Calculation method and evaluation of surrounding rock pressure of vertical shaft.

The surrounding rock pressure of vertical shafts is one of the basic parameters of shaft lining design. Investigating its calculation methods and applicable scopes has great engineering significance. The paper classifies and compares the calculation methods, discusses the application scopes of various calculation methods, and proposes that the axisymmetric layered method is highly consistent with the field monitoring data for the calculation of surrounding rock pressure of vertical shafts in bedrock sections on the basis of practical engineering examples. On the basis of Terzaghi theory, the calculation formula of surrounding rock pressure of vertical shaft in inclined rock strata with single group joints is derived. The formula can reflect the influence of rock strata dip angle and joints.

Artificial Retina Based on Organic Heterojunction Transistors for Mobile Recognition.

The flicker frequency of incident light constitutes a critical determinant in biology. Nevertheless, the exploration of methods to simulate external light stimuli with varying frequencies and develop artificial retinal neurons capable of responsive behavior remains an open question. This study presents an artificial neuron comprising organic phototransistors. The triggering properties of neurons are modulated by optical input, enabling them to execute rudimentary synaptic functions, emulating the biological characteristics of retinal neurons. The artificial retinal neuron exhibits varying responses to incoming light frequencies, allowing it to replicate the persistent visual behavior of the human eye and facilitating image discrimination. Additionally, through seamless integration with circuitry, it can execute motion recognition on a machine cart, preventing collisions with high-speed obstacles. The artificial retinal neuron offers a cost-effective and energy-efficient route for future mobile robot processors.

The overseas background of Chinese returnee energy scientists.

In an attempt to uncover the international affiliations impacting the Chinese energy sector, this study applies the method of Curriculum Vitae Analysis (CV Analysis) to explore the overseas background of Chinese returnee energy scientists. The investigation focuses on a representative group of scientists hailing from China's distinguished "985" project research universities. From the available online CVs, we gathered data and identified the United States, Japan, and the United Kingdom as the primary host countries that facilitate the growth and learning of these energy scientists. We also noted a concurrent surge in scientists return to China after acquiring academic and professional experience in prestigious global universities. This study thereby illuminates the evolving patterns of Chinese energy scientists' global mobility and return migration.

[Research Overview of Internet of Things Technology in Medical Engineering].

Internet of Things plays a vital role in the field of healthcare. Smart medical devices, innovative sensors and lightweight communication protocols are making the Internet of Medical Things possible. This paper summarizes the research progress of Internet of Things technology in medical engineering from two aspects of health monitoring system and ingestible sensor monitoring equipment. The health monitoring system is analyzed from heart disease monitoring, diabetes monitoring and brain nerve monitoring. The medical equipment that can absorb sensors is represented by capsule endoscope. This paper further summarizes the relevant situation of smart hospital, and finally discusses the challenges and countermeasures of the Internet of Things technology in medical engineering, in order to lay the foundation and provide ideas for the research of the Internet of Things technology in medical engineering.

Deep learning-assisted identification and quantification of aneurysmal subarachnoid hemorrhage in non-contrast CT scans: Development and external validation of Hybrid 2D/3D UNet.

Accurate stroke assessment and consequent favorable clinical outcomes rely on the early identification and quantification of aneurysmal subarachnoid hemorrhage (aSAH) in non-contrast computed tomography (NCCT) images. However, hemorrhagic lesions can be complex and difficult to distinguish manually. To solve these problems, here we propose a novel Hybrid 2D/3D UNet deep-learning framework for automatic aSAH identification and quantification in NCCT images. We evaluated 1824 consecutive patients admitted with aSAH to four hospitals in China between June 2018 and May 2022. Accuracy and precision, Dice scores and intersection over union (IoU), and interclass correlation coefficients (ICC) were calculated to assess model performance, segmentation performance, and correlations between automatic and manual segmentation, respectively. A total of 1355 patients with aSAH were enrolled: 931, 101, 179, and 144 in four datasets, of whom 326 were scanned with Siemens, 640 with Philips, and 389 with GE Medical Systems scanners. Our proposed deep-learning method accurately identified (accuracies 0.993-0.999) and segmented (Dice scores 0.550-0.897) hemorrhage in both the internal and external datasets, even combinations of hemorrhage subtypes. We further developed a convenient AI-assisted platform based on our algorithm to assist clinical workflows, whose performance was comparable to manual measurements by experienced neurosurgeons (ICCs 0.815-0.957) but with greater efficiency and reduced cost. While this tool has not yet been prospectively tested in clinical practice, our innovative hybrid network algorithm and platform can accurately identify and quantify aSAH, paving the way for fast and cheap NCCT interpretation and a reliable AI-based approach to expedite clinical decision-making for aSAH patients.

Optically Readable Organic Electrochemical Synaptic Transistors for Neuromorphic Photonic Image Processing.

Optically readable organic synaptic devices have great potential in both artificial intelligence and photonic neuromorphic computing. Herein, a novel optically readable organic electrochemical synaptic transistor (OR-OEST) strategy is first proposed. The electrochemical doping mechanism of the device was systematically investigated, and the basic biological synaptic behaviors that can be read by optical means are successfully achieved. Furthermore, the flexible OR-OESTs are capable of electrically switching the transparency of semiconductor channel materials in a nonvolatile manner, and thus the multilevel memory can be achieved through optical readout. Finally, the OR-OESTs are developed for the preprocessing of photonic images, such as contrast enhancement and denoising, and feeding the processed images into an artificial neural network, achieving a recognition rate of over 90%. Overall, this work provides a new strategy for the implementation of photonic neuromorphic systems.

Triboelectric Potential Powered High-Performance Organic Transistor Array.

Triboelectric potential gated transistors have inspired various applications toward mechanical behavior controlled logic circuits, multifunctional sensors, artificial sensory neurons, etc. Their rapid development urgently calls for high-performance devices and corresponding figure of merits to standardize the tribotronic gating properties. Organic semiconductors paired with solution processability promise low-cost manufacture of high-performance tribotronic transistor devices/arrays. Here, we demonstrate a record high-performance tribotronic transistor array composed of an integrated triboelectric nanogenerator (TENG) and a large-area device array of C8-BTBT-PS transistors. The working mechanism of effective triboelectric potential gating is elaborately explained from the aspect of conjugated energy bands of the contact-electrification mediums and organic semiconductors. Driven by the triboelectric potential, the tribotronic transistor shows superior properties of record high current on/off ratios (>108), a steep subthreshold swing (29.89 µm/dec), high stability, and excellent reproducibility. Moreover, tribotronic logic devices modulated by mechanical displacement have also been demonstrated with good stability and a high gain of 1260 V/mm. The demonstrated large-area tribotronic transistor array of organic semiconductor exhibits record high performance and offers an effective R&D platform for mechano-driven electronic terminals, interactive intelligent system, artificial robotic skin, etc.

Artificial Vision Adaption Mimicked by an Optoelectrical In2O3 Transistor Array.

Simulation of biological visual perception has gained considerable attention. In this paper, an optoelectrical In2O3 transistor array with a negative photoconductivity behavior is designed using a side-gate structure and a screen-printed ion-gel as the gate insulator. This paper is the first to observe a negative photoconductivity in electrolyte-gated oxide devices. Furthermore, an artificial visual perception system capable of self-adapting to environmental lightness is mimicked using the proposed device array. The transistor device array shows a self-adaptive behavior of light under different levels of light intensity, successfully demonstrating the visual adaption with an adjustable threshold range to the external environment. This study provides a new way to create an environmentally adaptive artificial visual perception system and has far-reaching significance for the future of neuromorphic electronics.

[Segmentation of retinal vessels by fusing contour information and conditional generative adversarial].

The existing retinal vessels segmentation algorithms have various problems that the end of main vessels are easy to break, and the central macula and the optic disc boundary are likely to be mistakenly segmented. To solve the above problems, a novel retinal vessels segmentation algorithm is proposed in this paper. The algorithm merged together vessels contour information and conditional generative adversarial nets. Firstly, non-uniform light removal and principal component analysis were used to process the fundus images. Therefore, it enhanced the contrast between the blood vessels and the background, and obtained the single-scale gray images with rich feature information. Secondly, the dense blocks integrated with the deep separable convolution with offset and squeeze-and-exception (SE) block were applied to the encoder and decoder to alleviate the gradient disappearance or explosion. Simultaneously, the network focused on the feature information of the learning target. Thirdly, the contour loss function was added to improve the identification ability of the blood vessels information and contour information of the network. Finally, experiments were carried out on the DRIVE and STARE datasets respectively. The value of area under the receiver operating characteristic reached 0.982 5 and 0.987 4, respectively, and the accuracy reached 0.967 7 and 0.975 6, respectively. Experimental results show that the algorithm can accurately distinguish contours and blood vessels, and reduce blood vessel rupture. The algorithm has certain application value in the diagnosis of clinical ophthalmic diseases.

Removing and recycling mercury from scrubbing solution produced in wet nonferrous metal smelting flue gas purification process.

Wet purification technology for nonferrous metal smelting flue gas is important for mercury removal; however, this technology produces a large amounts of spent scrubbing solution that contain mercury. The mercury in these scrubbing solutions pose a great threat to the environment. Therefore, this research provides a novel strategy for removing and recycling mercury from the scrubbing solution, which is significant for decreasing mercury pollution while also allowing for the safe disposal of wastewater and a stable supply of mercury resources. Some critical parameters for the electrochemical reduction of mercury were studied in detail. Additionally, the electrodeposition dynamics and electroreduction mechanism for mercury were evaluated. Results suggested that over 92.4% of mercury could be removed from the scrubbing solution in the form of a Hg-Cu alloy under optimal conditions within 150 min and with a current efficiency of approximately 75%. Additionally, mercury electrodeposition was a quasi-reversible process, and the controlled step was the mass transport of the reactant. A pre-conversion step from Hg(Tu)42+ to Hg(Tu)32+ before mercury electroreduction was necessary. Then, the formed Hg(Tu)32+ on the cathode surface gained electrons step by step. After electrodeposition, the mercury in the spent cathode could be recycled by thermal desorption. The results of the electrochemical reduction of mercury and subsequent recycling provides a practical and easy-to-adopt alternative for recycling mercury resources and decreasing mercury contamination.

LncRNA MBLN1-AS1 inhibits the progression of retinoblastoma through targeting miR-338-5p-Wnt/ß-catenin signaling pathway.

OBJECTIVE AND DESIGN: Retinoblastoma is the most common primary intraocular malignancy of childhood, which brings a heavy burden to the countries across the world, especially the developing countries. It has been shown that lncRNA muscleblind-like 1 antisense RNA 1 (MBNL1-AS1) exerts anti-tumor effects in various cancers, including bladder cancer, papillary thyroid cancer, and retinoblastoma. In the present study, we hypothesized that MBNL1-AS1 might play a protective role against retinoblastoma. METHODS: The expression of MBNL1-AS1 and its potential target miR-338-5p were evaluated in retinoblastoma cell line by real-time quantitative PCR and western blot. The involvement of MBNL1-AS1-miR-338-5p in the cell proliferation was evaluated by cell counting kit-8 (CCK8), and colony formation assay. The cell migration was evaluated by Transwell assay in Y79 cells, a retinoblastoma cell line. The involvement of MBNL1-AS1-miR-338-5p in tumor formation was also evaluated in mice. RESULTS: It was found that MBNL1-AS1 overexpression inhibited proliferation and migration in Y79 cells. In addition, the inhibitory effects of MBNL1-AS1 on Y79 cells were significantly reversed in the presence of miR-338-5p mimics, and MBNL1-AS1 overexpression significantly decreased miR-338-5p level in Y79 cells. Furthermore, MBNL1-AS1 overexpression significantly inhibited Wnt/ß-catenin signaling pathway, and this inhibitory effect was almost lost in the presence of miR-338-5p mimics. Finally, our in vivo study showed that MBNL1-AS1 overexpression significantly inhibited Y79-induced retinoblastoma in mice, and this inhibitory effect was lost in the presence of miR-338-5p mimics. CONCLUSION: Our study shows that MBNL1-AS1 exerts its anti-tumor effect by targeting miR-338-5p, thereby inactivating wnt/ß-catenin signaling pathway in retinoblastoma.

Two new phenylethanoid glycosides from Ginkgo biloba leaves and their tyrosinase inhibitory activities.

Two undescribed phenylethanoid glycosides, Ginkgoside C (1) and D (2), together with ten known glycosides (3-12) were isolated from Ginkgo biloba leaves. Their structures were characterized by physical data analyses such as NMR, HRESIMS, as well as chemical hydrolysis. All compounds were tested for their tyrosinase inhibitory activities. At a concentration of 25 µM, compounds 2, 4, 5, 6, and 11 showed obvious mushroom tyrosinase inhibition activities, with %inhibition values of 19.12 ± 2.59%, 25.79 ± 1.83%, 16.07 ± 1.07%, 24.46 ± 1.10%, 18.64 ± 3.62%, respectively, with kojic acid used as the positive control (27.50 ± 2.72%).

Performance of Different Urban Design Parameters in Improving Outdoor Thermal Comfort and Health in a Pedestrianized Zone.

Global climate change and urban heat islands have generated heat stress in summer, which does harm to people's health. The outdoor public commercial pedestrianized zone has an important role in people's daily lives, and the utilization of this space is evaluated by their outdoor thermal comfort and health. Using microclimatic monitoring and numerical simulation in a commercial pedestrianized zone in Tai Zhou, China, this study investigates people's outdoor thermal comfort in extreme summer heat. The final results provide a comprehensive system for assessing how to improve outdoor human thermal health. Under the guidance of this system, local managers can select the most effective strategy to improve the outdoor thermal environment.

Sub-60 mV per decade switching in ion-gel-gated In-Sn-O transistors with a nano-thick charge trapping layer.

In this paper, we present a new method for reducing the subthreshold swing (SS) of ionic-modulated oxide field-effect transistors (FETs) below 60 mV per decade. The electrical performances of ion gel-gated In-Sn-O FETs with and without a nano-thick Al2O3 charge trapping layer are compared and studied. A significant SS reduction in the In-Sn-O FETs is observed when naturally oxidized Al2O3 and an ion gel are used as the gate stacking dielectric layer. The back sweep SS reaches as low as ∼27 mV per decade and extends over three orders of magnitude in drain current. A theoretical explanation for these results based on energy band diagrams is presented. The proposed devices described here have the potential to open up new avenues for further development of low power electronics, as well as for energy efficient memristive devices and synaptic electronics.