Leading-edge Techniques Research Articles

Cross-correlation adjustment full-waveform inversion with source encoding in ultrasound computed tomography

Full-waveform inversion (FWI) is one of the leading-edge techniques in ultrasound computed tomography (USCT). FWI reconstructs the images of sound speed by iteratively minimizing the difference between the predicted and measured signals. The challenges of FWI are to improve its stability and reduce its computational cost. In this paper, a new USCT algorithm based on cross-correlation adjustment FWI with source encoding (CCAFWI-SE) is proposed. In this algorithm, the gradient is adjusted using the intermediate signals as the inversion target rather than the measured signals during iteration. The intermediate signals are generated using the travel time difference calculated by cross-correlation. In the case of conventional FWI failure, using the proposed algorithm, the estimated sound speed can converge toward the ground truth. To reduce the computational cost, an intermittent update strategy is implemented. This strategy only requires one time for the calculation of the travel time difference per stage, so that the source encoding can be used. Simulation and laboratory experiments are implemented to validate this approach. The experiment results show it has successfully recovered the sound speed model, while conventional FWI failed when the initial model greatly differed from the ground truth. This verifies that our approach improves the stability of the reconstruction in USCT. In practice, additional computational costs can be reduced by combining our approach with existing methods. The proposed approach increases the robustness of the FWI and expands its application.

Fine-tuning a pre-trained ResNet50 model to detect distributed denial of service attack

Distributed denial-of-service (DDoS) attacks pose a significant risk to the dependability and consistency of network services. The utilization of deep learning (DL) models has displayed encouraging outcomes in the identification of DDoS attacks. Nevertheless, crafting a precise DL model necessitates an extensive volume of labeled data and substantial computational capabilities. Within this piece, we introduce a technique to enhance a pre-trained DL model for the identification of DDoS attacks. Our strategy’s efficacy is showcased on an openly accessible dataset, revealing that the fine-tuned model we propose surpasses both the initial pre-trained model and other cutting-edge approaches in performance. The suggested fine-tuned model attained 95.1% accuracy, surpassing the initial pre-trained model as well as other leading-edge techniques. Please note that the specific evaluation metrics and their values may vary depending on the implementation, hyperparameter settings, number of datasets, or dataset characteristics. The proposed approach has several advantages, including reducing the amount of labeled data required and accelerating the training process. Initiating with a pre-existing ResNet50 model can also enhance the eventual model’s accuracy, given that the pre-trained model has already acquired the ability to extract significant features from unprocessed data.

Incidental pathogenic germline alterations detected through liquid biopsy in patients with solid tumors: prevalence, clinical utility and implications.

Liquid biopsy, a minimally invasive approach for detecting tumor biomarkers in blood, has emerged as a leading-edge technique in cancer precision medicine. New evidence has shown that liquid biopsies can incidentally detect pathogenic germline variants (PGVs) associated with cancer predisposition, including in patients with a cancer for which genetic testing is not recommended. The ability to detect these incidental PGV in cancer patients through liquid biopsy raises important questions regarding the management of this information and its clinical implications. This incidental identification of PGVs raises concerns about cancer predisposition and the potential impact on patient management, not only in terms of providing access to treatment based on the tumor molecular profiling, but also the management of revealing genetic predisposition in patients and families. Understanding how to interpret this information is essential to ensure proper decision-making and to optimize cancer treatment and prevention strategies. In this review we provide a comprehensive summary of current evidence of incidental PGVs in cancer predisposition genes identified by liquid biopsy in patients with cancer. We critically review the methodological considerations of liquid biopsy as a tool for germline diagnosis, clinical utility and potential implications for cancer prevention, treatment, and research.

Spatial Transcriptomic and Metabolomic Landscapes of Oral Submucous Fibrosis-Derived Oral Squamous Cell Carcinoma and its Tumor Microenvironment.

In South and Southeast Asia, the habit of chewing betel nuts is prevalent, which leads to oral submucous fibrosis (OSF). OSF is a well-established precancerous lesion, and a portion of OSF cases eventually progress to oral squamous cell carcinoma (OSCC). However, the specific molecular mechanisms underlying the malignant transformation of OSCC from OSF are poorly understood. In this study, the leading-edge techniques of Spatial Transcriptomics (ST) and Spatial Metabolomics (SM) are integrated to obtain spatial location information of cancer cells, fibroblasts, and immune cells, as well as the transcriptomic and metabolomic landscapes in OSF-derived OSCC tissues. This work reveals for the first time that some OSF-derived OSCC cells undergo partial epithelial-mesenchymal transition (pEMT) within the in situ carcinoma (ISC) region, eventually acquiring fibroblast-like phenotypes and participating in collagen deposition. Complex interactions among epithelial cells, fibroblasts, and immune cells in the tumor microenvironment are demonstrated. Most importantly, significant metabolic reprogramming in OSF-derived OSCC, including abnormal polyamine metabolism, potentially playing a pivotal role in promoting tumorigenesis and immune evasion is discovered. The ST and SM data in this study shed new light on deciphering the mechanisms of OSF-derived OSCC. The work also offers invaluable clues for the prevention and treatment of OSCC.

Establishing Hedgehog Gradients during Neural Development.

A morphogen is a signaling molecule that induces specific cellular responses depending on its local concentration. The concept of morphogenic gradients has been a central paradigm of developmental biology for decades. Sonic Hedgehog (Shh) is one of the most important morphogens that displays pleiotropic functions during embryonic development, ranging from neuronal patterning to axon guidance. It is commonly accepted that Shh is distributed in a gradient in several tissues from different origins during development; however, how these gradients are formed and maintained at the cellular and molecular levels is still the center of a great deal of research. In this review, we first explored all of the different sources of Shh during the development of the nervous system. Then, we detailed how these sources can distribute Shh in the surrounding tissues via a variety of mechanisms. Finally, we addressed how disrupting Shh distribution and gradients can induce severe neurodevelopmental disorders and cancers. Although the concept of gradient has been central in the field of neurodevelopment since the fifties, we also describe how contemporary leading-edge techniques, such as organoids, can revisit this classical model.

Applications of Extracellular Vesicles in Abdominal Aortic Aneurysm.

Abdominal aortic aneurysm (AAA) is a localized expansion of the abdominal aorta which can lead to lethal complication as the rupture of aortic wall. Currently there is still neither competent method to predict the impending rupture of aneurysm, nor effective treatment to arrest the progression of small and asymptomatic aneurysms. Accumulating evidence has confirmed the crucial role of extracellular vesicles (EVs) in the pathological course of AAA, acting as important mediators of intercellular communication. Given the advantages of intrinsic targeting properties, lower toxicity and fair stability, EVs show great potential to serve as biomarkers, therapeutic agents and drug delivery carriers. However, EV therapies still face several major challenges before they can be applied clinically, including off-target effect, low accumulation rate and rapid clearance by mononuclear phagocyte system. In this review, we first illustrate the roles of EV in the pathological process of AAA and evaluate its possible clinical applications. We also identify present challenges for EV applications, highlight different strategies of EV engineering and constructions of EV-like nanoparticles, including EV display technology and membrane hybrid technology. These leading-edge techniques have been recently employed in multiple cardiovascular diseases and their promising application in the field of AAA is discussed.

Video analytics using deep learning for crowd analysis: a review

Gathering a large number of people in a shared physical area is very common in urban culture. Although there are limitless examples of mega crowds, the Islamic religious ritual, the Hajj, is considered as one of the greatest crowd scenarios in the world. The Hajj is carried out once in a year with a congregation of millions of people when the Muslims visit the holy city of Makkah at a given time and date. Such a big crowd is always prone to public safety issues, and therefore requires proper measures to ensure safe and comfortable arrangement. Through the advances in computer vision based scene understanding, automatic analysis of crowd scenes is gaining popularity. However, existing crowd analysis algorithms might not be able to correctly interpret the video content in the context of the Hajj. This is because the Hajj is a unique congregation of millions of people crowded in a small area, which can overwhelm the use of existing video and computer vision based sophisticated algorithms. Through our studies on crowd analysis, crowd counting, density estimation, and the Hajj crowd behavior, we faced the need of a review work to get a research direction for abnormal behavior analysis of Hajj pilgrims. Therefore, this review aims to summarize the research works relevant to the broader field of video analytics using deep learning with a special focus on the visual surveillance in the Hajj. The review identifies the challenges and leading-edge techniques of visual surveillance in general, which may gracefully be adaptable to the applications of Hajj and Umrah. The paper presents detailed reviews on existing techniques and approaches employed for crowd analysis from crowd videos, specifically the techniques that use deep learning in detecting abnormal behavior. These observations give us the impetus to undertake a painstaking yet exhilarating journey on crowd analysis, classification and detection of any abnormal movement of the Hajj pilgrims. Furthermore, because the Hajj pilgrimage is the most crowded domain for video-related extensive research activities, this study motivates us to critically analyze the crowd on a large scale.

Construction of Co-doped NiS/S-g-C3N4 heterojunction for boosting degradation of dye and inactivation of pathogens in visible light

Constructingwell-definedheterojunction especially the one-dimensional/two-dimensional (1D/2D) is promising but still challenging for enhanced photocatalytic activity. In this work, I constructed a sequence of novel 1D/2D heterojunction nanocomposites (NCs) by the coupling of S-g-C3N4 nanosheets (NSs) with different quantities (1, 2, 3, 4 and 8 wt%) of 1D Co-doped NiS nanorods (NRs). A unique 1D/2D heterojunction designed between CNS and S-g-C3N4 produces abundant catalytic active sites and a vast number of heterojunctions for photocatalytic methylene blue (MB) degradation. The as-fabricated samples were evaluated by leading-edge techniques such as XRD, SEM, EDX, TEM, FTIR, XPS, UV–vis, BET, PL and transient photocurrent. Our results explored that the intimate interface contact between CNS NRs and S-g-C3N4 was probed via surface loading of CNS NRs on S-g-C3N4 NSs, enhancing the generation, separation and transportation of photogenerated electron/hole pairs and preventing the recombination of photoinduced charge carriers. When employed as photocatalysts to degrade MB under visible light illumination, 3CNS-10-SCN displayed the maximum removal rate (99%), substantially boosted than that of NiS NRs (35%), 3% CNS NRs (56%) and S-g-C3N4 (32%). Meanwhile, the photo-corrosion of S-g-C3N4 was suppressed by synchronized coupling with CNS NRs and doping with Co, which was proved by a structural stability experiment with six repeated runs. Such extraordinary improvement in photocatalytic performance and stability was mainly credited to active separation and transportation of photoinduced electron-hole pairs at the 3CNS-10-SCN heterojunction. Antibacterial activity of 1D/2D 3CNS-10-SCN NCs against 4 bacterial species was estimated by illumination of Vis-light.

Video Steganography: A Survey of Techniques and Methodologies

In recent decades, steganography has gained momentum due to its ability to communicate data covertly. Steganography embeds secret data into cover medium that are of many forms like text, image audio and video. Video steganography is drawing more impulse due to its scope of masking larger amount of secret information. This paper furnishes the leading-edge techniques and methodologies concerning video as covert communication channel. Both processed and un-processed videos are considered for surveying. Further the feasibility of encryption techniques are also discussed. This paper provides an overall view about the embedding and encryption techniques considering video as cover. Here different steganographic methodologies is divided as early embedding, intermediate embedding and delayed embedding which is based on the time data embedding is done.

Central and Peripheral Neuromuscular Adaptations to Ageing.

Ageing is accompanied by a severe muscle function decline presumably caused by structural and functional adaptations at the central and peripheral level. Although researchers have reported an extensive analysis of the alterations involving muscle intrinsic properties, only a limited number of studies have recognised the importance of the central nervous system, and its reorganisation, on neuromuscular decline. Neural changes, such as degeneration of the human cortex and function of spinal circuitry, as well as the remodelling of the neuromuscular junction and motor units, appear to play a fundamental role in muscle quality decay and culminate with considerable impairments in voluntary activation and motor performance. Modern diagnostic techniques have provided indisputable evidence of a structural and morphological rearrangement of the central nervous system during ageing. Nevertheless, there is no clear insight on how such structural reorganisation contributes to the age-related functional decline and whether it is a result of a neural malfunction or serves as a compensatory mechanism to preserve motor control and performance in the elderly population. Combining leading-edge techniques such as high-density surface electromyography (EMG) and improved diagnostic procedures such as functional magnetic resonance imaging (fMRI) or high-resolution electroencephalography (EEG) could be essential to address the unresolved controversies and achieve an extensive understanding of the relationship between neural adaptations and muscle decline.

Comprehensive Genome-Wide Approaches to Activity-Dependent Translational Control in Neurons.

Activity-dependent regulation of gene expression is critical in experience-mediated changes in the brain. Although less appreciated than transcriptional control, translational control is a crucial regulatory step of activity-mediated gene expression in physiological and pathological conditions. In the first part of this review, we overview evidence demonstrating the importance of translational controls under the context of synaptic plasticity as well as learning and memory. Then, molecular mechanisms underlying the translational control, including post-translational modifications of translation factors, mTOR signaling pathway, and local translation, are explored. We also summarize how activity-dependent translational regulation is associated with neurodevelopmental and psychiatric disorders, such as autism spectrum disorder and depression. In the second part, we highlight how recent application of high-throughput sequencing techniques has added insight into genome-wide studies on translational regulation of neuronal genes. Sequencing-based strategies to identify molecular signatures of the active neuronal population responding to a specific stimulus are discussed. Overall, this review aims to highlight the implication of translational control for neuronal gene regulation and functions of the brain and to suggest prospects provided by the leading-edge techniques to study yet-unappreciated translational regulation in the nervous system.

Classify mental states from EEG signal using XGBoost algorithm

Brain-computer interface (BCI) is a leading-edge technique which allows the brain communicates with external devices. It has been applied in several fields, such as medical rehabilitation, virtual reality and so on. This invention introduces a technique that can be applied in education field to monitor and analyze users’ electroencephalogram (EEG) so that the mental states could be identified. The algorithm of classifier used XGBoost which combined Bayes, KNN and SVM in it and its accuracy could reach to 80%. By using this technique, teacher could obtain the concentration status of students in real time and adjust his or her teaching method or remind the student who is wandering.

Possibilities of applying speckle tracking echocardiography to assess fetal myocardial function. Part 1. Methods to assess fetal cardiac function

The article deals with the physiology of the heart and methods to assess fetal cardiac function. The leadingedge technique to assess the myocardial deformation properties by speckle tracking echocardiography in prenatal period is presented.

Technology Focus: Seismic

Technology Focus Last year saw continued contraction in the seismic data-acquisition industry. This included both onshore and offshore operations. Most notably, WesternGeco exited land and marine data acquisition. (In the case of marine, WesternGeco sold all of its vessels, facilities, and technologies to Shearwater GeoServices.) Ironically, it was just 1 year ago when I discussed in this column the new and exciting acquisition-related advances in the industry that had been developed for the purpose of better data sampling. With this drop in acquisition business, it is not surprising that there were fewer seismic data-acquisition papers published in SPE proceedings. Nevertheless, several excellent SPE papers covered important acquisition and processing topics. One of the papers deals with the current state of the art for addressing marine challenges. This is described with a 3D case history from the Gulf of Thailand. Another paper deals with leading-edge techniques that were used in a recent onshore 3D survey in Abu Dhabi. And a third paper showcases the application of a relatively new technology, distributed acoustic sensing (DAS). DAS is rapidly finding a home in vertical-seismic-profile surveys and in unconventional programs. Indeed, this third paper deals with a DAS study performed in the Marcellus Shale. Offsetting the drop in the number of acquisition papers was a proportionate increase in the number of SPE papers that covered other important seismic topics. These included inversion and reservoir characterization, 4D interpretation, seismic for carbonate plays, and machine learning. (Similar to what is happening in other industries, machine learning is receiving tremendous attention now in the seismic world.) Though industry fluctuations may affect our areas of specialty, there will always be room for improvement driven by innovation. Recommended additional reading at OnePetro: www.onepetro.org. SPE 189888 Seismic Attributes Application for the Distributed Acoustic Sensing Data for the Marcellus Shale: New Insights to Cross-Stage Flow Communication by Payam Kavousi Ghahfarokhi, West Virginia University, et al. SPE 192948 How Broadband, High-Density, Full-Azimuth, and Point-Source Point-Receiver Acquisition Improves Seismic Interpretation in Onshore Abu Dhabi by Sheikha Al-Naqbi, ADNOC Onshore, et al. SPE 192956 Comparing Seismic Inversion Methods on a Carbonate Reservoir: A Case Study From the Mishrif Reservoir, Rumaila Field, Iraq by Olabode Joseph Olatoke, BP, et al. SPE 192927 Effect of Seismic Acquisition and Processing Techniques in Challenging Subsurface Imaging, Block G11/48, Gulf of Thailand by Phansakorn Kaewprain, Mubadala

A Time-Walk Correction Method for PET Detectors Based on Leading Edge Discriminators.

The leading edge timing pick-off technique is the simplest timing extraction method for PET detectors. Due to the inherent time-walk of the leading edge technique, corrections should be made to improve timing resolution, especially for time-of-flight PET. Time-walk correction can be done by utilizing the relationship between the threshold crossing time and the event energy on an event by event basis. In this paper, a time-walk correction method is proposed and evaluated using timing information from two identical detectors both using leading edge discriminators. This differs from other techniques that use an external dedicated reference detector, such as a fast PMT-based detector using constant fraction techniques to pick-off timing information. In our proposed method, one detector was used as reference detector to correct the time-walk of the other detector. Time-walk in the reference detector was minimized by using events within a small energy window (508.5 - 513.5 keV). To validate this method, a coincidence detector pair was assembled using two SensL MicroFB SiPMs and two 2.5 mm × 2.5 mm × 20 mm polished LYSO crystals. Coincidence timing resolutions using different time pick-off techniques were obtained at a bias voltage of 27.5 V and a fixed temperature of 20 °C. The coincidence timing resolution without time-walk correction were 389.0 ± 12.0 ps (425 -650 keV energy window) and 670.2 ± 16.2 ps (250-750 keV energy window). The timing resolution with time-walk correction improved to 367.3 ± 0.5 ps (425 - 650 keV) and 413.7 ± 0.9 ps (250 - 750 keV). For comparison, timing resolutions were 442.8 ± 12.8 ps (425 - 650 keV) and 476.0 ± 13.0 ps (250 - 750 keV) using constant fraction techniques, and 367.3 ± 0.4 ps (425 - 650 keV) and 413.4 ± 0.9 ps (250 - 750 keV) using a reference detector based on the constant fraction technique. These results show that the proposed leading edge based time-walk correction method works well. Timing resolution obtained using this method was equivalent to that obtained using a reference detector and was better than that obtained using constant fraction discriminators.

Interactions propel a magnetic dance

A combination of leading-edge techniques has enabled interaction-induced magnetic motion to be observed for pairs of ultracold atoms — a breakthrough in the development of models of complex quantum behaviour. See Letter p.519 Simulating topological band structures, the corresponding edge states, and the quantum Hall effect with neutral atoms requires the introduction of artificial gauge fields. Although challenging, various groups have recently demonstrated artificial gauge fields in ultracold neutral-atom systems. However, up to now, these simulations have been limited to single-particle effects, meaning that many fascinating condensed-matter phenomena, such as the fractional quantum Hall effect, could not be studied. Here, the authors subject a two-dimensional Bose–Einstein condensate of rubidium-87 atoms to an artificial gauge field and use a quantum gas microscope to investigate how two-body interactions affect the chiral dynamics. If extended to many-body interactions, this strategy could enable the simulation of the interplay between many-body interactions and topology in condensed-matter physics.

Postprocessing Phase Stabilizer for Wide Frequency Range Photonic-Microwave Signal Distribution

In the field of leading-edge techniques, such as broadband communications and large-scale radio interferometer applications, the need for a highly stable/wide-frequency-range photonic-microwave signal (continuous sine wave) is increasing. The main purpose of this research is to provide a highly stable photonic-microwave signal over a large broadband from microwave to terahertz frequencies using the same optical signal generation/transmission system. While transmitting signals through an optical cable, the transmission delay fluctuates and it suffers from chromatic dispersion that affects the distribution signal coherence. We have developed a postprocessing scheme transmission phase stabilizer. In the scheme, the measured phase of the round-tripped signal is acquired at time intervals at the optical transmitting port (an optical input port), and then the measured phase data are sent to the destination port (an optical output port) for the transmission phase compensation. The postprocessing method has advantages for a frequency dynamic range and compensation range issue. Theoretically, there is no upper frequency limit on the proposed phase stabilizer. We also discuss a high-frequency signal generator based on an optical comb signal generator up to terahertz frequencies.

Three-dimensional geology from potential field geophysics: Applications to Bathurst Mining Camp, Eastern Canada

SUMMARY Interpretation methods and tools for geophysics datasets continue to evolve. Advances in clustering algorithms, the use of implicit functions to create 3D surfaces, new algorithms to estimate source depths and dips, and the availability of clever computational geometry libraries, contribute to the discipline of potential field interpretation techniques, allowing for a much more explicit statement of implied 3D description. While traditional scalar measures of potential fields have benefited from applying new ideas, perhaps more exciting is the reduction in ambiguity imposed from gradient measurement when used as the basis for field interpretation. Full tensor gravity gradiometry in particular, allows for 2D fault dip and throw calculations. Direct detection of high density bodies and faults via state-of-the-art gravity gradiometry is now a reality. Bodies greater than 200m in lateral extent are detectable. Implicit 3D structural geology modelling techniques derived from gravity curvature attributes of the observed gravity field present a leading edge technique for defining structurally controlled near surface geology geometry. A demonstration from the Bathurst camp dataset is given.

Merging Single-well and Inter-well Tracer Tests into One Forced-gradient Dipole Test, at the Heletz Site within the MUSTANG Project

The Heletz site in Israel was chosen for conducting a CO2 transport experiment within the MUSTANG project, which aim is to demonstrate and validate leading-edge techniques for CCS site characterization, process monitoring and risk assessment. The major CO2 injection experiment at Heletz was supposed to be preceded and accompanied by a sequence of single-well (SW) ‘push-then-pull’ and inter-well (IW) tracer tests, aimed at characterizing transport properties of the storage formation. – Instead of the rather luxurious, multiple-SW and multiple-IW test sequence described in our previous work, we now propose a drastically economized tracer test concept, which lets the fluid sampling stages of SW and IW tests merge into a single production stage, and relies on a forced-gradient dipole flow field at any time of the overall test. Besides cost reduction, this economized design also improves on operational aspects, as well as on issues of parameter ambiguity and of scale disparity between SW and IW flow fields.

Comparative evaluation of Indian technical institutions using distance based approach method

Purpose – Due to liberalization, privatization and globalization, the need of competent technical manpower at an economical cost is increasing rapidly. Many foreign multinationals are focusing on India for employable talents. Many technical institutions with cutting edge technologies and leading edge techniques are being set up by foreign collaboration, national and private initiatives. The objective of this study is to propose a model for performance evaluation and benchmarking of Indian technical institutions from perspective of all stakeholders.Design/methodology/approach – For the proposed framework, a multiple criteria decision‐making tool, distance‐based approach (DBA) methodology is applied for performance evaluation of seven Indian technical institutions taking into account some selected criteria like, faculty strength (FS), student intake (SI), number of PhD awarded (PhD), number of patents applied for (patent), the campus area in acres (CA) and tuition fee per semester in rupees (TF). Consulting...