Search

Explanation and prediction for the product of trehalose dihydrate dehydration process was realized in this work. β form is the thermodynamic dehydration product of trehalose dihydrate. And α form is the kinetic dehydration product of trehalose dihydrate, which was analyzed by low-frequency Raman spectra, mid-frequency Raman difference spectra and IR difference spectra, and the analysis results confirmed that the crystal structure of trehalose dihydrate and α form are similar. The selective dehydration process from trehalose dihydrate to α form is due to their similar short-range orders. Amorphous trehalose is the uncontrollable dehydration product of trehalose dihydrate due to the collapse of water channels. The dehydration product of trehalose dihydrate by freeze-drying was a mixture of α form and amorphous phase, and the content of amorphous trehalose in the freeze-drying product increases with the decrease of the particle size of dihydrate. Study on the dehydration principle of organic hydrates will guide the preparation, storage and desolvation of drugs and foods. [ABSTRACT FROM AUTHOR]

Coal fly ash (CFA), a byproduct of coal combustion, is a hazardous industrial solid waste. Its excessive global production, coupled with improper disposal practices, insufficient utilization and limited awareness of its inherent hazards, poses a significant threat to both ecological environment and human health. Based on the physicochemical properties of CFA and its leachates, we elucidate the forms of CFA and potential pathways for its entry into the human body, as well as the leaching behavior, maximum tolerance and biological half-life of toxic elements present in CFA. Furthermore, we provide an overview of current strategies and methods for mitigating the leaching of these harmful elements from CFA. Moreover, we systemically summarize toxic effect of CFA on organisms across various tiers of complexity, analyze epidemiological findings concerning the human health implications resulting from CFA exposure, and delve into the biotoxicological mechanisms of CFA and its leachates at cellular and molecular levels. This review aims to enhance understanding of the potential toxicity of CFA, thereby promoting increased public awareness regarding the disposal and management of this industrial waste. • The properties of CFA determine its pathway into organisms and toxicity. • High CFA levels have detrimental to soil microbial activity and plant growth. • CFA exposure causes more toxic effects on lab animals than wild animals. • CFA exposure linked to neurological issues in children and respiratory/cardiovascular problems in adults. • Endocytosis and pinocytosis are the primary means by which cells ingest CFA particles. [ABSTRACT FROM AUTHOR]

Copyright of Angewandte Chemie is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

When ocean transportation is used, possible disruptions both at sea and on land should be taken into account in the planning process of the affected supply chain. In this paper, a framework to enable flexible global supply chain operational planning in stochastic environments is presented. In order to cope with unexpected events like natural or man-made disasters, flexible international long-distance transportation modes and postponement strategies are taken into account in our supply chain model. In order to balance supply chain costs and the flexibility of supply chains, a two-stage multi-scenario stochastic programming model is developed where the stochastic events are represented by corresponding scenarios. High quality solutions of all our problem instances are generated by using a Python based stochastic programming framework to solve the model. Finally, managerial insights related to flexible supply chain planning in stochastic environments are derived from our computational results. [ABSTRACT FROM AUTHOR]

The rapid expansion of coal-to-ethylene glycol (CtEG) industry leads to an oversupply of ethylene glycol and poor economic performance. Dimethyl oxalate is an important intermediate in this process, which can be selectively hydrogenated to methyl glycolate by changing the catalyst. Methyl glycolate is urgently needed for large-scale production of high-end degradable polyglycolic acid. However, the reported literature neither explores whether this alternative technology can turn the CtEG process into profit nor investigates the effect of various catalysts on the system performance of this alternative technology route. Therefore, three coal-to-methyl glycolate (CtMG) processes with various catalysts are proposed and optimized through rigorous modeling and simulation. The advantages and disadvantages of these three CtMG processes are analyzed and compared with the CtEG process. Results show that the dimethyl oxalate to methyl glycolate process with Ag-based catalyst has the highest yield of methyl glycolate (93.51%) compared with other catalysts. Three proposed CtMG processes have better techno-economic performance than the CtEG process. The carbon utilization and exergy efficiencies of the proposed CtMG processes are increased by 11.47%–19.22% and 9.58%–19.01%, respectively. The proposed CtMG processes turn a loss into a profit, which can improve the internal rate of return of CtEG process from −0.31% to higher than 24.14%. In particular, the CtMG process with Ag-based catalyst has the highest exergy efficiency, 50.95%, and internal rate of return, 27.48%. Therefore, CtMG technology can significantly relieve the survival pressure of CtEG enterprises, and improve their profitability and anti-risk capabilities. The research results of this study can provide an excellent theoretical basis and technical support for the transformation and upgrading of the CtEG industry. Feasibility analysis of coal-to-methyl glycolate technology to improve the technoeconomic performance of coal to ethylene glycol industry. [Display omitted] • Three CtMG processes with various catalysts are proposed and optimized through rigorous modeling. • Carbon and exergy efficiencies of the proposed CtMG processes are increased by 11.47%–19.22% and 9.58%–19.01%. • Proposed CtMG processes improve the internal rate of return from −0.31% to higher than 24.14%. • CtMG process with Ag-based catalyst has the best comprehensive performance. [ABSTRACT FROM AUTHOR]

The requirement for ethylene glycol (EG) continues to surge owing to the booming demand for indispensable platform materials. Unfortunately, there is limited insight into engineering modeling, process enhancement, and process optimization to achieve carbon neutrality in ethylene glycol production. Herein, four biomass-to-ethylene glycol (BtEG) processes that integrate renewable energy for hydrogen production and CO 2 utilization are proposed to find the best strategy for the carbon-neutral and cost-effective development of the ethylene glycol industry. Rigorous steady-state modeling and simulation of the proposed BtEG processes with various gasification agents are conducted to investigate the effect of different gasification agents on the performance of the BtEG processes. The technoeconomic and environmental performance of the proposed processes is assessed and compared with the conventional process. Results show that the proposed BtEG processes can significantly boost the system performance of the conventional process. The carbon utilization efficiency, exergy efficiency, and internal rate of return of four proposed BtEG processes are improved by 38.96%–43.2%, 0.98%–7.13%, and 1.94%–11.28%, respectively. The environmental performance of the proposed BtEG processes is greatly superior to that of the conventional process since the life cycle GHG emissions of the proposed processes are negative, which are lower than −1.47 t/t. Therefore, this study provides a sustainable and cost-efficient improvement direction for the carbon-intensive ethylene glycol industries. [Display omitted] • Four BtEG processes with various gasification agents were designed and simulated. • Effect of various gasification agents on the technoeconomic performance of BtEG process are optimized. • Proposed BtEG process can increase carbon efficiency from 39.3% to 82.5%. • Proposed BtEG process can improve internal rate of return from 17.56% to 28.84%. • Life cycle GHG emissions of the proposed BtEG processes is negative. [ABSTRACT FROM AUTHOR]

• Deep learning-assisted automatic resolution of overlapped peaks in untargeted GC-MS. • Resolution of high-quality chromatograms and mass spectra. • Batch processing without parameters to be optimized. Modern gas chromatography-mass spectrometry (GC-MS) is the workhorse for the high-throughput profiling of volatile compounds in complex samples. It can produce a considerable amount of two-dimensional data, and automatic methods are required to distill chemical information from raw GC-MS data efficiently. In this study, we proposed an Auto matic Res olution method (AutoRes) based on pseudo-Siamese convolutional neural networks (pSCNN) to extract the meaningful features swamped by the noises, baseline drifts, retention time shifts, and overlapped peaks. Two pSCNN models were trained with 400,000 augmented spectral pairs, respectively. They can predict the selective region (pSCNN1) and elution region (pSCNN2) of compounds in an untargeted manner. The accuracies of the pSCNN1 model and the pSCNN2 model on their test sets are 99.9% and 92.6%, respectively. Then, the chromatographic profile of each component was automatically resolved by full rank resolution (FRR) based on the predicted regions by these models. The performance of AutoRes was evaluated on the simulated and plant essential oil datasets. Compared to AMDIS and MZmine, AutoRes resolves more reasonable mass spectra, chromatograms, and peak areas to identify and quantify compounds. The average match scores of AutoRes (925 and 936) outperformed AMDIS (909 and 925) and MZmine (888 and 916) when resolving mass spectra from overlapped peaks on the Set Ⅰ and Set Ⅱ of plant essential oil dataset and matching them against the NIST17 library. It extracted peak areas and mass spectra automatically from 10 GC-MS files of plant essential oils, and the entire process was completed in 8 min without any prior information or manual intervention. It is implemented in Python and is available as an open-source package at https://github.com/dyjfan/AutoRes. [ABSTRACT FROM AUTHOR]

The development of carbon neutrality technology for the coal-based chemical industry is of great interest to many coal-rich countries. An improved coal to ethylene glycol process integrated with CO 2 utilization for direct synthesis of dimethyl carbonate (CTEG-CU) is proposed for in-situ utilization of CO 2 from the conventional coal to ethylene glycol plant to co-produce ethylene glycol and dimethyl carbonate. In the improved process, the CO 2 emitted from the conventional process is reused in the dimethyl carbonate direct synthesis unit with dehydration reactive distillation. It is coincidental that the products produced by this unit are the same as the conventional process. The improved process is firstly modeled and simulated to establish its material and exergy balance models. Its techno-economic and environmental performance are compared with those of the conventional process. Results show that the carbon utilization efficiency, exergy efficiency, and internal rate of return of the improved process are increased by 58.55%, 39.23%, and 22.32%, respectively. In addition, the improved process has better environmental performance since its direct CO 2 emission is significantly reduced by 96.92%. [Display omitted] • An improved CTEG-CU process is developed for in-situ utilization of CO 2 emissions. • Effect of the key operational parameters on the system performance is optimized. • Carbon efficiency and IRR of the improved process are increased by 58.55% and 22.32%. • Direct CO 2 emission of the improved process is significantly reduced by 96.92%. [ABSTRACT FROM AUTHOR]

To improve the volatile dust removal efficiency in the process of pulverized coal pyrolysis, investigate the characteristics of fine coke and coal ash in volatile and the requirements for dust collector. Expound the research status and development of dust removal technology in the process of coal pyrolysis. The results show that, the way of catalytic hydrogenation pyrolysis can promote cracking of heavy tar components, which can reduce the dust removal difficulty markedly. The combination of different dust removal devices and agglomeration of fine particles before entering dust collector also can improve the dust removal efficiency. [ABSTRACT FROM AUTHOR]

Radiotherapy plays an important role in modern oncology, but its treatment efficacy is limited by the radioresistance of tumor cells. As a member of the inhibitor of apoptosis protein family, survivin plays a key role in developing radioresistance by mediating apoptosis evasion, promoting epithelial‐mesenchymal transition, and modulating cell cycle dynamics. Efficient downregulation of survivin expression presents a promising strategy to enhance the antitumor effects of radiotherapy. Herein, we report the design of a hafnium‐porphyrin‐based cationic metal‐organic layer (CMOL) with quaternary ammonium capping groups to deliver small interfering RNAs (siRNAs) for enhanced radiotherapy. The CMOL@siRNA nanoplatform not only increased energy deposition from X‐rays and reactive oxygen species generation via a unique radiotherapy‐radiodynamic therapy process, but also effectively delivered siRNAs to downregulate survivin expression and ameliorate radioresistance of cancer cells. Consequently, CMOL@siRNA in combination with low‐dose X‐ray irradiation demonstrated remarkable antitumor efficacy with 96.9 % and 91.4 % tumor growth inhibition in murine colorectal carcinoma and triple‐negative breast cancer models, respectively. [ABSTRACT FROM AUTHOR]

Abnormal cancer metabolism causes hypoxic and immunosuppressive tumor microenvironment (TME), which limits the antitumor efficacy of photodynamic therapy (PDT). Herein, we report a photosensitizing nanoscale metal–organic layer (MOL) with anchored 3‐bromopyruvate (BrP), BrP@MOL, as a metabolic reprogramming agent to enhance PDT and antitumor immunity. BrP@MOL inhibited mitochondrial respiration and glycolysis to oxygenate tumors and reduce lactate production. This metabolic reprogramming enhanced reactive oxygen species generation during PDT and reshaped the immunosuppressive TME to enhance antitumor immunity. BrP@MOL‐mediated PDT inhibited tumor growth by >90 % with 40 % of mice being tumor‐free, rejected tumor re‐challenge, and prevented lung metastasis. Further combination with immune checkpoint blockade potently regressed the tumors with >98 % tumor inhibition and 80 % of mice being tumor‐free. [ABSTRACT FROM AUTHOR]

Background: Despite rising incomes and rapid economic growth, there remains a significant gender gap in health outcomes among rural children in China. This study examines whether the gender gap in child health is related to the behavior of caregivers when seeking healthcare, and whether healthcare subsidies help to bridge the gender gap in rural health outcomes. Methods: Focusing on vision care specifically, we draw on data from a randomized controlled trial of 13,100 children in Gansu and Shaanxi provinces in China that provided subsidized eyeglasses to myopic children in one set of schools (henceforth, referred to as the treatment schools) and provided prescription information but not subsidized eyeglasses to myopic children in another set of schools (control schools). Results: The baseline results reveal that while female students generally have worse vision than male students, they are significantly less likely than male students to be taken by their caregivers to a vision exam. The experimental results indicate, however, that caregivers respond positively to both health information and subsidized healthcare, regardless of the gender of their children. When prescription information is paired with a subsidy voucher for healthcare (a free pair of eyeglasses), the uptake rate rises dramatically. Conclusions: The gender gap in healthcare can be minimized by implementing subsidized healthcare policies. Trial registration: The protocol for this study was approved in full by Institutional Review Boards at Stanford University (Palo Alto, California, USA) and the Zhongshan Ophthalmic Center of Sun Yat-sen University (ZOC, Guangzhou, China). Permission was received from local Boards of Education in each region and from the principals of all schools. The principles of the Declaration of Helsinki were followed throughout. The original trial (Registration site: http://isrctn.org. Registration number: ISRCTN03252665) was designed to study the effect of providing free spectacles on children's educational performance. The original trial was retrospectively registered on 09/25/2012. [ABSTRACT FROM AUTHOR]

Copyright of Angewandte Chemie is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper is concerned with the finite-time synchronization (FTS) of delayed fractional-order memristive neural networks (FMNNs) by using quantized control. Firstly, two kinds of quantized controllers are designed to eliminate the residual synchronization errors that appear owing to the characteristics of memristive connection weights. Then, to derive α -dependent FTS criteria for drive–response FMNNs, the Gronwall inequality technique is used by combination with the direct estimation method. Compared with the existing results, the advantages of the derived synchronization criteria are discussed from the aspects of both theory and simulation. In addition, the relationships between the finite-time parameter and the quantization parameters are displayed. It reveals that there is a compromise between the admissible finite-time and the saved network bandwidth. Finally, two examples are given to illustrate the effectiveness of the obtained results. • Quantized controllers are designed for the finite-time synchronization. • Synchronization criteria is derived by Gronwall inequality and estimation technique. • Gronwall inequality and estimation technique are applied to obtain synchronization. • Relationship between finite time parameter and quantization parameters is given. [ABSTRACT FROM AUTHOR]

[Display omitted] • Various micro/nanostructures manufacturing technologies were adopted to assist sensitivity of gas sensors. • Flexible 2-D materials and various mechanisms were reported to aim extra-low concentrations and mechanically robustness. Gas devices were widely adopted in environmentally friendly electronics with the aid of coupling effect. Around machine learning and sustainable system, gas sensing with robustness and early/low concentration was the trends. Gas and environmental parameters monitoring is a hot research topic along with the technology development trends of the Internet of Things and smart systems (aiming for an early and accurate detection). To introduce next-generation gas sensors, this review paper reported gas electronics from micro/nano to the era of a self-powered and artificially intelligent system. To figure out the development trends of gas sensing, four key issues needed to be noted including micro/nanostructures, multi-functional purpose, assisted self-powered/zero power, and the machine learning-enhanced methodology. To increase sensitivity/early detection and to produce chip-level units, various micro/nanostructures manufacturing technologies were introduced to assist the sensitivity of gas sensors. Flexible 2-D materials and various mechanisms were reported to aim for the detection of extra-low concentrations and mechanically robustness for multi-functional applications. With the aid of the triboelectric/piezoelectric mechanism, the gas devices were widely adopted in environmentally friendly electronics. Moreover, facing the developmental trends in machine learning and sustainable system, smart gas detection with robustness and early/low concentration for medical and healthcare applications was the next engine trend. This review paper not only concluded the development trends of the next-generation gas sensor but also point out the era of the self-powered and artificially intelligent system in gas monitoring. [ABSTRACT FROM AUTHOR]

[Display omitted] • Real improvement potential of CTM process is ascertained by advanced exergy analysis. • 94.47% of the exergy destruction of the CTM process is endogenous. • Avoidable exergy destruction of the CTM process is about 46.55%. • Unavoidable endogenous exergy destruction of CTM process has the largest proportion. • Total exergy destruction of the improved CTM process is reduced by 14.78%. The efficient conversion and utilization of CO 2 is of great strategic significance to achieve the goal of "carbon neutrality". The production of green methanol from the captured CO 2 of industrial tail gas and green hydrogen of renewable energy can not only effectively reduce carbon emissions, but also solve the problem of green hydrogen storage and transportation. Facing with the unsatisfactory thermodynamic performance of CO 2 to methanol (CTM) process, however, little literature has been reported on the systematic investigation of its thermodynamic performance to reduce its avoidable exergy destruction instead of spending wasted effort to reduce unavoidable one. This study conducted an advanced exergy analysis of the CTM process to ascertain its real improvement potential and interactions among the components. Results show that the real improvement potential of the CTM process is 46.55%. Most of the exergy destruction of the CTM process is endogenous, which accounts for 94.47% of the total exergy destruction. After combination of splitting the exergy destruction, it founds that the unavoidable endogenous exergy destruction of the CTM process has the largest proportion, 50.93%, followed by avoidable endogenous exergy destruction, 43.55%. Besides, several improvement strategies are proposed to reduce the avoidable exergy destruction, which indicate that the total exergy destruction of the improved CTM process is reduced by 14.78% and exergy efficiency is increased by 4.91%. [ABSTRACT FROM AUTHOR]

[Display omitted] • A novel process for EG and LNG from steel mill off-gases is proposed. • Exergy efficiency of the proposed process is improved by 10.05%. • Total production cost of the proposed process is reduced by 17.46%. • Market fluctuations have much lower impact on the proposed process than the standalone processes. Coke oven gas and Linz Donawitz gas are pollutive off-gases of steel mill plants. Their potential chemical value can be used to produce high value-added chemicals and fuels by means of coproduction. Thus, a novel coproduction system for ethylene glycol and liquid natural gas from steel mill off-gases (CG-ELNG) is proposed and optimized through a rigorous process modeling and simulation. The thermodynamic and technoeconomic performance of the proposed process are analyzed and compared with the conventional standalone ethylene glycol and liquid natural gas production processes. Results show that the optimal feed ratio of coke oven gas and Linz Donawitz gas is 2.42 to have the most suitable hydrogen to carbon ratio and the highest resource utilization efficiency of the proposed processes. The exergy efficiency of the process is high to 60.45%, which is 10.05% higher than that of the standalone off-gases based ethylene glycol production process. The total production cost is reduced by 17.46%, and internal rate of return is improved by 7.47% in comparison with the standalone processes. In addition, the sensitivity analysis results reveal that the fluctuations of raw material, utilities consumption, and production capacity have much lower impact on the proposed process than the standalone processes. Therefore, the findings of this study provide a newly promising direction for highly efficiently utilization of steel off-gases. [ABSTRACT FROM AUTHOR]

PandaX-4T is a ton-scale dark matter direct detection experiment using a dual-phase TPC technique at the China Jinping Underground Laboratory. Various ultra-low background technologies have been developed and applied to material screening for PandaX-4T, including HPGe gamma spectroscopy, ICP-MS, NAA, radon emanation measurement system, krypton assay station, and alpha detection system. Low background materials were selected to assemble the detector. Surface treatment procedures were investigated to further suppress radioactive background. Combining measured results and Monte Carlo simulation, the total material background rates of PandaX-4T in the energy region of 1–25 keVee are estimated to be (9.9 ± 1.9) × 10−3 mDRU for electron recoil and (2.8 ± 0.6) × 10−4 mDRU for nuclear recoil. In addition, natKr in the detector is estimated to be < 8 ppt. [ABSTRACT FROM AUTHOR]

The CO 2 -to-light olefins technology represents a significant approach to mitigating the greenhouse effect and advancing green energy solutions. However, little literature comprehensively analyzes and optimizes its thermodynamic performance. This study proposes an interpretable machine learning-assisted advanced exergy analysis and optimization framework to ascertain the actual improvement potential and determine effective strategies for optimizing this system. The advanced exergy analysis method aims to identify the avoidable exergy destruction and interactions between components of the system, while integrating an interpretable machine learning model to provide the key parameters for enhancing the system's exergy efficiency through feature importance analysis. The findings indicate that the exergy destruction of the system amounts to 656.06 MW, with 96.81 % of this exergy destruction being attributed to endogenous factors and approximately 66.51 % of it being potentially avoidable. The random forest model, exhibiting superior predictive accuracy compared to other machine learning models, is coupled with the interpretable Shapley additive explanation approach to discern the most crucial parameters of the system. Results indicated catalyst properties have the greatest impact on the output performance of the system, contributing up to 66.1 % to the predicted results. The active component type, reaction temperature, and promoter content have the largest contribution to the prediction of CO 2 conversion ratio and light olefins selectivity. Furthermore, the key input features are optimized by screening for better catalysts and conducting sensitivity analysis. After optimization, the system's avoidable exergy destruction is significantly saved by 32.27 %, resulting in an enhancement in exergy efficiency by 8.12 %. [Display omitted] • Proposed an interpretable machine learning-assisted advanced exergy analysis and optimization framework. • Identified the preferred machine learning model for CTLO system. • Determined the key parameters for improving the performance of CTLO system by SHAP method. • 96.81 % of the exergy destruction of CTLO system is endogenous and its real improvement potential is 66.51 %. • Avoidable exergy destruction of CTLO system is saved by 32.27 % and exergy efficiency is improved by 8.12 %. [ABSTRACT FROM AUTHOR]

• An ISC scheme is developed, which combines the advantages of sampled-data control and intermittent control. • A control-interval-dependent functional is constructed for the stabilization analysis of the resulting closed-loop system. • Based on the designed Lyapunov functional, the 'jump' phenomena of adjacent Lyapunov functionals at the switching instants can be eliminated and some unnecessary restrictions on the Lyapunov matrices are dropped. • In combination with the Lyapunov stability theory and some inequality techniques, two stability criteria are presented to guarantee the exponential stabilization of NNs via ISC. In this article, a control-interval-dependent Lyapunov functional is introduced to address the stabilization problem of neural networks under intermittent sampled-data control. By virtue of this Lyapunov functional, the 'jump' phenomena of the adjacent Lyapunov functionals at the switching instants can be eliminated without imposing any additional restrictions on the Lyapunov matrices. Combining with the Lyapunov stability theory and inequality estimation techniques, some rigorous analyses on the exponential stability of the resulting closed-loop system are carried out. Then, an explicit expression for controller gain is developed based on the feasibility of certain specified LMIs. Furthermore, a quantitative relationship between the duty cycle of the rest interval and the sampling period is revealed when designing the intermittent sampled-data controller. Lastly, some simulation results are provided to illustrate the effectiveness of the proposed theoretical results. [ABSTRACT FROM AUTHOR]

• A method based on the interaction of organic components for exploring the synergistic effect of co-pyrolysis was proposed. • Positive synergy from volatile products was observed with the adding of vitrinite with 25%. • Inertinite inhibited the formation of volatiles during co-pyrolysis with negative synergy. • No obvious synergy was observed for acid-washed low-rank coal with cellulose at the hating rate of 10 or 20 ℃·min−1. • The integrative action of maceral groups played a significant role during the co-pyrolysis process. A methodological approach towards synergistic effects from co-pyrolysis of lignocellulosic biomass with low-rank coal was proposed. The main maceral group from low-rank coal and primary organic components from biomass were selected to investigate the interaction of organic components. Thermal behavior and kinetic analysis on the co-pyrolysis of cellulose with acid-washed low-rank coal/vitrinite/inertinite were explored via TGA combined with iso -conversional method. The results indicated that the maceral group from low-rank coal showed different synergistic effects on the pyrolysis parameters and product distribution. The synergistic effect of vitrinite on the yield of volatile was closely related to its mass ratio. Positive and negative synergistic effects were observed when the mass ratio of vitrinite was 25% and 75%, respectively. Inertinite inhibited the formation of volatiles during co-pyrolysis and overall exhibited a negative synergy. No obvious synergy was observed for acid-washed low-rank coal when the heating was 10 °C·min−1 and 20 °C·min−1, while positive synergistic effects were found at a high mass ratio and heating rate. The integrative action of maceral groups played a significant role during the co-pyrolysis process. [ABSTRACT FROM AUTHOR]

A novel strategy of enhancing the dielectric and energy storage properties of Na 0.5 Bi 0.5 TiO 3 –BaTiO 3 (NBT–BT) ceramics by introducing a K 0.5 Na 0.5 NbO 3 (KNN) ferroelectric phase is proposed herein, and its underlying mechanism is elucidated. The lead-free KNN ceramic decreases the residual polarisation and increases the electric breakdown strength of the NBT–BT matrix through the simultaneous modification of its A-sites and B-sites. The obtained NBT−BT− x −KNN ceramics have a perovskite structure with unifying grains. A bulk 0.9NBT–BT–0.1KNN ceramic sample with a thickness of 0.2 mm possesses a high energy storage density of 2.81 J/cm3 at an applied electric field of 180 kV/cm. Moreover, it exhibits good insulation properties and undergoes rapid charge and discharge processes. Therefore, the obtained 0.9NBT–BT–0.1KNN ceramic can be potentially used in high-power applications because of its high energy density, good insulation properties, and large discharge rate. [ABSTRACT FROM AUTHOR]

Conventional chemotherapy targets proliferative cancer cells to halt tumor progression or regress tumors. However, the plasticity of tumor cells enables their phenotypical changes to acquire chemo-resistance, leading to treatment failure or tumor recurrence after a successful treatment course. Here, we report the use of high-dose pharmacologic ascorbate to potentiate treatment efficacy of nanoscale coordination polymers (NCPs) delivering two clinical combinations of chemotherapeutics, carboplatin/docetaxel and oxaliplatin/SN38, and to target metabolic plasticity of tumor cells. Combination treatments of high-dose ascorbate and NCPs overcome multi-drug resistance by significantly reducing the abundance of cancer stem cells (CSCs) in solid tumors, as evidenced by reduced expression of tumor pluripotency factors. The clearance of CSCs inhibits post-surgery recurrence and systemic metastasis in multiple mouse models of cancer. [ABSTRACT FROM AUTHOR]

The PandaX-4T liquid xenon detector at the China Jinping Underground Laboratory is used to measure the solar ^{8}B neutrino flux by detecting neutrinos through coherent scattering with xenon nuclei. Data samples requiring the coincidence of scintillation and ionization signals (paired), as well as unpaired ionization-only signals (US2), are selected with energy threshold of approximately 1.1 keV (0.33 keV) nuclear recoil energy. Combining the commissioning run and the first science run of PandaX-4T, a total exposure of 1.20 and 1.04  tonne·year are collected for the paired and US2, respectively. After unblinding, 3 and 332 events are observed with an expectation of 2.8±0.5 and 251±32 background events, for the paired and US2 data, respectively. A combined analysis yields a best-fit ^{8}B neutrino signal of 3.5 (75) events from the paired (US2) data sample, with ∼37% uncertainty, and the background-only hypothesis is disfavored at 2.64σ significance. This gives a solar ^{8}B neutrino flux of (8.4±3.1)×10^{6}  cm^{-2} s^{-1}, consistent with the standard solar model prediction. It is also the first indication of solar ^{8}B neutrino "fog" in a dark matter direct detection experiment.

This article is concerned with the event-triggered synchronization of Lur'e systems subject to actuator saturation. Aiming at reducing control costs, a switching-memory-based event-trigger (SMBET) scheme, which allows a switching between the sleeping interval and the memory-based event-trigger (MBET) interval, is first presented. In consideration of the characteristics of SMBET, a piecewise-defined but continuous looped-functional is newly constructed, under which the requirement of positive definiteness and symmetry on some Lyapunov matrices is dropped within the sleeping interval. Then, a hybrid Lyapunov method (HLM), which bridges the gap between the continuous-time Lyapunov theory (CTLT) and the discrete-time Lyapunov theory (DTLT), is used to make the local stability analysis of the closed-loop system. Meanwhile, using a combination of inequality estimation techniques and the generalized sector condition, two sufficient local synchronization criteria and a codesign algorithm for the controller gain and triggering matrix are developed. Furthermore, two optimization strategies are, respectively, put forward to enlarge the estimated domain of attraction (DoA) and the allowable upper bound of sleeping intervals on the premise of ensuring local synchronization. Finally, a three-neuron neural network and the classical Chua's circuit are used to carry out some comparison analyses and to display the advantages of the designed SMBET strategy and the constructed HLM, respectively. Also, an application to image encryption is provided to substantiate the feasibility of the obtained local synchronization results.

The efficacy of radiotherapy (RT) is limited by inefficient X-ray absorption and reactive oxygen species generation, upregulation of immunosuppressive factors, and a reducing tumor microenvironment (TME). Here, the design of a mitochondria-targeted and digitonin (Dig)-loaded nanoscale metal-organic framework, Th-Ir-DBB/Dig, is reported to overcome these limitations and elicit strong antitumor effects upon low-dose X-ray irradiation. Built from Th 6 O 4 (OH) 4 secondary building units (SBUs) and photosensitizing Ir(DBB)(ppy) 2 2+ (Ir-DBB, DBB = 4,4'-di(4-benzoato)-2,2'-bipyridine; ppy = 2-phenylpyridine) ligands, Th-Ir-DBB exhibits strong RT-radiodynamic therapy (RDT) effects via potent radiosensitization with high-Z SBUs for hydroxyl radical generation and efficient excitation of Ir-DBB ligands for singlet oxygen production. Th-Ir-DBB/Dig releases digitonin in acidic TMEs to trigger disulfidptosis of cancer cells and sensitize cancer cells to RT-RDT through glucose and glutathione depletion. The released digitonin simultaneously downregulates multiple immune checkpoints in cancer cells and T cells through cholesterol depletion. As a result, Th-Ir-DBB/dig plus X-ray irradiation induces strong antitumor immunity to effectively inhibit tumor growth in mouse models of colon and breast cancer., (© 2024 The Author(s). Advanced Materials published by Wiley‐VCH GmbH.)