Capture Method Research Articles

Application of Reciprocity Principle in Ultrasound Bone Tomography

Abstract Full-matrix synthetic aperture imaging (FMSA) is a well-established and widely used modality for ultrasound imaging Nevertheless, the accompanying relatively large amount of data acquisition, storage, and process results in heavy costs of computation and memory, which further hinders FMSA from real-time implementation. Moreover, the most existing FMSAs employed the hypothesis uniform sound velocity to reconstruct the soft tissues, which is not suitable for hard tissue imaging, irrespective of the high acoustic impedance contrast (i.e., the difference of sound velocity) between the bone and soft tissues. To overcome these limitations, a half-matrix ultrasound bone tomography method combining the reciprocity principle and sound velocity estimation was proposed for cortical cross-section imaging. The travel-time inversion was firstly utilized for sound velocity prediction, and then half-matrix synthetic aperture (HMSA) with ray-tracing was conducted to image the cortical cross-section. An ex-vivo bovine femur was used to validate the effectiveness of the method. Compared to the full-matrix capture method, the proposed method was demonstrated to be an accurate and cost-effective modality for cortical bone tomography.

Virtual shadow puppet generation based on AlphaPose

This study aims to develop a novel motion capture method utilizing the AlphaPose project to support the production and analysis of shadow puppetry. Through precise capture and analysis of human body postures, we seek to enhance the performance quality of shadow puppetry, introducing modern technology to this ancient Chinese intangible cultural heritage art form, thereby facilitating its inheritance and development. This paper provides an introduction to the background and significance of the research, explores existing issues and shortcomings, and provides a detailed description of our methodology and the improvements achieved.

Influence of the stratification parameters on the wake field of an underwater vehicle in a two-layer stratified flow

Because the ocean exhibits different stratification states in different seasons and regions, the effect of different stratification parameters on a submarine wake must be studied. In particular, to investigate such effect in a two-layer stratified flow, this study established a computational fluid dynamics (CFD) model based on the URANS equations, shear-stress transport (SST) k-ω turbulence model, and Eulerian multiphase flow model. The volume of fluid (VOF) method was adopted to implement the free-surface capture method. The working conditions of the SUBOFF model under an infinite diving depth and near the free surface were compared with those of the experiments, and the convergence of the time step and grid number under stratified flow conditions was verified. These validation steps proved the feasibility of the CFD method. Finally, the effects of the stratification parameters on the free surface waves, internal waves, and turbulent kinetic energy behind the vehicle were observed by varying the stratification parameters to achieve different working conditions. The results show that when an underwater vehicle sails in a two-layer stratified flow, the interstratified density ratio and depth of the internal wave surface affect its wake field. When the underwater vehicle sails in the water layer, with an increase in the interstratified density ratio, the free-surface roughness increases and the turbulent kinetic energy decreases. When the underwater vehicle sails in the salt water layer, the result is just the opposite.

Historical Account of Managing Overabundant Wild Asian Elephants in Myanmar by the Kheddah System of Capture: Philosophy, Principles and Practices.

When standard methods of human-elephant conflict mitigation are not successful, free-ranging wild elephants may continue to come into close contact with people. This results in more frequent and severe conflict, with consequences ranging from crop raiding to loss of human and elephant lives. Understandably, in such situations, local communities may want to be rid of entire herds of elephants. Historically, one of the strategies the Myanmar Government practiced to resolve human-elephant conflict was the capture of whole herds using the Kheddah system. This involved trapping the herd in a stockade, immediately followed by on-site post-capture taming. After taming, the captured elephants were utilized as logging elephants. Elephants worked in timber extraction, retired at age 55 years and were then cared for by the Government until they died. The capture of wild elephants by the Kheddah system was formally banned in Myanmar in 1985 but occasional, small-scale, captures were allowed until 2013 under the strict control of the Myanmar Government. These operations were aimed primarily at capturing elephants involved in human-elephant conflict, rather than to supplement the working elephant population. One of the last Kheddah operations, organized and managed by the author, was conducted in 1996 at the Taikkyi township of the Yangon Region, as a last resort to end human-elephant conflict in an emergency. While chemical immobilization was being used at this time, it was not logistically possible with the high numbers of elephants engaged in the conflict. This review aims to record the history of an activity that was an important element of Myanmar's timber industry more than three decades ago. In this paper, the author presents a description of Kheddah not to endorse it, but to document (1) the Myanmar elephant population management strategy in the past, before it is forgotten, and (2) the practicality of the Kheddha operation when the singly selected commonly- used immobilization or noosing method of elephant capture is unfeasible. The author attempts to shed light on the modern veterinary procedures that may significantly reduce the notorious historical outcome of Kheddha, especially the resulting mortality of captured elephants, should the Kheddha system of capture ever be used as an emergency solution for ongoing problems of human-elephant conflict in the range states of Asia.

Analysis of emergency resuscitative thoracotomy in the combat setting

IntroductionEmergency resuscitative thoracotomy (ERT) is a resource-intensive procedure that can deplete a combat surgical team’s supply and divert attention from casualties with more survivable injuries. An understanding of survival after...

Antioxidant Activities Of Various Fraction Levels Of Kaik Kaik (Uruparia Multiflora K.Schum. & Lauterb)

Borneo has abundant biodiversity, especially regarding medicinal plants. One of the plants used in traditional medicine by the Dayak tribe in Kalimantan is kaik-kaik (Uncaria cordata (Lour.) Merr.), so research is needed to evaluate the activity of this plant. One of the methods used to assess its medicinal properties is through its antioxidant activity. This research aimed to test the antioxidant activity of various fractions derived from U. cordata stems. The study began with ethanol extraction followed by fractionation using n-hexane, ethyl acetate, and distilled water. The extracts and fractions obtained were then tested for antioxidant activity using the DPPH radical capture method. The results indicated that the n-hexane fraction, with a yield of 0.69%, contains terpenoids/steroids, alkaloids, and flavonoids; the ethyl acetate fraction, with a yield of 1.453%, contains alkaloids and flavonoids; and the distilled water fraction, with a yield of 4.832%, contains saponins, tannins, alkaloids, phenols, and flavonoids. The n-hexane, ethyl acetate, and distilled water fractions exhibited antioxidant capacity with IC₅₀ values of 138.39 ± 0.3777 ppm, 48.51 ± 0.056 ppm, and 36.31 ± 0.111 ppm, respectively. This research concluded that the distilled water fraction was the most active and is classified as a very strong antioxidant.

Laser microdissection system based on structured light modulation dual cutting mode and negative pressure adsorption collection.

Laser microdissection technology is favored by biomedical researchers for its ability to rapidly and accurately isolate target cells and tissues. However, the precision cutting capabilities of existing laser microdissection systems are hindered by limitations in overall mechanical movement accuracy, resulting in suboptimal cutting quality. Additionally, the use of current laser microdissection systems for target acquisition may lead to tissue burns and reduced acquisition rates due to inherent flaws in the capture methods. To address these challenges and achieve precise and efficient separation and capture of cellular tissues, we integrated a digital micromirror device (DMD) into the existing system optics to modulate spatial light. This allows the system to not only implement the traditional point scanning cutting method but also utilize the projection cutting method.We have successfully cut various patterns on commonly used laser microdissection materials such as PET films and mouse tissues. Under projection cutting mode, we were able to achieve precise cutting of special shapes with a diameter of 7.5 micrometers in a single pass, which improved cutting precision and efficiency. Furthermore, we employed a negative pressure adsorption method to efficiently collect target substances. This approach not only resulted in a single-pass capture rate exceeding 90% for targets of different sizes but also enabled simultaneous capture of multiple targets, overcoming the limitations of traditional single-target capture and enhancing target capture efficiency, and avoiding potential tissue damage from lasers.In summary, the integration of the digital micromirror device into laser microdissection systems significantly enhances cutting precision and efficiency, overcoming limitations of traditional systems. This advancement demonstrates the accuracy and effectiveness of laser microdissection systems in isolating and capturing biological tissues, highlighting their potential in medical applications.

CCUS Perspectives: Assessing Historical Contexts, Current Realities, and Future Prospects

CCUS technologies are crucial solutions for mitigating climate change by reducing CO2 emissions from industrial operations and energy sectors. This review critically examines the current state of CCUS technologies, and highlights advancements, challenges, regulatory frameworks, and future directions. It comprehensively analyzes carbon capture methods, such as pre-combustion, post-combustion, and oxy-fuel combustion capture, while comparing their efficiencies and limitations. The review also explores carbon utilization techniques, such as direct and indirect utilization, emphasizing their potential applications and technological constraints. Additionally, it assesses various carbon storage methods, focusing on geological, ocean, and mineralization storage, and discusses their capacity, feasibility, and environmental implications. The study reviews the policy and regulatory frameworks, economic viability, market trends, and environmental sustainability of CCUS. By identifying research gaps and recommending future research priorities, this review aims to guide the development of more efficient/effective, and cost-effective CCUS technology, ensuring their role in a sustaining low-carbon future. This review provides a forward-looking perspective, a critical and interdisciplinary analysis that assesses the current state of CCUS technologies, and further provides a roadmap for future development.

Techno-economic analysis on a hybrid system with carbon capture and energy storage for liquefied natural gas cold energy utilization

For cold energy utilization in the liquefied natural gas (LNG) regasification process, integrated cryogenic CO2 capture using high-grade cold energy is a mainstream method. However, high-grade cold energy for carbon capture may lead to a decrease in cold energy utilization efficiency. This paper aims to propose a hybrid system in which high-grade cold energy is used for liquid air energy storage (LAES) and post-combustion amine scrubbing technology is considered to replace cryogenic carbon capture for improved working efficiency. The medium and low-grade cold energy is utilized for similar working processes, e.g., organic Rankine cycle (ORC), carbon dioxide liquefaction, and data center cooling for comparison. Results show that the proposed hybrid system can produce 437.7 MW of power, 28.8 t·h−1 of CO2 capture capacity, and 23.0 MW of cooling capacity, respectively. The levelized cost of electricity and the annual revenue are 112.3 $·MWh−1 and 2.17 million $, respectively. LNG cold energy utilization efficiency, system energy efficiency, and cold exergy efficiency are 53.4 %, 24.0 %, and 51.5 %, higher than similar processes using cryogenic CO2 capture. It is demonstrated that the proposed system could be a promising method for cold energy utilization and post-combustion capture.

Accuracy of surgical death information: comparison of data held by Victorian Audit of Surgical Mortality and Victorian Agency for Health Information.

The Victorian Audit of Surgical Mortality (VASM) investigates all surgically related deaths in Victoria. The Victorian Admitted Episodes Database (VAED) is an administrative dataset maintained by the Health Department's Victorian Agency of Health Information (VAHI). We have reviewed clinical records to assess the correlation between deaths reported to the databases. Data July 2019 to June 2020 were compared. All hospitals that had surgical deaths not reported to VASM were asked to provide clinical summaries which were analysed to assess the deaths should have been reported. Case note review of 280 deaths only reported to VAHI through VAED was undertaken to establish whether these should have been reported to VASM. VASM received 1763 reported surgical deaths with VAHI recording 1907. Using individual patient identifiers, 517 (29.3%) of the VASM deaths were not reported to VAHI but subsequent data analysis revealed they were correctly identified as reportable deaths in 385 (74.5%). There were 914 (47.9%) VAED recorded deaths that were not reported to VASM. 280/914 (30.6%) were reviewed from 21 hospitals. Only 24 (8.6%) of these had a surgical procedure in the patient's final admission and should have been reported. This suggests that the current method of VASM capture of surgical mortality only missed 4% cases for the 2019/20 year. There were major differences between surgical deaths reported to VASM and those reported by health services and recorded in VAED. Less than 5% of cases are not reported to VASM and thus not subjected to peer review.

Novel amine emissions control methods for CO2 capture based on reducing amine concentration in the scrubbing liquid

Piperazine (PZ) activated 2-amino-2-methyl-1-propanol (AMP) is a high-performance solvent for CO2 capture that has undergone long-term pilot test. This study explores its vapor amine emissions characteristics on Aspen Plus. It was found that the steady-state amine concentration in the water wash (WW) is a crucial factor affecting emissions, determined by the amine-to-water ratio obtained from flue gas and feed water. Under optimized conditions, vapor amine emissions were reduced from 1768 mg/Nm3 after the absorber to 1.46 mg/Nm3 after two WW sections. Two novel amine control methods were proposed based on the approach of lowering the amine concentration in the scrubbing liquid. Staged condensation of the stripper gas provides super low amine (0.06 wt%) feed water to the WW, further reducing vapor amine emissions by an order of magnitude. The Cooling Dry Bed (CDB) can achieve amine emission control effects comparable to two WW sections with only 20 % of the theoretically calculated interfacial area. This process has a lower total packing height and does not require liquid collection trays, significantly reducing the construction height and load of the column.

Application of Reducible Covalent Capture Purification for Resolving Persulfidome and Nucleolin S-Sulfhydration.

Protein S-sulfhydration involves the regulation of various protein functions, and resolving the S-sulfhydrated proteome (persulfidome) allows for a deeper exploration of various redox regulations. Therefore, we designed a reducible covalent capture method for isolating S-sulfhydrated proteins, which can analyze the persulfidome in biological samples and monitor specific S-sulfhydrated proteins. In this study, we applied this method to reveal the S-sulfhydration levels of proteins, including 3-phosphoglyceraldehyde dehydrogenase, NFκB/p65, and nucleolin. Furthermore, this technique can be used to enrich S-sulfhydrated peptides, aiding in the determination of protein S-sulfhydration modification sites. Finally, we observed that the S-sulfhydration and oxidation of nucleolin on the C543 residue correlate with its nuclear translocation, downstream regulation of p53, Bcl-xL, and Bcl-2 RNA levels and protein expression, as well as the protective function against oxidative stress. Therefore, this method may facilitate the understanding of the regulation of protein function by redox perturbation.

Design and workspace analysis of a cable-driven space capture robot for noncooperative targets

Capturing noncooperative targets in space has garnered continuous research interest in aerospace applications. This study addresses the demands of large-scale, multifaceted activities and varied working conditions for space capture missions by designing a space capture robot composed of multiple cable-driven manipulators operating in parallel. First, single- and multi-segment cable-driven robot models were designed, and a geometric model was subsequently built. The optimal number of segments was determined by analysing the condition number of a Jacobian matrix using the Monte Carlo method. Subsequently, based on the constant-curvature assumption, a kinematic model of the cable-driven space capture robot was formulated, and capture methods for different capture targets were designed using the Monte Carlo method. Finally, an eight-segment cable-driven robot prototype was developed, and compliance and driving experiments were conducted. This robot exhibits promising application potential for space noncooperative target capture and can be feasibly manufactured using on-orbit 3D machining technology.

Walking representation and simulation based on multi-source image fusion and multi-agent reinforcement learning for gait rehabilitation

In the formulation of strategies for walking rehabilitation, achieving precise identification of the current state and making rational predictions about the future state are crucial but often unrealized. To tackle this challenge, our study introduces a unified framework that integrates a novel 3D walking motion capture method using multi-source image fusion and a walking rehabilitation simulation approach based on multi-agent reinforcement learning. We found that, (i) the proposal achieved an accurate 3D walking motion capture and outperforms other advanced methods. Experimental evidence indicates that, compared to similar visual skeleton tracking methods, the proposed approach yields results with higher Pearson correlation (r=0.93), intra-class correlation coefficient (ICC(2,1)=0.91), and narrower confidence intervals ([0.90,0.95] for r, [0.88,0.94] for ICC(2,1)) when compared to standard results. The outcomes of the proposed approach also exhibit commendable correlation and concurrence with those obtained through the IMU-based skeleton tracking method in the assessment of gait parameters ([0.85,0.89] for r, [0.75,0.81] for ICC(2,1)); (ii) multi-agent reinforcement learning has the potential to be used to solve the simulation task of gait rehabilitation. In mimicry experiment, our proposed simulation method for gait rehabilitation not only enables the intelligent agent to converge from the initial state to the target state, but also observes evolutionary patterns similar to those observed in clinical practice through motor state resolution. This study offers valuable contributions to walking rehabilitation, enabling precise assessment and simulation-based interventions, with potential implications for clinical practice and patient outcomes.

Specifics of Data Collection and Data Processing during Formation of RailVista Dataset for Machine Learning- and Deep Learning-Based Applications.

This paper presents the methodology and outcomes of creating the Rail Vista dataset, designed for detecting defects on railway tracks using machine and deep learning techniques. The dataset comprises 200,000 high-resolution images categorized into 19 distinct classes covering various railway infrastructure defects. The data collection involved a meticulous process including complex image capture methods, distortion techniques for data enrichment, and secure storage in a data warehouse using efficient binary file formats. This structured dataset facilitates effective training of machine/deep learning models, enhancing automated defect detection systems in railway safety and maintenance applications. The study underscores the critical role of high-quality datasets in advancing machine learning applications within the railway domain, highlighting future prospects for improving safety and reliability through automated recognition technologies.

Single-cell long-read targeted sequencing reveals transcriptional variation in ovarian cancer

Single-cell RNA sequencing predominantly employs short-read sequencing to characterize cell types, states and dynamics; however, it is inadequate for comprehensive characterization of RNA isoforms. Long-read sequencing technologies enable single-cell RNA isoform detection but are hampered by lower throughput and unintended sequencing of artifacts. Here we develop Single-cell Targeted Isoform Long-Read Sequencing (scTaILoR-seq), a hybridization capture method which targets over a thousand genes of interest, improving the median number of on-target transcripts per cell by 29-fold. We use scTaILoR-seq to identify and quantify RNA isoforms from ovarian cancer cell lines and primary tumors, yielding 10,796 single-cell transcriptomes. Using long-read variant calling we reveal associations of expressed single nucleotide variants (SNVs) with alternative transcript structures. Phasing of SNVs across transcripts enables the measurement of allelic imbalance within distinct cell populations. Overall, scTaILoR-seq is a long-read targeted RNA sequencing method and analytical framework for exploring transcriptional variation at single-cell resolution.

One fish, two fish, three fish, more: novel resighting method produces precise and cost-effective estimates of abundance.

Estimates of abundance are essential to manage and conserve marine species. Numerous methods are available to determine population size, but the suitability of methods for schooling fishes and the associated precision can vary depending on the species and system. Here, we developed and compared three mark-recapture/resight methods to assess the most robust method to estimate the abundance of silver trevally (Pseudocaranx georgianus). While the recapture rate was similar across the methods, the swim pass method (resighting) recorded the largest number of individuals (mean ± standard error 211 ± 14.9) and had the lowest coefficient of variation (CV; 4.5%-12%) compared to 360-video (resighting, 45 ± 2.1 individuals surveyed, 14.8%-22.2% CV) and large-scale capture methods (recapture, 30 ± 3.8 individuals surveyed, 17.3%-26.5% CV). The inclusion of individual identification into the abundance estimator models for large-scale capture did not change the abundance estimates and showed similar resolution between the models (CV 18.2%-26.7%). We showed that the swim pass method is logistically easy to implement and generates precise estimates of silver trevally abundance. This new method provides a low-cost, time-efficient resighting method that can be adapted to suit similar aggregating pelagic species interacting with wildlife tourism operations, enabling researchers to rapidly estimate the abundance of species that have been previously difficult to count.

(Invited) Challenges and Opportunities in the Integration of CO2 Capture and Conversion

Over the past 15 years or so, the electroreduction of CO2 for the synthesis of intermediates for the chemical industry as well as for the synthesis of small molecule fuels has become a very active area of research. Activities span the whole value chain from electro-catalyst synthesis and characterization, to electrode and cell design and optimization, as well as studies on techno-economic feasibility and life cycle assessment of envisioned overall processes. In the vast majority of these studies, >98% pure CO2 is being used as the feed. In reality, CO2 feeds captured from industrial flue gasses or even those captured from air may not be close to 100% in CO2.This presentation will explore the integration of a nanomembrane-based CO2 capture method with different CO2 electrolysis approaches. The nano-membrane-based CO2 capture is based on work by Fujikawa and Selyanchyn (Polymer J. 2021, 53, 111), using polydimethylsiloxane-derived membranes that are preferentially permeable to CO2 over nitrogen. Multistage arrangement of modules comprised of arrays of membranes allows for efficient concentration of CO2 from air, from 420 ppm to tens of percent, using just vacuum pumps to drive the process. We explore the use of these concentrated CO2 streams that still contain nitrogen and some oxygen as the feed in subsequent CO2 electrolysis conversions to CO, to methane, or to other products, depending on catalyst choice. We study the effects of feed composition, catalyst chosen, and cell configuration on product speciation, conversion efficiency, etc.

Immobilization of PCET Materials for Electrochemical pH Swing Driven Carbon Capture

Proton-coupled electron transfer (PCET) is a promising method in the realm of carbon capture and release mechanisms. Its fundamental capacity lies in electrochemically inducing pH swings within an aqueous solution, leveraging the high solubility of carbonates in highly alkaline water to capture CO2 and subsequently release iton demand when the aqueous solution is acidified. PCET-based methods promise higher energy efficiency for carbon capture compared to other electrochemical carbon capture methods because they feature fast charge transfer kinetics and can decouple gas-liquid contact and electrochemical activation. In theory, they also allow the use of cheap, widely available small-molecule PCET agents. However, in practice, PCET agents have shown a key limitation that has, thus far, hindered their scalability: oxygen-induced chemical degradation with continued electrochemical cycling. In this work we mitigate the prevailing issue of oxygen sensitivity by immobilizing PCET agents onto a fabric substrate. Via reactive vapor deposition (RVD), porous and conductive films composed of PEDOT-Cl and poly-aminoanthroquinone (PAAQ) are deposited on the surface of a wool felt blend fabric. This approach resulted in the development of a cost-effective, metal-free, and efficient electrode for both capture and release of CO2. Through electrochemical evaluation, the performance of PCET-active quinone moieties present on PAAQ was measured. The overall efficiency of electrochemical capture from gaseous CO2 was found to be 197 kJ/molCO2, substantiating the efficacy of this novel electrode. This work highlights the potential of fabric-immobilized PCET agents and presents a promising avenue towards a sustainable, efficient, and economically viable approach to carbon capture and release technologies.

Multi-layered medium ultrasonic phased array sparse TFM imaging based on self-adaptive differential evolution algorithm

Abstract Multilayer Composite material structures have been widely used in modern engineering fields. However, defects within these materials can adversely affect mechanical properties. Ultrasonic phased array total focusing method (TFM) imaging has advantages of high precision and dynamic focusing over the entire range, achieving significant progress in homogeneous medium detection. However, heavy computational burdens of multilayer structures lead to inefficient imaging. To address this issue, a sparse-TFM imaging algorithm using ultrasonic phased arrays suitable for multilayer media is proposed in this paper. This method constructs a fitness function with constraints such as main lobe width and sidelobe peak. Its objective is to obtain the distribution of sparse array element positions using an self-adaptive differential evolution algorithm. Subsequently, the delay time of each array element in multilayer media sparse TFM is calculated using the root mean square (RMS) principle and combined with amplitude weighting, the method corrects the imaging results. Compared with the Ray-based full-matrix capture and TFM method (Ray-based FMC/TFM), the RMS-based full-matrix capture and TFM (RMS-based FMC/TFM), and the phase shift method, the experimental and simulation results demonstrate that the proposed method significantly reduces the imaging data volume, improves computational efficiency, and maintains quantitative errors within 0.2 mm.