Molten Salt-Promoted MgO Adsorbents for CO2 Capture: Transient Kinetic Studies.

Optimization of MgO adsorbents is predominantly focused on the regulation of appropriate adsorption sites for CO2 associated with Mg2+-O2- sites of low coordination. Here, for the first time, we conducted transient kinetic experiments to identify and characterize changes of the CO2 molecular path in MgO-based CO2 adsorbents upon the addition of molten salt modifiers. Among the optimized samples, addition of 10 mol % NaNO2 on the surface of MgO exhibited the highest CO2 uptake (15.7 mmol g-1) at 350 °C compared to less than 0.1 mmol g-1 for the unpromoted MgO. Kinetic modeling showed that the interaction of molten salt-promoted MgO with CO2 at 300 °C involves three different processes, namely, fast surface adsorption associated with surface-active basic sites, chemical reaction associated with MgCO3 formation, and a slow diffusion step being the rate-limiting step of the carbonation process. Furthermore, transient kinetic studies coupled with mass spectrometry under low CO2 partial pressure agreed well with the kinetic simulation results based on TGA measurements, demonstrating an in-depth understanding of the CO2-capturing performance gained and its considerable significance for future practical designs of precombustion CO2 capture.

Industrial carbon dioxide capture and utilization: state of the art and future challenges.

Dramatically increased CO2 concentration from several point sources is perceived to cause severe greenhouse effect towards the serious ongoing global warming with associated climate destabilization, inducing undesirable natural calamities, melting of glaciers, and extreme weather patterns. CO2 capture and utilization (CCU) has received tremendous attention due to its significant role in intensifying global warming. Considering the lack of a timely review on the state-of-the-art progress of promising CCU techniques, developing an appropriate and prompt summary of such advanced techniques with a comprehensive understanding is necessary. Thus, it is imperative to provide a timely review, given the fast growth of sophisticated CO2 capture and utilization materials and their implementation. In this work, we critically summarized and comprehensively reviewed the characteristics and performance of both liquid and solid CO2 adsorbents with possible schemes for the improvement of their CO2 capture ability and advances in CO2 utilization. Their industrial applications in pre- and post-combustion CO2 capture as well as utilization were systematically discussed and compared. With our great effort, this review would be of significant importance for academic researchers for obtaining an overall understanding of the current developments and future trends of CCU. This work is bound to benefit researchers in fields relating to CCU and facilitate the progress of significant breakthroughs in both fundamental research and commercial applications to deliver perspective views for future scientific and industrial advances in CCU.

Combination of Multivariate Standard Addition Technique and Deep Kernel Learning Model for Determining Multi-Ion in Hydroponic Nutrient Solution.

Ion-selective electrodes (ISEs) have recently become the most attractive tools for the development of efficient hydroponic systems. Nevertheless, some inherent shortcomings such as signal drifts, secondary ion interferences, and effected high ionic strength make them difficult to apply in a hydroponic system. To minimize these deficiencies, we combined the multivariate standard addition (MSAM) sampling technique with the deep kernel learning (DKL) model for a six ISEs array to increase the prediction accuracy and precision of eight ions, including NO3-, NH4+, K+, Ca2+, Na+, Cl-, H2PO4-, and Mg2+. The enhanced data feature based on feature enrichment (FE) of the MSAM technique provided more useful information to DKL for improving the prediction reliability of the available ISE ions and enhanced the detection of unavailable ISE ions (phosphate and magnesium). The results showed that the combined MSAM-feature enrichment (FE)-DKL sensing structure for validating ten real hydroponic samples achieved low root mean square errors (RMSE) of 63.8, 8.3, 29.2, 18.5, 11.8, and 8.8 mg·L-1 with below 8% coefficients of variation (CVs) for predicting nitrate, ammonium, potassium, calcium, sodium, and chloride, respectively. Moreover, the prediction of phosphate and magnesium in the ranges of 5-275 mg·L-1 and 10-80 mg·L-1 had RMSEs of 29.6 and 8.7 mg·L-1 respectively. The results prove that the proposed approach can be applied successfully to improve the accuracy and feasibility of ISEs in a closed hydroponic system.

High Aspect Ratio Perforated Co3O4 Nanowires Derived from Cobalt-Carbonate-Hydroxide Nanowires with Enhanced Sensing Performance.

Herein, we report the facile synthesis of high-aspect ratio perforated Co3O4 nanowires derived from cobalt-carbonate-hydroxide (Co(CO3)0.5(OH) 0.11H2O) nanowires. The Co(CO3)0.5(OH) 0.11H2O nanowires were synthesized by simple hydrothermal process at 120 °C while annealing of such nanowires at 400 °C leads the formation of perforated Co3O4 nanowires. The prepared nanowires were characterized by several techniques which confirmed the high aspect ratio and well-crystallinity for the synthesized nanowires. For application point of view, the prepared perforated Co3O4 nanowires were used as efficient electrode material to fabricate highly sensitive and selective hydrazine chemical sensor. The electrochemical impedance spectroscopy (EIS) technique was employed to confirm the successful modification of the electrode. The key parameters of chemical sensor, such as detection limit, sensitivity, and linear range, have been systematically explored. The fabricated hydrazine sensor displayed a rather low detection limit of 4.52 µM (S/N = 3), a good sensitivity of 25.70 µA · mM-1, and a wide linear range of 16.97-358.34 µM.

Preparation and Characterization of Highly Efficient CuFe Mixed Oxides for Total Oxidation of Toluene.

In this study, Cu/Fe type mixed oxides catalysts with different ratios of metal irons are successfully synthesized via fixed hydrothermal treatment. The prepared samples were then characterized by a combination of several techniques, such as XRD, BET, SEM, H2-TPR and FT-IR. The catalytic activity enhanced with the increasing amount of Cu in the HT-precursors, but it decreases when the ratio of Cu/Fe is above 4. The influence of calcination temperature was also studied in the search of highly dispersed active catalysts. The catalytic test indicated that the Cu/Fe mixed oxides possessed outstanding highly activity towards toluene oxidation. The highest catalytic activity was exhibited by Cu4Fe-400 of which the T50 and T90 reaches at about 258 °C and 294 °C respectively.

Food preferences, personality and parental rearing styles: analysis of factors influencing health of left-behind children.

PURPOSE: To understand the health status and problems of left-behind children (LBC) in rural China, those whose parents have moved to urban areas without them, and to focus on ways to improve their physical and mental health. METHODS: The study examined 827 children between 7 and 15 years old, selected using stratified cluster random sampling from five towns in Xiji County of the Ningxia Hui Autonomous Region. Each child was classified as either LBC or non-LBC. Measures included age- and sex-specific height and body mass index (kg/m2), a food preference questionnaire, the Revised Junior Eysenck Personality Questionnaire, and the Egna Minnen av Barndoms Uppfostran-My Memories of Upbringing (EMBU). RESULTS: Malnutrition rates for LBC and non-LBC were 14.83 % (70/472) and 7.04 % (25/355) (χ 2  = 11.86, p < 0.01). More LBC reported hating vegetables and fruits. Eysenck Personality Questionnaire profiles of LBC revealed a significantly higher degree of neuroticism and psychoticism, and a significantly lower lie scale score (p < 0.01). LBC's EMBU profiles showed that the paternal approach lacked emotional warmth and understanding and the maternal approach was characterized by favoritism, over-interference and overprotection. There were a significant negative correlation between the personality characteristic of neuroticism and liking vegetables and fruits (p < 0.01), and a negative correlation between psychoticism and liking vegetables (p < 0.05). CONCLUSION: The health status of LBC is problematic. Food preferences, personality type and parenting styles should be taken into account when measures are developed to improve the health of these children.

Feature Correlation-Steered Capsule Network for object detection.

Despite Convolutional Neural Networks (CNNs) based approaches have been successful in objects detection, they predominantly focus on positioning discriminative regions while overlooking the internal holistic part-whole associations within objects. This would ultimately lead to the neglect of feature relationships between object and its parts as well as among those parts, both of which are significantly helpful for detecting discriminative parts. In this paper, we propose to "look insider the objects" by digging into part-whole feature correlations and take the attempts to leverage those correlations endowed by the Capsule Network (CapsNet) for robust object detection. Actually, highly correlated capsules across adjacent layers share high familiarity, which will be more likely to be routed together. In light of this, we take such correlations between different capsules of the preceding training samples as an awareness to constrain the subsequent candidate voting scope during the routing procedure, and a Feature Correlation-Steered CapsNet (FCS-CapsNet) with Locally-Constrained Expectation-Maximum (EM) Routing Agreement (LCEMRA) is proposed. Different from conventional EM routing, LCEMRA stipulates that only those relevant low-level capsules (parts) meeting the requirement of quantified intra-object cohesiveness can be clustered to make up high-level capsules (objects). In doing so, part-object associations can be dug by transformation weighting matrixes between capsules layers during such "part backtracking" procedure. LCEMRA enables low-level capsules to selectively gather projections from a non-spatially-fixed set of high-level capsules. Experiments on VOC2007, VOC2012, HKU-IS, DUTS, and COCO show that FCS-CapsNet can achieve promising object detection effects across multiple evaluation metrics, which are on-par with state-of-the-arts.

TLR2 agonist promotes myeloid-derived suppressor cell polarization via Runx1 in hepatocellular carcinoma.

Myeloid-derived suppressor cells (MDSCs) play a critical role in maintaining the tumor immune microenvironment; thus, the promotion of MDSC polarization will improve immunotherapies for cancers. However, the mechanisms involved in controlling MDSC polarization in hepatocellular carcinoma remain largely unclear. In this study, we found that injection of Pam3CSK4 attenuated the process of tumor growth, along with reduction of MDSC and recovery of T cell function. Moreover, Pam3CSK4 promoted MDSC polarization by targeting Runx1. Runx1 inhibitor reversed the therapeutic effect of Pam3CSK4 by increasing tumor size and weight and decreasing the survival rate of tumor mice. In addition, targeting Runx1 reduced the expression of CD11c, F4/80, CD80/CD86 and MHC-II in MDSC after Pam3CSK4 stimulation in vivo and in vitro. MDSC also exhibited consistent changes with increasing reactive oxygen species (ROS) production after Pam3CSK4 and Ro5-3335 treatment. RNA sequence data revealed that tfrc, steap3, and gclm were up-regulated in the Pam3CSK4/Ro5-3335 group compared with Pam3CSK4 treatment alone, suggesting that the regulatory effect of TLR2 and Runx1 on MDSC might act through the ferroptosis pathway. Overall, our study has identified a critical role for TLR2 and Runx1 in regulating the differentiation and function of MDSCs and has provided a new mechanism of controlling MDSC polarization during HCC immunotherapy.

Effects of micro-nano bubble with CO2 treated water on the growth of Amaranth green (Amaranthus viridis).

The micro and nano bubble (MNB) technology, due to its promising features and advantages, has become increasingly popular in agriculture. MNB-treated water positively impacts plant growth, especially when it is treated with a combination of gas-like carbon dioxide (CO2), injected through the MNB generator. Therefore, this study used MNB water with CO2 that are small bubbles of nanometer and micrometer diameters having several unique physical properties that make them useful for water treatments. This research evaluates the effect of MNBs and CO2-treated water on leafy vegetable Amaranth green (Amaranthus viridis). The experiment divided the Amaranth plants into three major groups, G1, G2, and G3, irrigated by MNB water with dissolved CO2, MNBs with only Air, and simple tap water, respectively. The first treatment group (G1) (MNBs with CO2) was further divided into three sub-divisions, i.e., G1A, G1B, G1C, and the second treatment group G2 (MNBs with Air) was divided into three sub-groups, i.e., G2A, G2B, and G2C, while the third group G3 with only one category as only controlled group. These sub-divisions of treatment groups G1 and G2 were done to investigate the impact of MNBs and CO2 treated water with different time durations. For example, in G1A, the water treatment with MNBs and CO2 was kept five minutes, for G1B 10 minutes, and G1C 15 minutes. Similar method was adopted for G2 as well. According to the results, water treated with MNB and CO2 has a significant (90%) impact on the Amaranth germination rate and plant growth. Specifically, pots irrigated with the MNBs + CO2-treated water showed better germination and plant growth rate than the MNBs + Air treated water. Overall, both treatment groups, G1 and G2, showed significantly higher impacts than the CK groups (simple water). Further, this experiment showed that the 10 and 15 minutes treatment of water (G1B, G1C and G2B, G2C) increased the stem height and root size compared to the 5 minutes treated water (G1A, G2A). This study concludes that the water with MNBs has a positive impact on the vegetables and can be an effective technology to improve crop yield.

Unravelling the Mechanism of Intermediate-Temperature CO2 Interaction with Molten-NaNO3 -Salt-Promoted MgO.

The optimization of MgO-based adsorbents as advanced CO2 -capture materials is predominantly focused on their molten-salt modification, for which theoretical and experimental contributions provide great insights for their high CO2 -capture performance. The underlying mechanism of the promotion effect of the molten salt on CO2 capture, however, is a topic of controversy. Herein, advanced experimental characterization techniques, including in situ environmental transmission electron microscopy (eTEM) and CO2 chemisorption by diffuse-reflectance infrared Fourier transform spectroscopy (DRIFTS), transient 18 O-isotopic exchange, and density functional theory (DFT), are employed to elucidate the mechanism of the CO2 interaction with molten-salt-modified MgO in the 250-400 °C range. Herein, eTEM studies using low (2-3 mbar) and high (700 mbar) CO2 pressures illustrate the dynamic evolution of the molten NaNO3 salt promoted and unpromoted MgO carbonation with high magnification (<50 nm). The formation of 18 O-NaNO3 (use of 18 O2 ) and C16 O18 O following CO2 interaction, verifies the proposed reaction path: conversion of NO3 - (NO3 -  â†’ NO2 +  + O2- ), adsorption of NO2 + on MgO with significant weakening of CO2 adsorption strength, and formation of [Mg2+ … O2- ] ion pairs preventing the development of an impermeable MgCO3 shell, which largely increases the rate of bulk MgO carbonation.

Assessment of spray deposition, drift and mass balance from unmanned aerial vehicle sprayer using an artificial vineyard.

Under the rapid development of unmanned aerial vehicle (UAV) plant protection products (PPP) application in Asian countries, the drift risk of UAV sprayer operation in orchard or vineyard is fairly high because of the much finer droplets generated and the higher height than ground sprayers, increasing threats to non-targeted crop, human and environment. However, there is few of comprehensive experimental study on the effects of UAV type and nozzle type on spray deposition and drift from UAV sprayer. The objectives of this study were to compare the spray performance of three different typical commercial UAV types (helicopter, 6-rotor and 8-rotor) with two nozzles types (hollow cone nozzle, HCN and air-injector flat fan nozzle, AIN) in vineyard. An artificial vineyard and three vertical collection frames, designed and built by ourselves, were applied for collecting droplets together with PVC collectors, petri dishes and rotary samples. The characteristics of deposition, drift and mass balance of UAV aerial spraying in vineyard were analyzed. As a result, under the crosswind speed of 3.11-3.79 m/s, AIN promoted spray deposition and uniformity and reduced drift significantly compared to HCN for all tested UAVs, improving of the utilization of PPP. The fitted regression functions of the sedimenting and airborne drift were obtained, respectively, and the drift percentage reduction values of AIN compared to HCN determined based on those functions varied from 81% to 95%. With HCN, 49.3%-73.4% of measured droplets drifted into non-targeted area and the highest proportion of drift loss was found for the airborne spray drift. According to the principle of more deposition and less drift, the spray performance of the three UAVs can be ranked in an order of 6-rotor, 8-rotor and helicopter, and two main reasons causing the difference in spray performance were the vortex airflow and the nozzle arrangement.

A smart diagnostic tool based on deep kernel learning for on-site determination of phosphate, calcium, and magnesium concentration in a hydroponic system.

Calcium, phosphate, and magnesium are essential nutrients for plant growth. The in situ determination of these nutrients is an important task for monitoring them in a closed hydroponic system where the nutrient elements need to be individually quantified based on ion-selective electrode (ISE) sensing. The accuracy issue of calcium ISEs due to interference, drift, and ionic strength, and the unavailability of phosphate and magnesium ISEs makes the development of these ion detecting tools hard to set up in a hydroponic system. This study modeled and evaluated a smart tool for recognising three ions (calcium, phosphate, and magnesium) based on the automatic multivariate standard addition method (AMSAM) and deep kernel learning (DKL) model. The purpose was to improve the accuracy of calcium ISEs, determining phosphate through cobalt electrochemistry, and soft sensing of magnesium ions. The model provided better performance in on-site detecting and measuring those ions in a lettuce hydroponic system achieving root mean square errors (RMSEs) of 12.5, 12.1, and 7.5 mg L-1 with coefficients of variation (CVs) below 5.0%, 7.0%, and 10% for determining Ca2+, H2PO4 -, and Mg2+ in the range of 150-250, 100-200, and 20-70 mg L-1 respectively. Furthermore, the DKL was implemented for the first time in the third platform (LabVIEW) and deployed to determine three ions in a real on-site hydroponic system. The open architecture of the SDT allowed posting the measured results on a cloud computer. This would help growers monitor their plants' nutrients conveniently. The informative data about the three mentioned ions that have no commercial sensors so far, could be adapted to the other components to develop a fully automated fertigation system for hydroponic production.

Evaluation of the growth, photosynthetic characteristics, antioxidant capacity, biomass yield and quality of tomato using aeroponics, hydroponics and porous tube-vermiculite systems in bio-regenerative life support systems.

The nutrient delivery system is one of the most important hardware components in tomato (Lycopersicon esculentum Mill.) production in Bio-regenerative Life Support Systems (BLSS) for future long-term space mission. The objective of this study was to investigate the influences of different nutrient delivery systems (aeroponics, hydroponics and porous tube-vermiculite) on the growth, photosynthetic characteristics, antioxidant capacity, biomass yield and quality of tomato during its life cycle. The results showed that the dry weight of aeroponics and porous tube-vermiculite treatment group was 1.95 and 1.93 g/fruit, but the value of hydroponics treatment group was only 1.56 g/fruit. Both tomato photosynthesis and stomatal conductance maximized at the development stage and then decreased later in senescent leaves. At the initial stage and the development stage, POD activities in the aeroponics treatment were higher than other two treatments, reached 3.6 U/mg prot and 4.6 U/mg prot, respectively. The fresh yield 431.3 g/plant of hydroponics treatment group was lower. At the same time, there were no significant differences among nutrient delivery systems in the per fruit fresh mass, which was 14.2-17.5 g/fruit.

Effect of Fluoride on the Morphology and Electrochemical Property of Co3O4 Nanostructures for Hydrazine Detection.

In this paper, we systematically investigated the influence of fluoride on the morphology and electrochemical property of Co3O4 nanostructures for hydrazine detection. The results showed that with the introduction of NH4F during the synthesis process of Co3O4, both Co(CO3)0.5(OH)·0.11H2O and Co(OH)F precursors would be generated. To understand the influence of F on the morphology and electrochemical property of Co3O4, three Co3O4 nanostructures that were respectively obtained from bare Co(CO3)0.5(OH)·0.11H2O, Co(OH)F and Co(CO3)0.5(OH)·0.11H2O mixtures and bare Co(OH)F were successfully synthesized. The electrochemical tests revealed the sensing performance of prepared Co3O4 nanostructures decreased with the increase in the fluoride contents of precursors. The more that dosages of NH4F were used, the higher crystallinity and smaller specific surface area of Co3O4 was gained. Among these three Co3O4 nanostructures, the Co3O4 that was obtained from bare Co(CO3)0.5(OH)·0.11H2O-based hydrazine sensor displayed the best performances, which exhibited a great sensitivity (32.42 µA·mM-1), a low detection limit (9.7 µΜ), and a wide linear range (0.010-2.380 mM), together with good selectivity, great reproducibility and longtime stability. To the best of our knowledge, it was revealed for the first time that the sensing performance of prepared Co3O4 nanostructures decreased with the increase in fluoride contents of precursors.

SPAD-based leaf nitrogen estimation is impacted by environmental factors and crop leaf characteristics.

Chlorophyll meters are widely used to guide nitrogen (N) management by monitoring leaf N status in agricultural systems, but the effects of environmental factors and leaf characteristics on leaf N estimations are still unclear. In the present study, we estimated the relationships among SPAD readings, chlorophyll content and leaf N content per leaf area for seven species grown in multiple environments. There were similar relationships between SPAD readings and chlorophyll content per leaf area for the species groups, but the relationship between chlorophyll content and leaf N content per leaf area, and the relationship between SPAD readings and leaf N content per leaf area varied widely among the species groups. A significant impact of light-dependent chloroplast movement on SPAD readings was observed under low leaf N supplementation in both rice and soybean but not under high N supplementation. Furthermore, the allocation of leaf N to chlorophyll was strongly influenced by short-term changes in growth light. We demonstrate that the relationship between SPAD readings and leaf N content per leaf area is profoundly affected by environmental factors and leaf features of crop species, which should be accounted for when using a chlorophyll meter to guide N management in agricultural systems.