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Internal tide generation and breaking play a primary role in the vertical transport and mixing of heat and other properties in the ocean interior, thereby influencing climate regulation. Additionally, internal tides increase sound speed variability in the ocean, consequently impacting underwater acoustic propagation. With advancements in large‐scale ocean modeling capabilities, it is essential to assess the impact of higher model resolutions (horizontal and vertical) in representing internal tides. This study investigates the influence of vertical resolution on internal tide energetics and its subsequent effects on underwater acoustic propagation in the HYbrid Coordinate Ocean Model (HYCOM). An idealized configuration with a ridge, forced only by semidiurnal tides and having 1‐km horizontal grid‐spacing, is used to test two different vertical‐grid discretizations, defined based on the zero‐crossings of horizontal velocity eigenfunctions and the merging of consecutive layers, with seven distinct numbers of isopycnal layers, ranging from 8 to 128. Analyses reveal that increasing the number of layers up to 48 increases barotropic‐to‐baroclinic tidal conversion, available potential energy, and vertical kinetic energy, converging with higher layer counts. Vertical shear exhibits a similar pattern but converges at 96 layers. Increasing the number of isopycnal layers, up to 48, increases the available potential energy contained in high (third‐to‐eighth) tidal baroclinic modes. Finally, sound speed variability and acoustic parameters differ for simulations with less than 48 layers. Therefore, the study concludes that a minimum vertical resolution (48 layers in this case) is required in isopycnal models to accurately represent internal tide properties and associated underwater acoustic propagation. Plain Language Summary Internal tides are waves that undulate along interfaces between waters of different densities inside the ocean and form when tides interact with sloping topography. Like waves at the beach, internal tides can break and mix cold, deep water with warmer surface water, helping to spread heat throughout the water column. This mixing can reduce the amount of heat at the ocean surface, affecting ocean‐atmosphere interactions and influencing the climate. Additionally, internal tides can impact acoustic propagation in the ocean interior. In the past decade, realistic numerical simulations have been able to model internal tides. However, model resolution (horizontal and vertical) may impact internal tide properties. This study uses “simplified” simulations with different vertical layers and forced only by tides to investigate the impact of the number of layers on the properties of modeled internal tides and subsequent effects on acoustic propagation. We find that increasing the number of layers up to 48 layers increases the vertical velocity and vertical shear, which have the potential to increase mixing of water and impact the way sound propagates in the ocean interior. Therefore, we conclude that at least 48 layers are required to accurately represent internal tides and associated underwater acoustic propagation. Key Points Model vertical resolution impacts internal tide‐induced kinetic energy, available potential energy, dissipation, and vertical shear Increasing the number of isopycnal layers, up to 48, increases the available potential energy contained in high (third to eighth) vertical modes At least 48 isopycnal layers are necessary to minimize variability in sound speed and acoustic propagation caused by the number of layers

We study the generation of resonantly growing mean flow by weakly nonlinear internal wave beams. With a perturbational expansion, we construct analytic solutions for three-dimensional internal wave beams, exact up to first-order accuracy in the viscosity parameter. We specifically focus on the subtleties of wave beam generation by oscillating boundaries, such as wave makers in laboratory set-ups. The exact solutions to the linearized equations allow us to derive an analytic expression for the mean vertical vorticity production term, which induces a horizontal mean flow. Whereas mean flow generation associated with viscous beam attenuation – known as streaming – has been described before, we are the first to also include a peculiar inviscid mean flow generation in the vicinity of the oscillating wall, resulting from line vortices at the lateral edges of the oscillating boundary. Our theoretical expression for the mean vertical vorticity production is in good agreement with earlier laboratory experiments, for which the previously unrecognized inviscid mean flow generation mechanism turns out to be significant.

Survivors of childhood cancer develop early and severe chronic health conditions (CHCs). A quantitative landscape of morbidity of survivors, however, has not been described. We aimed to describe the cumulative burden of curative cancer therapy in a clinically assessed ageing population of long-term survivors of childhood cancer. The St Jude Lifetime Cohort Study (SJLIFE) retrospectively collected data on CHCs in all patients treated for childhood cancer at the St Jude Children's Research Hospital who survived 10 years or longer from initial diagnosis and were 18 years or older as of June 30, 2015. Age-matched and sex-frequency-matched community controls were used for comparison. 21 treatment exposure variables were included in the analysis, with data abstracted from medical records. 168 CHCs for all participants were graded for severity using a modified Common Terminology Criteria of Adverse Events. Multiple imputation with predictive mean matching was used for missing occurrences and grades of CHCs in the survivors who were not clinically evaluable. Mean cumulative count was used for descriptive cumulative burden analysis and marked-point-process regression was used for inferential cumulative burden analysis. Of 5522 patients treated for childhood cancer at St Jude Children's Research Hospital who had complete records, survived 10 years or longer, and were 18 years or older at time of study, 3010 (54·5%) were alive, had enrolled, and had had prospective clinical assessment. 2512 (45·5%) of the 5522 patients were not clinically evaluable. The cumulative incidence of CHCs at age 50 years was 99·9% (95% CI 99·9–99·9) for grade 1–5 CHCs and 96·0% (95% CI 95·3–96·8%) for grade 3–5 CHCs. By age 50 years, a survivor had experienced, on average, 17·1 (95% CI 16·2–18·1) CHCs of any grade, of which 4·7 (4·6–4·9) were CHCs of grade 3–5. The cumulative burden in matched community controls of grade 1–5 CHCs was 9·2 (95% CI 7·9–10·6; p<0·0001 vs total study population) and of grade 3–5 CHCs was 2·3 (1·9–2·7, p<0·0001 vs total study population). Second neoplasms, spinal disorders, and pulmonary disease were major contributors to the excess total cumulative burden. Notable heterogeneity in the distribution of CHC burden in survivors with differing primary cancer diagnoses was observed. The cumulative burden of grade 1–5 CHCs at age 50 years was highest in survivors of CNS malignancies (24·2 [95% CI 20·9–27·5]) and lowest in survivors of germ cell tumours (14·0 [11·5–16·6]). Multivariable analyses showed that older age at diagnosis, treatment era, and higher doses of brain and chest radiation are significantly associated with a greater cumulative burden and severity of CHCs. The burden of CHCs in survivors of childhood cancer is substantial and highly variable. Our assessment of total cumulative burden in survivors of paediatric cancer, with detailed characterisation of long-term CHCs, provide data to better inform future clinical guidelines, research investigations, and health services planning for this vulnerable, medically complex population. The US National Cancer Institute, St Baldrick's Foundation, and the American Lebanese Syrian Associated Charities.

Type 2 innate lymphoid cells (ILC2s) both contribute to mucosal homeostasis and initiate pathologic inflammation in allergic asthma. However, the signals that direct ILC2s to promote homeostasis versus inflammation are unclear. To identify such molecular cues, we profiled mouse lung-resident ILCs using single-cell RNA sequencing at steady state and after in vivo stimulation with the alarmin cytokines IL-25 and IL-33. ILC2s were transcriptionally heterogeneous after activation, with subpopulations distinguished by expression of proliferative, homeostatic and effector genes. The neuropeptide receptor Nmur1 was preferentially expressed by ILC2s at steady state and after IL-25 stimulation. Neuromedin U (NMU), the ligand of NMUR1, activated ILC2s in vitro , and in vivo co-administration of NMU with IL-25 strongly amplified allergic inflammation. Loss of NMU–NMUR1 signalling reduced ILC2 frequency and effector function, and altered transcriptional programs following allergen challenge in vivo . Thus, NMUR1 signalling promotes inflammatory ILC2 responses, highlighting the importance of neuro-immune crosstalk in allergic inflammation at mucosal surfaces. Neuromedin receptor NMUR1 is specifically expressed by a subpopulation of type 2 innate lymphoid cells and promotes the inflammatory response of these cells in response to allergens, indicating the importance of neuro-immune crosstalk in allergic responses. Neuron regulation of immune cells Vijay Kuchroo and colleagues use single-cell RNA sequencing techniques to analyse the responses of lung innate lymphoid cells in mice to the epithelial-cell-derived cytokines IL-15 and IL-33. They identify the neuromedin U receptor NMUR1 as a receptor specifically expressed by a subpopulation of type 2 innate lymphoid cells (ILC2s), and show that it is activated by IL-25 plus the neuropeptide ligand neuromedin U (NMU), generating a lung inflammatory response. Loss of NMU–NMUR1 signalling results in allergic lung inflammation.

Steel slag is an industrial by-product of steel production which is obtained during the pyrometallurgical process. Technological dissemination on effective utilization of steel slag in vast quantities globally is essential as the generation of steel is escalating year by year and the availability of steel slag is also in millions of tons. Though steel slag has been used for various applications, large quantities of steel slag have been utilized in the field of construction only. This review focuses on the recent advances on utilization of steel slag in construction sector and the impact of steel slag incorporation has been described in detail. Utilization of steel slag in construction industry as aggregate and cementitious material for the applications toward bricks production, asphalt mixes, radiation shielding concrete, foam concrete, self-compacting concrete, ceramic manufacturing, waterproof mortars and geopolymer composites fabrication has been discussed in detail. Steel slag will be an alternate source to conserve natural resources by utilizing large quantity of steel slag in construction industry. Graphical abstract

We study the generation, propagation, and dissipation of wind-generated near-inertial waves (NIWs) in a global 1/25° Hybrid Coordinate Ocean Model (HYCOM) simulation with realistic atmospheric forcing and background circulation during 30 days in May–June 2019. The time-mean near-inertial wind power input and depth-integrated energy balance terms are computed for the total fields and the fields decomposed into vertical modes to differentiate between the radiative and (locally) dissipative components of NIW energy. Only 30.3% of the near-inertial wind input projects onto the first five modes, whereas the sum of the NIW energy in the first five modes adds up to 58% of the total NIW energy. Almost all of the depth-integrated NIW horizontal energy flux projects on the first five modes. The global distribution of dissipation and decay distances of NIW modes confirm that lower latitudes are a sink for NIW energy generated at higher latitudes. The locally dissipated fraction of NIW energy q local is found to be uniform throughout the global ocean, with a global mean value of 0.79. The horizontal NIW fluxes diverge from areas with cyclonic vorticity and converge in areas with anticyclonic vorticity; that is, anticyclonic eddies are a sink for NIW energy fluxes—in particular, for higher modes. Most of the residual energy that does not project onto modes propagates downward in anticyclonic eddies. The global near-inertial wind power input is 0.21 TW for the 30 days, of which only 19% is transmitted below 500-m depth.

Aim: Hypersensitivity is the most common clinical problem which is encountered by most of dental patients undergoing a vital tooth preparation for a fixed crown prosthesis. The aim of this study is to evaluate the effect of silver diamine fluoride, potassium nitrate, and glutaraldehyde in reducing dentinal hypersensitivity following vital tooth preparation. Settings and Design: This study is a randomized control trial performed on 119 teeth of 68 patients who are in need of fixed prosthesis treatment. Materials and Methods: After a thorough clinical examination, patients were allocated into any of the randomly assigned four groups (Control, silver diamine fluoride, potassium nitrate, and glutaraldehyde) and the level of hypersensitivity was measured by blasting air on the surface of tooth at five different intervals (before preparation, after preparation, after application of desensitizers, before cementation and after a follow up period of about 30 days) and is graded using Schiff 's cumulative hypersensitivity index. Statistical Analysis Used: Kruskal wallis test is used to compare the rate of sensitivity between the 4 groups. Friedman and Wilcoxon test is used to compare the rate of sensitivity at 5 different intervals. Results: All the desensitizers used in this study reduced the level of hypersensitivity. Among which, silver diamine fluoride was found to be more effective after application, before cementation, and after a follow up period of about 30 days followed by GLUMA and potassium nitrate. Conclusion: The results of this study suggest that silver diamine fluoride was found to be more effective after application, before cementation of the definitive prosthesis and after a follow up period of 30 days.

Natural products research increasingly applies -omics technologies to guide molecular discovery. While the combined analysis of genomic and metabolomic datasets has proved valuable for identifying natural products and their biosynthetic gene clusters (BGCs) in bacteria, this integrated approach lacks application to fungi. Because fungi are hyper-diverse and underexplored for new chemistry and bioactivities, we created a linked genomics–metabolomics dataset for 110 Ascomycetes, and optimized both gene cluster family (GCF) networking parameters and correlation-based scoring for pairing fungal natural products with their BGCs. Using a network of 3,007 GCFs (organized from 7,020 BGCs), we examined 25 known natural products originating from 16 known BGCs and observed statistically significant associations between 21 of these compounds and their validated BGCs. Furthermore, the scalable platform identified the BGC for the pestalamides, demystifying its biogenesis, and revealed more than 200 high-scoring natural product–GCF linkages to direct future discovery. Using an integrated metabologenomics approach, the biosynthetic pathway for the pestalamides is revealed and over 200 high-confidence targets are identified for future studies.

Biological organisms learn from interactions with their environment throughout their lifetime. For artificial systems to successfully act and adapt in the real world, it is desirable to similarly be able to learn on a continual basis. This challenge is known as lifelong learning, and remains to a large extent unsolved. In this Perspective article, we identify a set of key capabilities that artificial systems will need to achieve lifelong learning. We describe a number of biological mechanisms, both neuronal and non-neuronal, that help explain how organisms solve these challenges, and present examples of biologically inspired models and biologically plausible mechanisms that have been applied to artificial systems in the quest towards development of lifelong learning machines. We discuss opportunities to further our understanding and advance the state of the art in lifelong learning, aiming to bridge the gap between natural and artificial intelligence. It is an outstanding challenge to develop intelligent machines that can learn continually from interactions with their environment, throughout their lifetime. Kudithipudi et al. review neuronal and non-neuronal processes in organisms that address this challenge and discuss pathways to developing biologically inspired approaches for lifelong learning machines.

Remote health monitoring can help prevent disease at the earlier stages. The Internet of Things (IoT) concepts have recently advanced, enabling omnipresent monitoring. Easily accessible biomarkers for neurodegenerative disorders, namely, Alzheimer’s disease (AD) are needed urgently to assist the diagnoses at its early stages. Due to the severe situations, these systems demand high-quality qualities including availability and accuracy. Deep learning algorithms are promising in such health applications when a large amount of data is available. These solutions are ideal for a distributed blockchain-based IoT system. A good Internet connection is critical to the speed of these system responses. Due to their limited processing capabilities, smart gateway devices cannot implement deep learning algorithms. In this paper, we investigate the use of blockchain-based deep neural networks for higher speed and delivery of healthcare data in a healthcare management system. The study exhibits a real-time health monitoring for classification and assesses the response time and accuracy. The deep learning model classifies the brain diseases as benign or malignant. The study takes into account three different classes to predict the brain disease as benign or malignant that includes AD, mild cognitive impairment, and normal cognitive level. The study involves a series of processing where most of the data are utilized for training these classifiers and ensemble model with a metaclassifier classifying the resultant class. The simulation is conducted to test the efficacy of the model over that of the OASIS-3 dataset, which is a longitudinal neuroimaging, cognitive, clinical, and biomarker dataset for normal aging and AD, and it is further trained and tested on the UDS dataset from ADNI. The results show that the proposed method accurately (98%) responds to the query with high speed retrieval of classified results with an increased training accuracy of 0.539 and testing accuracy of 0.559.