Advanced Methods in Neural Networks-Based Sensitivity Analysis with their Applications in Civil Engineering

Artificial neural networks (ANNs) are powerful tools that are used in various engineering fields. Their characteristics enable them to solve prediction, regression, and classification problems. Nevertheless, the ANN is usually thought of as a black box, in which it is difficult to determine the effect of each explicative variable (input) on the dependent variables (outputs) in any problem. To investigate such effects, sensitivity analysis is usually applied on the optimal pre-trained ANN. Existing sensitivity analysis techniques suffer from drawbacks. Their basis on a single optimal pre-trained ANN model produces instability in parameter sensitivity analysis because of the uncertainty in neural network modeling. To overcome this deficiency, two successful sensitivity analysis paradigms, the neural network committee (NNC)-based sensitivity analysis and the neural network ensemble (NNE)-based parameter sensitivity analysis, are illustrated in this chapter. An NNC is applied in a case study of geotechnical engineering involving strata movement. An NNE is implemented for sensitivity analysis of two classic problems in civil engineering: (i) the fracture failure of notched concrete beams and (ii) the lateral deformation of deep-foundation pits. Results demonstrate good ability to analyze the sensitivity of the most influential parameters, illustrating the underlying mechanisms of such engineering systems

Enhanced DCT-OFDM system with index modulation

Discrete cosine transform (DCT) based orthogonal frequency division multiplexing (OFDM), which has double number of subcarrier compared to the classic discrete fourier transform (DFT) based OFDM (DFT-OFDM) at the same bandwidth, is a promising high spectral efficiency multicarrier techniques for future wireless communication. In this paper, an enhanced DCT-OFDM with index modulation (IM) (EDCT-OFDM-IM) is proposed to further exploit the benefits of the DCT-OFDM and IM techniques. To be more specific, a pre-filtering method based DCT-OFDM-IM transmitter is first designed and the non-linear maximum likelihood (ML) is developed for our EDCT-OFDM-IM system. Moreover, the average bit error probability (ABEP) of the proposed EDCT-OFDM-IM system is derived, which is confirmed by our simulation results. Both simulation and theoretical results are shown that the proposed EDCT-OFDM-IM system exhibits better bit error rate (BER) performance over the conventional DFT-OFDM-IM and DCT-OFDM-IM counterparts

Index Modulation Assisted DCT-OFDM with Enhanced Transceiver Design

An index modulation (IM) assisted Discrete Cosine Transform based Orthogonal Frequency Division Multiplexing (DCT-OFDM) with Enhanced Transmitter Design (termed as EDCT-OFDM-IM) is proposed. It amalgamates the concept of Discrete Cosine Transform assisted Orthogonal Frequency Division Multiplexing (DCT-OFDM) and Index Modulation (IM) to exploit the design freedom provided by the double number of available subcarrier under the same bandwidth. In the proposed EDCT-OFDM-IM scheme, the maximum likelihood (ML) detector used for symbol bits and index bits recovering is derived and the sophisticated designing guidelines for EDCT-OFDM-IM are provided. Based on the derived pairwise error event probability, a theoretical upper bound on the average bit-error probability (ABEP) of EDCT-OFDM-IM is provided over multipath fading channels. Furthermore, the maximum peak-to-average power ratio (PAPR) of our proposed EDCT-OFDM-IM scheme is derived and compared to than the general Discrete Fourier Transform (DFT) based OFDM-IM counterpart

Normal Red Blood Cell Count Reference Values in Chinese Presenile Women Given by Geographical Area

Background/PurposeWe aimed to standardize the normal reference value of red blood cell (RBC) counts in Chinese presenile women using an underlying scientific basis.MethodsThis research was conducted to study the relationship between the normal reference value of 31,405 RBC samples from presenile women in eight different geographical areas in China. RBC counts were determined using a microscopic counting method.ResultsThere was a significant correlation between geographical factors and the normal reference RBC value in presenile women (F = 187.82, p = 0.000). Using stepwise regression analysis, one regression equation was obtained.ConclusionIf geographical values are obtained in a certain area, the normal RBC reference value in presenile women in this area can be obtained using the regression equation

Leveraging Historical Medical Records as a Proxy via Multimodal Modeling and Visualization to Enrich Medical Diagnostic Learning

Simulation-based Medical Education (SBME) has been developed as a cost-effective means of enhancing the diagnostic skills of novice physicians and interns, thereby mitigating the need for resource-intensive mentor-apprentice training. However, feedback provided in most SBME is often directed towards improving the operational proficiency of learners, rather than providing summative medical diagnoses that result from experience and time. Additionally, the multimodal nature of medical data during diagnosis poses significant challenges for interns and novice physicians, including the tendency to overlook or over-rely on data from certain modalities, and difficulties in comprehending potential associations between modalities. To address these challenges, we present DiagnosisAssistant, a visual analytics system that leverages historical medical records as a proxy for multimodal modeling and visualization to enhance the learning experience of interns and novice physicians. The system employs elaborately designed visualizations to explore different modality data, offer diagnostic interpretive hints based on the constructed model, and enable comparative analyses of specific patients. Our approach is validated through two case studies and expert interviews, demonstrating its effectiveness in enhancing medical training.Comment: Accepted by IEEE VIS 202

Strong enhancement of photoresponsivity with shrinking the electrodes spacing in few layer GaSe photodetectors

A critical challenge for the integration of the optoelectronics is that photodetectors have relatively poor sensitivities at the nanometer scale. It is generally believed that a large electrodes spacing in photodetectors is required to absorb sufficient light to maintain high photoresponsivity and reduce the dark current. However, this will limit the optoelectronic integration density. Through spatially resolved photocurrent investigation, we find that the photocurrent in metal-semiconductor-metal (MSM) photodetectors based on layered GaSe is mainly generated from the photoexcited carriers close to the metal-GaSe interface and the photocurrent active region is always close to the Schottky barrier with higher electrical potential. The photoresponsivity monotonically increases with shrinking the spacing distance before the direct tunneling happen, which was significantly enhanced up to 5,000 AW-1 for the bottom contacted device at bias voltage 8 V and wavelength of 410 nm. It is more than 1,700-fold improvement over the previously reported results. Besides the systematically experimental investigation of the dependence of the photoresponsivity on the spacing distance for both the bottom and top contacted MSM photodetectors, a theoretical model has also been developed to well explain the photoresponsivity for these two types of device configurations. Our findings realize shrinking the spacing distance and improving the performance of 2D semiconductor based MSM photodetectors simultaneously, which could pave the way for future high density integration of 2D semiconductor optoelectronics with high performances.Comment: 25 pages, 4 figure

Tomographic Reconstruction of Light Field PIV Based on Backward Ray-Tracing Technique

The calculation of the weight matrix is one of the key steps of the tomographic reconstruction in the light field particle image velocimetry (light field PIV) system. At present, the existing calculation method of the weight matrix in light field PIV based on the forward ray-tracing technique (named as Fahringer’s method) is very time-consuming. To improve the computational efficiency of the weight matrix, this paper presents a computational method for the weight matrix based on the backward ray-tracing technique in combination with Gaussian function (named as Gaussian function method). An Expectation-Maximization (EM) algorithm is employed for the reconstruction of the 3D particle field, and a summed line-ofsight (SLOS) estimation is further used to accelerate the reconstruction process. The computational accuracy and efficiency of the weight matrix, the reconstruction quality of the 3D particle field, and the velocity field accuracy by Gaussian function method are numerically investigated. Finally, experiments are carried out to verify the feasibility of the weight matrix by Gaussian function method. Numerical results illustrated that Gaussian function method can improve the computational efficiency of the weight matrix by more than 10 times. SLOS is capable of further accelerating the computational efficiency of the overall reconstruction process including the pre-determination, the calculation of the weight matrix and the reconstruction. The velocity field accuracy by Gaussian function method is almost the same as that by Fahringer’s method. The experimental results of the 3D-3C velocity field of a laminar flow further verify the feasibility of the computational method for the weight matrix based on Gaussian function

Case report: Deep molecular remissions post two separate CD19-targeted chimeric antigen receptor T-cell therapies do not prevent disease from relapsing in Philadelphia chromosome-positive acute lymphoblastic leukemia

Philadelphia chromosome–positive acute lymphoblastic leukemia (Ph+ ALL) is an aggressive B-cell malignancy. The management of a relapsed Ph+ ALL patient is challenging. Currently, either allogeneic stem cell transplant (allo-SCT) or CD19-targeted chimeric antigen receptor T-cell (CAR T-cell) are usually employed as salvage modalities for a relapsed patient. However, there are few reports concerning cases that had both allo-SCT and multiple CAR T-cell therapies, and the optimal management of such patients is unclear. Here, we report a relapsed Ph+ ALL male who was first salvaged with autologous CAR T-cell therapy, followed by allo-SCT. Unfortunately, he had a second relapse even with complete molecular remission (CMR) response after the first CAR T and allo-SCT. This patient was then successfully salvaged by a second CAR T-cell product that is donor-derived. However, even with a CMR response once again following the second CAR T-cell therapy and prophylactic donor lymphocyte infusion, he experienced a molecular relapse; ponatinib was employed as the subsequent salvage treatment. He achieved a CMR response following ponatinib and was still in remission at the last follow-up. No ABL kinase mutation was detected during the whole course of the disease. This case indicated that a repeated CD19-targeted CAR T-cell treatment is feasible and may be effective in a relapsed Ph+ ALL patient that had previous CAR T-cell and allo-SCT, even though both CAR T-cell have the same construction. However, even with a deep response after each CAR T-cell therapy and allo-SCT, there is still a very small amount of undetectable leukemic cells. The optimal management of Ph+ ALL patients who have a deep response after a second CAR T-cell therapy deserves further exploration

A review of high-solid anaerobic digestion (HSAD):From transport phenomena to process design

High-solid anaerobic digestion (HSAD) is an attractive organic waste disposal method for bioenergy recovery and climate change mitigation. The development of HSAD is facing several challenges such as low biogas and methane yields, low reaction rates, and ease of process inhibition due to low mass diffusion and mixing limitations of the process. Therefore, the recent progress in HSAD is critically reviewed with a focus on transport phenomena and process modelling. Specifically, the work discusses hydrodynamic phenomena, biokinetic mechanisms, HSAD-specific reactor simulations, state-of-the-art multi-stage reactor designs, industrial ramifications, and key parameters that enable sustained operation of HSAD processes. Further research on novel materials such as bio-additives, adsorbents, and surfactants can augment HSAD process efficiency, while ensuring the stability. Additionally, a generic simulation tool is of urgent need to enable a better coupling between biokinetic phenomena, hydrodynamics, and heat and mass transfer that would warrant HSAD process scale-up

Decreased programmed cell death ligand 2-positive monocytic myeloid-derived suppressor cells and programmed cell death protein 1-positive T-regulatory cells in patients with type 2 diabetes: implications for immunopathogenesis

Objectives: The activation of immune cells plays a significant role in the progression of type 2 diabetes. This study aimed to investigate the potential role of myeloid-derived suppressor cells (MDSCs) and T-regulatory cells (Tregs) in type 2 diabetes. Methods: A total of 61 patients diagnosed with type 2 diabetes were recruited. Clinical characteristics were reviewed and peripheral blood samples were collected. We calculated the percentage of different cells. Frequencies of MDS C subsets refered to the percentage of G-MDSCs (CD15+CD33+CD11b+CD14-HLA-DR-/low) in CD45 positive cells and the percentage of M-MDSCs (CD14+CD15-CD11b+CD33+HLA-DR-/low) in lymphocytes plus monocytes. Results: Frequencies of programmed cell death ligand 1-positive granulo cytic MDSCs (PD-L1+ G-MDSCs), programmed cell death ligand 2-positive monocytic MDSCs (PD-L2+ M-MDSCs), PD-L2+ G-MDSC, and programmed cell death protein 1-positive Tregs (PD-1+Tregs) were decreased in patients with type 2 diabetes. The frequency of PD-1+ Tregs was positively related to PD-L2+ M-MDSCs (r = 0.357, P = 0.009) and negatively related to HbA1c (r = -0.265, P = 0.042), fasting insulin level (r = −0.260, P = 0.047), and waist circumference (r = −0.373, P = 0.005). Conclusions: Decreased PD-L2+ M-MDSCs and PD-1+ Tregs may promote effector T cell activation, leading to chronic low-grade inflammation in type 2 diabetes. These findings highlight the contribution of MDSCs and Tregs to the immunopathogenesis of type 2 diabetes and suggest their potential as targets for new therapeutic approaches