New species of Tropicoporus (Basidiomycota, Hymenochaetales, Hymenochaetaceae) from India, with a key to Afro-Asian Tropicoporus species.

The Inonotuslinteus complex, predominantly reported from East Asia, Mesoamerica and Caribbean countries, was circumscribed into Tropicoporus as one of the new genera, based on morphological and phylogenetic data. The present paper describes four new species of Tropicoporus from India. Morphological characteristics and phylogenetic analyses, based on ITS and nLSU data, delimited the new species, which are named T.cleistanthicola, T.indicus, T.pseudoindicus and T.tamilnaduensis. The pairwise homoplasy index (PHI) test was done to confirm the distinctive nature of the new species. The traits of Indian species remain distinct from one another, except for the pileate basidiome with the mono-dimitic hyphal system, cystidioles and broadly ellipsoid basidiospores. Descriptions, illustrations, PHI test results and a phylogenetic tree to show the position of the new species are provided. In addition, an identification key to Tropicoporus in Asia and an African species is given.

Human-Robot Collaborations in Smart Manufacturing Environments: Review and Outlook.

The successful implementation of Human-Robot Collaboration (HRC) has become a prominent feature of smart manufacturing environments. Key industrial requirements, such as flexibility, efficiency, collaboration, consistency, and sustainability, present pressing HRC needs in the manufacturing sector. This paper provides a systemic review and an in-depth discussion of the key technologies currently being employed in smart manufacturing with HRC systems. The work presented here focuses on the design of HRC systems, with particular attention given to the various levels of Human-Robot Interaction (HRI) observed in the industry. The paper also examines the key technologies being implemented in smart manufacturing, including Artificial Intelligence (AI), Collaborative Robots (Cobots), Augmented Reality (AR), and Digital Twin (DT), and discusses their applications in HRC systems. The benefits and practical instances of deploying these technologies are showcased, emphasizing the substantial prospects for growth and improvement in sectors such as automotive and food. However, the paper also addresses the limitations of HRC utilization and implementation and provides some insights into how the design of these systems should be approached in future work and research. Overall, this paper provides new insights into the current state of HRC in smart manufacturing and serves as a useful resource for those interested in the ongoing development of HRC systems in the industry.

Taxonomic and Phylogenetic Studies of Saprobic Fungi Associated with Mangifera indica in Yunnan, China.

Fungi are a large and diverse group of microorganisms, and although the estimated number of species ranges between 2 and 11 million, only around 150,000 species have been described thus far. The investigation of plant-associated fungi is beneficial for estimating global fungal diversity, for ecosystem conservation, and for the continued development of industry and agriculture. Mango, one of the world's five most economically important fruit crops, is grown in over 100 countries and has been demonstrated to have a great economical value. During surveys of mango-associated saprobic fungi in Yunnan (China), we discovered three new species (Acremoniisimulans hongheensis, Chaenothecopsis hongheensis and Hilberina hongheensis) and five new records. The phylogenetic analyses of multi-gene sequences (LSU, SSU, ITS, rpb2, tef1-α and tub2) coupled with morphological examinations were used to identify all the taxa.

Taxonomy and Phylogeny of Fungi Associated with Mangifera indica from Yunnan, China.

During investigations of saprobic fungi associated with mango (Mangifera indica) in Baoshan and Honghe of Yunnan Province (China), fungal taxa belonging to the orders Botryosphaeriales, Calosphaeriales, Chaetothyriales, Diaporthales, and Xylariales were recorded. Morphological examinations coupled with phylogenetic analyses of multigene sequences (ITS, LSU, SSU, tef1-α, rpb1, rpb2, ß-tubulin and CAL) were used to identify the fungal taxa. A new genus viz. Mangifericola, four new species viz. Cyphellophora hongheensis, Diaporthe hongheensis, Hypoxylon hongheensis, and Mangifericola hongheensis, four new host and geographical records viz. Aplosporella artocarpi, Hypomontagnella monticulosa, Paraeutypella citricola and Pleurostoma ootheca, and two new collections of Lasiodiplodia are reported.

Taxonomic Reappraisal of Periconiaceae with the Description of Three New Periconia Species from China.

As a result of an ongoing research survey of microfungi in Yunnan, China, several saprobic ascomycetes were collected from various host substrates. Preliminary morphological analyses identified a few of these taxa as Periconia species. We obtained DNA sequence data of the Periconia species from pure cultures and investigated their phylogenetic affinities. Phylogenetic analyses of a combined LSU, ITS, SSU and tef1-α sequence dataset demonstrated that five isolates of Periconia formed well-resolved subclades within Periconiaceae. Accordingly, three new Periconia species are introduced viz. P. artemisiae, P. chimonanthi and P. thysanolaenae, and new host and geographical records of P. byssoides and P. pseudobyssoides, are also reported from dead branches of Prunus armeniaca and Scrophularia ningpoensis. Periconia celtidis formed a monophyletic clade with P. byssoides in the present phylogenetic analyses. Results of the pairwise homoplasy index (PHI) test indicated significant recombination between P. byssoides and P. celtidis. Therefore, P. celtidis has been synonymized under P. byssoides. In addition, we re-illustrated and studied the type specimen of the sexual genus Bambusistroma. As a type species of Bambusistroma, B. didymosporum features similar morphology to the sexual morph of Periconia homothallica and P. pseudodigitata. We therefore synonymize Bambusistroma under Periconia based on morphological and phylogenetic evidence. Furthermore, our new isolates produced brown conidia of asexual morph in agar media typical of the genus Noosia. Based on morphological comparison with Periconia in vitro and phylogenetic status of Noosia, we also treat Noosia as a synonym of Periconia. Detailed descriptions and illustrations of three novel taxa and two new records of Periconia byssoides and P. pseudobyssoides as well as the illustration of P. didymosporum comb. nov. are provided. An updated phylogenetic tree of Periconiaceae using maximum likelihood and Bayesian inference analyses is constructed. Generic circumscription of Periconia is amended.

Taxonomy and Phylogeny of Novel and Extant Taxa in Pleosporales Associated with Mangifera indica from Yunnan, China (Series I).

Pleosporales is the largest fungal order with a worldwide distribution in terrestrial and aquatic environments. During investigations of saprobic fungi associated with mango (Mangifera indica) in Baoshan and Honghe, Yunnan, China, fungal taxa belonging to pleosporales were collected. Morphological examinations and phylogenetic analyses of ITS, LSU, SSU, rpb2 and tef1-α loci were used to identify the fungal taxa. A new genus, Mangifericomes; four new species, namely Mangifericomes hongheensis, Neomassaria hongheensis, Paramonodictys hongheensis, and Paramonodictys yunnanensis; and six new host and country records, namely Byssosphaeria siamensis, Crassiparies quadrisporus, Paradictyoarthrinium aquatica, Phaeoseptum mali, Torula fici, and Vaginatispora amygdali, are introduced. Photoplates, full descriptions, and phylogenetic trees to show the placement of new and known taxa are provided.

Two-stage extended recursive gradient algorithm for locally linear RBF-based autoregressive models with colored noises.

A novel parameter identification method for locally linear radial basis function-based autoregressive models in presence of colored noises is proposed in this paper. Taking advantage of the global nonlinear and local linear structural characteristics of the models, two dynamical criterion functions are constructed based on the separated parameters to realize the dynamical acquisition and utilization of the entire process data. Two recursive gradient sub-algorithms are derived for estimating the separated parameters by using the nonlinear gradient optimization. To coordinate the associated variables existing in the sub-algorithms and to estimate the unmeasurable noise terms, we combine the sub-algorithms and propose a two-stage extended recursive gradient (2S-ERG) algorithm. In addition, an extended recursive gradient algorithm is given as a comparison. The feasibility of the 2S-ERG algorithm is validated by numerical simulations.

Five Novel Taxa from Freshwater Habitats and New Taxonomic Insights of Pleurotheciales and Savoryellomycetidae.

Pleurotheciales is the largest order in Savoryellomycetidae with a large proportion of species known from freshwater habitats. In order to investigate the phylogenetic relationships of taxa within Pleurotheciales and contribute to their diversity, submerged wood was collected from freshwater habitats in China (Yunnan Province) and Thailand. Two dematiaceous, sporodochial hyphomycetes and one annulatascales-like ascomycete with unusual morphology as compared to extant ones were discovered. They were subjected to DNA-based phylogenetic analyses and the results revealed three distinct lineages in Savoryellomycetidae. This morpho-phylo taxonomic study supports the establishment of five novel taxa including two novel genera, Obliquifusoideum and Saprodesmium, and three novel species, Coleodictyospora muriformis, Obliquifusoideum guttulatum and Saprodesmium dematiosporum. Coleodictyospora muriformis and S. dematiosporum are placed in Pleurotheciales, while O. guttulatum is referred to Savoryellomycetidae genera incertae sedis. The phylogenetic relationships are also presented for Coleodictyospora and Pseudocoleodictyospora, which raises an intriguing taxonomic issue. These two genera are positioned in two different classes, viz Sordariomycetes and Dothideomycetes, although they are quite similar except for the presence of a conidial sheath. This study expands our knowledge of the fungal diversity of freshwater fungi, and also indicates that Pleurotheciales species are mostly found in freshwater habitats.

Morphological and phylogenetic appraisal of Ophioceras (Ophioceraceae, Magnaporthales).

Ophioceras is accommodated in the monotypic family Ophioceraceae (Magnaporthales, Sordariomycetes), and the genus is delimited based on molecular data. During an ongoing survey of bambusicolous fungi in southwest China, we collected a submerged decaying branch of bamboo from Sichuan Province, China and an Ophioceras species occurring on this substrate was observed and isolated. An Ophioceras taxon was delimited based on morphological characteristics and combined LSU, RPB1 and ITS sequence analyses and is described as Ophioceras sichuanense sp. nov. The species formed a well-supported clade basal to Ophioceras (100% ML, 1.00 PP). Based on the updated phylogenetic tree of Magnaporthales, Ceratosphaerella castillensis (generic type) and C. rhizomorpha formed a clade within Ophioceras and morphologically resemble Ophioceras. Therefore, Ceratosphaerella is synonymized under Ophioceras. The phylogenetic relationships of Ophioceras are discussed in relation to morphological similarities of genera in Magnaporthales. The generic circumscription of Ophioceras is emended.

Rubroshiraia gen. nov., a second hypocrellin-producing genus in Shiraiaceae (Pleosporales).

Shiraiaceae is an important family in Pleosporales (Dothideomycetes), which includes medical fungi and plant pathogens. Two hypocrellin-producing taxa, Shiraia bambusicola and a novel genus Rubroshiraia gen. nov., typified by Rubroshiraia bambusae are treated in this article. Maximum likelihood analysis, generated via RAxML (GTR+G model), using a combined SSU, LSU, TEF1 and RPB2 sequence dataset, shows that Rubroshiraia is close to Shiraia and belongs to the family Shiraiaceae. Descriptions, illustrations and a taxonomic key are provided for the genera in Shiraiaceae. Rubroshiraia morphologically differs from Shiraia in having small and dark ascostromata and filiform ascospores. Production of the ascostromatal metabolites, hypocrellin A and B, were examined by HPLC and spectrophotometer. The content of hypocrellin A and B of specimen HKAS 102255 (R. bambusae) is twice that produced by HKAS 102253 (S. bambusicola). To clarify the relationship between R. bambusae and Hypocrella bambusae, type material of the latter was examined and provided the illustration.

Smart Sensing and Adaptive Reasoning for Enabling Industrial Robots with Interactive Human-Robot Capabilities in Dynamic Environments-A Case Study.

Traditional industry is seeing an increasing demand for more autonomous and flexible manufacturing in unstructured settings, a shift away from the fixed, isolated workspaces where robots perform predefined actions repetitively. This work presents a case study in which a robotic manipulator, namely a KUKA KR90 R3100, is provided with smart sensing capabilities such as vision and adaptive reasoning for real-time collision avoidance and online path planning in dynamically-changing environments. A machine vision module based on low-cost cameras and color detection in the hue, saturation, value (HSV) space is developed to make the robot aware of its changing environment. Therefore, this vision allows the detection and localization of a randomly moving obstacle. Path correction to avoid collision avoidance for such obstacles with robotic manipulator is achieved by exploiting an adaptive path planning module along with a dedicated robot control module, where the three modules run simultaneously. These sensing/smart capabilities allow the smooth interactions between the robot and its dynamic environment, where the robot needs to react to dynamic changes through autonomous thinking and reasoning with the reaction times below the average human reaction time. The experimental results demonstrate that effective human-robot and robot-robot interactions can be realized through the innovative integration of emerging sensing techniques, efficient planning algorithms and systematic designs.

Semi-Supervised Generative Adversarial Nets with Multiple Generators for SAR Image Recognition.

As an important model of deep learning, semi-supervised learning models are based on Generative Adversarial Nets (GANs) and have achieved a competitive performance on standard optical images. However, the training of GANs becomes unstable when they are applied to SAR images, which reduces the feature extraction capability of the discriminator in GANs. This paper presents a new semi-supervised GANs with Multiple generators and a classifier (MCGAN). This model improves the stability of training for SAR images by employing multiple generators. A multi-classifier is introduced to the new GANs to utilize the labeled images during the training of the GANs, which shares the low level layers with the discriminator. Then, the layers of the trained discriminator and the classifier construct the recognition network for SAR images after having been finely tuned using a small number of the labeled images. Experiments on the Moving and Stationary Target Acquisition and Recognition (MSTAR) databases show that the proposed recognition network achieves a better and more stable recognition performance than several traditional semi-supervised methods as well as other GANs-based semi-supervised methods.

A Novel Active Semisupervised Convolutional Neural Network Algorithm for SAR Image Recognition.

Convolutional neural network (CNN) can be applied in synthetic aperture radar (SAR) object recognition for achieving good performance. However, it requires a large number of the labelled samples in its training phase, and therefore its performance could decrease dramatically when the labelled samples are insufficient. To solve this problem, in this paper, we present a novel active semisupervised CNN algorithm. First, the active learning is used to query the most informative and reliable samples in the unlabelled samples to extend the initial training dataset. Next, a semisupervised method is developed by adding a new regularization term into the loss function of CNN. As a result, the class probability information contained in the unlabelled samples can be maximally utilized. The experimental results on the MSTAR database demonstrate the effectiveness of the proposed algorithm despite the lack of the initial labelled samples.

A Novel Classification Algorithm Based on Incremental Semi-Supervised Support Vector Machine.

For current computational intelligence techniques, a major challenge is how to learn new concepts in changing environment. Traditional learning schemes could not adequately address this problem due to a lack of dynamic data selection mechanism. In this paper, inspired by human learning process, a novel classification algorithm based on incremental semi-supervised support vector machine (SVM) is proposed. Through the analysis of prediction confidence of samples and data distribution in a changing environment, a "soft-start" approach, a data selection mechanism and a data cleaning mechanism are designed, which complete the construction of our incremental semi-supervised learning system. Noticeably, with the ingenious design procedure of our proposed algorithm, the computation complexity is reduced effectively. In addition, for the possible appearance of some new labeled samples in the learning process, a detailed analysis is also carried out. The results show that our algorithm does not rely on the model of sample distribution, has an extremely low rate of introducing wrong semi-labeled samples and can effectively make use of the unlabeled samples to enrich the knowledge system of classifier and improve the accuracy rate. Moreover, our method also has outstanding generalization performance and the ability to overcome the concept drift in a changing environment.