3-D calibration method and algorithm for freehand image of phased array ultrasonic testing

Phased array ultrasonic testing (UT) is an advanced technique applying ultrasound wave vibration theory to detect the flaw in tested materials by imaging. In this research, computer 3-D visualization of the flaw through calibrating the ultrasonic phased array image is proposed. 3-D calibration for ultrasonic phased array image is a procedure to calculate the spatial transformation matrix, spatial relationship between the US image plane and the tracker attached to the UT probe. The calibration method depends on a cross-string phantom and the corresponding algorithm. The phantom with a set of crosses guiding the operator quickly to find the scanning plane. The ten string crosses in the scanning plane provide the coordinates and spatial vectors for the calibration algorithm, thus the calibration algorithm can be realized based on the least-squares fitting method of the homologous points matching. Select the points having different distances and angles with the reference point to calculate the matrix and average them as the final result. The results show that the scanning plane positioning time is no more than 5 s. The precision and the accuracy results are the same as that is obtained through the other published methods in the medical 3-D ultrasound image calibration. The results make the 3-D flaw model reconstruction possible in phased array ultrasonic NDT. It will reduce the difficulties in the flaw recognizing and localization

Optimize Weight Rounding via Signed Gradient Descent for the Quantization of LLMs

Large Language Models (LLMs) have proven their exceptional capabilities in performing language-related tasks. However, their deployment poses significant challenges due to their considerable memory and storage requirements. In response to this issue, weight-only quantization, particularly 3 and 4-bit weight-only quantization, has emerged as one of the most viable solutions. As the number of bits decreases, the quantization grid broadens, thus emphasizing the importance of up and down rounding. While previous studies have demonstrated that fine-tuning up and down rounding with the addition of perturbations can enhance accuracy in some scenarios, our study is driven by the precise and limited boundary of these perturbations, where only the threshold for altering the rounding value is of significance. Consequently, we propose a concise and highly effective approach for optimizing the weight rounding task. Our method, named SignRound, involves lightweight block-wise tuning using signed gradient descent, enabling us to achieve outstanding results within 400 steps. SignRound competes impressively against recent methods without introducing additional inference overhead. The source code will be publicly available at \url{https://github.com/intel/neural-compressor} soon

The effect of fog on the probability density distribution of the ranging data of imaging laser radar

This paper outlines theoretically investigations of the probability density distribution (PDD) of ranging data for the imaging laser radar (ILR) system operating at a wavelength of 905 nm under the fog condition. Based on the physical model of the reflected laser pulses from a standard Lambertian target, a theoretical approximate model of PDD of the ranging data is developed under different fog concentrations, which offer improved precision target ranging and imaging. An experimental test bed for the ILR system is developed and its performance is evaluated using a dedicated indoor atmospheric chamber under homogeneously controlled fog conditions. We show that the measured results are in good agreement with both the accurate and approximate models within a given margin of error of less than 1%

Effective Quantization for Diffusion Models on CPUs

Diffusion models have gained popularity for generating images from textual descriptions. Nonetheless, the substantial need for computational resources continues to present a noteworthy challenge, contributing to time-consuming processes. Quantization, a technique employed to compress deep learning models for enhanced efficiency, presents challenges when applied to diffusion models. These models are notably more sensitive to quantization compared to other model types, potentially resulting in a degradation of image quality. In this paper, we introduce a novel approach to quantize the diffusion models by leveraging both quantization-aware training and distillation. Our results show the quantized models can maintain the high image quality while demonstrating the inference efficiency on CPUs. The code is publicly available at: https://github.com/intel/intel-extension-for-transformers

Preliminary exploration of amide proton transfer weighted imaging in differentiation between benign and malignant bone tumors

PurposeTo explore the value of 3D amide proton transfer weighted imaging (APTWI) in the differential diagnosis between benign and malignant bone tumors, and to compare the diagnostic performance of APTWI with traditional diffusion-weighted imaging (DWI).Materials and methodsPatients with bone tumors located in the pelvis or lower limbs confirmed by puncture or surgical pathology were collected from January 2021 to July 2023 in the First Affiliated Hospital of Zhengzhou University. All patients underwent APTWI and DWI examinations. The magnetization transfer ratio with asymmetric analysis at the frequency offset of 3.5 ppm [MTRasym(3.5 ppm)] derived by APTWI and the apparent diffusion coefficient (ADC) derived by DWI for the tumors were measured. The Kolmogorou-Smirnou and Levene normality test was used to confirm the normal distribution of imaging parameters; and the independent sample t test was used to compare the differences in MTRasym(3.5 ppm) and ADC between benign and malignant bone tumors. In addition, the receiver operating characteristic (ROC) curve was used to evaluate the diagnostic performance of different imaging parameters in differentiation between benign and malignant bone tumors. P<0.05 means statistically significant.ResultsAmong 85 bone tumor patients, 33 were benign and 52 were malignant. The MTRasym(3.5 ppm) values of malignant bone tumors were significantly higher than those of benign tumors, while the ADC values were significantly lower in benign tumors. ROC analysis shows that MTRasym(3.5 ppm) and ADC values perform well in the differential diagnosis of benign and malignant bone tumors, with the area under the ROC curve (AUC) of 0.798 and 0.780, respectively. Combination of MTRasym(3.5 ppm) and ADC values can further improve the diagnostic performance with the AUC of 0.849 (sensitivity = 84.9% and specificity = 73.1%).ConclusionMTRasym(3.5 ppm) of malignant bone tumors was significantly higher than that of benign bone tumors, reflecting the abnormal increase of protein synthesis in malignant tumors. APTWI combined with DWI can achieve a high diagnostic efficacy in differentiation between benign and malignant bone tumors

Macro-scale relationship between body mass and timing of bird migration

Clarifying migration timing and its link with underlying drivers is fundamental to understanding the evolution of bird migration. However, previous studies have focused mainly on environmental drivers such as the latitudes of seasonal distributions and migration distance, while the effect of intrinsic biological traits remains unclear. Here, we compile a global dataset on the annual cycle of migratory birds obtained by tracking 1531 individuals and 177 populations from 186 species, and investigate how body mass, a key intrinsic biological trait, influenced timings of the annual cycle using Bayesian structural equation models. We find that body mass has a strong direct effect on departure date from non-breeding and breeding sites, and indirect effects on arrival date at breeding and non-breeding sites, mainly through its effects on migration distance and a carry-over effect. Our results suggest that environmental factors strongly affect the timing of spring migration, while body mass affects the timing of both spring and autumn migration. Our study provides a new foundation for future research on the causes of species distribution and movement

Efficacy of autologous platelet-rich plasma intradiscal injection in the treatment of discogenic low back pain

Objective To investigate the efficacy of intradiscal injection of autologous platelet-rich plasma (PRP) in the treatment of discogenic low back pain (DLBP). b>Methods A retrospective analysis of clinical data from 47 DLBP patients treated at No.908 Hospital of Joint Logistics Support Force from January 2022 to June 2023 was conducted. Patients were divided into a PRP combined with celecoxib capsule treatment group (experimental group, n=16) and a celecoxib capsule monotherapy group (control group, n=31) based on the treatment method. The visual analogue scale (VAS) of low back pain and Oswestry disability index (ODI) scores were recorded before treatment, at 1 week, 1 month, and 6 months after treatment. Results VAS scores and ODI scores in the experimental group gradually decreased over time; the VAS scores and ODI scores in the control group decreased at 1 week after treatment compared to before treatment, but then showed a gradual upward trend. The VAS scores and ODI scores in the experimental group were lower than those in the control group at 1 month and 6 months after treatment (P＜0.05). Conclusion he long-term efficacy of autologous PRP combined with celecoxib capsule in treating DLBP is superior to that of celecoxib capsule monotherapy and can be considered as an effective treatment for DLBP

A targeted next-generation sequencing method for identifying clinically relevant mutation profiles in lung adenocarcinoma

Molecular profiling of lung cancer has become essential for prediction of an individual’s response to targeted therapies. Next-generation sequencing (NGS) is a promising technique for routine diagnostics, but has not been sufficiently evaluated in terms of feasibility, reliability, cost and capacity with routine diagnostic formalin-fixed, paraffin-embedded (FFPE) materials. Here, we report the validation and application of a test based on Ion Proton technology for the rapid characterisation of single nucleotide variations (SNVs), short insertions and deletions (InDels), copy number variations (CNVs), and gene rearrangements in 145 genes with FFPE clinical specimens. The validation study, using 61 previously profiled clinical tumour samples, showed a concordance rate of 100% between results obtained by NGS and conventional test platforms. Analysis of tumour cell lines indicated reliable mutation detection in samples with 5% tumour content. Furthermore, application of the panel to 58 clinical cases, identified at least one actionable mutation in 43 cases, 1.4 times the number of actionable alterations detected by current diagnostic tests. We demonstrated that targeted NGS is a cost-effective and rapid platform to detect multiple mutations simultaneously in various genes with high reproducibility and sensitivity

Promoting Cardiac Repair through Simple Engineering of Nanoparticles with Exclusive Targeting Capability toward Myocardial Reperfusion Injury by Thermal Resistant Microfluidic Platform

Nanoparticle (NP)-based intravenous administration represents the most convenient cardiac targeting delivery routine, yet, there are still therapeutic issues due to the lack of targeting efficiency and specificity. Active targeting methods using functionalization of ligands onto the NPs' surface may be limited by trivial modification procedures and reduced targeting yield in vivo. Here, a microfluidics assisted single step, green synthesis method is introduced for producing targeting ligands free heart homing NPs in a tailored manner. The generated beta-glucan-based NPs exhibit precise and efficient targeting capability toward Dectin-1(+) monocytes/macrophages, which are confirmed as main pathogenesis mediators for cardiac ischemic/reperfusion (I/R) injury, with a sequentially enhanced cardiac NP accumulation, and this targeting strategy is exclusively suitable for cardiac I/R but not for other cardiovascular diseases, as confirmed both in murine and human model. Comparing to FDA-approved nano-micelles formulation, beta-glucan NPs loaded with NACHT, LRR, and PYD domains-containing protein 3 (NLRP3) inflammasome inhibitor (CY-09) exhibit better efficiency in ameliorating myocardial injury and heart failure induced by surgically induced I/R. These findings indicate a simple production of targeting-ligand free NPs, and demonstrate their potential therapeutic applications for preclinical I/R-induced cardiac injury amelioration.Peer reviewe

Promoting Cardiac Repair through Simple Engineering of Nanoparticles with Exclusive Targeting Capability toward Myocardial Reperfusion Injury by Thermal Resistant Microfluidic Platform

Nanoparticle (NP)-based intravenous administration represents the most convenient cardiac targeting delivery routine, yet, there are still therapeutic issues due to the lack of targeting efficiency and specificity. Active targeting methods using functionalization of ligands onto the NPs' surface may be limited by trivial modification procedures and reduced targeting yield in vivo. Here, a microfluidics assisted single step, green synthesis method is introduced for producing targeting ligands free heart homing NPs in a tailored manner. The generated beta-glucan-based NPs exhibit precise and efficient targeting capability toward Dectin-1(+) monocytes/macrophages, which are confirmed as main pathogenesis mediators for cardiac ischemic/reperfusion (I/R) injury, with a sequentially enhanced cardiac NP accumulation, and this targeting strategy is exclusively suitable for cardiac I/R but not for other cardiovascular diseases, as confirmed both in murine and human model. Comparing to FDA-approved nano-micelles formulation, beta-glucan NPs loaded with NACHT, LRR, and PYD domains-containing protein 3 (NLRP3) inflammasome inhibitor (CY-09) exhibit better efficiency in ameliorating myocardial injury and heart failure induced by surgically induced I/R. These findings indicate a simple production of targeting-ligand free NPs, and demonstrate their potential therapeutic applications for preclinical I/R-induced cardiac injury amelioration.Peer reviewe