Search

Short-chain olefins are the important feedstock for the chemical industries. The selection of a proper catalyst for oxidative dehydrogenation (ODH) reaction is critical. Here, the study summarized different catalysts by physicochemical techniques such as BET surface area, Raman spectroscopy, and temperature programmed reduction (TPR). The BET analysis of different catalysts gives an optimum value of active and metal loading catalysts for optimum alkenes selectivity. From different Raman spectroscopy analyses, the study pointed out the factor responsible for varying mono vanadate and poly vanadate formation. From TPR analysis of different catalysts, this study pointed out the factors that varied on increasing or decreasing temperature and the effect on the selectivity of alkenes. The effect of different operating conditions was studied. Without catalyst regeneration after each ODH run, the catalyst under the study shows stable behavior and increases the selectivity of the desired product. The CREC riser simulator was used for ODH of propane and ethane, while two zones of fluidized bed reactor (TZFBR) and ICFBR reactors were used for ODH of butane. From the study of MoO3/MgO catalyst, it was observed that TZFBR have high selectivity of butadiene than CFBR and fixed bed reactor. It was concluded that the catalyst VOx–Nb/La-ɣAl2O3 has high conversion (20.1%) of ethane and good selectivity of (85.7%) of ethylene, while in ODH of propane and butane the catalyst 7.5 VOx/ɣAl2O3·ZrO2 (1:1) and MoO3/MgO have high selectivity of propane and 1,3-butadiene respectively. This review will help researchers in decision making for the selection of proper catalyst for ODH of alkane to alkenes. [ABSTRACT FROM AUTHOR]

Fluoride (F−) pollution in potable groundwater (GW) is a serious environmental concern in Pakistan with substantial human health hazard reports. The research on F− pollution in GW resources in Sindh Province is still incomplete. To explore the realistic conditions, the present research aimed to investigate the GW quality of community tube wells concerning F− contamination in Tharparkar, Sindh, Pakistan. A total of 53 samples were collected and examined for F−, along with other physicochemical parameters. The F− values observed varied from 0.2–4.2 mg/L, with a mean value of 1.63 mg/L. Among the 53 samples, 46% had F− levels that were higher than the World Health Organization's (WHO) recommended limit (1.5 mg/L). The water type of the studied region was Ca-HCO3 type, which can be attributed to fresh recharged water. The interaction of rock–water contact controls the hydrochemistry of GW. The GW resources of the research zone were highly saturated with fluorite minerals. Human health risk calculation outcomes exposed that 21 samples showed high HQ values for children and 7 samples showed high values for adults in the research zone. Children are at high risk in the study area from drinking F−-contaminated GW. WQI results showed that 31 samples were not suitable for drinking. [ABSTRACT FROM AUTHOR]

The spread of infectious diseases such as COVID-19, flu influenza, malaria, dengue, mumps, and rubella in a population is a big threat to public health. The infectious diseases spread from one person to another person through close contact. Without proper planning, an infectious disease can become an epidemic and can result in large human and financial losses. To better respond to the spread of infectious disease and take measures for its control, the public health authorities need models and simulations to study the spread of such diseases. In this paper, an agent-based simulation engine is presented that models the spread of infectious diseases in the population. The simulation takes as an input the human-to-human interactions, population dynamics, disease transmissibility and disease states and shows the spread of disease over time. The simulation engine supports non-pharmaceutical interventions and shows its impact on the disease spread across locations. A unique feature of this tool is that it is generic; therefore, it can simulate a wide variety of infectious disease models (SIR), susceptible-infectious-susceptible (SIS) and susceptible-infectious (SI). The proposed simulation engine will help the policy-makers and public health authorities study the behavior of disease spreading; thus, allowing for better planning.

In this work, we considered the problem of anomaly detection in next-generation cyber-physical systems (NG-CPS). For this, we used a double deep Q-network-enabled framework, where an agent was trained to detect anomalies in the traffic that does not match the behavior of the legitimate traffic at the end side. Furthermore, the proposed paradigm recognizes known and unknown anomalies by directly engaging with a simulation environment. Given that, it progressively develops its interpretation of anomalies to encompass new, previously unrecognized classes of anomalies by proactively exploring probable anomalies in data that have not been labeled. The method achieves this by concurrently optimizing the use of a limited amount of labeled abnormality data for better understanding (exploitation) and the identification of infrequent, unlabeled anomalies (exploration). During analysis, we observed that the proposed model achieves significant results in the context of average and greedy catching of anomalies in the presence of comparative models. [ABSTRACT FROM AUTHOR]

The present study was the first comprehensive investigation of genetic mutation and expression levels of the p53 signaling genes in cutaneous melanoma through various genetic databases providing large datasets. The mutational landscape of p53 and its signaling genes was higher than expected, with TP53 followed by CDKN2A being the most mutated gene in cutaneous melanoma. Furthermore, the expression analysis showed that TP53, MDM2, CDKN2A, and TP53BP1 were overexpressed, while MDM4 and CDKN2B were under-expressed in cutaneous melanoma. Overall, TCGA data revealed that among all the other p53 signaling proteins, CDKN2A was significantly higher in both sun and non-sun-exposed healthy tissues than in melanoma. Likewise, MDM4 and TP53BP1 expressions were markedly greater in non-sun-exposed healthy tissues compared to other groups. However, CDKN2B expression was higher in the sun-exposed healthy tissues than in other tissues. In addition, various genes were expressed significantly differently among males and females. In addition, CDKN2A was highly expressed in the SK-MEL-30 skin cancer cell line, whereas, Immune cell type expression analysis revealed that the MDM4 was highly expressed in naïve B-cells. Furthermore, all six genes were significantly overexpressed in extraordinarily overweight or obese tumor tissues compared to healthy tissues. MDM2 expression and tumor stage were closely related. There were differences in gene expression across patient age groups and positive nodal status. TP53 showed a positive correlation with B cells, MDM2 with CD8+ T cells, macrophages and neutrophils, and MDM4 with neutrophils. CDKN2A/B had a non-significant correlation with all six types of immune cells. However, TP53BP1 was positively correlated with all five types of immune cells except B cells. Only TP53, MDM2, and CDKN2A had a role in cutaneous melanoma-specific tumor immunity. All TP53 and its regulating genes may be predictive for prognosis. The results of the present study need to be validated through future screening, in vivo, and in vitro studies. [ABSTRACT FROM AUTHOR]