Miracle-dz/UniFAR-FTUs huggingface dataset:
The current status of non-intubated thoracoscopic lobectomy

Surgical innovation has come a full circle with the recent advances in performing thoracic surgery without general anesthesia and mechanical ventilation. What was done out of necessity historically is now presented as a choice. Wang and colleagues present here, a patient that underwent a non-intubated uniportal lobectomy with mediastinal lymph node dissection and discuss the indications and rationale for performing non-intubated video-assisted thoracoscopic (NIVATS) lobectomy (1). There is an abundance of literature describing NIVATS techniques and the benefits of avoiding general anesthesia in thoracic surgery. It is important to note however, that a lobectomy performed with an intention to cure cancer is an entity of its own. In this editorial we will aim to focus on the specific role of NIVATS for lobectomy as an oncological procedure.
Foreign Language Education for Sustainable Development in China: A Case Study of German Language Education

Sustainable development is a widely discussed topic. English language education plays the dominant role in China, but the education of languages other than English (LOTEs) is more important for sustainable development. Based on a case study of German language education, this paper draws SWOT analysis to discuss the current foreign language education in China associated with sustainable development. We find that there are four current trends in the sustainable development of foreign language education in China: promotion of sustainable multilingual education, cultivation of sustainable citizens, integration of cultural values for sustainable development and digitalization for sustainable foreign language education. There are also challenges and new perspectives. A rational and systematic policy of multilingualism should be planned. In order to cultivate sustainable citizens who are able to respond to various global problems, the curricula, teaching materials and examinations for LOTE teaching at secondary schools and universities should be co-designed to work with each other. In order to integrate cultural values effectively, more suitable teaching materials should be developed and published, and teachers need to be trained for practicing these contents in class. Digitization in teaching, research and learning should be promoted.
Cooperative Service Placement and Request Routing in Mobile Edge Networks for Latency-Sensitive Applications

The emergence of mobile applications like self-driving cars, networked gaming, virtual reality, and augmented reality has created a demand for computation-intensive and latency critical applications. The dense deployment of base stations (BSs) makes the overlapping coverage of BS that induces the placement of services and routing the requests to the appropriate node is a challenging issue. Further, the limited resources at the edge node invite additional problems of allocating the existing limited edge resources cooperatively to fulfil the user demands. To address the problems mentioned above, we formulate the cooperative service placement and routing problem by placing the diversified latency critical services to maximize the time utility with the deadline and resource constraints. The problem is formulated as an integer linear programming problem for cooperative service placement in mobile edge networks. A greedy and randomized rounding technique is presented to solve the service caching and request routing problems decomposed from the proposed problem. Further, a heuristic algorithm based on the circular convex set is presented to solve the proposed NP-hard problem. Extensive simulation results demonstrate that the proposed cooperative service placement schemes significantly improve the delay, cache hit ratio, load on cloud, and time utility performance compared with existing mechanisms.
Full-Length SMN Transcript in Extracellular Vesicles as Biomarker in Individuals with Spinal Muscular Atrophy Type 2 Treated with Nusinersen

Background: Three therapeutic strategies have radically changed the therapeutic scenario for spinal muscular atrophy (SMA). However, therapeutic response differs between individuals. There is a need to identify biomarkers to further assess therapeutic response and to better understand which variables determine the extent of response. Methods: We conducted a study using an optimized digital droplet PCR-based method for the ultra-sensitive detection of SMN transcript in serum EVs from SMA 2 individuals treated with nusinersen over 14 months. In parallel, we investigated levels of serum and CSF neurofilament heavy chain (pNF-H) in the same cohort. Results: Expression of flSMN transcript in EVs of SMA 2 individuals prior to nusinersen was lower than in controls (0.40 vs 2.79 copies/ul; p < 0.05) and increased after 14 months of nusinersen (0.40 vs 1.11 copies/ul; p < 0.05). The increase in flSMN with nusinersen was significantly higher in younger individuals (p < 0.05). Serum pNF-h was higher in non-treated individuals with SMA 2 than in controls (230.72 vs 22.88 pg/ml; p < 0.05) and decreased with nusinersen (45.72 pg/ml at 6 months, 39.02 pg/ml at 14 months). CSF pNF-h in SMA 2 individuals also decreased with nusinersen (248.04 pg/ml prior to treatment, 197.10 pg/dl at 2 months, 104.43 pg/dl at 6 months, 131.03 pg/dl at 14 months). Conclusions: We identified an increase of flSMN transcript in serum EVs of SMA 2 individuals treated with nusinersen that was more pronounced in the younger individuals. Our results indicate that flSMN transcript expression in serum EVs is a possible biomarker in SMA to predict or monitor the response to treatment.
Research on image matching method in binocular stereo vision

The image matching technique based on Scale Invariant Feature Transform is studied,and the fake matching points are eliminated effectively by adding epipolar restriction in this method.A new matching method which combines feature matching and area matching,edge feature and corner feature,is depicted,and the experiments show that the matching time can be reduced,and precision can be improved by using this method.
Combined Nanofibrous Face Mask: Co-Formulation of Lipases and Antibiotic Agent by Electrospinning Technique

The application of enzyme-based therapies has received significant attention in modern drug development. Lipases are one of the most versatile enzymes that can be used as therapeutic agents in basic skin care and medical treatment related to excessive sebum production, acne, and inflammation. The traditional formulations available for skin treatment, such as creams, ointments or gels, are widely applied; however, their use is not always accompanied by good drug penetration properties, stability, or patient adherence. Nanoformulated drugs offer the possibility of combining enzymatic and small molecule formulations, making them a new and exciting alternative in this field. In this study polymeric nanofibrous matrices made of polyvinylpyrrolidone and polylactic acid were developed, entrapping lipases from Candida rugosa and Rizomucor miehei and antibiotic compound nadifloxacin. The effect of the type of polymers and lipases were investigated, and the nanofiber formation process was optimized to provide a promising alternative in topical treatment. Our experiments have shown that entrapment by electrospinning induced two orders of magnitude increase in the specific enzyme activity of lipases. Permeability investigations indicated that all lipase-loaded nanofibrous masks were capable of delivering nadifloxacin to the human epidermis, confirming the viability of electrospinning as a formulation method for topical skin medications.
Local Brain Network Alterations and Olfactory Impairment in Alzheimer’s Disease: An fMRI and Graph-Based Study

Alzheimer’s disease (AD) is associated with the abnormal connection of functional networks. Olfactory impairment occurs in early AD; therefore, exploring alterations in olfactory-related regions is useful for early AD diagnosis. We combined the graph theory of local brain network topology with olfactory performance to analyze the differences in AD brain network characteristics. A total of 23 patients with AD and 18 normal controls were recruited for resting-state functional magnetic resonance imaging (fMRI), clinical neuropsychological examinations and the University of Pennsylvania Smell Identification Test (UPSIT). Between-group differences in the topological properties of the local network were compared. Pearson correlations were explored based on differential brain regions and olfactory performance. Statistical analysis revealed a correlation of the degree of cognitive impairment with olfactory recognition function. Local node topological properties were significantly altered in many local brain regions in the AD group. The nodal clustering coefficients of the bilateral temporal pole: middle temporal gyrus (TPOmid), degree centrality of the left insula (INS.L), degree centrality of the right middle temporal gyrus (MTG.R), and betweenness centrality of the left middle temporal gyrus (MTG.L) were related to olfactory performance. Alterations in local topological properties combined with the olfactory impairment can allow early identification of abnormal olfactory-related regions, facilitating early AD screening.
T cell receptor repertoire as a novel indicator for identification and immune surveillance of patients with severe obstructive sleep apnea

Background Obstructive sleep apnea (OSA) is the most prevalent sleep disturbance that affects approximately 936 million people worldwide and leads to extensively increased incidence of cardiovascular disease, metabolic syndrome, neurological disorders, and traffic accidents. Severe OSA patients suffer a significantly higher risk of complications and worse comorbidity outcomes. Notwithstanding, with inadequate access to contact diagnosis based on polysomnography (PSG), numerous patients with severe sleep apnea have not been diagnosed, especially during the pandemic. Moreover, how the T cell immunity is impaired in OSA remains largely unknown. Methods We primarily investigated the T cell receptor (TCR) repertoires of 50 patients with severe OSA, 23 patients with mild-to-moderate OSA, 23 patients without OSA, and 157 healthy individuals, from their peripheral blood. Firstly, we compared the clinical characteristics, blood cell counts, the ratio of neutrophil-to-lymphocyte (NLR), platelet-to-lymphocyte (PLR), and CD4+/CD8+T cell count between groups. Then, we compared the diversity, clonotypes, unique VJ alleles in patients with different disease severity. Furthermore, by identifying a series of disease-associated amino acid sequences, we employed a repeated hold-out machine learning strategy to explore the optimal algorithm for calculating the TCR repertoire characteristic Index (OSA-TCI). We further confirmed its relation with clinical features by linear regression analysis. Moreover, in followup of severe OSA patients who accepted adherent non-invasive ventilation, we assessed the changes of TCR repertoires, OSA-TCI, ESS, NLR, PLR, and CD4+/CD8+T after therapy. Results We found an unexpected increase in diversity and clonotypes in the TCR repertoire of OSA patients. Furthermore, we successfully developed a novel indicator termed OSA-TCI to summarize the unique repertoire alteration, which provided 90% of sensitivity and 87% of specificity in distinguishing severe OSA. In rationalization, OSA-TCI was found correlated to AHI, BMI, hemoglobin, N1, N2 percentage of sleep, snoring, smoking and lowest oxygen saturation, but only independently related to AHI (R = 0.603) and smoking (R = 0.22). Finally, we observed OSA-TCI in the eight severe patients decreased significantly after home noninvasive ventilation for three months during follow-up, consistently in line with the TCR repertoire improvement. In contrast, NLR, PLR, and the ratio of CD4+/CD8+T cell count were found useless to diagnose and therapeutic surveillance of severe OSA. Conclusions Our study is the first to unveil the TCR repertoire alteration in OSA, indicates possible insidious autoimmune mechanisms underlying OSA, and suggests that TCR repertoires serve as a convenient peripheral blood biomarker for OSA assessment without long-time contact and facility/instrument occupation. It may shed light on future diagnostic, immunological, pathophysiological, and prognostic research on OSA.
Semantic-Aware Region Loss for Land-Cover Classification

Integrating superpixel segmentation into convolutional neural networks is known to be effective in enhancing the accuracy of land-cover classification. However, most of existing methods accomplish such integration by focusing on the development of new network architectures, which suffer from several flaws: conflicts between general superpixels and semantic labels introduce noise into the training, especially at object boundaries; absence of training guidance for superpixels leads to ineffective regional feature learning; and unnecessary superpixel segmentation in the testing stage not only increases the computational burden but also incurs jagged edges. In this study, we propose a novel semantic-aware region (SARI) loss to guide the effective learning of regional features with superpixels for accurate land-cover classification. The key idea of the proposed method is to reduce the feature variance inside and between homogeneous superpixels while enlarging feature discrepancy between heterogeneous ones. The SARI loss is thus designed with three subparts, including superpixel variance loss, intraclass similarity loss and interclass distance loss. We also develop semantic superpixels to assist in the network training with SARI loss while overcoming the limitations of general superpixels. Extensive experiments on two challenging datasets demonstrate that the SARI loss can facilitate regional feature learning, achieving state-of-the-art performance with mIoU scores of around 97.11% and 73.99% on Gaofen Image dataset and DeepGlobe dataset, respectively.
Proton-Pump Inhibitors and Serum Concentrations of Uremic Toxins in Patients with Chronic Kidney Disease

Use of proton-pump inhibitors (PPIs) is common in patients with chronic kidney disease (CKD). PPIs and many uremic toxins (UTs) are eliminated by the kidney’s tubular organic anion transporter system. In a cross-sectional study, we sought to evaluate the association between PPI prescription and serum concentrations of various UTs. We studied a randomly selected sub-group of participants in the CKD-REIN cohort (adult patients with a confirmed diagnosis of CKD and estimated glomerular filtration rate (eGFR) < 60 mL/min/1.73 m2) with available frozen samples collected at baseline. PPI prescription was recorded at baseline. Serum concentrations of 10 UTs were measured using a validated liquid chromatography tandem mass spectrometry technique. Multiple linear regression was performed, with the log UT concentration as the dependent variable. Of the 680 included patients (median age: 68 years; median eGFR: 32 mL/min/1.73 m2), 31% had PPI prescriptions at baseline. Patients using PPIs had higher levels of certain UTs in comparison to other patients, including total and free indoxyl sulfate (IS), total and free p-cresylsulfate, total and free p-cresylglucuronide (PCG), phenylacetylglutamine (PAG), free kynurenine, and free hippuric acid. After adjustment for baseline co-morbidities, number of co-prescribed drugs, and laboratory data, including eGFR, associations between PPI prescription and elevated serum concentrations of free and total IS, free and total PCG, and PAG remained significant. Our results indicate that PPI prescription is independently associated with serum UT retention. These findings are interesting to better understand the factors that may modulate serum UT concentration in CKD patients, however, they will need to be confirmed by longitudinal studies.
An experimentally validated simulation model of a two-bin flat-panel cadmium telluride photon-counting detector for spectroscopic breast imaging applications

Flat-panel, cadmium telluride (CdTe) photon counting detectors (PCDs) are of interest for contrast-enhanced spectral mammography (CESM). Modelling of the frequency-dependent imaging performance of CdTe PCDs is useful for optimization of technique parameters. The purpose of this work is to experimentally validate a Monte-Carlo-based model of the frequency-dependent imaging performance of a CdTe PCD for contrast-enhanced breast imaging. Our Monte-Carlo model accounts for the basic physics of x-ray detection by PCDs, including the finite range of photo-electrons, characteristic emission and subsequent reabsorption, the finite size of charge clouds due to diffusion and Coulomb repulsion, electronic noise and energy thresholding. We validated the model using a two-bin CdTe PCD with charge summation for charge-sharing correction. The detector consists of a 750-um-thick CdTe converter with 100 um pixels. Our model was used to predict both the modulation transfer function (MTF) and the normalized noise power spectrum (NNPS) of both energy bins, in addition to the cross NPS between energy bins. Validation was performed for 40 kVp, 45 kVp and 50 kVp tube voltages. For each tube voltage, we validated for energy thresholds that resulted in photon ratios between the two energy bins of 1:2, 1:1 and 2:1. In all cases, our model predicted the MTF of both energy bins within 3%. The modelled NNPS was 5% to 15% of the measured NNPS. We conclude that the Monte-Carlo-based model can be used to model the frequency-dependent signal and noise properties of contrast-enhanced spectral mammography implemented with CdTe PCDs.
Convergence of trinomial formula for call option prices

The binomial formula given by Cox, Ross and Rubinstein (1979) is a tool for valuating the call option price. It is well known that the price from binomial formula converges to the price from Black-Scholes formula which was given by Black, Scholes and Merton (1973) as the number of periods (n) converges to infinity. In 1988, Boyle introduced the trinomial formula which is another tool for calculating call option price. He considered the trinomial formula in the case that the rising rate of a stock price is u = e λσ√T n and the falling rate of the stock price is d = u −1 , where T is maturity time, σ is volatility and λ > 1. After that, Entit et al. (2013) gave examples which show that the call option price from trinomial formula is closed to the call option price from the Black-Scholes formula. In this thesis, we give the rigorous proof of this conjecture by showing that the trinomial formula converges to the Black-Scholes formula. Moreover, we prove that the rate of this convergence is 1 √ n .
Automatic Mapping of Physical Urban Problems Using Remotely Sensed Imagery

While big cities are expected to exercise cost-effective, evidence-based planning, many are under reactive management, facing simultaneous problems and limited resources. This project develops a proof-of-concept workflow for the automatic monitoring of physical urban problems by combining remote sensing for detection and cartography for visualization. The example problem treated was the obstructive parking of vehicles on pavements as proxy for restricted urban mobility. Nine aerial images of UK urban areas were processed by a deep learning object detector of standard cars, achieving an F-score of 70.72%. Two large scale map reports of 200m wide areas were produced, featuring car detections and overlaps with topographic mapping features. Complementary analysis included the calculation of total detection window overlap per roadside pavement and its change with time. The proposed method combines uniform city-wide coverage with fast interpretation and can inspire the development of professional urban planning tools.
A Remote Health Care System Based on Wireless Sensor Networks

An embedded remote health care system based on wireless sensor network technology is established.Firstly,a new system architecture is proposed which introduces a scalable wireless sensor network with a variety of wireless physiological sensor nodes.Then the designs of several wireless physiological sensor nodes and the care base-station are presented.Wireless communication between the sensor nodes and the care base-station is realized with IEEE 802.15. 4 /Zigbee standard,and the care base-station and the remote central server are connected in one of the following ways,including computing network,GSM short messages and telephone modem.The system can be used at home or in hospitals to form a remote health care system among home,community and hospital.
Malignant breast lesions detection in histopathological images based on the combination of bioinspired texture descriptors and deep features

ABSTRACT Breast cancer is a neoplasm resulting from the multiplication of abnormal cells in the breast tissue that initially form nodules or thickening. The survival of patients with the disease can be highly effective in cases where the diagnosis is early. However, this diagnosis requires the analysis of extensive histopathological breast tissue samples by specialists. This task is considered complex and may require the attention of the pathologist for a long period of time. Fortunately, computational methods, which include digital image processing and deep learning, can help quickly identify tumour malignancies on images from these scans and speed up diagnosis. Thus, this work proposes a methodology for the automatic diagnosis of malignant breast lesions on histopathological images based on the mutual measurement of bioinspired texture features (BiT) and deep learning features. Additionally, in this study, we also evaluated the effect of methods of colour normalisation to reduce colour variation in the images. The proposed methodology obtained a result of 92.9% accuracy with the random forest classifier. These numbers show that a combination of BiT with deep features produces better results than the techniques applied individually, and show that the proposed method can be used to compose computer-aided detection systems.
Application of Genetic Algorithm in Optimizing the Z-R Parameter to Radar Rainfall Estimation

A real coded genetic algorithm(GA) using GUC crossover is introduced to optimize the Z-R parameter for radar rainfall estimation and a new error function is proposed with the control of total rainfall estimation error.This new method is compared with the conventional Least Means Method(LMS),Optimized Method and M-P parameter with the Fuyang radar data and associated raingauge data from June 28 to July 2,1998.Experiment result shows that the accuracy of total rainfall estimation is increased and the new method is more adaptive.