Toxic elements released due to mining activities are of the most important environmental concerns, characterised not only by their concentration, but also by their distribution among different chemical species, known as speciation. These are conventionally determined using chemical analysis and sequential extraction, which are expensive and time-demanding. In this study, the possibility of using visible-near-infrared-shortwave infrared (VNIR-SWIR) reflectance spectroscopy was investigated as an alternative technique to quantify the contents of cobalt (Co) and nickel (Ni) in soil samples collected from Sarcheshmeh copper mine waste dump surface, in Iran. As a novel approach, the capability of VNIR-SWIR spectroscopy was also investigated in speciation of those elements. Three machine learning (ML) techniques (i.e., extreme gradient boosting (EGB), random forest (RF) and support vector regression (SVR)) were used to make relationships between soil spectral responses and Co and Ni contents of the samples. For all ML algorithms, the best prediction accuracies were obtained by the models developed on the first derivative (FD) spectra (for Co: RMSEp values of 7.82, 8.03 and 9.22 mg·kg-1, and for Ni: RMSEp values of 9.88, 10.32 and 11.02 mg·kg-1, using EGB, RF and SVR, respectively). Spatial variability maps of elements showed relatively similar patterns between observed and predicted values. Correlation and ML (EGB, RF, SVR)-based methods revealed that the most important wavelengths for Co and Ni prediction were those related to iron oxides/hydroxides and clay minerals, as two main soil properties responsible for controlling their speciation. This study demonstrated that the EGB technique was successful at indirect quantification and spatial variability mapping of Co and Ni on the mine waste dump surface. In addition, it provided an inspiration for implementation of the VNIR-SWIR reflectance spectroscopy as a potentially fast and cost-effective method for speciation studies of toxic elements, specially in heterogeneous soil environments.
Integration of smart grid technologies in distribution systems, particularly behind-the-meter initiatives, has a direct impact on transmission network planning. This paper develops a coordinated expansion planning of transmission and active distribution systems via a stochastic multistage mathematical programming model. In the transmission level, in addition to lines, sitting and sizing of utility-scale battery energy storage systems and wind power plants under renewable portfolio standard policy are planned. Switchable feeders and distributed generations are decision variables in the distribution level while the impact of demand response programs as a sort of behind-the-meter technologies is accommodated as well. Expansion of electric vehicle taxi charging stations is included as a feasible option in both transmission and distribution levels. In order to deal with short-term uncertainty of load demand, renewable energy sources output power, and the charging pattern of electric vehicle taxis in each station, a chronological time-period clustering algorithm along with Monte Carlo simulation is utilized. The proposed model is tackled by means of Benders Dual Decomposition (BDD) method. The IEEE RTS test system (as the transmission system) along with four IEEE 33-node test feeders (as distribution test systems) are examined to validate effectiveness of the proposed model.
Fault type classification is a critical stage in modern distance relays for activating the effective phase and ground distance elements. It is also used for some supplementary functions such as single-pole tripping and reclosing, teleprotection, and fault location. Traditional fault type classifiers are based on the symmetrical or superimposed components of the current signal. However, owing to the unconventional behavior of inverter-based resources (IBRs) compared to the synchronous generators, traditional methods are not reliable in the presence of IBRs. For example, modern grid codes impose some restrictions in terms of injected current during asymmetrical fault which put the accuracy of conventional fault classification methods in danger. Fault resistance could also affect the accuracy of fault type classification method. In this paper, first, the fault current signature of IBRs is analytically derived. Then, impacts of modern grid code and fault resistance on the conventional fault classification are properly evaluated by executing some simulation studies. Finally, a new fault classifier is proposed which is based on symmetrical components of the local voltage and current during asymmetrical faults. The proposed classifier presents a satisfactory degree of security in the faulted phase identification in the presence of IBRs under different host grid codes. Performance of the proposed method is properly analysed with different simulation scenarios such as different fault locations, fault resistances, pre-fault condition, test systems, and host grid codes in PSCAD/EMTDC software.
Hand hygiene plays a crucial role in healthcare environments which can cease infections and diseases from spreading. It is also regarded as the second most effective way to control the transmission of COVID-19. The World Health Organization (WHO) recommends a 12-step guideline for alcohol-based hand rubbing. Compliance with this guideline is vital in order to clean the hands thoroughly. Hence, an automated system can help to improve the quality of this procedure. In this study, a large-scale and diverse dataset for both real and fake hand rubbing motions is collected as the first stage of building a reliable hand hygiene system. In the next stage, various pre-trained networks were analyzed and compared using a swift version of the Separation Index (SI) method. The proposed Swift SI method facilitates choosing the best pre-trained network without fine-tuning them on the whole dataset. Accordingly, the Inception-ResNet architecture achieved the highest SI among Inception, ResNet, Xception, and MobileNet networks. Fine-tuning the Inception-ResNet model led to an accuracy of 98% on the test dataset, which is the highest score in the literature. Therefore, from the proposed approach, a lightweight version of this model with fewer layers but almost the same accuracy is produced and examined. In the final stage, a novel metric, called Feature-Based Confidence (FBC), is devised for estimating the confidence of models in prediction. The proposed confidence measure is able to profoundly differentiate models with similar accuracy and determine the superior one. Based on the metrics results, the Inception-ResNet model is about 2x slower but 5% more confident than its lightweight version. Putting all together, by addressing the real-time application concerns, a Deep Learning based method is offered to qualify the hand rubbing process. The model is also employed in a commercial machine, called DeepHARTS, to estimate the quality of the hand rubbing procedure in different organizations and healthcare environments.
Re-curing partly recovers the mechanical and durability properties of fire-damaged concretes. This inexpensive method can be used to reduce the cost of rehabilitation and probably prevent the demolition of fire-damaged concrete infrastructures. This paper investigates the macro- and microstructure of zeolite containing concretes after heating and re-curing. In this research, two mixtures including OPC concrete and zeolite concrete were studied. The specimens were heated up to 800 °C and then re-cured in moist air or water for 28, 56 or 90 days. Macrostructure testing including compressive strength, water absorption, surface resistivity and gas permeability was conducted on the specimens. A set of rehydration products including portlandite, C–S–H gel, ettringite, etc. regenerated during the re-curing period, which was identified by SEM and XRD analyses. These products improved the properties of the heated concretes, especially the OPC concrete. The recovery of properties was more pronounced in the water re-cured specimens. Formation of needle-shaped crystals in the zeolite concrete, which appears to be thaumasite-ettringite solid solution, led to a decrease in compressive strength at the early ages of re-curing. However, the durability properties were improved at the early ages of re-curing due to the expansion of these needle-shaped crystals during the formation. In the zeolite concrete, strength recovery occurred after 56 days of re-curing. Although the unheated specimens of the zeolite concrete had better mechanical and durability properties compared to the OPC concrete, the properties of the zeolite concrete were inferior after heating and re-curing in moist air or water.
In this paper, a formal transition system model is presented called Linear Temporal Public Announcement Logic (LTPAL) to extract knowledge in a classification process. The model combines Public Announcement Logic (PAL) and Linear Temporal Logic (LTL). For this purpose, first, an epistemic logic model is created to capture information gathered by classifiers in single-framed data input. Next, using LTL, classifiers are considered for data stream inputs. Then, a verification method is proposed for such data streams. Finally, we formalize natural language properties in LTPAL with a video-stream object detection sample.
The Choghart and Chadormalu iron deposits in Bafq metallogenic zone in Central Iran are classified as Kiruna-type deposits and surrounded by metasomatic rocks which Russian experts named them metasomatite. These rocks include different types of acidic to mafic igneous rocks and sediment and metamorphic rocks known as metasomatic bedrocks. The enrichment pattern of LREEs compared to HREEs in the spider diagrams is consistent with the felsic and alkaline nature of magma in the Choghart and Chadormalu deposits. Also, the negative anomaly of Nb and Ta and the positive anomaly of Th could be an important geochemical indicators for magmas produced in subduction zones. These metasomatic rocks formed as a result of the earliest and the deepest sodic metasomatism, multi-stage calcic metasomatism, and younger potassic metasomatism. The origin of the fluids responsible for metasomatism and alteration is magmatic, and these processes occur at a pressure of 40 MPa and a maximum depth of 2 km. The hydrothermal fluids have had an intermediate temperature and low salinity resulted in the sodic and primary calcic alteration and originated from the gabbro-diorite intrusive masses. The circulation of the high-salinity and high-temperature fluids has caused the next calcic alteration which can be related to a magmatic-hydrothermal origin which is associated with felsic magmatism in the region. The high-temperature potassium-containing fluids derived from intermediate to felsic magmas flowed towards shallow depths and caused potassic alteration. In the last stage of alteration, the release of calcium-rich hydrothermal fluids with low temperature and salinity created subsequent alteration after the main mineralization phases.
Accurate and comprehensive modelling aimed at investigating the impact of climate change on rainfed crop yields is of great importance due to the interconnected issues of water scarcity and food security. Because the process-based and statistical approaches to simulating crop yields are different in nature, a comparison between them is needed. This study investigates the accuracy of crop yield simulations in the historical period as well as future projections using two modelling approaches: 1) a process-based approach employing the Soil and Water Assessment Tool+ (SWAT+) model, and 2) a statistical approach employing a data-driven model, Feed Forward Back Propagation Neural Network (FFBPNN) over a medium-sized catchment in northwestern Poland. The application of two potential evapotranspiration methods (Penman-Monteith and Hargreaves) in SWAT+ permitted calibration (2004-2011) and validation (2012-2019) of runoff and yields of winter wheat and spring barley. Different combinations of climatic parameters with a drought index based on Joint Deficit Index were applied to simulate and project rainfed crop yields (winter wheat, barley, potato, rye, rapeseed, sugar beets, cereals, maize for grain, maize for green forage, pulses) with FFBPNN. The results reveal that adding the new drought index helped increase the FFBPNN performance. This approach showed that future yields of the studied crops would slightly increase under RCP8.5 by 2060. Winter wheat and spring barley projections from SWAT+ showed very small changes using both the Penman-Monteith and Hargreaves method. Policy-wise, the results should be of interest to climate change adaptation practitioners and food security experts. Future studies should aim at more thorough investigation of the role of the downscaling technique and extreme events, as well as the effect of elevated CO 2 on future crop yields.
Modeling of karstic basins can provide a better understanding of the interactions between surface water and groundwater, a more accurate estimation of infiltrated water amount, and a more reliable water balance calculation. In this study, the hydrological simulation of a karstic basin in a semiarid region in Iran was performed in three different stages. In the first stage, the original SWAT model was used to simulate surface-water flow. Then, the SWAT-MODFLOW conjunctive model was implemented according to the groundwater characteristics of the study area. Finally, due to the karstic characteristics of the region and using the CrackFlow (CF) package, the SWAT-MODFLOW-CF conjunctive model was developed to improve the simulation results. The coefficient of determination (R2) and the Nash-Sutcliffe efficiency coefficient (NSE) as error evaluation criteria were calculated for the models, and their average values were 0.63 and 0.57 for SWAT, 0.68 and 0.61 for SWAT-MODFLOW, 0.73 and 0.7 for SWAT-MODFLOW-CF, respectively. Moreover, the mean absolute error (MAE) and root mean squared error (RMSE) of the calibration for groundwater simulation using the SWAT-MODFLOW model were 1.23 and 1.77 m, respectively. These values were 1.01 and 1.33 m after the calibration of the SWAT-MODFLOW-CF model. After modifying the CF code and keeping the seams and cracks open in both dry and wet conditions, the amount of infiltrated water increased and the aquifer water level rose. Therefore, the SWAT-MODFLOW-CF conjunctive model can be proposed for use in karstic areas containing a considerable amount of both surface water and groundwater resources.
Discharging the tannery wastewater into the environment is a serious challenge worldwide due to the release of severe recalcitrant pollutants such as oil compounds and organic materials. The biological treatment through enzymatic hydrolysis is a cheap and eco-friendly method for eliminating fatty substances from wastewater. In this context, lipases can be utilized for bio-treatment of wastewater in multifaceted industrial applications. To overcome the limitations in removing pollutants in the effluent, we aimed to identify a novel robust stable lipase (PersiLipase1) from metagenomic data of tannery wastewater for effective bio-degradation of the oily wastewater pollution. The lipase displayed remarkable thermostability and maintained over 81 % of its activity at 60 °C.After prolonged incubation for 35 days at 60°C, the PersiLipase1 still maintained 53.9 % of its activity. The enzyme also retained over 67 % of its activity in a wide range of pH (4.0 to 9.0). In addition, PersiLipase1 demonstrated considerable tolerance toward metal ions and organic solvents (e.g., retaining >70% activity after the addition of 100 mM of chemicals). Hydrolysis of olive oil and sheep fat by this enzyme showed 100 % efficiency. Furthermore, the PersiLipase1 proved to be efficient for biotreatment of oil and grease from tannery wastewater with the hydrolysis efficiency of 90.76 % ± 0.88. These results demonstrated that the metagenome-derived PersiLipase1 from tannery wastewater has a promising potential for the biodegradation and management of oily wastewater pollution.
Gastrointestinal (GI) tumors (cancers of the esophagus, gastric, liver, pancreas, colon, and rectum) contribute to a large number of deaths worldwide. STAT3 is an oncogenic transcription factor that promotes the transcription of genes associated with proliferation, antiapoptosis, survival, and metastasis. STAT3 is overactivated in many human malignancies including GI tumors which accelerates tumor progression, metastasis, and drug resistance. Research in recent years demonstrated that noncoding RNAs (ncRNAs) play a major role in the regulation of many signaling pathways including the STAT3 pathway. The major types of endogenous ncRNAs that are being extensively studied in oncology are microRNAs, long noncoding RNAs, and circular RNAs. These ncRNAs can either be tumor-promoters or tumor-suppressors and each one of them imparts their activity via different mechanisms. The STAT3 pathway is also tightly modulated by ncRNAs. In this article, we have elaborated on the tumor-promoting role of STAT3 signaling in GI tumors. Subsequently, we have comprehensively discussed the oncogenic as well as tumor suppressor functions and mechanism of action of ncRNAs that are known to modulate STAT3 signaling in GI cancers.
Mites and insects have different kinds of relationships with each other, which is very important to be studied. One of these relationships is parasitism, which is seen between larvae of terrestrial Parasitengona mites (Acari: Trombidiformes) and different active stages of insects. This study aimed to determine parasitic mites associated with the solitary wasps of the family Crabronidae. The presence of mites was investigated on 3247 wasp individuals belonging to 250 species from 53 genera. Among them, 32 specimens representing 23 species were parasitized by Leptus Latreille mite larvae. As a result, a total of 58 mite larvae were detected and two species, Leptus rosellae Haitlinger, 1999 and L. tridentatus Saboori, Hakimitabar & Khademi, 2018, were identified. The latter one has been reported for the first time from Türkiye and all mite-parasitized wasp species are new host records of both mite species. This study is the first record of the parasite-host relationship between the family Crabronidae and the genus Leptus.
This paper describes the procedure for developing a new airfoil family. This airfoil family applies to heavy-duty, industrial, and aero-derivative gas turbine compressors ranging from subsonic to transonic flow regimes. The airfoil family is generated by filling a database with optimized airfoil geometries. This database is structured in six dimensions, called design space parameters, including inlet Mach number, inlet flow angle, outlet flow angle, axial velocity density ratio, maximum thickness to chord ratio, and solidity. This six-dimensional space includes all compressor blades used in stationary gas turbine compressors. Each set of these design space parameters is related to an optimal geometry produced by the optimization system. The optimization system includes a parametrized airfoil generator, an accurate, fast blade-to-blade flow solver, and an evolutionary optimization algorithm. Airfoils of different stationary gas turbine compressor types are investigated to cover the required design space. Four hundred thirty airfoils, denoted as reference airfoils, are used to define design space borders. Comparing the newly optimized airfoils with reference airfoils revealed superior performance throughout the entire design space. They incorporate these optimized airfoils into a surrogate model, resulting in a fast, optimized airfoil generator (airfoil family). The transonic rotor of the existing multistage compressor has been redesigned according to the developed airfoil family. 3D computational fluid dynamics showed a 2% efficiency improvement for optimized blade row over the original design. Integrating this airfoil family and a streamline curvature code as part of a compressor design system is the main application of this advanced airfoil family.
In this study, the impact of vegetation, land surface temperature, and precipitation on changes in water level and area of seven inland lakes (Urmia lake in Iran, Tharthar, Mosul lakes and Hammar 4 wetland in Iraq, and Beyşehir and Erçek lakes in Turkey) is analyzed to evaluate the variability of these lakes due to climate change. The altimetric data from four remote sensing databases (TOPEX/POSEIDON and Jason 1, 2, and 3), the area of the lakes from the images of Landsat OLI and ETM + sensors, the vegetation from MOD13Q1-NDVI 250 m database, land surface temperature from LST-MOD11A1, and precipitation from GPM_3IMERGM product were used in this study to assess the changes occurring in the period of the last 20 years (2000–2019). The results showed that in the analyzed area the values of the land surface temperature and vegetation indices increased, whereas annual precipitation sums decreased. Although temperature and vegetation changes in all three countries were almost consistent with each other, changes in the water level and area of the studied lakes were different. The highest decrease in the water level was observed for Urmia lake. Although decreases in the water level were also observed in other lakes, their water level returned after a time to its initial level (1992). This was not the case for Urmia lake, where the water level after 1999 never returned to the initial value, finally lowering by 7 m. The fluctuations of the water level and area of Iran, Turkey, and Iraq lakes are however caused by factors other than only those related to climate, which needs more investigations to determine more precisely the changes in the water level of these lakes.
Research is an indispensable part of any educational endeavour generally and graduate/postgraduate studies particularly, since the Iranian educational system requires M.A. and Ph.D. candidates to submit a thesis or dissertation as partial fulfilment of the requirements for attaining their respective academic degrees. However, a review of the related research reveals that students’ perceptions of ELT research have largely gone unexplored. The current study is a step forward in attempting to fill the mentioned gap through an examination of Iranian graduate students’ perceptions of conducting ELT research. In this line, 32 Iranian graduate-level ELT students were initially selectedbased on convenient sampling. Their perceptions of ELT research were collected through interviews and later analysed using the framework of Grounded Theory Analysis (GTA). The data collected in the form of participants’ answers to interview questions were grouped into three general themes: a) definitions and conceptualisations, b) motivational drives, and c) challenges of conducting ELT research. The results revealed that by removing impediments to the way of conducting ELT research, the quality and quantity of research conducted by Iranian M.A./Ph.D. ELT candidates may be greatly improved. The findings may yield some implications for Iranian ELT policymakers, practitioners, instructors, researchers, and graduate students.
Abiotic stresses such as salinity and drought stresses are known as the main constraints for optimum growth of plants, especially in arid and semi-arid regions. Therefore, in recent years, agricultural scientists have begun to research about the fertilizers that have a multifaceted use and can be used to maintain the optimum growth and yield of strategic plants under environmental stresses. Since wheat is the most important crop worldwide, stress tolerance plays a crucial role in food security. By different mechanisms, silicon (Si) improves the tolerance of plants to salinity and drought stresses including regulation of plant water relationships, gas exchange, photosynthesis, nutrient balance, reducing oxidative stress, reducing ionic toxicity, osmoregulation and root growth, potassium uptake, and stimulation of plant hormones. In the present work, the effects of Si on wheat tolerance to salinity and drought stresses will be discussed and it will try to explain the involved mechanisms in the regulation of the plant growth and yield by Si. This study also highlights the need for future research on the role of Si in wheat under drought stress and in saline soils.
The development of photocatalysts has an influential role in solving the environmental pollution crisis. Herein, the two different noble metals of silver (Ag)/ruthenium (Ru) were separately decorated on cadmium sulfide (CdS) photocatalysts by novel chemical methods. Characterization tests confirmed the formation of Ag/Ru-decorated CdS with spherical morphologies. According to the DRS and PL experiments, Ru-decorated CdS accounted for the highest light absorbance and the most accelerated transfer and detachment of photoelectrons/holes, followed by Ag-decorated CdS compared to pure CdS, which brought proper optical properties of Ag/Ru-decorated CdS. The photodecomposition of methylene blue (MB)/rhodamine B (RhB) as dyes and phenol as a colorless pollutant in the presence of Ag-decorated CdS (96%, 95%, and 69%) and Ru-decorated CdS (100%, 100%, and 80%) exposed to visible light radiation climbed compared to pure CdS (80%, 67%, and 61%) respectively. The influence of various parameters on the MB/RhB photocatalytic activity was investigated. The quenching experiment determined the functions of active species. Finally, experimental results proved that the MB/RhB photodecomposition by Ag/Ru-decorated CdS followed the pseudo-first-order kinetic model.
The environmental geochemical characterization of mineralized areas prior to mining does not receive adequate attention. This study shows trace element distribution in soils of two unexploited porphyry copper deposits located in Darreh-Zereshk and Ali-Abad in central Iran. The study was carried out using a compositional data analysis (CoDa) approach and combination of multivariate statistics and clustering techniques, which made it possible to identify the geochemical associations representing the different areas of the mineral deposits. The results of the chemical analyses, performed by ICP-MS, revealed high concentrations of those elements typically associated with porphyry deposits (As, Co, Cu, Mo, Ni, Pb, and Zn). The typical zonal pattern with an anomaly of Cu in central parts of the system and the prevalence of epithermal elements (Ag, Cd, Pb, and Zn) toward the peripheral propylitic alteration zone were recognized. The XRD analysis of selected soil samples allowed us to determine the distribution of elements within the different carrier minerals. Afterward, geochemical speciation patterns were investigated by a four-step sequential extraction procedure based on BCR protocol. The residual fraction consisting of primary resistant minerals was found to be the main host for As (73-93.4%), Cr (65.1-79.6%), Cu (54.3-81.4%), Ni (58.9-80.6%), V (75.9-88%), and Zn (56.5-60.5%) in the studied soils. Even though these elements are not readily leachable, their behavior and distribution could be largely affected by the mining operation and consequent changes in the physicochemical properties of the soil. The soluble-exchangeable phase was only less than 15% of the total extractions for all elements, except for Cd. With respect to the mobility factor (MF), Cd was the most mobile element followed by Sb and Pb. The measured risk assessment code (RAC) presented the following risk order: Cd > Sb > Ni > Co > Pb > Cr > As > Zn > Cu > V. This study reveals that the acquisition of pre-mining geo-environmental data of trace elements is very important to establish pre-mining backgrounds and baselines for evaluating post-mining or post-reclamation geochemical signatures.
A one-pot, four-component reaction for the synthesis of novel chromeno[3,4-c]spiropyrrolidine-indenoquinoxalines is described via a 1,3-dipolar cycloaddition of 3-acetyl-coumarins with the azomethine ylides followed by deacetylation and protonation (deuteration). The products were obtained in moderate to high yields, and their structures were confirmed by ¹H NMR, ¹³C NMR, FT-IR, and MS spectroscopy. Graphical abstract
Soil contamination by anthropogenic heavy metals has become a global issue. This study aimed to investigate cadmium (Cd) concentration, mobility, and contamination indices of Cd in soils in the Hamadan province, west of Iran. To investigate the concentration of Cd in soil, one hundred soil samples from wheat farms and five samples from control lands were collected. Pollution indexes, including Cd mobility, enrichment factor, geoaccumulation index, contamination index, and availability ratio, were investigated. The structural equation model was also used to evaluate effective parameters on cadmium durability in soil. Results showed that mean values of available phosphorus (P) were 83.65, 129, and 65 (mg kg⁻¹) in three land-use types rainfed, irrigated, and controlled, respectively. The mean values of Cd in different land-use types of rainfed, irrigated, and controlled were 0.15, 0.18, and 0.08 (mg kg⁻¹), respectively. The results indicated that the amount of Cd in both forms (available and total) in ones that received fertilizer, especially P fertilizers, was higher than in the controlled one. Other pollution indexes revealed that the study area had been slightly contaminated due to anthropogenic activities. Lime, clay, lead, and OM were identified as affective parameters on cadmium durability. Finally, the results demonstrated that the mobility rate was high. Cd had a higher potential mobility in soil samples in the rain-fed and irrigated land than in the controlled land, and Cd had a low retention time.
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