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The partial replacement of Portland cement by aluminosilicate-rich supplementary cementitious materials (SCMs) represents a valuable approach to lower the CO2 footprint of concrete. However, SCMs alter the composition and structure of the principal binding component, calcium-alumino-silicate-hydrate (C-(A)-S-H), a less-crystalline aluminum-substituted calcium silicate hydrate. The uptake and structural impact of alkalis and aluminum are investigated for synthesized C-(A)-S-H phases with different Ca/Si and Al/Si ratios and alkali (Na+) contents, using solid-state Na-23, Al-27, and Si-29 NMR as principal analytical tools. Si-29{H-1} CP/MAS NMR data propose that the -87 ppm resonance originates from a second type of Q(2) pairing sites most likely in the middle of octameric or longer silicate units. This assignment along with constraints induced by the silicate dreierketten structure results in reliable simulations of the Si-29 NMR spectra. A quantitative 1:1 relation between the Al/Si ratios from Si-29 NMR and the content of fourfold-coordinated Al from Al-27 NMR is observed, which reveals that the Si-29 Q(p)(2)(1Al) resonance is only associated with Al(IV) in C-(A)-S-H. Combined analysis of the Al-27 and Si-29 NMR spectra can account for sixfold-coordinated AI being present in the bridging sites of the silicate chains as proposed very recently. The sodium uptake is found to decrease with increasing Ca/Si ratio. For C-(A)-S-H phases with high Ca/Si ratios (Ca/Si greater than or similar to 1.0), sodium promotes the incorporation of Al(IV) in the silicate chains but not at low Ca/Si ratios (Ca/Si less than or similar to 1.0). The results indicate that the mutual uptake of alkali and AI ions is governed by more than one mechanism and depends on the composition/structure of the C-(A)-S-H phase.

BACKGROUND During winemaking, after extraction from the skins, anthocyanins and tannins adsorb onto the pulp flesh cell walls. This study aims to quantify the amounts adsorbed and their impact on wine composition, the impact of variety and ethanol on adsorption, and whether the presence of anthocyanins plays a role and impacts tannin adsorption. RESULTS Anthocyanin and tannin fractions obtained by mimicking winemaking conditions were mixed with fresh flesh cell walls of two varieties: Carignan and Grenache. Adsorption isotherms were measured. Adsorption of tannins was higher with Carignan than with Grenache and decreased when the ethanol content increased. In comparison, anthocyanins were adsorbed in small amounts, and their mixing with tannins had no impact on their adsorption. The differences were related to differences in pulp cell wall composition, particularly in terms of extensins and arabinans. CONCLUSION Adsorption of tannins, which can reach 50% of the initial amount, depends on the pulp cell wall composition. This needs to be further investigated. This article is protected by copyright. All rights reserved.

The coronavirus disease-2019 pandemic affected the countries differently. South Africa is a middle-income country with a struggling economy and a resource-constrained public healthcare system. Three aspects of the pandemic in South Africa are examined, the lockdown and its effect on personal freedoms, how health care resources were used and the novel stratification of health workers into vulnerability categories. It is a perspective written after experiencing the first pandemic peak in 2020.

In this study, dimensional, physical, visual and thermal comfort properties of fabrics knitted with elastic core cotton slub yarns were analyzed. The yarn production methods (core slub yarn and conventional slub yarn) were also compared according to the fabric properties. Additionally, the influence of slub yarn production parameters (slub thickness ratio and slub length) on the previously mentioned properties were investigated. The results indicated that elastic core fabrics produced with slub length 10 mm exhibited lower spirality property than the other fabrics. Due to their higher thermal conductivity, thermal absorptivity and relative water vapor permeability properties, fabrics produced with slub length 10 mm or slub thickness ratio 2.0 can be preferable for hot climate clothes without regard to yarn production techniques., Ege University Scientific Research Project Office [18-MUH-033], This work was supported by the Ege University Scientific Research Project Office [18-MUH-033].

ispartof: QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY vol:147 issue:735 pages:825-846 status: published

A recent study based on observations has shown that after precipitation over tropical oceans rather shallow temperature structures occur in the lower troposphere and that their magnitude depends on climatological low- to midtropospheric humidity. As any process that produces temperature perturbations in the lower troposphere can be of great significance for the formation of atmospheric deep convection, the vertical temperature structure associated with evaporation of stratiform precipitation and its sensitivity to low- to midtropospheric humidity are studied by conducting three-dimensional, high-resolution, idealized simulations with the Advanced Research version of the Weather Research and Forecasting (WRF) Model. In the simulations, rainwater with mixing ratio and number concentration characteristic of stratiform precipitation associated with mesoscale convective systems is added in a large round area at roughly 560 hPa. Evaporative cooling and subsidence warming below result in a cold anomaly at roughly 560–750 hPa and, especially, a warm anomaly at roughly 750–900 hPa. The cold-over-warm anomalies are stronger with smaller low- to midtropospheric relative humidity in the initial conditions, with the maximum magnitude of the warm anomaly ranging between 0.7 and 1.2 K. The temperature anomalies propagate to the environment and still remain present after precipitation stops. The results show that evaporation of stratiform precipitation alone can lead to temperature structures, which are on the same order of magnitude as the observed ones, that potentially inhibit subsequent convection by increasing convective inhibition. Therefore, the representation of microphysical processes affecting the location, amount, and vertical and horizontal distribution of stratiform precipitation and its evaporation in numerical models requires special attention. A recent study based on observations has shown that after precipitation over tropical oceans rather shallow temperature structures occur in the lower troposphere and that their magnitude depends on climatological low- to midtropospheric humidity. As any process that produces temperature perturbations in the lower troposphere can be of great significance for the formation of atmospheric deep convection, the vertical temperature structure associated with evaporation of stratiform precipitation and its sensitivity to low- to midtropospheric humidity are studied by conducting three-dimensional, high-resolution, idealized simulations with the Advanced Research version of the Weather Research and Forecasting (WRF) Model. In the simulations, rainwater with mixing ratio and number concentration characteristic of stratiform precipitation associated with mesoscale convective systems is added in a large round area at roughly 560 hPa. Evaporative cooling and subsidence warming below result in a cold anomaly at roughly 560–750 hPa and, especially, a warm anomaly at roughly 750–900 hPa. The cold-over-warm anomalies are stronger with smaller low- to midtropospheric relative humidity in the initial conditions, with the maximum magnitude of the warm anomaly ranging between 0.7 and 1.2 K. The temperature anomalies propagate to the environment and still remain present after precipitation stops. The results show that evaporation of stratiform precipitation alone can lead to temperature structures, which are on the same order of magnitude as the observed ones, that potentially inhibit subsequent convection by increasing convective inhibition. Therefore, the representation of microphysical processes affecting the location, amount, and vertical and horizontal distribution of stratiform precipitation and its evaporation in numerical models requires special attention.

The offshore extent of Antarctic katabatic winds exert a strong control on sea ice production and the formation of polynyas. In this study, we combine ground-based remotely-sensed and meteorological measurements at Dumont d’Urville (DDU) station, satellite images and simulations with the WRF model to analyze a major katabatic wind event in Adélie Land. Once developed over the slope of the ice sheet, the katabatic flow experiences an abrupt transition near the coastal edge. The transition consists in a sharp increase in the boundary layer depth, a sudden decrease in wind speed and a decrease in Froude number from 3.5 to 0.3. This so-called ‘katabatic jump’ visually manifests as a turbulent ‘wall’ of blowing snow in which updrafts exceed 5 m s −1 . The wall reaches heights of 1000 m and its horizontal extent along the coast is more than 400 km. By destabilizing the boundary-layer downstream, the jump favors the trapping of a gravity wave train with an horizontal wavelength of 10.5 km. The trapped gravity waves exert a drag that significantly slows down the low-level outflow. Moreover, atmospheric rotors form below the first wave crests. The wind speed record measured at DDU in 2017 (58.5 m s −1 ) is due to the vertical advection of momentum by a rotor. A statistical analysis of observations at DDU reveals that katabatic jumps and low-level trapped gravity waves occur frequently over coastal Adélie Land. It emphasizes the important role of such phenomena in the coastal Antarctic dynamics.

Recent growth in remote studies has shown the effectiveness of digital health technologies in recruiting and monitoring the health and behavior of large and diverse populations of interest in real-world settings. However, retaining and engaging participants to monitor their long-term health trajectories has remained a significant challenge. Uneven participant engagement combined with attrition over the course of the study could lead to imbalanced study cohort and data collection, which may severely impact the generalizability of real-world evidence.We report findings from long-term participant retention and engagement patterns in a multinational remote digital depression study with up to two years of real-world behavior monitoring. In total, real-world engagement data from 614 participants with 14,964 surveys and 135,014 days of phone passive and wearable (Fitbit) data were analyzed using survival and unsupervised clustering methods. A considerable proportion of participants (N=415; 67.6%) were retained during the first 43 weeks of the study. Clustering participants’ long-term usage data of study apps and wearables showed three distinct subgroups with different engagement levels (most, middle, and least). Notable findings comparing participants' characteristics across these subgroups were: 1.) Participants (33.2%; N= 204) with the highest baseline depression severity (4 points higher PHQ8 score, p < .01) were in the least engaged group (median bi-weekly surveys completed = 4) compared to the most engaged group (37.6%; N = 231) that on average completed 20 bi-weekly surveys. 2.) A considerable proportion (44.6%; N = 91) of participants in the least engaged group still contributed wearable data for up to 10 months. 3.) The participants in the least engaged group also took significantly longer in responding to surveys in naturalistic settings (3.8 hours more, p < .001) and were younger (age difference = 5 years, p < .01) in comparison to participants in the most engaged group. Our findings show various factors such as socio-demographics, app usage behavior, and depression severity can be linked to the long-term retention and density of real-world data collected in remote digital research studies. Finally, passive data gathered from wearables without additional participant burden showed advantages over active survey data for long-term monitoring, providing greater contiguity and duration of data collected. Together these findings could inform the design of future remote digital health research studies to enable equitable and balanced health data collection from diverse target populations.

High temperature oxidic systems are encountered in nature (magma chambers) and pyrometallurgical processes. In these systems, the solidification of the oxidic liquids influences the flow, the cooling after tapping, the viscosity and rheological behaviour within the reactor and also the freeze lining behaviour. On the mesoscale, the phase field concept has proved to be a very powerful tool for modeling crystallizing microstructures. However, application of the method to slag solidification is still challenging. In this work, we present a phase field model to simulate the faceted crystallization of Fe3O4 in a quaternary FeO-Fe2O3-Cu2O-SiO2 melt under different partial pressures of oxygen to solve certain problems encountered related to more realistic simulations in oxidic systems. The ratio of FeO/Fe2O3 at the upper boundary is in equilibrium with the oxygen fugacity of the atmosphere, while conserving Fe. Two-dimensional simulations are performed with different varying oxygen fugacity in the atmosphere. For the considered composition range, the growth velocities of the spinel crystals increase with decreasing oxygen fugacity. One of the focus points in creating more realistic phase field models is the incorporation of the thermodynamic driving forces in multicomponent multiphase-field models by coupling to thermodynamic databases. The first part of this work used a tabular method. However, as the number of components in the system increases, the number of thermodynamic data points also increases exponentially, and so do the computational and memory requirements. A possible solution for this might be the use of a canonical polyadic decomposition of the tensors containing the thermodynamic data. In this way, the huge tensors are approximated well by compact multilinear models or decompositions. This promising solution has been applied in the second part of this work on the same oxidic liquid-solid system.

Can we improve the modeling of urban land surface processes with machine learning (ML)? A prior comparison of urban land surface models (ULSMs) found that no single model is 'best' at predicting all common surface fluxes. Here, we develop an urban neural network (UNN) trained on the mean predicted fluxes from 22 ULSMs at one site. The UNN emulates the mean output of ULSMs accurately. When compared to a reference ULSM (Town Energy Balance; TEB), the UNN has greater accuracy relative to flux observations, less computational cost, and requires fewer input parameters. When coupled to the Weather Research Forecasting (WRF) model using TensorFlow bindings, WRF-UNN is stable and more accurate than the reference WRF-TEB. Although the application is currently constrained by the training data (1 site), we show a novel approach to improve the modeling of surface fluxes by combining the strengths of several ULSMs into one using ML., Published version

The Schur decomposition of a square matrix $A$ is an important intermediate step of state-of-the-art numerical algorithms for addressing eigenvalue problems, matrix functions, and matrix equations. This work is concerned with the following task: Compute a (more) accurate Schur decomposition of $A$ from a given approximate Schur decomposition. This task arises, for example, in the context of parameter-dependent eigenvalue problems and mixed precision computations. We have developed a Newton-like algorithm that requires the solution of a triangular matrix equation and an approximate orthogonalization step in every iteration. We prove local quadratic convergence for matrices with mutually distinct eigenvalues and observe fast convergence in practice. In a mixed low-high precision environment, our algorithm essentially reduces to only four high-precision matrix-matrix multiplications per iteration. When refining double to quadruple precision, it often needs only 3-4 iterations, which reduces the time of computing a quadruple precision Schur decomposition by up to a factor of 10-20.

A recently developed, height-distributed urban drag parametrization is tested with the London Model, a sub-kilometre resolution version of the Met Office Unified Model over Greater London. The distributed-drag parametrization requires vertical morphology profiles in the form of height-distributed frontal-area functions, which capture the full extent and variability of building heights. London’s morphology profiles are calculated and parametrized by an exponential distribution with the ratio of maximum to mean building height as the parameter. A case study evaluates the differences between the new distributed-drag scheme and the current London Model setup using the MORUSES urban land-surface model. The new drag parametrization shows increased horizontal spatial variability in total surface stress, identifying densely built-up areas, high-rise building clusters, parks, and the river. Effects on the wind speed in the lower levels include a lesser gradient and more heterogeneous wind profiles, extended wakes downwind of the city centre, and vertically growing perturbations that suggest the formation of internal boundary layers. The surface sensible heat fluxes are underpredicted, which is attributed to difficulties coupling the distributed momentum exchange with the surface-based heat exchange., Quarterly Journal of the Royal Meteorological Society, 147 (741), ISSN:0035-9009, ISSN:1477-870X

The COVID-19 pandemic has disrupted all walks of life on an unprecedented scale. In the following report, we recount the experience of stroke and neurointerventional practitioners from different parts of India. It was written in September 2020 when the first wave of the pandemic was at its zenith in India and vaccines were not yet available.

Hydride formation in zircaloy-4 under cyclic thermomechanical loading has been investigated using characterized notched beam samples in four-point beam testing, and microstructurally-representative crystal plasticity modelling of the beam tests which incorporates an atomistically-informed thermodynamically-equilibrium model for hydrogen concentration. The model provided the locations within the microstructure of high hydrogen content, above that required for saturation, hence predicting the anticipated locations of hydride observations in the experiments. The strain rate sensitivity of this alloy over the temperature range considered led to considerable intragranular slip and corresponding stress redistribution, and cyclic strain ratcheting leading to high hydrostatic stresses and in turn hydrogen concentrations, which explains the locations of experimentally observed hydride formation. The interstitial hydrogen interaction energy as well as the intragranular geometrically necessary dislocation density were shown to be important in controlling the spatial distributions of observed hydrides.

Capsular closure in femoroacetabular impingement syndrome (FAIS) patients during hip arthroscopy procedures is debated. The Danish Hip Arthroscopy Registry (DHAR) contains data to perform matched-cohort analyses. The purpose of this study is to evaluate 1-year subjective outcome data from DHAR after hip arthroscopy for FAIS with capsular closure and compare these outcome data with a matched-cohort study group. The primary hypothesis was that there would be no difference in Copenhagen Hip and Groin Outcome Score (HAGOS) subjective outcome between patients with and without capsular closure. This is a retrospective cohort study (level of evidence, 3). FAIS patients eligible for hip arthroscopy between January 2012 and December 2017, and where the interportal capsulotomy was closed, were identified and matched with patients without capsular closure. Matching criteria were gender (1:1), age (±5 years), degree of cartilage injury: ICRS and modified Becks grade (±1 grade) and radiological parameters: lateral center edge angle and alpha angle (±10°). A comparison between cohorts regarding differences in patient outcome scores, HAGOS, Hip Sports Activity Scale (HSAS), EuroQol-5 Domain (EQ-5D) and numeric rating scale (NRS) pain at 1-year follow-up were performed. Wilcoxon rank-sum test was used to compare differences between preoperative and postoperative subjective outcome scores, level of statistical significance was 0.05. A total of 189 patients were included in the capsular closure group and matched with 189 control patients. The mean age in years (±standard deviation) was 39.4 (±11.8) and 39.3 (±11.2), respectively, 55% females. Both groups improved significantly at 1-year follow-up. Significant improvements in the capsular closure group were found in HSAS, EQ-5D, NRS pain (rest and walk) and most HAGOS subscales compared with the non-closure group. All patients underwent labral repair in combination with both femoral osteochondroplasty and acetabuloplasty. The revision rate reported after 2 years was 6.8% in the non-closure group and 3.5% in the closure group. One patient in each cohort received a total hip replacement after 2 years. Capsular closure during arthroscopic FAIS treatment resulted in better subjective outcomes and less pain during rest and walking compared with matched controls. Both groups demonstrated improved outcome at 1-year follow-up. Furthermore, capsular closure might result in a lower risk of a revision hip arthroscopy.

The Japan healthcare system is considered as one of the world's finest. However, medical facilities across Japan are struggling to cope with the recent surge in novel coronavirus infections, leaving the medical care system in many areas on the brink of collapse. Physician burnout was already a growing problem, and the coronavirus disease 2019 pandemic has only made it worse. The personal impact of coronavirus disease 2019 in Japan is reported.

Journal of clinical monitoring and computing 35(4), 711-722 (2021). doi:10.1007/s10877-020-00527-6, Published by Springer Science + Business Media B.V., Dordrecht [u.a.]

Numerical simulations often overpredict precipitation over the Tibetan Plateau (TP). To examine the factors causing precipitation overprediction, different parameterizations of liquid-phase microphysical processes (accretion, autoconversion, and entrainment mixing) are implemented into the Morrison microphysics scheme to simulate a TP precipitation event in summer with the Weather Research and Forecasting (WRF) model. The general spatial distribution and temporal trend of precipitation are captured by all simulations, but the precipitation rate is overpredicted. The results from sensitivity experiments suggest that compared to other examined liquid-phase processes, the accretion process is more important in precipitation simulation over the TP region. Further investigation with the Heidke skill scores reveals that accretion parameterization that takes into account the raindrop size produces the most accurate results in terms of the total surface precipitation. This parameterization suppresses spurious accretion and does not produce liquid-phase precipitation until cloud droplets are big enough. It is also confirmed that increasing the model resolution can reduce precipitation overprediction. Results from the case study are confirmed by the use of a 1-month simulation.

We provide an algorithm to generate trajectories of sparse stochastic processes that are solutions of linear ordinary differential equations driven by L\'evy white noises. A recent paper showed that these processes are limits in law of generalized compound-Poisson processes. Based on this result, we derive an off-the-grid algorithm that generates arbitrarily close approximations of the target process. Our method relies on a B-spline representation of generalized compound-Poisson processes. We illustrate numerically the validity of our approach.

The Zero Emissions Commitment (ZEC) is the change in global mean temperature expected to occur following the cessation of net CO2 emissions and as such is a critical parameter for calculating the remaining carbon budget. The Zero Emissions Commitment Model Intercomparison Project (ZECMIP) was established to gain a better understanding of the potential magnitude and sign of ZEC, in addition to the processes that underlie this metric. A total of 18 Earth system models of both full and intermediate complexity participated in ZECMIP. All models conducted an experiment where atmospheric CO2 concentration increases exponentially until 1000 PgC has been emitted. Thereafter emissions are set to zero and models are configured to allow free evolution of atmospheric CO2 concentration. Many models conducted additional second-priority simulations with different cumulative emission totals and an alternative idealized emissions pathway with a gradual transition to zero emissions. The inter-model range of ZEC 50 years after emissions cease for the 1000 PgC experiment is −0.36 to 0.29 ∘C, with a model ensemble mean of −0.07 ∘C, median of −0.05 ∘C, and standard deviation of 0.19 ∘C. Models exhibit a wide variety of behaviours after emissions cease, with some models continuing to warm for decades to millennia and others cooling substantially. Analysis shows that both the carbon uptake by the ocean and the terrestrial biosphere are important for counteracting the warming effect from the reduction in ocean heat uptake in the decades after emissions cease. This warming effect is difficult to constrain due to high uncertainty in the efficacy of ocean heat uptake. Overall, the most likely value of ZEC on multi-decadal timescales is close to zero, consistent with previous model experiments and simple theory.

The plant to be stabilized is a system node $\Sigma$ with generating triple $(A,B,C)$ and transfer function $\bf G$, where $A$ generates a contraction semigroup on the Hilbert space $X$. The control and observation operators $B$ and $C$ may be unbounded and they are not assumed to be admissible. The crucial assumption is that there exists a bounded operator $E$ such that, if we replace ${\bf G}(s)$ by ${\bf G}(s)+E$, the new system $\Sigma_E$ becomes impedance passive. An easier case is when $\bf G$ is already impedance passive and a special case is when \mm $\Sigma$ has colocated sensors and actuators. Such systems include many wave, beam and heat equations with sensors and actuators on the boundary. It has been shown for many particular cases that the feedback $u=-\kappa y+v$, where $u$ is the input of the plant and $\kappa>0$, stabilizes $\Sigma$, strongly or even exponentially. Here, $y$ is the output of \m $\Sigma$ and $v$ is the new input. Our main result is that if for some $E\in{\mathcal L}(U)$, $\Sigma_E$ is impedance passive, and \m $\Sigma$ is approximately observable or approximately controllable in infinite time, then for sufficiently small $\kappa$ the closed-loop system is weakly stable. If, moreover, $\sigma(A)\cap i{\mathbb R}$ is countable, then the closed-loop semigroup and its dual are both strongly stable., Comment: 29 pages

Cooling electrical tabs of the cell instead of the lithium ion cell surfaces has shown to provide better thermal uniformity within the cell, but its ability to remove heat is limited by the heat transfer bottleneck between tab and electrode stack. A two-dimensional electro-thermal model was validated with custom made cells with different tab sizes and position and used to study how heat transfer for tab cooling could be increased. We show for the first time that the heat transfer bottleneck can be opened up with a single modification, increasing the thickness of the tabs, without affecting the electrode stack. A virtual large-capacity automotive cell (based upon the LG Chem E63 cell) was modelled to demonstrate that optimised tab cooling can be as effective in removing heat as surface cooling, while maintaining the benefit of better thermal, current and state-of-charge homogeneity. These findings will enable cell manufacturers to optimise cell design to allow wider introduction of tab cooling. This would enable the benefits of tab cooling, including higher useable capacity, higher power, and a longer lifetime to be possible in a wider range of applications.

In this paper, the effect of sodium alginate (SA) on the flotation separation of molybdenite (MoS2) from chalcopyrite using kerosene as collector was systematically investigated. The results of single-mineral micro-flotation tests indicated that SA exhibited strong depression on chalcopyrite flotation while it imposed no impact on the floatability of molybdenite. However, in the chalcopyrite–molybdenite mixed-mineral flotation system, the presence of chalcopyrite significantly increased the depressing effect of SA on molybdenite flotation, leading to a considerable reduction in the flotation selectivity. The negative impact of chalcopyrite on the performance of SA in molybdenite flotation was eliminated by adding a certain dosage of kerosene prior to SA. A concentrate containing 53.43% of molybdenum (Mo) was obtained at 76.90% of recovery using 19 mg/L kerosene and 40 mg/L SA at pH 5.4. Zeta potential measurements indicated that the adsorption of SA on chalcopyrite surfaces was stronger than that on molybdenite surfaces, which agreed with the single-mineral flotation test results. The adsorption of SA on chalcopyrite was further confirmed to be chemisorption by Fourier-transform infrared spectroscopy (FTIR) spectra analyses. When Cu2+ appeared in solution, the flotation of molybdenite was strongly depressed by SA. Mechanism analyses indicated that more active sites were generated on molybdenite surfaces after the addition of Cu2+, thus promoting the adsorption of SA. Published version

As a vital land surface parameter, soil moisture influences climate through its impact on water and energy cycles. However, the effect of soil moisture on precipitation has been strongly debated. In this study, a new causal detection method, convergent cross mapping (CCM), was applied to explore the causality between soil moisture and precipitation over low- and mid- latitude regions in the Northern Hemisphere. CCM method generally identified a strong effect of soil moisture on precipitation. Specifically, the optimal effect of soil moisture on precipitation occurred with a lag of one month and clearly decreased after four months, suggesting that soil moisture has potentials to improve the accuracy of precipitation forecast at a sub-seasonal scale. In addition, as climate (i.e., aridity index) changed from dry to wet, the effect of soil moisture on precipitation first increased and then decreased with peaks in semi-arid and semi-humid areas. These findings statistically support the hypothesis that soil moisture impacts precipitation and also provide a reference for the design of climate prediction systems.

Lithium ion batteries are increasingly important in large scale applications where thermal management is critical for safety and lifetime. Yet, the effect of different thermal boundary conditions on the performance and lifetime is still not fully understood. In this work, a two-dimensional electro-thermal model is developed to simulate cell performance and internal states under complex thermal boundary conditions. Attention was paid to model, not only the electrode stack but also the non-core components (e.g. tab weld points) and thermal boundaries, but also the experiments required to parameterize the thermal model, and the reversible heat generation. The model is comprehensively validated and the performance of tab and surface cooling strategies was evaluated across a wide range of operating conditions. Surface cooling was shown to keep the cell at a lower average temperature, but with a large thermal gradient for high C rates. Tab cooling provided much smaller thermal gradients but higher average temperatures caused by lower heat removing ability. The thermal resistance between the current collectors and tabs was found to be the most significant heat transfer bottleneck and efforts to improve this could have significant positive impacts on the performance of li-ion batteries considering the other advantages of tab cooling.