Novel approach for identifying VOC emission characteristics based on mobile monitoring platform data and deep learning: Application of source apportionment in a chemical industrial park.

Refined volatile organic compound (VOC) emission characteristics are crucial for accurate source apportionment in chemical industrial parks. The data from mobile monitoring platforms in chemical industrial parks contain pollution information that is not intuitively displayed, requiring further excavation. A novel approach was proposed to identify VOC emission characteristics using the class activation map (CAM) technology of convolutional neural network (CNN), which was applied on the mobile monitoring platform data (MD) derived from a typical fine chemical industrial park. It converts a large amount of monitoring data with high spatiotemporal complexity into simple and interpretable characteristic maps, effectively improving the identification effect of VOC emission characteristics, supporting more accurate source apportionment of VOC pollution around the park. Using this method, the VOC emission characteristics of eight key factories were identified. VOC source apportionment in the park was conducted for one day using a positive matrix factorization (PMF) model and seven combined factor profiles (CFPs) were calculated. Based on the identified VOC emission characteristics, the main pollution sources and their contributions to surrounding schools and residential areas were determined, revealing that one pesticide factory (named LKA) had the highest contribution ratio. The source apportionment results indicated that the impact of the chemical industrial park on the surrounding areas varied from morning to afternoon, which to some extent reflected the intermittent production methods employed for fine chemicals.

Effectiveness of Person-Centered Health Education in the General Practice of Geriatric Chronic Disease Care.

Objective: This study assesses the impact of personalized health education on elderly patients with chronic diseases in a general practice setting. The rationale behind the incorporation of personalized health education stems from the growing recognition of the need for patient-centered care approaches, particularly in geriatric populations, where such interventions could lead to improved health outcomes. Our study aims to evaluate the effects of personalized health education on elderly patients with chronic diseases in a general practice context. The initiation of this study is grounded in the increasing acknowledgment of patient-centered care's significance, especially in geriatric demographics. We hypothesize that personalized health education interventions could significantly enhance health outcomes in this patient group. Methods: We conducted a randomized controlled trial involving 126 elderly patients with chronic diseases, assigning them equally to receive either standard care or standard care supplemented with personalized health education. The effectiveness of this education was measured through outcomes related to cognition, self-care, health literacy, psychological and physical health, quality of life, and prognosis. In our study, we executed a randomized controlled trial encompassing 126 elderly patients diagnosed with a range of chronic diseases. These participants were evenly divided into two groups: one receiving standard care and the other receiving standard care enhanced with personalized health education. The study spanned over a specified period, during which the impact of the personalized health education was meticulously evaluated. To comprehensively measure the effectiveness of the personalized health education, we employed a variety of tools and scales. These instruments were specifically chosen to assess changes in cognition, self-care abilities, health literacy, and psychological and physical health. Additionally, we evaluated the quality of life and prognosis of these patients, aiming to capture the holistic impact of the intervention. This approach ensured a thorough and nuanced understanding of how personalized health education influences the health outcomes of elderly patients with chronic diseases. Results: The intervention group demonstrated significant improvements across all measured outcomes compared to the control group, highlighting the efficacy of personalized health education in enhancing comprehensive health parameters in geriatric patients with chronic conditions. In our study, the intervention group, which received personalized health education, exhibited notable improvements in several key areas compared to the control group. Specifically, there was a marked enhancement in cognition and health literacy, with patients showing improved understanding and management of their conditions. Additionally, significant gains were observed in the quality of life, indicating that the tailored health education effectively addressed the holistic needs of geriatric patients with chronic diseases. These specific findings underscore the substantial impact of personalized health education in improving critical health outcomes in this patient population. Conclusion: Personalized health education in geriatric chronic disease management significantly betters disease comprehension, health literacy, self-care, psychological well-being, and physical health while also lowering the risk of adverse events. This study underscores the value of patient-centered educational strategies in chronic disease care for the elderly.Our study conclusively demonstrates that personalized health education plays a pivotal role in managing chronic diseases among the elderly. It significantly improves disease comprehension, health literacy, self-care capabilities, psychological well-being, and physical health. Furthermore, it contributes to a reduced risk of adverse health events. These findings emphasize the critical importance of integrating patient-centered educational strategies into general practice care for the elderly. By doing so, we can enhance their overall well-being and quality of life, making personalized health education an essential component in the holistic care of elderly patients with chronic conditions. This approach not only aligns with the principles of modern geriatric care but also sets a benchmark for the future of chronic disease management in older populations.

Life cycle assessment perspective on waste resource utilization and sustainable development: A case of glyphosate production.

The growing demand for pesticide manufacturing and increasing public awareness of sustainable development, have let to urgent requirements for a refined environmental management framework. It is imperative to conduct process-based life cycle assessments (LCAs) to promote clean and environment-friendly technologies. Herein, the cradle-to-gate LCA of glyphosate production was executed as an example to investigate crucial production factors (materials or energy) and multiple environmental impacts during the production processes. Results showed that methanol caused the highest environmental damage in terms of toxicity, with a normalized value of 85.7 × 10-8, followed by coal-fired electricity in 6.00 × 10-8. Furthermore, optimized schemes were proposed, including energy improvement (electricity generated by switching from coal-fired power to solar power) and wastewater targeted conversion. Regarding the normalization results before and after optimization, the latter showed more significant results with the normalized value decreasing by 21.10 × 10-8, while that of the former only decreased by 6.50 × 10-8. This study provides an integrated LCA framework for organophosphorus pesticides (OPs) from upstream control and offers an important supplement to managing the key pollution factors and control links of the OP industry. Moreover, it reveals the positive influence of optimized schemes in facilitating cleaner production technologies, thus ultimately promoting new methodologies for resource recycling.

Quantifying the energy-material-pollution nexus in a typical fine chemical industry: A sustainable development-oriented support for collaborative emission reduction.

The fine chemical industry is currently facing challenges in energy saving, material conservation, and pollution reduction due to the dual policy pressure of precise system management and collaborative pollution and carbon reduction. However, the interweaving of materials and energy input-output was not well understood due to the incomplete coverage and the lack of a generic framework. Therefore, a methodology based on the energy-material-pollution (E-M-P) coupling nexus was proposed to quantitatively assess multi-level coupling. According to the selected generic 32 coupling units, two representative glyphosate (PMG) production processes were taken as case studies. Quantification results showed that the solvent element and the material system had a higher priority. Moreover, Process 2 owned a greater optimization potential as the coupling relationship pairs were 2.55 compared to 2.32 for Process 1, and the correlation proportions of material systems reached 69.26 % and 56.92 %, respectively. In addition, assessment results indicated that Process 2 was more environmentally friendly because of the lower ecological indexes (9.7 GPt vs. 15.8 GPt) and weaker carbon footprint (CF) (1.16E+08 vs. 2.32E+08). Combined coupling nexus and environmental assessment organically, methanol had the most optimization potential and was beneficial for the measures such as solvent substitution. This work offered theory and practice guidance with demonstrative value to support the sustainable development of precise system management.

Analysis of Risk Factors for Urinary Tract Infection in Children and Construction and Validation of a Prediction Model.

OBJECTIVE: To analyse the risk factors for urinary tract infection (UTI) in children and construct and validate a risk prediction model. METHODS: The study selected 258 children with suspected UTI in the paediatric department of our hospital from August 2019 to August 2021. Identified as the subjects in this research, paediatric patients' clinical data were used for retrospective analysis. Based on the counting results of urinary leucocytes and bacteria, children were divided into the UTI group (n = 67) and non-UTI group (n = 191). Univariate analysis and multivariate logistic regression analysis were used to screen the independent risk factors for UTI in children, and a prediction model was constructed according to the results. The Hosmer-Lemeshow goodness-of-fit (GOF) test and receiver operator characteristic (ROC) curve analysis were used to validate the calibration and application value of prediction model. RESULTS: Logistic regression analysis identified length of hospitalisation ≥10 days (OR = 3.611, 95% CI: 1.781-7.325), indwelling ureter (odds ratio (OR) = 3.203, 95% CI: 1.615-6.349), history of infection (OR = 4.827, 95% CI: 2.424-9.612), congenital malformation/dysplasia (OR = 4.212, 95% CI: 2.079-8.531), constipation (OR = 4.021, 95% CI: 1.315-12.299) and anaemia (OR = 2.275, 95% CI: 1.236-4.186) as risk factors for UTI in children (p < 0.05). The formulation method was adopted to construct the following prediction model of UTI in children: Z = 2.066 × (length of hospitalisation ≥10 days) + 1.164 × (indwelling ureter) + 1.574 × (history of infection) + 1.438 × (congenital malformation/dysplasia) + 1.392 × (constipation) + 0.882 × (anaemia). The test results revealed the good GOF and high calibration (χ2 = 9.077, p = 0.336) of prediction model. Furthermore, the area under the ROC curve was 0.825 (95% CI: 0.766-0.884, p < 0.001), indicating the good discrimination and prediction efficiency of model. CONCLUSIONS: Based on clinical results, further attention should be given to high-risk children with UTI, and intervention measures should be taken immediately. The application and popularisation of prediction model will allow us to provide strategic guidance for preventing and treating UTIs in clinics.

Chemical upcycling of commodity thermoset polyurethane foams towards high-performance 3D photo-printing resins.

Polyurethane thermosets are indispensable to modern life, but their widespread use has become an increasingly pressing environmental burden. Current recycling approaches are economically unattractive and/or lead to recycled products of inferior properties, making their large-scale implementation unviable. Here we report a highly efficient chemical strategy for upcycling thermoset polyurethane foams that yields products of much higher economic values than the original material. Starting from a commodity foam, we show that the polyurethane network is chemically fragmented into a dissolvable mixture under mild conditions. We demonstrate that three-dimensional photo-printable resins with tunable material mechanical properties-which are superior to commercial high-performance counterparts-can be formulated with the addition of various network reforming additives. Our direct upcycling of commodity foams is economically attractive and can be implemented with ease, and the principle can be expanded to other commodity thermosets.

Analysis of Risk Factors for Urinary Tract Infection in Children and Construction and Validation of a Prediction Model

Objective: To analyse the risk factors for urinary tract infection (UTI) in children and construct and validate a risk prediction model. Methods: The study selected 258 children with suspected UTI in the paediatric department of our hospital from August 2019 to August 2021. Identified as the subjects in this research, paediatric patients’ clinical data were used for retrospective analysis. Based on the counting results of urinary leucocytes and bacteria, children were divided into the UTI group (n = 67) and non-UTI group (n = 191). Univariate analysis and multivariate logistic regression analysis were used to screen the independent risk factors for UTI in children, and a prediction model was constructed according to the results. The Hosmer–Lemeshow goodness-of-fit (GOF) test and receiver operator characteristic (ROC) curve analysis were used to validate the calibration and application value of prediction model. Results: Logistic regression analysis identified length of hospitalisation ≥10 days (OR = 3.611, 95% CI: 1.781–7.325), indwelling ureter (odds ratio (OR) = 3.203, 95% CI: 1.615–6.349), history of infection (OR = 4.827, 95% CI: 2.424–9.612), congenital malformation/dysplasia (OR = 4.212, 95% CI: 2.079–8.531), constipation (OR = 4.021, 95% CI: 1.315–12.299) and anaemia (OR = 2.275, 95% CI: 1.236–4.186) as risk factors for UTI in children (p < 0.05). The formulation method was adopted to construct the following prediction model of UTI in children: Z = 2.066 × (length of hospitalisation ≥10 days) + 1.164 × (indwelling ureter) + 1.574 × (history of infection) + 1.438 × (congenital malformation/dysplasia) + 1.392 × (constipation) + 0.882 × (anaemia) (AU)

A supplementary assessment system of AQI-V for comprehensive management and control of air quality in chemical industrial parks.

Volatile organic compounds (VOCs) are the dominant pollutants in industrial parks. However, they are not generally considered as part of the air quality index (AQI) system, which leads to a biased assessment of pollution in industrial parks. In this study, a supplementary assessment system of AQI-V was established by analyzing VOCs characteristics with vehicle-mounted PTR-TOFMS instrument, correlation analysis and the standards analysis. Three hourly and daily scenarios were considered, and the hierarchical parameter setting was further optimized by field application. The hourly and daily assessments revealed the evaluation factors for the discriminability of different air quality levels, practiced value for regional air quality improvement, and the reservation of general dominant pollutants. Finally, the universality testing in ZPIP successfully recognized most of the peaks, with 54.76%, 38.39% and 6.85% for O3, VOCs and NO2 as the dominant pollutant, and reflected the daily ambient air quality condition, together with the dominant pollutant. The AQI-V system with VOCs sub-index is essential for air quality evaluation in industrial parks, which can further provide scientific support to control the pollution of VOCs and the secondary pollutant, therefore significantly improve the air quality in local industrial parks.

Revealing the Excellent Low-Temperature Activity of the Fe1-xCexOδ-S Catalyst for NH3-SCR: Improvement of the Lattice Oxygen Mobility.

The development of selective catalytic reduction catalysts by NH3(NH3-SCR) with excellent low-temperature activity and a wide temperature window is highly demanded but is still very challenging for the elimination of NOx emission from vehicle exhaust. Herein, a series of sulfated modified iron-cerium composite oxide Fe1-xCexOδ-S catalysts were synthesized. Among them, the Fe0.79Ce0.21Oδ-S catalyst achieved the highest NOx conversion of more than 80% at temperatures of 175-375 °C under a gas hourly space velocity of 100000 h-1. Sulfation formed a large amount of sulfate on the surface of the catalyst and provided rich Brønsted acid sites, thus enhancing its NH3 adsorption capacity and improving the overall NOx conversion efficiency. The introduction of Ce is the main determining factor in regulating the low-temperature activity of the catalyst by modulating its redox ability. Further investigation found that there is a strong interaction between Fe and Ce, which changed the electron density around the Fe ions in the Fe0.79Ce0.21Oδ-S catalyst. This weakened the strength of the Fe-O bond and improved the lattice oxygen mobility of the catalyst. During the reaction, the iron-cerium composite oxide catalyst showed higher surface lattice oxygen activity and a faster replenishment rate of bulk lattice oxygen. This significantly improved the adsorption and activation of NOx species and the activation of NH3 species on the catalyst surface, thus leading to the superior low-temperature activity of the catalyst.

Medical Applications of Hydrogels in Skin Infections: A Review.

Skin infections are common diseases for which patients seek inpatient and outpatient medical care. Globally, an increasing number of people are affected by skin infections that could lead to physical and psychological damage. Skin infections always have a broad spectrum of clinical presentations that require physicians to make an aggressive and accurate diagnosis for prescribing the proper symptomatic antimicrobials. In most instances, the treatment for skin infections mainly includes oral or topical anti-infective drugs. However, some of the classical anti-infective drugs have limitations, such as poor water solubility, low bioavailability, and poor targeting efficiency, which can lead to poor efficacy, adverse effects, and drug resistance. Therefore, research priorities should focus on the development of more effective drug delivery systems with new materials. Hydrogels are a highly multifunctional class of medical materials with potential applications in dermatology. Several hydrogel dressings with anti-infective functions have been formulated and demonstrated to improve the efficacy and tolerance of oral or topical classical anti-infective drugs to a certain degree. In this study, the medical applications of hydrogels for the treatment of various skin infections are systematically reviewed to provide an important theoretical reference for future research studies on the treatment options for skin infections.

Erythema Nodosum following Nocardia Infection: A Case Report.

Cutaneous nocardiosis is a rare bacterial infection that can result in various dermatologic manifestations such as actinomycetoma, lymphocutaneous infection, superficial skin infection, and secondary infection due to hematogenous dissemination. We report on a Chinese patient with erythema nodosum-like exanthema, possibly secondary to nocardiosis. Our diagnosis for this patient was based on the clinical presentation, histopathological evidence, and microbiological findings. Given the protean manifestation of Nocardia, persistent reports on new presentations of the disease are important for early identification and treatment.

A simple APACHE IV risk dynamic nomogram that incorporates early admitted lactate for the initial assessment of 28-day mortality in critically ill patients with acute myocardial infarction.

BACKGROUND: Early risk stratification is important for patients with acute myocardial infarction (AMI). We aimed to develop a simple APACHE IV dynamic nomogram, combined with easily available clinical parameters within 24 h of admission, thus improving its predictive power to assess the risk of mortality at 28 days. METHODS: Clinical information on AMI patients was extracted from the eICU database v2.0. A preliminary XGBoost examination of the degree of association between all variables in the database and 28-day mortality was conducted. Univariate and multivariate logistic regression analysis were used to perform screening of variables. Based on the multifactorial analysis, a dynamic nomogram predicting 28-day mortality in these patients was developed. To cope with missing data in records with missing variables, we applied the multiple imputation method. Predictive models are evaluated in three main areas, namely discrimination, calibration, and clinical validity. The discrimination is mainly represented by the area under the receiver operating characteristic curve (AUC), net reclassification improvement (NRI) and integrated discrimination improvement (IDI). Calibration is represented by the calibration plot. Clinical validity is represented by the decision curve analysis (DCA) curve. RESULTS: A total of 504 people were included in the study. All 504 people were used to build the predictive model, and the internal validation model used a 500-bootstrap method. Multivariate analysis showed that four variables, APACHE IV, the first sample of admission lactate, prior atrial fibrillation (AF), and gender, were included in the nomogram as independent predictors of 28-day mortality in AMI. The prediction model had an AUC of 0.819 (95%CI 0.770-0.868) whereas the internal validation model had an AUC of 0.814 (95%CI 0.765-0.860). Calibration and DCA curves indicated that the dynamic nomogram in this study were reflective of real-world conditions and could be applied clinically. The predictive model composed of these four variables outperformed a single APACHE IV in terms of NRI and IDI. The NRI was 16.4% (95% CI: 6.1-26.8%; p = 0.0019) and the IDI was 16.4% (95% CI: 6.0-26.8%; p = 0.0020). Lactate accounted for nearly half of the total NRI, which showed that lactate was the most important of the other three variables. CONCLUSION: The prediction model constructed by APACHE IV in combination with the first sample of admission lactate, prior AF, and gender outperformed the APACHE IV scoring system alone in predicting 28-day mortality in AMI. The prediction dynamic nomogram model was published via a website app, allowing clinicians to improve the predictive efficacy of the APACHE IV score by 16.4% in less than 1 min.

Identification of Significant Genes and Pathways for the Chronic and Subacute Cutaneous Lupus Erythematosus via Bioinformatics Analysis.

Background: Chronic cutaneous lupus erythematosus (CCLE) and subacute cutaneous lupus erythematosus (SCLE) are both common variants of cutaneous lupus erythematosus (CLE) that mainly involve the skin and mucous membrane. Oral mucosal involvement is frequently observed in patients of CLE. Despite that they have different clinicopathological features, whether there is a significant difference in pathogenesis between them remains unclear. Herein, we investigated specific genes and pathways of SCLE and CCLE via bioinformatics analysis. Methods: Microarray expression datasets of GSE109248 and GSE112943 were both retrieved from the GEO database. Differentially expressed genes (DEGs) between CCLE or SCLE skin tissues and health controls were selected by GEO2R. Common DEGs were picked out via the Venn diagram software. Then, functional enrichment and PPI network analysis were conducted, and the top 10 key genes were identified via Cytohubba. Results: Totally, 176 DEGs of SCLE and 287 DEGs of CCLE were identified. The GO enrichment and KEGG analysis of DEGs of SCLE is significantly enriched in the response to virus, defense response to virus, response to IFN-gamma, cellular response to IFN-γ, type I IFN signaling pathway, chemokine activity, chemokine receptor binding, NOD-like receptor signaling pathway, etc. The GO enrichment and KEGG analysis of DEGs of CCLE is significantly enriched in the response to virus, regulation of multiorganism process, negative regulation of viral process, regulation of lymphocyte activation, chemokine receptor binding, CCR chemokine receptor binding, NOD-like receptor signaling pathway, etc. The top 10 hub genes of SCLE and CCLE, respectively, include STAT1, CXCL10, IRF7, ISG15, and RSAD2 and CXCL10, IRF7, IFIT3, CTLA4, and ISG15. Conclusion: Our finding suggests that SCLE and CCLE have the similar potential key genes and pathways and majority of them belong to IFN signatures and IFN signaling pathway. Besides, the NOD-like receptor signaling pathway might also have an essential role in the pathogenesis of SCLE and CCLE. Together, the identified genes and signaling pathways have enhanced our understanding of the mechanism underlying the occurrence and development of both SCLE and CCLE.

Top 100 most-cited publications in hidradenitis suppurativa: An updated bibliometric analysis.

Background: Over the last several decades, our understanding of hidradenitis suppurativa (HS) has improved considerably, thereby enhancing our ability to clinically diagnose and treat the disease. Objective: The purpose of this study was to identify and analyze the top 100 most-cited publications related to HS to update bibliometric information on HS. Materials and methods: We used the Web of Science database to identify reports on hidradenitis suppurativa. Data from the 100 most-cited publications were extracted and analyzed. Results: The citation number of the top 100 most-cited articles was 89-532 (mean, 153.51), with the most productive periods being from years 2007 to 2016. Most publications originated from the British Journal of Dermatology and the Journal of the American Academy of Dermatology. The 100 articles originated from 18 countries, with Denmark being the most productive country, followed by the United States (17), England (14), and Germany (12). Jemec GB, from the University of Copenhagen, had 32 citations and was the most frequently identified author. The 100 articles encompassed several fields of research as follows: pathogenesis (18%), pathophysiology (7%), epidemiology (14%), clinical diagnosis and features (16%), treatment (25%), comorbidity (10%), and others (10%). In total, 11 reviews, three guidelines, and 86 original articles (nine randomized clinical trials) were included. Conclusion: Through this bibliometric analysis, we aimed to indicate a series of intellectual landmark publications that offer us critical reviews, guidelines, and original articles, which highlight the immense level of progress achieved in the field of HS.

A novel approach for VOC source apportionment combining characteristic factor and pattern recognition technology in a Chinese industrial area.

Volatile organic compound (VOC) emission control and source apportionment in small-scale industrial areas have become key topics of air pollution control in China. This study proposed a novel characteristic factor and pattern recognition (CF-PR) model for VOC source apportionment based on the similarity of characteristic factors between sources and receptors. A simulation was carried out in a typical industrial area with the CF-PR model involving simulated receptor samples. Refined and accurate source profiles were constructed through in situ sampling and analysis, covering rubber, chemicals, coating, electronics, plastics, printing, incubation and medical treatment industries. Characteristic factors of n-undecane, styrene, o-xylene and propane were identified. The source apportionment simulation results indicated that the predicted contribution rate was basically consistent with the real contribution rate. Compared to traditional receptor models, this method achieves notable advantages in terms of refinement and timeliness at similar accuracy, which is more suitable for VOC source identification and apportionment in small-scale industrial areas.

Phosphate on ceria with controlled active sites distribution for wide temperature NH3-SCR.

Practical catalysts that work well at a wide operation window for selective catalytic reduction of NOx by NH3 (NH3-SCR) are essential for the purification of non-isothermal emission such as vehicle exhaust. However, NH3-SCR catalyst with high low-temperature performance has excellent NO activation and oxidation ability, leading inevitably to NH3-intermediates over-oxidation and N2 selectivity deterioration at high operation temperatures. By far the best performance ceria-based catalyst with a super-wide temperature window of 175-400 oC for 90% NOx conversion in ideal environment and 225-475 oC for 90% NOx conversion by addition of 50 ppm SO2 and 5% H2O is obtained via distributing phosphate over the outer of ceria. NH3 protection strategy is the key for keeping high-temperature activity. Brønsted acidity surged as the formation of P-OH network via a charge compensatory mechanism of phosphate. NH3 was prone to be captured by the surface P-OH network, forming NH4+ species, avoiding being oxidized and contributing to both low and high temperature activity. NO can also be readily absorbed and oxidized to the absorbed NO2(ad) species over phosphate as reflected by in situ DRIFTS and DFT calculation, providing a facile pathway for 'fast SCR' by reacting with NH4+ species to form N2 and H2O. The reaction followed the L-H mechanism and contributed to catalytic activity under 300 oC. This directional structure fabricate strategy helps to increases the NOx conversion and N2 selectivity under a broaden temperature window. The enriched Brønsted acid sites over phosphate treated ceria were also demonstrated to have largely suppressed SO2 adsorption, which significantly slowed down the catalyst poisoning. A dynamic equilibrium between the poisoning and regeneration process can be achieved according to the shrinking-core model for each nanosphere, leading to the excellent resistance.

Brønsted acid enhanced hexagonal cerium phosphate for the selective catalytic reduction of NO with NH3: In situ DRIFTS and DFT investigation.

The possible effect of optimized acid sites on NH3-SCR performance and the fundamental mechanism are barely illustrated. In this work, we report two model catalysts of hexagonal (h-CPO) and monoclinic (m-CPO) cerium phosphate with disparate acidity that show different NH3-SCR activities under the same reaction conditions. Brønsted acid sites were found to be crucial for NH3-SCR performance at both low and high temperature. The electron localization discrepancy of h-CPO was more pronounced as compared with m-CPO, leading to the enrichment of P-OH (Brønsted acid site) which could strongly absorb NH3 and then generate NH4+ to participate in fast SCR via Langmuir-Hinshelwood mechanism, resulting in good activity at low temperature. The zeolitic water stored in the open channels of h-CPO could be released as supplement for P-OH sites which prevent the depletion and non-selective oxidation of NH3 thus maintaining its high activity at high temperature via the Eley-Rideal mechanism. Meanwhile, as DFT calculation revealed, cerium is the electron deficient center which can easily fix NO and NO2 from the intake, generating active NO2(ad) or nitrites and facilitating fast SCR by reacting with NH4+ species. Hence, the superior protonation ability to form P-OH and low energy barrier to generate active nitrites of h-CPO led its T80 NOx conversion to a broaden temperature of 150-450 oC under high GHSV of 177,000 h-1. Furthermore, experimental and DFT calculation also demonstrated that the enriched Brønsted acid sites over h-CPO have largely suppressed SO2 adsorption, thus significantly reducing the formation of metal sulfates and achieving great SO2 resistance. The ammonium sulfate deposits can be storage of NH3, supplying additional reductant to promote high temperature activity and selectivity.

A Novel Dual-Stage Phase Separation Process for CO2 Absorption into a Biphasic Solvent with Low Energy Penalty.

An amine-based biphasic solvent is promising to cut down the energy penalty of CO2 capture. However, the high viscosity of the CO2-enriched solvent retards its industrial application. This work proposed a novel dual-stage phase separation process using a triethylenetetramine and 2-(diethylamino)ethanol blend as a biphasic solvent, which separates a certain proportion of CO2-enriched phase during CO2 absorption to reduce its viscosity. Experimental results showed that the proposed dual-stage phase separation process improved the phase separation behavior and effectively enhanced the absorption rate by 49% at 50 °C, when 50 vol % CO2-enriched phase was separated at 0.3 mol mol-1. Kinetic analysis showed that the absorption rate was mainly controlled by liquid-side mass transfer. The regeneration heat of the dual-stage phase separation process cut down the energy penalty by 33% compared with the monoethanolamine-based process. Compared with the conventional biphasic solvent-based process, the heat duty was further declined by 8%. The 1H nuclear magnetic resonance analysis showed that the dual-stage phase separation process could effectively control the generation of absorption products and intensify the interphase migration of tertiary amines.

Ultraviolet Radiation and Basal Cell Carcinoma: An Environmental Perspective.

Ultraviolet radiation (UVR) is a known carcinogen participated for the development of skin cancers. Solar UVR exposure, particularly ultraviolet B (UVB), is the mostly significant environmental risk factor for the occurrence and progress of basal cell carcinoma(BCC). Both cumulative and intermittent high-grade UVR exposure could promote the uncontrolled replication of skin cells. There are also exsiting other contributing environmental factors that combine with the UVR exposure to promote the development of BCC. DNA damage in formation of skin cancers is considered to be a result of UVR toxicity. It is UVR that could activate a series of oncogenes simultaneously inactivating tumor suppressor genes and aberrant proliferation and survival of keratinocytes that repair these damages. Furthermore, mounting evidence demonstrates that inflammatory responses of immune cells in the tumor microenvironment plays crucial role in the skin tumorigenesis as well. In this chapter, we will follow the function of UVR in the onset and development of BCC. We describe the factors that influence BCC induced by UVR, and also review the recent advances of pathogenesis of BCC induced by UVR from the genetic and inflammatory aspects.