Assessment of the Bill Emerson Memorial Cable-Stayed Bridge based on Seismic Instrumentation Data

In this study, both ambient and earthquake data measured from the Bill Emerson Memorial Cable-stayed Bridge are reported and analyzed. Based on the seismic instrumentation data, the vibration characteristics of the bridge are investigated and used to validate a three-dimensional Finite Element (3-D FE) model of the bridge structure. The 3-D model is rigorous and comprehensive, representing realistic dynamic behaviors of the bridge. It takes into account the geometric nonlinear properties caused by cable sagging and soil-foundation-structure interaction in the Illinois approach of the bridge. The FE model is successfully verified and validated by using the natural frequencies and mode shapes of the bridge extracted from the measured data. With the calibrated model, time history analyses were performed to assess the condition of the bridge structure under a postulated design earthquake. Since the FE model is developed according to as-built drawings, the calibrated model can be used as a benchmark for safety evaluation and health monitoring of the cable-stayed bridge in the future

Robust Anti-Windup Control Considering Multiple Design Objectives

A new saturation control technique is proposed to design multiobjective and robust anti-windup controllers for linear systems with input saturations. Based on the characterization of saturation nonlinearities and modeling uncertainties via integral quadratic constraints (IQCs), this method considers a mixed H2/H∞ performance indexes while maintaining dynamic constraints on the controller. The analysis and synthesis conditions are presented in terms of scaled linear matrix inequalities (LMIs). The proposed control algorithm can improve the performance of the input-constrained system while also guaranteeing robustness with respect to the modeling uncertainties. Finally, a numerical example is given to illustrate the effectiveness of the developed techniques

Toward 6G TKμ\mu Extreme Connectivity: Architecture, Key Technologies and Experiments

Sixth-generation (6G) networks are evolving towards new features and order-of-magnitude enhancement of systematic performance metrics compared to the current 5G. In particular, the 6G networks are expected to achieve extreme connectivity performance with Tbps-scale data rate, Kbps/Hz-scale spectral efficiency, and $\mu$s-scale latency. To this end, an original three-layer 6G network architecture is designed to realise uniform full-spectrum cell-free radio access and provide task-centric agile proximate support for diverse applications. The designed architecture is featured by super edge node (SEN) which integrates connectivity, computing, AI, data, etc. On this basis, a technological framework of pervasive multi-level (PML) AI is established in the centralised unit to enable task-centric near-real-time resource allocation and network automation. We then introduce a radio access network (RAN) architecture of full spectrum uniform cell-free networks, which is among the most attractive RAN candidates for 6G TK$\mu$ extreme connectivity. A few most promising key technologies, i.e., cell-free massive MIMO, photonics-assisted Terahertz wireless access and spatiotemporal two-dimensional channel coding are further discussed. A testbed is implemented and extensive trials are conducted to evaluate innovative technologies and methodologies. The proposed 6G network architecture and technological framework demonstrate exciting potentials for full-service and full-scenario applications.Comment: 15 pages, 12 figure

Optimal Production and Biochemical Properties of a Lipase from Candida albicans

Lipases from microorganisms have multi-faceted properties and play an important role in ever-growing modern biotechnology and, consequently, it is of great significance to develop new ones. In the present work, a lipase gene from Candida albicans (CaLIP10) was cloned and two non-unusual CUG serine codons were mutated into universal codons, and its expression in Pichia pastoris performed optimally, as shown by response surface methodology. Optimal conditions were: initial pH of culture 6.86, temperature 25.53 °C, 3.48% of glucose and 1.32% of yeast extract. The corresponding maximal lipolytic activity of CaLIP10 was 8.06 U/mL. The purified CaLIP10 showed maximal activity at pH 8.0 and 25 °C, and a good resistance to non-ionic surfactants and polar organic solvent was noticed. CaLIP10 could effectively hydrolyze coconut oil, but exhibited no obvious preference to the fatty acids with different carbon length, and diacylglycerol was accumulated in the reaction products, suggesting that CaLIP10 is a potential lipase for the oil industry

Synergistic structural and functional alterations in the medial prefrontal cortex of patients with high-grade gliomas infiltrating the thalamus and the basal ganglia

BackgroundHigh-grade gliomas (HGGs) are characterized by a high degree of tissue invasion and uncontrolled cell proliferation, inevitably damaging the thalamus and the basal ganglia. The thalamus exhibits a high level of structural and functional connectivity with the default mode network (DMN). The present study investigated the structural and functional compensation within the DMN in HGGs invading the thalamus along with the basal ganglia (HITBG).MethodsA total of 32 and 22 healthy controls were enrolled, and their demographics and neurocognition (digit span test, DST) were assessed. Of the 32 patients, 18 patients were involved only on the left side, while 15 of them were involved on the right side. This study assessed the amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo), gray matter (GM) volume, and functional connectivity (FC) within the DMN and compared these measures between patients with left and right HITBG and healthy controls (HCs).ResultThe medial prefrontal cortex (mPFC) region existed in synchrony with the significant increase in ALFF and GM volume in patients with left and right HITBG compared with HCs. In addition, patients with left HITBG exhibited elevated ReHo and GM precuneus volumes, which did not overlap with the findings in patients with right HITBG. The patients with left and right HITBG showed decreased GM volume in the contralateral hippocampus without any functional variation. However, no significant difference in FC values was observed in the regions within the DMN. Additionally, the DST scores were significantly lower in patients with HITBG, but there was no significant correlation with functional or GM volume measurements.ConclusionThe observed pattern of synchrony between structure and function was present in the neuroplasticity of the mPFC and the precuneus. However, patients with HITBG may have a limited capacity to affect the connectivity within the regions of the DMN. Furthermore, the contralateral hippocampus in patients with HITBG exhibited atrophy. Thus, preventing damage to these regions may potentially delay the progression of neurological function impairment in patients with HGG

Differentiation of malignant brain tumor types using intratumoral and peritumoral radiomic features

Tumor infiltration of central nervous system (CNS) malignant tumors may extend beyond visible contrast enhancement. This study explored tumor habitat characteristics in the intratumoral and peritumoral regions to distinguish common malignant brain tumors such as glioblastoma, primary central nervous system lymphoma, and brain metastases. The preoperative MRI data of 200 patients with solitary malignant brain tumors were included from two datasets for training. Quantitative radiomic features from the intratumoral and peritumoral regions were extracted for model training. The performance of the model was evaluated using data (n = 50) from the third clinical center. When combining the intratumoral and peritumoral features, the Adaboost model achieved the best area under the curve (AUC) of 0.91 and accuracy of 76.9% in the test cohort. Based on the optimal features and classifier, the model in the binary classification diagnosis achieves AUC of 0.98 (glioblastoma and lymphoma), 0.86 (lymphoma and metastases), and 0.70 (glioblastoma and metastases) in the test cohort, respectively. In conclusion, quantitative features from non-enhanced peritumoral regions (especially features from the 10-mm margin around the tumor) can provide additional information for the characterization of regional tumoral heterogeneity, which may offer potential value for future individualized assessment of patients with CNS tumors

How to Improve Users’ Loyalty to Smart Health Devices? The Perspective of Compatibility

Despite the explosive growth of smart health devices in recent years, the industry faces serious sustainability challenges. From the perspective of compatibility, this study proposed a theoretical model to help understand the formation of users’ loyalty. Using an online survey method, we collected empirical data from 375 users with experience of smart health devices. The results indicate that compatibility with online health management and compatibility with value positively affect users’ satisfaction, which in turn contributes to users’ loyalty to smart health devices. Meanwhile, both compatibility with online and offline health management have significant impacts on users’ compatibility with value. Finally, the mediation tests suggested that user satisfaction significantly mediates the effects of compatibility with online practice and compatibility with value on loyalty. Theoretically, this study contributes to the literature by investigating the influence of three compatibilities on loyalty and verifying the underlying mechanism linking them. Practically, the findings of this study can provide valuable insights for practitioners to increase consumers’ loyalty

Motion Estimation of Non-Cooperative Space Objects Based on Monocular Sequence Images

The motion estimation of non-cooperative space objects is an important prerequisite for successfully completing on-orbit servicing, debris removing and asteroid exploration missions. The motion estimation of non-cooperative space objects is a challenging task because of the lack of prior information about the object in unknown scenarios. In this paper, a motion estimation method of non-cooperative space objects for autonomous navigation based on a monocular sequence of images is proposed. The rotational attitude estimation of the non-cooperative space object is realized by matching the feature points of adjacent frame images, and the conditions required for translational estimation are discussed. This method has small calculation costs and runs stably, which meets the requirements of real-time computation on-board. As a result, this method implements the estimation of the complete unknown information of the object, including the attitude quaternion and angular velocity. Numerical simulations and results verify the effectiveness of the proposed method