Generic Classification Research Articles

The First Complete Mitochondrial Genome of Genus Isocapnia (Plecoptera: Capniidae) and Phylogenetic Assignment of Superfamily Nemouroidea.

Capniidae are a family of stoneflies, also known as snow flies, who emerge in winter. The phylogeny of Capniidae is widely accepted to be based on morphological analysis. Until now, only five Capniidae mitochondrial genomes have been sequenced so far. In addition, sampling is required to determine an accurate phylogenetic association because the generic classification of this family is still controversial and needs to be investigated further. In this study, the first mitogenome of genus Isocapnia was sequenced with a length of 16,200 bp and contained 37 genes, including a control region, two rRNAs, 22 tRNAs, and 13 PCGs, respectively. Twelve PCGs originated with the common start codon ATN (ATG, ATA, or ATT), while nad5 used GTG. Eleven PCGs had TAN (TAA or TAG) as their last codon; however, cox1 and nad5 had T as their final codon due to a shortened termination codon. All tRNA genes demonstrated the cloverleaf structure, which is distinctive for metazoans excluding the tRNASer1 (AGN) that missed the dihydrouridine arm. A Phylogenetic analysis of the superfamily Nemouroidea was constructed using thirteen PCGs from 32 formerly sequenced Plecoptera species. The Bayesian inference and maximum likelihood phylogeny tree structures derived similar results across the thirteen PCGs. Our findings strongly supported Leuctridae + ((Capniidae + Taeniopterygidae) + (Nemouridae + Notonemouridae)). Ultimately, the best well-supported generic phylogenetic relationship within Capniidae is as follows; (Isocapnia + (Capnia + Zwicknia) + (Apteroperla + Mesocapnia)). These findings will enable us to better understand the evolutionary relationships within the superfamily Nemouroidea and the generic classification and mitogenome structure of the family Capniidae.

First cladistic analysis of Toxotarsinae (Diptera: Calliphoridae), with insights on the evolution of the group and on the transformation series of some historically controversial characters.

Toxotarsinae is a subfamily of Calliphoridae (Diptera: Calyptratae: Oestroidea) with 11 species currently distributed in three genera: Neta Shannon, 1926, Sarconesia Bigot, 1857, and Toxotarsus Macquart, 1851. All known species are endemic to South America, mostly restricted to areas with cooler temperatures-like high elevation areas of the Andean Cordillera-and lowlands and coastal regions in the subtropical and temperate parts of the continent. The classification of the subfamily has been somewhat controversial, with eleven, mostly monotypic nominal genera established to accommodate its species, mostly due to distinct interpretations of certain controversial characters by different authors. To provide a sound basis for a generic classification, we performed the first study aimed to understand the transformation series of those controversial characters and character states under a phylogenetic framework. Our maximum parsimony analyses, under both equal and implied weighting of characters and including all currently known species in the subfamily, retrieved two main clades of Toxotarsinae: the roraima group, composed of Sarconesia roraima (Townsend, 1935), Neta chilensis (Walker, 1836), and S. magellanica (Le Guillou, 1842), and the splendida group, composed of the remaining species of the subfamily. The position of S. magellanica varied, but the species was mostly recovered within the roraima group except in the analyses under implied weighting with k values between 1 and 6. Our results, which include an explicit interpretation of the transformation series associated with some characters and character states commonly used in Toxotarsinae systematics, suggest that both Sarconesia and Neta, along with other genera proposed in the past for species of the subfamily such as Sarconesiomima Lopes & Albuquerque, 1955, Chlorobrachycoma Townsend, 1918, Sarconesiopsis Townsend, 1918, and Roraimomusca Townsend, 1935, previously suggested to be synonyms of Sarconesia, do not properly reflect the evolution of lineages in the subfamily and should not be considered as valid nominal genera. Toxotarsus was the only genus consistently recovered as monophyletic and, based on the phylogenetic relationships recovered herein, we suggest including all known Toxotarsinae within this genus, with the roraima and splendida clades treated as species-groups. Finally, we discuss the characters commonly used to delimit the taxa subordinated to Toxotarsinae, such as the length of the first flagellomere, the position of the rays of the arista relative to the pedicel, the extension of the plumosity of the arista, and the number of postsutural acrostichal setae.

Classifying the unknown: Insect identification with deep hierarchical Bayesian learning

Abstract Classifying insect species involves a tedious process of identifying distinctive morphological insect characters by taxonomic experts. Machine learning can harness the power of computers to potentially create an accurate and efficient method for performing this task at scale, given that its analytical processing can be more sensitive to subtle physical differences in insects, which experts may not perceive. However, existing machine learning methods are designed to only classify insect samples into described species, thus failing to identify samples from undescribed species. We propose a novel deep hierarchical Bayesian model for insect classification, given the taxonomic hierarchy inherent in insects. This model can classify samples of both described and undescribed species; described samples are assigned a species while undescribed samples are assigned a genus, which is a pivotal advancement over just identifying them as outliers. We demonstrated this proof of concept on a new database containing paired insect image and DNA barcode data from four insect orders, including 1040 species, which far exceeds the number of species used in existing work. A quarter of the species were excluded from the training set to simulate undescribed species. With the proposed classification framework using combined image and DNA data in the model, species classification accuracy for described species was 96.66% and genus classification accuracy for undescribed species was 81.39%. Including both data sources in the model resulted in significant improvement over including image data only (39.11% accuracy for described species and 35.88% genus accuracy for undescribed species), and modest improvement over including DNA data only (73.39% genus accuracy for undescribed species). Unlike current machine learning methods, the proposed deep hierarchical Bayesian learning approach can simultaneously classify samples of both described and undescribed species, a functionality that could become instrumental in biodiversity monitoring across the globe. This framework can be customized for any taxonomic classification problem for which image and DNA data can be obtained, thus making it relevant for use across all biological kingdoms.

Combining target enrichment and Sanger sequencing data to clarify the systematics of the diverse Neotropical butterfly subtribe Euptychiina (Nymphalidae, Satyrinae)

AbstractThe diverse, largely Neotropical subtribe Euptychiina is widely regarded as one of the most taxonomically challenging groups among all butterflies. Over the last two decades, morphological and molecular studies have revealed widespread paraphyly and polyphyly among genera, and a comprehensive, robust phylogenetic hypothesis is needed to build a firm generic classification to support ongoing taxonomic revisions at the species level. Here, we generated a dataset that includes sequences for up to nine nuclear genes and the mitochondrial COI ‘barcode’ for a total of 1280 specimens representing 449 described and undescribed species of Euptychiina and 39 out‐groups, resulting in the most complete phylogeny for the subtribe to date. In combination with a recently developed genomic backbone tree, this dataset resulted in a topology with strong support for most branches. We recognize eight major clades that each contain two or more genera, together containing all but seven Euptychiina genera. We provide a summary of the taxonomy, diversity and natural history of each clade, and discuss taxonomic changes implied by the phylogenetic results. We describe nine new genera to accommodate 38 described species: Lazulina Willmott, Nakahara & Espeland, gen.n., Saurona Huertas & Willmott, gen.n., Argentaria Huertas & Willmott, gen.n., Taguaiba Freitas, Zacca & Siewert, gen.n., Xenovena Marín & Nakahara, gen.n., Deltaya Willmott, Nakahara & Espeland, gen.n., Modica Zacca, Casagrande & Willmott, gen.n., Occulta Nakahara & Willmott, gen.n., and Trico Nakahara & Espeland, gen.n. We also synonymize Nubila Viloria, Andrade & Henao, 2019 (syn.n.) with Splendeuptychia Forster, 1964, Macrocissia Viloria, Le Crom & Andrade, 2019 (syn.n.) with Satyrotaygetis Forster, 1964, and Rudyphthimoides Viloria, 2022 (syn.n.) with Malaveria Viloria & Benmesbah, 2020. Overall, we revised the generic placement of 79 species (74 new generic combinations and five revised combinations), and as a result all but six described species of Euptychiina are accommodated within 70 named, monophyletic genera. For all newly described genera, we provide illustrations of representative species, drawings of wing venation and male and (where possible) female genitalia, and distribution maps, and summarize the natural history of the genus. For three new monotypic genera, Occulta gen.n., Trico gen.n. and Xenovena gen.n. we provide a taxonomic revision with a review of the taxonomy of each species and data from examined specimens. We provide a revised synonymic list for Euptychiina containing 460 valid described species, 53 subspecies and 255 synonyms, including several new synonyms and reinstated species.

Inpatient antibacterial use trends and patterns, China, 2013-2021.

To analyse trends and patterns in inpatient antibacterial use in China's tertiary and secondary hospitals between 2013 and 2021. The analysis involved quarterly data from hospitals covered by China's Center for Antibacterial Surveillance. We obtained information on hospital characteristics (e.g. province, a de-identified hospital code, hospital level and inpatient days) and antibacterial characteristics (e.g. generic name, drug classification, dosage, administration route and usage volume). We quantified antibacterial use as the number of daily defined doses per 100 patient-days. The analysis took into account the World Health Organization's (WHO's) Access, Watch, Reserve classification of antibiotics. Between 2013 and 2021, overall antibacterial use in inpatients decreased significantly from 48.8 to 38.0daily defined doses per 100 patient-days (P < 0.001). In 2021, the variation between provinces was almost twofold: 29.1daily defined doses per 100 patient-days in Qinghai versus 55.3 in Tibet. The most-used antibacterials in both tertiary and secondary hospitals throughout the study period were third-generation cephalosporins, which comprised around one third of total antibacterial use. Carbapenems entered the list of most-used antibacterial classifications in 2015. The most frequently used antibacterials in WHO's classification belonged to the Watch group: usage increased significantly from 61.3% (29.9/48.8) in 2013 to 64.1% (24.4/38.0) in 2021 (P < 0.001). Antibacterial use in inpatients decreased significantly during the study period. However, the rising proportion of last-resort antibacterials used is concerning, as is the large gap between the proportion of antibacterials used belonging to the Access group and WHO's global target of no less than 60%.

Unmasking hidden disparities: a comparative observational study examining the impact of different rurality classifications for health research in Aotearoa New Zealand

ObjectivesExamine the impact of two generic—urban–rural experimental profile (UREP) and urban accessibility (UA)—and one purposely built—geographic classification for health (GCH)—rurality classification systems on the identification of rural–urban health disparities in...

Effect of Different Excipients on Fungal Flora during Aerobic Fermentation of Thermal Hydrolyzed Kitchen Waste

In this paper, a comparative study was conducted on the aerobic fermentation of kitchen waste pretreated by thermal hydrolysis and three different excipients, the dynamic changes of temperature and organic matter of kitchen waste after thermal hydrolysis were measured during aerobic fermentation with peanut shell, corn stalk and corn cob as additives, and high-throughput sequencing was performed on the samples of the three excipients in the high temperature fermentation stage to identify the dominant bacterial community in the high temperature region of different excipients. The results showed that the dominant bacterial communities of peanut shell, corn stalk and corn cob were similar at the phylum classification level. Among them, Ascomycota accounted for 97.68%, 99.55% and 99.98% in HS, YM and YX treatment groups, respectively, which means it was the absolute dominant fungal phyla in high temperature fermentation stage. At the level of genus classification, there were differences among the dominant bacterial genera in each group. The main bacterial genera in peanut shell treatment group were Aspergillus, unclassified_f__Dipodascaceae, Penicillium, unclassified_o__Sordariales, Candida and Diutina. The main bacterial genera in corn stalk treatment group were Candida, Aspergillus and Penicillium. The main bacteria in corn cob treatment group was unclassified_o__Sordariales. The percentage of saprophytic fungi in HS, YM and YX high-temperature treatment groups was 96.40%, 99.25% and 99.97%, respectively. Saprophytic fungi played a major role in the high-temperature fermentation stage.

Leveraging relevant summarized information and multi-layer classification to generalize the detection of misleading headlines

Disinformation is an important problem facing society nowadays. Given the rapid and easy access to information, news stories quickly go viral, the vast majority of which are misleading and with no prospect of verification. Specifically, the headline of a correctly designed news item must correspond to a summary of the main information of that news item and it should be neutral. However, many headlines circulating on the Internet use false or distorted information, seeking to confuse or mislead the reader. Misleading headlines indicate a dissonance between the headline and the content of the news story. From a computational perspective, this problem is being tackled as a Stance Detection problem between the headline and the body text of the news item. This paper contributes to the fight against the spread of misleading information by presenting a generic and flexible multi-level hierarchical classification. The approach is based on two stages that enable the detection of the stance between the news headline and the body text. The proposed architecture, called HeadlineStanceChecker+ uses the headline and only the essential information of the news item (not the full body text) as inputs. To extract this essential information, different summarization approaches (extractive and abstractive) are analyzed in order to determine the most relevant information for the task. The experimentation has been carried out using the Fake News Challenge (FNC-1) dataset. A 94.49% accuracy was obtained using extractive summaries, which were more helpful than abstractive ones. HeadlineStanceChecker+ improves the accuracy results of existing state-of-the-art systems. In conclusion, using automatic extractive summaries together with the two-stage generic architecture is an effective solution to the problem.

Multi-Gene Phylogeny and Taxonomy of the Wood-Rotting Fungal Genus Phlebia sensu lato (Polyporales, Basidiomycota).

Phlebia s.l. (Polyporales, Basidiomycota) accommodates numerous species of wood-inhabiting fungi within the phylum Basidiomycota. The present study employs the morphological and phylogenetic approaches to revise the generic and species classification of Phlebia s.l. and surveys the species diversity. The phylogenetic analyses were performed using multiple gene regions viz. the internal transcribed spacer (ITS), the large subunit nuclear ribosomal RNA gene (nLSU), the translation elongation factor 1-α (tef1), the small subunit of mitochondrial rRNA gene (mtSSU), the glyceraldehyde 3-phosphate dehydrogenase (GAPDH), RNA polymerase II largest subunit (rpb1), and RNA polymerase II second largest subunit (rpb2). We overall recognize twenty genera of Phlebia s.l., including three new genera viz. Ceriporiopsoides, Phlebicolorata, and Pseudophlebia, seven new species viz. Crustodontia rhododendri, Hydnophlebia fissurata, Luteoporia straminea, Merulius sinensis, Mycoaciella brunneospina, Phlebia niveomarginata, and P. poroides and seventeen new combinations viz. Ceriporiopsoides guidella, C. lagerheimii, Hydnophlebia acanthocystis, H. capsica, H. fimbriata, Merulius fuscotuberculatus, M. nantahaliensis, M. tomentopileatus, Mycoacia tuberculata, Mycoaciella uda, Phlebicolorata alboaurantia, Ph. brevispora, Ph. pseudoplacenta, Ph. rosea, Pseudophlebia lindtneri, Ps. semisupina, and Ps. setulosa. Descriptions, illustrations, phylogenetic trees to show the placements, and notes of new taxa are provided.

Open-Set Classification for Signal Diagnosis of Machinery Sensor in Industrial Environment

In recent years, the signal diagnosis on devices operating under industrial environment has attracted increasing attention. Most data-driven signal diagnosis methods are based on a closed-set assumption that class sets of training and test data are the same. However, in industrial scenarios, during the running process of the device, the operating environment and condition may change over time, continuing generating data belonging to unknown classes with new characteristics and distribution. The unknown classes usually reflect new modes or faults of the device needed to be captured. They are unavailable in training phase, contradicting the closed-set assumption. Existing methods are inappropriate to this type of open-set classification, requiring to classify known classes and recognize unknown classes. To address this challenging problem, this article proposes a generic open-set signal classification method. First, we apply Fourier transform to convert the sensor signals from time domain to frequency domain, then data in the time and frequency domains are fused. Next, a variational encoder-classifier network is proposed to classify known classes and learn the distribution of feature space to extract robust latent features. Finally, based on extreme value theory and entropy, a pair of discriminators determine whether samples belong to unknown or not. The experimental results on two vibration-signal datasets from bearings and nuclear reactor demonstrate the effectiveness and superiority of our proposed open-set signal classification method, especially in practical applications.

Reinforced Two-Stream Fuzzy Neural Networks Architecture Realized With the Aid of One-Dimensional/Two-Dimensional Data Features

A novel structure of reinforced two-stream fuzzy neural networks (TSFNNs) realized with the aid of fuzzy logic and transfer learning method is presented. This architecture consists of a TSFNN and a fusion strategy. TSFNN architecture consists of two combined networks of both fuzzy rules-based radial basis function neural networks (FRBFNN) and convolutional neural networks (CNNs). In the TSFNN architecture, one stream employs the deep CNN to extract the spatial information of images and effectively learn the high-level features and another stream uses the FRBFNN to analyze the distribution of data points over the input space and learn to capture complex relationships in data. In the fusion strategy, the outputs of two streams are concatenated by a softmax function, which normalizes the output to a probability distribution. A transfer learning method is considered to reconstruct new data representation as the inputs of CNN to mine potential spatial features of data. Moreover, L <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> -norm regularization is used to alleviate the possible overfitting and enhance the generalization ability. The proposed method not only inherits the advantages of FRBFNN and CNN such as global feature extraction ability, good local approximating performance, ability of handling uncertainty by fuzzy logic but also improves the classification performance under the synergy between two-stream architecture and the fusion strategy. Experimental results obtained for a diversity of datasets as well as partial discharge datasets be using in the real life of fault diagnosis and black plastic wastes datasets for recycling confirm the effectiveness of the proposed TSFNN. A comprehensive comparative analysis is covered. This design can simultaneously capture different level information of inputs and easing the insufficient problem of extracting features from a single steam. Especially, we show that the synergistic effect of FRBFNN, CNN, enabling deep learning for generic classification tasks and multipoint crossover, and L <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> -norm regularization can effectively improve the performance of the TSFNNs.

Surface layer proteins in species of the family Lactobacillaceae.

The S-layer or surface layer protein (SLP) is the most ancient biological envelope, highly conserved in several Bacteria and Archaea. In lactic acid bacteria (LAB), SLP is only found in species belonging to the Lactobacillaceae family, many of them considered probiotic microorganisms. New reclassification of members within the Lactobacillaceae family (International Journal of Systematic and Evolutionary Microbiology, 2020, 70, 2782) and newly sequenced genomes demands an updated revision on SLP genes and domain organization. There is growing information concerning SLP occurrence, molecular biology, biophysical properties, and applications. Here, we focus on the prediction of slp genes within the Lactobacillaceae family, and specifically, on the neat interconnection between the two different modular SLP domain organizations and the new reclassified genera. We summarize the results in a concise tabulated manner to review the present knowledge on SLPs and discuss the most relevant and updated concepts regarding SLP sequence clustering. Our assessment is based on sequence alignments considering the new genera classification and protein domain definition with post-translational modifications. We analyse the difficulties encountered to resolve the SLPs 3D structure, describing the need for structure prediction approaches and the relation between protein structure and its anchorage mechanism to the cell wall. Finally, we enumerate new SLP applications regarding heterologous display, pathogen exclusion, immunostimulation, and metal binding.

Genetic Diversity and Population Structure of a Wide Pisum spp. Core Collection.

Peas (Pisum sativum) are the fourth most cultivated pulses worldwide and a critical source of protein in animal feed and human food. Developing pea core collections improves our understanding of pea evolution and may ease the exploitation of their genetic diversity in breeding programs. We carefully selected a highly diverse pea core collection of 325 accessions and established their genetic diversity and population structure. DArTSeq genotyping provided 35,790 polymorphic DArTseq markers, of which 24,279 were SilicoDArT and 11,511 SNP markers. More than 90% of these markers mapped onto the pea reference genome, with an average of 2787 SilicoDArT and 1644 SNP markers per chromosome, and an average LD50 distance of 0.48 and 1.38 Mbp, respectively. The pea core collection clustered in three or six subpopulations depending on the pea subspecies. Many admixed accessions were also detected, confirming the frequent genetic exchange between populations. Our results support the classification of Pisum genus into two species, P. fulvum and P. sativum (including subsp. sativum, arvense, elatius, humile, jomardii and abyssinicum). In addition, the study showed that wild alleles were incorporated into the cultivated pea through the intermediate P. sativum subsp. jomardii and P. sativum subsp. arvense during pea domestication, which have important implications for breeding programs. The high genetic diversity found in the collection and the high marker coverage are also expected to improve trait discovery and the efficient implementation of advanced breeding approaches.

Generic classification of Asian horned toads (Anura: Megophryidae: Megophryinae) and monograph of Chinese species.

The subfamily Megophryinae, as a representative batrachian group of the Oriental Realm and one of the most diverse groups of amphibians, has attracted considerable attention due to continued conjecture regarding its generic classification and failure to reach a satisfactory consensus. China boasts the richest diversity of Asian horned toads, containing some two thirds of the total species cataloged. However, most species have a complicated taxonomic history, resulting in multiple misidentifications. As such, an overall clarification of historical records and regional checklists is required. In the current investigation, we established the phylogeny of the Asian horned toads and performed detailed examinations with redefinitions of several important morphological traits. Based on the phylogenetic relationships and morphological differences, we propose a new ten-genus classification for the Asian horned toad subfamily Megophryinae: i.e., Brachytarsophrys, Atympanophrys, Grillitschia, Sarawakiphrys gen. nov., Jingophrys gen. nov., Xenophrys, Megophrys, Pelobatrachus, Ophryophryne, and Boulenophrys. Revisions on the diagnosability, distribution, and content of each genus are provided. Furthermore, we present a careful review of the taxonomic history of Asian horned toad species from China and provide a monograph of congeners, including six species of Brachytarsophrys, four species of Atympanophrys, five species of Jingophrys gen. nov., 10 species of Xenophrys, two species of Ophryophryne, and 60 species of Boulenophrys. Finally, we discuss the importance of traditional morphological traits based on multiple populations in taxonomic work as well as taxonomic inflation caused by the genetic species delimitation.

Alimentary Temporalities: Queer Food, Asexuality, and the Global Culinary-Roman

ABSTRACT: This essay explores the queer temporalities figured within “culinary-romane”: those contemporary, coming-of-age novels that use food to interrogate the literary construct of the female journey. In opposition to the female Bildungsroman , which maps maturation via hegemonic temporal structures—historical, narrative, reproductive—the culinary-roman cleaves development from heteropatriarchal time. Instead, it conceives anti-normative models of female development via “alimentary temporalities”: atemporal narrative spaces constructed through recipes, food nightmares, family meals, and magical cooking and eating. Using Han Kang’s surrealist allegory The Vegetarian (2007) as a case study, this essay uncovers the ways strange alimentary temporalities in Han’s novel formally decenter sexual attraction as a marker of modern subject formation, uncovering the Bildungsroman ’s structural perpetuation of compulsory sexuality and its attendant abuses. Through its food-driven, double frame-tale narration, The Vegetarian unsettles received notions of narrative coherence, generic classification, and the relationship between sexuality and subjectivity.

Identification of novel genera and subcluster classifications for mycobacteriophages.

Aim: To identify novel genera amongst mycobacteriophages (MP) and verify a hypothesised correlation between the taxonomy set by the International Committee on Taxonomy of Viruses (ICTV) and the National Centre for Biotechnology Information (NCBI) with that of the Actinobacteriophage Database, which may help formalise subcluster assignment. Methods: A dataset of 721 MP genomes was analysed using VIRIDIC, a nucleotide alignment-based software that predicts genus assignments. Potentially novel genera were analysed using Gegenees and VICTOR, respectively. These genera were then compared to the subclusters assigned by the Actinobacteriophage Database to verify a hypothesis that one genus can be assigned to one subcluster (i.e., the genus-subcluster hypothesis). Results: Initially, when comparing the current genus classifications of the 721 MP dataset to the Actinobacteriophage database subcluster assignments, 83.3% of subclusters supported the genus-subcluster hypothesis. Following the sequential VIRIDIC, Gegenees and VICTOR analyses, a total of 20 novel genera were identified based on a ≥ 70% and ~ 50% similarity threshold for VIRIDIC and Gegenees, respectively, and a monophyletic nature in the VICTOR output. Interestingly, these criteria also appear to support the creation of 13 novel subclusters, which would increase the support for the genus-subcluster hypothesis to 97.6%. Conclusion: The link between genus and subcluster classifications appears robust, as most subclusters can be assigned a single genus and vice versa. By relating the taxonomic and clustering classification systems, they can be easily kept up to date to best reflect MP diversity, which could aid the rapid selection of related (or diverse) phages for research, therapeutic and diagnostic purposes.

A Local–Global Interactive Vision Transformer for Aerial Scene Classification

Generic image classification has been widely studied in the past decade. However, for the bird-view aerial images, aerial scene classification remains challenging due to the dramatic variation of the scale and object size. Existing methods usually learn the aerial scene representation from the convolutional neural networks (CNN), which focus on the local response of an image. In contrast, the recently-developed vision transformers (ViT) can learn stronger global representation for aerial scenes, but are not qualified enough to highlight the key objects in an aerial scene due to the dramatic size and scale variation. To address this challenge, in this paper, we propose a local-global interactive vision transformer (LG-ViT) for this task. It is based on our deliberately designed local-global feature interactive learning scheme, which intends to jointly utilize the local-wise and global-wise feature representations. To realize the learning scheme in an end-to-end manner, the proposed LG-ViT consists of three key components, namely, local-global feature extraction, local-global feature interaction, and local-global semantic constraints. Extensive experiments on three aerial scene classification benchmarks, namely, UCM, AID and NWPU, demonstrate the effectiveness of the proposed LG-ViT against the state-of-the-art methods. The effectiveness of each component and generalization capability is also validated.

Correlation between Abnormal Gait Pattern With Femoral Neck Stress Fracture In Athletes: A Systematic Review

Backgrounds: Stress fractures are common overuse injuries in the lower extremities. Repetitive episodes of high-intensity or extended-duration axial load to the leg place the bone at risk of stress-related injury. The femoral neck is an uncommon location for stress fracture (less than 5% of all stress fractures). Fracture location, type, and grade permits generic dichotomized classification of “low-risk” and “high-risk” fractures. Tension-side femoral neck stress fractures are considered “high-risk” because of their potential for displacement, nonunion, and avascular necrosis if displaced. Fractures in locations prone to these 3 outcomes are categorized as “high risk.” These include anterior tibial cortex, medial malleolus, talar neck, dorsal tarsal navicular, proximal fifth metatarsal metaphysis, tension side patella, and tension side of the femoral neck. The risk of avascular necrosis following treatment of displaced femoral neck fractures in adults may be as high as 45%. In runners, pain typically begins with onset of weight bearing early in the run. Pain may progressively increase and does not remit until the run ends. In some athletes, the desire to train or perform may supersede the pain. This may lead to disastrous consequences if a femoral neck stress fracture completes itself and displaces. This paper describes side effects abnormal gait pattern to femoral neck stress fractures in athlete. Methods: Our trial was an international, expertise-based, randomized, controlled trial. Details of the trial objectives and design have been published previously. Additional information about the eligibility criteria, interventions, follow-up, outcome definitions, and statistical analysis. To identify studies pertaining to the clinical results about Correlation between Abnormal Running Gait Pattern and Femoral Neck Stress Fracture, we reviewed the Cochrane, Pubmed, Embase databases for relevant articles published up to July 2022. We also reviewed the references of all identified articles to identify additional studies. Search terms were as follows: femoral neck stress fracture, femoral fracture, running gait. Following the PICOS (Participants, Interventions, Comparisons, Outcomes and Study design) principle, the key search terms included (P) patients were runner with FNSFs; (I) patients were running as a recreational sport, and or professional athlete; (C/O) the outcomes including sign and symptoms, femoral neck stress fracture, length of rehabilitation, time to get back in early performance in sport; (S) RTC, cohort study, or case control study. Results: A total of 13 RCTs, meta- analysis and systematic review correlation abnormal running gait with femoral neck stress fractures. Discussions: There are correlations between abnormal running gait with femoral neck fractures, because abnormal running gait with high intense could make bone stress injury. However, bone stress injury at neck femoral is one of many factors that commonly happen become a femoral neck stress fractures. Conclusions: Abnormal running gait combining with high intense training are etiology of bone stress injuries in athletes. Bone stress injuries in femoral neck could possibly become femoral neck stress fractures.

Detecting and analyzing fine-grained user roles in social media?

While identifying specific user roles in social media -in particular bots or spammers- has seen significant progress, generic and all-encompassing user role classification remains elusive on the large data sets of today?s social media. Yet, such broad classifications enable a deeper understanding of user interactions and pave the way for longitudinal studies, capturing the evolution of users such as the rise of influencers. Studies of generic roles have been performed predominantly in a small scale, establishing fundamental role definitions, but relying mostly on ad-hoc, data set-dependent rules that need to be carefully hand-tuned. We build on those studies and provide a largely automated, scalable detection of a wide range of roles. Our approach clusters users hierarchically on salient, complementary features such as their actions, their ability to trigger reactions and their network positions. To associate these clusters with roles, we use supervised classifiers: trained on human experts on completely new media, but transferable on related data sets. Furthermore, we employ the combination of samples in order to improve scalability and allow probabilistic assignments of user roles. Our evaluation on Twitter indicates that a) stable and reliable detection of a wide range of roles is possible b) the labeling transfers well as long as the fundamental properties don?t strongly change between data sets and c) the approaches scale well with little need for human intervention.

Systematics of the avian family Alaudidae using multilocus and genomic data

The family Alaudidae, larks, comprises 93–100 species (depending on taxonomy) that are widely distributed across Africa and Eurasia, with single species extending their ranges to North and northernmost South America and Australia. A decade-old molecular phylogeny, comprising ∼80% of the species, revealed multiple cases of parallel evolution and large variation in rates of morphological evolution, which had misled taxonomists into creating many non-monophyletic genera. Here, we reconstruct the phylogeny of the larks, using a dataset covering one mitochondrial and 16 nuclear loci and comprising all except one of the currently recognised species as well as several recently proposed new species (in total 133 taxa; not all loci available for all species). We provide additional support using genome-wide markers to infer a genus-level phylogeny based on near-complete generic sampling (in total 51 samples of 44 taxa across 40 species). Our results confirm the previous findings of rampant morphological convergence and divergence, and reveal new cases of paraphyletic genera. We propose a new subfamily classification, and also that the genus Mirafra is divided into four genera to produce a more balanced generic classification of the Alaudidae. Our study supports recently proposed species splits as well as some recent lumps, while also questioning some of the latter. This comprehensive phylogeny will form an important basis for future studies, such as comparative studies of lark natural history, ecology, evolution and conservation.