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Multi-temporal glacier inventories provide key information about the glaciers, their characteristics, and changes and are inevitable for glacier modelling and investigating geodetic mass changes. However, to date, no consistent multi-temporal glacier inventory for the whole of the Karakoram exists, negatively affecting the monitoring of spatio-temporal variations in glaciers' geometric parameters and their related applications. We used a semi-automatic method combining automatic segmentation and manual correction and produced a multi-temporal Karakoram glacier inventory (KGI) compiled from Landsat TM/ETM+/OLI (Thematic Mapper, Enhanced Thematic Mapper Plus, and Operational Land Imager) images for the 1990s, 2000s, 2010s, and 2020s. Our assessments using independent multiple digitisation of 37 glaciers show that the KGI is sufficiently accurate, with an overall uncertainty of ±3.68 %. We also performed uncertainty evaluation for the contiguous glacier polygons using a buffer of half a pixel, which resulted in an average mapping uncertainty of ±5.21 %. We calculated more than 20 attributes for each glacier, including coordinates, area, supraglacial debris area, date information, and topographic parameters derived from the ASTER GDEM (Advanced Spaceborne Thermal Emission and Reflection Radiometer global digital elevation model). According to KGI-2020s, approximately 10 500 alpine glaciers (>0.01 km2 each) cover an area of 22 510±828 km2 of which 10.18±0.38 % (2290±84 km2) is covered by supraglacial debris. Over the past 3 decades, the glaciers experienced a loss of clean ice and/or snow area but a gain in supraglacial debris. Supraglacial debris cover has increased by 17.63±1.44 % (343.30±27.95 km2), while non-debris-covered glaciers decreased by 1.56±0.24 % (319.85±49.92 km2). The total glacier area was relatively stable and showed only a slight insignificant increase of 23.45±28.85 km2 (0.10±0.13 %). The glacier area has declined by 3.27±0.24 % in the eastern Karakoram, while the glacier area slightly increased in central (0.65±0.10 %) and western Karakoram (1.26±0.11 %). Supraglacial debris has increased over the whole of Karakoram, especially in areas above 4200 m a.s.l. (above sea level), showing an upward shift. The glacier area changes were characterised by strong spatial heterogeneity, influenced by surging and advancing glaciers. However, due to global warming, the glaciers are on average retreating. This is in particular true for small and debris-free glaciers. The multi-temporal KGI data are available at the National Cryosphere Desert Data Center of China: https://doi.org/10.12072/ncdc.glacier.db2386.2022 (F. Xie et al., 2022).

Background Mycobacterium fortuitum is a rapidly growing non-tuberculous mycobacterium (NTM) with weak pathogenicity. Here, we present a rare case of disseminated M. fortuitum and Talaromyces marneffei coinfection in a human immunodeficiency virus (HIV) negative patient. Case presentation A 28-year-old female was admitted to our hospital due to 2 months of swelling of lymph nodes on the right side of her cervix, accompanied by repeated low fever for more than 1 month. Biopsy of the right cervical lymph node and endobronchial ultrasound-guided transbronchial fine needle aspiration (EBUS-TBNA) both suggested granulomatous inflammation. The bacterial culture and mycobacteria examination of the lesion as well as HIV antibody test were all negative. Disseminated T. marneffei infection was diagnosed by the quantitative polymerase chain reaction (qPCR) results from the blood showing 1798 copies/ul. In the meantime, treatment with amphotericin B combined with cefoxitin was administered for suspected NTM infection. However, the once-dropped fever recurred and the lymph nodes continued to swell. Metagenomics next-generation sequencing (mNGS) detection of the lymph nodes indicated M. fortuitum. After combination treatment with amphotericin B, voriconazole, linazolamide, and imipenem, the patient's body temperature returned to normal, the lymph node swelling was gradually reduced, and the lung lesion was absorbed. Conclusion We report the first case of an HIV-negative patient diagnosed with disseminated M. fortuitum and T. marneffei coinfection with nonspecific clinical manifestation, in order to heighten awareness of these infections.

In order to mine information from medical health data and develop intelligent application-related issues, the multi-modal medical health data feature representation learning related content was studied, and several feature learning models were proposed for disease risk assessment. In the aspect of medical text feature learning, a medical text feature learning model based on convolutional neural network is proposed. The convolutional neural network text analysis technology is applied to the disease risk assessment application. The medical data feature representation adopts the deep learning method. The learning and extraction of different disease characteristics use the same method to realize the versatility of the model. A simple preprocessing of the experimental data samples, including its power frequency denoising and lead convolution regularization, constructs a convolutional neural network for medical data feature advancement and intelligent recognition. On the basis of it, several sets of experiments were carried out to discuss the influence of the convolution kernel and the choice of learning rate on the experimental results. In addition, comparative experiments with support vector machine, BP neural network and RBF neural network are carried out. The results show that the convolutional neural network used in this paper shows obvious advantages in recognition rate and training speed compared with other methods. In the aspect of time series data feature learning, a multi-channel convolutional self-encoding neural network is proposed. Analyze the connection between fatigue and emotional abnormalities and define the concept of emotional fatigue. The proposed multi-channel convolutional neural network is used to learn the data features, and the convolutional self-encoding neural network is used to learn the facial image data features. These two characteristics and the collected physiological data are combined to perform emotional fatigue detection. An emotional fatigue detection demonstration platform for multi-modal data feature fusion is established to realize data acquisition, emotional fatigue detection and emotional feedback. The experimental results verify the validity, versatility and stability of the model.

Hemangioendothelioma (HE) is a type of angiomatous lesions that features endothelial cell proliferation. Understanding the mechanisms orchestrating HE angiogenesis can provide therapeutic insights. It has been shown that platelets can support normal and malignant endothelial cells during angiogenesis. Using the mouse endothelial-derived EOMA cell line as a model of HE, we explored the regulatory effect of platelets. We found that platelets stimulated EOMA proliferation but did not mitigate apoptosis. Furthermore, direct platelet-EOMA cell contact was required and the proliferation was mediated via integrin β3/Akt signaling in EOMA cells. SiRNA knockdown of integrin β3 and inhibition of Akt activity significantly abolished platelet-induced EOMA cell proliferation in vitro and tumor development in vivo. These results provide a new mechanism by which platelets support HE progression and suggest integrin β3 as a potential target to treat HE.

In this study, the weight loss and tensile property of wool fibers and cashmere fibers before and after various potassium permanganate solution treatment were investigated. The scale morphology and crystallization index of the original and treated fibers were analysed with scanning electron microscopy and X-ray diffraction analysis. The experimental results showed that the weight loss of wool fibers is more than that of cashmere fibers under low potassium permanganate content treatment, but is less than that of cashmere fibers under high potassium permanganate content treatment. The force loss of cashmere fibers increased linearly with an increase in potassium permanganate content. The scales of cashmere fiber were damaged at a potassium permanganate content of 9%, but the scales of wool fiber were clear. The relative crystallisation index of treated wool is twice as that of treated cashmere at a potassium permanganate content of 9%.

Maximal Biclique Enumeration (MBE) has become a central task to many data mining problems arising in Web mining, shopping recommendation, business and bioinformatics. It is crucial to accelerate the sequential MBE that is the basis of the parallel MBE. In this paper, we present an efficient algorithm for maximal biclique enumeration (EMBE) on bipartite graphs in a depth-first manner and need not to store previously computed maximal bicliques in memory for duplicate detection. Previous studies have shown that reduce the number of checking closure condition and manage the child nodes are huge challenges for generating all maximal bicliques. In this paper, we propose that (1) an efficient implementation for pruning technique based on the stack when checking nodes are closed or not, (2) a new method to manage the expansion child nodes through a global data structure.

Enumerating maximal biclique subgraphs from a graph is substantially important in many fields such as web mining, business intelligence, bioinformatics, social network analysis and so on. Although many previous studies have contributed much to efficient enumerating maximal biclique subgraphs from a graph, all of them proposed their algorithms based on a large static graph which remained unchanged in their application scenarios. In the real world, the social networks and other models have often dynamically changed thus either vertices or edges will be added to or removed from the corresponding graph. Therefore, these traditional approaches are not effective because they will repeat a complete enumeration process which has much repetitive work done in the previous enumeration. To reduce repetitive work and achieve high efficiency, we proposed a novel algorithm for enumerating maximal bicliques in a dynamically changed graph. Rather than to search the whole graph from first to last, we only search for newly created or reduced maximal bicliques based on the results enumerated before the change of the graph. In this paper, we proved the rightness of our methods and performed many simulations compared with other algorithms only for static graphs. The results demonstrated that our methods achieved high efficiency for dynamically changed graphs.

Objective: Study clinical curative effect of levonorgestrel treatment on perimenopausal dysfunctional uterine bleeding. Method: Selected 126 outpatient of dysfunctional uterine bleeding which hospitalize from December 2010 to December 2012 at department of gynaecology to undergo levonorgestrel treatment on the 5‒7 days of menstruation. The endometrial thickness, hemoglobin, and the PBAC score of before and 3, 6, and 12 months after placement were observed and recorded. To observation the adverse reactions after levonorgestrel treatment. Results: After treatment, the thickness of the endometrium, the amount of menstruation and the hemoglobin concentration increased in 126 patients. During the treatment, 21 patients experienced mild dizziness and nausea, but did not affect the drug use and efficacy. Conclusion: Effects of levonorgestrel on intrauterine treatment of perimenopausal dysfunctional uterine bleeding can effectively reduce the amount of menstruation and increase hemoglobin levels. It is economic, simple, less adverse reaction, and widely entrenched in clinical practice.