Maximum entropy-based modeling of community-level hazard responses for civil infrastructures

Perturbed by natural hazards, community-level infrastructure networks operate like many-body systems, with behaviors emerging from coupling individual component dynamics with group correlations and interactions. It follows that we can borrow methods from statistical physics to study the response of infrastructure systems to natural disasters. This study aims to construct a joint probability distribution model to describe the post-hazard state of infrastructure networks and propose an efficient surrogate model of the joint distribution for large-scale systems. Specifically, we present maximum entropy modeling of the regional impact of natural hazards on civil infrastructures. Provided with the current state of knowledge, the principle of maximum entropy yields the ``most unbiased`` joint distribution model for the performances of infrastructures. In the general form, the model can handle multivariate performance states and higher-order correlations. In a particular yet typical scenario of binary performance state variables with knowledge of their mean and pairwise correlation, the joint distribution reduces to the Ising model in statistical physics. In this context, we propose using a dichotomized Gaussian model as an efficient surrogate for the maximum entropy model, facilitating the application to large systems. Using the proposed method, we investigate the seismic collective behavior of a large-scale road network (with 8,694 nodes and 26,964 links) in San Francisco, showcasing the non-trivial collective behaviors of infrastructure systems

An Empirical Study on Impact of College Carve-Out Education on Entrepreneur Intention

Abstract Carve-out education is becoming increasingly important in current days since the business set up by college students produce a significant effect on the economic growth. Entrepreneur intention, part of carve-out education, is receiving more and more attention. Based on educational systems over the world and the datum of Chinese college students, the article studies the impact of the college carve-out education on students’ entrepreneur intention with the structure equation modeling (SEM). The research shows that carve-out education can enhance entrepreneur intention indirectly by updating students’ knowledge, cultivating their entrepreneurial abilities and reinforcing their determination. The colleges and other educational organizations should also provide plenty of training projects and encourage students to participate in company operation. In addition, some successful entrepreneurs should be invited to give lectures in colleges.Key words: Entrepreneurship Education; College Student Entrepreneurship; Entrepreneurship Intentio

An Empirical Study on Campus Dwelling Environment Quality in Beijing and Its Influencing Factors

Combining with the current dwelling environmental assessment system, this article reviews the domestic and foreign theoretical documents, and tries to construct an evaluation model based on the influencing factors of campus dwelling environment quality in Beijing, including natural landscape, amenities and cultural environment. The research indicates that the campus dwelling environment quality is linearly related with and can be effectively predicted by these three factors. It also shows that the regression coefficient of cultural environment is the highest among the three; but most interviewees didn’t appraise their campus dwelling environment quality high. Therefore, colleges in Beijing need to improve especially in the following three aspects – gas power system (natural landscape), population density (amenities) and manager quality (cultural environment) – to make the campus dwelling environment clean pleasant and eco-friendly.Key words: Universities in Beijing; Dwelling environment; Natural landscape; Amenities; Cultural environmen

Edge-Cloud Polarization and Collaboration: A Comprehensive Survey for AI

Influenced by the great success of deep learning via cloud computing and the rapid development of edge chips, research in artificial intelligence (AI) has shifted to both of the computing paradigms, i.e., cloud computing and edge computing. In recent years, we have witnessed significant progress in developing more advanced AI models on cloud servers that surpass traditional deep learning models owing to model innovations (e.g., Transformers, Pretrained families), explosion of training data and soaring computing capabilities. However, edge computing, especially edge and cloud collaborative computing, are still in its infancy to announce their success due to the resource-constrained IoT scenarios with very limited algorithms deployed. In this survey, we conduct a systematic review for both cloud and edge AI. Specifically, we are the first to set up the collaborative learning mechanism for cloud and edge modeling with a thorough review of the architectures that enable such mechanism. We also discuss potentials and practical experiences of some on-going advanced edge AI topics including pretraining models, graph neural networks and reinforcement learning. Finally, we discuss the promising directions and challenges in this field.Comment: 20 pages, Transactions on Knowledge and Data Engineerin

MERS coronaviruses from camels in Africa exhibit region-dependent genetic diversity

International audienceMiddle East respiratory syndrome coronavirus (MERS-CoV) causes a zoonotic respiratory disease of global public health concern, and dromedary camels are the only proven source of zoonotic infection. Although MERS-CoV infection is ubiquitous in dromedaries across Africa as well as in the Arabian Peninsula, zoonotic disease appears confined to the Arabian Peninsula. MERS-CoVs from Africa have hitherto been poorly studied. We genetically and phenotypically characterized MERS-CoV from dromedaries sampled in Morocco, Burkina Faso, Nigeria, and Ethiopia. Viruses from Africa (clade C) are phylogenetically distinct from contemporary viruses from the Arabian Peninsula (clades A and B) but remain antigenically similar in microneutralization tests. Viruses from West (Nigeria, Burkina Faso) and North (Morocco) Africa form a subclade, C1, that shares clade-defining genetic signatures including deletions in the accessory gene ORF4b. Compared with human and camel MERS-CoV from Saudi Arabia, virus isolates from Burkina Faso (BF785) and Nigeria (Nig1657) had lower virus replication competence in Calu-3 cells and in ex vivo cultures of human bronchus and lung. BF785 replicated to lower titer in lungs of human DPP4-transduced mice. A reverse genetics-derived recombinant MERS-CoV (EMC) lacking ORF4b elicited higher type I and III IFN responses than the isogenic EMC virus in Calu-3 cells. However, ORF4b deletions may not be the major determinant of the reduced replication competence of BF785 and Nig1657. Genetic and phenotypic differences in West African viruses may be relevant to zoonotic potential. There is an urgent need for studies of MERS-CoV at the animal-human interface

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Co-inhibition of TIGIT and PD-1/PD-L1 in Cancer Immunotherapy: Mechanisms and Clinical Trials

Abstract Over the past decade, immune checkpoint inhibitors (ICIs) have emerged as a revolutionary cancer treatment modality, offering long-lasting responses and survival benefits for a substantial number of cancer patients. However, the response rates to ICIs vary significantly among individuals and cancer types, with a notable proportion of patients exhibiting resistance or showing no response. Therefore, dual ICI combination therapy has been proposed as a potential strategy to address these challenges. One of the targets is TIGIT, an inhibitory receptor associated with T-cell exhaustion. TIGIT has diverse immunosuppressive effects on the cancer immunity cycle, including the inhibition of natural killer cell effector function, suppression of dendritic cell maturation, promotion of macrophage polarization to the M2 phenotype, and differentiation of T cells to regulatory T cells. Furthermore, TIGIT is linked with PD-1 expression, and it can synergize with PD-1/PD-L1 blockade to enhance tumor rejection. Preclinical studies have demonstrated the potential benefits of co-inhibition of TIGIT and PD-1/PD-L1 in enhancing anti-tumor immunity and improving treatment outcomes in several cancer types. Several clinical trials are underway to evaluate the safety and efficacy of TIGIT and PD-1/PD-L1 co-inhibition in various cancer types, and the results are awaited. This review provides an overview of the mechanisms of TIGIT and PD-1/PD-L1 co-inhibition in anti-tumor treatment, summarizes the latest clinical trials investigating this combination therapy, and discusses its prospects. Overall, co-inhibition of TIGIT and PD-1/PD-L1 represents a promising therapeutic approach for cancer treatment that has the potential to improve the outcomes of cancer patients treated with ICIs

Second-harmonic generation of embedded plasmonic nanoparticle arrays via interparticle coupling

Efficient nonlinear frequency conversion, such as second-harmonic generation in ultracompact structures, is essential for the development of modern nanophotonic devices. Here, we demonstrate intense second-harmonic emission in scalable embedded Ag nanoparticle arrays fabricated by ion implantation into BK7 glass. The interparticle coupling effect significantly enhances the local field at the nanogap (gap size ∼1 nm) of two neighboring Ag nanoparticles and finally amplifies second-harmonic emission generated at the surface of plasmonic nanoparticles. Notably, the intensity of second-harmonic emission in embedded Ag nanoparticle arrays is comparable to that of two-dimensional transition metal dichalcogenides under the excitation of a fundamental wave at 1064 nm and independent of the incident polarization angles. Our work offers a promising strategy on the rapid fabrication of low-cost nonlinear optical nanostructures with great environmental stability.Published versionThis work was supported by National Natural Science Foundation of China (Grant No. 11535008) and Taishan Scholars Program of Shandong Province (No. tspd20210303)

Surface plasmon enhanced photoluminescence of monolayer WS₂ on ion beam modified functional substrate

Developing efficient methods for boosting light-matter interactions is critical to improve the functionalities of two-dimensional (2D) transition metal dichalcogenides toward next-generation optoelectronic devices. Here, we demonstrate that the light-matter interactions in tungsten disulfide (WS2) monolayer can be significantly enhanced by introducing an air-stable functional substrate (fused silica with embedded plasmonic Ag nanoparticles). Distinctive from conventional strategies, the Ag nanoparticles are embedded under the surface of fused silica via ion implantation, forming a functional substrate for WS2 monolayer with remarkably environmental stability. A tenfold photoluminescence enhancement in WS2 monolayer has been achieved due to the plasmonic effect of Ag nanoparticles. This work offers a strategy to fabricate the plasmon-2D hybrid system at low cost and large scale and paves the way for their applications in optoelectronics and photonics.Published versionThis work was supported by the National Natural Science Foundation of China (Grant No. 11535008) and the Taishan Scholars Program of Shandong Province (No. tspd20210303)

Relationships among shift work, hair cortisol concentration and sleep disorders: a cross-sectional study in China

Objective The present study was designed to demonstrate the relationships among shift work, hair cortisol concentration (HCC) and sleep disorders.Design A cross-sectional study.Setting Three petroleum administrations in Karamay city of Xinjiang, China.Participants 435 individuals including 164 males and 271 females participated in the research.Outcome measures Information on shift work was collected by a self-administered questionnaire. HCC was determined using an automatic radioimmunoassay instrument. Sleep quality was measured on the Pittsburgh Sleep Quality Index scale.Results Shiftwork was associated with an increased prevalence of sleep disorders compared with the fixed day shift (two shifts: OR 3.11, 95% CI 1.57 to 6.19; three shifts: OR 2.87, 95% CI 1.38 to 5.98; four shifts: OR 2.22, 95% CI 1.17 to 4.18; others: OR 3.88, 95% CI= 1.36 to 11.08). Workers with different shift patterns had higher HCC levels than day workers ((fixed day shift: geometric mean±geometric SD=2.33±1.65; two shifts: 3.76±1.47; three shifts: 3.15±1.64; four shifts: 3.81±1.55; others: 3.60±1.33) ng/g hair, η2=0.174) and high HCC was associated with the higher prevalence of sleep disorders (OR 4.46, 95% CI 2.70 to 7.35). The mediating effect of HCC on the relationship between shift work and sleep disorders was 0.25 (95% CI 0.09 to 0.41).Conclusion We found that, when compared with the fixed day shift, shiftwork was associated with both the higher HCC, and also with an increased risk of sleep disorders. High HCC was associated with the occurrence of sleep disorders. In addition, HCC had mediating effect in shift work and sleep disorders. Thus, HCC can be considered as an early marker of shiftwork circadian disruption to early detection and management of sleep disorders