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● Gasification of cow dung was evaluated using Aspen Plus software.● Optimum reaction conditions were utilized to maximize hydrogen production.● Steam gasification can effectively increase hydrogen production.● Optimum hydrogen production was achieved at 800 °C and steam/biomass of 1.5 and 0.1 MPa. In this study, a biomass gasification model was developed and simulated based on Gibbs free energy minimization by using software Aspen Plus. Two reactors, RYIELD and RGIBBS, were moslty used. The biomass feedstock used was cow dung. The model was validated. The composition, H2/CO ratio and low heating value (LHV) of the resulting synthetic gas (also known as syngas) was estimated by changing the operating parameters of gasification temperatures, steam and biomass ratios and pressures. Simulation results showed that increased gasification temperature helped to elevate H2 and CO content and H2 peaked at 900 °C. When steam increased as the gasification agent, H2 production increased. However, the steam/biomass (S/B) ratio negatively affected CO and CH4, resulting in lower LHV. The optimal S/B ratio was 1.5. An increase in pressure lead to a decrease in H2 and CO content, so the optimal pressure for gasification was 0.1 MPa.

To achieve large-scale development of triboelectric nanogenerators (TENGs) for water wave energy harvesting and powering the colossal sensors widely distributed in the ocean, facile and scalable TENGs with high output are urgently required. Here, an elastic self-recovering hybrid nanogenerator (ES-HNG) is proposed for water wave energy harvesting and marine environmental monitoring. The elastic skeletal support of the ES-HNG is manufactured using three-dimensional (3D) printing technology, which is more conducive to the large-scale integration of the ES-HNG. Moreover, the combination of a TENG and an electromagnetic generator (EMG) optimizes the utilization of device space, leading to enhanced energy harvesting efficiency. Experimental results demonstrate that the TENG achieves a peak power output of 42.68 mW, and the EMG reaches a peak power output of 4.40 mW. Furthermore, various marine environment monitoring sensors, such as a self-powered wireless meteorological monitoring system, a wireless alarm system, and a water quality monitoring pen, have been successfully powered by the sophisticated ES-HNG. This work introduces an ES-HNG for water wave energy harvesting, which demonstrates potential in marine environment monitoring and offers a new solution for the sustainable development of the marine internet of things. [ABSTRACT FROM AUTHOR]

Escalating global climate change and the intensification of urban heatwaves have led to an increase in summer air conditioning cooling energy consumption. This phenomenon is particularly critical in tropical regions, as it may trigger an energy crisis. The rational setting of indoor thermal design parameters can help conserve energy to the maximum extent while ensuring thermal comfort for occupants. This study selected Haikou City, a unique tropical city in China, as the research location. Indoor environment measurements and a questionnaire survey were conducted with participants, and the outdoor thermal environment sensitivity, population attributes and differences in thermal sensation, thermal neutral temperature, and comfort range were calculated and analyzed. The following results were obtained. Based on the overall population, long-term residence, and temporary residence classification, the indoor thermal comfort needs of residents in tropical cities in Haikou were effectively identified. The actual thermal neutral temperature of the overall population is 25.7 °C, and 90% of the acceptable thermal comfort temperature range is 23.2 °C–28.0 °C. The actual thermal neutral temperature of the regular residents is 27.3 °C, and 90% of the acceptable thermal comfort temperature range is 23.3 °C–31.4 °C. The actual thermal neutral temperature of the temporary population is 25.5 °C, and 90% of the acceptable thermal comfort temperature range is 23.0 °C–28.0 °C. These research results have an important reference value for improving the setting of the temperature of air conditioning in tropical areas in summer and further reducing energy consumption, which is conducive to sustainable development. [ABSTRACT FROM AUTHOR]

As natural medicines in complementary and alternative medicine, edible and medicinal resources are being gradually recognized throughout the world. According to statistics from the World Health Organization, about 80% of the worldwide population has used edible and medicinal resource products to prevent and treat diseases. Polysaccharides, one of the main effective components in edible and medicinal resources, are considered ideal regulators of various biological responses due to their high effectiveness and low toxicity, and they have a wide range of possible applications for the development of functional foods for the regulation of common, frequently occurring, chronic and severe diseases. Such applications include the development of polysaccharide products for the prevention and treatment of neurodegenerative diseases that are difficult to control by a single treatment, which is of great value to the aging population. Therefore, we evaluated the potential of polysaccharides to prevent neurodegeneration by their regulation of behavioral and major pathologies, including abnormal protein aggregation and neuronal damage caused by neuronal apoptosis, autophagy, oxidative damage, neuroinflammation, unbalanced neurotransmitters, and poor synaptic plasticity. This includes multi-target and multi-pathway regulation involving the mitochondrial pathway, MAPK pathway, NF-κB pathway, Nrf2 pathway, mTOR pathway, PI3K/AKT pathway, P53/P21 pathway, and BDNF/TrkB/CREB pathway. In this paper, research into edible and medicinal resource polysaccharides for neurodegenerative diseases was reviewed in order to provide a basis for the development and application of polysaccharide health products and promote the recognition of functional products of edible and medicinal resources. [ABSTRACT FROM AUTHOR]

Accurate tracking of all components (including core, anvil, and cirrus) of deep convective systems (DCSs) throughout their lifecycle is key to quantifying their impacts on radiative forcing, especially of the anvil and cirrus. Here, a new Full‐tracking Algorithm for Convective Thunderstorm System is developed based on geostationary satellite. It successfully tracks DCSs starting from the initial core to complete dissipation of cirrus detrained from them, and integrates all the related components that split from the initial convective core into a whole DCS. Results show that more than half of the tracked DCSs experience splitting evolutions, with an average of eight sub‐cores during their lifetime. With tracking cirrus generated by DCSs, the lifetime of DCSs is lengthened by up to 10 hr, and their area is enlarged by 16% on average. Generally, long‐lived DCSs have lower cloud top temperature, greater rainfall, and larger area, with more frequent splitting evolutions than short‐lived DCSs. Additionally, DCSs always reach their peaks within 6 hr after initiation regardless of their lifetime. This paper provides a basis for further quantifying the evolution of DCS properties, their impacts on the global radiation budget, and the water cycle in the climate system. Key Points: A novel method is developed to track full components of deep convective systems (DCSs) from their initiation to total cirrus dissipationLifetime of DCSs is extended by up to 10 hr, and their area is enlarged by 16% averagely after continuously tracking their detrained cirrusIntegrated total rainfall amounts are comparably contributed between frequent but small and rare but large DCSs [ABSTRACT FROM AUTHOR]

This study evaluates ice particle size distribution and aspect ratio φ Multi-Radar Multi-Sensor (MRMS) dual-polarization radar retrievals through a direct comparison with two legs of observational aircraft data obtained during a winter storm case from the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) campaign. In situ cloud probes, satellite, and MRMS observations illustrate that the often-observed Kdp and ZDR enhancement regions in the dendritic growth layer can either indicate a local number concentration increase of dry ice particles or the presence of ice particles mixed with a significant number of supercooled liquid droplets. Relative to in situ measurements, MRMS retrievals on average underestimated mean volume diameters by 50% and overestimated number concentrations by over 100%. IWC retrievals using ZDR and Kdp within the dendritic growth layer were minimally biased relative to in situ calculations where retrievals yielded −2% median relative error for the entire aircraft leg. Incorporating φ retrievals decreased both the magnitude and spread of polarimetric retrievals below the dendritic growth layer. While φ radar retrievals suggest that observed dendritic growth layer particles were nonspherical (0.1 ≤ φ ≤ 0.2), in situ projected aspect ratios, idealized numerical simulations, and habit classifications from cloud probe images suggest that the population mean φ was generally much higher. Coordinated aircraft radar reflectivity with in situ observations suggests that the MRMS systematically underestimated reflectivity and could not resolve local peaks in mean volume diameter sizes. These results highlight the need to consider particle assumptions and radar limitations when performing retrievals. significance statement: Developing snow is often detectable using weather radars. Meteorologists combine these radar measurements with mathematical equations to study how snow forms in order to determine how much snow will fall. This study evaluates current methods for estimating the total number and mass, sizes, and shapes of snowflakes from radar using images of individual snowflakes taken during two aircraft legs. Radar estimates of snowflake properties were most consistent with aircraft data inside regions with prominent radar signatures. However, radar estimates of snowflake shapes were not consistent with observed shapes estimated from the snowflake images. Although additional research is needed, these results bolster understanding of snow-growth physics and uncertainties between radar measurements and snow production that can improve future snowfall forecasting. [ABSTRACT FROM AUTHOR]

Severe regional haze events, which are characterized by exceedingly high levels of fine particulate matter (PM), occur frequently in many developing countries (such as China and India), with profound implications for human health, weather, and climate. The occurrence of the haze extremes involves a complex interplay between primary emissions, secondary formation, and conducive meteorological conditions, and the relative contributions of the various processes remain unclear. Here we investigated severe regional haze episodes in 2013 over the Northern China Plain (NCP), by evaluating the PM production and the interactions between elevated PM and the planetary boundary layer (PBL). Analysis of the ground-based measurements and satellite observations of PM properties shows nearly synchronized temporal PM variations among the three megacities (Beijing, Baoding, and Shijiazhuang) in this region and a coincidence of the aerosol optical depth (AOD) hotspots with the three megacities during the polluted period. During the clean-to-hazy transition, the measured oxygenated organic aerosol concentration ([OOA]) well correlates with the odd-oxygen concentration ([Ox]=[O3]+[NO2]), and the mean [OOA] / [ Ox ] ratio in Beijing is much larger than those in other megacities (such as Mexico City and Houston), indicating highly efficient photochemical activity. Simulations using the Weather Research and Forecasting (WRF) model coupled with an explicit aerosol radiative module reveal that strong aerosol–PBL interaction during the polluted period results in a suppressed and stabilized PBL and elevated humidity, triggering a positive feedback to amplify the haze severity at the ground level. Model sensitivity study illustrates the importance of black carbon (BC) in the haze–PBL interaction and the aerosol regional climatic effect, contributing to more than 30 % of the PBL collapse and about half of the positive radiative forcing on the top of the atmosphere. Overall, severe regional haze exhibits strong negative radiative forcing (cooling) of - 63 to - 88 Wm-2 at the surface and strong positive radiative forcing (warming) of 57 to 82 Wm-2 in the atmosphere, with a slightly negative net radiative forcing of about - 6 Wm-2 on the top of the atmosphere. Our work establishes a synthetic view for the dominant regional features during severe haze events, unraveling rapid in situ PM production and inefficient transport, both of which are amplified by atmospheric stagnation. On the other hand, regional transport sufficiently disperses gaseous aerosol precursors (e.g., sulfur dioxide, nitrogen oxides, volatile organic compounds, and ammonia) during the clean period, which subsequently result in rapid in situ PM production via photochemistry during the transition period and via multiphase chemistry during the polluted period. Our findings highlight the co-benefits for reduction in BC emissions, which not only improve local and regional air quality by minimizing air stagnation but also mitigate the global warming by alleviating the positive direct radiative forcing. [ABSTRACT FROM AUTHOR]

Most existing cloud models tend to overestimate the size of cloud ice particles and underestimate their concentration. This emphasizes the need to provide a reliable observational reference to optimize cloud model performance, particularly in areas of high concentration of ice at high altitudes. The dual‐polarization radars give the community a unique opportunity to quantify cloud ice with a good accuracy using polarimetric radar retrievals. In this study, we utilize the network of operational WSR‐88D radars to build a climatology of the vertical profiles of radar variables, such as radar reflectivity Z, differential reflectivity ZDR, and specific differential phase KDP as well as the radar‐retrieved vertical profiles of ice water content (IWC) above the melting layer and liquid water content below it, mean volume diameter Dm, and total number concentration Nt of ice and liquid particles. Such climatology was created for continental/marine mesoscale convective systems (MCSs) and tropical cyclones including hurricanes. The dataset includes 13 continental MCSs, 10 marine MCSs, and 11 tropical cyclones. Separate statistics of the "background" vertical profiles and the ones associated with high IWC aloft have been obtained in the course of this study. It is shown that continental MCSs exhibit larger size of ice in lower concentration aloft compared to the marine MCSs and especially tropical cyclones/hurricanes. A combination of high KDP and low Z aloft signifies lower Dm, higher Nt, and often substantial IWC. Key Points: Climatology of the vertical profiles of polarimetric radar variables and microphysical parameters is documented for different storm typesAreas of high ice water content (IWC) in clouds are characterized by high values of specific differential phase combined with low reflectivityTropical clouds have smaller size ice in higher concentration compared to their continental counterparts with comparable IWC [ABSTRACT FROM AUTHOR]

Severe regional haze events, which are characterized by exceedingly high levels of fine particulate matter (PM), occur frequently in many developing countries (such as China and India), with profound implications for human health, weather, and climate. The occurrence of the haze extremes involves a complex interplay between primary emissions, secondary formation, and conducive meteorological conditions, and the relative contributions of the various processes remains unclear. Here we investigated severe regional haze episodes in 2013 over the Northern China Plain (NCP), by evaluating the PM production and the interactions between elevated PM and the planetary boundary layer (PBL). Analysis of the ground-based measurements and satellite observations of PM properties shows nearly synchronized temporal PM variations among the three megacities (Beijing, Baoding, and Shijiazhuang) in this region and a coincidence of the aerosol optical depth (AOD) hotspots with the three megacities during the polluted period. During the clean-to-hazy transition, the measured oxygenated organic aerosol concentration ([OOA]) well correlates with the odd-oxygen concentration ([Ox] = [O3] + [NO2]), and the mean [OOA]/[Ox] ratio in Beijing is much larger than those in other megacities (such as Mexico City and Houston), indicating highly efficient photochemical activity. Simulations using the Weather Research and Forecasting (WRF) model coupled with an explicit aerosol radiative module reveal that strong aerosol-PBL interaction during the polluted period results in a suppressed and stabilized PBL and elevated humidity, triggering a positive feedback to amplify the haze severity at the ground level. Model sensitivity study illustrates the importance of black carbon (BC) in the haze-PBL interaction and the aerosol regional climatic effect, contributing to more than 30% of the PBL collapse and about half of the positive radiative forcing on the top of the atmosphere. Overall, severe regional haze exhibits strong negative radiative forcing (cooling) of -63 to -88 W m-2 at the surface and strong positive radiative forcing (warming) of 57 to 82 W m-2 in the atmosphere, with a slightly negative net radiative forcing of about -6 W m-2 on the top of the atmosphere. Our work establishes a synthetic view for the dominant regional features during severe haze events, unraveling rapid in-situ PM production and inefficient transport, both of which are amplified by atmospheric stagnation. On the other hand, regional transport sufficiently disperses gaseous aerosol precursors (e.g., sulfur dioxide, nitrogen oxides, volatile organic compounds, and ammonia) during the clean period, which subsequently result in rapid in-situ PM production via photochemistry during the transition period and via multiphase chemistry during the polluted period. Our findings highlight the co-benefits for reduction in BC emissions, which not only improve local and regional air quality by minimizing air stagnation but also mitigate the global warming by alleviating the positive direct radiative forcing. [ABSTRACT FROM AUTHOR]

Purpose: To investigate the significance of collagen in predicting the aggressiveness of rectal tumors in patients, examined in vivo based on tomoelastography quantified stiffness and ex vivo by histologically measured collagen volume fraction (CVF). Experimental Design: 170 patients with suspected rectal cancer were prospectively enrolled and underwent preoperative magnetic resonance imaging (MRI) and rectal tomoelastography, a technique based on multifrequency magnetic resonance elastography. Histopathologic analysis identified eighty patients with rectal cancer who were divided into subgroups by tumor-node (TN) stage, prognostic stage, and risk level. Rectal tumor stiffness was correlated with histopathologic CVF. Area-under-the-curve (AUC) and contingency analysis were used to evaluate the performance of rectal stiffness in distinguishing tumor stages which was compared to standard clinical MRI Results: In vivo tomoelastography revealed that rectal tumor stiffened significantly with increased TN stage (p<0.05). Tumors with poorly differentiated status, perineural and lymphovascular invasion also displayed higher stiffness than well-to-moderately differentiated, noninvasive tumors (all p<0.05). Similar to in vivo stiffness, CVF indicated an abnormally high collagen content in tumors with perineural invasion and poor differentiation status. CVF was also positively correlated with stiffness (p<0.05). Most importantly, both stiffness (AUROC: 0.82) and CVF (AUROC: 0.89) demonstrated very good diagnostic accuracy in detecting rectal tumors that have high risk for progressing to an aggressive state with poorer prognosis. Conclusion: In human rectal carcinomas, overexpression of collagen is correlated with increased tissue stiffness and high risk for tumor advancing more aggressively. In vivo tomoelastography quantifies rectal tumor stiffness which improves the diagnostic performance of standard MRI in the assessment of lymph nodes metastasis. Therefore, in vivo stiffness mapping by tomoelastography can predict rectal tumor aggressiveness and add diagnostic value to MRI. [ABSTRACT FROM AUTHOR]

Polarimetric radar observations from the NEXRAD WSR-88D operational radar network in the contiguous United States, routinely available since 2013, are used to reveal three prominent microphysical signatures in landfalling tropical cyclones: 1) hydrometeor size sorting within the eyewall convection, 2) vertical displacement of the melting layer within the inner core, and 3) dendritic growth layers within stratiform regions of the inner core. Size sorting signatures within eyewall convection are observed with greater frequency and prominence in more intense hurricanes, and are observed predominantly within the deep-layer environmental wind shear vector-relative quadrants that harbor the greatest frequency of deep convection (i.e., downshear and left-of-shear). Melting-layer displacements are shown that exceed 1 km in altitude compared to melting-layer altitudes in outer rainbands and are complemented by analyses of archived dropsonde data. Dendritic growth and attendant snow aggregation signatures in the inner core are found to occur more often when echo-top altitudes are low (≤10 km MSL), nearer the −15°C isotherm commonly associated with dendritic growth. These signatures, uniquely observed by polarimetric radar, provide greater insight into the physical structure and thermodynamic characteristics of tropical cyclones, which are important for improving rainfall estimation and the representation of tropical cyclones in numerical models. [ABSTRACT FROM AUTHOR]

Cataluminescence (CTL), a kind of chemiluminescence emitted at the gas–solid interface during catalytic oxidation reactions, has been developed for many decades as a novel and promising gas sensing technique. In this review, we introduce the origin, basic principles, and mechanisms of CTL sensing systems and summarize the recent advances in CTL sensing, focusing on methodologies and extended applications such as in gas selective monitoring, recognition of complex mixture, evaluation for catalytic property and use in high‐performance liquid chromatography, capillary electrophoresis and gas chromatography detectors. In addition, development prospects and some challenges facing CTL‐based sensing are also discussed. [ABSTRACT FROM AUTHOR]

Changes in land cover and aerosols resulting from urbanization may impact convective clouds and precipitation. Here we investigate how Houston urbanization can modify sea-breeze-induced convective cloud and precipitation through the urban land effect and anthropogenic aerosol effect. The simulations are carried out with the Chemistry version of the Weather Research and Forecasting model (WRF-Chem), which is coupled with spectral-bin microphysics (SBM) and the multilayer urban model with a building energy model (BEM-BEP). We find that Houston urbanization (the joint effect of both urban land and anthropogenic aerosols) notably enhances storm intensity (by ∼ 75 % in maximum vertical velocity) and precipitation intensity (up to 45 %), with the anthropogenic aerosol effect more significant than the urban land effect. Urban land effect modifies convective evolution: speed up the transition from the warm cloud to mixed-phase cloud, thus initiating surface rain earlier but slowing down the convective cell dissipation, all of which result from urban heating-induced stronger sea-breeze circulation. The anthropogenic aerosol effect becomes evident after the cloud evolves into the mixed-phase cloud, accelerating the development of storm from the mixed-phase cloud to deep cloud by ∼ 40 min. Through aerosol–cloud interaction (ACI), aerosols boost convective intensity and precipitation mainly by activating numerous ultrafine particles at the mixed-phase and deep cloud stages. This work shows the importance of considering both the urban land and anthropogenic aerosol effects for understanding urbanization effects on convective clouds and precipitation. [ABSTRACT FROM AUTHOR]

Hypotheses have been proposed for decades about the effect of activated cloud condensation nuclei (CCN) on delaying the warm rain process, invigorating deep convective cloud vertical development, and enhancing mixed‐phase processes. Observational support has been only qualitative with mixed results due to the lack of regional measurements of CCN concentration (NCCN), while simulations have not produced a robust consensus. Quantitative assessments of these relationships became possible with the advent of NCCN retrievals from satellites; when combined with measurements by polarimetric radar and Lightning Mapping Array (LMA), tracking convective cells observed on radar and examining precipitation properties throughout the cells' life cycle has permitted the study of the impact of NCCN on cloud and precipitation characteristics. We composited more than 2,800 well‐tracked cells in the Houston region and stratified them by NCCN, convective available potential energy (CAPE), and urban/rural locations. The results show that increased NCCN invigorates the convection until saturation near NCCN = 1,000 cm3; increasing NCCN from ~400 to an optimum of ~1,000 cm3 increases lightning activity by an order of magnitude. A further increase in CCN decreases lightning rates. Adding CAPE enhances lightning only under low NCCN (e.g., less than 500 cm3). The presence of the urban area enhances lightning for similar NCCN concentrations, although this applies mainly under low NCCN conditions. The urban heat island as manifested by cloud base height cannot explain this observation. It is suspected that the urban ultrafine aerosols contribute to the storm electrification. Plain Language Summary: Deep convective clouds are propelled by rising air currents and are composed of cloud droplets that nucleate on CCN aerosols. Isolating the effects of CAPE and NCCN on cloud properties has been an unresolved challenge. Tracking the time‐height evolution of a large number of individual summer convective storm cells in the Houston area under various CAPE and NCCN shows their relations to the storm's dynamics, precipitation, and electrification processes. The results show that increased NCCN invigorates the convection, produces larger hydrometeors, and enhances lightning. Variability in NCCN was found to be more important than variability in CAPE, cloud base height, and wind shear in explaining the variability of the vigor and electrification of deep convective clouds in the study area. Key Points: Increased CCN invigorates convection, produces larger hydrometeors, and enhances lightningCCN invigoration effect saturates near NCCN = 1,000 cm3 in an environment with similar CAPECCN is more important than CAPE in explaining the variability of the vigor and electrification of storms after convection is initiated [ABSTRACT FROM AUTHOR]

Graphene lateral spin valves (LSVs) are promising devices for future memory and magnetic field sensing applications. In this article, we study the dependence of the nonlocal spin resistance, $\Delta {R}_{{\text {NL}}}$ , and the baseline resistance, ${R}_{{\text {BS}}}$ , as a function of the graphene channel width, ${W}$. The scaling trend is quantitatively assessed by using graphene deposited by chemical vapor deposition, which provides a large number of devices with consistent performance. As ${W}$ is scaled from 10 to $0.5~\mu \text{m}$ , the change in $\Delta {R}_{{\text {NL}}}$ matches the theory of contact-induced spin relaxation with a current spin polarization of 3%–5% and a spin diffusion length of $\lambda _{s} = 1.5$ – $2.5~\mu \text{m}$. We also observe a systematic and dramatic decrease in ${R}_{{\text {BS}}}$ , which we attribute to the reduction in charge current spreading. However, we find in the narrowest devices that a small ${R}_{{\text {BS}}}$ remains that arises due to thermoelectric effects, and this trend is confirmed using gate voltage- and charge current-dependent analyses. Finally, we introduce a nonideality factor, ${m} = \vert {R}_{{\text {BS}}} / \Delta {R}_{{\text {NL}}}\vert $ , as a figure of merit to describe the suppression of the baseline relative to the spin signal. In an LSV with ${L} = {1.5}\,\,\mu \text{m}$ , ${W} = {0.5}\,\,\mu \text{m}$ , and n-type conduction, the nonideality factor is as low as ${m} = {0.0252}\,\,\pm \,\,0.0202$ at room temperature showing that nearly ideal bipolar and symmetric spin signals can be achieved in graphene LSVs. [ABSTRACT FROM AUTHOR]

Polarimetric radars make it possible to retrieve information on hydrometeors types, sizes and concentrations. Additional information on cloud electrification can be obtained from Lightning Mapping Arrays (LMAs). To study the development time and height of the hydrometeors and electrification require tracking their evolution within the lifecycle of convective cells. A new methodology for multi-cell identification and tracking (MCIT) is presented in this study. The algorithm in this study is different from traditional tracking methods; this new algorithm is applied to time series of radar volume scans. It tracks local maxima of vertically integrated liquid (VIL) water by identifying the two cells in consecutive radar scans that have maximum common VIL. The vertical profile of the polarimetric variables is used for constructing the time-height cross section of the cells' microphysical properties around the peak reflectivity as a function of height. The LMA sources that occur within the cell area are integrated as a function of height as well for each time step, as determined by the radar volume scans. The result of the tracking can provide insights on the evolution of storms, hydrometer types, precipitation initiation and cloud electrification under different thermodynamic and aerosol conditions. The details of the MCIT algorithm, its products and their performance for different type of storms are described in this paper. • Development of a novel cloud cell tracking algorithm. • Tracking cloud types include: convective and stratiform, isolated and clustered. • Tracking cloud cells through maturation into stratiform storm elements. • Use a synergy of polarimetric radar, satellite, lightning detection and model data. • Algorithm has flexible output options and possibilities for further studies. [ABSTRACT FROM AUTHOR]

Stochastic computing (SC) is a promising technology that can be used for low-cost hardware designs. However, SC suffers from its long latency. Although parallel processing can efficiently shorten the latency, duplicated stochastic number generators (SNGs) are necessary, which cause substantial hardware overhead. This paper proposes a scalable SNG based on the spin-Hall-effect (SHE), which is capable of generating multiple independent stochastic streams simultaneously. The design takes advantages of the efficient charge-to-spin conversion from the Spin-Hall material and the intrinsic stochasticity of nanomagnets. Compared to previous spintronic SNGs, the SHE-SNG can reduce the area by $1.6\times -7.8\times $ and the power by $4.9\times -13\times $ while increasing the degree of parallelism from 1 to 16. Compared to CMOS-based SNGs, the proposed SNG obtained $24\times -120\times $ and $53\times $ reduction in terms of area and power, respectively. Finally, three benchmarks were implemented, and the results indicate that SC implementations with the proposed SHE-SNG can achieve $1.2\times -29\times $ reduction of hardware resources compared to implementations with previous CMOS- and spintronic-based designs while scaling the degree of parallelism from 1 to 64. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • NiO, a new cataluminescence sensing material, was synthesized by a simple template-free hydrothermal method. • Camellia-like NiO with high specific surface area showed excellent sensing performance towards H 2 S. • The sensing mechanism was studied which proved the main emission peak is from SO 2 *. Abstract In this work, three different microstructures of NiO nanomaterials including tremella, camellia and hexagonal nanosheets were successfully synthesized by a simple template-free hydrothermal method. Among them, camellia-like NiO was reported and applied to cataluminescence (CTL) for the first time. SEM, TEM, XRD, XPS, BET and BJH were employed to characterize the as-prepared samples. As sensing materials, these NiO with various morphologies showed different CTL capabilities to detect H 2 S, and the camellia-like NiO exhibited the best catalytic performance with high sensitivity and selectivity, which may be attributed to the synergistic effect of its high specific surface area, porous nanostructure, as well as the surface adsorption oxygen. After optimization, a good linear relationship was obtained in the range of 0.8–30.8 ppm and the detection limit (S/N = 3, LOD) was 0.3 ppm. Sixteen common volatile organic compounds (VOCs), such as carbon disulfide, ethyl mercaptan and formaldehyde, were discussed as possible interferent components, and the sensing mechanism of the CTL sensing towards H 2 S was discussed in detail. Camellia-like NiO could be used as a new sensing material for H 2 S monitoring. [ABSTRACT FROM AUTHOR]

Cataluminescence (CTL), one kind of the chemiluminescence, generates on the surface of solid catalyst during a heterogeneous catalytic oxidation reaction with the advantages of high sensitivity, fast response, simple instrument and longtime stability. This review provides the advances in CTL, mainly discussed the developments of sensing materials, detection technologies and application of CTL in recent 3 years. Also, we proposed various prospects and expectations of CTL-based sensor system at the end of this paper. [ABSTRACT FROM AUTHOR]