Mechanism understanding of Li-ion separation using a perovskite-based membrane

Lithium ions play a crucial role in the energy storage industry. Finding suitable lithium-ion-conductive membranes is one of the important issues of energy storage studies. Hence, a perovskite-based membrane, Lithium Lanthanum Titanate (LLTO), was innovatively implemented in the presence and absence of solvents to precisely understand the mechanism of lithium ion separation. The ion-selective membrane’s mechanism and the perovskite-based membrane’s efficiency were investigated using Molecular Dynamic (MD) simulation. The results specified that the change in the ambient condition, pH, and temperature led to a shift in LLTO pore sizes. Based on the results, pH plays an undeniable role in facilitating lithium ion transmission through the membrane. It is noticeable that the hydrogen bond interaction between the ions and membrane led to an expanding pore size, from (1.07 Å) to (1.18 – 1.20 Å), successfully enriching lithium from seawater. However, this value in the absence of the solvent would have been 1.1 Å at 50 °C. It was found that increasing the temperature slightly impacted lithium extraction. The charge analysis exhibited that the trapping energies applied by the membrane to the first three ions (Li +, K +, and Na+) were more than the ions’ hydration energies. Therefore, Li +, K +, and Na + were fully dehydrated, whereas Mg2 + was partially dehydrated and could not pass through the membrane. Evaluating the membrane window diameter, and the combined effect of the three key parameters (barrier energy, hydration energy, and binding energy) illustrates that the required energy to transport Li ions through the membrane is higher than that for other monovalent cations

Global prevalence of nosocomial infection: A systematic review and meta-analysis

Objectives: Hospital-acquired infections (HAIs) are significant problems as public health issues which need attention. Such infections are significant problems for society and healthcare organizations. This study aimed to carry out a systematic review and a meta-analysis to analyze the prevalence of HAIs globally.   Methods: We conducted a comprehensive search of electronic databases including EMBASE, Scopus, PubMed and Web of Science between 2000 and June 2021. We found 7031 articles. After removing the duplicates, 5430 studies were screened based on the titles/abstracts. Then, we systematically evaluated the full texts of the 1909 remaining studies and selected 400 records with 29,159,630 participants for meta-analysis. Random-effects model was used for the analysis, and heterogeneity analysis and publication bias test were conducted.   Results: The rate of universal HAIs was 0.14 percent. The rate of HAIs is increasing by 0.06 percent annually. The highest rate of HAIs was in the AFR, while the lowest prevalence were in AMR and WPR. Besides, AFR prevalence in central Africa is higher than in other parts of the world by 0.27 (95% CI, 0.22-0.34). Besides, E. coli infected patients more than other micro-organisms such as Coagulase-negative staphylococci, Staphylococcus spp. and Pseudomonas aeruginosa. In hospital wards, Transplant, and Neonatal wards and ICU had the highest rates. The prevalence of HAIs was higher in men than in women.   Conclusion: We identified several essential details about the rate of HAIs in various parts of the world. The HAIs rate and the most common micro-organism were different in various contexts. However, several essential gaps were also identified. The study findings can help hospital managers and health policy makers identify the reason for HAIs and apply effective control programs to implement different plans to reduce the HAIs rate and the financial costs of such infections and save resources

Prediction of bruise volume propagation of pear during the storage using soft computing methods

Bruises occur under both static and dynamic loadings when the imposed stress on fruit goes over the failure stress of the fruit tissue. Bruise damage is the main reason for fruit quality loss. In this study, the potential of artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS), and multiple regression (MR) techniques to predict bruise volume propagation of pears during the storage time was evaluated. For this purpose, at first, the radius of curvature at loading region was obtained. Samples were divided into five groups and subjected to five force levels. Then, they were kept under storage conditions and at 7-time intervals after loading tests, bruise volume was calculated using magnetic resonance imaging (MRI) and image processing techniques. Force, storage time, and radius of curvature at loading region were employed as input variables, and bruise volume (BV) was considered as output in the developed models. Multilayer perceptron (MLP) artificial neural network with three layers that includes an input layer (three neurons), two hidden layers (two and nine neurons), and one output layer was used. For the evaluation of models, three criteria (RMSE, VAF, and R2) were calculated. ANN and MR gave the highest and lowest correlation between predicted and actual values, respectively. These results indicate that the ANN techniques can be used to predict pear bruising propagation in storage time

QSPR study of viscoplastic properties of peptide-based hydrogels

In this study, the power of machine learning was harnessed to probe the link between molecular structures of peptide-based hydrogels and their viscoplastic properties. The selection of compounds was attempted in accordance with the prescribed full list of peptide-based materials exhibiting hydrogel functionality in the literature. In this pursuit, a complete set of molecular descriptors and fingerprints was considered – accounting for an entry of size 17,968 for each peptide-based structure analyzed. The elastic and viscous moduli response of materials were mapped over a wide frequency spectrum in the range [0.1–100] (rad/s). In general, the results indicate that the frequency-dependent mechanical response of peptide-based hydrogels is statistically correlated with its (inter)molecular attributes, such as charge, first ionization potential (or equivalently electronegativity), surface area, number of chemical substrates, bond type, and intermolecular interactions. The performance of several (supervised) soft computing techniques was measured, for our quantitative structure property relationships model. In addition, the hypothesis of mapping our databank to a new system of principal components was tested, by using an unsupervised methodology, which resulted in enhancement of the prediction accuracy. In terms of significance, the present article provides the first report of frequency-dependent elastic and viscous moduli, for a set of 70 peptide-based formulations with hydrogel functionality. Communicated by Ramaswamy H. Sarma</p

Mechanism Understanding of Li-ion Separation Using A Perovskite-Based Membrane

Lithium ions play a crucial role in the energy storage industry. Finding suitable lithium-ion-conductive membranes is one of the important issues of energy storage studies. Hence, a perovskite-based membrane, Lithium Lanthanum Titanate (LLTO), was innovatively implemented in the presence and absence of solvents to precisely understand the mechanism of lithium ion separation. The ion-selective membrane&rsquo;s mechanism and the perovskite-based membrane&rsquo;s efficiency were investigated using Molecular Dynamic (MD) simulation. The results specified that the change in the ambient condition, pH, and temperature led to a shift in LLTO pore sizes. Based on the results, pH plays an undeniable role in facilitating lithium ion transmission through the membrane. It is noticeable that the hydrogen bond interaction between the ions and membrane led to an expanding pore size, from (1.07 &Aring;) to (1.18&ndash;1.20 &Aring;), successfully enriching lithium from seawater. However, this value in the absence of the solvent would have been 1.1 &Aring; at 50 &deg;C. It was found that increasing the temperature slightly impacted lithium extraction. The charge analysis exhibited that the trapping energies applied by the membrane to the first three ions (Li+, K+, and Na+) were more than the ions&rsquo; hydration energies. Therefore, Li+, K+, and Na+ were fully dehydrated, whereas Mg2+ was partially dehydrated and could not pass through the membrane. Evaluating the membrane window diameter, and the combined effect of the three key parameters (barrier energy, hydration energy, and binding energy) illustrates that the required energy to transport Li ions through the membrane is higher than that for other monovalent cations

Production of Innovative Essential Oil-Based Emulsion Coatings for Fungal Growth Control on Postharvest Fruits

This work assessed the antimicrobial potential of natural essential oils (EOs) from cinnamon (CEO), zataria (ZEO), and satureja (SEO), applied natively or as coatings against Penicillium expansum and Botrytis cinerea during both in vitro and in vivo (on apple fruits) experiments. The induced inhibitory effect towards fungal growth, as a function of both EO type and concentration (75&ndash;1200 &mu;L/L), was preliminarily investigated to select the most suitable EO for producing bacterial cellulose nanocrystals (BCNCs)/fish gelatin (GelA)-based emulsions. CEO and ZEO exhibited the best performances against P. expansum and B. cinerea, respectively. None of the pristine EOs completely inhibited the fungal growth and &ldquo;disease severity&rdquo;, properly quantified via size measurements of lesions formed on fruit surfaces. As compared to pristine CEO, coating emulsions with variable CEO concentration (75&ndash;2400 &micro;L/L) curbed lesion spreading on apples, owing to the controlled CEO release during a 21-day temporal window. The strongest effect was displayed by BCNCs/GelA-CEO emulsions at the highest CEO concentration, upon which lesions on fruit skins were barely detectable. This work demonstrated the capability of EOs embedded in BCNCs/GelA-based nanocapsules to efficiently slow down microbial spoilage on postharvest fruits, thus offering viable opportunities for developing innovative antimicrobial packaging systems

Preliminary report of Iranian Registry of Alzheimer's disease in Tehran province: A cross‐sectional study in Iran

Abstract Background and Aims Alzheimer's disease (AD) is the main cause of dementia and over the 55 million people live with dementia worldwide. We aimed to establish the first database called the Iranian Alzheimer's Disease Registry to create a powerful source for future research in the country. In this report, the design and early results of the Iranian Alzheimer's Disease Registry will be described. Methods We performed this multicenter investigation and patients' data including age, sex, educational level, disease status, Mini‐Mental State Examination (MMSE), and Geriatric Depression Scale (GDS) from 2018 to 2021 were collected, registered, and analyzed by GraphPad Prism software. Results Totally 200 AD patients were registered in our database. 107 (54%) were women and age of 147 (74%) were over 65. The mean age for men and women was 76.20 ± 8.29 and 76.40 ± 8.83 years, respectively. 132 (66%) were married and 64 (32%) were illiterate. Also, 94 (47%) were in the moderate stage of disease, and 150 (75%) lived at home together with their families. The most frequent neurological comorbidity was psychosis (n = 72, 36%), while hypertension was the most common non‐neurological comorbidity (n = 104, 52%). The GDS score of women in the mild stage (5.23 ± 2.9 vs. 6.9 ± 2.6, p = 0.005) and moderate stage (5.36 ± 2.4 vs. 8.21 ± 2.06, p = <0.001) of the disease was significantly greater than men. In univariate analysis, MMSC score was remarkably associated with stroke (β = −2.25, p = 0.03), psychosis (β = −2.18, p = 0.009), diabetes (β = 3.6, p = <0.001), and hypercholesteremia (β = 1.67, p = 0.05). Also, the MMSE score showed a notable relationship with stroke (β = −2.13, p = 0.05) and diabetes (β = 3.26, p = <0.001) in multivariate analysis. Conclusion Iranian Alzheimer's Disease Registry can provide epidemiological and clinical data to use for purposes such as enhancing the current AD management in clinical centers, filling the gaps in preventative care, and establishing effective monitoring and cure for the disease

Global prevalence of nosocomial infection: A systematic review and meta-analysis.

ObjectivesHospital-acquired infections (HAIs) are significant problems as public health issues which need attention. Such infections are significant problems for society and healthcare organizations. This study aimed to carry out a systematic review and a meta-analysis to analyze the prevalence of HAIs globally.MethodsWe conducted a comprehensive search of electronic databases including EMBASE, Scopus, PubMed and Web of Science between 2000 and June 2021. We found 7031 articles. After removing the duplicates, 5430 studies were screened based on the titles/ abstracts. Then, we systematically evaluated the full texts of the 1909 remaining studies and selected 400 records with 29,159,630 participants for meta-analysis. Random-effects model was used for the analysis, and heterogeneity analysis and publication bias test were conducted.ResultsThe rate of universal HAIs was 0.14 percent. The rate of HAIs is increasing by 0.06 percent annually. The highest rate of HAIs was in the AFR, while the lowest prevalence were in AMR and WPR. Besides, AFR prevalence in central Africa is higher than in other parts of the world by 0.27 (95% CI, 0.22-0.34). Besides, E. coli infected patients more than other micro-organisms such as Coagulase-negative staphylococci, Staphylococcus spp. and Pseudomonas aeruginosa. In hospital wards, Transplant, and Neonatal wards and ICU had the highest rates. The prevalence of HAIs was higher in men than in women.ConclusionWe identified several essential details about the rate of HAIs in various parts of the world. The HAIs rate and the most common micro-organism were different in various contexts. However, several essential gaps were also identified. The study findings can help hospital managers and health policy makers identify the reason for HAIs and apply effective control programs to implement different plans to reduce the HAIs rate and the financial costs of such infections and save resources