Reinvestigation of Na5GdSi4O12: A Potentially Better Solid Electrolyte than Sodium ß Alumina for Solid-State Sodium Batteries.

Developing high-performing solid electrolytes that could replace flammable organic liquid electrolytes is vital in designing safer solid-state batteries. Among the sodium-ion (Na+) conducting solid electrolytes, Na-ß″-alumina (BASE) is highly regarded for its employment in solid-state battery applications due to its high ionic conductivity and electrochemical stability. BASE has long been employed in commercial Na-NiCl2 and Na-S batteries. However, the synthesis of highly conductive BASE is energy-intensive, involving elevated temperatures for sintering and the incorporation of stabilizing additives. Additionally, BASE is highly sensitive to humidity, which limits its applications. Hence, there is an intense search to identify suitable high-performing solid electrolytes that could replace BASE. In this context, we reinvestigated Na5GdSi4O12 (NGS) and demonstrated that phase pure NGS could be synthesized by a simple solid-state reaction. Beyond a high ionic conductivity of 1.9 × 10-3 S cm-1 at 30 °C (1.5 × 10-3 S cm-1 for BASE), NGS exhibited high chemical as well as electrochemical stability, lower interfacial resistance, lower deposition and stripping potential, and higher short-circuiting current, designating NGS as a better solid electrolyte than BASE.

Warming may offset impact of precipitation changes on riverine nitrogen loading.

Climate change, especially in the form of precipitation and temperature changes, can alter the transformation and delivery of nitrogen on the land surface and to aquatic systems, impacting the trophic states of downstream water bodies. While the expected impacts of changes in precipitation have been explored, a quantitative understanding of the impact of temperature on nitrogen loading is lacking at landscape scales. Here, using several decades of nitrogen loading observations, we quantify how individual and combined future changes in precipitation and temperature will affect riverine nitrogen loading. We find that, contrary to recent decades, rising temperatures are likely to offset or even reverse previously reported impacts of future increases in total and extreme precipitation on nitrogen runoff across the majority of the contiguous United States. These findings highlight the multifaceted impacts of climate change on the global nitrogen cycle.

Biome-scale temperature sensitivity of ecosystem respiration revealed by atmospheric CO2 observations.

The temperature sensitivity of ecosystem respiration regulates how the terrestrial carbon sink responds to a warming climate but has been difficult to constrain observationally beyond the plot scale. Here we use observations of atmospheric CO2 concentrations from a network of towers together with carbon flux estimates from state-of-the-art terrestrial biosphere models to characterize the temperature sensitivity of ecosystem respiration, as represented by the Arrhenius activation energy, over various North American biomes. We infer activation energies of 0.43 eV for North America and 0.38 eV to 0.53 eV for major biomes therein, which are substantially below those reported for plot-scale studies (approximately 0.65 eV). This discrepancy suggests that sparse plot-scale observations do not capture the spatial-scale dependence and biome specificity of the temperature sensitivity. We further show that adjusting the apparent temperature sensitivity in model estimates markedly improves their ability to represent observed atmospheric CO2 variability. This study provides observationally constrained estimates of the temperature sensitivity of ecosystem respiration directly at the biome scale and reveals that temperature sensitivities at this scale are lower than those based on earlier plot-scale studies. These findings call for additional work to assess the resilience of large-scale carbon sinks to warming.

Increasing sensitivity of dryland vegetation greenness to precipitation due to rising atmospheric CO2.

Water availability plays a critical role in shaping terrestrial ecosystems, particularly in low- and mid-latitude regions. The sensitivity of vegetation growth to precipitation strongly regulates global vegetation dynamics and their responses to drought, yet sensitivity changes in response to climate change remain poorly understood. Here we use long-term satellite observations combined with a dynamic statistical learning approach to examine changes in the sensitivity of vegetation greenness to precipitation over the past four decades. We observe a robust increase in precipitation sensitivity (0.624% yr-1) for drylands, and a decrease (-0.618% yr-1) for wet regions. Using model simulations, we show that the contrasting trends between dry and wet regions are caused by elevated atmospheric CO2 (eCO2). eCO2 universally decreases the precipitation sensitivity by reducing leaf-level transpiration, particularly in wet regions. However, in drylands, this leaf-level transpiration reduction is overridden at the canopy scale by a large proportional increase in leaf area. The increased sensitivity for global drylands implies a potential decrease in ecosystem stability and greater impacts of droughts in these vulnerable ecosystems under continued global change.

India's Riverine Nitrogen Runoff Strongly Impacted by Monsoon Variability.

Agricultural intensification in India has increased nitrogen pollution, leading to water quality impairments. The fate of reactive nitrogen applied to the land is largely unknown, however. Long-term records of riverine nitrogen fluxes are nonexistent and drivers of variability remain unexamined, limiting the development of nitrogen management strategies. Here, we leverage dissolved inorganic nitrogen (DIN) and discharge data to characterize the seasonal, annual, and regional variability of DIN fluxes and their drivers for seven major river basins from 1981 to 2014. We find large seasonal and interannual variability in nitrogen runoff, with 68% to 94% of DIN fluxes occurring in June through October and with the coefficient of variation across years ranging from 44% to 93% for individual basins. This variability is primarily explained by variability in precipitation, with year- and basin-specific annual precipitation explaining 52% of the combined regional and interannual variability. We find little correlation with rising fertilizer application rates in five of the seven basins, implying that agricultural intensification has thus far primarily impacted groundwater and atmospheric emissions rather than riverine runoff. These findings suggest that riverine nitrogen runoff in India is highly sensitive to projected future increases in precipitation and intensification of the seasonal monsoon, while the impact of projected continued land use intensification is highly uncertain.

Higher-Order Optimality Conditions in Set-Valued Optimization with Respect to General Preference Mappings.

We present higher order necessary conditions for a model of welfare economics, where the preference mapping has a star-shape property. We assume that the preferences can be satiable and can be described by an arbitrary preference set, without the use of utility functions. These conditions are formulated in terms of higher-order directional derivatives of multivalued mappings, and the variable domination structure is not given by cones.

The role of heterodimer IL-17-A/F in atopic dermatitis.

Introduction: The importance of multifactorial dysregulation in immune response is well recognised in atopic dermatitis (AD). Th17 family cytokine IL-17 (IL-17A-F) is of significance in both acute and chronic phase of AD. Aim: We analysed the differences between serum levels of IL-17A/F and IL-17A, IL-17-F, IL-13, IL-4, association of rs2275913 IL-17A and rs763780 IL-17F gene polymorphisms in paediatric AD patients and control subjects. Material and methods: We assessed 30 children with AD and 30 healthy patients aged 2-12 years. Eczema Area and Severity Index, Investigator Global Assessment and Scoring Atopic Dermatitis scales were used to analyse the severity of skin lesions in AD patients. Genotyping was performed using PCR and the serum concentrations of IL-17A/F, IL-17A, IL-17F, while IL-13 and IL-4 interleukins were determined by enzyme-linked immuno-sorbent assays (ELISA). Results: The revised median assessment scoring in disease severity showed that the studied AD population had a moderate course of the disease. The obtained results indicated elevated plasma levels of IL-17A/F and IL-17-13 in AD patients with no statistically significance of IL-17A, IL-17F and IL-4 compared to controls. AD duration was positively correlated with IL-13 levels and negatively with IL-17A/F (p < 0.05). Moreover, there was no significant difference between case and control groups in the frequency of genotypes and alleles at rs2275913 IL-17A and rs763780 IL-17F polymorphisms (p > 0.05). Conclusions: This study demonstrates increased levels of IL-17A/F in atopic patients, which is positively correlated with severity of the disease and the early phase of the disease. These results highlight a functional role of this cytokine in the pathogenesis of AD in paediatric patients.

Accuracy Evaluation of Selected Mobile Inspection Robot Localization Techniques in a GNSS-Denied Environment.

Locating an inspection robot is an essential task for inspection missions and spatial data acquisition. Giving a spatial reference to measurements, especially those concerning environmental parameters, e.g., gas concentrations may make them more valuable by enabling more insightful analyses. Thus, an accurate estimation of sensor position and orientation is a significant topic in mobile measurement systems used in robotics, remote sensing, or autonomous vehicles. Those systems often work in urban or underground conditions, which are lowering or disabling the possibility of using Global Navigation Satellite Systems (GNSS) for this purpose. Alternative solutions vary significantly in sensor configuration requirements, positioning accuracy, and computational complexity. The selection of the optimal solution is difficult. The focus here is put on the assessment, using the criterion of the positioning accuracy of the mobile robot with no use of GNSS signals. Automated geodetic surveying equipment is utilized for acquiring precise ground truth data of the robot's movement. The results obtained, with the use of several methods, compared: Wheel odometry, inertial measurement-based dead-reckoning, visual odometry, and trilateration of ultra-wideband signals. The suitability, pros, and cons of each method are discussed in the context of their application in autonomous robotic systems, operating in an underground mine environment.

Changes in lipid and apolipoprotein levels in response to 8-week cardiac rehabilitation in men with coronary artery disease.

Concentrations of selected lipoproteins are currently useful cardiovascular risk assessment indicators, especially in monitoring lipid-lowering therapy. AIM: The aim was to evaluate the influence of 8-week mid-term CR on apolipoproteins: A-I, B, E and VLDL in CAD patients in relation to conventional lipid profile and prior coronary intervention: PCI or CABG. MATERIALS AND METHODS: 93 male patients admitted to CR after PCI or CABG. At baseline and after CR, conventional lipid profile parameters and VLDL concentrations were evaluated. Apolipoproteins: A-I, B, E were also determined. Basic anthropometric indicators and measurements of hemodynamic and exercise tolerance at rest and peak workload in exercise testing (HR, sBP, dBP, DP, W) were measured. RESULTS: After CR, depending on revasculazation intervention, no changes in HDL-C, LDL-C, TG and VLDL values were observed (p>0.05). Reduction in apoA-I was noted in PCI group (p=0.0254). No statistically significant changes in apoB and apoE were found in groups. Significant increase in apo B/apo A-I index was observed only in PCI group (p=0.0329). PCI and CABG patients did not differ in hemodynamic and exercise tolerance parameters, except sBP in rest and dBP at peak workload in exercise testing (p=0.014 and p=0.031). Regardless on type of intervention, there was observed statistically significant increase in Wpeak (p=0,0000 in both groups) and DPpeak (p=0.0000 in PCI-patients and p=0.0003 in CABGpatients) after CR. CONCLUSIONS: CR has various effects on lipid concentrations. Indicators of conventional lipid profile and selected apolipoproteins are not optimal parameters allowing assessment of effectiveness of CR program in such a short time, this role is well fullfilled by the hemodynamic and physical exercise indices. Apo B/apo A-I ratio value suggests an increasing risk of IHD complications, especially in post- PCI group. CR program requires intensification of lipid-reducing therapy and education on lifestyle modification.

Author Correction: Modeling suggests fossil fuel emissions have been driving increased land carbon uptake since the turn of the 20th Century.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Modeling suggests fossil fuel emissions have been driving increased land carbon uptake since the turn of the 20th Century.

Terrestrial vegetation removes CO2 from the atmosphere; an important climate regulation service that slows global warming. This 119 Pg C per annum transfer of CO2 into plants-gross primary productivity (GPP)-is the largest land carbon flux globally. While understanding past and anticipated future GPP changes is necessary to support carbon management, the factors driving long-term changes in GPP are largely unknown. Here we show that 1901 to 2010 changes in GPP have been dominated by anthropogenic activity. Our dual constraint attribution approach provides three insights into the spatiotemporal patterns of GPP change. First, anthropogenic controls on GPP change have increased from 57% (1901 decade) to 94% (2001 decade) of the vegetated land surface. Second, CO2 fertilization and nitro gen deposition are the most important drivers of change, 19.8 and 11.1 Pg C per annum (2001 decade) respectively, especially in the tropics and industrialized areas since the 1970's. Third, changes in climate have functioned as fertilization to enhance GPP (1.4 Pg C per annum in the 2001 decade). These findings suggest that, from a land carbon balance perspective, the Anthropocene began over 100 years ago and that global change drivers have allowed GPP uptake to keep pace with anthropogenic emissions.

Gas-phase hydration of Mg2+ complexes with deprotonated uracil, thymine, uridine, and thymidine.

The gas-phase hydration of Mg2+ complexes with deprotonated uracil (U), thymine (T), uridine (Ur , uracil riboside), and thymidine (Tdr , thymine deoxyriboside) was studied. The aim of the work was to analyze the hydration of product ions (eg, [2U-H+Mg]+ ) formed as a result of the collision induced dissociation of the respective parent ion (eg, [3Ur -H+Mg]+ ). The efficiency of gas-phase hydration of the ions [2U-H+Mg]+ and [2T-H+Mg]+ was similar. However, the efficiency of gas-phase hydration of the ion [U+Ur -H+Mg]+ was much higher than that of gas-phase hydration of the ion [T+Tdr -H+Mg]+ . On the basis of the mass spectra obtained and the performed molecular modelling, it was concluded that in the ion [T+Tdr -H+Mg]+ , we deal with a steric hindrance due to the presence of a sugar moiety, which affects water attachment. In the ion [U+Ur -H+Mg]+ , the position of the sugar moiety does not affect water attachment.

Model of the Vibration Signal of the Vibrating Sieving Screen Suspension for Condition Monitoring Purposes.

Diagnostics of industrial machinery is a topic related to the need for damage detection, but it also allows to understand the process itself. Proper knowledge about the operational process of the machine, as well as identification of the underlying components, is critical for its diagnostics. In this paper, we present a model of the signal, which describes vibrations of the sieving screen. This particular type is used in the mining industry for the classification of ore pieces in the material stream by size. The model describes the real vibration signal measured on the spring set being the suspension of this machine. This way, it is expected to help in better understanding how the overall motion of the machine can impact the efforts of diagnostics. The analysis of real vibration signals measured on the screen allowed to identify and parameterize the key signal components, which carry valuable information for the following stages of diagnostic process of that machine. In the proposed model we take into consideration deterministic components related to shaft rotation, stochastic Gaussian component related to external noise, stochastic α-stable component as a model of excitations caused by falling rocks pieces, and identified machine response to unitary excitations.

Global vegetation biomass production efficiency constrained by models and observations.

Plants use only a fraction of their photosynthetically derived carbon for biomass production (BP). The biomass production efficiency (BPE), defined as the ratio of BP to photosynthesis, and its variation across and within vegetation types is poorly understood, which hinders our capacity to accurately estimate carbon turnover times and carbon sinks. Here, we present a new global estimation of BPE obtained by combining field measurements from 113 sites with 14 carbon cycle models. Our best estimate of global BPE is 0.41 ± 0.05, excluding cropland. The largest BPE is found in boreal forests (0.48 ± 0.06) and the lowest in tropical forests (0.40 ± 0.04). Carbon cycle models overestimate BPE, although models with carbon-nitrogen interactions tend to be more realistic. Using observation-based estimates of global photosynthesis, we quantify the global BP of non-cropland ecosystems of 41 ± 6 Pg C/year. This flux is less than net primary production as it does not contain carbon allocated to symbionts, used for exudates or volatile carbon compound emissions to the atmosphere. Our study reveals a positive bias of 24 ± 11% in the model-estimated BP (10 of 14 models). When correcting models for this bias while leaving modeled carbon turnover times unchanged, we found that the global ecosystem carbon storage change during the last century is decreased by 67% (or 58 Pg C).

Widespread global increase in intense lake phytoplankton blooms since the 1980s.

Freshwater blooms of phytoplankton affect public health and ecosystem services globally1,2. Harmful effects of such blooms occur when the intensity of a bloom is too high, or when toxin-producing phytoplankton species are present. Freshwater blooms result in economic losses of more than US$4 billion annually in the United States alone, primarily from harm to aquatic food production, recreation and tourism, and drinking-water supplies3. Studies that document bloom conditions in lakes have either focused only on individual or regional subsets of lakes4-6, or have been limited by a lack of long-term observations7-9. Here we use three decades of high-resolution Landsat 5 satellite imagery to investigate long-term trends in intense summertime near-surface phytoplankton blooms for 71 large lakes globally. We find that peak summertime bloom intensity has increased in most (68 per cent) of the lakes studied, revealing a global exacerbation of bloom conditions. Lakes that have experienced a significant (P < 0.1) decrease in bloom intensity are rare (8 per cent). The reason behind the increase in phytoplankton bloom intensity remains unclear, however, as temporal trends do not track consistently with temperature, precipitation, fertilizer-use trends or other previously hypothesized drivers. We do find, however, that lakes with a decrease in bloom intensity warmed less compared to other lakes, suggesting that lake warming may already be counteracting management efforts to ameliorate eutrophication10,11. Our findings support calls for water quality management efforts to better account for the interactions between climate change and local hydrological conditions12,13.

Carbon and Water Use Efficiencies: A Comparative Analysis of Ten Terrestrial Ecosystem Models under Changing Climate.

Terrestrial ecosystems carbon and water cycles are tightly coupled through photosynthesis and evapotranspiration processes. The ratios of carbon stored to carbon uptake and water loss to carbon gain are key ecophysiological indicators essential to assess the magnitude and response of the terrestrial plant to the changing climate. Here, we use estimates from 10 terrestrial ecosystem models to quantify the impacts of climate, atmospheric CO2 concentration, and nitrogen (N) deposition on water use efficiency (WUE), and carbon use efficiency (CUE). We find that across models, WUE increases over the 20th Century particularly due to CO2 fertilization and N deposition and compares favorably to experimental studies. Also, the results show a decrease in WUE with climate for the last 3 decades, in contrasts with up-scaled flux observations that demonstrate a constant WUE. Modeled WUE responds minimally to climate with modeled CUE exhibiting no clear trend across space and time. The divergence between simulated and observationally-constrained WUE and CUE is driven by modeled NPP and autotrophic respiration, nitrogen cycle, carbon allocation, and soil moisture dynamics in current ecosystem models. We suggest that carbon-modeling community needs to reexamine stomatal conductance schemes and the soil-vegetation interactions for more robust modeling of carbon and water cycles.

Comment on "Legacy nitrogen may prevent achievement of water quality goals in the Gulf of Mexico".

Van Meter et al (Reports, 27 April 2018, p. 427) warn that achieving nitrogen reduction goals in the Gulf of Mexico will take decades as a result of legacy nitrogen effects. We discuss limitations of the modeling approach and demonstrate that legacy effects ranging from a few years to decades are equally consistent with observations. The presented time scales for system recovery are therefore highly uncertain.

Enhanced North American carbon uptake associated with El Niño.

Long-term atmospheric CO2 mole fraction and δ13CO2 observations over North America document persistent responses to the El Niño-Southern Oscillation. We estimate these responses corresponded to 0.61 (0.45 to 0.79) PgC year-1 more North American carbon uptake during El Niño than during La Niña between 2007 and 2015, partially offsetting increases of net tropical biosphere-to-atmosphere carbon flux around El Niño. Anomalies in derived North American net ecosystem exchange (NEE) display strong but opposite correlations with surface air temperature between seasons, while their correlation with water availability was more constant throughout the year, such that water availability is the dominant control on annual NEE variability over North America. These results suggest that increased water availability and favorable temperature conditions (warmer spring and cooler summer) caused enhanced carbon uptake over North America near and during El Niño.

Long-Term Changes in Precipitation and Temperature Have Already Impacted Nitrogen Loading.

Increases in nitrogen loading over the past several decades have led to widespread water quality impairments across the U.S. Elevated awareness of the influence of climate variability on nitrogen loading has led to several studies investigating future climate change impacts on water quality. However,  it remains unclear whether long-term climate impacts can already be observed in the historical record. Here, we quantify long-term trends in total nitrogen loading over the period 1987-2012 across the contiguous U.S. and attribute these trends to long-term changes in nitrogen inputs and climatic variables. We find that annual precipitation, extreme springtime precipitation, and springtime temperature are key drivers of trends in historical loading in most regions. These decadal climate trends have either  amplified or offset loading trends expected from nitrogen inputs alone. We also find that rising temperatures have been insufficient to offset precipitation-induced loading increases, suggesting that future increases in temperature under climate change may have limited potential to counteract loading increases expected as a result of anticipated changes in precipitation. This work demonstrates the important role of decadal climate variability in long-term nitrogen loading, emphasizing the need to consider climate change risks when designing and monitoring nutrient reduction programs.