Iron and Steel Industry Emissions: A Global Analysis of Trends and Drivers.

The iron and steel industry (ISI) is important for socio-economic progress but emits greenhouse gases and air pollutants detrimental to climate and human health. Understanding its historical emission trends and drivers is crucial for future warming and pollution interventions. Here, we offer an exhaustive analysis of global ISI emissions over the past 60 years, forecasting up to 2050. We evaluate emissions of carbon dioxide and conventional and unconventional air pollutants, including heavy metals and polychlorinated dibenzodioxins and dibenzofurans. Based on this newly established inventory, we dissect the determinants of past emission trends and future trajectories. Results show varied trends for different pollutants. Specifically, PM2.5 emissions decreased consistently during the period 1970 to 2000, attributed to adoption of advanced production technologies. Conversely, NOx and SO2 began declining recently due to stringent controls in major contributors such as China, a trend expected to persist. Currently, end-of-pipe abatement technologies are key to PM2.5 reduction, whereas process modifications are central to CO2 mitigation. Projections suggest that by 2050, developing nations (excluding China) will contribute 52-54% of global ISI PM2.5 emissions, a rise from 29% in 2019. Long-term emission curtailment will necessitate the innovation and widespread adoption of new production and abatement technologies in emerging economies worldwide.

Properties of Ni-Al2O3 composite coating by laser-assisted pulse electrodeposition.

To study the influence of laser process parameters on the surface properties of the coating, N i-A l 2 O 3 composite coatings on 304 stainless-steel sheets with laser-assisted pulsed electrodeposition was proposed in this paper. Laser single pulse energy and scanning speed were selected as research factors. Single-factor experiments were performed to investigate the effect of various factors on the surface morphology, particle mass fraction, microhardness, surface roughness, and corrosion resistance of the composite coating. The experimental results show that the surface properties of the composite coating first increase and then decrease with increasing laser single pulse energy. When the laser single pulse energy is 11 µJ, the minimum surface roughness value is 0.380 µm with a smooth and uniform coating surface and the best surface morphology. Moreover, as the scanning speed increases, the corrosion resistance of the composite coating initially increases and then decreases. The corrosion resistance of the composite coatings is best with a scanning speed of 1000 mm/s. When the scanning speed was 1500 mm/s, the particle mass fraction in the coating reached a maximum of 1.984%; meanwhile, the highest hardness of the composite coating was obtained with the value of 476.38 HV.

Development and validation of a genomic nomogram based on a ceRNA network for comprehensive analysis of obstructive sleep apnea.

Objectives: Some ceRNA associated with lncRNA have been considered as possible diagnostic and therapeutic biomarkers for obstructive sleep apnea (OSA). We intend to identify the potential hub genes for the development of OSA, which will provide a foundation for the study of the molecular mechanism underlying OSA and for the diagnosis and treatment of OSA. Methods: We collected plasma samples from OSA patients and healthy controls for the detection of ceRNA using a chip. Based on the differential expression of lncRNA, we identified the target genes of miRNA that bind to lncRNAs. We then constructed lncRNA-related ceRNA networks, performed functional enrichment analysis and protein-protein interaction analysis, and performed internal and external validation of the expression levels of stable hub genes. Then, we conducted LASSO regression analysis on the stable hub genes, selected relatively significant genes to construct a simple and easy-to-use nomogram, validated the nomogram, and constructed the core ceRNA sub-network of key genes. Results: We successfully identified 282 DElncRNAs and 380 DEmRNAs through differential analysis, and we constructed an OSA-related ceRNA network consisting of 292 miRNA-lncRNAs and 41 miRNA-mRNAs. Through PPI and hub gene selection, we obtained 7 additional robust hub genes, CCND2, WT1, E2F2, IRF1, BAZ2A, LAMC1, and DAB2. Using LASSO regression analysis, we created a nomogram with four predictors (CCND2, WT1, E2F2, and IRF1), and its area under the curve (AUC) is 1. Finally, we constructed a core ceRNA sub-network composed of 74 miRNA-lncRNA and 7 miRNA-mRNA nodes. Conclusion: Our study provides a new foundation for elucidating the molecular mechanism of lncRNA in OSA and for diagnosing and treating OSA.

Photocatalytic destruction of volatile aromatic compounds by platinized titanium dioxide in relation to the relative effect of the number of methyl groups on the benzene ring.

The photocatalytic destruction (PCD) of volatile organic compounds (VOC) into environmentally benign compounds is one of the most ideal routes for the management of indoor air quality. It is nevertheless not easy to achieve the mineralization of aromatic VOC through PCD technology because of their recalcitrant structures (i.e., conjugated π benzene ring). In this research, the PCD potential against three model aromatic hydrocarbons (i.e., benzene (B), toluene (T), and m-xylene (X): namely, BTX) has been explored using a titanium dioxide (TiO2) supported platinum (Pt) catalyst after the high-temperature hydrogen (H2)-based reduction (R) pre-treatment (i.e., Pt/TiO2-R). The effects of the key process variables (e.g., relative humidity (RH), oxygen (O2) content, flow rate, VOC concentration, and the co-presence of VOC) on the PCD efficiency and related mechanisms were also assessed in detail. The PCD efficiency is seen to increase with the rise in the increasing number of methyl groups on the benzene ring (in the order of benzene (46.5%), toluene (68.2%), and m-xylene (95.9%)), as the adsorption and activation of the VOC molecule on the photocatalyst surface are promoted by the increased distribution of electrons on the benzene ring. The BTX were oxidated subsequently by the photogenerated reactive oxygen species (ROS), i.e., the hydroxyl radicals (•OH) and superoxide anion radicals (•O2-). The overall results of this study are expected to help expand the applicability of photocatalysis towards air quality management by offering detailed insights into the factors and processes governing the photocatalytic decomposition of aromatic VOCs.

Prediction of the oxidation potential of PM2.5 exposures from pollutant composition and sources.

The inherent oxidation potential (OP) of atmospheric particulate matter has been shown to be an important metric in assessing the biological activity of inhaled particulate matter and is associated with the composition of PM2.5. The current study examined the chemical composition of 388 personal PM2.5 samples collected from students and guards living in urban and suburban areas of Beijing, and assessed the ability to predict OP from the calculated metrics of carcinogenic risk, represented by ELCR (excess lifetime cancer risk), non-carcinogenic risk represented by HI (hazard index), and the composition and sources of the particulate matter using multiple linear regression methods. The correlations between calculated ELCR and HI and the measured OP were 0.37 and 0.7, respectively. HI was a better predictor of OP than ELCR. The prediction models based on pollutants (Model_1) and pollution sources (Model_2) were constructed by multiple linear regression method, and Pearson correlation coefficients between the predicted results of Model_1 and Model_2 with the measured volume normalized OP are 0.81 and 0.80, showing good prediction ability. Previous investigations in Europe and North America have developed location-specific relationships between the chemical composition of particulate matter and OP using regression methods. We also examined the ability of relationships between OP and composition, sources, developed in Europe and North America, to predict the OP of particulate matter in Beijing from the composition and sources determined in Beijing. The relationships developed in Europe and North America provided good predictive ability in Beijing and it suggests that these relationships can be used to predict OP from the chemical composition measured in other regions of the world.

Haploidentical hematopoietic SCT using helical tomotherapy for total-body irradiation and targeted dose boost in patients with high-risk/refractory acute lymphoblastic leukemia.

A novel conditioning regimen using helical tomotherapy (HT) was developed to deliver 10 Gy for total body irradiation (TBI) and simultaneously augment dose to 12 Gy for targeted dose boost to total marrow, central nervous system leukemia, and extramedullary disease sites in patients with high-risk or relapsed/refractory acute lymphoblastic leukemia (ALL) receiving haploidentical allogeneic hematopoietic stem cell transplantation (allo-HSCT). Fourteen patients were included, eight of these patients were in first complete remission (CR1), one was in CR2, one had a partial response and four patients had refractory disease at transplantation. The median delivered average dose was 11.395 Gy (range 10.06-12.17). The median planning target volume D95 was 8.2 Gy (range 7.52-9.01). The median delivered dose to skeleton bone with active bone marrow sites was 12.685 Gy (range 11.12-13.52). The results of this trial suggest that using HT TBI confers satisfactory immunosuppression and excellent eradication of malignant cells in patients with high-risk ALL undergoing allo-HSCT, especially in those with refractory ALL. After a median follow-up of 14.6 months (range 4-28), four patients experienced non-relapse mortality, ten patients are alive in durable CR including remission of extramedullary leukemic infiltration. One-year overall survival and disease-free survival rates post-transplantation were both 70.7%.

Activity-dependent synaptic plasticity of a chalcogenide electronic synapse for neuromorphic systems.

Nanoscale inorganic electronic synapses or synaptic devices, which are capable of emulating the functions of biological synapses of brain neuronal systems, are regarded as the basic building blocks for beyond-Von Neumann computing architecture, combining information storage and processing. Here, we demonstrate a Ag/AgInSbTe/Ag structure for chalcogenide memristor-based electronic synapses. The memristive characteristics with reproducible gradual resistance tuning are utilised to mimic the activity-dependent synaptic plasticity that serves as the basis of memory and learning. Bidirectional long-term Hebbian plasticity modulation is implemented by the coactivity of pre- and postsynaptic spikes, and the sign and degree are affected by assorted factors including the temporal difference, spike rate and voltage. Moreover, synaptic saturation is observed to be an adjustment of Hebbian rules to stabilise the growth of synaptic weights. Our results may contribute to the development of highly functional plastic electronic synapses and the further construction of next-generation parallel neuromorphic computing architecture.

Ultrafast synaptic events in a chalcogenide memristor.

Compact and power-efficient plastic electronic synapses are of fundamental importance to overcoming the bottlenecks of developing a neuromorphic chip. Memristor is a strong contender among the various electronic synapses in existence today. However, the speeds of synaptic events are relatively slow in most attempts at emulating synapses due to the material-related mechanism. Here we revealed the intrinsic memristance of stoichiometric crystalline Ge2Sb2Te5 that originates from the charge trapping and releasing by the defects. The device resistance states, representing synaptic weights, were precisely modulated by 30 ns potentiating/depressing electrical pulses. We demonstrated four spike-timing-dependent plasticity (STDP) forms by applying programmed pre- and postsynaptic spiking pulse pairs in different time windows ranging from 50 ms down to 500 ns, the latter of which is 10(5) times faster than the speed of STDP in human brain. This study provides new opportunities for building ultrafast neuromorphic computing systems and surpassing Von Neumann architecture.