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

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

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

Monetary incentives and peer referral in promoting secondary distribution of HIV self-testing among men who have sex with men in China: A randomized controlled trial

Background Digital network–based methods may enhance peer distribution of HIV self-testing (HIVST) kits, but interventions that can optimize this approach are needed. We aimed to assess whether monetary incentives and peer referral could improve a secondary distribution program for HIVST among men who have sex with men (MSM) in China. Methods and findings Between October 21, 2019 and September 14, 2020, a 3-arm randomized controlled, single-blinded trial was conducted online among 309 individuals (defined as index participants) who were assigned male at birth, aged 18 years or older, ever had male-to-male sex, willing to order HIVST kits online, and consented to take surveys online. We randomly assigned index participants into one of the 3 arms: (1) standard secondary distribution (control) group (n = 102); (2) secondary distribution with monetary incentives (SD-M) group (n = 103); and (3) secondary distribution with monetary incentives plus peer referral (SD-M-PR) group (n = 104). Index participants in 3 groups were encouraged to order HIVST kits online and distribute to members within their social networks. Members who received kits directly from index participants or through peer referral links from index MSM were defined as alters. Index participants in the 2 intervention groups could receive a fixed incentive ($3 USD) online for the verified test result uploaded to the digital platform by each unique alter. Index participants in the SD-M-PR group could additionally have a personalized peer referral link for alters to order kits online. Both index participants and alters needed to pay a refundable deposit ($15 USD) for ordering a kit. All index participants were assigned an online 3-month follow-up survey after ordering kits. The primary outcomes were the mean number of alters motivated by index participants in each arm and the mean number of newly tested alters motivated by index participants in each arm. These were assessed using zero-inflated negative binomial regression to determine the group differences in the mean number of alters and the mean number of newly tested alters motivated by index participants. Analyses were performed on an intention-to-treat basis. We also conducted an economic evaluation using microcosting from a health provider perspective with a 3-month time horizon. The mean number of unique tested alters motivated by index participants was 0.57 ± 0.96 (mean ± standard deviation [SD]) in the control group, compared with 0.98 ± 1.38 in the SD-M group (mean difference [MD] = 0.41),and 1.78 ± 2.05 in the SD-M-PR group (MD = 1.21). The mean number of newly tested alters motivated by index participants was 0.16 ± 0.39 (mean ± SD) in the control group, compared with 0.41 ± 0.73 in the SD-M group (MD = 0.25) and 0.57 ± 0.91 in the SD-M-PR group (MD = 0.41), respectively. Results indicated that index participants in intervention arms were more likely to motivate unique tested alters (control versus SD-M: incidence rate ratio [IRR = 2.98, 95% CI = 1.82 to 4.89, p-value < 0.001; control versus SD-M-PR: IRR = 3.26, 95% CI = 2.29 to 4.63, p-value < 0.001) and newly tested alters (control versus SD-M: IRR = 4.22, 95% CI = 1.93 to 9.23, p-value < 0.001; control versus SD-M-PR: IRR = 3.49, 95% CI = 1.92 to 6.37, p-value < 0.001) to conduct HIVST. The proportion of newly tested testers among alters was 28% in the control group, 42% in the SD-M group, and 32% in the SD-M-PR group. A total of 18 testers (3 index participants and 15 alters) tested as HIV positive, and the HIV reactive rates for alters were similar between the 3 groups. The total costs were $19,485.97 for 794 testers, including 450 index participants and 344 alter testers. Overall, the average cost per tester was$24.54, and the average cost per alter tester was $56.65. Monetary incentives alone (SD-M group) were more cost-effective than monetary incentives with peer referral (SD-M-PR group) on average in terms of alters tested and newly tested alters, despite SD-M-PR having larger effects. Compared to the control group, the cost for one more alter tester in the SD-M group was$14.90 and $16.61 in the SD-M-PR group. For newly tested alters, the cost of one more alter in the SD-M group was$24.65 and $49.07 in the SD-M-PR group. No study-related adverse events were reported during the study. Limitations include the digital network approach might neglect individuals who lack internet access. Conclusions Monetary incentives alone and the combined intervention of monetary incentives and peer referral can promote the secondary distribution of HIVST among MSM. Monetary incentives can also expand HIV testing by encouraging first-time testing through secondary distribution by MSM. This social network–based digital approach can be expanded to other public health research, especially in the era of the Coronavirus Disease 2019 (COVID-19). Trial registration Chinese Clinical Trial Registry (ChiCTR) ChiCTR190002543