Explore the vast range of titles available.

Given the rapidly increasing use of metal oxide nanoparticles in agriculture as well as their inadvertent addition through sewage sludge application to soils, it is imperative to assess their possible toxic effects on soil functions that are vital for healthy crop production. In this regard, we designed a lab study to investigate the potential toxicity of one of the most produced nanoparticles, i.e. zinc oxide nanoparticles (nZnO), in a calcareous soil. Microcosms of 80 g of dry-equivalent fresh soils were incubated in mason jars for 64 days, after adding 100 or 1000 mg of biogenically produced nZnO kg −1 soil. Moreover, we also added rice-straw derived biochar at 1 or 5% (w: w basis) hypothesizing that the biochar would alleviate nZnO-induced toxicity given that it has been shown to adsorb and detoxify heavy metals in soils. We found that the nZnO decreased microbial biomass carbon by 27.0 to 33.5% in 100 mg nZnO kg −1 soil and by 39.0 to 43.3% in 1000 mg nZnO kg −1 soil treatments across biochar treatments in the short term i.e. 24 days after incubation. However, this decrease disappeared after 64 days of incubation and the microbial biomass in nZnO amended soils were similar to that in control soils. This shows that the toxicity of nZnO in the studied soil was ephemeral and transient which was overcome by the soil itself in a couple of months. This is also supported by the fact that the nZnO induced higher cumulative C mineralization (i.e. soil respiration) at both rates of addition. The treatment 100 mg nZnO kg −1 soil induced 166 to 207%, while 1000 mg nZnO kg −1 soil induced 136 to 171% higher cumulative C mineralization across biochar treatments by the end of the experiment. However, contrary to our hypothesis increasing the nZnO addition from 100 to 1000 mg nZnO kg −1 soil did not cause additional decrease in microbial biomass nor induced higher C mineralization. Moreover, the biochar did not alleviate even the ephemeral toxicity that was observed after 24d of incubation. Based on overall results, we conclude that the studied soil can function without impairment even at 1000 mg kg −1 concentration of nZnO in it.

This study aimed to determine if there has been an increase of global interest on pet adoption immediately after the WHO declaration of the pandemic and if the effect has been sustainable in 8 months on. We conducted a Google Trends search using keywords related to pet adoption. Relative search volume (RSV) was scored between 0 and 100 for the lowest and the highest, respectively. Top countries contributing to the dataset included Australia, the United States, Canada, New Zealand, the United Kingdom, Singapore, the Philippines, and Malaysia. From 2015 through 2020, the worldwide RSV for the categories of pet, dog and cat adoption peaked between April and May 2020, the early epidemic phase of the pandemic. These were significantly higher than the 5-year worldwide average RSV for all three categories ( P = 0.001). Comparing to the same period in 2019, the RSV ratio (2020/2019) for both dog and cat adoption increased by up to 250%. Nonetheless, the RSV for dog adoption has been decreasing since July 2020 and returned to the 5-year average by December 2020. In contrast, the interest in cat adoption remained sustainably high, possibly reflecting the feline acclimation to indoor living. In conclusion, the global interest in pet adoptions surged in the early phase of the pandemic but not sustainable. With the launch of COVID-19 vaccines, there is a concern for separation anxiety and possible abandonment of these newly adopted pets when the owners would leave their homes for work in the future.

Coronary heart disease is one of the major causes of deaths around the globe. Predicating a heart disease is one of the most challenging tasks in the field of clinical data analysis. Machine learning (ML) is useful in diagnostic assistance in terms of decision making and prediction on the basis of the data produced by healthcare sector globally. We have also perceived ML techniques employed in the medical field of disease prediction. In this regard, numerous research studies have been shown on heart disease prediction using an ML classifier. In this paper, we used eleven ML classifiers to identify key features, which improved the predictability of heart disease. To introduce the prediction model, various feature combinations and well-known classification algorithms were used. We achieved 95% accuracy with gradient boosted trees and multilayer perceptron in the heart disease prediction model. The Random Forest gives a better performance level in heart disease prediction, with an accuracy level of 96%.

Wastewater originating from the textile industry is one of the major sources of pollution for surface and groundwater bodies in countries where textiles and other dye-products are produced. Along with dyes, textile wastewaters also contain varying amounts of metals/metalloids, salts and organic pollutants. Moreover, these wastewaters have high temperatures and varying pH. Various physico-chemical and biological strategies have been devised to remove dye contaminants from such wastewaters. However, biotechnological approaches have attracted worldwide attention for their relative cost-effectiveness and environmentally friendly nature. Most biotechnological approaches rely on the use of microbes that have the potential to enzymatically degrade and decolorize dye-containing textile effluents. During recent years, several microbial cultures as well as microbial enzymes have been characterized and used for removal of dyes from simulated wastewaters having defined chemical compositions. However, there are still many challenges in scaling up microbial and enzymatic technologies for decolorization of raw textile wastewater that contain metals/metalloids, salts and other toxic compounds. The present review article summarizes the findings of recent studies conducted on decolorization of raw textile wastewaters. To the best of our knowledge, this is the only review reporting the biodegradation of azo dyes in raw textile effluents.

In this paper, we continue studying the properties of weak soft axioms discussed and studied in [8]. We initiate and explore soft semi- spaces at soft point in terms of soft semi-open sets and study its characterizations and properties. It is interesting to mention that this soft contains the soft semi-closure of each of its soft point singletons. We also define soft semi- spaces at soft point and discuss some of its characterizations.

High lead (Pb) concentration in soils is becoming a severe threat to human health. It also deteriorates plants, growth, yield and quality of food. Although the use of plant growth-promoting rhizobacteria (PGPR), biochar and compost can be effective environment-friendly amendments for decreasing Pb stress in crop plants, the impacts of their simultaneous co-application has not been well documented. Thus current study was carried, was conducted to investigate the role of rhizobacteria and compost mixed biochar (CB) under Pb stress on selected soil properties and agronomic parameters in mint ( Mentha piperita L.) plants. To this end, six treatments were studied: Alcaligenes faecalis , Bacillus amyloliquefaciens , CB, PGPR1 + CB, PGPR2 + CB and control. Results showed that the application A. faecalis  + CB significantly decreased soil pH and EC over control. However, OM, nitrogen, phosphorus and potassium concentration were significantly improved in the soil where A. faecalis  + CB was applied over control. The A. faecalis  + CB treatment significantly improved mint plant root dry weight (58%), leaves dry weight (32%), chlorophyll (37%), and N (46%), P (39%) and K (63%) leave concentration, while also decreasing the leaves Pb uptake by 13.5% when compared to the unamended control. In conclusion, A. faecalis  + CB has a greater potential to improve overall soil quality, fertility and mint plant productivity under high Pb soil concentration compared to the sole application of CB and A. faecalis .

Distributed generation connected with AC, DC, or hybrid loads and energy storage systems is known as a microgrid. Campus microgrids are an important load type. A university campus microgrids, usually, contains distributed generation resources, energy storage, and electric vehicles. The main aim of the microgrid is to provide sustainable, economical energy, and a reliable system. The advanced energy management system (AEMS) provides a smooth energy flow to the microgrid. Over the last few years, many studies were carried out to review various aspects such as energy sustainability, demand response strategies, control systems, energy management systems with different types of optimization techniques that are used to optimize the microgrid system. In this paper, a comprehensive review of the energy management system of campus microgrids is presented. In this survey, the existing literature review of different objective functions, renewable energy resources and solution tools are also reviewed. Furthermore, the research directions and related issues to be considered in future microgrid scheduling studies are also presented.

Steering on the intrinsic active site of an electrode material is essential for efficient electrochemical biomass upgrading to valuable chemicals with high selectivity. Herein, we show that an in-situ surface reconstruction of a two-dimensional layered CdPS 3 nanosheet electrocatalyst, triggered by electrolyte, facilitates efficient 5-hydroxymethylfurfural (HMF) hydrogenation to 2,5-bis(hydroxymethyl)furan (BHMF) under ambient condition. The in-situ Raman spectroscopy and comprehensive post-mortem catalyst characterizations evidence the construction of a surface-bounded CdS layer on CdPS 3 to form CdPS 3 /CdS heterostructure. This electrocatalyst demonstrates promising catalytic activity, achieving a Faradaic efficiency for BHMF reaching 91.3 ± 2.3 % and a yield of 4.96 ± 0.16 mg/h at − 0.7 V versus reversible hydrogen electrode. Density functional theory calculations reveal that the in-situ generated CdPS 3 /CdS interface plays a pivotal role in optimizing the adsorption of HMF* and H* intermediate, thus facilitating the HMF hydrogenation process. Furthermore, the reconstructed CdPS 3 /CdS heterostructure cathode, when coupled with MnCo 2 O 4.5 anode, enables simultaneous BHMF and formate synthesis from HMF and glycerol substrates with high efficiency. Targeting the electrosynthesis of valuable chemicals from biomass-based feedstocks requires understanding the phenomena at the interface and electrode surface. Here, the authors demonstrate electrolyte-driven surface reconstruction on layered CdPS3 nanosheets for the efficient hydrogenation of 5-hydroxymethylfurfural.

Background: Zinc is an essential micronutrient required for optimum plant growth. Zinc-solubilizing bacteria convert applied inorganic zinc to available forms that could be used by plants. Research design: In present study, experiments were conducted to isolate, characterize, and evaluate Zn solubilization potential of different bacteria. Results: Among 10 isolated strains, Pseudomonas protegens (RY2, MF351762) was found to be the most promising strain having zinc-solubilizing potential on 4 different insoluble zinc sources. In quantitative assay, Zn solubilization by RY2 was significantly higher than other strains at different incubation time. P. protegens RY2 was selected (based on zinc solubilizing and plant growth promoting activities like P solubilization and ACC deaminase) for plant experiments. Meanwhile, available Zn release rate in soil was determined at day 10 of incubation. Chickpea seeds were inoculated with RY2 strain and ZnO is used as zinc source. Growth parameters and quantifying zinc content of shoot and root using atomic absorption spectrophotometer were determined. Enhanced shoot and root dry weights and lengths were observed in chickpea plants compared to control. Maximum increase of 44%, 67%, and 75% in T2 (Soil + RY2), T5 (Soil + ZnO + RY2), and T7 (Soil + manure + ZnO + RY2), respectively, was found in shoot length compared to control (T1). Conclusion: The study indicated that zinc-solubilizing RY2 strain possesses potential for enhanced Zn in soil so it would allow reduced inorganic Zn application.

Discharge of untreated textile wastewaters loaded with dyes is not only contaminating the soil and water resources but also posing a threat to the health and socioeconomic life of the people. Hence, there is a need to devise the strategies for effective treatment of such wastewaters. The present study reports the catalytic potential of biogenic ZnO nanoparticles (ZnO NPs) synthesized by using a bacterial strain Pseudochrobactrum sp. C5 for degradation of dyes and wastewater treatment. The catalytic potential of the biogenic ZnO NPs for degradation of dyes and wastewater treatment was also compared with that of the chemically synthesized ones. The characterization of the biogenic ZnO NPs through FT-IR, XRD, and field emission scanning electron microscopy (FESEM) indicated that these are granular agglomerated particles having a size range of 90–110 nm and zeta potential of −27.41 mV. These catalytic NPs had resulted into almost complete (> 90%) decolorization of various dyes including the methanol blue and reactive black 5. These NPs also resulted into a significant reduction in COD, TDS, EC, pH, and color of two real wastewaters spiked with reactive black 5 and reactive red 120. The findings of this study suggest that the biosynthesized ZnO NPs might serve as a potential green solution for treatment of dye-loaded textile wastewaters.