Comparative efficacy and safety of subcutaneous infliximab and vedolizumab in patients with Crohn's disease and ulcerative colitis included in randomised controlled trials.

BACKGROUND: While indirect comparison of infliximab (IFX) and vedolizumab (VDZ) in adults with Crohn's disease (CD) or ulcerative colitis (UC) shows that IFX has better effectiveness during induction, and comparable efficacy during maintenance treatment, comparative data specific to subcutaneous (SC) IFX (i.e., CT-P13 SC) versus VDZ are limited. AIM: Pooled analysis of randomised studies to compare efficacy and safety with IFX SC and VDZ in moderate-to-severe inflammatory bowel disease. METHODS: Parallel-group, randomised studies evaluating IFX SC and VDZ in patients with moderate-to-severe CD or UC were identified. Eligible studies reported ≥ 1 prespecified outcome of interest at Week 6 (reflecting treatment during the induction phase) and/or at 1 year (Weeks 50-54; reflecting treatment during the maintenance phase). Prespecified efficacy and safety outcomes considered in this pooled analysis included the proportions of patients achieving disease-specific clinical responses, clinical remission, or discontinuing due to lack of efficacy, and the proportions of patients experiencing adverse events (AEs), serious AEs, infections, serious infections, or discontinuing due to AEs. Data from multiple studies or study arms were extracted and pooled using a random-effect model; comparative analyses were performed separately for patients with CD and UC. RESULTS: We identified three eligible CD trials and four eligible UC trials that assigned over 1200 participants per disease cohort to either IFX SC or VDZ. In patients with CD, intravenous induction therapy with IFX demonstrated better efficacy (non-overlapping 95% confidence intervals [CIs]) compared with VDZ; during the maintenance phase, IFX SC showed numerically better efficacy (overlapping 95% CIs) than VDZ. A lower proportion of IFX SC-treated patients discontinued therapy due to lack of efficacy over 1 year. In patients with UC, efficacy profiles were similar with IFX SC and VDZ during the induction and maintenance phases, and a lower proportion of IFX SC-treated patients discontinued therapy due to lack of efficacy over 1 year. In both cohorts, safety profiles for IFX SC and VDZ were generally comparable during 1 year. CONCLUSION: IFX SC demonstrated better efficacy than VDZ in patients with CD, and similar efficacy to VDZ in patients with UC; 1-year safety was comparable with IFX SC and VDZ.

Milestones in corrole chemistry: historical ligand syntheses and post-functionalization.

Corroles are synthetic porphyrin analogs that contain one meso carbon atom lesser and bear a trianionic N4 metal-chelating core. They require in-depth preparative chemistry, demonstrate unique coordination chemistry and have impressive and diverse physical properties, and these are commonly compared to their respective porphyrins. The corrole's macrocyclic system is inherently electron rich and chelates metal ions in a more compact, less symmetric tetranitrogen cavity compared to that of porphyrins. Herein, we cover the highlights of the corrole research through the decades by first reviewing, in a chronological sense, multi-step syntheses; some routes have since been discontinued. This is followed by describing post-functionalization of already formed corroles via reactions performed on either the macrocycle's periphery or the inner nitrogen atoms or on the existing substituents. We do also mention milestones in literature reviewing, publication of encyclopedias, and the creation of professional organizations and conferences (ICPP) which make up the corrole/porphyrin research landscape. Also highlighted are still existing challenges and future perspectives.

Improvement of a Green's Function Estimation for a Moving Source Using the Waveguide Invariant Theory.

Understanding the characteristics of underwater sound channels is essential for various remote sensing applications. Typically, the time-domain Green's function or channel impulse response (CIR) is obtained using computationally intensive acoustic propagation models that rely on accurate environmental data, such as sound speed profiles and bathymetry. Ray-based blind deconvolution (RBD) offers a less computationally demanding alternative using plane-wave beamforming to estimate the Green's function. However, the presence of noise can obscure low coherence ray arrivals, making accurate estimation challenging. This paper introduces a method using the waveguide invariant to improve the signal-to-noise ratio (SNR) of broadband Green's functions for a moving source without prior knowledge of range. By utilizing RBD and the frequency shifts from the striation slope, we coherently combine individual Green's functions at adjacent ranges, significantly improving the SNR. In this study, we demonstrated the proposed method via simulation and broadband noise data (200-900 Hz) collected from a moving ship in 100 m deep shallow water.

Strategies to Enrich Electrochemical Sensing Data with Analytical Relevance for Machine Learning Applications: A Focused Review.

In this review, recent advances regarding the integration of machine learning into electrochemical analysis are overviewed, focusing on the strategies to increase the analytical context of electrochemical data for enhanced machine learning applications. While information-rich electrochemical data offer great potential for machine learning applications, limitations arise when sensors struggle to identify or quantitatively detect target substances in a complex matrix of non-target substances. Advanced machine learning techniques are crucial, but equally important is the development of methods to ensure that electrochemical systems can generate data with reasonable variations across different targets or the different concentrations of a single target. We discuss five strategies developed for building such electrochemical systems, employed in the steps of preparing sensing electrodes, recording signals, and analyzing data. In addition, we explore approaches for acquiring and augmenting the datasets used to train and validate machine learning models. Through these insights, we aim to inspire researchers to fully leverage the potential of machine learning in electroanalytical science.

Development of a prediction model for cognitive impairment of sarcopenia using multimodal neuroimaging in non-demented older adults.

INTRODUCTION: Despite prior research on the association between sarcopenia and cognitive impairment in the elderly, a comprehensive model that integrates various brain pathologies is still lacking. METHODS: We used data from 528 non-demented older adults with or without sarcopenia in the Catholic Aging Brain Imaging (CABI) database, containing magnetic resonance imaging scans, positron emission tomography scans, and clinical data. We also measured three key components of sarcopenia: skeletal muscle index (SMI), hand grip strength (HGS), and the five times sit-to-stand test (5STS). RESULTS: All components of sarcopenia were significantly correlated with global cognitive function, but cortical thickness and amyloid-beta (Aß) retention had distinctive relationships with each measure. In the path model, brain atrophy resulting in cognitive impairment was mediated by Aß retention for SMI and periventricular white matter hyperintensity for HGS, but directly affected by the 5STS. DISCUSSION: Treatments targeting each sub-domain of sarcopenia should be considered to prevent cognitive decline. HIGHLIGHTS: We identified distinct impacts of three sarcopenia measures on brain structure and Aß. Muscle mass is mainly associated with Aß and has an influence on the brain atrophy. Muscle strength linked with periventricular WMH and brain atrophy. Muscle function associated with cortical thinning in specific brain regions. Interventions on sarcopenia may be important to ease cognitive decline in the elderly.

A Comparative Analysis of Two Automated Quantification Methods for Regional Cerebral Amyloid Retention: PET-Only and PET-and-MRI-Based Methods.

Accurate quantification of amyloid positron emission tomography (PET) is essential for early detection of and intervention in Alzheimer's disease (AD) but there is still a lack of studies comparing the performance of various automated methods. This study compared the PET-only method and PET-and-MRI-based method with a pre-trained deep learning segmentation model. A large sample of 1180 participants in the Catholic Aging Brain Imaging (CABI) database was analyzed to calculate the regional standardized uptake value ratio (SUVR) using both methods. The logistic regression models were employed to assess the discriminability of amyloid-positive and negative groups through 10-fold cross-validation and area under the receiver operating characteristics (AUROC) metrics. The two methods showed a high correlation in calculating SUVRs but the PET-MRI method, incorporating MRI data for anatomical accuracy, demonstrated superior performance in predicting amyloid-positivity. The parietal, frontal, and cingulate importantly contributed to the prediction. The PET-MRI method with a pre-trained deep learning model approach provides an efficient and precise method for earlier diagnosis and intervention in the AD continuum.

BERN2: an advanced neural biomedical named entity recognition and normalization tool.

In biomedical natural language processing, named entity recognition (NER) and named entity normalization (NEN) are key tasks that enable the automatic extraction of biomedical entities (e.g. diseases and drugs) from the ever-growing biomedical literature. In this article, we present BERN2 (Advanced Biomedical Entity Recognition and Normalization), a tool that improves the previous neural network-based NER tool by employing a multi-task NER model and neural network-based NEN models to achieve much faster and more accurate inference. We hope that our tool can help annotate large-scale biomedical texts for various tasks such as biomedical knowledge graph construction. AVAILABILITY AND IMPLEMENTATION: Web service of BERN2 is publicly available at http://bern2.korea.ac.kr. We also provide local installation of BERN2 at https://github.com/dmis-lab/BERN2. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Efficacy of subcutaneous vs intravenous infliximab in rheumatoid arthritis: a post-hoc analysis of a randomized phase III trial.

OBJECTIVES: The primary endpoint of the pivotal phase III study of infliximab (IFX) s.c. demonstrated non-inferiority of s.c. to i.v. IFX, based on 28-joint DAS-CRP (DAS28-CRP) improvement at week (W) 22 (NCT03147248). This post-hoc analysis investigated whether numerical differences in efficacy outcomes at W30/54 were statistically significant, using conservative imputation methods. METHODS: Patients with active RA and inadequate response to MTX received IFX i.v. 3 mg/kg at W0 and W2 (induction) and were randomized (1:1) to IFX s.c. 120 mg every 2 weeks or i.v. 3 mg/kg every 8 weeks thereafter (maintenance). Patients randomized to IFX i.v. switched to IFX s.c. from W30-54. This post-hoc analysis compared efficacy outcomes for s.c. and i.v. groups pre-switch (W30) and post-switch (W54) using last observation carried forward (LOCF) and non-responder imputation (NRI) methods. RESULTS: Of 343 randomized patients, 165 (IFX s.c.) and 174 (IFX i.v.) were analysed. At W30, significantly improved outcomes were identified with s.c. vs i.v. IFX for DAS28-CRP/DAS28-ESR/Clinical Disease Activity Index (CDAI)/Simplified Disease Activity Index (SDAI) scores (LOCF); ACR/good EULAR responses, DAS28-CRP/Boolean remission, and DAS28-CRP/DAS28-ESR/CDAI/SDAI low disease activity and remission (LOCF and/or NRI); and minimal clinically important difference in HAQ score (LOCF and NRI). After switching to IFX s.c. from IFX i.v., fewer significant between-group differences were identified at W54. CONCLUSION: IFX s.c. showed improved efficacy at W30 compared with IFX i.v., and the reduced between-group difference in efficacy outcomes at W54 after switching supports the results suggesting benefits of IFX s.c. compared with IFX i.v. at W30. TRIAL REGISTRATION: ClincialTrials.gov, http://clinicaltrials.gov, NCT03147248, https://clinicaltrials.gov/ct2/show/NCT03147248.

Integrative Data Mining Approach: Case Study with Adverse Outcome Pathway Network Leading to Pulmonary Fibrosis.

An adverse outcome pathway (AOP) framework can be applied as an efficient tool for the rapid screening of environmental chemicals. For the development of an AOP, a database mining approach can support an expert derivation approach by gathering a wider range of evidence than in a literature review. In this study, data from various databases were integrated and analyzed to supplement the AOP leading to pulmonary fibrosis by analyzing additional evidence using a data mining approach and establishing an application domain for chemicals. First, we collected chemicals, genes, and phenotypes that were studied and related to pulmonary fibrosis through the Comparative Toxicogenomics Database (CTD). CGPD-tetramers constructed by linking each related chemical, gene, phenotype, and disease can provide the basic components for the assembly of putative AOPs. Next, an AOP network was established by connecting eight existing AOPs for pulmonary fibrosis developed by expert derivation from the AOP Wiki. Finally, the pulmonary fibrosis AOP network was proposed by integrating the AOP network from AOP Wiki and the CGPD-tetramers from the CTD. To prioritize potential chemical stressors in the AOP network, 61 chemicals were ranked using the relevance of the chemical to the AOP and chemical exposure information from the CompTox Chemicals Dashboard. The approach proposed in this study can guide the utilization of available evidence from various databases as well as the literature in constructing AOP networks related to specific diseases.

A regional brain volume-based age prediction model for neonates and the derived brain maturation index.

OBJECTIVE: To develop a postmenstrual age (PMA) prediction model based on segmentation volume and to evaluate the brain maturation index using the proposed model. METHODS: Neonatal brain MRIs without clinical illness or structural abnormalities were collected from four datasets from the Developing Human Connectome Project, the Catholic University of Korea, Hammersmith Hospital (HS), and Dankook University Hospital (DU). T1- and T2-weighted images were used to train a brain segmentation model. Another model to predict the PMA of neonates based on segmentation data was developed. Accuracy was assessed using mean absolute error (MAE), root mean square error (RMSE), and mean error (ME). The brain maturation index was calculated as the difference between the PMA predicted by the model and the true PMA, and its correlation with postnatal age was analyzed. RESULTS: A total of 247 neonates (mean gestation age 37 ± 4 weeks; range 24-42 weeks) were included. Thirty-one features were extracted from each neonate and the three most contributing features for PMA prediction were the right lateral ventricle, left caudate, and corpus callosum. The predicted and true PMA were positively correlated (coefficient = 0.88, p < .001). MAE, RMSE, and ME of the external dataset of HS and DU were 1.57 and 1.33, 1.79 and 1.37, and 0.37 and 0.06 weeks, respectively. The brain maturation index negatively correlated with postnatal age (coefficient = - 0.24, p < .001). CONCLUSION: A model that calculates the regional brain volume can predict the PMA of neonates, which can then be utilized to show the brain maturation degree. CLINICAL RELEVANCE STATEMENT: A brain maturity index based on regional volume of neonate's brain can be used to measure brain maturation degree, which can help identify the status of early brain development. KEY POINTS: • Neonatal brain MRI segmentation model could be used to assess neonatal brain maturation status. • A postmenstrual age (PMA) prediction model was developed based on a neonatal brain MRI segmentation model. • The brain maturation index, derived from the PMA prediction model, enabled the estimation of the neonatal brain maturation status.

"Lighting up" fluoride: cellular imaging and zebrafish model interrogations using a simple ESIPT-based mycophenolic acid precursor-based probe.

The discovery and implementation of media that derive from bioinspired designs and bear optical readouts featuring large Stokes shifts are of continued interest to a wide variety of researchers and clinicians. Myco-F, a novel mycophenolic acid precursor-based probe features a cleavable tert-butyldimethylsiloxy group to allow for fluoride detection. Myco-F exhibits high selectivity and specificity towards F- (Stokes shift = 120 nm). All measurements were performed in complete aqueous media (LOD=0.38 µM). Myco-F enables detection of fluoride ions in living HEK293 cells and localizes in the eye region (among other regions) of the zebrafish. DFT calculations support the proposed ESIPT working photomechanism.

Exploring the potential of ToxCast™ data for mechanism-based prioritization of chemicals in regulatory context: Case study with priority existing chemicals (PECs) under K-REACH.

Recent studies have highlighted the potential of the ToxCast™ database for mechanism-based prioritization of chemicals. To explore the applicability of ToxCast data in the context of regulatory inventory chemicals, we screened 510 priority existing chemicals (PECs) regulated under the Act on the Registration and Evaluation, etc. of Chemical Substances (K-REACH) using ToxCast bioassays. In our analysis, a hit-call data matrix containing 298984 chemical-gene interactions was computed for 949 bioassays with the intended target genes, which enabled the identification of the putative toxicity mechanisms. Based on the reactivity to the chemicals, we analyzed 412 bioassays whose intended target gene families were cytochrome P450, oxidoreductase, transporter, nuclear receptor, steroid hormone, and DNA-binding. We also identified 141 chemicals based on their reactivity in the bioassays. These chemicals are mainly in consumer products including colorants, preservatives, air fresheners, and detergents. Our analysis revealed that in vitro bioactivities were involved in the relevant mechanisms inducing in vivo toxicity; however, this was not sufficient to predict more hazardous chemicals. Overall, the current results point to a potential and limitation in using ToxCast data for chemical prioritization in regulatory context in the absence of suitable in vivo data.

A Fully Automated Visual Grading System for White Matter Hyperintensities of T2-Fluid Attenuated Inversion Recovery Magnetic Resonance Imaging.

BACKGROUND: The Fazekas scale is one of the most commonly used visual grading systems for white matter hyperintensity (WMH) for brain disorders like dementia from T2-fluid attenuated inversion recovery magnetic resonance (MR) images (T2-FLAIRs). However, the visual grading of the Fazekas scale suffers from low-intra and inter-rater reliability and high labor-intensive work. Therefore, we developed a fully automated visual grading system using quantifiable measurements. METHODS: Our approach involves four stages: (1) the deep learning-based segmentation of ventricles and WMH lesions, (2) the categorization into periventricular white matter hyperintensity (PWMH) and deep white matter hyperintensity (DWMH), (3) the WMH diameter measurement, and (4) automated scoring, following the quantifiable method modified for Fazekas grading. We compared the performances of our method and that of the modified Fazekas scale graded by three neuroradiologists for 404 subjects with T2-FLAIR utilized from a clinical site in Korea. RESULTS: The Krippendorff's alpha across our method and raters (A) versus those only between the radiologists (R) were comparable, showing substantial (0.694 vs. 0.732; 0.658 vs. 0.671) and moderate (0.579 vs. 0.586) level of agreements for the modified Fazekas, the DWMH, and the PWMH scales, respectively. Also, the average of areas under the receiver operating characteristic curve between the radiologists (0.80 ± 0.09) and the radiologists against our approach (0.80 ± 0.03) was comparable. CONCLUSIONS: Our fully automated visual grading system for WMH demonstrated comparable performance to the radiologists, which we believe has the potential to assist the radiologist in clinical findings with unbiased and consistent scoring.

Cognitive Normal Older Adults with APOE-2 Allele Show a Distinctive Functional Connectivity Pattern in Response to Cerebral Aß Deposition.

The ε2 allele of apolipoprotein E (ε2) has neuroprotective effects against beta-amyloid (Aß) pathology in Alzheimer's disease (AD). However, its impact on the functional connectivity and hub efficiency in cognitively normal older adults (CN) with ε2 is unclear. We investigated the functional connectivity differences in the default mode network (DMN), salience network, and central executive network (CEN) between A-PET-negative (N = 29) and A-PET-positive (N = 15) CNs with ε2/ε2 or ε2/ε3 genotypes. The A-PET-positive CNs exhibited a lower anterior DMN functional connectivity, higher posterior DMN functional connectivity, and increased CEN functional connectivity compared to the A-PET-negative CNs. Cerebral Aß retention was negatively correlated with anterior DMN functional connectivity and positively correlated with posterior DMN and anterior CEN functional connectivity. A graph theory analysis showed that the A-PET-positive CNs displayed a higher betweenness centrality in the middle frontal gyrus (left) and medial fronto-parietal regions (left). The betweenness centrality in the middle frontal gyrus (left) was positively correlated with Aß retention. Our findings reveal a reversed anterior-posterior dissociation in the DMN functional connectivity and heightened CEN functional connectivity in A-PET-positive CNs with ε2. Hub efficiencies, measured by betweenness centrality, were increased in the DMN and CEN of the A-PET-positive CNs with ε2. These results suggest unique functional connectivity responses to Aß pathology in CN individuals with ε2.

Sex-Related Disparities in the Resting State Functional Connectivity of the Locus Coeruelus and Salience Network in Preclinical Alzheimer's Disease.

Recent studies have demonstrated the pivotal role of locus coeruleus (LC) and salience network (SN) resting state functional connectivity (rsFC) changes in the early stage of Alzheimer's disease (AD). Moreover, sex has been a crucial point of discussion in understanding AD pathology. We aimed to demonstrate the sex-related disparities in the functional connectivity (FC) of the SN and LC in preclinical AD. A total of 89 cognitively normal patients with evidence of amyloid beta (Aß) accumulation ([18F] flutemetamol +) were recruited in the study. A seed-to-voxel analysis was conducted to measure the LC and SN rsFC differences between sexes. In addition, sex by Aß interactive effects on FC values were analyzed with a general linear model. There were statistically significant sex by regional standardized uptake value ratio (SUVR) interactions in the LC FC with the parietal, frontal, and occipital cortices. Moreover, there was a significant sex by global SUVR interaction in the SN FC with the temporal cortex. The findings suggest that there are differential patterns of LC FC and SN FC in males and females with preclinical AD, which interact with regional Aß deposition.

Comparisons of musculoskeletal injuries among three different modalities of Taekwondo (Kyorugi, Poomsae, and Shibum): a one-year follow-up prospective epidemiologic study.

The purpose of the study was to report the injury rates and characteristics (body location, type, mechanism, and severity) of musculoskeletal injuries in Kyorugi, Poomsae, and Shibum. A total of 137 Korean collegiate Taekwondo players - Kyorugi (n = 44), Poomsae (n = 46), and Shibum (n = 47) - were prospectively studied in 2019. Injury rates per 1,000 athlete-exposures (AEs) and time-exposures (TEs) during training and competition were calculated. Additionally, body location, type, mechanism, and severity of injury were analysed. The highest injury rate was recorded in Poomsae (172.0/1,000 AEs and 79.5/1,000 TEs) followed by Kyorugi (47.1/1,000 AEs and 25.9/1,000 TEs) and Shibum (57.5/1,000 AEs and 17.0/1,000 TEs). The frequently injured body location was the thigh (Kyorugi = 17%; Poomsae = 25%; Shibum = 18%). The common injury types were muscle cramps/spasms in Kyorugi (33%) and Poomsae (59%), and sprain in Shibum (41%). The common injury mechanisms were gradual onset in Kyorugi (40%) and Shibum (49%), and non-contact trauma in Poomsae (91%). Regarding the severity, the number of days from the injury onset to recovery > 1 week were higher in the order of Kyorugi (78%), Shibum (54%), and Poomsae (28%). Our data provide preliminary evidence that different injury prevention strategies should be applied to each modality of Taekwondo.

Comparative efficacy and safety of infliximab and vedolizumab therapy in patients with inflammatory bowel disease: a systematic review and meta-analysis.

BACKGROUND AND AIMS: There are limited comparative data for infliximab and vedolizumab in inflammatory bowel disease patients. METHODS: We conducted a systematic review and meta-analysis to compare the efficacy and safety of infliximab and vedolizumab in adult patients with moderate-to-severe Crohn's disease or ulcerative colitis. RESULTS: We identified six eligible Crohn's disease and seven eligible ulcerative colitis trials that randomised over 1900 participants per disease cohort to infliximab or vedolizumab. In the Crohn's disease and ulcerative colitis cohorts, infliximab yielded better efficacy than vedolizumab for all analysed outcomes (CDAI-70, CDAI-100 responses, and clinical remission for Crohn's disease and clinical response and clinical remission for ulcerative colitis) during the induction phase, with non-overlapping 95% confidence intervals. In the maintenance phase, similar proportions of infliximab- or vedolizumab-treated patients achieved clinical response, clinical remission, or mucosal healing in both Crohn's disease and ulcerative colitis. For the safety outcomes, rates of adverse events, serious adverse events, and discontinuations due to adverse events were similar in infliximab- and vedolizumab-treated patients in both diseases. The infection rate was higher in infliximab for Crohn's disease and higher in vedolizumab when treating patients with ulcerative colitis. There was no difference between the treatments in the proportions of patients who reported serious infections in both indications. CONCLUSIONS: Indirect comparison of infliximab and vedolizumab trials in adult patients with moderate-to severe Crohn's disease or ulcerative colitis demonstrated that infliximab has better efficacy in the induction phase and comparable efficacy during the maintenance phase and overall safety profile compared to vedolizumab.

Effect of folic acid supplementation on proliferation and apoptosis in bovine mammary epithelial (MAC-T) cells.

Folic acid (FA) is known to be an important micronutrient in humans; however, information regarding the effect of FA supplementation on bovine mammary epithelial (BME) cells is insufficient. FA supplementation is reported to increase milk production in dairy cows, but the underlying molecular mechanisms are unknown. This study examined the effects of FA supplementation on the proliferation and apoptosis of a BME cell line (MAC-T). MAC-T cells were treated with various concentrations (deficient in FA (DF) < 0.01 ng/mL; low-level FA (LF) 3.1 ng/mL; normal FA (NF) 15.4 ng/mL; and high-level FA (HF) 30.8 ng/mL) based on serum folate (10-20 ng/mL) in milking cows. HF treatment significantly increased the proliferation of MAC-T cells. Cellular apoptosis was observed mainly in the DF group. The number of apoptotic cells in DF media was significantly higher than that in NF media. The bcl-2/bax mRNA expression ratio was significantly increased in the HF group compared to that in the DF group. FA supplementation significantly increased the ratio of Bcl-2/Bax protein levels in MAC-T cells. FA supplementation increases proliferation and decreases apoptosis in these cells. This study might provide information regarding the molecular mechanism through which FA supplementation is associated with increased milk yield.

Direction-of-Arrival Estimation Based on Frequency Difference-Wavenumber Analysis for Sparse Vertical Array Configuration.

Frequency-wavenumber (f-k) analysis can estimate the direction of arrival (DOA) of broadband signals received on a vertical array. When the vertical array configuration is sparse, it results in an aliasing error due to spatial sampling; thus, several striation patterns can emerge in the f-k domain. This paper extends the f-k analysis to a sparse receiver-array, wherein a multitude of sidelobes prevent resolving the DOA estimates due to spatial aliasing. The frequency difference-wavenumber (Δf-k) analysis is developed by adopting the concept of frequency difference, and demonstrated its performance of DOA estimation to a sparse receiver array. Experimental results verify the robustness of the proposed Δf-k analysis in the estimation of the DOA of cracking sounds generated by the snapping shrimps, which were recorded by a sparse vertical array configuration during the shallow water experiment.

Long-Range Underwater Communication Based on Time Reversal Processing Using Various Diversity Methods.

Time reversal processing (TRP) exploits signal diversity methods, namely, spatial, temporal, beam, and frequency, to mitigate the distortion caused by multipath time delay. Using the same experimental data, this study compares the performance of communication utilizing TRP based on various diversity methods. In October 2018, the biomimetic long-range acoustic communication experiment 2018 (BLAC18) was conducted in the East Sea, east of Pohang, Korea. During the experiment, communication signals modulated by binary phase-shift keying were transmitted over a range of 60 km, and a vertical line array of 16 elements (with an aperture of ∼42 m) was utilized. The BLAC18 analysis showed that the performance of each diversity method depends on the order of diversity. When the order of diversity was one, the beam diversity method with the beamformed signal yielded the best performance. For the maximum order of diversity, however, the spatial diversity method delivered the best performance, owing to the high channel variability and large number of receivers.