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With the increasing demand for location-based services, Wi-Fi-based indoor positioning technology has attracted much attention in recent years because of its ubiquitous deployment and low cost. Considering that Wi-Fi signals fluctuate greatly with time, extracting robust features of Wi-Fi signals is the key point to maintaining good positioning accuracy. To handle the dynamic fluctuation with time and sparsity of Wi-Fi signals, we propose an SDAE (Stacked Denoising Autoencoder)-based feature extraction method, which can obtain a robust and time-independent Wi-Fi fingerprint by learning the reconstruction distribution from a raw Wi-Fi signal and an artificial-noise-added Wi-Fi signal. We also leverage the strong representation ability of MLP (Multi-Layer Perceptron) to build a regression model, which maps the extracted features to the corresponding location. To fully evaluate the performance of our proposed algorithm, three datasets are applied, which represent three different scenarios, namely, spacious area with time interval, no time interval, and complex area with large time interval. The experimental results confirm the validity of our proposed SDAE-based feature extraction method, which can accurately reflect Wi-Fi signals in corresponding locations. Compared with other regression models, our proposed regression model can better map the extracted features to the target position. The average positioning error of our proposed algorithm is 4.24 m when there is a 52-day interval between training dataset and testing dataset. That confirms that the proposed algorithm outperforms other state-of-the-art positioning algorithms when there is a large time interval between training dataset and testing dataset. present, due to the wide deployment and availability of Wi-Fi infrastructure, Wi-Fi fingerprint-based localization has become one of the most dominant indoor positioning techniques.There are two main types of Wi-Fi-based indoor positioning technologies: RSSI (Received Signal Strength Indicator)-based ranging positioning algorithm [9][10][11], and fingerprint-based positioning algorithm [12][13][14]. The RSSI-based ranging positioning algorithm [11] usually adopts the received Wi-Fi signal to estimate the distance between the target (its location is unknown) and the access point (its location is known) using the wireless radio signal propagation model, and then estimates the target position using trilateration or multilateration methods. The fingerprint-based positioning algorithm [14] adopts the signal matching algorithm to estimate the user location. It first collects environmental Wi-Fi signals and constructs a Wi-Fi fingerprint database during the offline phase. During the online positioning phase, the fingerprint-based positioning algorithm compares the current Wi-Fi observation with the recorded fingerprint in the database to obtain the target position using the optimum matching criterion. Compared with the fingerprint-based positioning algorithm, the RSSI-based ranging positioning algorithm struggles to meet...

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Percutaneous computed tomography (CT)-guided transthoracic needle biopsy (TTNB) is a valuable procedure for obtaining tissue or cells for diagnosis, which is especially indispensable in thoracic oncology. Pneumothorax and hemoptysis are the most common complications of percutaneous needle biopsy of the lung. According to reports published over the past decades, pneumothorax incidence in patients who underwent TTNB greatly varies. The morbidity of pneumothorax after CT-guided TTNB depends on several factors, including size and depth of lesions, emphysema, the number of pleural surfaces and fissure crossed, etc. Attention to biopsy planning and technique and post-biopsy precautions help to prevent or minimize potential complications. Many measures can be taken to help prevent the progression of a pneumothorax, which in turn might reduce the number of pneumothoraces requiring chest tube placement. A multitude of therapeutic options is available for the treatment of pneumothorax, varying from observation and oxygen treatment, simple manual aspiration, to chest tube placement. When a pneumothorax develops during the biopsy procedure, it can be manually aspirated after the needle is retracted back into the pleural space or by inserting a separate needle into the pleural space. Biopsy side down positioning of the patient after biopsy significantly reduces the incidence of pneumothorax and the requirement of chest tube placement. Aspiration in biopsy side down position is also recommended for treating pneumothorax when simple manual aspiration is unsuccessful or delayed pneumothorax occurred. Chest tube placement is an important treatment strategy for patients with a large or symptomatic pneumothorax. Clinicians are encouraged to understand the development, prevention, and treatment of pneumothorax. Efforts should be made to reduce the incidence of pneumothorax in biopsy planning and post-biopsy precautions. When pneumothorax occurs, appropriate treatment should be adopted to reduce the risk of worsening pneumothorax.

Background: In the past decade, several antibodies directed against the PD-1/PD-L1 interaction have been approved. However, therapeutic antibodies also exhibit some shortcomings. Using small molecules to regulate the PD-1/PD-L1 pathway may be another way to mobilize the immune system to fight cancer. Method: 52,765 marine natural products were screened against PD-L1(PDBID: 6R3K). To identify natural compounds, a structure-based pharmacophore model was generated, following by virtual screening and molecular docking. Then, the absorption, distribution, metabolism, and excretion (ADME) test was carried out to select the most suitable compounds. Finally, molecular dynamics simulation was also performed to validate the binding property of the top compound. Results: Initially, 13 small marine molecules were screened based on the pharmacophore model. Then, two compounds were selected for further evaluation based on the molecular docking scores. After ADME and toxicity studies, molecule 51320 was selected for further verification. By molecular dynamics analysis, molecule 51320 maintains a stable conformation with the target protein, so it has the chance to become an inhibitor of PD-L1. Conclusions: Through structure-based pharmacophore modeling, virtual screening, molecular docking, ADMET approaches, and molecular dynamics (MD) simulation, the marine natural compound 51320 can be used as a small molecule inhibitor of PD-L1.

In this article, a multiple-image encryption method based on the optical interference principle and phase-only mask (POM) multiplexing is proposed. During the encryption process, each secret image is encoded into two analytically obtained POMs and one computer-generated random POM, in which no iterative computation is required. The analytically obtained POMs taken from different secret images are then synthesized by POM multiplexing and further encoded into two complex ciphertext images. The silhouette problem that exists in the earlier interference principle-based encryption approaches is totally resolved by the proposal. Both digital and optical means can be used for decryption. The crosstalk effect between the secret images will not appear in the decrypted results by using the proposed system. Numerical simulations have been given to verify the performance and feasibility of the proposal. We also discuss briefly the influence of information compression on the quality of decrypted images.

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