The mining areas of the Middle Atlas, already inhabited in the Neolithic period, have been under the influences of different cultures, firstly Phoenician, then Punic or Ibero-Punic, Berber, Roman and finally Islamic. The impact of external cultures on the evolution and development of ancient metallurgy in the north-central Atlas region and the Southern Rift occurred since prehistoric times to Arab domination in the Middle Ages. This study proposes the development of an up-to-date protocol for archaeometallurgical investigation, based on the correlation between the chemical-physical analysis of the pyrometallurgical materials and the contextual systematic geoarchaeological excavations. The microchemical analysis has been carried out on opportunely selected pyrometallurgical materials, coming from different mining areas of the Middle Atlas regions in Morocco (Tabarouch for Cu and Aouam for Pb/Ag) in order to understand the evolution of the technological knowledge in archaeometallurgical work of local people. After that, the analytical results have been included in a Geographic Information System (GIS) software with the aim of creating an easily usable database that will support multidisciplinary research on the ancient metallurgical activities also with its future development and implementation. The GIS application could indeed correlate all the data coming from different extraction/work sites, present in the exploited mining veins. Furthermore, the GIS application is a starting point for an integrated study of the different mining archaeological sites in the Mediterranean basin proposing an innovative method of data exchange of archaeological, physical and geological chemical results.

The issue tending toward alternative water resources tremendously becomes important for supplying the increasing water demand all over the world. It may be a good option to evaluate industrial effluents for agricultural irrigation. However, industrial effluent must be cleansed from the factors such as salt, toxic compounds, and microbial load that possibly cause negative effects on soil during agricultural irrigation. In this study, microbiological qualities and toxicity conditions of water sources such as membrane bioreactor (MBR) influent, MBR effluent, and mixture of MBR effluent and reverse osmosis (RO) permeate (MBR:RO = 2:1) were analyzed and evaluated according to irrigation standards. Total aerobic heterotrophic bacteria (TAHB), total coliforms (TC), fecal coliforms (FC), fecal streptococci (FS), and Clostridium spp. were screened and enumerated as indicator microbial groups for the microbial quality of water samples. Analyses of indicator microorganisms showed that loads of different bacterial groups decreased by 5.2 and 6.66 log units at maximum levels in MBR and MBR + RO system at the end of treatment. Also, evaluation of the toxicity effects of MBR effluent and MBR + RO permeate waters on Vibrio fischeri and Daphnia magna was investigated. None of the samples showed any acute toxic effect on D. magna after 48 h and V. fischeri in 5 min and 15 min. From the outputs of this study, it can be said that industrial effluents treated by advanced filtration technologies may provide a significant source of water for agricultural irrigation. This option can have positive impacts on both environmental and economic factors.

This study deals with the macrobenthic assemblages and the biotic environmental quality of Kochi backwaters (KBW), India. Due to the heavy river discharge, extensive limnetic and turbid conditions prevailed in the KBW during the southwest monsoon (June to September). This exerted a profound adverse effect on the abundance, richness, and diversity of macrobenthic assemblages. Overall, mesohaline conditions with a clayey sand bottom substratum favored the high macrofaunal abundance during the southwest and northeast monsoon seasons. But mesohaline condition and sandy silt bottom were found to support high macrofaunal abundance in the KBW during the pre-monsoon season. Polychaete dominated the macrobenthic community, regardless of seasons. Capitella capitata, Heteromastus similis, Paraheteromastus sp., Prionospio cirrobranchiata, Minuspio cirrifera, Pagurapseudopsis kochindica, P. gymnophobia, Ctenapseudes indiana, C.chilkensis, Tanais sp., Villorita cyprinoides, Grandidierella sp., Ampelisca sp., and Littorina sp. were the dominant ones observed during the study. The sediment organic carbon, in general, showed a positive correlation with polychaete abundance during all three seasons. The ecological status of KBW during all three seasons was assessed as per BO2A index, which ranged from 0.05 to 0.18, suggesting a healthy to a moderately polluted bottom environmental condition.

This paper first proposed a parallel heuristic search strategy for simultaneous identification of groundwater contamination source and aquifer parameters. As identification results are influenced by many factors, such as noisy contamination concentration data, data denoising is necessary. The existing wavelet threshold denoising method has unavoidable shortcomings; therefore, this paper first proposed a new weighted–average wavelet variable–threshold denoising (WWVD) method to improve the denoising effect for concentration data, which further enhanced the subsequent identification accuracy. However, frequent calls to the simulation model could produce high computational cost during likelihood calculation. Hence, single surrogate model of the simulation model was developed to reduce cost; however, it presented limitation. Thus, this paper first developed a differential evolution–tabu search (DE-TS) hybrid algorithm to construct an optimal ensemble surrogate model, which assembled Gaussian process, kernel extreme learning machine, and support vector regression. The first proposed DE-TS algorithm also improved the approximation accuracy of surrogate model to simulation model. This paper first proposed and implemented a parallel heuristic search iterative process for simultaneous identification, and the identification results were obtained when the iteration process terminated. The accuracy and efficiency of these newly proposed approaches were tested through a hypothetical case. Results showed that the WWVD method not only improved the denoising effect for concentration data but also enhanced the subsequent identification accuracy. The OES model using DE-TS hybrid algorithm improved the approximation accuracy of surrogate model to simulation model, and the parallel heuristic search strategy is helpful for simultaneous identification of groundwater contamination source and aquifer parameters.

The coronavirus disease 2019 (COVID-19) pandemic has brought unprecedented public health, and social and economic challenges. It remains unclear whether seasonal changes in ambient temperature will alter spreading trajectory of the COVID-19 epidemic. The probable mechanism on this is still lacking. This review summarizes the most recent research data on the effect of ambient temperature on the COVID-19 epidemic characteristic. The available data suggest that (i) mesophilic traits of viruses are different due to their molecular composition; (ii) increasing ambient temperature decreases the persistence of some viruses in aquatic media; (iii) a 1°C increase in the average monthly minimum ambient temperatures (AMMAT) was related to a 0.72% fewer mammalian individuals that would be infected by coronavirus; (iv) proportion of zoonotic viruses of mammals including humans is probably related to their body temperature difference; (v) seasonal divergence between the northern and southern hemispheres may be a significant driver in determining a waved trajectory in the next 2 years. Further research is needed to understand its effects and mechanisms of global temperature change so that effective strategies can be adopted to curb its natural effects. This paper mainly explores possible scientific hypothesis and evidences that local communities and authorities should consider to find optimal solutions that can limit the transmission of SARS-CoV-2 virus.

Nanotechnology has opened up a plethora of opportunities and has acquired extreme importance in a myriad of fields to produce enhanced materials. Their special properties make them sustainable for industrial purposes. One of the most crucial processes in the petroleum and geothermal industries is cementing. Various classes of Portland cement are used according to API classifications. The conventional Portland cement fails to perform its function at high pressure and high temperature (HPHT) conditions. Hence, various admixtures are used to improve its properties. HPHT conditions not only have a bad impact on Portland cement by affecting its rheological properties but also reduce its strength, porosity, and permeability. So, additives like nano silica are used to improve its properties. Better compressive strength, low porosity and permeability, higher yield stress, and reduced setting time are some of the major properties that improve by the use of nano silica. This paper discusses in detail the different types of cement, cementing processes, failure of Portland cement, and effect of nano silica as an admixture on the compressive strength, rheology, porosity, and permeability of the cement. Furthermore, the upcoming challenges in cementing are discussed along with future potential in this field.

Population of white-rumped vulture has not recovered in India to a desired level even after diclofenac was banned in 2006. During 2019, there were two known separate incidents of white-rumped vulture mortality involving four white-rumped vultures in Gujarat. After post-mortem examinations, tissues of all four vultures were received for toxicological investigation at the National Centre for Avian Ecotoxicology, SACON. Tissues were screened for a set of toxic pesticides, and none of them was at detectable level. Subsequently, the tissues were analysed for thirteen NSAIDs and paracetamol. Of all the drugs tested, only nimesulide was detected in all the tissues (17–1395 ng/g) indicative of exposure. Visceral gout was also observed in all the four vultures during post-mortem. Residues of nimesulide in tissues with symptoms of gout indicated that the vultures died due to nimesulide poisoning. Although, other than diclofenac, many NSAIDs are suspected to be toxic to white-rumped vultures, only nimesulide is reported in the recent past with clear symptom of gout in wild dead white-rumped vultures similar to diclofenac. Since, nimesulide appears to act similar to diclofenac in exerting toxic effects, if veterinary use of nimesulide continues, white-rumped vulture are bound to suffer. Hence, it is recommended that nimesulide should be banned by the government to conserve white-rumped vulture in the Indian subcontinent. Further, an effective system is recommended to be put in place to collect the tissues of dead vultures for toxicological investigations and eventual conservation of the critically endangered species.

The herbicide 2,4-dichlorophenoxyacetic acid (2,4-D) is widely used in agriculture to control various weeds. The objective of this study was to use the digital image processing method to identify alveolar lesions in the lungs of rats submitted to chronic 2,4-dichlorophenoxyacetic acid (2,4-D) inhalation exposure. We used forty adult male Wistar rats. The rats were divided into four groups: control group (CG), low concentration group (LCG), medium concentration group (MCG), and high concentration group (HCG). In a 6-month exposure period, we used two boxes connected to ultrasonic nebulizers for herbicide spraying. After this period, the rats were euthanized for the collection and study of lung tissue. For each image, counts of injuries and blisters were performed automatically using a methodology based on digital image processing techniques. For analysis of the results, an electronic database (Excel®) was created. We used the Pearson method for correlation analysis; values of p <0.05 were considered significant. In the evaluation of healthy alveoli, we recorded positive and significant correlations between analysis from a pathologist and computational analysis. In the evaluation of injured alveoli, we recorded a positive but non-significant correlation between analysis from a pathologist and computational analysis. These results show the effectiveness of digital image processing when evaluating alveolar integrity.

Nitrogen deposition from air pollution is increasingly reaching alpine lakes where the addition of nitrate and ammonium to sensitive surface waters can cause acidification and/or eutrophication. Thirty years of sampling in the Wind River Range, WY, has shown some lakes increasing in nitrogen. We sought to (1) determine if nutrient concentrations in Deep Lake increase during snowmelt when atmospheric deposition is released from the snowpack and (2) assess if the sampling season, location, meteorological factors, and time of day samples are collected influence lake chemistry metrics, to inform monitoring. We analyzed water samples from the outlet of Deep Lake in peak snowmelt (June) and from the inlet, outlet, and middle of Deep Lake when the basin was snow free (August). In June, outlet samples were more acidic, and nitrogen content was three times August levels. Acid neutralizing capacity (ANC) declined with snowmelt. August inlet samples were higher in nutrients than outlet and mid-lake samples. Our results indicate that atmospheric pollution in the snowpack enters the lake with snowmelt. Although Deep Lake has not acidified, ANC levels indicate a risk of episodic acidification if nitrogen deposition continues to increase. When monitoring lakes at risk for episodic acidification, sampling during the late snowmelt pulse should be prioritized. Simplified sampling protocols may be used in some lakes, as epilimnion and outlet samples were nearly identical. The time of day and cloud cover did not affect lake chemistry, while wind speed and precipitation weakly increased August ANC and June pH, respectively.

Environmental sustainability has become a major concern for policymakers across the globe. In this regard, understanding the factors responsible for environmental degradation is particularly important for developing nations. Against this backdrop, this study aims to evaluate the impacts of environmental regulations and other vital macroeconomic aggregates on the ecological footprints in the context of four fossil fuel-dependent South Asian countries: Bangladesh, India, Pakistan, and Sri Lanka. The major findings from the econometric analysis, accounting for cross-sectional dependency, slope heterogeneity, and structural break issues in the data, reveal that environmental regulations portray significant roles in directly and indirectly reducing the ecological footprints across South Asia. Besides, the elasticity estimates verify the authenticity of the environmental Kuznets curve and the pollution haven hypotheses. On the other hand, non-renewable and renewable energy consumptions are found to increase and decrease the ecological footprints, respectively. Moreover, renewable energy use and environmental regulations are found to jointly reduce the ecological footprints further. More importantly, environmental regulations are predicted to reduce the adverse environmental impacts of economic growth, non-renewable energy use, and foreign direct investment inflows while increasing the favorable environmental impacts associated with renewable energy use. Furthermore, the country-specific impacts of environmental regulations on the ecological footprints are found to be more or less homogeneous to the corresponding panel estimates. The environmental Kuznets curve and pollution haven hypotheses are evidenced to hold for the majority of the four South Asia nations. In line with these findings, several relevant policy-level suggestions are put forward.