DESIGN OF A TIME-AMPLIFIED, STOCHASTIC PHASE INTERPOLATION TIME-TO-DIGITAL-CONVERTER FOR BIOMEDICAL IMAGING APPLICATIONS

Time-to-digital converters (TDC) and single-photon avalanche diodes (SPAD) can be integrated together into SPAD-imagers. TDC is a mixed-signal circuit that can convert the time differences between the two input signals. In SPAD-imagers, the electrical pulses triggered by incident photons are measured against the reference clock to extract time-of flight (ToF) data. The performance of TDC is directly related to the temporal performance of the SPAD-imagers in biomedical imaging systems, such as positron emission tomography (PET) and diffuse optical tomography (DOT). In recent years, the evolution of modern complementary metal-oxide-semiconductor (CMOS) technology made it possible to implant SPAD-imagers for imaging neural activities in moving subjects. This work proposes a new TDC design to further improve future SPAD-imager based time-domain imaging systems. Firstly, this thesis provides a detailed review of the current research on brain imaging and neural activity recording methods. Next, the operating principles of different TDC architectures are presented. In the following chapter, the proposed time amplified, stochastic phase interpolation (TASPI) TDC architecture was designed and tested in TSMC 65 nm standard CMOS technology nodes that can achieve a ~16 ps resolution with 6 effective number of bits in a 0.06 mm2 silicon area is presented. Based on the results, areas for future improvements are identified and discussed in detail.ThesisMaster of Applied Science (MASc

REAL-TIME MONITORING DEFORMATION OF BUILDING USING PHOTOGRAPHY DYNAMIC MONITORING SYSTEM

The spatial structure building is a type of building system; it is necessary to monitor deformation to determine its stability and robustness. Under the dynamic deformation of structures, it is challenging to determine appropriate zero image (the reference image) if we use the PST-IM- MP (photograph scale transformation-image matching-motion parallax) method to obtain the deformation of structures. This paper offers the Z-MP (zero-centered motion parallax) method to solve these problems and offers PDMS (Photography Dynamic Monitoring System) based on the digital photography system to monitor the dynamic deformation of the tennis stadium located in Jinan Olympic Sports Center. The results showed that the spatial structures of the tennis stadium were robust, and the deformations were elastic and within the permissible value. Compared with the PST-IM-MP method, the Z-MP method is more suitable for deformation monitoring structures under real-time deformation. This paper indicates PDMS has advantages of the simplicity of operations, automation, and the ability of non-contact dynamic deformation monitoring for multiple points in a short period. In the future, it will have broader application prospects

A Non-Contact PCB Multi-Fault Diagnosis Algorithm Based on Scalar Magnetic Field Fusion Feature and Transformer Architecture

Non-contact printed circuit board (PCB) fault diagnosis has been widely applied in PCB detection and maintenance. Due to objective factors such as visual blind spots, low-loss circuit structure design, and frequency insensitivity, traditional algorithms based on visual and temperature features are limited in practice. Therefore, the algorithm based on electromagnetic features containing rich physical connotations and prominent frequency features has received attention in PCB fault diagnosis. Based on the basic principles of electromagnetic physics and PCB fault relationship, this article proposes a scalar magnetic field source feature and further improves feature performance by adding topological relationships of multi-faults to generate the fusion feature. The backbone of the PCB diagnosis model is established on the Transformer architecture, effectively utilizing self-attention and parallel computing mechanisms to explore the inner correlation between each group feature. The paper provides a new non-contact PCB fault diagnosis solution that enriches existing methods. Besides, through actual experiments setting up multi-fault PCBs, the feasibility of our process is proved based on the proposed features and models. The specific multiple indicators Overall Precision (OP), Per Class Precision (CP), Overall Recall (OR), Per Class Recall (CR), Overall F1 Measure (OF1), Per Class F1 Measure (CF1), Accuracy (ACC), Mean Average Precision (mAP) are 98.55%, 94.89%, 98.55%, 95.11%, 98.55%, 95.32%, 96.01%, and 97.27

Preparation of ZrB2-ZrC-SiC-ZrO2 nanopowders with in-situ grown homogeneously dispersed SiC nanowires

To explore the application of SiC nanowires (SiCnws) in ZrB2 based ceramic materials, a facile approach is reported to in situ synthesize homogeneously dispersed SiCnws in ZrB2-ZrC-SiC-ZrO2 nanopowders by pyrolyzing a B-Si-Zr containing sol precursor impregnated in polyurethane sponge. The sponge was used to provide porous skeletons for the growth of SiC nanowires and facilitate their uniform distribution in the powders. After heat-treatment of the precursor with a Si/Zr atomic ratio of 10 at 1500 °C for 2 h, ZrB2-ZrC-SiC-ZrO2 ceramic powders were obtained with an even and fine particle size of ~100 nm. The SiCnws were in a diameter of ~100 nm with a controllable length varying from tens to hundreds of microns by increasing the silicon content in the precursor. Moreover, the produced SiCnws were in high purity, and homogeneously dispersed in the hybrid nanopowders. The study can open up a feasible route to overcome the critical fabrication process in SiCnws reinforced ceramic matrix composites

CLIP-Guided Source-Free Object Detection in Aerial Images

Domain adaptation is crucial in aerial imagery, as the visual representation of these images can significantly vary based on factors such as geographic location, time, and weather conditions. Additionally, high-resolution aerial images often require substantial storage space and may not be readily accessible to the public. To address these challenges, we propose a novel Source-Free Object Detection (SFOD) method. Specifically, our approach begins with a self-training framework, which significantly enhances the performance of baseline methods. To alleviate the noisy labels in self-training, we utilize Contrastive Language-Image Pre-training (CLIP) to guide the generation of pseudo-labels, termed CLIP-guided Aggregation (CGA). By leveraging CLIP's zero-shot classification capability, we aggregate its scores with the original predicted bounding boxes, enabling us to obtain refined scores for the pseudo-labels. To validate the effectiveness of our method, we constructed two new datasets from different domains based on the DIOR dataset, named DIOR-C and DIOR-Cloudy. Experimental results demonstrate that our method outperforms other comparative algorithms. The code is available at https://github.com/Lans1ng/SFOD-RS.Comment: Accepted by IGARSS202

Does epigenetic polymorphism contribute to phenotypic variances in Jatropha curcas L.?

<p>Abstract</p> <p>Background</p> <p>There is a growing interest in <it>Jatropha curcas </it>L. (jatropha) as a biodiesel feedstock plant. Variations in its morphology and seed productivity have been well documented. However, there is the lack of systematic comparative evaluation of distinct collections under same climate and agronomic practices. With the several reports on low genetic diversity in jatropha collections, there is uncertainty on genetic contribution to jatropha morphology.</p> <p>Result</p> <p>In this study, five populations of jatropha plants collected from China (CN), Indonesia (MD), Suriname (SU), Tanzania (AF) and India (TN) were planted in one farm under the same agronomic practices. Their agronomic traits (branching pattern, height, diameter of canopy, time to first flowering, dormancy, accumulated seed yield and oil content) were observed and tracked for two years. Significant variations were found for all the agronomic traits studied. Genetic diversity and epigenetic diversity were evaluated using florescence Amplified Fragment Length Polymorphism (fAFLP) and methylation sensitive florescence AFLP (MfAFLP) methods. Very low level of genetic diversity was detected (polymorphic band <0.1%) within and among populations. In contrast, intermediate but significant epigenetic diversity was detected (25.3% of bands were polymorphic) within and among populations. More than half of CCGG sites surveyed by MfAFLP were methylated with significant difference in inner cytosine and double cytosine methylation among populations. Principal coordinates analysis (PCoA) based on Nei's epigenetic distance showed Tanzania/India group distinct from China/Indonesia/Suriname group. Inheritance of epigenetic markers was assessed in one F1 hybrid population between two morphologically distinct parent plants and one selfed population. 30 out of 39 polymorphic markers (77%) were found heritable and followed Mendelian segregation. One epiallele was further confirmed by bisulphite sequencing of its corresponding genomic region.</p> <p>Conclusion</p> <p>Our study confirmed climate and practice independent differences in agronomic performance among jatropha collections. Such agronomic trait variations, however, were matched by very low genetic diversity and medium level but significant epigenetic diversity. Significant difference in inner cytosine and double cytosine methylation at CCGG sites was also found among populations. Most epigenetic differential markers can be inherited as epialleles following Mendelian segregation. These results suggest possible involvement of epigenetics in jatropha development.</p

Risk prediction for <1 cm lateral lymph node metastasis in papillary thyroid microcarcinoma

BackgroundBecause the diameter of the suspicious lymph nodes is less than 1 cm and adjacent to important structures in the neck, the diagnosis of small LLNM is important but difficult without the help of fine needle aspiration (FNA). There are no relevant reports of risk factors that predict the risk of suspicious &lt;1 cm LLNM.MethodsA total of 159 PTMC patients with suspicious &lt;1 cm LLNM were included in the study. Multivariate logistic regression analysis was used to identify ultrasound independent predictors of LLNM. A predictive model was developed according to multivariate logistic regression and evaluated by Hosmer-Lemeshow fit test.ResultsAge ≤ 38 years old, the largest PTMC was located in the upper part, and the presence of liquefaction or microcalcification in suspicious lymph nodes were independent risk factors for LLNM (univariate analysis P = 0.00, 0.00, 0.00; multivariate analysis P = 0.00, 0.02, 0.00. OR = 4.66 [CI: 1.78-12.21], 3.04 [CI: 1.24-7.46], 6.39 [CI: 1.85-22.00]). The predictive model for the diagnosis of suspicious &lt;1 cm lymph nodes was established as: P = ex/(1 + ex). X = -1.29 + (1.11 × whether the largest tumor is located in the upper part) + (1.54 × whether the age is ≤ 38 years) + (1.85 × whether the suspicious lymph nodes have liquefaction/microcalcification). The Hosmer-Lemeshow fit test was used to test the predicted ability, and it found that the predictive model had a good fit and prediction accuracy (X2 = 6.214, P = 0.623 &gt; 0.05). Chi squared trend analysis showed that the increase in the number of risk factors gradually increased the malignancy possibility of suspicious &lt;1 cm lymph nodes (chi squared trend test, P = 0.00).ConclusionsAge ≤ 38 years old, the largest PTMC located in the upper part, and the presence of liquefaction or microcalcification in suspicious lymph nodes were independent risk factors for suspicious &lt;1 cm LLNM in PTMC patients. Our result show that it is feasible to evaluate the malignant possibility of these lymph nodes using the number of risk factors