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With the rapid development of data stream, multi-label algorithms for mining dynamic data become more and more important. At the same time, when data distribution changes, concept drift will occur, which will make the existing classification models lose effectiveness. Ensemble methods have been used for multi-label classification, but few methods consider both the accuracy and diversity of base classifiers. To address the above-mentioned problem, a Weighted Ensemble classification algorithm based on Nearest Neighbors for Multi-Label data stream (WENNML) is proposed. WENNML uses data blocks to train Active candidate Ensemble Classifiers (AEC) and Passive candidate Ensemble Classifiers (PEC). The base classifiers of AEC and PEC are dynamically updated using geometric and diversity weighting methods. When the difference value between the number of current instances and the number of warning instances reaches the passive warning value, the algorithm selects the optimal base classifiers from AEC and PEC according to the subset accuracy and hamming score and puts them into the predictive ensemble classifiers. Experiments are carried out on 12 kinds of datasets with 9 comparison algorithms. The results show that WENNML achieves the best average rankings among the four evaluation metrics.

The concept drift detection method is an online learner. Its main task is to determine the position of drifts in the data stream, so as to reset the classifier after detecting the drift to improve the learning performance, which is very important in practical applications such as user interest prediction or financial transaction fraud detection. A new level transition threshold parameter is proposed, and a piecewise weighting mechanism including "Stable Level-Warning Level-Drift Level" is innovatively introduced in concept drift detection. The instances in the window are weighted in levels, and it is applied to the double sliding window. Based on this, a multi-level weighted drift detection method(MWDDM) is proposed. Especially, two variants which are MWDDM_H and MWDDM_M are proposed basd on Hoeffding inequality and Mcdiarmid inequality respectively. Experiments on artificial datasets show that MWDDM can detect abrupt and gradual concept drift faster than any other comparison algorithms, while maintaining a low false positive ratio and false alarm rate. Experiments on real-world datasets show that MWDDM has the highest classification accuracy in most cases.

With the rapid development of information technology, data streams in various fields are showing the characteristics of rapid arrival, complex structure and timely processing. Complex types of data streams make the classification performance worse. However, ensemble classification has become one of the main methods of processing data streams. Ensemble classification performance is better than traditional single classifiers. This article introduces the ensemble classification algorithms of complex data streams for the first time. Then overview analyzes the advantages and disadvantages of these algorithms for steady-state, concept drift, imbalanced, multi-label and multi-instance data streams. At the same time, the application fields of data streams are also introduced which summarizes the ensemble algorithms processing text, graph and big data streams. Moreover, it comprehensively summarizes the verification technology, evaluation indicators and open source platforms of complex data streams mining algorithms. Finally, the challenges and future research directions of ensemble learning algorithms dealing with uncertain, multi-type, delayed, multi-type concept drift data streams are given.

In the data stream scenarios such as the Internet of Things and network click streams, the high-speed, continuous, and endless characteristics of data stream make it a challenging task to quickly mine high utility itemsets in limited memory space. In the data stream scenario, the sliding window model has received extensive research and attention because of its emphasis on recent data. However, in the sliding window model, adjacent windows have a large number of communal batches resulting in a large set of identical itemsets in the resultsets of adjacent windows. At the same time, to provide users with a concise and lossless resultset, a novel algorithm is proposed for mining closed high utility itemsets from data streams, named FCHM-Stream. The algorithm devises a new utility list structure based on batch division. It presents a resultset maintenance strategy based on the skip-list structure to quickly and effectively update the resultset when the window slides which can effectively avoid repeated mining of redundant itemsets. Moreover, various experiments are carried out to compare our method with state-of-the-art algorithms both in static and stream environments. Extensive experimental results show that the proposed algorithm significantly reduces the running time compared to previous algorithms.

Using the principles and methods of eco-economics as the research object, Aral City comprehensively expounds the ecological service functions such as ecosystem regulation of climate, carbon sequestration, soil conservation, water conservation and purification environment, and evaluates its economic value.The total value of the estimated 2021 is 1303.65 million yuan. At the same time, the importance of ecological service functions of urban ecosystems, from large to small, is to sequester carbon and release oxygen, purify the environment, maintain soil, conserd water sources, regulate the climate. The ecosystem service function which needs to be paid attention to in the concept of ecological construction and restoration of the next stage of ecological construction in Aral City.

In recent years, people have become more interested in using acoustics to locate equipment in intelligent human–computer interfaces (HCI). However, existing acoustic locating systems have poor compatibility with smart devices. To achieve millimeter-level accuracy, most systems require large microphone spacing, complex algorithms, and a high cost. In this paper, we propose a new HCI system, MilliLoc, to achieve millimeter-level real-time acoustic locating. Our first contribution is to design a high-performance and convenient microphone array. It has a high sampling rate of 96 kHz, real-time complete dataflow, and is compatible with any smart device. The second contribution is to propose an improved generalized cross-correlation phase transform method with simplicity and real-time capability. Even if the signal-to-noise ratio is not high enough, it can still estimate the time delay accurately. We combine the microphone array with the algorithm to illustrate the implementation of MilliLoc. Experiments show that MilliLoc has a median 2D accuracy of 7.2 mm in a 60 cm sector area and achieves millimeter-level locating.

A Gram-reaction-positive, facultatively anaerobic, rod-shaped and non-motile bacterial strain, designated TEYR-7T, was isolated from the leaves of Sinopodophyllum hexandrum collected from the Qinling Mountains in Shaanxi Province, northwest China. Growth of strain TEYR-7T occurred at 15–37 °C (optimum, 28–30 °C), at pH 6.0–9.0 (optimum, pH 7.0) and in the presence of 0–3 % (w/v) NaCl (optimum, 0–1 %). Propionate and acetate were produced from glucose fermentation. Phylogenetic analyses based on 16S rRNA gene sequences showed that strain TEYR-7T was a member of the phylum Actinobacteria, exhibiting the highest sequence similarity to Propioniciclava tarda DSM 22130T (94.3 %). The only respiratory quinone detected in strain TEYR-7T was menaquinone MK-9(H4) and the major cellular fatty acids (>10 %) were anteiso-C15 : 0 and C16 : 0. The polar lipid profile consisted of phosphatidylglycerol, diphosphatidylglycerol, two unidentified glycolipids, an unidentified phospholipid and three unidentified lipids. The genomic DNA G+C content was 71.2 mol%. meso-Diaminopimelic acid was detected in the peptidoglycan. On the basis of data from the present polyphasic taxonomic study, strain TEYR-7T is considered to represent a novel species of the genus Propioniciclava , for which the name Propioniciclava sinopodophylli sp. nov. is proposed. The type strain is TEYR-7T (=CCTCC AB 2015257T=KCTC 33808T).

A novel indole-3-acetic acid-producing bacterium, designated TEGT-2T, was isolated from the roots of Sinopodophyllum hexandrum collected from the Qinling Mountains in shaanxi province, northwestern China, and was subjected to a taxonomic study by using a polyphasic approach. Cells of strain TEGT-2T were Gram-stain-positive, strictly aerobic, endospore-forming rods and motile by means of peritrichous flagella. Phylogenetic analyses based on 16S rRNA gene sequences showed that strain TEGT-2T was a member of the genus Paenibacillus , exhibiting the highest sequence similarity to Paenibacillus pectinilyticus KCTC 13222T (97.9 %), Paenibacillus frigoriresistens CCTCC AB 2011150T (97.3 %), Paenibacillus ferrarius CCTCC AB 2013369T (96.9 %) and Paenibacillus alginolyticus NBRC 15375T (96.5 %). The only menaquinone detected was MK-7, and the major fatty acid was anteiso-C15 : 0. The major polar lipids were diphosphatidylglycerol, phosphatidylglycerol, phosphatidylethanolamine, two unidentified aminophospholipids, two unidentified phospholipids, an unidentified aminolipid and two unidentified lipids. meso-Diaminopimelic acid was detected in the peptidoglycan. The DNA G+C content was 46.6 mol%. DNA–DNA relatedness values for strain TEGT-2T with respect to its closest phylogenetic relatives Paenibacillus pectinilyticus KCTC 13222T and Paenibacillus . frigoriresistens CCTCC AB 2011150T were lower than 40 %. Based on the phenotypic, phylogenetic and genotypic data, strain TEGT-2T is considered to represent a novel species of the genus Paenibacillus , for which the name Paenibacillus qinlingensis sp. nov. is proposed. The type strain is TEGT-2T (=CCTCC AB 2015258T=KCTC 33806T).

A Gram-stain-positive, strictly aerobic, rod-shaped, motile and endospore-forming bacterial strain, designated TEGR-3T, was isolated from the roots of Sinopodophyllum hexandrum collected from the Qinling Mountains in Shaanxi Province, China. Strain TEGR-3T produced siderophores and hydrolysed aesculin, starch and CM-cellulose. Phylogenetic analyses based on 16S rRNA gene sequences showed that strain TEGR-3T was a member of the genus Paenibacillus, exhibiting the highest sequence similarity to Paenibacillus endophyticus LMG 27297T (97.3 %) and Paenibacillus castaneae DSM 19417T (97.3 %). MK-7 was the only menaquinone detected and anteiso-C15 : 0 and C16 : 0 were the major fatty acids. The major polar lipids were diphosphatidylglycerol, phosphatidylglycerol, phosphatidylethanolamine, two unidentified aminophospholipids, two unidentified phospholipids and an unidentified lipid. The cell-wall peptidoglycan contained meso-diaminopimelic acid as the diagnostic diamino acid. The DNA G+C content was 45.2 mol%. DNA-DNA relatedness values for strain TEGR-3T with respect to its closest phylogenetic relatives Paenibacillus endophyticus LMG 27297T and Paenibacillus castaneae DSM 19417T were lower than 40 %. Based on the phenotypic, phylogenetic and genotypic data, strain TEGR-3T is considered to represent a novel species of the genus Paenibacillus, for which the name Paenibacillus sinopodophylli sp. nov. is proposed. The type strain is TEGR-3T (=CCTCC AB 2016047T=KCTC 33807T).

To investigate mycothiol peroxidase (MPx) of Corynebacterium glutamicum that is a novel CysGPx family peroxidase using both the mycoredoxin and thioredoxin reducing systems as proton donors for peroxide detoxification and may be involved in the relief of acid stress. A Δmpx mutant exhibited significantly decreased resistance to acid stress and markedly increased accumulation of reactive oxygen species (ROS) and protein carbonylation levels in vivo. Over-expression of mpx increased the resistance of C. glutamicum to acid stress by reducing ROS accumulation. The stress-responsive extracytoplasmic function-sigma (ECF-σ) factor, SigH, mediated acid-induced expression of mpx in the wild-type under acid conditions, which in turn directly contributed to tolerance to acid stress. MPx is essential for combating acid stress by reducing intracellular ROS levels induced by acid stress in C. glutamicum, which adds a new dimension to the general physiological functions of CysGPx.