A document by Frank Arthur. Click on the document to view its contents.

Computational fluid dynamics simulations are carried out to better understand how to manage thermally coupled reactors for conducting simultaneous endothermic and exothermic reactions. Particular emphasis is placed upon the mechanisms involved in the heat transfer processes in thermally coupled reactors for hydrogen production by steam reforming. The effects of catalyst layer thickness on the enthalpy of reaction, methanol conversion, and hydrogen yield are delineated. The oxidation and reforming reaction rates involved in the endothermic and exothermic processes are determined. Contour maps denoting temperature, enthalpy, and species mole fractions are constructed and design recommendations are made. The results indicate that the waste heat can efficiently be recovered in a low-temperature region, although the reactivity of a steam reforming reaction is low in such a region. The steam reforming device is configured as to be heated by part of the combustion heat to cause a steam reforming reaction in the device. The steam reforming reaction is endothermic and is therefore typically carried out in an externally heated steam reforming reactor. The incorporation of a simultaneous exothermic reaction to provide an improved heat source can provide a typical heat flux of roughly an order of magnitude above the convective heat flux. Structured catalysts offer heat transfer benefits and extra activity, which is more effective in the inlet zone of the steam reformer. The metallic support is formed substantially to have the same shape as the reactor wall and is arranged in a direct heat conduction relationship with the reactor wall. Desirably all of the tubes contain the same proportions of structured catalyst and particulate catalyst, which provides the benefits of the higher activity, higher heat transfer, and low pressure drop of the structured catalyst at the inlet end and the benefit of the stronger particulate catalyst at the outlet end. Heat transport is more efficient when catalyzed hardware is used in the steam reforming process.Keywords: Heat transfer; Heat management; Heat fluxes; Heat losses; Heat resistances; Heat exchange

The West African Monsoon (WAM) strongly drives precipitation variability and seasonality across continental West Africa and the tropical Eastern Atlantic. However, the evolution of the WAM in the late Cenozoic, in response to changes in vegetation, atmospheric CO 2 , orbital forcings, paleogeography, and orography as well as its teleconnections such as the mean location of the African Easterly Jet (AEJ), Tropical Easterly Jet (TEJ), SubTropical Jet (STJ), Inter-Tropical Discontinuity (ITD) and low-level westerly flow is not well constrained. We contribute to understanding past WAM dynamics by performing high-resolution, time-specific paleoclimate simulation using General Circulation Model ECHAM5. We focus our analysis on the migration and intensification of the WAM and its associated atmospheric thermodynamic structure which influence the rainfall seasonality and patterns across the Sahel, Guinea Coast, and Sahara regions.

Cloud computing (CC) provides users with online access to network services, including enhanced, transparent user management and the capacity to gather and process data. A shared Internet gateway is offered by CC, which is evolving into a private and public data center set. The integration of AI technologies into a substantial amount of computer resources, especially integrated systems, presents a number of resource problems that require careful adjustment. The IoT paradigm recently evolved in an application for smart environments. Security and privacy are seen as being of the utmost importance in any smart IoT environment in the real world. Digital environments face security threats as a result of security flaws in IoT-based networks. Because AI has excellent learning capabilities, it is more dependable and effective at spotting harmful threats. The current architecture presented in this article will support several applications of AI in digital homes detailed study of security concerns and issues.

Snow interacts with its environment in many ways, is constantly changing with time, and thus has a highly heterogeneous spatial and temporal variability. Therefore, modeling snow variability is difficult, especially when additional components such as vegetation add complexity. To increase our understanding of the spatio-temporal variability of snow and to validate snow models, we need reliable observation data at similar spatial and temporal scales. For these purposes, airborne LiDAR surveys or time series derived from snow sensors on the point scale are commonly used. However, these are limited either to one point in space or in time. We present a new, extensive dataset of snow variability in a sub-alpine forest in the Alptal, Switzerland. The core dataset consists of a dense sensor network, repeated high-resolution LiDAR data acquired using a fixed-wing UAV, and manual snow depth and snow density measurements. Using machine learning algorithms, we determine four distinct spatial clusters of similar snow depth dynamics. These clusters are characterized and further used to derive daily snow depth and snow water equivalent (SWE) maps. The results underline the complex relation of topography and canopy cover towards snow accumulation and ablation. The derived products are the first to our knowledge that provide daily, high-resolution snow depth and SWE based almost exclusively on field data. They are therefore ideally suited for the validation of distributed snow models. Our approach can be applied to other project areas and improve our understanding of the spatio-temporal variability of snow in forested environments.

The understating of the dynamics of tracers and water transit times at catchment scale has increasingly grown in the last decades, becoming a consolidated approach in the field of hydrological and ecohydrological research. Recently, a benchmark contribution has been given in the work by Benettin et al. (2022), which reviews the state of art on the topic, also addressing present and future challenge, pointing out some open questions in transit time research. This commentary tries to contextualize the above article, highlighting the most focal points and relating it to a broader context in the field. A brief overview on the main concepts of backward transit times, StorAge selection functions and forward transit time distributions is given in a logical-historical order, giving to the reader the primary instruments for a later comprehensive understating of the Transit Time Theory. Eventually, a numerical example helps to clarify the above concepts in a very simple and effective way.

Left anterior descending (LAD) coronary arterial injury is an underappreciated and rare consequence of ablation in the right ventricular outflow tract (RVOT). The authors present five cases of acute or subacute LAD injury after RVOT ablation. Most patients had fairly extensive ablation and two had coincident cardiac perforation. The patients reported also had a strikingly similar ECG morphology of their spontaneous ventricular arrhythmias. The authors’ report serves an important cautionary tale regarding ablation of intramural septal VAs.

Predictive Modeling of Lead Durability, An Important Step ForwardGeorge H. Crossley MD, FHRS, FACCVanderbilt Heart and Vascular Institute, Nashville, TN; and Cardiovascular Diseases Section, Vanderbilt University School of MedicineRWI: Dr. Crossley consults for Medtronic, Boston Scientific, and Phillips.Running Title: Lead Durability AnalysisWord Count: 893

Radiofrequency (RF) ablation for the treatment of atrial fibrillation has gained widespread acceptance since the concept was introduced by Haissaguerre et al a quarter of a century ago. High power short duration ablation has been widely adopted in the management of atrial fibrillation. Evidence for combining lesion size index and high power short duration ablation is lacking. In this issue of the journal, Cai et al evaluated the combination of HPSD with LSI with a focus on long-term efficacy.

AbstractBackground and objective: Many studies have demonstrated and recommended that biomarkers such as Procalcitonin (PCT), C-reactive protein (CRP), and serum amyloid A (SAA) be used to diagnose sepsis in adults. However, there is limited literature on the efficacy and safety of serum amyloid A in diagnosing sepsis in adults. Therefore, this study aims to establish the safety and effectiveness of SAA in diagnosing sepsis in adults.Methods: A thorough search was done across five electronic databases, Google Scholar, PubMed, Science Direct, EMBASE, and Cochrane, to acquire the relevant articles exploring the diagnosis of sepsis in adults using SAA. The data extracted include the concentration levels of SAA in the patients’ blood and the sensitivity and specificity of SAA. In the end, a meta-analysis was done on the included studies using Cochrane Review Manager Software version 5.4.Results: Ten primary articles were retrieved comprising RCTs and retrospective and prospective study designs. The outcomes of the included studies and meta-analysis indicated high concentration levels of SAA in the serum group than in the control, CRP, and PCT groups. The differences were statistically significant for control and CRP but insignificant with PCT, (MD 78.01, 95% CI 37.93 to 118.09; I2 = 98%; P < 0.0001), (MD 5.68, 95% CI 0.57 to 10.78; I2 = 99%; P = 0.03), and (MD -94.25, 95% CI -212.65 to 24.16; I2 = 92%; P = 0.12), respectively. Comparison of SAA and CRP levels in sepsis expression was insignificant at various post-diagnosis days (MD 1.64, 95% CI -2.01 to 5.30; I2 = 97%; P = 0.38). The studies included in this article revealed high sensitivity and specificity of SAA compared to CRP, PCT, and other biomarkers.Conclusion: This study demonstrates that serum amyloid A can also be used as a biomarker in diagnosing and predicting adult sepsis due to its high sensitivity, specificity, and concentration levels in expressing viral and bacterial infections.

A document by Nicholas Fogne Appiah. Click on the document to view its contents.

A document by Damien Ketcherside. Click on the document to view its contents.

Salt marshes are ecosystems with significant economic and environmental value. With accelerating rate in sea-level rise, it is not clear whether salt marshes will be able to retain their resilience. Field and numerical investigations have shown that storms play a significant role in marsh accretion and that they might be crucial to salt marsh survival to sea-level rise. Here we present the results from two studies (Pannozzo et al., 2021a,b; Pannozzo et al., 2022) that used numerical and field investigations to quantify the impact of storm surges on the sediment budget of salt marshes within different sea-level scenarios and to investigate how sediment transport pathways determine marsh response to storm sediment input. The Ribble Estuary, North-West England, was used as a test case. The hydrodynamic model Delft3D was used to simulate the estuary morpho-dynamics under selected storm surge and sea-level scenarios. In addition, sediment samples collected with a monthly frequency from different areas of the marsh were analysed with sediments collected from possible sources to integrate field observations with the numerical investigation of sediment transport pathways during stormy and non-stormy conditions. Results showed that, although sea-level rise threatens the estuary and marsh stability by promoting ebb dominance and triggering a net export of sediment, storm surges promote flood dominance and trigger a net import of sediment, increasing the resilience of the estuary and salt marsh to sea-level rise, with the highest surges having the potential to offset sea-level effects on sediment transport and sediment budget of the system. However, although storm sediment input resulted to be significant for the accretion of the marsh platform and particularly for the marsh interior, data showed that storms mainly remobilise sediments already present in the intertidal system and only to a minor extent transport new sediment from external sources.ReferencesPannozzo N. et al., 2021. Salt marsh resilience to sea-level rise and increased storm intensity. Geomorphology, 389 (4): 107825.Pannozzo N. et al., 2021. Dataset of results from numerical simulations of increased storm intensity in an estuarine salt marsh system. Data in Brief, 38 (6): 107336.Pannozzo N. et al., 2022. Sediment transport pathways determine the sensitivity of salt marshes to storm sediment input. In preparation.

A document by Yashvardhan Verma. Click on the document to view its contents.

The Government of India announced its commitment to reach net-zero greenhouse gas emissions by 2070 at the recent COP 26 summit. Modeling projections suggest that meeting this target would likely require substantial amounts of CO2 capture and storage (CCS) from large-point sources (LPS). Our analysis first reveals the key co-benefits for India in the adoption of CCS, viz. energy security, lower aggregate costs of carbon mitigation, higher resilience and lower stranded assets. For instance, we estimate that stranding of >100 GW and >70 GW of coal- and gas-fired power capacity could be avoided with the presence of CCS in the power sector mix.This analysis is further supplemented by our recent estimates on CO2 storage potential estimates in Indian geologic formations. Our results indicate that the storage capacity via enhanced oil recovery (EOR) is 1.2 GtCO2 after incorporating engineering and geologic constraints. Similarly, the storage capacity in unminable coal fields is estimated to be 3.5-6.3 GtCO2. Even though the combined storage potential in these formations is constrained, they should be actively considered within policy-making as they predominantly lie within areas of dense areas of LPS, thus creating possibilities of CCS hubs and clusters. In addition, 291 GtCO2 could be sequestered in saline aquifers and 97-316 GtCO2 in basalts; though, these values are subject to higher uncertainties. A number of saline aquifers may be characterized as having storage potential equivalent to several years of LPS emissions (>10 GtCO2) along with high storage feasibility.Our ongoing analysis attempts a more evolved approach towards source-sink mapping in India by combining the storage potential estimates with geospatial layers of LPS. Large power plants, which emit >20 MtCO2 annually, and high-purity CO2 sources such as refineries, are of particular interest. Preliminary source-sink mapping results show substantial clustering opportunities in eastern India, which has active coalbed methane extraction undertaken by five companies, and western India, with large industrial sources interspersed with EOR sites. The results of this analysis will also inform decision-makers on future LPS siting opportunities if a policy thrust on CCS is undertaken for meeting net-zero targets over the next two decades.

This response is to clarify some major confusions and misunderstandings in an abstract written by Zhang & Wen (the abstract hereafter) [1], in which they questioned the possibility of core-diffracted SKS phases (SPdKS-SKPdS) in the analysis of the seismic structure in the Earth’s outer core in  Zhou (2022) (the paper hereafter) [2]. The response is summarized below: 

In conventional fuel cells, a predominantly diffusive heat and mass transport is established in the diffusion layer. However, conventional fuel cells cannot ensure a heat and mass transport from the porous diffusion layer to the catalytic reaction layer that is sufficiently uniform for this purpose. The present study aims to provide a methodology for determining the characteristics of heat and mass transport in catalytic reaction layers. Numerical simulations are performed using computational fluid dynamics to better understand the characteristics of heat and mass transport in catalytic reaction layers of thermally integrated reformers. The present study aims to provide a fundamental understanding of the heat and mass transport in catalytic reaction layers of thermally integrated reformers. Particular emphasis is placed upon the dimensionless quantities involved in thermally integrated reformer with different catalytic reaction layer structures. The results indicate that a vapor-liquid equilibrium exists when the escape tendency of the specie from liquid to a vapor phase is exactly balanced with the escape phase at the same temperature and pressure. It may be beneficial to utilize the thermodynamic work potential provided by the transfer of heat to drive the separation process in the desired direction. If a chamber partition operates below its maximum heat transfer flux capability, this flux often can be increased by augmenting adjacent latent energy transfer which transfers through the partition as sensible energy. The external balance establishes the net enthalpy offset and therefore the temperature difference and the net amount of liquid that may be evaporated or condensed. A pure diffusive heat and mass transport would lead to an uneven reaction density or current density in the catalytic reaction layer, on account of a corresponding lack of uniformity in the heat and mass transport in the same catalytic reaction layer. A high pressure-drop in the thermally integrated reformer is to be avoided, since a high-pressure drop is associated with correspondingly high-power losses, which in turn results in a low overall efficiency. The conduit surface may vary along the general direction of flow to provide the zones either intermittently or preferably continuously as with an undulating membrane surface. When tubular membranes are employed, which membranes are preferably circular in cross section, the zones are preferably provided by circumferential furrowing.Keywords: Integrated reformers; Temperature differences; Membrane surfaces; Dimensionless quantities; Heat transport; Mass transport

Cerasus conradinae is an important germplasm resource of wild cherry in China. In this work, sampling was expanded and genetic evidence was added for further study. The current and future potential populations were predicted by niche model. Based on three cpDNA sequences and one nrDNA sequence, and combined with the phylogeographic evolution of 12 populations of 244 individuals in C.conradinae, the temporal and spatial patterns of genetic variation in C.conradinae were investigated, and the effects of genetic drift and differentiation as well as natural environmental factors on the genetic variation and evolutionary distribution of C.conradinae were elucidated. Finally, morphological evidence combined with molecular evidence was used to discuss the species definition of population variation and differentiation. The results showed that Central China, East China and Southwest China were the core regions for the conservation and utilization of germplasm resources of C.conradinae. Support for variant Cerasus conradinae var. ruburm is established. The genetic diversity of C.conradinae was high (Hd = 0.830; Rd = 0.798). There was genetic variation among populations of C.conradinae, and genealogical geographic structure existed among the populations and three geographical groups, but the genetic differentiation coefficient at each level was low. The gene exchange was obvious in Southwest China, and the differentiation was obvious in Central China. The population and three geographic groups do not reject the expectation of expansion model. Two distinct lineages (three geographic groups) were identified from the population of C.conradinae: Central China+ East China lineage and East China+ (Central China+Southwest China) lineage, two lineages of 4.38Mya occurred in the early Pliocene based on geographical isolation. The southeastern part of Eastern China near Mount Wuyi was the most likely refuge for C.conradinae. The results provided a theoretical basis for the classification and identification of C.conradinae and the protection and utilization of germplasm resources.

In eastern Indonesia, Sulawesi Island lies at the triple junction of the Australian, Sunda, and Phillippine Sea plates. The distinctive K-shape of Sulawesi, consisting of four arms (North, South, East, and Southeast), resulted from continuous geological evolution at different stages. Consequently, each arm has a different deformation style and tectonic setting. We studied the seismotectonics of Sulawesi using the updated dataset for earthquake seismicity and focal mechanisms, including additional supporting data. We grouped Sulawesi shallow part (< 60 kilometers) into six regions, while the deep part (60-400 kilometers) related to the Celebes Sea and Sula slabs. Regarding the shallow part, we found a lack of seismicity in the northern Palu-Koro fault and near the center of the North Sulawesi Trench, although these zones have high slip rates. On the deep part, the Celebes Sea slab showed an increasing dip as depth increased, whereas the Sula slab showed a steeply dipping slab. Moreover, the western Sula slab indicated an absence of shallow depth earthquakes (60–230 kilometers). Based on our investigations, we derived the following well-founded conclusions: (1) The northern Palu-Koro fault was beyond the high relative motion of the Makassar and North Sula blocks, resulting inactive seismicity. (2) A seismic gap or aseismic slip from the Celebes Sea subduction probably produced the low seismicity level near the center of the North Sulawesi Trench. (3) The shallow inactive seismicity in the western Sula slab might be due to the upper slab detaching during the first stage collision in the Early Miocene.

El Niño Southern Oscillation (ENSO) flavours in the tropical Pacific are studied from a regime perspective. Five recurring spatial patterns or regimes characterising the diversity of ENSO are established using a clustering approach applied to the HadISST sea surface temperature anomalies (SSTA). Two warm (eastern and central El Niño), two cold (basin wide and central La Niña) and a neutral reference regimes are found. Simulated SSTA by the models from the latest Coupled Model Intercomparison Project (CMIP6) are then matched to these reference regimes. This allows for a consistent assessment of the skill of the models in reproducing the reference regimes over the historical period and the change in these regimes under the high-warming Shared Socio-economic Pathway (SSP5.8.5) scenario. Results over the historical period show that models simulate well the reference regimes with some discrepancies. Models simulate overly strong and broad ENSO patterns and have issues in capturing the correct regime seasonality, persistence and transition between regimes. Some models also have difficulty simulating the frequency of regimes, the eastern El Niño regime in particular. In the future, eastern El Niño and central La Niña regimes are expected to be more frequent accompanied with a less frequent neutral regime. The central Pacific El Niño and La Niña regimes are projected to increase in amplitude and variability. Compared to previous studies, our approach gives a common characterisation across models and observations of the diversity of the warm and cold phases of ENSO at the same time established from observations.

An ensemble-based method for wave data assimilation is implemented using significant wave height observations from the globally distributed network of Sofar Spotter buoys and satellite altimeters. The Local Ensemble Transform Kalman Filter (LETKF) method generates skillful analysis fields resulting in reduced forecast errors out to 2.5 days when used as initial conditions in a cycled wave data assimilation system. The LETKF method provides more physically realistic model state updates that better reflect the underlying sea state dynamics and uncertainty compared to methods such as optimal interpolation. Skill assessment far from any included observations and inspection of specific storm events highlight the advantages of LETKF over an optimal interpolation method for data assimilation. This advancement has immediate value in improving predictions of the sea state and, more broadly, enabling future coupled data assimilation and utilization of global surface observations across domains (atmosphere-wave-ocean).

Sediment flows dynamics (erosion, transport and deposition) have been disrupted in South America (SA), a continent with the highest erosion and sediment transport rates globally. However, the magnitude and spatial distribution of the main drivers of changes have been poorly identified and explored. Here, we performed simulations using a hydrological-hydrodynamic-sediment model to comprehensively estimate the spatial and temporal sediment changes and trends in SA from 1984 to 2019. We found that 51% of the main SA rivers experienced significant changes in simulated sediment transport (QST) over this period, with 36% due to Amazon deforestation and river damming and 15% due to precipitation changes. We also estimated a 10% reduction in the average sediment delivery to the oceans. Deforestation was responsible for QST changes above 80% in some Amazon sites, and hydropower expansion led to a greater reduction of sediment flows (as high as 80-100%) in the Tocantins, Uruguay, Upper Paraná, lower São Francisco, Desaguadero, and Negro rivers. In addition, our results suggest that reservoirs built in the Amazon region in the last decade are also affecting sediment transport. Our modeling outputs provide unprecedented information about the status of sediment dynamics in SA, and a means to develop evidence-based strategies and transboundary policies related to continental-wide sediment dynamics and the conservation and restoration of ecosystems.

Classification of lightning produced VLF/LF signals plays crucial role in the detection and location of lightning flashes. The machine learning method has potential in the VLF/LF lightning signal classification. Traditional machine learning methods are data-driven and work in a black-box fashion, making the classification accuracy highly dependent on the size and quality of dataset. In this paper, an interpretable convolutional neural network model is proposed for VLF/LF lightning electric field waveform classification. Multi-scale convolutional kernels and shortcut connections are adopted in this model to enhance the ability to capture local waveform features. The CAM method is embedded in our model to open the black-box by visualizing the weight of different waveform features on the classification results. Based on the measured data from five different provinces in China, an accuracy of 98.5% is achieved in a four-type classification task including RS, active stage of IC, PB and NB. The correlation between the weight values of different waveform features and corresponding lightning discharge process are analyzed. It is found that the proposed model can extract decisive features of VLF/LF lightning signals closely related to the physical process of lightning discharges, which is similar to the human expert’s behavior. The proposed model is validated by using an open-source dataset from Argentina. It is indicated that the proposed model can resist the impact of unexpected waveform oscillation and achieve a higher accuracy of 98.39% than that of the support vector method. It is demonstrated that our model is less dependent on the training dataset.

Planetary boundary layer (PBL) schemes parameterize unresolved turbulent mixing within the PBL and free troposphere (FT). Previous studies reported that precipitation simulation over the Amazon in South America is quite sensitive to PBL schemes and the exact relationship between the turbulent mixing and precipitation processes is, however, not disentangled. In this study, regional climate simulations over the Amazon in January-February 2019 are examined at process level to understand the precipitation sensitivity to PBL scheme. The focus is on two PBL schemes, the Yonsei University (YSU) scheme, and the asymmetric convective model v2 (ACM2) scheme, which show the largest difference in the simulated precipitation. During daytime, while the FT clouds simulated by YSU dissipate, clouds simulated by ACM2 maintain because of enhanced moisture supply due to the enhanced vertical moisture relay transport process: 1) vertical mixing within PBL transports surface moisture to the PBL top, and 2) FT mixing feeds the moisture into the FT cloud deck. Due to the thick cloud deck over Amazon simulated by ACM2, surface radiative heating is reduced and consequently the convective available potential energy (CAPE) is reduced. As a result, precipitation is weaker from ACM2. Two key parameters dictating the vertical mixing are identified, p, an exponent determining boundary layer mixing and λ, a scale dictating FT mixing. Sensitivity simulations with altered p, λ, and other treatments within YSU and ACM2 confirm the precipitation sensitivity. The FT mixing in the presence of clouds appears most critical to explain the sensitivity between YSU and ACM2.