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Two allied and little-known genera, Bulborhodopis Breuning, 1948 and Mimapatelarthron Breuning, 1940 (Coleoptera: Cerambycidae: Lamiinae: Desmiphorini), are newly recorded from China upon the discoveries of Bulborhodopis barbicornis Breuning, 1948 and B. humeralis sp. nov. from Yunnan, and Mimapatelarthron laosense Breuning, 1968 from Yunnan and Hainan. Description and illustrations of the habitus, endophallic structure and major diagnostic features for the involved taxa are provided.

The polycystic ovary syndrome (PCOS) is a most common cause of infertility among women of reproductive age. Unfortunately, the etiology of PCOS is poorly understood. Large scale clinical trials for Pregnancy in Polycystic Ovary Syndrome (PPCOS) were conducted to evaluate the effectiveness of treatments. Ovulation, pregnancy, and live birth are three sequentially nested binary outcomes, typically analyzed separately. However, the separate models may lose power in detecting the treatment effects and influential variables for live birth, due to decreased sample sizes and unbalanced event counts. It has been a long-held hypothesis among the clinicians that some of the important variables for early pregnancy outcomes may continue their influence on live birth. To consider this possibility, we develop an ℓ(0)-norm based regularization method in favor of variables that have been identified from an earlier stage. Our approach explicitly bridges the connections across nested outcomes through computationally easy algorithms and enjoys theoretical guarantee of estimation and variable selection. By analyzing the PPCOS data, we successfully uncover the hidden influence of risk factors on live birth, which confirm clinical experience. Moreover, we provide novel infertility treatment recommendations (e.g., letrozole vs clomiphene citrate) for women with PCOS to improve their chances of live birth.

Fibroblast-like synoviocytes (FLSs) are the predominant effector cells in the pathological progression of rheumatoid arthritis (RA). Therefore, elucidating the underlying molecular mechanism of the biologic behaviors in RA-FLSs will be helpful in developing the potent targets for the treatment of RA. We have previously documented that the tumor-like biologic behaviors of RA-FLSs are exacerbated by urokinase-type plasminogen activator receptor (uPAR), a specifically up-regulated receptor in RA-FLSs. Here, we investigate the further mechanism of uPAR and clarify its function in RA-FLSs. We demonstrate that miR-221-3p positively correlates to uPAR and regulates uPAR level in RA-FLSs. Simultaneously, one long noncoding RNA, nuclear paraspeckle assembly transcript 1_1 (NEAT1_1) is identified, which can predictively target miR-221-3p at three sites, indicating a strong possibility of being a competing endogenous RNA in RA-FLSs. Interestingly, NEAT1_1 and miR-221-3p can colocate in the nucleus and cytoplasm in RA-FLSs. Importantly, NEAT1_1 can act as a rheostat for the miR-221-3p/uPAR axis and the downstream JAK signaling. In line with the biologic function, NEAT1_1 negatively regulates the tumor-like characters, and cytokine secretions of RA-FLSs. Collectively, our data provide new insight into the mechanisms of NEAT1_1 in modulating RA-FLSs tumor-like behaviors. The targeting of NEAT1_1 and miR-221-3p/uPAR axis may have a promising therapeutic role in patients with RA.

This article provides an overview of tensors, their properties, and their applications in statistics. Tensors, also known as multidimensional arrays, are generalizations of matrices to higher orders and are useful data representation architectures. We first review basic tensor concepts and decompositions, and then we elaborate traditional and recent applications of tensors in the fields of recommender systems and imaging analysis. We also illustrate tensors for network data and explore the relations among interacting units in a complex network system. Some canonical tensor computational algorithms and available software libraries are provided for various tensor decompositions. Future research directions, including tensors in deep learning, are also discussed.

Unicornileptura gen. nov. (独角花天牛属, Dú jiǎo huā tiān niú shǔ) is established for Unicornileptura emeiensis sp. nov. from Sichuan (as the type species) and U. laticollis sp. nov. from Hubei. Illustrations of habitus, endophallic structure and major diagnostic features are provided.

The genus Meges Pascoe, 1866 stat. res. is resurrected from synonyms of Monochamus Dejean, 1821 and is made a senior synonym of Magninia Clermont, 1932 syn. nov. Meges currently contains two species, i.e. Meges gravidus (Pascoe, 1858) and Meges tonkineus (Clermont, 1932) comb. nov. The male of the latter species is described for the first time. A related genus Pseudomeges Breuning, 1944 is investigated for comparison and Pseudomeges aureus Bi, Chen & Lin sp. nov. (金斑伪侎天牛, Jîn bân wěi mǐ tiân niú) is described from Yunnan, China. New localities are reported. Illustrations of habitus, endophallic structures and major diagnostic features for all involved taxa are provided.

This work presents a review of species of the Asian genusSinocymbachusStrohecker & Chûjô, 1970. Four new species are described from China:S. fanjingshanensisChang & Bi,sp. nov.,S. longipennisChang & Bi,sp. nov.,S. sinicusChang & Bi,sp. nov., andS. wangyinjieiChang & Bi,sp. nov.Cymbachus koreanusChûjô & Lee, 1993 is transferred toSinocymbachusasS. koreanus(Chûjô & Lee)comb. nov.Sinocymbachus bimaculatus(Pic, 1927) is reported for the first time from China. The male ofS. parvimaculatus(Mader, 1938) is discovered and described for the first time. Illustration, diagnosis and distribution are provided for each species. Prior to the present study,Sinocymbachusincluded ten species. An updated key to the species ofSinocymbachusis given.

Brain-imaging data have been increasingly used to understand intellectual disabilities. Despite significant progress in biomedical research, the mechanisms for most of the intellectual disabilities remain unknown. Finding the underlying neurological mechanisms has been proved difficult, especially in children due to the rapid development of their brains. We investigate verbal reasoning, which is a reliable measure of individuals’ general intellectual abilities, and develop a class of high-order imaging regression models to identify brain subregions which might be associated with this specific intellectual ability. A key novelty of our method is to take advantage of spatial brain structures, and specifically the piecewise smooth nature of most imaging coefficients in the form of high-order tensors. Our approach provides an effective and urgently needed method for identifying brain subregions potentially underlying certain intellectual disabilities. The idea behind our approach is a carefully constructed concept called Internal Variation (IV). The IV employs tensor decomposition and provides a computationally feasible substitution for Total Variation (TV), which has been considered in the literature to deal with similar problems but is problematic in high order tensor regression. Before applying our method to analyze the real data, we conduct comprehensive simulation studies to demonstrate the validity of our method in imaging signal identification. Then, we present our results from the analysis of a dataset based on the Philadelphia Neurodevelopmental Cohort for which we preprocessed the data including re-orienting, bias-field correcting, extracting, normalizing and registering the magnetic resonance images from 978 individuals. Our analysis identified a subregion across the cingulate cortex and the corpus callosum as being associated with individuals’ verbal reasoning ability, which, to the best of our knowledge, is a novel region that has not been reported in the literature. This finding is useful in further investigation of functional mechansims for verbal reasoning.

Rheumatoid arthritis (RA) is an autoimmune disease characterized by chronic inflammatory in joints. Invasive pannus is a characteristic pathological feature of RA. RA fibroblast-like synoviocytes (FLSs) are showed tumor-like biological characters that facilitate pannus generation. Importantly, it has been documented that extracellular vesicle (EVs) derived microRNAs have a vital role of angiogenesis in various immune inflammatory diseases. However, whether RA FLSs derived EVs can facilitate angiogenesis and the underlying mechanism is undefined. Herein, we aim to investigate the key role of RA FLSs derived EVs on angiogenesis in endothelial cells (ECs). We indicate that RA FLSs derived EVs promote ECs angiogenesis by enhancing migration and tube formation of ECs in vitro. Also, we confirm that RA FLSs derived EVs can significantly facilitate ECs angiogenesis with a matrigel angiogenesis mice model. In terms of the mechanisms, both RNAs and proteins in EVs play roles in promoting ECs angiogenesis, but the RNA parts are more fundamental in this process. By combining microRNA sequencing and qPCR results, miR-1972 is identified to facilitate ECs angiogenesis. The blockage of miR-1972 significantly abrogated the angiogenesis stimulative ability of RA FLSs derived EVs in ECs, while the overexpression of miR-1972 reversed the effect in ECs. Specifically, the p53 level is decreased, and the phosphorylated mTOR is upregulated in miR-1972 overexpressed ECs, indicating that miR-1972 expedites angiogenesis through p53/mTOR pathway. Collectively, RA FLSs derived EVs can promote ECs angiogenesis via miR-1972 targeted p53/mTOR signaling, targeting on RA FLSs derived EVs or miR-1972 provides a promising strategy for the treatment of patients with RA.

Consistent subtyping is employed in some gradual type systems to validate type conversions. The original definition by Siek and Taha serves as a guideline for designing gradual type systems with subtyping. Polymorphic types à la System F also induce a subtyping relation that relates polymorphic types to their instantiations. However, Siek and Taha’s definition is not adequate for polymorphic subtyping. The first goal of this article is to propose a generalization of consistent subtyping that is adequate for polymorphic subtyping and subsumes the original definition by Siek and Taha. The new definition of consistent subtyping provides novel insights with respect to previous polymorphic gradual type systems, which did not employ consistent subtyping. The second goal of this article is to present a gradually typed calculus for implicit (higher-rank) polymorphism that uses our new notion of consistent subtyping. We develop both declarative and (bidirectional) algorithmic versions for the type system. The algorithmic version employs techniques developed by Dunfield and Krishnaswami for higher-rank polymorphism to deal with instantiation. We prove that the new calculus satisfies all static aspects of the refined criteria for gradual typing. We also study an extension of the type system with static and gradual type parameters, in an attempt to support a variant of the dynamic criterion for gradual typing. Assuming a coherence conjecture for the extended calculus, we show that the dynamic gradual guarantee of our source language can be reduced to that of λ B, which, at the time of writing, is still an open question. Most of the metatheory of this article, except some manual proofs for the algorithmic type system and extensions, has been mechanically formalized using the Coq proof assistant.

In this article, we propose a two-way multinomial logistic model for recommender systems for categorical ratings. Specifically, we treat the possible ratings as mutually exclusive events, whose pro...

This work is motivated by multimodality breast cancer imaging data, which is quite challenging in that the signals of discrete tumor-associated microvesicles (TMVs) are randomly distributed with heterogeneous patterns. This imposes a significant challenge for conventional imaging regression and dimension reduction models assuming a homogeneous feature structure. We develop an innovative multilayer tensor learning method to incorporate heterogeneity to a higher-order tensor decomposition and predict disease status effectively through utilizing subject-wise imaging features and multimodality information. Specifically, we construct a multilayer decomposition which leverages an individualized imaging layer in addition to a modality-specific tensor structure. One major advantage of our approach is that we are able to efficiently capture the heterogeneous spatial features of signals that are not characterized by a population structure as well as integrating multimodality information simultaneously. To achieve scalable computing, we develop a new bi-level block improvement algorithm. In theory, we investigate both the algorithm convergence property, tensor signal recovery error bound and asymptotic consistency for prediction model estimation. We also apply the proposed method for simulated and human breast cancer imaging data. Numerical results demonstrate that the proposed method outperforms other existing competing methods.

Background/aims Rheumatoid arthritis (RA) is a progressive, chronic, even disabling systemic autoimmune disease. Imbalance between pathogenic immune cells and immunosuppressive cells is associated with the pathogenesis and development of RA and other autoimmune diseases. As Foxp3 is also expressed on activated CD4+ cells in the presence of inflammation, the identification of Treg cells in patients with RA remains a challenge. Methods Comprehensive analyses were carried out by Flow cytometry. Expression of Helios, CD226, T cell immunoreceptor with Ig and ITIM domains clinical samples and healthy controls. Results We have systemically examined three potential markers, Helios, CD226 and TIGIT, that are possibly related to Treg identification, and found that Helios expression on CD4+Foxp3+cells was decreased and negatively correlated with the disease activity of RA patients, while CD226 and TIGIT both showed elevated expression levels in CD4+Foxp3+cells in RA patients and they were not associated with disease activity of RA patients. Conclusion Taken together, our findings indicate that CD4+CD25hiCD127low/-Foxp3+Helios+ may represent the real Treg cell population in patients with RA.

After a century since the erection of the genus Manipuria from India, its type species M. dohertyi Jacoby was discovered in Yunnan Province of China. A new Manipuria species, M. yuaesp. nov., is described from Tibet and Yunnan, China. The new species differs from M. dohertyi by its larger size, unicolored elytra, and absence of a tooth-like prolongation in front of the mandible. Additional data is provided for M. dohertyi based on new material from China.

Because of the accessibility of big data collections from consumers, products, and stores, advanced sales forecasting capabilities have drawn great attention from many businesses, especially those in retail, because of the importance of forecasting in decision making. Improvement of forecasting accuracy, even by a small percentage, may have a substantial impact on companies’ production and financial planning, marketing strategies, inventory controls, and supply chain management. Specifically, our research goal is to forecast the sales of each product in each store in the near future. Motivated by tensor factorization methodologies for context-aware recommender systems, we propose a novel approach called the advanced temporal latent factor approach to sales forecasting, or ATLAS for short, which achieves accurate and individualized predictions for sales by building a single tensor factorization model across multiple stores and products. Our contribution is a combination of a tensor framework (to leverage information across stores and products), a new regularization function (to incorporate demand dynamics), and extrapolation of the tensor into future time periods using state-of-the-art statistical (seasonal autoregressive integrated moving-average models) and machine-learning (recurrent neural networks) models. The advantages of ATLAS are demonstrated on eight product category data sets collected by Information Resources, Inc., where we analyze a total of 165 million weekly sales transactions of over 15,560 products from more than 1,500 grocery stores. Summary of Contribution: Sales forecasting has been a task of long-standing importance. Accurate sales forecasting provides critical managerial implications for companies’ decision making and operations. Improvement of forecasting accuracy may have a substantial impact on companies’ production planning, marketing strategies, inventory controls, and supply chain management, among other things. This paper proposes a novel computational (machine-learning-based) approach to sales forecasting and thus is positioned directly at the intersection of computing and business/operations research.

A new species, Anoplophora siderea Bi, Chen & N. Ohbayashi, sp. nov. (繁星星天牛, Fán xîng xîng tiân niú), is described from Guangxi and Guangdong, China. Unknown males of Anoplophora cheni Bi & N. Ohbayashi, 2015, A. chiangi Hua & Zhang, 1991, A. flavomaculata (Gressitt, 1933) and A. multimaculata (Xie & Wang, 2015) are recorded for the first time. The endophalli of those species and A. ankangensis (Chiang, 1981) are described. New localities, habitus, endophallic structure and major diagnostic features of them are provided.

Ithocritus ruber (Hope, 1839), the type species of the genus Ithocritus Lacordaire, 1872 is reinvestigated, and a partially sympatric species, Ithocritus similis Bi & Lin, sp. nov. (相似短柄天牛, Xiāng sì duǎn bǐng tiān niú), is described. The genus Falsimalmus Breuning, 1956 is newly recorded from China, based on the discovery of Falsimalmus niger Breuning, 1956 from Yunnan. New localities, illustrations of habitus, endophallic structure and major diagnostic features for all involved taxa are provided.

How to acquire the most valuable consumers to grow your recommender system? We propose a dynamic consumer acquisition model to enable value-driven acquisition decisions. We build a model of consumer acquisition that takes into account the value that a consumer contributes to the recommender system, the cost of their participation (e.g., privacy loss), and the value of their participation to other consumers (via network externality). We also propose data-driven procedures to estimate this model to enable informed, value-driven acquisition decisions. On three different data sets, we perform comprehensive simulation-based evaluations to demonstrate the performance of this dynamic consumer acquisition model. We find nuanced relationships between the firm’s choice of incentive strategies and acquisition outcomes. Neither a constant pricing strategy nor a greedy pricing strategy may be optimal. Instead, under a moderately greedy strategy, where the firm only partially extracts the network externality from consumers, the dynamic acquisition sequence can outperform random acquisition sequences on firm utility, recommender system performance, and consumer surplus simultaneously. Our work contributes a novel theoretical framework, practical insights, and design artifacts to facilitate effective consumer acquisition in recommender systems.

A second Chinese species of the beetle family Jacobsoniidae, Sarothrias songi sp. nov., is described from Hainan Island. The new species is compared with and separated from similar congeners, supported by illustrations of diagnostic characters. A new collection record for S. sinicus Bi & Chen, 2015 from Yunnan is given, and the genital structures of this species are illustrated for the first time.

The nearly complete mitochondrial genome (mitogenome) of Sinopyrophorus schimmeli Bi et Li, the luminous click beetle recorded in Asia, is described in this study. It totalizes 15,951 bp and contai...

This paper presents a review of the genus Brachytrycherus Arrow from mainland China. Three new species are described and illustrated: B. bipunctatus Chang & Bi, sp. nov., B. denticulatus Chang & Bi, sp. nov., and B. humerali Chang & Bi, sp. nov. The diagnosis, distribution, type locality, biology, and ecology are provided for each species. A key to the species of Brachytrycherus known in China is updated.

Career situation of first and presenting author: Student for a master or a PhD. Introduction Long non-coding RNAs (lncRNAs) have drawn increasing attention because of the pivotal roles which they play in various types of autoimmune diseases, including rheumatoid arthritis (RA). LncRNA HOTAIR is a crucial lncRNA function as an oncogene in multiple cancers. Fibroblast-like synoviocytes (FLSs), a prominent component of hyperplastic synovial pannus tissue, are critical to synovial aggression and joint destruction in RA. However, the functions of lncRNA and the potential mechanisms remain to be further elucidated in FLSs of RA patients. Objectives Our present study aimed to investigate the expression and roles of lncRNA HOTAIR in RA-FLSs and explore its possible mechanism. Methods FLSs were cultured from synovial tissues of join. LncRNA and mircoRNA expression profiles in FLSs were screened by microarrays, and then we validated the results by Real-time Quantitative polymerase chain reaction (qRT-PCR). Small interfering RNA (siRNA) was then used to knock down the expression of HOTAIR in order to determine its role in RA FLSs. Cell viability was evaluated using the CCK-8 assay and flow cytometry. Cell invasion was analyzed by transwell chamber methodology. Bioinformatics analysis were performed to predict the possible competitive endogenous RNA (ceRNA) mechanisms via miRanda, PITA, RNAhybrid, as well as KEGG and Gene Ontology(GO) analysis. Results Both microarray analysis and qRT-PCR showed the expressions of lncRNA HOTAIR were up-regulated in RA FLSs compared with healthy controls (HCs). Transfection of HOTAIR-siRNA significantly decreased the expression of lncRNA HOTAIR in RA FLSs. HOTAIR knockdown largely inhibited cell proliferation and invasion of RA FLSs. Furthermore, the bioinformatics analysis predicted that some of microRNAs and mRNAs may be the downstream molecules of lncRNA HOTAIR. Considering the mircoRNA expression profiles detected by microarrays and the results from qRT-PCR, we designated miR-138 and miR-17–5 p as potential ceRNAs which lncRNA HOTAIR could directly bind to. In addition, the expressions of miR-138 and miR-17–5 p were markedly downregulated in RA FLSs, whereas the knockdown of lncRNA HOTAIR upregulated the expressions compared with the negative control group (NC-siRNA). Conclusions Our study illuminated that elevated lncRNA HOTAIR expression promoted the proliferation and invasion of RA FLSs. Meanwhile, it may function as a novel microRNAs sponging agent and regulate RA FLSs pathological behaviors via miR-138 or miR-17–5 p associated ceRNA network. In summary, the regulation of lncRNA HOTAIR may be a promising therapeutic strategy for RA in the future. Acknowledgements This work was supported by grants provided from Province Natural Science Fund of Guangdong, China (No.2014A030313080) and National Natural Science Foundation of China (No.81771750). Disclosure of Interest None declared

We propose a novel multivariate model for analyzing hybrid traits and identifying genetic factors for comorbid conditions. Comorbidity is a common phenomenon in mental health in which an individual suffers from multiple disorders simultaneously. For example, in the Study of Addiction: Genetics and Environment (SAGE), alcohol and nicotine addiction were recorded through multiple assessments that we refer to as hybrid traits. Statistical inference for studying the genetic basis of hybrid traits has not been well developed. Recent rank-based methods have been utilized for conducting association analyses of hybrid traits but do not inform the strength or direction of effects. To overcome this limitation, a parametric modeling framework is imperative. Although such parametric frameworks have been proposed in theory, they are neither well developed nor extensively used in practice due to their reliance on complicated likelihood functions that have high computational complexity. Many existing parametric frameworks tend to instead use pseudo-likelihoods to reduce computational burdens. Here, we develop a model fitting algorithm for the full likelihood. Our extensive simulation studies demonstrate that inference based on the full likelihood can control the type-I error rate, and gains power and improves the effect size estimation when compared with several existing methods for hybrid models. These advantages remain even if the distribution of the latent variables is misspecified. After analyzing the SAGE data, we identify three genetic variants (rs7672861, rs958331, rs879330) that are significantly associated with the comorbidity of alcohol and nicotine addiction at the chromosome-wide level. Moreover, our approach has greater power in this analysis than several existing methods for hybrid traits.Although the analysis of the SAGE data motivated us to develop the model, it can be broadly applied to analyze any hybrid responses.

Background: Long non-coding RNAs (lncRNAs) have drawn increasing attention because they play a pivotal role in various types of autoimmune diseases, including rheumatoid arthritis (RA). Fibroblast-like synoviocytes (FLSs), a prominent component of hyperplastic synovial pannus tissue, are the primary effector cells in RA synovial hyperplasia and invasion which can lead to joint destruction. In this study, we investigated whether lncRNAs could act as competing endogenous RNAs to regulate the pathological behaviors of RA-FLSs. Methods: LncRNA microarray was conducted to establish lncRNA expression profiles in FLSs isolated from RA patients and healthy controls (HCs). Differentially expressed lncRNAs were verified by quantitative real-time PCR (qRT-PCR). The functional role of lncRNA PICSAR downregulation was evaluated in RA-FLSs. We conducted molecular biological analysis to predict miRNAs which have a potential binding site for PICSAR and further refined the results by qRT-PCR. Luciferase reporter assay was adopted to validate the interaction of lncRNA PISCAR and miRNA-4701-5p. The functional role of miR-4701-5p upregulation was examined in in RA-FLSs. Findings: We identified a long intergenic non-protein-coding RNA162 (LINC00162), also known as lncRNA PICSAR (p38 inhibited cutaneous squamous cell carcinoma associated lincRNA), has significantly higher expression in RA-FLSs and was directly associated with cell proliferation, migration and invasion of RA-FLSs. Mechanistically, lncRNA PISCAR functioned through sponging miR-4701-5p in RA-FLSs. Interpretation: Our results reveal PISCAR may exert an essential role in promoting synovial invasion and joint destruction by sponging miRNA-4701-5p in RA and that targeting lncRNA PISCAR may have therapeutic potential on RA patients. Funding Statement: This work was supported by grants provided from the National Natural Science Foundation of China (81771750; 81671611 to YFP); Program from Guangdong Introducing Innovative and Entrepreneurial Teams (2016ZT06S252 to YFP); NIH R01 AR059103, R61 AR073409 and NIH STAR award (to SGZ). Declaration of Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Ethics Approval Statement: The research was approved by the ethics committee of the Third Affiliated Hospital of Sun Yat-sen University and all subjects provided the written informed consent in this study according to the Declaration of Helsinki principles.

Popular programming techniques such as shallow embeddings of Domain Specific Languages (DSLs), finally tagless or object algebras are built on the principle of compositionality. However, existing programming languages only support simple compositional designs well, and have limited support for more sophisticated ones. This paper presents the F+i calculus, which supports highly modular and compositional designs that improve on existing techniques. These improvements are due to the combination of three features: disjoint intersection types with a merge operator; parametric (disjoint) polymorphism; and BCD-style distributive subtyping. The main technical challenge is F+i’s proof of coherence. A naive adaptation of ideas used in System F’s parametricity to canonicity (the logical relation used by F+i to prove coherence) results in an ill-founded logical relation. To solve the problem our canonicity relation employs a different technique based on immediate substitutions and a restriction to predicative instantiations. Besides coherence, we show several other important meta-theoretical results, such as type-safety, sound and complete algorithmic subtyping, and decidability of the type system. Remarkably, unlike F

The new subfamily Sinopyrophorinae within Elateridae is proposed to accommodate a bioluminescent species, Sinopyrophorusschimmeli Bi & Li, gen. et sp. nov., recently discovered in Yunnan, China. This lineage is morphologically distinguished from other click-beetle subfamilies by the strongly protruding frontoclypeal region, which is longitudinally carinate medially, the pretarsal claws without basal setae, the hind wing venation with a well-defined wedge cell, the abdomen with seven (male) or six (female) ventrites, the large luminous organ on the abdominal sternite II, and the male genitalia with median lobe much shorter than parameres, and parameres arcuate, with the inner margin near its apical third dentate. Molecular phylogeny based on the combined 14 mitochondrial and two nuclear genes supports the placement of this taxon far from other luminescent click-beetle groups, which provides additional evidence for the multiple origin of bioluminescence in Elateridae. Illustrations of habitus and main diagnostic features of S.schimmeli Bi & Li, gen. et sp. nov. are provided, as well as the brief description of its luminescent behavior.

Recommender systems have been widely adopted by electronic commerce and entertainment industries for individualized prediction and recommendation, which benefit consumers and improve business intelligence. In this article, we propose an innovative method, namely the recommendation engine of multilayers (REM), for tensor recommender systems. The proposed method utilizes the structure of a tensor response to integrate information from multiple modes, and creates an additional layer of nested latent factors to accommodate between-subjects dependency. One major advantage is that the proposed method is able to address the "cold-start" issue in the absence of information from new customers, new products or new contexts. Specifically, it provides more effective recommendations through sub-group information. To achieve scalable computation, we develop a new algorithm for the proposed method, which incorporates a maximum block improvement strategy into the cyclic blockwise-coordinate-descent algorithm. In theory, we investigate both algorithmic properties for global and local convergence, along with the asymptotic consistency of estimated parameters. Finally, the proposed method is applied in simulations and IRI marketing data with 116 million observations of product sales. Numerical studies demonstrate that the proposed method outperforms existing competitors in the literature., Accepted by the Annals of Statistics