Soil sodicity is a major constraint to seedling emergence and crop production, potentially reducing plant growth due to physical and chemical constraints. Examining responses to ion imbalances may assist in the identification of genotypes tolerant to chemical constraints in sodic soils and improve productivity. We evaluated the performance of four wheat (Triticum aestivum. L) genotypes in solutions with five sodium adsorption ratios (SARs) ranging from 0 to 60. For all four genotypes, seedling emergence and shoot dry matter (DM) decreased significantly with increasing SAR. A significant positive correlation was observed between Ca concentration in roots, as well as both root and shoot DM for all genotypes. At SAR values >20, a more tolerant genotype (EGA Gregory), had higher Ca concentrations in root tissues, while a more sensitive genotype (Baxter) exhibited Na-induced Ca deficiency. Thus, selection for genotypes that are able to accumulate Ca in roots in sodic conditions may be a useful trait for selecting genotypes tolerant of soils with high ESP values. However, for soils that restrict plant growth at ESP (SAR) values of 6-10%, it is likely that growth is restricted by physical constraints rather than by a Na-induced Ca deficiency.

In a recent effort to mitigate harm from human pathogens, many biosynthetic pathways are extensively evaluated for their ability to inhibit pathogen growth and determine drug targets. Among those, one of the important products/targets of such pathways is isopentenyl diphosphate, the universal precursor of isoprenoids, which are essential for the normal functioning of microorganisms. In general, two biosynthetic pathways lead to the formation of isopentenyl diphosphate: 1) the mevalonate pathway in animals and 2) the non-mevalonate or methylerythritol phosphate (MEP) in many bacteria, some protozoa, and plants. Because the MEP pathway is not found in mammalian cells, it is considered an attractive target for the development of antimicrobials against a variety of human pathogens, including Mycobacterium tuberculosis (M.tb). In the MEP pathway, 4-diphosphocytidyl-2-c-methyl-d-erythritol kinase (IspE) phosphorylates 4-diphosphocytidyl-2-C-methyl-D-erythritol (CDPME) to form 4-diphosphocytidyl-2-C-methyl-D-erythritol 2-phosphate (CDPME2P), followed by cyclization to 2-C-methyl-D-erythritol 2,4-cyclodiphosphate (MECPP) by 2-C-methyl-D-erythritol 2,4-cyclodiphosphate synthase (IspF). A virtual high throughput screening was done by docking IspE protein with commercially available compounds and identified an active heterotricyclic compound. Hence, we designed, synthesized, and tested similar new heterotricyclic compounds. This study will provide the critical insight necessary for the ability to develop novel antimicrobials that target the MEP pathways in pathogens.

Arctic sea ice prediction holds significant importance for facilitating Arctic route planning, optimizing fisheries management, and advancing the field of sea ice dynamics research. While various deep learning models have been developed for sea ice prediction, they predominantly operate at the seasonal or sub-seasonal scale, often focusing on localized areas, and few cater to full-region daily scale prediction. This study introduces the use of spatiotemporal sequence data prediction models, namely, the convolutional LSTM (ConvLSTM) and predictive recurrent neural network (PredRNN), for the prediction of sea ice concentration (SIC). Our analysis reveals that, when solely utilizing SIC historical data as the input, the ConvLSTM model outperforms the PredRNN model in SIC prediction. To enhance the model's capacity to capture spatiotemporal relationships between multiple variables, we expanded the range of input data types to form the ConvLSTM-multi and PredRNN-multi models. Experimental findings demonstrate that the ConvLSTM-multi model excels in assimilating the influence of reanalysis data on sea ice within the sea ice edge region, thus exhibiting superior performance in predicting daily Arctic SIC over the subsequent 10 days. Furthermore, sensitivity tests on various model parameters highlight the substantial impact of sea surface temperature and prediction date on the accuracy of daily sea ice prediction. Additionally, meteorological and oceanographic parameters primarily affect the prediction accuracy of the thin ice region at the edge of the sea ice.

Activated sludge process is a well known method to treat municipal and industrial waste water. In this complex process, the oxygen concentration in the reactors plays a critical role in the plant efficiency. This paper proposes the use of a Long Short-Term Memory (LSTM) network to identify an input-output model suitable for the design of an oxygen concentration controller. The model is identified from easy-accessible measures collected from a real plant. This dataset covers almost a month. The performances achieved with the proposed LSTM model are compared with the ones obtained with a standard AutoRegressive model with eXogenous input (ARX). Both models catch the oscillation and the overall behaviour (ARX ρ=0.833 , LSTM ρ=0.921), but, while the ARX model fails in reaching the correct amplitude (FIT=41.20%), the LSTM presents satisfactory performance (FIT=60.56%).

Understanding the evolving hydrological characteristics of landslide-induced barrier lakes is crucial for flood control, forecasting, early warning, and safety measures in the reservoir area. This study examines the changes in hydrological characteristics of the Attabad landslide-dammed lake over the past decade after the occurrence of the landslide, focusing on lake area dynamics and sediment concentration. High-resolution satellite images from QuickBird, Pleiades, and WorldView2 over seven periods were analyzed. The findings indicate that the lake area has gradually decreased, with the center of mass shifting towards the lake dam, indicating a trend towards stability. The suspended sediment in the barrier lake is distributed in a strip running from north to south, then northeast to southwest, with sediment concentration decreasing from the lake entrance to the dam and from the lake bank to the center. Over time, the average sediment concentration has decreased from 2010 to 2020, with higher concentrations in summer than in winter. Notably, during the 2017-2020 period, the lower-middle parts of the lake experienced higher sediment concentration, while the dam area witnessed lower concentrations, thereby reducing the sediment impact on the dam.

This study examines the impact of chainsaw chain type and tree species on the concen-tration of inhalable wood dust generated during motor-manual harvesting in forested areas. The chainsaw chain is a critical component, contributing not only to productivity but also to the oper-ator's health and safety. Wood dust creation during harvesting operations poses significant risks and necessitates careful attention due to its potential health effects. We investigated the effects by conducting real-world measurements of inhalable dust within the operator's breathing zone during forestry work. Two different chain types were evaluated: the commonly used 3/8" pitch chain (conventional chain) and the 0.325" pitch chain. Additionally, measurements were taken for three tree species: beech, oak, and pine (including both live and standing dead trees after a fire). Results showed that, overall, using the conventional 3/8" chain type yielded the highest concentration of wood dust for all three tree species. Notably, the highest wood dust concentration was observed in the burned Pinus brutia cluster, also with the 3/8" chain pitch. These findings emphasize the im-portance of understanding how chain type and tree species contribute to wood dust levels and provide valuable insights for enhancing operator health and safety during motor-manual har-vesting operations

In the presence of absorbing aerosol in the atmosphere a number of systematic errors of standard Ocean Color algorithms were noted, for example, negative values of remote sensing reflectance in the short-wavelength region at 412 nm and 443 nm. The main goal of this work is to develop an algorithm for additional correction of remote sensing reflectance level 2 satellite data, taking into account the presence of absorbing aerosol over the Black Sea, where a large number of dust transfers from the Sahara are observed annually. To implement the algorithm, an analytical and experimental evaluation of the interpolation function is carried out, taking into account the optical effects caused by the stratification of the absorbing aerosol. This algorithm is based on the constancy of the color index value, characteristic of the selected region. For the Black Sea the average value of CI(412/443) = 0.80±0.08, a small standard deviation indicates that the sample is slightly variable. Therefore, CI(412/443) = 0.80 will be further considered as the reference value of the color index for calculating new restored Rrs(λ).

For the purpose of clean energy hydropower development, the construction of reservoirs has been continuously promoted in the Jinsha River basin for many years, and how the reservoirs affect the water and sediment process is a very necessary topic to study. This study is based on the gauged water and sediment data (span from the 1960’s to 2020) at Shigu, Panzhihua, and Xiangjiaba stations downstream located in the trunk channel of the river, and uses Mann-Kendall trend test method and double cumulative curve method to comprehensively judge the variation trends of runoff and suspended sediment load and reveal their credible mutation years. The linear regression method is used to reveal the variation characteristics of the relationship between water and sediment before and after the abrupt change years. The results show that the variations in runoff at Shigu and Panzhihua stations have significant and relatively obvious increasing trends, respectively, and that at Panzhihua station has a mutation year of 1985. The runoff at Xiangjiaba Station slightly increased but not significantly. The variation of suspended sediment load showed a temporal and spatial differentiation. The variation of sediment discharge at Shigu Station showed an increasing trend with a mutation year of 1997. For Panzhihua Station, it showed an increasing trend before 1998, but has significantly decreased since 1998. The fluctuation of sediment transport at Xiangjiaba Station was significant before 1998, but the trend is unclear. In the period of 1998−2020, it showed a significant decreasing trend, especially since 2013, when the mean annual suspended sediment load only accounted for 0.61% of its multi-year average. The variations of mean annual sediment concentration and sediment inflow coefficient at the hydrological stations is consistent with the variation trend of sediment transport. Before 2013, the correlation between water and sediment was strong, but thereafter it was extremely weak. The two sudden years of 1998 and 2013 are consistent with the year when large reservoirs were built in the river basin. The construction of large reservoirs and their large amount of sediment retention are the key reasons for the sudden changes in the water-sediment relationship and the sharp decrease in sediment transport in the downstream reach of the reservoir dam. The climate and underlying surface changes in the study area are not significant, and their impact on the water and sediment processes in the watershed is limited.

In this report, we establish a straightforward method for estimating the equilibrium constant for the CK reaction over wide but physiologically and experimentally relevant ranges of pH, Mg2+ and temperature. Our empirical formula for CK Keq” is based on experimental measurements. It can be used to estimate [ADP] when [ADP] is below the resolution of experimental measurements, a typical situation because [ADP] is on the order of micromolar concentrations in living cells, and may be much lower in many in vitro experiments. Accurate prediction of [ADP] is essential for in vivo studies of cellular energetics and metabolism, and for in vitro studies of ATP-dependent enzyme function under near-physiological conditions. With [ADP], we could estimate ΔGATP. Application to actomyosin force generation in muscle provides support for the hypothesis that, when [Pi] varies but not when pH is altered, maximum Ca2+-activated isometric force depends on ΔGATP in both living and permeabilized muscle preparations. Further analysis of the pH studies introduces a novel hypothesis for the role of submicromolar ADP in force generation.

A study was carried out in a Waste Sorting Plant (WSP) located in France and treating dry recyclable household waste (DRHW) as well as dry recyclable commercial and industrial waste (DRCIW). The aim was to investigate the exposure to bioaerosol and dust. The aim of the study was to assess the extent to which the measurement of concentration, species composition and particle size distribution can contribute to a better assessment of the biological risks associated with exposure. Both stationary and personal bioaerosol and dust samples were collect in the (WSP). The results confirm that waste and waste sorting activities are sources of airborne fungi. Indeed, ambient concentrations ranged from 7.3×103 to 8.5×105 CFU/m3 for culturable moulds and up to up to 4 mg/m3 for dust. Personal exposure to inhalable dust was found up to 3 mg/m3 for dust and ranged from 8.6×103 to 1.5×106 CFU/m3 for fungi. Airborne fungal communities were found to be dominated by the Penicillium genera in both bioaerosols and settled dust samples, followed by the Aspergillus, Cladosporium, Wallemia, Mucor, and Rhizopus genera. Fungi were carried by particles of aerodynamic diameters mainly between around 2.0 and 10.0 µm. The findings dealing with size distribution and biodiversity of bioaerosols suggest that employees are exposed to complex bioaerosols during their work and helps to make a finer diagnosis of the risks involved, which is often difficult in the absence of any OEL for bioaerosols in general.

This study assessed the acute effects of oral methylliberine (DynamineTM) supplementation on cognitive function and indices of well-being. This was a double-blind, randomized, within-subject crossover trial. 25 healthy men and women (33.5±10.7yr, 172.7±8.6cm, 73.3±11.0kg) underwent pretesting before ingesting methylliberine (100mg) or placebo (PLA) for 3 days. On the fourth day participants were tested before their 4th dose (baseline) and every hour post-ingestion for 3 hours. After a one-week washout period, participants repeated testing with the alternate investigational product. The testing battery consisted of vitals, Stroop test and Trail Making Test-B, and visual analog scales that assessed various indices of well-being. Mixed factorial ANOVA with repeated measures were used to assess all variables. There were significant (p≤0.050) interactions in concentration, motivation, and mood. Methylliberine improved concentration 1- and 3-hours, motivation 3 hours, and mood 1-, 2-, and 3 hours (p≤0.050). Methylliberine improved energy, sustained energy, and mood in all participants to a greater extent than PLA at 1-hour and 3-hours relative to baseline (p≤0.050). PLA improved motivation at 1- and 2-hours and mood at 2-hours (p≤0.050). Methylliberine improved concentration, well-being, and the ability to tolerate stress to a greater extent than PLA at 3-hours relative to baseline (p≤0.050). Women observed elevations in sustained energy 1- and 3-hours (p≤0.050) in methylliberine vs. PLA. Methylliberine had negligible influence on cognitive function, vitals (p>0.050), and no adverse events were reported. Methylliberine significantly improved subjective feelings of energy, concentration, motivation, and mood, but not cognitive function. PLA improved motivation and mood at hours 1 and 2, while methylliberine sustained benefits for longer. Methylliberine also improved concentration, well-being, and the ability to tolerate stress to a greater degree than PLA while having no detrimental effects on vital signs. Methylliberine also seems to have a positive impact on sustained energy in women.

The new energy structure needs to balance energy security and dual carbon goals, which has brought major challenges to coal-fired power plants, the pollution reduction and carbon emissions reduction of coal-fired power plants will be a key task in the future. This article proposes an optimization operation of electrostatic precipitators(ESP), based on the working mechanism and historical data of ESP, voltage-current characteristic model and outlet dust concentration prediction model are constructed by deep learning algorithm, Particle Swarm Optimization(PSO) is used to achieve the optimal energy consumption while ensuring stable outlet dust concentration. By training with historical data collected on site, accurate prediction of secondary current and outlet dust concentration of ESP has been achieved, the Mean Absolute Percentage Error(MAPE) of secondary current is less than 1.5%, and the MAPE of outlet dust concentration of ESP on the test set is less than 5.2%. Finally, the optimization experiment is carried out in a 330MW coal-fired power plants, the results showed that the fluctuation of the outlet dust concentration is more stable, and the energy saving is about 43% after optimization, according to the annual operation of 300 days, the annual average carbon reduction is approximately 2621.34 tons. This method is effective and can be applied widely.

The goal of this lab is to look at how the characteristics of cementitious materials are affected by bending loads combined with dry and wet cycles of sulfate. In this paper, three sets of specimens with different water–cement ratios were designed. This study applied 20% and 40% of the ultimate bending load as a continuous bending load to the cementitious material specimens for a sulfate erosion test. It was discovered that the specimens' porosity, flexural strength, and compressive strength all tended to improve initially before declining as the cementitious material was degraded in the sulfate solution aged. The flexural strength of the cementitious materials declined as the bending load increased, and their internal sulfate ion concentration rose. A transport model of sulfate ions in cementitious materials under the coupling effect of bending load and sulfate erosion was created by combining the improved version of Fick’s second law and chemical reaction kinetics. The simulation results show that the ion transport properties of sulfate ions in cementitious materials are in accordance with the experimental laws. These research results formed the basis of the unified standards for the coupling of load dry and wet cycle systems, as well as evaluating the durability of cementitious materials under corrosive environments.

Determining accurate PM2.5 pollution concentrations and understanding their dynamic patterns is crucial for scientifically informed air pollution control strategies. Traditional reliance on linear correlation coefficients for ascertaining PM2.5 related factors only uncovers superficial relationships. Moreover, the invariance of conventional prediction models restricts their accuracy. To enhance the precision of PM2.5 concentration prediction, this study introduces a novel integrated model that leverages feature selection and a clustering algorithm. Comprising three components - feature selection, clustering, and integrated prediction, the model first employs the non-dominated sorting Genetic Algorithm (NSGA-III) to identify the most impactful features affecting PM2.5 concentration within air pollutants and meteorological factors. This step offers more valuable feature data for subsequent modules. The model then adopts a two-layer clustering method (SOM+K-means) to analyze the multifaceted irregularity within the dataset. Finally, the model establishes the Extreme Learning Machine (ELM) weak learner for each classification, integrating multiple weak learners using the Adaboost algorithm to obtain a comprehensive prediction model. Through feature correlation enhancement, data irregularity exploration, and model adaptability improvement, the proposed model significantly enhances the overall prediction performance. Data sourced from 12 Beijing-based monitoring sites in 2016 were utilized for an empirical study, and the model's results compared with five other predictive models. The outcomes demonstrate that the proposed model significantly heightens prediction accuracy, offering useful insights and potential for broadened application to multifactor correlation concentration prediction methodologies for other pollutants.

This study aimed to determine whether the EQ-5D-5L tool captures the most common persistent symptoms, such as fatigue, memory/concentration problems and dyspnea in patients with post COVID-19 conditions, and if adding these symptoms improves the explained variance of the health-related quality of life (HRQoL). In this exploratory cross-sectional study, two cohorts of Swedish patients (n=177) with a history of COVID-19 infection answeared a questionnaire covering sociodemographic characteristics, clinical factors and HRQoL assessed using EQ-5D-5L with the Visual Analogue Scale (EQ-VAS). Spearman rank correlation and multiple regression analyses were employed to investigate the extent to which the most common persistent symptoms such as fatigue, memory/concentration problems and dyspnea were explained by the EQ-5D-5L. The explanatory power of EQ-5D-5L for EQ-VAS was also analysed, both with and without inclusion of symptom(s). We found that the EQ-5D-5L dimensions partly captured fatigue and memory/concentration problems but performed poorly in capturing dyspnea. Specifically, the EQ-5D-5L explained 55% of the variance in memory/concentration problems, 47% in fatigue and only 14% in dyspnea. Adding fatigue to the EQ-5D-5L increased the explained variance of the EQ-VAS by 5.7%, while the addition of memory/concentration problems and dyspnea had a comparatively smaller impact on the explained variance. Our study highlights the EQ-5D-5L’s strength in capturing fatigue and memory/concentration problems in post COVID-19 patients. However, it also underscores the challenges in assessing dyspnea in this group. Fatigue emerged as a notably influential symptom, significantly enhancing the EQ-5D-5L's predictive ability to for the EQ-VAS score in these patients.

Based on the analysis of the spatial distribution of uranium grade in 348 boreholes of a uranium deposit in Xinjiang, the enrichment and spatial variation of uranium ore in two stopes of the deposit are discussed by using multifractal theory. The distribution characteristics of uranium ore of the two stopes are studied by multifractal parameters: the scaling exponent of mass , the scaling exponent of each sub-set and its corresponding fractal dimension , the fractal dimension D0 and information dimension D1. The differences of uranium distribution in two stopes can be well quantified by multifractal spectrum and multifractal parameters( , , ).10m×10m is defined as a fence unit, and the window sizes are respectively set, the singularity exponent of the two stopes are calculated by this element concentration-area(C-A) method. The results show that the multifractal theory and model can organically combine spatial structure information, scale change information and anisotropy information to obtain low-grade and weak mineral resources information, and can effectively distinguish complex and superimposed anomalies. This will provide a basis for local concentration and spatial variation rules of uranium distribution and the design of the parameters of leaching uranium mining well site.

This study examines the absorption and concentration of anthracene (AN) in the garden radish. Studies were conducted to grow radishes from the sowing stage in soil contaminated with AN, and to grow radishes in soil contaminated with AN following maturity (27 days after sowing). For the growth in AN-containing soil from sowing onward, AN levels immediately after seeding ranged from 12,500-36,300 ng/g-ww. AN concentrations during growing period ranged from 7140-16,000 ng/g-ww in soil and from 38.2-2160 ng/g-ww in radish, respectively. For the growth in AN-containing soil after maturity, AN concentrations in soil and radish ranged from 9560-22,100 ng/g-ww and 342-2270 ng/g-ww. The concentrations of AN in the roots and leaves had a higher density than those in the stems. In these experiments, positive relationships between AN levels in soil and radishes were observed. It is inferred that the greater the degree of soil contamination, the greater the effect on the amount of AN assimilated by the radishes. The concentration ratio (radish-to-soil; Cr/Cs) decreased exponentially with days since AN application. This indicates that the concentration ratio is affected by time in contact with AN. According to the results for the change over time of Cr/Cs and contents by radish part, it is thought that AN in the soil has good absorption through the roots to circulate within the organism, and is preferentially distributed and accumulated in the roots and leaves, which have high organic matter content.

To meet the International Maritime Organization’s requirements for carbon dioxide emissions from ships, a cost-effective and practical ship decarbonization tower was autonomously designed based on the marine diesel engine model 6135G128ZCa. The tower is internally filled with structured packing, and a slot-type liquid distributor at the top of the packing evenly distributes the NaOH solution to absorb carbon dioxide from the ship’s exhaust gas. Experimental research was conducted to investigate the influence of factors such as liquid-to-gas ratio and NaOH concentration on the performance of the decarbonization tower. The results confirmed that the use of NaOH solution can effectively absorb CO2 from ship exhaust gas, reducing CO2 emissions by more than 81.59% and meeting the EEDI (Energy Efficiency Design Index) requirements specified by the IMO.

The airflow carried by artificial aeration provides oxidant O2 for microbial growth and mineral dissolution in heap bioleaching. To investigate the effect of forced aeration rate on bioleaching of low-grade copper sulfide ores, column bioleaching experiments with six columns were conducted in the aeration range of 0~150 L/h at 30~45 ℃. The results showed that when the aeration rate was higher than 95 L/h, the proportions of heap settlement and fine particles mass were much greater than that without aeration. The final total Fe concentration and bacterial cell numbers in pregnant leach solution increased with the increase of aeration rate.The final concentrations of Cu2 + in the mother liquor under aeration conditions of 60-150 L / h were 1.411, 1.432, 1.498, 1.491 and 1.583 g / L, respectively, which were higher than 1.345 g / L under non-aeration conditions. When the aeration rate was 150 L / h, the final Cu leaching rate was 80.1 %, which was 11.4 % higher than that without aeration ( 68.7 % ). Furthermore, in the early stage of leaching, copper leaching rate with 95 L/h aeration rate remained the highest. 结论Artificial aeration accelerates the bioleaching of low-grade copper sulfide ores by improving porosity structure, temperature range of bacterial activity and microbial catalyzed dissolution of targeted minerals.

This article is a logical continuation of the work of Nuritdinov et al. (2021). We analyzed space observations of the apparent surface density of 81 globular clusters (GCs) observed by GAIA DR2 and published in de Boer et al (2019). First, we studied the features of the quality of the GC surface density data, including comparing them with the HST data. Using our 3-parameter model, previously tested on the example of HST space observations, we found the values of the stellar concentration parameter towards the center of the cluster. As a result, we found good correlations of this parameter with the physical characteristics of the GCs. We have also found the corresponding empirical formulas for this parameter.

As a major coal country, China faces the issue of significant gas emissions during the coal mining process. This study aims to improve the utilization efficiency of mine gas, reduce greenhouse gas emissions, and promote the low-carbon and green transformation of the coal industry. A 10kW gas regenerative thermal oxidation (RTO) experimental system was constructed. The effects of initial methane concentration, low-temperature flue gas proportion, and operating load on combustion temperature, methane oxidation rate, high-temperature flue gas energy, and system thermal efficiency were studied. The results show that when the combustion temperature is below 600°C, the CH4 combustion reaction cannot proceed effectively, and the system temperature continuously decreases and cannot be maintained stable. The experiment determines the stable operating methane concentration range of RTO. In this experimental system, the lower limit of the initial methane concentration is 0.28%, corresponding to an 86% methane oxidation rate. As the initial methane concentration decreases, the combustion temperature also decreases, and the methane oxidation rate follows suit. The higher the low-temperature flue gas proportion, the higher the combustion temperature, and the system thermal efficiency and output heat decrease with the increase of the low-temperature flue gas proportion. This experiment explores multiple factors affecting regenerative thermal oxidation, providing an basis for ensuring the safe and stable operation of the system and optimization. Improving the thermal insulation and heat exchange performance of the storage body can expand the lower limit of the initial methane concentration, thereby increasing the stability and thermal efficiency of the system.

While the simple model of the total atmospheric carbon sink effect as a linear function of concentration has provided excellent prediction results, several problems remained to be investigated and solved. The most obvious open issue is the correct treatment of land use change emssions. It turns out that the model improves by mostly neglecting them after 1959. This effectively implies that land use change emissions have been constant and small since then. The key investigation starts with the observation, that the total carbon sink has a short term component which be explained by temperature changes commonly known as El Nin˜o. The apparent paradox is analysed and explained, why contrary to the short term changes no temperature caused trend can be detected in the model, despite the fact that several contributing processes exhibit temperature dependency. The result of this analysis leads to the model extension, where the total effect of sinks and natural emissions are a linear function of concentration and temperature. This model not only explains current measurements but also paleo climate from ice-core time series.

The effect of H2S with high concentrations on catalytic dry reforming of methane (DRM) process has seldom been focused on previously. Herein, a thermodynamic analysis of the DRM reactions in the presence of H2S with the concentration varying in 0-20 vol% was conducted firstly. Several typical types of catalysts including MgO, NiO/MgO and LaNiO3 in different states were prepared for executing DRM at 800 C, 0.1 MPa in the feed of 20 vol% CO2 and 20 vol% CH4 balanced with N2. The catalytic performance of each catalyst for DRM process under conditions of absence and presence of H2S was compared. A promotion effect of increasing H2S concentration on both the conversions of CO2 and CH4 and the molar yields of CO and H2 was observed on all the catalysts especially the MgO and the pristine NiO/MgO. While a significant decline in catalytic activity of either the reduced NiO/MgO or the reduced LaNiO3 catalyst after adding H2S, moderate reactant conversions still sustained. The results of process analysis and catalyst structure characterization suggest that H2S participation can contribute to the increment in CO2 and CH4 conversion, and active S-adsorbed species may play the key role of catalysis in the reactions involving H2S.

p-type Ag-N dual acceptor doped ZnO thin films with long electrical stability were deposited by DC magnetron reactive co-sputtering technique. After deposition, the films were annealed at 400 °C for one hour in a nitrogen-controlled atmosphere. The deposited films were amorphous. However, after annealing they crystallize in the typical hexagonal wurtzite structure of ZnO. The Ag-N dual acceptors were incorporated substitutionally in the structure of zinc oxide and achieving that the three samples presented the p-type conductivity in the ZnO. Initial electrical properties showed a low resistivity of from 1 to10^{−3} Ω.cm, Hall mobility of tens cm2/V.s and a hole concentration from 10^{17} to 10^{19} cm^{−3}. The electrical stability analysis reveals that the p-type conductivity of the ZnO:Ag,N films is very stable and does not revert to n-type, even after 36 months of aging. These results reveal the feasibility of using these films for applications in short-wavelength or transparent optoelectronic devices.

Despite its growing importance as a dry beneficiation method, there is a lack of studies exploring the fundamentals aspects of dry jigging. In this sense, this study focuses on explore some essential aspects of density-based separation in dry jigs, like pulse profile, energy consumption and, especially, stratification over time, also exploring an innovative operational strategy here called “transient pulsation”. The tests were carried out using density tracers distributed across 11 density ranges (0.4-2.4 g/cm³) and employing a base bed (gravel) to analyze their segregation in a pilot-scale dry jig. Pressure drop and active power data were acquired to measure the pulse characteristics and energy consumption. The findings suggest that establishing the dry jigging cycle is more complex than in hydraulic jigs due to the compressibility of air. Stationary pulsation tests revealed an unstable behavior of stratification over time, contrasting with traditional hydraulic jigs, while transient pulsation tests unveiled varied trends in separation quality. Energy consumption analysis underscored the significant role of the blower drive. These insights have the potential to inform operational enhancements in dry jigging.