Imaging Technology Research Articles

Usefulness of combined pseudo-continuous arterial spin labelling and spectroscopic analysis in schizophrenic Egyptian population sample

BackgroundSchizophrenia is a prevalent psychiatric disorder that affects 1% of the global population. Schizophrenia frequently begins in late adolescence or early adulthood, causing significant educational, social, and economic costs for people and society. Functional neuroimaging research on schizophrenia physiopathology has been beneficial. Arterial spin labelling (ASL) is one of functional magnetic resonance imaging (fMRI) technologies that assess brain function without radiation. ASL uses magnetic resonance (MR) imaging to quantify tissue-level brain perfusion non-invasively. Arterial spin labelling (ASL) is one of the functional magnetic resonance imaging (fMRI) technologies that assess the brain function without radiation hazards. ASL uses magnetic resonance (MR) imaging to quantify tissue-level brain perfusion non-invasively. Many publications were performed on role of different advanced MRI techniques in schizophrenia, but our study insisted on the added value of combined ASL and MRS over the conventional MRI in schizophrenic Egyptian population sample.Aim of the workThe purpose of this work was to evaluate the added value of combined ASL-perfusion MRI and MRS in schizophrenic patients.MethodsThis prospective case–control study was carried out on two groups: First group was 30 patients who were diagnosed clinically as schizophrenic patients, and second group was 20 healthy volunteers as a control group for comparison in the period from August 2021 till July 2022.ResultsThe majority of newly diagnosed cases had significant higher positive symptoms than chronic cases. According to arterial spin labelling (ASL) data, rCBF was noticed to be reduced in anterior cingulate, frontal lobe, and parietal lobe of both patients’ subgroups but more significant in chronically ill patients. Convergent results of decreased rCBF were also found in the parietal lobe and occipital lobe. Magnetic resonance spectroscopic analysis showed that NAA was decreased in the anterior cingulate cortex, thalami and basal ganglia of the newly diagnosed cases more than chronic cases. The ASL-MRI perfusion accurately detected the hypo-perfusion of different brain regions with sensitivity 100%, specificity 66.67%, positive predictive value 96.43%, negative predictive value 100%, and accuracy 96.67%, while MR spectroscopy showed sensitivity 100%, specificity 33.33%, positive predictive value 93.10%, negative predictive value 100%, and accuracy 93.33% in evaluation of changes of brain metabolites.ConclusionASL is a promising functional MRI technique that can produce together with MRS quantitative information about the metabolites of different brain regions. The ASL-MRI appears as a reliable non-invasive technique to measure cerebral blood flow and identify decreased rCBF without any contrast administration, and it could be repeatable which helps in early diagnosis as well as follow-up of the progression of the disease.

Intracranial meningioma: A review of recent and emerging data on the utility of preoperative imaging for management.

Meningiomas are the most common neoplasms of the central nervous system, accounting for approximately 40% of all brain tumors. Surgical resection represents the mainstay of management for symptomatic lesions. Preoperative planning is largely informed by neuroimaging, which allows for evaluation of anatomy, degree of parenchymal invasion, and extent of peritumoral edema. Recent advances in imaging technology have expanded the purview of neuroradiologists, who play an increasingly important role in meningioma diagnosis and management. Tumor vascularity can now be determined using arterial spin labeling and dynamic susceptibility contrast-enhanced sequences, allowing the neurosurgeon or neurointerventionalist to assess patient candidacy for preoperative embolization. Meningioma consistency can be inferred based on signal intensity; emerging machine learning technologies may soon allow radiologists to predict consistency long before the patient enters the operating room. Perfusion imaging coupled with magnetic resonance spectroscopy can be used to distinguish meningiomas from malignant meningioma mimics. In this comprehensive review, we describe key features of meningiomas that can be established through neuroimaging, including size, location, vascularity, consistency, and, in some cases, histologic grade. We also summarize the role of advanced imaging techniques, including magnetic resonance perfusion and spectroscopy, for the preoperative evaluation of meningiomas. In addition, we describe the potential impact of emerging technologies, such as artificial intelligence and machine learning, on meningioma diagnosis and management. A strong foundation of knowledge in the latest meningioma imaging techniques will allow the neuroradiologist to help optimize preoperative planning and improve patient outcomes.

Labeling selectivity of lipid droplets fluorescent probes: Twisted intramolecular charge transfer (TICT) vs intramolecular charge transfer (ICT)

Fluorescence imaging technology is a versatile and essential tool in the field of biomedical research. To obtain excellent imaging results, the precise labeling of fluorescent probes is an important prerequisite. Nevertheless, the labeling selectivity of most fluorescent probes is not satisfactory, new design concepts are desperately needed. In this context, two isomeric lipid droplets (LDs) fluorescent probes Lipi-Cz-1 and Lipi-Cz-2 have been sophisticatedly developed with TICT and ICT-emitting characteristic, respectively. The more environmentally sensitive TICT-emitting Lipi-Cz-1 exhibits a significantly enhanced labeling selectivity in LDs imaging compared to the ICT-emitting Lipi-Cz-2, sufficiently illustrating the effectiveness of TICT-emitting characteristic in improving labeling selectivity. Additionally, Lipi-Cz-1 displays high photostability and biocompatibility. These advantages enable Lipi-Cz-1 to be finely applied in multimode fluorescence imaging, e.g. time-lapse 3D confocal imaging to monitor changes of the number and size of LDs during starvation, two-photon 3D imaging to compare the variations of LDs in various liver tissues, and STED super-resolution imaging to visualize the nanoscale LDs with the resolution of 65 nm. Overall, these imaging findings validate the effectiveness of the new strategy for improving the labeling selectivity.

Deep learning ensemble approach with explainable AI for lung and colon cancer classification using advanced hyperparameter tuning

Lung and colon cancers are leading contributors to cancer-related fatalities globally, distinguished by unique histopathological traits discernible through medical imaging. Effective classification of these cancers is critical for accurate diagnosis and treatment. This study addresses critical challenges in the diagnostic imaging of lung and colon cancers, which are among the leading causes of cancer-related deaths worldwide. Recognizing the limitations of existing diagnostic methods, which often suffer from overfitting and poor generalizability, our research introduces a novel deep learning framework that synergistically combines the Xception and MobileNet architectures. This innovative ensemble model aims to enhance feature extraction, improve model robustness, and reduce overfitting.Our methodology involves training the hybrid model on a comprehensive dataset of histopathological images, followed by validation against a balanced test set. The results demonstrate an impressive classification accuracy of 99.44%, with perfect precision and recall in identifying certain cancerous and non-cancerous tissues, marking a significant improvement over traditional approach.The practical implications of these findings are profound. By integrating Gradient-weighted Class Activation Mapping (Grad-CAM), the model offers enhanced interpretability, allowing clinicians to visualize the diagnostic reasoning process. This transparency is vital for clinical acceptance and enables more personalized, accurate treatment planning. Our study not only pushes the boundaries of medical imaging technology but also sets the stage for future research aimed at expanding these techniques to other types of cancer diagnostics.

Polyfunctional Arylamine Based Nanofiltration Membranes with Enhanced Aggressive Organic Solvents Resistance.

Organic solvent nanofiltration (OSN) membranes with high separation performance and excellent stability in aggressive organic solvents are urgently desired for chemical separation. Herein, we utilized a polyfunctional arylamine tetra-(4-aminophenyl) ethylene (TAPE) to prepare a highly cross-linked polyamide membrane with a low molecular weight cut-off (MWCO) of 312 Da. Owing to its propeller-like conformation, TAPE formed micropores within the polyamide membrane and provided fast solvent transport channels. Importantly, the rigid conjugated skeleton and high connectivity between micropores effectively prevented the expansion of the polyamide matrix in aggressive organic solvents. The membrane maintained high separation performance even immersed in N,N-dimethylformamide for 90 days. Based on the aggregation-induced emission (AIE) effect of TAPE, the formation of polyamide membrane can be visually monitored by fluorescence imaging technology, which achieved visual guidance for membrane fabrication. This work provides a vital foundation for utilizing polyfunctional monomers in the interfacial polymerization reaction to prepare high-performance OSN membranes.

The Role of Cone Beam Computed Tomography (CBCT) in the Diagnosis and Clinical Management of Medication-Related Osteonecrosis of the Jaw (MRONJ)

Medication-related osteonecrosis of the jaw (MRONJ) is a debilitating condition associated with antiresorptive and antiangiogenic medications that are frequently used in treating osteoporosis and cancers. With the ability to produce high-resolution images with a lower radiation dose, cone beam computed tomography (CBCT) is an emerging technology in maxillofacial imaging that offers several advantages in evaluating MRONJ. This review aims to summarise the radiological features of MRONJ as observed via CBCT and highlight its advantages over two-dimensional plain films in assessing MRONJ. CBCT has the capability to detect early MRONJ lesions, characterise the extent and nature of lesions, distinguish MRONJ from other osseous pathologies, and assist in treatment planning. By leveraging the advantages of CBCT, clinicians can enhance their understanding of MRONJ, improve decision making, and ultimately optimize patient care.

Crucial future observations and directions for unveiling magnetopause dynamics and their geospace impacts

The dynamics of Earth’s magnetopause, driven by several different external/internal physical processes, plays a major role in the geospace energy budget. Given magnetopause motion couples across many space plasma regions, numerous forms of observations may provide valuable information in understanding these dynamics and their impacts. In-situ multi-point spacecraft measurements measure the local plasma environment, dynamics and processes; with upcoming swarms providing the possibility of improved spatiotemporal reconstruction of dynamical phenomena, and multi-mission conjunctions advancing understanding of the “mesoscale” coupling across the geospace “system of systems.” Soft X-ray imaging of the magnetopause should enable boundary motion to be directly remote sensed for the first time. Indirect remote sensing capabilities might be enabled through the field-aligned currents associated with disturbances to the magnetopause; by harnessing data from satellite mega-constellations in low-Earth orbit, and taking advantage of upgraded auroral imaging and ionospheric radar technology. Finally, increased numbers of closely-spaced ground magnetometers in both hemispheres may help discriminate between high-latitude processes in what has previously been a “zone of confusion.” Bringing together these multiple modes of observations for studying magnetopause dynamics is crucial. These may also be aided by advanced data processing techniques, such as physics-based inversions and machine learning methods, along with comparisons to increasingly sophisticated geospace assimilative models and simulations.

Reliable Stenosis Detection Based on Thrill Waveform Analysis Using Non-Contact Arteriovenous Fistula Imaging

Hemodialysis therapy is an extracorporeal circulation treatment that serves as a substitute for renal function. In Japan, patients receive this efficient four-hour treatment, three times per week, allowing them to maintain a social life nearly equivalent to that of healthy individuals. Before the treatment, two punctures are performed to establish extracorporeal circulation, and a high blood flow rate is essential to ensure efficient therapy. Specialized blood vessels created through arteriovenous fistula (AVF) surgery are utilized to achieve high blood flow rates. Although the AVF allows safe and efficient dialysis treatment, AVF stenosis leads to a serious problem in dialysis. To early detect this abnormal blood flow, auscultation and palpation methods are widely used in hospitals. However, these methods can only provide qualitative judgment of the AVF condition, so the results cannot be shared among other doctors and staff. Additionally, since the conventional methods require contact with the skin, some issues require consideration regarding infection and low reproducibility. In our previous study, we proposed an alternative method for auscultation using non-contact optical imaging technology. This study aims to construct a reliable AVF stenosis detection method using Thrill waveform analysis based on the developed non-contact device to solve the problem with the contact palpation method. This paper demonstrates the performance validation of the non-contact imaging in the normal AVF group (206 total data, 75 patients, mean age: 69.1 years) and in the treatable stenosis group (107 total data, 17 patients, mean age: 70.1 years). The experimental results of the Mann–Whitney U test showed a significant difference (p=0.0002) between the normal and abnormal groups, which indicated the effectiveness of the proposed method as a new possible alternative to palpation.

Optical and scintillation properties of 2D-(BA)2PbBr4 needle-shaped crystals

In this study, we examine the impact of optical and scintillation properties on needle-shaped bis(butylammonium) lead bromide [(BA)2PbBr4] crystals (average length of 12.7 mm and average width of 1.3 mm), considering different growth methods and dimensions. Needle-shaped crystals with a length-to-width aspect ratio greater than 10 are essential for cutting-edge radiation imaging technology. Through X-ray diffraction characterization, we observe lattice expansion in the needle-shaped crystals compared to previous single crystals. This expansion leads to a stronger overlap between absorption and photoluminescence (PL) spectra, resulting in a smaller Stokes shift of 26 meV. Time-resolved PL analysis reveals a fast decay component of 0.8 ns, which is 68 % faster than the previously reported best value of 2.0 ns, with an average decay time of 3.6 ns, 48 % faster than the best reported value of 7.0 ns. Although our measured sample exhibits a comparatively low light yield (LY) of 7.8 ph/keV due to strong self-absorption, the best energy resolution is observed with a value of 11.5 %, similar to the best reported value of 10.9 %. Despite this, the LY is notably superior to that of previously reported benzylammonium lead bromide [(BZA)2PbBr4] crystals (3.7 ph/keV). Additionally, scintillation decay shows a fast component of 9.4 ns and an average decay time of 119 ns. These characteristics make two-dimensional-(BA)2PbBr4 needle-shaped crystals promising candidates for cost-effective and scalable applications in radiation imaging technology.

Intraoperative margin assessment during radical prostatectomy: is microscopy frozen in time or ready for digital defrost?

Intraoperative frozen section (IFS) is used with the intention to improve functional and oncological outcomes for patients undergoing radical prostatectomy (RP). High resource requirements of IFS techniques such as NeuroSAFE may preclude widespread adoption, even if there are benefits to patients. Recent advances in fresh-tissue microscopic digital imaging technologies may offer an attractive alternative, and there is a growing body of evidence regarding these technologies. In this narrative review, we discuss some of the familiar limitations of IFS and compare these to the attractive counterpoints of modern digital imaging technologies such as the speed and ease of image generation, the locality of equipment within (or near) the operating room, the ability to maintain tissue integrity, and digital transfer of images. Confocal laser microscopy (CLM) is the modality most frequently reported in the literature for margin assessment during RP. We discuss several imitations and obstacles to widespread dissemination of digital imaging technologies. Among these, we consider how the 'en-face' margin perspective will challenge urologists and pathologists to understand afresh the meaning of positive margin significance. As a part of this, discussions on how to describe, categorize, react to, and evaluate these technologies are needed to improve patient outcomes. Limitations of this review include its narrative structure and that the evidence base in this field is relatively immature but developing at pace.

The impact of peri-procedural imaging on safety and efficacy of atrial fibrillation ablation: insights from the Israeli AF Catheter Ablation Registry (ICAR).

Pulmonary vein isolation (PVI) is the most effective therapy to achieve rhythm control in atrial fibrillation (AF). Peri-procedural imaging is used in many but not all centers. However, the impact of imaging on safety and efficacy of PVI is not clear. The Israeli Catheter Ablation Registry (ICAR) is a great opportunity to explore this issue in real-world practice. To describe the real-world utilization of peri-procedural imaging technologies in a large cohort of patients undergoing ablation for AF. A prospective-multicenter cohort of AF patients who underwent PVI during the years 2019-2021. Peri-procedural imaging (CT, ICE, TEE) was utilized based on the center and operator discretion. The study endpoints were peri-procedural complications and AF recurrence at 12months follow-up among patients with and without peri-procedural imaging. Between January 2019 and December 2021, a total of 921 patients underwent PVI. Peri-procedural imaging (at least 1 modality of CT, TEE, and or ICE) was utilized in 753 (81.8%) and no imaging among 168 (18.2%) patients. Cryoablation was the dominant energy used for PVI in both groups (92.3% of the non-imaging group, and 95.3% among imaging group), while RF was used in the rest of the patients. Fluoroscopy time was not different between the 2 groups; however, procedure duration was longer among the imaging group (90min) compared to the non-imaging group (74.5min, p = 0.006). By 12months, the incidence of AF recurrence and repeated ablation were not different between the groups. Complications and re-hospitalization for cardiocerebrovascular reasons were not different among the 2 groups. Cox regression model demonstrated no association between preprocedural imaging and the risk of AF recurrence after ablation. This real-world multicenter prospective registry study demonstrated that the rate of complications and the rate of recurrence of AF during 1year follow-up were not different among patients who had PVI either with or without peri-procedural imaging.

Anomalous Electroluminescence Characteristics of Perovskite Modules.

Spatially resolved photoluminescence (PL) and electroluminescence (EL) imaging technologies play a crucial role in evaluating the performance and stability of photovoltaic devices. However, their application in perovskite devices presents unique challenges. In this study, we report a discrepancy between the electrical performance of perovskite solar modules (PSMs) and the EL images. Following the application of a reverse bias voltage, we observed an increase in EL brightness associated with prolonged carrier lifetime and transport length. Furthermore, cross-sectional Kelvin probe force microscopy identified a significant potential increase primarily at the electron-transport layer (ETL) side after reverse bias, suggesting the presence of defective ETL/perovskite interfaces with filled hole traps. To address this EL mismatch, we proposed a mild reverse current recovery method aimed at aligning EL images with the cell performance without compromising device efficiency. This approach effectively mitigates discrepancies, ensuring alignment between the device performance and EL imaging. Our study underscores that caution is required when utilizing EL imaging to monitor spatial homogeneity in PSMs for future industrial production.

Multi-Scale X-Ray Imaging Technologies for Rechargeable Batteries

Multi-Scale X-Ray Imaging Technologies for Rechargeable Batteries

Asymptotic multilayer pooled transformer based strategy for medical assistance in developing countries

With the continuous progress of medical imaging technology, pathology images have become an important basis for doctors to judge the condition. However, pathology images have problems such as large numbers, large sizes, and complex backgrounds, which make the task of manual recognition exceptionally difficult. The use of computer-aided diagnosis technology can improve the diagnostic accuracy of medical image recognition. Transformer model-based methods have made great progress in the field of medical image recognition, but the self-attention mechanism in them has high computational complexity. Although single-layer pooling can reduce the computational cost, the strategy is prone to feature loss, and too many self-attention operations can exacerbate the distraction problem. Based on this, this study proposes an asymptotic multilayer pooling transformer-based pathology image assistance strategy in medical decision-making systems. First, we pre-process the pathology images with denoising and enhancement to accurately capture the detailed features of the lesion region. Then the asymptotic multilayer pooling transformer pyramid structure (PMPSNet) is used to identify cell nuclei. In the self-focused module, a multilayer pooling operation is employed to simplify the sequence and efficiently capture contextual features. In addition, the strategy utilizes a pyramid encoder to obtain multi-scale feature maps and a novel multilayer perceptual structure to limit the attention interference problem. The results show that our proposed PMPSNet-L model achieves a DSC value of 0.822, which is about 1.4 % better than the second-ranked model, and the IoU value reaches up to 0.702. In addition, our PMPSNet-S maintains a relatively lightweight parameter size of about 14.49 million, which is considerably lower than the existing segmentation models. Our proposed method not only achieves higher segmentation accuracy but also has fewer model parameters and lower computational complexity.

Evaluation of radiofrequency identification tag accuracy using bronchoscopy with fluoroscopy and virtual navigation guidance before segmentectomy.

The use of sublobar resection has increased with advances in imaging technologies. However, it is difficult for thoracic surgeons to identify small lung tumours intraoperatively. Radiofrequency identification (RFID) lung-marking systems are useful for overcoming this difficulty; however, accurate placement is essential for maximum effectiveness. We retrospectively reviewed patients who underwent RFID tag placement via fluoroscopic bronchoscopy under virtual bronchoscopic navigation (VBN) guidance before our institution's sublobar resection of lung lesions. Thirty-one patients with 31 lung lesions underwent RFID lung-marking with fluoroscopic bronchoscopy under VBN guidance. Of the 31 procedures, 26 tags were placed within 10mm of the target site, 2 were placed more than 10mm away from the target site, and 3 were placed in a different area from the target bronchus. No clinical complications were associated with RFID tag placement, such as pneumothorax or bleeding. The contribution of the RFID lung-marking system to surgery was high, particularly when the RFID tag was placed at the target site and tumour was located in the intermediate hilar zone. An RFID tag can be placed near the target site using fluoroscopic bronchoscopy in combination with VBN guidance. RFID tag placement under fluoroscopic bronchoscopy with VBN guidance is useful for certain segmentectomies.

High-Performance Metabolic Profiling of High-Risk Thyroid Nodules by ZrMOF Hybrids.

Thyroid nodules (TNs) have emerged as the most prevalent endocrine disorder in China. Fine-needle aspiration (FNA) remains the standard diagnostic method for assessing TN malignancy, although a majority of FNA results indicate benign conditions. Balancing diagnostic accuracy while mitigating overdiagnosis in patients with benign nodules poses a significant clinical challenge. Precise, noninvasive, and high-throughput screening methods for high-risk TN diagnosis are highly desired but remain less explored. Developing such approaches can improve the accuracy of noninvasive methods like ultrasound imaging and reduce overdiagnosis of benign nodule patients caused by invasive procedures. Herein, we investigate the application of gold-doped zirconium-based metal-organic framework (ZrMOF/Au) nanostructures for metabolic profiling of thyroid diseases. This approach enables the efficient extraction of urine metabolite fingerprints with high throughput, low background noise, and reproducibility. Utilizing partial least-squares discriminant analysis and four machine learning models, including neural network (NN), random forest (RF), logistic regression (LR), and support vector machine (SVM), we achieved an enhanced diagnostic accuracy (98.6%) for discriminating thyroid cancer (TC) from low-risk TNs by using a diagnostic panel. Through the analysis of metabolic differences, potential pathway changes between benign nodule and malignancy are identified. This work explores the potential of rapid thyroid disease screening using the ZrMOF/Au-assisted LDI-MS platform, providing a potential method for noninvasive screening of thyroid malignant tumors. Integrating this approach with imaging technologies such as ultrasound can enhance the reliability of noninvasive diagnostic methods for malignant tumor screening, helping to prevent unnecessary invasive procedures and reducing the risk of overdiagnosis and overtreatment in patients with benign nodules.

Three-dimensional quantitative characterization of defects in inconel 625 superalloy based on deep learning image identification

Three-dimensional (3D) quantitative characterization of defects in superalloys is an important way to promote the ability of material design and service life prediction. In this work, 3D spatial distribution of defects for Inconel 625 superalloy manufactured by laser additive manufacturing (LAM) is carried out deep learning (DL) image identification technology and 3D image reconstruction. Firstly, computer tomography (CT) technology was used to obtain continuous slice images of sample. The U-net DL algorithm was applied to intelligently identify material defects in the continuous slices. On this basis, quantitative identification and analysis of spatial defect positions and typical sizes is achieved by using 3D reconstruction software. Compared with traditional threshold segmentation (TS) techniques, the defect recognition rate has significantly improved from 61.90 ​% to 95.00 ​%. This work provides a promising characterization method for efficient characterizing alloy defects and damage especially during material performance evaluation.

Role of green and sustainable practices in shaping the future of medical imaging technology: A cross-sectional multi-stakeholder analysis among students, radiographers, and academic experts

IntroductionThe detection and treatment of diseases like COVID, diabetes, cancer, cardiovascular conditions, etc., have made medical imaging technology more necessary, so it is expected that the demands of imaging modalities are also increasing and are major contributors to carbon emissions in the healthcare industry. Hence, the Radiology departments, like the rest of the healthcare industry should adapt the procedures to become more sustainable. MethodsA total of 1016 respondents completed the online survey to assess the perception, current practices, and challenges in adopting green and sustainable practices in medical imaging. The radio technologists, teaching faculties, and students of medical imaging were recruited for the study. The survey tool was distributed to the closed groups through social media and emails. ResultsThe majority of participants (66.6%) highlighted the importance of green and sustainable practices in medical imaging whereas only 21.06% of participants seem to have implemented these practices. Most of the participants give positive responses on the use of zero-lead aprons (77%), refurbished medical systems (85.8%), and eco-friendly packaging (89.5%). The mixed response was received from waste segregation and energy-saving measures. The majority (60.3%) of them have no formal education or training. However, they have a good attitude towards the willingness to adopt green practices. ConclusionsThere is a gap between perception and implementation of green and sustainable practices due to leadership and information barriers. Comprehensive training for stakeholders of medical imaging is crucial to fully integrate sustainability practices, possibly through webinars or educational modules. Implications for practiceThe study's findings shed light on how important medical imaging stakeholders view green and sustainable practices as well as potential obstacles to their implementation at the local level whilst suggesting the need for exclusive training on these practices to promote sustainability.

Study on the microscopic characteristics of pentanol/highly active fuel spray based on high-speed droplet tracking velocimetry technology

Pentanol blending with highly reactive fuels for internal combustion engines holds considerable promise. The atomization of sprays closely influences the efficiency and combustion characteristics of the system. Based on Particle Tracking Velocimetry and high-speed shadow imaging technology, we propose a method termed High-speed Droplet Tracking Velocimetry for analyzing spray particle size. Prior to conducting our study, we validated the reliability of High-speed Droplet Tracking Velocimetry through comparisons with the Malvern and Phase Doppler methods. This study utilized long working distance micro high-speed shadow imaging technology in a visualized constant volume combustion chamber to investigate the spray micro-characteristics of pentanol blended with highly reactive fuels, including Fatty Acid Methyl Ester, Hydrogenated Catalytic Biodiesel, and Diesel. The results indicate that under all operating conditions, the droplets of P20H80 (the volume fraction of 20 % n-pentanol mixed with 80 % Hydrogenated Catalytic Biodiesel) are smaller and more uniformly distributed, demonstrating the minimum Sauter Mean Diameter, characteristic diameter, and width of droplet size distribution. The droplet velocities of P20H80 are the lowest, followed by P20Di80 (the volume fraction of 20 % n-pentanol mixed with 80 % Diesel), while P20B80 (the volume fraction of 20 % n-pentanol mixed with 80 % Fatty Acid Methyl Ester) exhibits the highest velocities. These velocity differences among the three fuels generally remain within 10 %-20 % across various injection pressures. P20Di80 shows the highest Reynolds and Weber numbers, followed by P20H80, with P20B80 having the smallest values due to its intermediate physical properties. The gaps between each fuel type range from 20 % to 30 %.

Towards an ultrafast 3D imaging scanning LiDAR system: a review

Light detection and ranging (LiDAR), as a hot imaging technology in both industry and academia, has undergone rapid innovation and evolution. The current mainstream direction is towards system miniaturization and integration. There are many metrics that can be used to evaluate the performance of a LiDAR system, such as lateral resolution, ranging accuracy, stability, size, and price. Until recently, with the continuous enrichment of LiDAR application scenarios, the pursuit of imaging speed has attracted tremendous research interest. Particularly, for autonomous vehicles running on motorways or industrial automation applications, the imaging speed of LiDAR systems is a critical bottleneck. In this review, we will focus on discussing the upper speed limit of the LiDAR system. Based on the working mechanism, the limitation of optical parts on the maximum imaging speed is analyzed. The beam scanner has the greatest impact on imaging speed. We provide the working principle of current popular beam scanners used in LiDAR systems and summarize the main constraints on the scanning speed. Especially, we highlight the spectral scanning LiDAR as a new paradigm of ultrafast LiDAR. Additionally, to further improve the imaging speed, we then review the parallel detection methods, which include multiple-detector schemes and multiplexing technologies. Furthermore, we summarize the LiDAR systems with the fastest point acquisition rate reported nowadays. In the outlook, we address the current technical challenges for ultrafast LiDAR systems from different aspects and give a brief analysis of the feasibility of different approaches.