Excavation method optimization and mechanical responses investigating of a shallow buried super large section tunnels: a case study in Zhejiang.

The construction of super large section (SLS) shallow buried tunnels involves challenges related to their large span, high flat rate, and complex construction process. Selecting an appropriate excavation method is crucial for ensuring stability, controlling costs, and managing the construction timeline. This study focuses on the selection of excavation methods and the mechanical responses of SLS tunnels in different types of surrounding rock.

Efficient exploration of compositional space for high-performance copolymers Bayesian optimization.

The traditional approach employed in copolymer compositional design, which relies on trial-and-error, faces low-efficiency and high-cost obstacles when attempting to simultaneously improve multiple conflicting properties. For example, designing co-cured polycyanurates that exhibit both moisture and thermal resistance, along with high modulus, is a long-term challenge because of the intrinsic trade-offs between these properties. In this work, to surmount these barriers, we developed a Bayesian optimization (BO)-guided method to expedite the discovery of co-cured polycyanurates exhibiting low water uptake, coupled with higher glass transition temperature and Young's modulus.

A Waterborne Epoxy Composite Coating with Smart Corrosion Resistance Based on 2-Phenylbenzimidazole-5-sulfonic Acid/Layered Double Hydroxide Composite.

In this study, ZnAl-layered double hydroxide (ZnAl-LDH) was functionalized with 2-phenylbenzimidazole-5-sulfonic acid (PBSA) to prepare ZnAl-PBSA-LDH using a simple one-step method. The electrochemical impedance spectroscopy (EIS) result of the solution phase demonstrated excellent corrosion inhibition performance of ZnAl-PBSA-LDH. Subsequently, 0.

Binary Classification Quantum Neural Network Model Based on Optimized Grover Algorithm.

We focus on the problem that the Grover algorithm is not suitable for the completely unknown proportion of target solutions. Considering whether the existing quantum classifier used by the current quantum neural network (QNN) to complete the classification task can solve the problem of the classical classifier, this paper proposes a binary quantum neural network classifical model based on an optimized Grover algorithm based on partial diffusion. Trial and error is adopted to extend the partial diffusion quantum search algorithm with the known proportion of target solutions to the unknown state, and to apply the characteristics of the supervised learning of the quantum neural network to binary classify the classified data.

Machine-Learning-Assisted Design of Highly Tough Thermosetting Polymers.

Despite advances in machine learning for accurately predicting material properties, forecasting the performance of thermosetting polymers remains a challenge due to the sparsity of historical experimental data and their complicated crosslinked structures. We proposed a machine-learning-assisted materials genome approach (MGA) for rapidly designing novel epoxy thermosets with excellent mechanical properties (high tensile moduli, high tensile strength, and high toughness) through high-throughput screening in a vast chemical space. Machine-learning models were established by combining attention- and gate-augmented graph convolutional networks, multilayer perceptrons, classical gel theory, and transfer learning from small molecules to polymers.

Risk Factors for Mucosal Involvement in Bullous Pemphigoid and the Possible Mechanism: A Review.

Bullous pemphigoid (BP) is the most common type of autoimmune bullous disease and is characterized by the presence of circulating anti-BP180 and/or anti-BP230 autoantibodies. Patients with BP often present with tense blisters and erythema, mainly on the trunk and limbs, but a few patients also have mucosal involvement. In this article, we discuss the fact that BP patients with mucosal involvement tend to have more serious conditions and their disease is more difficult to control.

Facile synthesis of nanosheet-assembled γ-FeO magnetic microspheres and enhanced Sb(III) removal.

The development and utilization of magnetic nanoadsorption materials with large adsorption capacity and easy separation are the research hotspot nowadays. In this study, nanosheet-assembled maghemite (γ-FeO) magnetic microspheres were successfully synthesized by an environmental friendly, quick, and simple method, for enhanced Sb(III) removal from aqueous solution. Scanning electron microscopy (SEM), X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), vibrating sample magnetometer (VSM), and Brunauer-Emmett-Teller (BET) were used to characterize the material.

The adsorption of Mn(II) by insolubilized humic acid.

The eco-friendly and non-toxic natural organic substance, insolubilized humic acid (IHA), was used to remove Mn(II) from aqueous solutions. The adsorption characteristics were studied through a series of static adsorption tests. The results show that conditions such as the dose, the pH of the solution and the initial concentration of Mn(II) all affect removal efficiency, and the optimal pH value was 5.

[Clinical Features and Prognostic Factors of Children with Acute Lymphoblastic Leukemia in High-Risk Group].

Objective: To explore the clinical features and prognostic factors of pediatric acute lymphoblastic leukemia (ALL) in high-risk (HR) group.

Methods: A total of 421 children with ALL in the Children's Hospital of Soochow University from August 2008 to March 2013 were diagnosed and treated according to the Chinese Children Leukemia Group (CCLG)-2008 Protocol. Among different risk-groups, 148 cases were stratified into the low-risk group and 191 cases were included in the moderate-risk group.

Acetic acid pretreatment improves the hardness of cooked potato slices.

The effects of acetic acid pretreatment on the texture of cooked potato slices were investigated in this work. Potato slices were pretreated with acetic acid immersion (AAI), distilled water immersion (DWI), or no immersion (NI). Subsequently, the cell wall material of the pretreated samples was isolated and fractioned to evaluate changes in the monosaccharide content and molar mass (MM), and the hardness and microscopic structure of the potato slices in different pretreatments before and after cooking were determined.

Changes in physicochemical properties related to the texture of lotus rhizomes subjected to heat blanching and calcium immersion.

Pretreatments such as low temperature blanching and/or calcium soaking affect the cooked texture of vegetal food. In the work, lotus rhizomes (Nelumbo nucifera Gaertn.) were pretreated using the following 4 treatments, blanching at 40°C, blanching at 90°C, soaking in 0.