Modelling wire problems using the unstructured transmission line modelling method

In this thesis, the Unstructured Transmission Line Modelling (UTLM) method is used to study wire problems with various configurations and structures. The analysis of multi-wire systems based upon local field solutions for wave equations is presented for the understanding of propagation mode within a wire bundle. The derivation of TLM scheme based upon unstructured triangular and tetrahedral meshes is presented, along with applications to the study of electromagnetic coupling and field transmission of canonical single-wire models and junction structures. The impact of wire configurations and positioning of wires within a bundle on the electromagnetic coupling into wires is investigated. Moreover, the radiation patterns of a Log-periodic dipole array (LPDA) antenna in different frequency bands is investigated. The accuracy of results presented in this work is validated by self-convergence with respect to sufficient simulation parameters and the efficiency of this method is evaluated based upon computational expenses

Photoproduction of C-even quarkonia at EIC and EicC

The $\eta_c$ photoproduction in $ep$ collision has long been proposed as an ideal process to probe the existence of odderon. In the current work, we systematically investigate the photoproduction of various $C$-even heavy quarkonia (exemplified by $\eta_{c(b)}$, and $\chi_{c(b)J}$ with $J=0,1,2$) via one-photon exchange channel, at the lowest order in $\alpha_s$ and heavy quark velocity in the context of NRQCD factorization. We find that the photoproduction rates of the $C$-even quarkonia through this mechanism are comparable in magnitude with that through the odderon-initiated mechanism, even in the Regge limit ($s\gg -t$), though the latter types of predictions suffers from considerable theoretical uncertainties. The future measurements of these types of quarkonium photoproduction processes in \texttt{EIC} and \texttt{EicC} are crucial to ascertain which mechanism plays the dominant role.Comment: 16 pages, 9 figure

Hard-scattering approach to strongly hindered electric dipole transitions between heavy quarkonia

The conventional wisdom in dealing with electromagnetic transition between heavy quarkonia is the multipole expansion, when the emitted photon has a typical energy of order quarkonium binding energy. Nevertheless, in the case when the energy carried by the photon is of order typical heavy quark momentum, the multipole expansion doctrine is expected to break down. In this work, we apply the "hard-scattering" approach originally developed to tackle the strongly hindered magnetic dipole ($M1$) transition [Y.~Jia {\it et al.}, Phys. \ Rev. \ D. 82, 014008 (2010)] to the strongly hindered electric dipole ($E1$) transition between heavy quarkonia. We derive the factorization formula for the strongly hindered $E1$ transition rates at the lowest order in velocity and $\alpha_s$ in the context of the non-relativistic QCD (NRQCD), and conduct a detailed numerical comparison with the standard predictions for various bottomonia and charmonia $E1$ transition processes.Comment: 18 pages, 2 figures, 4 table

Fast Prototyping Next-Generation Accelerators for New ML Models using MASE: ML Accelerator System Exploration

Machine learning (ML) accelerators have been studied and used extensively to compute ML models with high performance and low power. However, designing such accelerators normally takes a long time and requires significant effort. Unfortunately, the pace of development of ML software models is much faster than the accelerator design cycle, leading to frequent and drastic modifications in the model architecture, thus rendering many accelerators obsolete. Existing design tools and frameworks can provide quick accelerator prototyping, but only for a limited range of models that can fit into a single hardware device, such as an FPGA. Furthermore, with the emergence of large language models, such as GPT-3, there is an increased need for hardware prototyping of these large models within a many-accelerator system to ensure the hardware can scale with the ever-growing model sizes. In this paper, we propose an efficient and scalable approach for exploring accelerator systems to compute large ML models. We developed a tool named MASE that can directly map large ML models onto an efficient streaming accelerator system. Over a set of ML models, we show that MASE can achieve better energy efficiency to GPUs when computing inference for recent transformer models. Our tool will open-sourced upon publication

HASS:Hardware-aware sparsity search for dataflow DNN accelerator

Deep Neural Networks (DNNs) excel in learning hierarchical representations from raw data, such as images, audio, and text. To compute these DNN models with high performance and energy efficiency, these models are usually deployed onto customized hardware accelerators. Among various accelerator designs, dataflow architecture has shown promising performance due to its layer-pipelined structure and its scalability in data parallelism.Exploiting weights and activations sparsity can further enhance memory storage and computation efficiency. However, existing approaches focus on exploiting sparsity in non-dataflow accelerators, which cannot be applied onto dataflow accelerators because of the large hardware design space introduced. As such, this could miss opportunities to find an optimal combination of sparsity features and hardware designs.In this paper, we propose a novel approach to exploit unstructured weights and activations sparsity for dataflow accelerators, using software and hardware co-optimization. We propose a Hardware-Aware Sparsity Search (HASS) to systematically determine an efficient sparsity solution for dataflow accelerators. Over a set of models, we achieve an efficiency improvement ranging from 1.3× to 4.2× compared to existing sparse designs, which are either non-dataflow or non-hardware-aware. Particularly, the throughput of MobileNetV3 can be optimized to 4895 images per second. HASS is open-source: https://github.com/Yu-Zhewen/HAS

Numerical simulation of electromagnetic coupling in explicitly meshed wiring looms and bundles

In this paper, the Unstructured Transmission Line Modelling (UTLM) method based on a tetrahedral mesh is applied to model the electromagnetic coupling into wire looms and bundles with multiple cores that are typical of an aircraft system, when they are exposed to plane wave illuminations. The impact on the electromagnetic coupling into wires of both bundle configuration and the positioning of the bundle relative to simple structures are investigated using the UTLM method with explicit meshing of the wires. The work not only confirms that UTLM method as a powerful tool for dealing with wire looms and bundles but provides invaluable information on the margins to be expected in key experimental waveform parameters such as peak amplitude and frequency response

Characteristic cytokine profile of the aqueous humor in eyes with congenital cataract and pre-existing posterior capsule dysfunction

ObjectivesTo investigate the characteristic cytokine profile of the aqueous humor in eyes with congenital cataract and pre-existing posterior capsule dysfunction (PCD).MethodsIn this cross-sectional study, the enrolled eyes with congenital cataract and PCD were included in the PCD group, while those with an intact posterior capsule were included in the control group. Demographic data and biometric parameters were recorded. The levels of 17 inflammatory factors in the aqueous humor collected from the enrolled eyes were detected using Luminex xMAP technology, and intergroup differences in the collected data were analyzed.ResultsThe PCD group comprised 41 eyes from 31 patients with congenital cataract and PCD, whereas the control group comprised 42 eyes from 27 patients with congenital cataract and an intact posterior capsule. Lens thickness was significantly thinner in the PCD group than in the control group. However, the levels of monocyte chemoattractant protein-1 (MCP-1), transforming growth factor-β2 (TGF-β2), and vascular endothelial growth factor (VEGF) were significantly higher in the PCD group than in the control group. Multivariate logistic regression confirmed that lens thickness and TGF-β2 level were independent risk factors for PCD.ConclusionA thinner lens thickness in eyes with congenital cataract and PCD could serve as a biometric feature of these eyes. The higher levels of MCP-1, TGF-β2, and VEGF in eyes with PCD indicated a change in their intraocular inflammatory microenvironment, which possibly led to cataract progression. Lens thickness and TGF-β2 level are independent risk factors for PCD

Meta-analysis of the effect of PGM on survival prognosis of tumor patients

ObjectiveA systematic evaluation of the impact of phosphoglucose translocase PGM on the survival prognosis of tumor patients was conducted to understand its impact on tumors so as to improve the quality of survival and to find effective therapeutic targets for tumor patients.MethodsThe following were searched in the databases China National Knowledge Infrastructure (CNKI), Wanfang, Wipu, PubMed, EMBASE, ScienceDirect, Web of Science, and Cochrane Library: “PGM1”, “PGM2”, “PGM3”, “PGM4”, and “PGM5” as Chinese keywords and “PGM1”, “PGM2”, “PGM3”, “PGM4”, “PGM5”, “PGM1 cancer”, “PGM2 cancer”, “PGM3 cancer”, “PGM4 cancer”, “PGM5 cancer”, and “phosphoglucomutase”. Relevant studies published from the database establishment to April 2022 were collected. Studies that met the inclusion criteria were extracted and evaluated for quality with reference to the Cochrane 5.1.0 systematic evaluation method, and quality assessment was performed using RevMan 5.3 software.ResultsThe final results of nine articles and 10 studies with a total of 3,806 patients were included, including 272 patients in the PGM1 group, 541 patients in the PGM2 group, 1,775 patients in the PGM3 group, and 1,585 patients in the PGM5 group. Results of the meta-analysis: after determining the results of the nine articles, it was found that the difference was statistically significant with a p-value <0.05 (hazard ratio (HR) = 0.89, 95% CI 0.69–1.09, p = 0.000). To find the sources of heterogeneity, the remaining eight papers were tested after removing the highly sensitive literature, and the results showed I2 = 26.5%, p < 0.001, a statistically significant difference. The HR for high expression of PGM1 and PGM2 and PGM5 was <1, while the HR for high expression of PGM3 was >1.ConclusionAlthough PGM1, PGM2, PGM3, and PGM5 are enzymes of the same family, their effects on tumors are different. High expression of PGM1, PGM2, and PGM5 can effectively prolong the overall survival of patients. In contrast, high expression of PGM3 reduced the overall survival of patients. This study of PGM family enzymes can assist in subsequent tumor diagnosis, treatment, and prognostic assessment

Enhanced Stem Cell Osteogenic Differentiation by Bioactive Glass Functionalized Graphene Oxide Substrates

An unmet need in engineered bone regeneration is to develop scaffolds capable of manipulating stem cells osteogenesis. Graphene oxide (GO) has been widely used as a biomaterial for various biomedical applications. However, it remains challenging to functionalize GO as ideal platform for specifically directing stem cell osteogenesis. Herein, we report facile functionalization of GO with dopamine and subsequent bioactive glass (BG) to enhance stem cell adhesion, spreading, and osteogenic differentiation. On the basis of graphene, we obtained dopamine functionalized graphene oxide/bioactive glass (DGO/BG) hybrid scaffolds containing different content of DGO by loading BG nanoparticles on graphene oxide surface using sol-gel method. To enhance the dispersion stability and facilitate subsequent nucleation of BG in GO, firstly, dopamine (DA) was used to modify GO. Then, the modified GO was functionalized with bioactive glass (BG) using sol-gel method. The adhesion, spreading, and osteoinductive effects of DGO/BG scaffold on rat bone marrow mesenchymal stem cells (rBMSCs) were evaluated. DGO/BG hybrid scaffolds with different content of DGO could influence rBMSCs’ behavior. The highest expression level of osteogenic markers suggests that the DGO/BG hybrid scaffolds have great potential or elicit desired bone reparative outcome

Cancer-associated fibroblast related gene signature in Helicobacter pylori-based subtypes of gastric carcinoma for prognosis and tumor microenvironment estimation in silico analysis

IntroductionGastric cancer (GC) remains the major constituent of cancer-related deaths and a global public health challenge with a high incidence rate. Helicobacter pylori (HP) plays an essential role in promoting the occurrence and progression of GC. Cancer-associated fibroblasts (CAFs) are regarded as a significant component in the tumor microenvironment (TME), which is related to the metastasis of GC. However, the regulation mechanisms of CAFs in HP-related GC are not elucidated thoroughly.MethodsHP-related genes (HRGs) were downloaded from the GSE84437 and TCGA-GC databases. The two databases were combined into one cohort for training. Furthermore, the consensus unsupervised clustering analysis was obtained to sort the training cohort into different groups for the identification of differential expression genes (DEGs). Weighted correlation network analysis (WGCNA) was performed to verify the correlation between the DEGs and cancer-associated fibroblasts which were key components in the tumor microenvironment. The least absolute shrinkage and selection operator (LASSO) was executed to find cancer-associated fibroblast-related differential expression genes (CDEGs) for the further establishment of a prognostic model.Results and discussionIn this study, 52 HP-related genes (HRGs) were screened out based on the GSE84437 and TCGA-GC databases. A total of 804 GC samples were analyzed, respectively, and clustered into two HP-related subtypes. The DEGs identified from the two subtypes were proved to have a relationship with TME. After WGCNA and LASSO, the CAFs-related module was identified, from which 21 gene signatures were confirmed. Then, a CDEGs-Score was constructed and its prediction efficiency in GC patients was conducted for validation. Overall, a highly precise nomogram was established for enhancing the adaptability of the CDEGs-Score. Furthermore, our findings revealed the applicability of CDEGs-Score in the sensitivity of chemotherapeutic drugs. In general, our research provided brand-new possibilities for comprehending HP-related GC, evaluating survival, and more efficient therapeutic strategies