited at Northeast Normal University, China.</p> <p> <b>Description and taxonomic notes.</b> For <i>Myotis</i> species from mainland China, this is a medium to large size <i>Myotis</i> with a forearm length of 48.5 mm (Table 3)(52.5 mm in Shamel 1944), which is within the range (45 – 55 mm) given by Lin <i>et al.</i> (2005). The bases of the dorsal and ventral pelage are grayish white with their tips golden yellow and pale yellow, respectively (Fig. 2 a). Light brown bands exist around the digits of the wings. There are no black edges on the upper margin of the auricles, around the nostrils, thumbs, toes and the end of the tail (Fig. 2 a and Fig. 2 b). This clearly differs from <i>M. rufoniger</i> (Bates & Harrison 1997), <i>M. watasei</i> (Lin <i>et al.</i>, 2005) and <i>M. tsuensis</i> (Yoshiyuki 1989). The tragus is narrow and tapering towards a bluntly-pointed tip. The nose and chin are bare of long hairs for a distance of about 5 mm from tip, but the remainder of the face is well haired (Fig. 2 b), which corresponds to those specimens described in Shamel (1944). Metacarpals are considerably shorter than the forearm, and the third, fourth, fifth metacarpals were 91.2%, 88.6% and 90% of forearm length, respectively (Table 3). The wings are attached to the base of the phalanx of the outer metatarsal of each foot. Tail vertebrae extend 2.5 mm beyond the interfemoral membrane.</p> <p> The greatest antero-posterior length of the skull is 18.3 mm (Table 3)(19.5 mm in Shamel, 1944). The skull has the forehead region strongly concave (Fig. 3 c). The sagittal crest is well defined anteriorly but the lambdoid crest is inconspicuous (Fig. 3 a). The joint between the supraoccipital and foramen magnum is round and protruding downwards. The supraoccipital is slightly orbicular and plump (Fig. 3 c). The upper incisors become gradually larger from the inner to the outer teeth, and the canine is well developed (Fig. 3 b). The upper middle premolar (P3) site is completely within the upper tooth row, whereas in <i>M. rufoniger</i> and <i>M. watasei</i>, P3 is usually only partially within the tooth row of the upper jaw (Shamel, 1944). The upper anterior premolar (P2) and the upper posterior premolar (P4) are not in contact with each other; P3 is not visible when the tooth row is viewed externally, but is visible from a buccal view, which is same included in Shamel (1944). P3 extends its tip barely above the level of the cingulum on P2 (Fig. 3 c). The anterior and middle upper molars have distinct W- shaped ridges, and the posterior upper molar is half reduced (Fig. 3 b). The crowns of the second and third lower incisors divide into four leaflets. The first lower incisor is prolate, and the incisors are aligned forming a convex arch (Fig. 3 d). P3 is set inward, but visible from the outside of the tooth row, and the cusp is more slender and pointed than in P2 and about half its height (Fig. 3 c).</p> <p> The baculum of the sample JX- 07X-20 is generally Y-shaped, but slightly (Fig. 4 a). Proximal and distal ends concave at its central portion, and its ventral surface is not deeply fluted. Total length is 0.975 mm and maximum basal width is 0.575 mm. However, the baculum of <i>M. formosu</i> s from Jilin province clearly differs from that of the sample JX- 07X- 20 in having a concavity only in its proximal end and showing a deeply fluted ventral surface (Fig. 4 b). In addition, the size of the baculum of <i>M. formosu</i> s (total length 0.8 mm, maximum basal width 0.575 mm.) is slightly smaller than that of JX- 07X-20.</p> <p>Definitions follow those given in Bates and Harrison(1997).</p> <p> <b>Echolocation.</b> The echolocation calls of individual JX- 07X-20 are short, broadband frequency modulated signals with a dominant fundamental harmonic. The mean value for the frequency containing the maximum energy is 43.91 kHz, with a range of 41.0 – 46.2 kHz (n = 22).</p> <p> <b>Discussion.</b> When describing <i>M. flavus</i>, Shamel (1944) indicated that from <i>M. rufoniger</i> and <i>M. watasei</i> in body size and dental characteristics. Chou (2004) also distinguished <i>M. flavus</i> from <i>M. watasei</i>. In the present study, <i>M. flavus</i> is found to be different from <i>M. formosus</i> in coloration, skull and dental characteristics. In addition, differences in baculum morphology indicate a potential for the occurrence of reproductive isolation between <i>M. flavus</i> and <i>M. formosus</i> (Wu <i>et al.</i>, 2008).</p> <p> Relatively inexpensive and rapid DNA sequencing techniques have given biologists a new tool for detecting and differentiating morphologically similar species (Bickford, <i>et al.</i>, 2007). We took advantage of this by analyzing the mtDNA cytb gene, which showed that our specimen JX- 07X-20 differed by 0.61% from <i>M. flavus</i> from Taiwan (Table 2) which most likely corresponds to a divergence of intraspecific level. This genetical similarity supported the result of our morphological identification of this specimen. In contrast, it was surprising to see that the divergence values between <i>M. flavus</i> and other <i>M. formosus</i> specimens were so much larger (15.53–16.67 %) and even higher than the other interspecific divergences (Table 2). Genetic distances over 5% at cytb are generally considered to indicate the existence of cryptic taxonomic diversity, and values exceeding 10% in bats are indicative of species-level divergence (Baker & Bradley 2006). Moreover, our phylogenetic analysis shows that <i>M. formosus</i> and <i>M. flavus</i> are not sister taxa (Fig. 1). Hence, we consider <i>M. flavus</i> to be a distinct species and different from <i>M. formosus</i>. In addition, the phylogenetic grouping of and sequence similarity between <i>M. watasei</i> and <i>M. formosus</i> from mainland China strongly suggests that <i>M. watasei</i> is synonymous with <i>M. formosus</i>.</p> <p> <b>Distribution and ecological notes.</b> So far, <i>M. flavus</i> is only known from Taiwan (Lin <i>et al.</i>, 2005; Shamel 1944). The present report gives the first confirmed account of this species from mainland China. Our specimen JX- 07X-20 was captured at Shiyan cave in Liping village of Jinggangshan Natural Reserve of Jiangxi Province in China where the average temperature and mean rainfall are 14 °C and 1865 mm per year, respectively, resulting in a subtropical wet climate. The collection site is dominated by a forest consisting of <i>Phyllostachys heterocycla</i>, <i>Cunninghamia lanceolata</i>, <i>Schima uperba</i> and <i>P. heterocycla</i>. The other bat species roosting in the same cave were <i>Rhinolophus affinis</i>, <i>R. pearsoni</i>, <i>R. macrotis</i>, <i>Hipposideros armiger</i>, <i>M. davidii</i> and <i>M. formosus</i>.</p>Published as part of <i>Jiang, Tinglei, Sun, Keping, Chou, Chenghan, Zhang, Zhenzhen & Feng, Jiang, 2010, First record of Myotis flavus (Chiroptera: Vespertilionidae) from mainland China and a reassessment of its taxonomic status, pp. 41-51 in Zootaxa 2414</i> on pages 46-50, DOI: <a href="http://zenodo.org/record/194368">10.5281/zenodo.194368</a&gt

Screening Cu-Zeolites for Methane Activation using Curriculum-based Training

Machine learning (ML), when used synergistically with atomistic simulations, has recently emerged as a powerful tool for accelerated catalyst discovery. However, the application of these techniques has been limited by the lack of interpretable and transferable ML models. In this work, we propose a new philosophy called curriculum-based training (CBT) to systematically develop reactive machine learning potentials (rMLPs) for high-throughput screening zeolite catalysts. Our CBT approach combines several different types of calculations to gradually teach the ML model about the relevant regions of the reactive potential energy surface. The resulting rMLPs are accurate, transferrable, and interpretable. We further demonstrate the effectiveness of this approach by exhaustively screening thousands of [CuOCu]2+ sites across hundreds of Cu-zeolites for the industrially relevant methane activation reaction. Specifically, this large-scale analysis of the entire International Zeolite Association (IZA) database identifies a set of previously unexplored zeolites (i.e., MEI, ATN, EWO, and CAS) that show the highest ensemble-averaged rates for [CuOCu]2+-catalyzed methane activation. We believe that this CBT philosophy can be generally applied to other zeolite-catalyzed reactions and subsequently, to other types of heterogeneous catalysts. Thus, this represents an important step towards overcoming the long- standing barriers within the computational heterogeneous catalysis community