On characterization of entropy measure using logarithmic regression model for Copper(II) Fluoride.

The versatile uses of Copper(II) Fluoride (CuF2) are well known; these include its usage as a precursor in chemical synthesis as well as its contribution to the creation of sophisticated materials and electronics. There are interesting opportunities to study the interactions between these elements because of their unique crystal structure, which contains copper ions and fluoride anions. Its potential in optoelectronic devices and conductive qualities also make it a viable material for next-generation technologies. To better understand the structural properties of CuF2 and how they affect its entropy, we present new Zagreb indices in this study and use them to calculate entropy measures. We also build a regression model to clarify the relationship between the calculated indices and entropy levels. The findings of our investigation offer significant understanding regarding the ability of the suggested Zagreb indices to extract meaningful content and their correlation with entropy in the context of CuF2. This information is important for understanding CuF2 alloys and for exploring related complex materials.

Molybdenum disulfide (MoS2) along with graphene nanoplatelets (GNPs) utilized to enhance the capacitance of conducting polymers (PANI and PPy).

Hybrid composites of molybdenum disulfide (MoS2), graphene nanoplatelets (GNPs) and polyaniline (PANI)/polypyrrole (PPy) have been synthesized as cost-effective electrode materials for supercapacitors. We have produced MoS2 from molybdenum dithiocarbamate by a melt method in an inert environment and then used a liquid exfoliation method to form its composite with graphene nanoplatelets (GNPs) and polymers (PANI and PPy). The MoS2 melt/GNP ratio in the resultant composites was 1 : 3 and the polymer was 10% by wt. of the original composite. XRD (X-ray diffraction analysis) confirmed the formation of MoS2 and SEM (scanning electron microscopy) revealed the morphology of the synthesized materials. The electrochemical charge storage performance of the synthesized composite materials was assessed by cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS) and galvanostatic charge/discharge (GCCD) measurements. Resultant composites showed enhanced electrochemical performances (specific capacitance = 236.23 F g-1, energy density = 64.31 W h kg-1 and power density = 3858.42 W kg-1 for MoS2 melt 5 mPP at a current density of 0.57 A g-1 and had 91.87% capacitance retention after 10 000 charge-discharge cycles) as compared to the produced MoS2; thus, they can be utilized as electrode materials for supercapacitors.

On network construction and module detection for molecular graph of titanium dioxide.

Titanium dioxide is the most common and valuable oxide among four types of oxides of titanium. Its physicochemical properties make it a very valuable compound. The main objective of this article is to initially detect the modules based on highly connected links of the network of the degree-based topological indices. This information is lately integrated with different physical properties of the chemical compound of titanium dioxide to develop different mathematical frameworks based on master regulatory indices of the modules. This connection can be helpful in studying the physical measures at a deeper level in the form of different degree based topological indices.Communicated by Ramaswamy H. Sarma.

Modeling the impact of the vaccine on the COVID-19 epidemic transmission via fractional derivative.

To achieve the goal of ceasing the spread of COVID-19 entirely it is essential to understand the dynamical behavior of the proliferation of the virus at an intense level. Studying this disease simply based on experimental analysis is very time consuming and expensive. Mathematical modeling might play a worthy role in this regard. By incorporating the mathematical frameworks with the available disease data it will be beneficial and economical to understand the key factors involved in the spread of COVID-19. As there are many vaccines available globally at present, henceforth, by including the effect of vaccination into the model will also support to understand the visible influence of the vaccine on the spread of COVID-19 virus. There are several ways to mathematically formulate the effect of disease on the population like deterministic modeling, stochastic modeling or fractional order modeling etc. Fractional order derivative modeling is one of the fundamental methods to understand real-world problems and evaluate accurate situations. In this article, a fractional order epidemic model S p E p I p E r p R p D p Q p V p on the spread of COVID-19 is presented. S p E p I p E r p R p D p Q p V p consists of eight compartments of population namely susceptible, exposed, infective, recovered, the quarantine population, recovered-exposed, and dead population. The fractional order derivative is considered in the Caputo sense. For the prophecy and tenacity of the epidemic, we compute the reproduction number R 0 . Using fixed point theory, the existence and uniqueness of the solutions of fractional order derivative have been studied. Furthermore, we are using the generalized Adams-Bashforth-Moulton method, to obtain the approximate solution of the fractional-order COVID-19 model. Finally, numerical results and illustrative graphic simulation are given. Our results suggest that to reduce the number of cases of COVID-19 we should reduce the contact rate of the people if the population is not fully vaccinated. However, to tackle the issue of reducing the social distancing and lock down, which have very negative impact on the economy as well as on the mental health of the people, it is much better to increase the vaccine rate and get the whole nation to be fully vaccinated.

Polyaniline inside the pores of high surface area mesoporous silicon as composite electrode material for supercapacitors.

Mesoporous silicon (mSi) obtained by the magnesiothermic reduction of mesoporous silica was used to deposit polyaniline (PANI) in its pores, the composite was tested for its charge storage application for high performance supercapacitor electrodes. The mesoporous silica as confirmed by Small Angle X-ray Scattering (SAXS) has a Brunauer-Emmett-Teller (BET) surface area of 724 m2g-1 and mean pore size of 5 nm. After magnesiothermic reduction to mSi, the BET surface area is reduced to 348 m2g-1 but the mesoporousity is retained with a mean pore size of 10 nm. The BET surface area of mesoporous silicon is among the highest for porous silicon prepared/reduced from silica. In situ polymerization of PANI inside the pores of mSi was achieved by controlling the polymerization conditions. As a supercapacitor electrode, the mSi-PANI composite exhibits better charge storage performance as compared to pure PANI and mesoporous silica-PANI composite electrodes. Enhanced electrochemical performance of the mSi-PANI composite is attributed to the high surface mesoporous morphology of mSi with a network structure containing abundant mesopores enwrapped by an electrochemically permeable polyaniline matrix.

On physical analysis of topological indices via curve fitting for natural polymer of cellulose network.

Plant materials are processed in a variety of ways to produce biologically active compounds. Cellulose (natural polymer) has the ability to deliver physiologically active compounds to organ targets that have been extracted by CO 2 . Researchers have recently become interested in polymers that can transport biologically active compounds into human bodies. For appropriately selecting bearers of biologically active chemicals, knowledge of the thermodynamic properties of cellulose is required. In QSPR/QSAR modelling, which provides the theoretical and optimum foundation for costly experimental drug discovery, molecular descriptors are extremely important. In this article, we investigated a natural polymer of cellulose network which has interesting pharmacological applications, outstanding characteristics, and a novel molecular structure. We plan to look into and compute a variety of closed-form formulas of various K-Banhatti indices along with their respective K-Banhatti entropies and the heat of formation. The numerical and graphical characterization of computed results was combined with curve fitting between calculated thermodynamic properties and topological indices. This presentation will provide a complete description of potentially important thermodynamic features that could be useful in modifying the structure of natural polymer of cellulose network CN y x .

Helicobacters and cancer, not only gastric cancer?

The Helicobacter genus actually comprises 46 validly published species divided into two main clades: gastric and enterohepatic Helicobacters. These bacteria colonize alternative sites of the digestive system in animals and humans, and contribute to inflammation and cancers. In humans, Helicobacter infection is mainly related to H. pylori, a gastric pathogen infecting more than half of the world's population, leading to chronic inflammation of the gastric mucosa that can evolve into two types of gastric cancers: gastric adenocarcinomas and gastric MALT lymphoma. In addition, H. pylori but also non-H. pylori Helicobacter infection has been associated with many extra-gastric malignancies. This review focuses on H. pylori and its role in gastric cancers and extra-gastric diseases, as well as malignancies induced by non-H. pylori Helicobacters. Their different virulence factors and their involvement in carcinogenesis is discussed. This review highlights the importance of both gastric and enterohepatic Helicobacters in gastrointestinal and liver cancers.

Diagnostic and predictive performance of biomarkers in patients with sepsis in an intensive care unit.

OBJECTIVE: This study was performed to compare the predictive performance of serum procalcitonin (PCT), N-terminal brain natriuretic propeptide (NT-proBNP), interleukin-6 (IL-6), prothrombin time (PT), thrombin time (TT), and Sequential Organ Failure Assessment (SOFA) score in the intensive care unit (ICU). METHODS: This retrospective cohort study enrolled 150 patients with sepsis and septic shock and 30 control patients without sepsis. Each patient was followed until death or 28 days. Correlations between variables were assessed with Spearman's rho test. The Kruskal-Wallis and Mann-Whitney U tests were used for between-group comparisons. RESULTS: Receiver operating characteristic curve analysis of the SOFA score, PCT, NT-proBNP, IL-6, PT, and TT showed an area under the curve of 0.872, 0.732, 0.711, 0.706, 0.806, and 0.691, respectively, for diagnosing sepsis. Binary logistic regression demonstrated that the SOFA score was an independent predictor of 28-day mortality and septic shock. The correlation coefficient (r) between SOFA and PCT, NT-proBNP and SOFA, IL-6 and SOFA, PT and SOFA, and TT and SOFA was 0.79, 0.52, 0.57, 0.56, and 0.58, respectively. CONCLUSION: While the SOFA score is the gold standard, analysis of multiple biomarkers could increase the performance capacity for diagnosis and prognosis in patients with sepsis in the ICU.

Synthesis of 4-(dimethylamino)pyridine propylthioacetate coated gold nanoparticles and their antibacterial and photophysical activity.

BACKGROUND: Gold nanoparticles are useful candidate for drug delivery applications and are associated with enhancement in the bioavailability of coated drugs and/or therapeutic agent. Since, heterocyclic compounds are known to exhibit antimicrobial potential against variety of pathogens, we designed this study to evaluate the antibacterial effects of gold nanoparticles conjugation with new synthesized cationic ligand; 4-Dimethyl aminopyridinium propylthioacetate (DMAP-PTA) in comparison with pure compound and antibiotic drug Pefloxacin. Antibacterial activity of DMAP-PTA coated gold nanoparticles was investigated against a fecal strain of E. coli (ATCC 8739). RESULTS: A new dimethyl aminopyridine based stabilizing agent named as DMAP-PTA was synthesized and used for stabilization of gold nanoparticles. Gold nanoparticles coated with DMAP-PTA abbreviated as DMAP-PTA-AuNPs were thoroughly characterized by UV-visible, FT-IR spectroscopic methods and transmission electron microscope before biological assay. DMAP-PTA, DMAP-PTA-AuNPs and Pefloxacin were examined for their antibacterial potential against E. coli, and the minimum inhibitory concentration (MIC) was determined to be 300, 200 and 50 µg/mL respectively. Gold nanoparticles conjugation was found to significantly enhance the antibacterial activity of DMAP-PTA as compared to pure compound. Moreover, effects of DMAP-PTA-AuNPs on the antibacterial potential of Pefloxacin was also evaluated by combination therapy of 1:1 mixture of DMAP-PTA-AuNPs and Pefloxacin against E. coli in a wide range of concentrations from 5 to 300 µg/mL. The MIC of Pefloxacin + DMAP-PTA-AuNPs mixture was found to be 25 µg/mL as compared to Pefloxacin alone (50 µg/mL), which clearly indicates that DMAP-PTA-AuNPs increased the potency of Pefloxacin. AFM analysis was also carried out to show morphological changes occur in bacteria before and after treatment of test samples. Furthermore, DMAP-PTA-AuNPs showed high selectivity towards Pefloxacin in spectrophotometric drug recognition studies which offers tremendous potential for analytical applications. CONCLUSIONS: Gold nanoparticles conjugation was shown to enhance the antibacterial efficacy of DMAP-PTA ligand, while DMAP-PTA-AuNPs also induced synergistic effects on the potency of Pefloxacin against E. coli. DMAP-PTA-AuNPs were also developed as Pefloxacin probes in recognizing the drug in blood and water samples in the presence of other drugs.