Dual-engine-driven realizing high-yield synthesis of Para-Xylene directly from CO2-containing syngas.

The direct synthesis of light aromatics, especially para-xylene (p-X), from syngas/CO2 is drawing strong interest, but improving the space-time yield (STY) of p-X is a significant challenge. Here, a dynamic "dual-engine-driven" (DED) catalytic system is designed by combining two partners of ZnCr and FeMn (named "dual-engine") with Z5@SiO2 capsule zeolite. The DED catalyst of 1.0%FeMn&[ZnCr&Z5@SiO2] shows an extremely higher p-X STY of 36.1 gp-x·kgcat-1·h-1, about eight times higher than that of [ZnCr&Z5]. DED manipulates ZnCr engine for methanol formation and drives FeMn engine for light olefins generation together, and then the formed methanol and light olefins are coordinately converted in situ into p-X-rich aromatics over Z5@SiO2. The DED model boosts the driving force for syngas/CO2 conversion, simultaneously concerting the cooperation of "dual-engine" for p-X generation, resulting in extremely high STY of p-X. This study achieves non-petroleum p-X production at industrial-relevant level and advances knowledge in designing innovative heterogeneous catalysts.

Research and application discussion of cranial bone model preparation method based on three-dimensional reconstruction and 3D printing technology.

PURPOSE: The aim of this study was to find an alternative method to meet traditional human anatomy teaching and clinical needs in order to solve the problem of cranial specimen attrition and specimen resource shortage due to long-term use. METHODS: We performed a computed tomography (CT) scan of a well-preserved male cranial specimen and used Mimics 19.0 software for 3D reconstruction and cranial block separation. Subsequently, we compared the recognition ability of the processed cranial digital model with that of the 3D body digital model and used 3D printing to create the cranial model and compare it with the physical specimen. RESULTS: Twenty-two cranial bone block models were obtained, excluding the hyoid bone. Their 3D reconstructed digital models had better bony landmark recognition than the 3D body human digital models, and the differences between the 3D printed models and the physical specimens were minimal. In addition, only one stereolithography (STL) file was required to produce the cranial models, which facilitates repetitive printing at any time. CONCLUSION: By isolating cranial bone blocks through 3D reconstruction techniques and preparing high-quality cranial models in combination with 3D printing techniques, this study solves the problem of shortage of cranial teaching specimens for the sustainable development of clinical and medical schools.

Utility of interim apparent diffusion coefficient value in predicting treatment response among patients with locally advanced cervical cancer treated with radiotherapy.

Background: For locally advanced cervical cancer (LACC), treatment response to radiotherapy (RT) can vary significantly even among those with the same stage classification of International Federation of Gynecology and Obstetrics (FIGO). This study investigated the value of ADC metric for forecasting end-of-treatment outcomes in LACC patients referred for RT. Methods: Eighty patients with pathologically confirmed cervical squamous cell carcinoma with (SCC) were included in the research. Abdominal or pelvic MRI scans were conducted at least three times for all participants: before RT, three weeks after beginning of RT and approximately two months after RT was finalized. Calculated apparent diffusion coefficient (ADC) values of the LACC include: pre-ADC, interim-ADC, ΔADC and Δ%ADC. Based on Response Evaluation Criteria in Solid Tumors (RECIST) 1.1, subjects were calculated and subsequently categorized into good responders group (complete response) and poor responders group (progressive disease, stable disease or partial response). Results: Compared to good-responders, subjects of poor-responder group showed significantly lower values of interim-ADC, ΔADC, and Δ%ADC (all P < 0.05). To distinguish between good and poor responders, the optimal cutoff values of interim-ADC, ΔADC, and Δ%ADC were determined to be 1.067 × 10-3 mm2/sec, 0.209 × 10-3 mm2/sec, and 30.74 % using the ROC curve, with corresponding sensitivities of 83.78 %, 86.49 %, 75.68 %, and specificities of 88.37 %, 86.49 %, 75.68 %, respectively. Multivariate logistic regression revealed that the baseline tumor diameter and interim-ADC were significant prognostic factors for treatment response with an odds ratio (OR) of 0.105 (95 % confidence interval [95 % CI] 0.018-0.616) for baseline tumor diameter and 42.896 (95 % CI 8.205-224.262) for interim-ADC. Conclusion: The interim-ADC value and baseline tumor diameter surfaced as possible indicative factors for predicting the response to RT in patients with LACC.

SPX family response to low phosphorus stress and the involvement of ZmSPX1 in phosphorus homeostasis in maize.

Phosphorus (P) is a crucial macronutrient for plant growth and development, and low-Pi stress poses a significant limitation to maize production. While the role of the SPX domain in encoding proteins involved in phosphate (Pi) homeostasis and signaling transduction has been extensively studied in other model plants, the molecular and functional characteristics of the SPX gene family members in maize remain largely unexplored. In this study, we identified six SPX members, and the phylogenetic analysis of ZmSPXs revealed a close relationship with SPX genes in rice. The promoter regions of ZmSPXs were abundant in biotic and abiotic stress-related elements, particularly associated with various hormone signaling pathways, indicating potential intersections between Pi signaling and hormone signaling pathways. Additionally, ZmSPXs displayed tissue-specific expression patterns, with significant and differential induction in anthers and roots, and were localized to the nucleus and cytoplasm. The interaction between ZmSPXs and ZmPHRs was established via yeast two-hybrid assays. Furthermore, overexpression of ZmSPX1 enhanced root sensitivity to Pi deficiency and high-Pi conditions in Arabidopsis thaliana. Phenotypic identification of the maize transgenic lines demonstrated the negative regulatory effect on the P concentration of stems and leaves as well as yield. Notably, polymorphic sites including 34 single-nucleotide polymorphisms (SNPs) and seven insertions/deletions (InDels) in ZmSPX1 were significantly associated with 16 traits of low-Pi tolerance index. Furthermore, significant sites were classified into five haplotypes, and haplotype5 can enhance biomass production by promoting root development. Taken together, our results suggested that ZmSPX family members possibly play a pivotal role in Pi stress signaling in plants by interacting with ZmPHRs. Significantly, ZmSPX1 was involved in the Pi-deficiency response verified in transgenic Arabidopsis and can affect the Pi concentration of maize tissues and yield. This work lays the groundwork for deeper exploration of the maize SPX family and could inform the development of maize varieties with improved Pi efficiency.

Genome-wide association studies dissect low-phosphorus stress response genes underling field and seedling traits in maize.

Phosphorus (P) is an essential element for plant growth, and its deficiency can cause decreased crop yield. This study systematically evaluated the low-phosphate (Pi) response traits in a large population at maturity and seedling stages, and explored candidate genes and their interrelationships with specific traits. The results revealed a greater sensitivity of seedling maize to low-Pi stress compared to that at maturity stage. The phenotypic response patterns to low-Pi stress at different stages were independent. Chlorophyll content was found to be a potential indicator for screening low-Pi-tolerant materials in the field. A total of 2900 and 1446 significantly associated genes at the maturity and seedling stages were identified, respectively. Among these genes, 972 were uniquely associated with maturity traits, while 330 were specifically detected at the seedling stage under low-Pi stress. Moreover, 768 and 733 genes were specifically associated with index values (low-Pi trait/normal-Pi trait) at maturity and seedling stage, respectively. Genetic network diagrams showed that the low-Pi response gene Zm00001d022226 was specifically associated with multiple primary P-related traits under low-Pi conditions. A total of 963 out of 2966 genes specifically associated with traits under low-Pi conditions or index values were found to be induced by low-Pi stress. Notably, ZmSPX4.1 and ZmSPX2 were sharply up-regulated in response to low-Pi stress across different lines or tissues. These findings advance our understanding of maize's response to low-Pi stress at different developmental stages, shedding light on the genes and pathways implicated in this response.

Exploring the phosphorus-starch content balance mechanisms in maize grains using GWAS population and transcriptome data.

Examining the connection between P and starch-related signals can help elucidate the balance between nutrients and yield. This study utilized 307 diverse maize inbred lines to conduct multi-year and multi-plot trials, aiming to explore the relationship among P content, starch content, and 100-kernel weight (HKW) of mature grains. A significant negative correlation was found between P content and both starch content and HKW, while starch content showed a positive correlation with HKW. The starch granules in grains with high-P and low-starch content (HPLS) were significantly smaller compared to grains with low-P high-starch content (LPHS). Additionally, mian04185-4 (HPLS) exhibited irregular and loosely packed starch granules. A significant decrease in ZmPHOs genes expression was detected in the HPLS line ZNC442 as compared to the LPHS line SCML0849, while no expression difference was observed in AGPase encoding genes between these two lines. The down-regulated genes in ZNC442 grains were enriched in nucleotide sugar and fatty acid anabolic pathways, while up-regulated genes were enriched in the ABC transporters pathway. An accelerated breakdown of fat as the P content increased was also observed. This implied that HPLS was resulted from elevated lipid decomposition and inadequate carbon sources. The GWAS analysis identified 514 significantly associated genes, out of which 248 were differentially expressed. Zm00001d052392 was found to be significantly associated with P content/HKW, exhibiting high expression in SCML0849 but almost no expression in ZNC442. Overall, these findings suggested new approaches for achieving a P-yield balance through the manipulation of lipid metabolic pathways in grains.

PUM2 promoted osteoarthritis progression through PTEN-mediated chondrocyte ferroptosis by facilitating NEDD4 mRNA degradation.

Osteoarthritis (OA) is a prevalent degenerative joint disease with a lack of effective therapeutic. Chondrocyte ferroptosis contributes to the progression of OA. PUM2 is shown to exacerbate ischemia-reperfusion-induced neuroinflammation by promoting ferroptosis, but its role in OA remains unexplored. Here, primary mouse chondrocytes were stimulated with IL-1ß to mimic OA chondrocyte injury in vitro. And PUM2 was upregulated in OA cartilage tissues and IL-1ß-induced chondrocytes. Silencing PUM2 alleviated IL-1ß-induced chondrocyte inflammation and ECM degradation. Mechanistically, PUM2 facilitated the degradation of NEDD4 mRNA by binding to the 3'UTR of NEDD4 mRNA, which in turn inhibited NEDD4 induced PTEN ubiquitination and degradation. Consistently, NEDD4 silencing reversed the ameliorative effect of PUM2 knockdown on chondrocyte injury, and overexpression of PTEN abolished the improved role of NEDD4 in chondrocyte injury. Moreover, PTEN aggravated IL-1ß-induced ferroptosis in chondrocytes through the Nrf2/HO-1 pathway by increasing the levels of Fe2+, ROS, MDA, and ACSL4 protein, decreasing the activity of SOD and the levels of GSH and GPX4 protein, and aggravating mitochondrial damage. Additionally, destabilized medial meniscus (DMM) were conducted to establish the OA mouse model, and adenovirus-mediated PUM2 shRNA was administered intra-articularly. Silencing PUM2 attenuated OA-induced cartilage damage in vivo. In conclusion, PUM2 promoted OA progression through PTEN-mediated chondrocyte ferroptosis by facilitating NEDD4 mRNA degradation.

PPARγ inhibition promotes osteogenic differentiation of bone marrow mesenchymal stem cells and fracture healing.

This study aimed to explore the effects of peroxisome proliferator-activated receptor γ (PPARγ) inhibition on fracture healing of nonunion and the underlying mechanisms. Bone marrow mesenchymal stem cells (BMSCs) were treated with PPARγ antagonist GW9662 (5 µM, 10 µM). Alkaline phosphatase (ALP) staining and Alizarin Red S was used to assess early stage of osteogenesis and osteogenic differentiation. GW9662 (1 mg/kg/day) were administered intraperitoneally into the rats with bone fracture. Bone healing processes in the rat femur fracture model were recorded and assessed by radiographic methods on Weeks 8, 14, and 20 postoperation. Osteogenesis and angiogenesis at the fracture sites were evaluated by radiographic and histological methods on postoperative Week 20. GW9662 treatment increased ALP activity and Alp mRNA expression in rat BMSCs. Moreover, GW9662 administration increased matrix mineralization and mRNA and protein levels of Bmp2 and Runx2 in the BMSCs. In addition, GW9662 treatment improved radiographic score in the fracture rats and increased osteogenesis-related proteins, including type I collagen, osteopontin, and osteoglycin, in the bone tissues of the fracture sites. In conclusion, PPARγ inhibition promotes osteogenic differentiation of rat BMSCs, as well as improves the fracture healing of rats through Bmp2/Runx2 signaling pathway in the rat model of bone fracture.

A review of clinical use of surface-enhanced Raman scattering-based biosensing for glioma.

Glioma is the most common malignant tumor of the nervous system in recent centuries, and the incidence rate of glioma is increasing year by year. Its invasive growth and malignant biological behaviors make it one of the most challenging malignant tumors. Maximizing the resection range (EOR) while minimizing the impact on normal brain tissue is crucial for patient prognosis. Changes in metabolites produced by tumor cells and their microenvironments might be important indicators. As a powerful spectroscopic technique, surface-enhanced Raman scattering (SERS) has many advantages, including ultra-high sensitivity, high specificity, and non-invasive features, which allow SERS technology to be widely applied in biomedicine, especially in the differential diagnosis of malignant tumor tissues. This review first introduced the clinical use of responsive SERS probes. Next, the sensing mechanisms of microenvironment-responsive SERS probes were summarized. Finally, the biomedical applications of these responsive SERS probes were listed in four sections, detecting tumor boundaries due to the changes of pH-responsive SERS probes, SERS probes to guide tumor resection, SERS for liquid biopsy to achieve early diagnosis of tumors, and the application of free-label SERS technology to detect fresh glioma specimens. Finally, the challenges and prospects of responsive SERS detections were summarized for clinical use.

Target intensity correction method based on incidence angle and distance for a pulsed Lidar system.

Pulsed light detecting and ranging (Lidar) is capable of acquiring comprehensive target information within a single pulse, including distance and intensity data. Intensity data reflects the target's backscattered intensity and is commonly regarded as a crucial observational parameter associated with target reflectivity information. Multiple studies have indicated the potential of intensity data in various applications within pulsed Lidar contexts. However, the intensity data is influenced by the incident angle and distance; hence it cannot directly manifest target characteristics. Consequently, a prerequisite for its usage is the implementation of intensity calibration. This paper presents a target intensity correction method based on an improved tail model, designed for preprocessing intensity data. First, the pulse echo signal equation is derived by incorporating the improved tail model with the detected target. On this foundation, a target echo intensity correction model is established to correct the intensities at various incident angles to those at the normal direction. Lastly, the derived approach is validated through simulation analysis, and practical experiments are conducted on a constructed pulsed Lidar system. These experiments meticulously investigate the influences of incident angle and distance, two prominent factors, on echo intensity. In the context of incident angle correction experiments, the mean absolute errors (MAEs) in calibrated values for diverse targets all remain within 0.04 V. Prior to correction, the maximum MAE for the cystosepiment is 0.505 V; after the correction it is reduced to merely 0.02 V, indicating a 96% reduction in error. Furthermore, all discrepancies exhibit an error standard deviation (ESD) of 0.03 V or less, showcasing favorable stability. For distance correction, under normal incidence conditions, a diverse set of targets is measured at different distances to achieve corrected MAE and ESD within 0.05 V. Consequently, the proposed method effectively achieves intensity correction concerning incident angles and distances. To achieve this, a reflectivity lookup table for the relevant targets was established. Combining this with the corrected intensity information enabled target identification in the three-dimensional imaging of pulsed Lidar.

CD274 (PD-L1) negatively regulates M1 macrophage polarization in ALI/ARDS.

Background: Acute lung injury (ALI)/severe acute respiratory distress syndrome (ARDS) is a serious clinical syndrome characterized by a high mortality rate. The pathophysiological mechanisms underlying ALI/ARDS remain incompletely understood. Considering the crucial role of immune infiltration and macrophage polarization in the pathogenesis of ALI/ARDS, this study aims to identify key genes associated with both ALI/ARDS and M1 macrophage polarization, employing a combination of bioinformatics and experimental approaches. The findings could potentially reveal novel biomarkers for the diagnosis and management of ALI/ARDS. Methods: Gene expression profiles relevant to ALI were retrieved from the GEO database to identify co-upregulated differentially expressed genes (DEGs). GO and KEGG analyses facilitated functional annotation and pathway elucidation. PPI networks were constructed to identify hub genes, and differences in immune cell infiltration were subsequently examined. The expression of hub genes in M1 versus M2 macrophages was evaluated using macrophage polarization datasets. The diagnostic utility of CD274 (PD-L1) for ARDS was assessed by receiver operating characteristic (ROC) analysis in a validation dataset. Experimental confirmation was conducted using two LPS-induced M1 macrophage models and an ALI mouse model. The role of CD274 (PD-L1) in M1 macrophage polarization and associated proinflammatory cytokine production was further investigated by siRNA-mediated silencing. Results: A total of 99 co-upregulated DEGs were identified in two ALI-linked datasets. Enrichment analysis revealed that these DEGs were mainly involved in immune-inflammatory pathways. The following top 10 hub genes were identified from the PPI network: IL-6, IL-1ß, CXCL10, CD274, CCL2, TLR2, CXCL1, CCL3, IFIT1, and IFIT3. Immune infiltration analysis revealed a significantly increased abundance of M1 and M2 macrophages in lung tissue from the ALI group compared to the control group. Subsequent analysis confirmed that CD274 (PD-L1), a key immunological checkpoint molecule, was highly expressed within M1 macrophages. ROC analysis validated CD274 (PD-L1) as a promising biomarker for the diagnosis of ARDS. Both in vitro and in vivo experiments supported the bioinformatics analysis and confirmed that the JAK-STAT3 pathway promotes CD274 (PD-L1) expression on M1 macrophages. Importantly, knockdown of CD274 (PD-L1) expression potentiated M1 macrophage polarization and enhanced proinflammatory cytokines production. Conclusion: This study demonstrates a significant correlation between CD274 (PD-L1) and M1 macrophages in ALI/ARDS. CD274 (PD-L1) functions as a negative regulator of M1 polarization and the secretion of proinflammatory cytokines in macrophages. These findings suggest potential new targets for the diagnosis and treatment of ALI/ARDS.

CO2 hydrogenation over Fe-Co bimetallic catalysts with tunable selectivity through a graphene fencing approach.

Tuning CO2 hydrogenation product distribution to obtain high-selectivity target products is of great significance. However, due to the imprecise regulation of chain propagation and hydrogenation reactions, the oriented synthesis of a single product is challenging. Herein, we report an approach to controlling multiple sites with graphene fence engineering that enables direct conversion of CO2/H2 mixtures into different types of hydrocarbons. Fe-Co active sites on the graphene fence surface present 50.1% light olefin selectivity, while the spatial Fe-Co nanoparticles separated by graphene fences achieve liquefied petroleum gas of 43.6%. With the assistance of graphene fences, iron carbides and metallic cobalt can efficiently regulate C-C coupling and olefin secondary hydrogenation reactions to achieve product-selective switching between light olefins and liquefied petroleum gas. Furthermore, it also creates a precedent for CO2 direct hydrogenation to liquefied petroleum gas via a Fischer-Tropsch pathway with the highest space-time yields compared to other reported composite catalysts.

A novel aging-associated lncRNA signature for predicting prognosis in osteosarcoma.

Osteosarcoma (OS) is one of the most prevalent bone tumors in adolescents, and the correlation between aging and OS remains unclear. Currently, few accurate and reliable biomarkers have been determined for OS prognosis. To address this issue, we carried out a detailed bioinformatics analysis based on OS with data from the Cancer Genome Atlas data portal and Human Aging Genomic Resources database, as well as in vitro experiments. A total of 88 OS samples with gene expression profiles and corresponding clinical characteristics were obtained. Through univariate Cox regression analysis and survival analysis, 10 aging-associated survival lncRNAs (AASRs) were identified to be associated with the overall survival of OS patients. Based on the expression levels of the 10 AASRs, the OS patients were classified into two clusters (Cluster A and Cluster B). Cluster A had a worse prognosis, while Cluster B had a better prognosis. Then, 5 AASRs were ultimately included in the signature through least absolute shrinkage and selection operator-Cox regression analysis. Kaplan‒Meier survival analysis verified that the high-risk group exhibited a worse prognosis than the low-risk group. Furthermore, univariate and multivariate Cox regression analyses confirmed that the riskScore was an independent prognostic factor for OS patients. Subsequently, we discovered that the risk signature was correlated with the properties of the tumor microenvironment and immune cell infiltration. Specifically, there was a positive association between the risk model and naïve B cells, resting dendritic cells and gamma delta T cells, while it was negatively related to CD8+ T cells. Finally, in vitro experiments, we found that UNC5B-AS1 inhibited OS cells from undergoing cellular senescence and apoptosis, thereby promoting OS cells proliferation. In conclusion, we constructed and verified a 5 AASR-based signature, that exhibited excellent performance in evaluating the overall survival of OS patients. In addition, we found that UNC5B-AS1 might inhibit the senescence process, thus leading to the development and progression of OS. Our findings may provide novel insights into the treatment of OS patients.

Efficient purification of low-level uranium-containing wastewater by polyamine/amidoxime synergistically reinforced fiber.

The removal and recovery of uranium [U(VI)] from organic containing wastewater has been a challenging in radioactive wastewater purification. Here, we designed a polyamine/amidoxime polyacrylonitrile fiber (PAN-AO-A) with high removal efficiency, excellent selectivity, excellent organic resistance and low cost by combining the anti-organic properties of amidoxime polyacrylonitrile fiber (PAN-AO-A) with the high adsorption capacity of polyamine polyacrylonitrile fiber, which is used to extract U(VI) from low-level uranium-containing wastewater with high ammonia nitrogen and organic content. PAN-AO-A adsorbent with high grafting rate (86.52%), high adsorption capacity (qe = 618.8 mg g-1), and strong resistance to organics and impurity interference is achieved. The adsorption rate of U(VI) in both real organic and laundry wastewater containing uranium is as high as 99.7%, and the partition coefficients (Kd) are 7.61 × 105 mL g-1 and 9.16 × 106 mL g-1, respectively. The saturated adsorption capacity of PAN-AO-A in the continuous system solution can reach up to 505.5 mg g-1, and the concentration of U(VI) in the effluent is as low as 1 µg L-1. XPS analysis and Density functional theory (DFT) studies the coordination form between U(VI) and PAN-AO-A, where the most stable structure is η2-AO(UO2)(CO3)2. The -NH-/-NH2 and -C(NH2)N-OH groups of PAN-AO-A exhibit a synergistic complex effect in the U(VI) adsorption process. PAN-AO-A is a material with profound influence and limitless potential that can be used for wastewater containing U(VI) and organic matter.

[Application of micro-bolus injection and piezoelectric sensors to improve the safety of radiopharmaceuticals bolus injection].

Radiopharmaceutical dynamic imaging typically necessitates intravenous injection via the bolus method. However, manual bolus injection carries the risk of handling errors as well as radiological injuries. Hence, there is potential for automated injection devices to replace manual injection methods. In this study, the effect of micro-bolus pulse injection technology was compared and verified by radioactive experiments using a programmable injection pump, and the overall bubble recognition experiment and rat tail vein simulation injection verification were performed using the piezoelectric sensor preloading method. The results showed that at the same injection peak speed, the effective flushing volume of micro-bolus pulse flushing (about 83 µL/pulse) was 49.65% lower than that of uniform injection and 25.77% lower than that of manual flushing. In order to avoid the dilution effect of long pipe on the volume of liquid, the use of piezoelectric sensor for sealing preloading detection could accurately predict the bubbles of more than 100 µL in the syringe. In the simulated injection experiment of rat tail vein, when the needle was placed in different tissues by preloading 100 µL normal saline, the piezoelectric sensor fed back a large difference in pressure attenuation rate within one second, which was 2.78% in muscle, 17.28% in subcutaneous and 54.71% in vein. Micro-bolus pulse injection method and piezoelectric sensor sealing preloading method have application potential in improving the safety of radiopharmaceutical automatic bolus injection.

Tuning the Acid-Base Properties of Lignin-Derived Carbon Modulated ZnZr/SiO2 Catalysts for Selective and Efficient Production of Butadiene from Ethanol.

The direct selective conversion of ethanol to butadiene (ETB) is a competitive and environmentally friendly process compared to the traditional crude cracking route. The acid-base properties of catalysts are crucial for the direct ETB process. Herein, we report a rationally designed multifunctional lignin-derived carbon-modulated ZnZr/SiO2 (L-ZnZr/SiO2) catalyst with suitable acid-base properties for the direct ETB reaction. A variety of characterization techniques are employed to investigate the relationship between the acid-base properties and catalytic performance of the multifunctional lignin-modulated ZnZr/SiO2 catalysts. The results revealed that the rationally additional lignin-modulated carbon enhances both the acidity and basicity of the ZnZr/SiO2 catalysts, providing a suitable acid-base ratio that boosts the direct ETB reactivity. Meanwhile, the 1% L-ZnZr/SiO2 catalyst possessed ethanol conversion and butadiene selectivity as high as 98.4% and 55.5%, respectively, and exhibited excellent catalytic stability.

The roles of liquidity and delay in financial markets based on an optimal forecasting model.

We investigate the roles of liquidity and delay in financial markets through our proposed optimal forecasting model. The efficiency and liquidity of the financial market are examined using stochastic models that incorporate information delay. Based on machine learning, we estimate the in-sample and out-of-sample forecasting price performances of the six proposed methods using the likelihood function and Bayesian methods, and the out-of-sample prediction performance is compared with the benchmark model ARIMA-GARCH. We discover that the forecasting price performance of the proposed simplified delay stochastic model is superior to that of the benchmark methods by the test methods of a variety of loss function, superior predictive ability test (SPA), Akaike information criterion (AIC), and Bayesian information criterion (BIC). Using data from the Chinese stock market, the best forecasting model assesses the efficiency and liquidity of the financial market while accounting for information delay and trade probability. The rise in trade probability and delay time affects the stability of the return distribution and raises the risk, according to stochastic simulation. The empirical findings show that empirical and best forecasting approaches are compatible, that company size and liquidity (delay time) have an inverse relationship, and that delay time and liquidity have a nonlinear relationship. The most efficient have optimal liquidity.

Carbon-Based Electron Buffer Layer on ZnOx -Fe5 C2 -Fe3 O4 Boosts Ethanol Synthesis from CO2 Hydrogenation.

The conversion of CO2 into ethanol with renewable H2 has attracted tremendous attention due to its integrated functions of carbon elimination and chemical synthesis, but remains challenging. The electronic properties of a catalyst are essential to determine the adsorption strength and configuration of the key intermediates, therefore altering the reaction network for targeted synthesis. Herein, we describe a catalytic system in which a carbon buffer layer is employed to tailor the electronic properties of the ternary ZnOx -Fe5 C2 -Fe3 O4 , in which the electron-transfer pathway (ZnOx →Fe species or carbon layer) ensures the appropriate adsorption strength of -CO* on the catalytic interface, facilitating C-C coupling between -CHx * and -CO* for ethanol synthesis. Benefiting from this unique electron-transfer buffering effect, an extremely high ethanol yield of 366.6 gEtOH kgcat -1 h-1 (with CO of 10 vol % co-feeding) is achieved from CO2 hydrogenation. This work provides a powerful electronic modulation strategy for catalyst design in terms of highly oriented synthesis.

3D Printing Hierarchically Nano-Ordered Structures.

Natural materials are composed of a limited number of molecular building blocks and their exceptional properties are governed by their hierarchical structure. However, this level of precision is unattainable with current state-of-the-art materials for 3D printing. Herein, new self-assembled printable materials based on block copolymers (BCPs) enabling precise control of the nanostructure in 3D are presented. In particular, well-defined BCPs consisting of poly(styrene) (PS) and a polymethacrylate-based copolymer decorated with printable units are selected as suitable self-assembled materials and synthesized using controlled radical polymerization. The synthesized library of BCPs are utilized as printable formulations for the fabrication of complex 3D microstructures using two-photon laser printing. By fine-tuning the BCP composition and solvent in the formulations, the fabrication of precise 3D nano-ordered structures is demonstrated for the first time. A key point of this work is the achievement of controlled nano-order within the entire 3D structures. Thus, imaging of the cross-sections of the 3D printed samples is performed, enabling the visualization also from the inside. The presented versatile approach is expected to create new avenues for the precise design of functional polymer materials suitable for high-resolution 3D printing exhibiting tailor-made nanostructures.

Use of Alkali-Activated Slag as an Environment-Friendly Agent for High-Performance Stabilized Soil.

Discharged slag not only occupies a large amount of land for disposal, but also causes serious environmental pollution. The use of alkali-activated slag (AAS) instead of cement as a soil-stabilization agent is beneficial for industrial waste disposal and energy conservation, which complies with the concept of green and low-carbon sustainable development in the construction industry. In this study, the compressive strength, water permeability coefficient, chloride migration coefficient and sulfate resistance of alkali-activated slag-stabilized soil (AASS) were evaluated, and compared with those of cement-stabilized soil (CSS). The hydrated crystalline phases and microscopic pore structures were analyzed by X-ray diffraction, electrochemical impedance spectroscopy (EIS) and mercury intrusion porosimetry (MIP) tests, respectively. The results indicate that, compared with CSS, AASS exhibits a higher compressive strength, lower water permeability, chloride migration coefficient and better resistance to sulfate attack, with the optimum dosage higher than 10 wt.%. The results of the MIP analysis show that the addition of AAS reduces the porosity by 6.47%. The combined use of soil and AAS proves to be a viable and sustainable method of waste utilization and carbon emission reduction in the construction industry, which provides a practical path towards carbon peaking and carbon neutrality.