The present research employs new boosting-based ensemble machine learning models i.e., gradient boosting (GB) and adaptive boosting (AdaBoost) to predict the unconfined compressive strength (UCS) of geopolymer stabilized clayey soil. The GB and AdaBoost models were developed and validated using 270 clayey soil samples stabilized with geopolymer, with ground-granulated blast-furnace slag and fly ash as source materials and sodium hydroxide solution as alkali activator. The database was randomly divided into training (80%) and testing (20%) sets for model development and validation. Several performance metrics, including coefficient of determination (R2), mean absolute error (MAE), root mean square error (RMSE), and mean squared error (MSE), were utilized to assess the accuracy and reliability of the developed models. The statistical results of this research showed that the GB and AdaBoost are reliable models based on the obtained values of R2 (= 0.980, 0.975), MAE (= 0.585, 0.655), RMSE (= 0.969, 1.088), and MSE (= 0.940, 1.185) for the testing dataset, respectively compared to the widely used artificial neural network, random forest, extreme gradient boosting, multivariable regression, and multi-gen genetic programming based models. Furthermore, the sensitivity analysis result shows that ground-granulated blast-furnace slag content was the key parameter affecting the UCS.

We aimed to obtain magnesium/iron (Mg/Fe)-layered double hydroxides (LDHs) nanoparticles-immobilized on waste foundry sand-a byproduct of the metal casting industry. XRD and FT-IR tests were applied to characterize the prepared sorbent. The results revealed that a new peak reflected LDHs nanoparticles. In addition, SEM-EDS mapping confirmed that the coating process was appropriate. Sorption tests for the interaction of this sorbent with an aqueous solution contaminated with Congo red dye revealed the efficacy of this material where the maximum adsorption capacity reached approximately 9127.08 mg/g. The pseudo-first-order and pseudo-second-order kinetic models helped to describe the sorption measurements, indicating that the physical and chemical forces governed the removal process.

Cold plasma (low pressure) technology has been effectively used to boost the germination and growth of various crops in recent decades. The durability of these plasma-treated seeds is essential because of the need to store and distribute the seeds at different locations. However, these ageing effects are often not ascertained and reported because germination and related tests are carried out within a short time after the plasma-treatment. This research aims to fill that knowledge gap by subjecting three different types of seeds (and precursors): Bambara groundnuts (water), chilli (oxygen), and papaya (oxygen) to cold plasma-treatment. Common mechanisms found for these diverse seed types and treatment conditions were the physical and chemical changes induced by the physical etching and the cold plasma on the seeds and subsequent oxidation, which promoted germination and growth. The high glass transition temperature of the lignin-cellulose prevented any physical restructuring of the surfaces while maintaining the chemical changes to continue to promote the seeds germination and growth. These changes were monitored over 60 days of ageing using water contact angle (WCA), water uptake, electrical conductivity, field emission scanning electron microscopy (FE-SEM) and X-ray photoelectron spectroscopy (XPS). The vacuum effect was also investigated to separate its effect from cold plasma (low pressure). This finding offers a framework for determining how long agricultural seeds that have received plasma treatment can be used. Additionally, there is a need to transfer this research from the lab to the field. Once the impact of plasma treatment on seeds has been estimated, it will be simple to do so.

Thin, binder-less zeolite NaX laminates, with thicknesses ranging between 310 to 750 μm and widths exceeding 50 mm and biaxial tensile strength in excess of 3 MPa, were produced by pulsed current processing. The NaX laminates displayed a high CO2 adsorption capacity and high binary CO2-over-N2 and CO2-over-CH4 selectivity, suitable for CO2 capture from flue gas and upgrading of raw biogas. The thin laminates displayed a rapid CO2 uptake; NaX laminates with a thickness of 310 μm were saturated to 40% of their CO2 capacity within 24 seconds. The structured laminates of 310 μm thickness and 50 mm thickness would offer low pressure drop and efficient carbon capture performance in a laminate-based swing adsorption technology.

A straightforward and efficient spectrum technique was created using Ortho-chloranil as the electron acceptor (-acceptor) in a charge transfer (CT) complex formation reaction to determine the concentration of famotidine (FMD) in solutions. Compared to the double-distilled blank solution, the reaction result detected a definite violet colour at a maximum absorption wavelength of 546 nm, For concentrations range 2—28 µg/ml, the technique demonstrated excellent compliance with Beer-Law and Lambert's, as evidenced by its molar absorptivity of 2159.648 L mol−1 cm–1. Lower detection limits of 0.3024 µg/ml and 1.471 µg/ml, respectively, were discovered. The complexes of famotidine and Ortho-chloranil were found to have a 2:1 stoichiometry. Additionally, the suggested approach effectively estimated famotidine concentrations in pharmaceutical formulations, particularly in tablet form.

Polymer derived ceramic (PDC) composite coatings were deposited on AISI 304 substrates using siloxane based preceramic polymer polymethlysilsquioxane (PMS) and ZrSi2 as active filler or Ag as passive filler. The tribological performance of the composite coatings was evaluated at room temperature and moderately high temperatures (150 °C, 200 °C, 300 °C and 400 °C). The composite coatings showed low coefficient of friction (COF), µ, from 0.08 to 0.2 for SiOC-ZrSi2 composite coatings, and from 0.02 to 0.3 for SiOC-Ag composite coatings, at room temperature with increasing normal load from 1 to 5 N. High temperature tribology tests showed high COF values from 0.4 to 1 but low wear for SiOC-ZrSi2 coating, and low COF from 0.2 to 0.3 for SiOC-Ag coatings at lower temperature ranges. Low load friction tests at room temperature showed negligible wear in SiOC-ZrSi2 coatings, suggesting good wear resistant and lubricating properties due to formation of t-ZrO2 and carbon. Low COF and high amount of wear was observed in SiOC-Ag composite coatings at room temperature due to high ductility of Ag and smearing of wear debris in the wear track. The coatings and wear tracks were characterized to evaluate the lubrication and wear behavior.

Polymer microcapsules containing cyanoacrylates have represented a promising option to develop self-healing biomaterials. This study aims to develop an electrospray method for the preparation of capsules using poly(methyl methacrylate) (PMMA) as the encapsulant and ethyl 2-cyanoacrylate (EC) as the encapsulate. It also aims to study the effect of the electrospray process parameters on the size and morphology of the capsules. The capsules were characterized using Fourier-transform infrared (FTIR) spectroscopy, thermogravimetric analysis (TGA), and field-emission scanning electron microscopy (FE-SEM). Moreover, the effects of electrospray process parameters on the size were investigated by Taguchi experimental design. FTIR and TGA approved the presence of both PMMA and EC without further reaction. FE-SEM micrograph demonstrated that an appropriate choice of solvents, utilizing an appropriate PMMA:EC ratio and sufficient PMMA concentration are critical factors to produce capsules dominantly with an intact and spherical morphology. Utilizing various flow rates (0.3–0.5 ml/h) and applied voltage (18–26 kV), capsules were obtained with a 600–1000 nm size range. At constantly applied voltages, the increase in flow rate increased the capsule size up to 40% (ANOVA, p ≤ 0.05), while at constant flow rates, the increase in applied voltage reduced the average capsule size by 3.4–26% (ANOVA, p ≤ 0.05). The results from the Taguchi design represented the significance of solution flow rate, applied voltage, and solution concentration. It was shown that the most effective parameter on the size of capsules is flow rate. This research demonstrated that electrospray can be utilized as a convenient method for the preparation of sub-micron PMMA capsules containing EC. Furthermore, the morphology of the capsules is dominated by solvents, PMMA concentration, and PMMA:EC ratio, while the average size of the capsules can be altered by adjusting the flow rate and applied voltage of the electrospray process.

Carbonatites are rare, carbonate-rich magmatic rocks that make up a minute portion of the crust only, yet they are of great relevance for our understanding of crustal and mantle processes. Although they occur in all continents and from Archaean to present, the deeper plumbing system of carbonatite ring-complexes is usually poorly constrained. Here, we show that carbonatite ring-complexes can be explained by caldera-style volcanism. Our geophysical investigation of the Alnö carbonatite ring-complex in central Sweden identifies a solidified saucer-shaped magma chamber at ∼3 km depth that links to surface exposures through a ring fault system. Caldera subsidence during final stages of activity caused carbonatite eruptions north of the main complex, providing the crucial element to connect plutonic and eruptive features of carbonatite magmatism. The way carbonatite magmas are stored, transported and erupt at the surface is thus comparable to known emplacement styles from silicic calderas.

This research was carried out to predict daily streamflow for the Swat River Basin, Pakistan through four deep learning (DL) models: Feed Forward Artificial Neural Networks (FFANN), Seasonal Artificial Neural Networks (SANN), Time Lag Artificial Neural Networks (TLANN) and Long Short-Term Memory (LSTM) under two Shared Socioeconomic Pathways (SSPs) 585 and 245. Taylor Diagram, Random Forest, and Gradient Boosting techniques were used to select the best combination of General Circulation Models (GCMs) for Multi-Model Ensemble (MME) computation. MME was computed via the Random Forest technique for Maximum Temperature (Tmax), Minimum Temperature (Tmin), and precipitation for the aforementioned three techniques. The best MME for Tmax, Tmin, and precipitation was rendered by Compromise Programming. The DL models were trained and tested using observed precipitation and temperature as independent variables and discharge as dependent variables. The results of deep learning models were evaluated using statistical performance indicators such as root mean square error (RMSE), mean square error (MSE), mean absolute error (MAE), and coefficient of determination (R2). The TLANN demonstrated superior performance compared to the other models based on RMSE, MSE, MAE, and R2 during training (65.25 m3/s, 4256.97 m3/s, 46.793 m3/s and 0.7978) and testing (72.06 m3/s, 5192.95 m3/s, 51.363 m3/s and 0.7443) respectively. Subsequently, TLANN was utilized to make predictions based on MME of SSP245 and SSP585 scenarios for future streamflow until the year 2100. These results can be used for planning, management, and policy-making regarding water resources projects in the study area.

This article presents a numerical and artificial intelligence (AI) based investigation on the web crippling performance of pultruded glass fiber reinforced polymers’ (GFRP) rectangular hollow section (RHS) profiles subjected to interior-one-flange (IOF) loading conditions. To achieve the desired research objectives, a finite element based computational model was developed using one of the popular simulating software ABAQUS CAE. This model was then validated by utilizing the results reported in experimental investigation-based article of Chen and Wang. Once the finite element model was validated, an extensive parametric study was conducted to investigate the aforementioned phenomenon on the basis of which a comprehensive, universal, and coherent database was assembled. This database was then used to formulate the design guidelines for the web crippling design of pultruded GFRP RHS profiles by employing AI based gene expression programming (GEP). Based on the findings of numerical investigation, the web crippling capacity of abovementioned structural profiles subjected to IOF loading conditions was found to be directly related to that of section thickness and bearing length whereas inversely related to that of section width, section height, section’s corner radii, and profile length. On the basis of the findings of AI based investigation, the modified design rules proposed by this research were found to be accurately predicting the web crippling capacity of aforesaid structural profiles. This research is a significant contribution to the literature on the development of design guidelines for pultruded GFRP RHS profiles subjected to web crippling, however, there is still a lot to be done in this regard before getting to the ultimate conclusions.

The current study involves a synthesis of a composite of nickel oxide nanoparticles (NiONPs) with a chromium dopant to yield (Cr/NiONPs). Synthesis of nickel oxide was performed by the co-precipitation method. The synthesis of the composite was conducted by the impregnation method. FTIR, EDX, SEM, and XRD were used to characterize the synthesized materials. The synthesised materials’ point zero charges (PZC) were performed using the potentiometric titration method. The obtained results show that the PZC for neat nickel oxide was around 5, and it was around 8 for Cr/NiONPs. The adsorption action of the prepared materials was examined by applying them to remove Reactive Red 2 (RR2) and Crystal Violate (CV) dyes from solutions. The outcomes demonstrated that Cr/NiONPs were stronger in the removal of dyes than NiONPs. Cr/NiONPs achieved 99.9% removal of dyes after 1 h. Adsorption isotherms involving Freundlich and Langmuir adsorption isotherms were also conducted, and the outcomes indicated that the most accurate representation of the adsorption data was offered by Langmuir adsorption isotherms. Additionally, it was discovered that the adsorption characteristics of the NiONPs and Cr/NiONPs correspond well with the pseudo-second-order kinetic model. Each of the NiONPs and Cr/NiONPs was reused five times, and the results display that the effectiveness of the removal of RR2 dye slightly declined with the increase in reuse cycles; it lost only 5% of its original efficiency after the 5 cycles. Generally, Cr/NiONPs showed better reusability than NiONPs under the same conditions.

Engineering rockmass classifications are an integral part of design, support and excavation procedures of tunnels, mines, and other underground structures. These classifications are directly linked to ground reaction and support requirements. Various classification systems are in practice and are still evolving. As different classifications serve different purposes, it is imperative to establish inter-correlatability between them. The rating systems and engineering judgements influence the assignment of ratings owing to cognition. To understand the existing correlation between different classification systems, the existing correlations were evaluated with the help of data of 34 locations along a 618-m-long railway tunnel in the Garhwal Himalaya of India and new correlations were developed between different rock classifications. The analysis indicates that certain correlations, such as RMR-Q, RMR-RMi, RMi-Q, and RSR-Q, are comparable to the previously established relationships, while others, such as RSR-RMR, RCR-Qn, and GSI-RMR, show weak correlations. These deviations in published correlations may be due to individual parameters of estimation or measurement errors. Further, incompatible classification systems exhibited low correlations. Thus, the study highlights a need to revisit existing correlations, particularly for rockmass conditions that are extremely complex, and the predictability of existing correlations exhibit high variations. In addition to augmenting the existing database, new correlations for metamorphic rocks in the Himalayan region have been developed and presented that can serve as a guide for future rock engineering projects in such formations and aid in developing appropriate excavation and rock support methodologies.

Here we inspect whether microbial life may disperse using dust transported by wind in the Atacama Desert in northern Chile, a well-known Mars analog model. By setting a simple experiment across the hyperarid core of the Atacama we found that a number of viable bacteria and fungi are in fact able to traverse the driest and most UV irradiated desert on Earth unscathed using wind-transported dust, particularly in the later afternoon hours. This finding suggests that microbial life on Mars, extant or past, may have similarly benefited from aeolian transport to move across the planet and find suitable habitats to thrive and evolve.

Groundwater management requires a systematic approach since it is crucial to the long-term viability of livelihoods and regional economies all over the world. There is insufficient groundwater management and difficulties in storage plans as a result of increased population, fast urbanisation, and climate change, as well as unpredictability in rainfall frequency and intensity. Groundwater exploration using remote sensing (RS) data and geographic information system (GIS) has become a breakthrough in groundwater research, assisting in the assessment, monitoring, and conservation of groundwater resources. The study region is the Mand catchment of the Mahanadi basin, covering 5332.07 km2 and is located between 21°42′15.525″N and 23°4′19.746″N latitude and 82°50′54.503″E and 83°36′1.295″E longitude in Chhattisgarh, India. The research comprises the generation of thematic maps, delineation of groundwater potential zones and the recommendation of structures for efficiently and successfully recharging groundwater utilising RS and GIS. Groundwater Potential Zones (GPZs) were identified with nine thematic layers using RS, GIS, and the Multi-Criteria Decision Analysis (MCDA) method. Satty's Analytic Hierarchy Process (AHP) was used to rank the nine parameters that were chosen. The generated GPZs map indicated regions with very low, low to medium, medium to high, and very high groundwater potential encompassing 962.44 km2, 2019.92 km2, 969.19 km2, and 1380.42 km2 of the study region, respectively. The GPZs map was found to be very accurate when compared with the groundwater fluctuation map, and it is used to manage groundwater resources in the Mand catchment. The runoff of the study area can be accommodated by the computing subsurface storage capacity, which will raise groundwater levels in the low and low to medium GPZs. According to the study results, various groundwater recharge structures such as farm ponds, check dams and percolation tanks were suggested in appropriate locations of the Mand catchment to boost groundwater conditions and meet the shortage of water resources in agriculture and domestic use. This study demonstrates that the integration of GIS can provide an efficient and effective platform for convergent analysis of various data sets for groundwater management and planning.

Gilsonite has a wide variety of applications in the industry, including the manufacture of electrodes, paints and resins, as well as the production of asphalt and roof-waterproofing material. Gilsonite ash is a determining parameter for its application in some industries (e.g., gilsonite with ash content < 5% used as an additive in drilling fluids, resins). Due to the shortage of high grade (low ash) gilsonite reserves, the aim of this study is to develop a processing flowsheet for the production of ultra-low-ash gilsonite (< 5%), based on process mineralogy studies and processing tests. For this purpose, mineralogical studies and flotation tests have been performed on a sample of gilsonite with an average ash content of 15%. According to mineralogical studies, carbonates and clay minerals are the main associated impurities (more than 90 vol.%). Furthermore, sulfur was observed in two forms of mineral (pyrite and marcasite) and organic in the structure of gilsonite. Most of these impurities are interlocked with gilsonite in size fractions smaller than 105 µm. The size fraction of + 105 − 420 µm has a higher pure gilsonite (approximately 90%) than other size fractions. By specifying the gangue minerals with gilsonite and the manner and extent of their interlocking with gilsonite, + 75 − 420 µm size fraction selected to perform flotation tests. Flotation tests were performed using different reagents including collector (Gas oil, Kerosene and Pine oil), frother (MIBC) and depressant (sodium silicate, tannic acid, sulfuric acid and sodium cyanide) in different dosages. Based on the results, the use of kerosene collector, MIBC frother and a mixture of sodium silicate, tannic acid, sulfuric acid and sodium cyanide depressant had the most favorable results in gilsonite flotation in the rougher stage. Cleaner and recleaner flotation stages for the rougher flotation concentrate resulted in a product with an ash content of 4.89%. Due to the interlocking of gilsonite with impurities in size fractions − 105 µm, it is better to re-grinding the concentrate of the rougher stage beforehand flotation in the cleaner and recleaner stages. Finally, based on the results of mineralogical studies and processing tests, a processing flowsheet including crushing and initial granulation of gilsonite, flotation in rougher, cleaner and recleaner stages has been proposed to produce gilsonite concentrate with < 5% ash content.

Dicarboxylic amino acid-based surfactants (N-dodecyl derivatives of -aminomalonate, -aspartate, and -glutamate) in combination with hexadecyltrimethylammonium bromide (HTAB) form a variety of aggregates. Composition and concentration-dependent mixtures exhibit liquid crystal, gel, precipitate, and clear isotropic phases. Liquid crystalline patterns, formed by surfactant mixtures, were identified by polarizing optical microscopy. FE-SEM studies reveal the existence of surface morphologies of different mixed aggregates. Phase transition and associated weight loss were found to depend on the composition where thermotropic behaviours were revealed through combined differential scanning calorimetry and thermogravimetric studies. Systems comprising more than 60 mol% HTAB demonstrate shear-thinning behaviour. Gels cause insignificant toxicity to human peripheral lymphocytes and irritation to bare mouse skin; they do not display the symptoms of cutaneous irritation, neutrophilic invasion, and inflammation (erythema, edema, and skin thinning) as evidenced by cumulative irritancy index score. Gels also exhibit substantial antibacterial effects on Staphylococcus aureus, a potent causative agent of skin and soft tissue infections, suggesting its possible application as a vehicle for topical dermatological drug delivery.

We report the fabrication and testing of dye sensitized solar cells (DSSC) based on tin oxide (SnO2) particles of average size ~20 nm. Fluorine-doped tin oxide (FTO) conducting glass substrates were treated with TiOx or TiCl4 precursor solutions to create a blocking layer before tape casting the SnO2 mesoporous anode. In addition, SnO2 photoelectrodes were treated with the same precursor solutions to deposit a TiO2 passivating layer covering the SnO2 particles. We found that the modification enhances the short circuit current, open-circuit voltage and fill factor, leading to nearly 2-fold increase in power conversion efficiency, from 1.48% without any treatment, to 2.85% achieved with TiCl4 treatment. The superior photovoltaic performance of the DSSCs assembled with modified photoanode is attributed to enhanced electron lifetime and suppression of electron recombination to the electrolyte, as confirmed by electrochemical impedance spectroscopy (EIS) carried out under dark condition. These results indicate that modification of the FTO and SnO2 anode by titania can play a major role in maximizing the photo conversion efficiency

The loss of peri-urban wetlands is a major side effect of urbanization in India in recent days. Timely and proper assessment of wetland area change is essential for the conservation of wetlands. This study follows the integrated way of the peri-urban wetland degradation assessment in the case of medium and small-size urban agglomerations with a special focus on Chatra Wetland. Analysis of land-use and land cover (LULC) maps of the past 28 years shows a decrease of 60% area of the wetland including marshy land. This has reduced the ecosystem services value by about 71.90% over the period 1991–2018. From this end, The Land Change Modeler of IDRISI TerrSet using the combination of MLPNN and Markov Chain has been used to predict the LULC map of this region. The scenario-based modeling following the LULC conversion and nine explanatory variables suggests the complete loss of this wetland by 2045. However, the authors have also tried to present a future LULC pattern of this region based on an environmental perspective. This proposed map suggests possible areas for built-up expansion on the western side of the city without significantly affecting the environment.

Slope streaks have been frequently observed in the equatorial, low thermal inertia and dusty regions of Mars. The reason behind their formation remains unclear with proposed hypotheses for both dry and wet mechanisms. Here, we report an up-to-date distribution and morphometric investigation of Martian slope streaks. We find: (i) a remarkable coexistence of the slope streak distribution with the regions on Mars with high abundances of water-equivalent hydrogen, chlorine, and iron; (ii) favourable thermodynamic conditions for transient deliquescence and brine development in the slope streak regions; (iii) a significant concurrence of slope streak distribution with the regions of enhanced atmospheric water vapour concentration, thus suggestive of a present-day regolith-atmosphere water cycle; and (iv) terrain preferences and flow patterns supporting a wet mechanism for slope streaks. These results suggest a strong local regolith-atmosphere water coupling in the slope streak regions that leads to the formation of these fluidised features. Our conclusions can have profound astrobiological, habitability, environmental, and planetary protection implications

Several interpretations of recurring slope lineae (RSL) have related RSL to the potential presence of transient liquid water on Mars. Such probable signs of liquid water have implications for Mars exploration in terms of rover safety, planetary protection during rover operations, and the current habitability of the planet. Mawrth Vallis has always been a prime target to be considered for Mars rover missions due to its rich mineralogy. Most recently, Mawrth Vallis was one of the two final candidates selected by the European Space Agency as a landing site for the ExoMars 2020 mission. Therefore, all surface features and landforms in Mawrth Vallis that may be of special interest in terms of scientific goals, rover safety, and operations must be scrutinised to better assess it for future Mars missions. Here, we report on the initial detection of RSL candidates in two craters of Mawrth Vallis. The new sightings were made outside of established RSL regions and further prompt the inclusion of a new geographical region within the RSL candidate group. Our inferences on the RSL candidates are based on several morphological and geophysical evidences and analogies: (i) the dimensions of the RSL candidates are consistent with confirmed mid-latitude RSL; (ii) albedo and thermal inertia values are comparable to those of other mid-latitude RSL sites; and (iii) features are found in a summer season image and on the steep and warmest slopes. These results denote the plausible presence of transient liquid brines close to the previously proposed landing ellipse of the ExoMars rover, rendering this site particularly relevant to the search of life. Further investigations of Mawrth Vallis carried out at higher spatial and temporal resolutions are needed to identify more of such features at local scales to maximize the scientific return from the future Mars rovers, to prevent probable biological contamination during rover operations, to evade damage to rover components as brines can be highly corrosive, and to quantify the ability of the regolith at mid-latitudes to capture atmospheric water which is relevant for in-situ-resource utilization.

Revolutionizing construction, the concrete blend seamlessly integrates human hair (HH) fibers and millet husk ash (MHA) as a sustainable alternative. By repurposing human hair for enhanced tensile strength and utilizing millet husk ash to replace sand, these materials not only reduce waste but also create a durable, eco-friendly solution. This groundbreaking methodology not only adheres to established structural criteria but also advances the concepts of the circular economy, representing a significant advancement towards environmentally sustainable and resilient building practices. The main purpose of the research is to investigate the fresh and mechanical characteristics of concrete blended with 10–40% MHA as a sand substitute and 0.5–2% HH fibers by applying response surface methodology modeling and optimization. A comprehensive study involved preparing 225 concrete specimens using a mix ratio of 1:1.5:3 with a water-to-cement ratio of 0.52, followed by a 28 day curing period. It was found that a blend of 30% MHA and 1% HH fibers gave the best compressive and splitting tensile strengths at 28 days, which were 33.88 MPa and 3.47 MPa, respectively. Additionally, the incorporation of increased proportions of MHA and HH fibers led to reductions in both the dry density and workability of the concrete. In addition, utilizing analysis of variance (ANOVA), response prediction models were created and verified with a significance level of 95%. The models&apos; R2 values ranged from 72 to 99%. The study validated multi-objective optimization, showing 1% HH fiber and 30% MHA in concrete enhances strength, reduces waste, and promotes environmental sustainability, making it recommended for construction.

Identifying the critical factors related to influenza spreading is crucial in predicting and mitigating epidemics. Specifically, uncovering the relationship between epidemic onset and various risk indicators such as socioeconomic, mobility and climate factors can reveal locations and travel patterns that play critical roles in furthering an outbreak. We study the 2009 A(H1N1) influenza outbreaks in Sweden’s municipalities between 2009 and 2015 and use the Generalized Inverse Infection Method (GIIM) to assess the most significant contributing risk factors. GIIM represents an epidemic spreading process on a network: nodes correspond to geographical objects, links indicate travel routes, and transmission probabilities assigned to the links guide the infection process. Our results reinforce existing observations that the influenza outbreaks considered in this study were driven by the country’s largest population centers, while meteorological factors also contributed significantly. Travel and other socioeconomic indicators have a negligible effect. We also demonstrate that by training our model on the 2009 outbreak, we can predict the epidemic onsets in the following five seasons with high accuracy.

Commonly used humidity sensors are based on metal oxides, polymers or carbon. Their sensing accuracy often deteriorates with time, especially when exposed to higher temperatures or very high humidity. An alternative solution based on the utilization of Portland cement-based mortars containing in-situ grown carbon nanofibers (CNFs) was evaluated in this study. The relationship between the electrical resistivity, CNF content and humidity were determined. The highest sensitivity was observed for samples containing 10 wt.% of the nanomodified cement which corresponded to 0.27 wt.% of CNFs. The highest calculated sensitivity was approximately 0.01024 per 1% change in relative humidity (RH). The measured electrical resistivity is a linear function of the RH in the humidity range between 11% and 97%. The percolation threshold value was estimated to be at around 7 wt.% of the nanomodified cement, corresponding to ~0.19 wt.% of CNFs.

Methane (CH4) is a greenhouse gas resulting from human activities, especially landflls, and it hasmany potential environmental issues, such as its major role in global warming. On the other hand,methane can be converted to liquid fuel or electricity using chemical conversion or gas turbinegenerators. Therefore, reusing such gases could be of great environmental and economic beneft. Inthis context, this study aims to estimate the emissions of methane gas from the landflls in Al-HillahCity, Iraq, from 2023 to 2070 and the producible electric energy from this amount. The estimatingprocess was carried out using the Land GEM model and compared with traditional models. Theobtained results demonstrated that the total estimated landfll methane emissions for 48 years are875,217 tons, and the average annual methane emission is 18,234 tons based on a yearly wasteaccumulation rate of 1,046,413 tons and a total waste amount of 50,227,808 tons. The anticipatedloads of methane gas can be utilized to generate about 287,442 MW/year of electricity from 2023to 2070. In conclusion, the results obtained from this study could be evidence of the potentialenvironmental and economic benefts of harvesting and reusing methane gas from landflls.

Durability and reliability are the key factors that prevent fuel cells from successful implementation in automotive sector. Dynamic load change is a common and frequent condition that the fuel cell has to undergo in automotive applications. Fuel cells are more sensitive to changes in load conditions and degrade based on load variation representing idling, rated power, and high power operating conditions. To examine the influence of dynamic load step on the fuel cell performance, two similar cells of active 25 cm2 was tested under two different load step for the same dynamic load cycle. The main difference in dynamic load cycle 2 was the ramp rate which was fixed as 0.1, 0.3, and 0.25 A/cm2/s for 0.2, 0.6, and 1.0 A/cm2 respectively. To investigate the degradative effects, polarization curves, electrochemical impedance spectroscopy, and field emission scanning electron microscopy were used. The results indicated that the degradation rate increased in both dynamic load cycles but however the impact of load change was comparatively minimal in dynamic load cycle 2. The total degradation in performance was 20.67% and 10.72% in dynamic load cycles 1 and 2 respectively. Fuel cell performance degraded in a manner that was consistent with the electrochemical impedance spectroscopy and cross-sectional analysis of field emission scanning electron microscopy. The results prove that the degradation rate is dependent on the load step and the number of load cycles. Severe catalyst degradation and delamination were observed in fuel cells operated under dynamic load cycle 1.

Grinding is the most energy-intensive step in mineral beneficiation processes. The use of grinding aids (GAs) could be an innovative solution to reduce the high energy consumption associated with size reduction. Surprisingly, little is known about the effects of GAs on downstream mineral beneficiation processes, such as flotation separation. The use of ecofriendly GAs such as polysaccharide-based materials would help multiply the reduction of environmental issues in mineral processing plants. As a practical approach, this work explored the effects of a novel polysaccharide-based grinding aid (PGA) on magnetite's grinding and its reverse flotation. Batch grinding tests indicated that PGA improved grinding performance by reducing energy consumption, narrowing particle size distribution of products, and increasing their surface area compared to grinding without PGA. Flotation tests on pure samples illustrated that PGA has beneficial effects on magnetite depression (with negligible effect on quartz floatability) through reverse flotation separation. Flotation of the artificial mixture ground sample in the presence of PGA confirmed the benefits, giving a maximum Fe recovery and grade of 84.4 and 62.5%, respectively. In the absence of starch (depressant), PGA resulted in a separation efficiency of 56.1% compared to 43.7% without PGA. The PGA adsorption mechanism was mainly via physical interaction based on UV–vis spectra, zeta potential tests, Fourier transform infrared spectroscopy (FT-IR), and stability analyses. In general, the feasibility of using PGA, a natural green polymer, was beneficial for both grinding and reverse flotation separation performance.

Day-by-day increasing irrigation water scarcity requires the application of water-saving irrigation techniques to sustain agriculture production. A two-year field investigation was conducted during 2018 to 2020 to determine the effects of various mulches and irrigation volumes on the growth, leaf chemicals and soil properties of one-year-old sweet oranges (Citrus sinensis) cv. Mosambi. The study included three irrigation schedules, viz.100% ETc (I1), 80% ETc (I2), and 60% ETc (I3), and five different mulches were used, viz. without mulch, white polythene, coriander straw, dry grass and black polythene mulches, replicated thrice. Results demonstrated that drip irrigation with 100% ETc and mulching with black polythene mulch significantly increase the plant growth attributes like height of the plant (28.64%) (30.31%), rootstock girth (36.61%) (37.90%), plant canopy spread (E-W and N-S) (EW- 63.82%, NS- 63.87%) (EW- 67.56%, NS- 67.90%) and leaf area (2.4%) (2.34%). Furthermore, plant leaf chlorophyll content (2.41 mg g-1) (2.41 mg g-1) and leaf mineral content such as N (2.39%) (2.40%), P (0.16%) (0.165%), K (1.57%) (1.59%), Ca (47.34 g kg-1) (47.80 g kg-1), Mg (4.54 g kg-1) (4.57 g kg-1), Fe (120.51 g kg-1) (123.15 g kg-1) and Zn (39.00 g kg-1) (37.84 g kg-1) were noted to be significantly (p ≤ 0.05) higher in plants that received 100% (were ETc (I1) and mulching with black polythene mulch (M1) treatment. Taken together, the results suggested that treatments I1 and M1 have the potential to maximize plant growth, leaf chemicals and soil nutrients of sweet orange (Citrus sinensis) cv. Mosambi plants.

It is commonly accepted that the evolution of the human eye has been driven by the maximum intensity of the radiation emitted by the Sun. However, the interpretation of the surrounding environment is constrained not only by the amount of energy received but also by the information content of the radiation. Information is related to entropy rather than energy. The human brain follows Bayesian statistical inference for the interpretation of visual space. The maximization of information occurs in the process of maximizing the entropy. Here, we show that the photopic and scotopic vision absorption peaks in humans are determined not only by the intensity but also by the entropy of radiation. We suggest that through the course of evolution, the human eye has not adapted only to the maximum intensity or to the maximum information but to the optimal wavelength for obtaining information. On Earth, the optimal wavelengths for photopic and scotopic vision are 555 nm and 508 nm, respectively, as inferred experimentally. These optimal wavelengths are determined by the temperature of the star (in this case, the Sun) and by the atmospheric composition.

Geo-polymer concrete has a significant influence on the environmental condition and thus its use in the civil industry leads to a decrease in carbon dioxide (CO2) emission. However, problems lie with its mixed design and casting in the field. This study utilizes supervised artificial-based machine learning algorithms (MLAs) to anticipate the mechanical characteristic of fly ash/slag-based geopolymer concrete (FASBGPC) by utilizing AdaBoost and Bagging on MLPNN to make an ensemble model with 156 data points. The data consist of GGBS (kg/m3), Alkaline activator (kg/m3), Fly ash (kg/m3), SP dosage (kg/m3), NaOH Molarity, Aggregate (kg/m3), Temperature (°C) and compressive strength as output parameter. Python programming is utilized in Anaconda Navigator using Spyder version 5.0 to predict the mechanical response. Statistical measures and validation of data are done by splitting the dataset into 80/20 percent and K-Fold CV is employed to check the accurateness of the model by using MAE, RMSE, and R2. Statistical analysis relies on errors, and tests against external indicators help determine how well models function in terms of robustness. The most important factor in compressive strength measurements is examined using permutation characteristics. The result reveals that ANN with AdaBoost is outclassed by giving maximum enhancement with R2 = 0.914 and shows the least error with statistical and external validations. Shapley analysis shows that GGBS, NaOH Molarity, and temperature are the most influential parameter that has significant content in making FASBGPC. Thus, ensemble methods are suitable for constructing prediction models because of their strong and reliable performance. Furthermore, the graphical user interface (GUI) is generated through the process of training a model that forecasts the desired outcome values when the corresponding inputs are provided. It streamlines the process and provides a useful tool for applying the model&apos;s abilities in the field of civil engineering.

The treatment of methylene blue (MB) dye wastewater through the adsorption process has been a subject of extensive research. However, a comprehensive understanding of the thermodynamic aspects of dye solution adsorption is lacking. Previous studies have primarily focused on enhancing the adsorption capacity of methylene blue dye. This study aimed to develop an environmentally friendly and cost-effective method for treating methylene blue dye wastewater and to gain insights into the thermodynamics and kinetics of the adsorption process for optimization. An adsorbent with selective methylene blue dye adsorption capabilities was synthesized using rice straw as the precursor. Experimental studies were conducted to investigate the adsorption isotherms and models under various process conditions, aiming to bridge gaps in previous research and enhance the understanding of adsorption mechanisms. Several adsorption isotherm models, including Langmuir, Temkin, Freundlich, and Langmuir–Freundlich, were applied to theoretically describe the adsorption mechanism. Equilibrium thermodynamic results demonstrated that the calculated equilibrium adsorption capacity (qe) aligned well with the experimentally obtained data. These findings of the study provide valuable insights into the thermodynamics and kinetics of methylene blue dye adsorption, with potential applications beyond this specific dye type. The utilization of rice straw as an adsorbent material presents a novel and cost-effective approach for MB dye removal from wastewater.

SnO₂ nanocrystals were prepared by precipitation in dodecylamine at 100 °C, then they were reacted with vanadium chloromethoxide in oleic acid at 250 °C. The resulting materials were heat-treated at various temperatures up to 650 °C for thermal stabilization, chemical purification and for studying the overall structural transformations. From the crossed use of various characterization techniques, it emerged that the as-prepared materials were constituted by cassiterite SnO₂ nanocrystals with a surface modified by isolated V(IV) oxide species. After heat-treatment at 400 °C, the SnO₂ nanocrystals were wrapped by layers composed of vanadium oxide (IV-V mixed oxidation state) and carbon residuals. After heating at 500 °C, only SnO₂ cassiterite nanocrystals were obtained, with a mean size of 2.8 nm and wrapped by only V₂O₅-like species. The samples heat-treated at 500 °C were tested as RhB photodegradation catalysts. At 10^-7 M concentration, all RhB was degraded within 1 h of reaction, at a much faster rate than all pure SnO₂ materials reported until now.

Cement production is one of the most energy-intensive manufacturing industries, and the milling circuit of cement plants consumes around 4% of a year's global electrical energy production. It is well understood that modeling and digitalizing industrial-scale processes would help control production circuits better, improve efficiency, enhance personal training systems, and decrease plants' energy consumption. This tactical approach could be integrated using conscious lab (CL) as an innovative concept in the internet age. Surprisingly, no CL has been reported for the milling circuit of a cement plant. A robust CL interconnect datasets originated from monitoring operational variables in the plants and translating them to human basis information using explainable artificial intelligence (EAI) models. By initiating a CL for an industrial cement vertical roller mill (VRM), this study conducted a novel strategy to explore relationships between VRM monitored operational variables and their representative energy consumption factors (output temperature and motor power). Using SHapley Additive exPlanations (SHAP) as one of the most recent EAI models accurately helped fill the lack of information about correlations within VRM variables. SHAP analyses highlighted that working pressure and input gas rate with positive relationships are the key factors influencing energy consumption. eXtreme Gradient Boosting (XGBoost) as a powerful predictive tool could accurately model energy representative factors by R-square ever 0.80 in the testing phase. Comparison assessments indicated that SHAP-XGBoost could provide higher accuracy for VRM-CL structure than conventional modeling tools (Pearson correlation, Random Forest, and Support vector regression.

Graphene nanoplatelets (GrNs) emerge as promising conductive fillers to significantly enhance the electrical conductivity and strength of cementitious composites, contributing to the development of highly efficient composites and the advancement of non-destructive structural health monitoring techniques. However, the complexities involved in these nanoscale cementitious composites are markedly intricate. Conventional regression models encounter limitations in fully understanding these intricate compositions. Thus, the current study employed four machine learning (ML) methods such as decision tree (DT), categorical boosting machine (CatBoost), adaptive neuro-fuzzy inference system (ANFIS), and light gradient boosting machine (LightGBM) to establish strong prediction models for compressive strength (CS) of graphene nanoplatelets-based materials. An extensive dataset containing 172 data points was gathered from published literature for model development. The majority portion (70%) of the database was utilized for training the model while 30% was used for validating the model efficacy on unseen data. Different metrics were employed to assess the performance of the established ML models. In addition, SHapley Additve explanation (SHAP) for model interpretability. The DT, CatBoost, LightGBM, and ANFIS models exhibited excellent prediction efficacy with R-values of 0.8708, 0.9999, 0.9043, and 0.8662, respectively. While all the suggested models demonstrated acceptable accuracy in predicting compressive strength, the CatBoost model exhibited exceptional prediction efficiency. Furthermore, the SHAP analysis provided that the thickness of GrN plays a pivotal role in GrNCC, significantly influencing CS and consequently exhibiting the highest SHAP value of + 9.39. The diameter of GrN, curing age, and w/c ratio are also prominent features in estimating the strength of graphene nanoplatelets-based cementitious materials. This research underscores the efficacy of ML methods in accurately forecasting the characteristics of concrete reinforced with graphene nanoplatelets, providing a swift and economical substitute for laborious experimental procedures. It is suggested that to improve the generalization of the study, more inputs with increased datasets should be considered in future studies.

The current study developed an innovative design for the production of smart multifunctional core-double shell superparamagnetic nanoparticles (NPs) with a focus on the development of a pH-responsive drug delivery system tailored for the controlled release of Phenytoin, accompanied by real-time monitoring capabilities. In this regard, the ultra-small superparamagnetic iron oxide@silica NPs (IO@Si MNPs) were synthesized and then coated with a layer of gelatin containing Phenytoin as an antiepileptic drug. The precise saturation magnetization value for the resultant NPs was established at 26 emu g-1. The polymeric shell showed a pH-sensitive behavior with the capacity to regulate the release of encapsulated drug under neutral pH conditions, simultaneously, releasing more amount of the drug in a simulated tumorous-epileptic acidic condition. The NPs showed an average size of 41.04 nm, which is in the desired size range facilitating entry through the blood–brain barrier. The values of drug loading and encapsulation efficiency were determined to be 2.01 and 10.05%, respectively. Moreover, kinetic studies revealed a Fickian diffusion process of Phenytoin release, and diffusional exponent values based on the Korsmeyer-Peppas equation were achieved at pH 7.4 and pH 6.3. The synthesized NPs did not show any cytotoxicity. Consequently, this new design offers a faster release of PHT at the site of a tumor in response to a change in pH, which is essential to prevent epileptic attacks.

Nano-graphene oxide (nano-GO) is a new class of carbon based materials being proposed for biomedical applications due to its small size, intrinsic optical properties, large specific surface area, and easy to functionalize. To fully exploit nano-GO properties, a reproducible method for its production is of utmost importance. Herein we report, the study of the sequential fracture of GO sheets onto nano-GO with controllable lateral width, by a simple, and reproducible method based on a mechanism that we describe as a confined hot spot atomic fragmentation/reduction of GO promoted by ultrasonication. The chemical and structural changes on GO structure during the breakage were monitored by XPS, FTIR, Raman and HRTEM. We found that GO sheets starts breaking from the defects region and in a second phase through the disruption of carbon bonds while still maintaining crystalline carbon domains. The breaking of GO is accompanied by its own reduction, essentially by the elimination of carboxylic and carbonyl functional groups. Photoluminescence and photothermal studies using this nano-GO are also presented highlighting the potential of this nanomaterial as a unique imaging/therapy platform

Pancreatic Neuroendocrine tumors (PanNET) are challenging to diagnose and often detected at advanced stages due to a lack of specific and sensitive biomarkers. This study utilized proteomics as a valuable approach for cancer biomarker discovery; therefore, mass spectrometry-based proteomic profiling was conducted on plasma samples from 12 subjects (3 controls; 5 Grade I, 4 Grade II PanNET patients) to identify potential proteins capable of effectively distinguishing PanNET from healthy controls. Data are available via ProteomeXchange with the identifier PXD045045. 13.2% of proteins were uniquely identified in PanNET, while 60% were commonly expressed in PanNET and controls. 17 proteins exhibiting significant differential expression between PanNET and controls were identified with downstream analysis. Further, 5 proteins (C1QA, COMP, HSP90B1, ITGA2B, and FN1) were selected by pathway analysis and were validated using Western blot analysis. Significant downregulation of C1QA (p = 0.001: within groups, 0.03: control vs. grade I, 0.0013: grade I vs. grade II) and COMP (p = 0.011: within groups, 0.019: control vs grade I) were observed in PanNET Grade I & II than in controls. Subsequently, ELISA on 38 samples revealed significant downregulation of C1QA and COMP with increasing disease severity. This study shows the potential of C1QA and COMP in the early detection of PanNET, highlighting their role in the search for early-stage (Grade-I and Grade-II) diagnostic markers and therapeutic targets for PanNET.

A considerable amount of ultrafine magnetite as the iron source will end up in the tailing dams since the magnetic separation process markedly drops as the particle size. Cationic reverse flotation could be one of the main alternatives for recovering ultrafine magnetite. As a systematic approach, this study explored the flotation efficiency and interaction mechanisms of two biodegradable ether amines (diamine and monoamine) to separate ultrafine quartz from magnetite (− 20 µm). Several assessments (single and mixed mineral flotation, zeta potential, contact angle, surface tension measurement, turbidity, and Fourier transform infrared) were conducted to explore the efficiency of the process and the interaction mechanisms. Results indicated that ether diamine and monoamine could highly float ultrafine quartz particles (95.9 and 97.7%, respectively) and efficiently separate them from ultrafine magnetite particles. Turbidity assessments highlighted that these cationic collectors could aggregate magnetite particles (potentially hydrophobic coagulation) and enhance their depression. Surface analyses revealed that the collector mainly adsorbed on the quartz particles, while it was essentially a weak interaction on magnetite.

In the present work, three different Mn²⁺-doped calcium pyrophosphate (CPP, Ca₂P₂O₇) polymorphs were synthesized by wet co-precipitation method followed by annealing at different temperatures. The crystal structure and purity were studied by powder X-ray diffraction (XRD), Fourier-transform infrared (FTIR), solid-state nuclear magnetic resonance (SS-NMR), and electron paramagnetic resonance (EPR) spectroscopies. Scanning electron microscopy (SEM) was used to investigate the morphological features of the synthesized products. Optical properties were investigated using photoluminescence measurements. Excitation spectra, emission spectra, and photoluminescence decay curves of the samples were studied. All Mn-doped polymorphs exhibited a broadband emission ranging from approximately 500 to 730 nm. The emission maximum was host-dependent and centered at around 580, 570, and 595 nm for γ-, β-, and α-CPP, respectively.

The Danube is a significant transboundary river on a global scale, with several tributaries. The effluents from industrial operations and wastewater treatment plants have an impact on the river&apos;s aquatic ecosystem. These discharges provide a significant threat to aquatic life by deteriorating the quality of water and sediment. Hence, a total of 16 Polycyclic Aromatic Hydrocarbons (PAHs) compounds were analyzed at six locations along the river, covering a period of 12 months. The objective was to explore the temporal and spatial fluctuations of these chemicals in both water and sediment. The study revealed a significant fluctuation in the concentration of PAHs in water throughout the year, with levels ranging from 224.8 ng/L during the summer to 365.8 ng/L during the winter. Similarly, the concentration of PAHs in sediment samples varied from 316.7 ng/g in dry weight during the summer to 422.9 ng/g in dry weight during the winter. According to the Europe Drinking Water Directive, the levels of PAHs exceeded the permitted limit of 100 ng/L, resulting in a 124.8% rise in summer and a 265.8% increase in winter. The results suggest that the potential human-caused sources of PAHs were mostly derived from pyrolytic and pyrogenic processes, with pyrogenic sources being more dominant. Assessment of sediment quality standards (SQGs) showed that the levels of PAHs in sediments were below the Effect Range Low (ERL), except for acenaphthylene (Acy) and fluorene (Fl) concentrations. This suggests that there could be occasional biological consequences. The cumulative Individual Lifetime Cancer Risk (ILCR) exceeds 1/104 for both adults and children in all sites.

In the context of degradation of soil health, environmental pollution, and yield stagnation in the rice–wheat system in the Indo-Gangetic Plains of South Asia, an experiment was established in split plot design to assess the long-term effect of crop residue management on productivity and phosphorus requirement of wheat in rice–wheat system. The experiment comprised of six crop residue management practices as the main treatment factor with three levels (0, 30 and 60 kg P2O5 ha–1) of phosphorus fertilizer as sub-treatments. Significant improvement in soil aggregation, bulk density, and infiltration rate was observed under residue management (retention/incorporation) treatments compared to residue removal or residue burning. Soil organic carbon (SOC), available nutrient content (N, P, and K), microbial count, and enzyme activities were also significantly higher in conservation tillage and residue-treated plots than without residue/burning treatments. The residue derived from both crops when was either retained/incorporated improved the soil organic carbon (0.80%) and resulted in a significant increase in SOC (73.9%) in the topsoil layer as compared to the conventional practice. The mean effect studies revealed that crop residue management practices and phosphorus levels significantly influenced wheat yield attributes and productivity. The higher grain yield of wheat was recorded in two treatments, i.e. the basal application of 60 kg P2O5 ha–1 without residue incorporation and the other with half the P-fertilizer (30 kg P2O5 ha–1) with rice residue only. The grain yield of wheat where the rice and wheat residue were either retained/incorporated without phosphorus application was at par with 30 and 60 kg P2O5ha–1. Phosphorus levels also significantly affected wheat productivity and available P content in the soil. Therefore, results suggested that crop residue retention following the conservation tillage approach improved the yield of wheat cultivated in the rice–wheat cropping system.

Nitrogen (N) and phosphorus (P) are vital for crop growth. However, most agricultural systems have limited inherent ability to supply N and P to crops. Biochars (BCs) are strongly advocated in agrosystems and are known to improve the availability of N and P in crops through different chemical transformations. Herein, a soil-biochar incubation experiment was carried out to investigate the transformations of N and P in two different textured soils, namely clay loam and loamy sand, on mixing with rice straw biochar (RSB) and acacia wood biochar (ACB) at each level (0, 0.5, and 1.0% w/w). Ammonium N (NH4-N) decreased continuously with the increasing incubation period. The ammonium N content disappeared rapidly in both the soils incubated with biochars compared to the unamended soil. RSB increased the nitrate N (NO3–N) content significantly compared to ACB for the entire study period in both texturally divergent soils. The nitrate N content increased with the enhanced biochar addition rate in clay loam soil until 15 days after incubation; however, it was reduced for the biochar addition rate of 1% compared to 0.5% at 30 and 60 days after incubation in loamy sand soil. With ACB, the net increase in nitrate N content with the biochar addition rate of 1% remained higher than the 0.5% rate for 60 days in clay loam and 30 days in loamy sand soil. The phosphorus content remained consistently higher in both the soils amended with two types of biochars till the completion of the experiment.

Climatic condition is triggering human health emergencies and earth’s surface changes. Anthropogenic activities, such as built-up expansion, transportation development, industrial works, and some extreme phases, are the main reason for climate change and global warming. Air pollutants are increased gradually due to anthropogenic activities and triggering the earth’s health. Nitrogen Dioxide (NO2), Carbon Monoxide (CO), and Aerosol Optical Depth (AOD) are truthfully important for air quality measurement because those air pollutants are more harmful to the environment and human’s health. Earth observational Sentinel-5P is applied for monitoring the air pollutant and chemical conditions in the atmosphere from 2018 to 2021. The cloud computing-based Google Earth Engine (GEE) platform is applied for monitoring those air pollutants and chemical components in the atmosphere. The NO2 variation indicates high during the time because of the anthropogenic activities. Carbon Monoxide (CO) is also located high between two 1-month different maps. The 2020 and 2021 results indicate AQI change is high where 2018 and 2019 indicates low AQI throughout the year. The Kolkata have seven AQI monitoring station where high nitrogen dioxide recorded 102 (2018), 48 (2019), 26 (2020) and 98 (2021), where Delhi AQI stations recorded 99 (2018), 49 (2019), 37 (2020), and 107 (2021). Delhi, Kolkata, Mumbai, Pune, and Chennai recorded huge fluctuations of air pollutants during the study periods, where ~ 50–60% NO2 was recorded as high in the recent time. The AOD was noticed high in Uttar Pradesh in 2020. These results indicate that air pollutant investigation is much necessary for future planning and management otherwise; our planet earth is mostly affected by the anthropogenic and climatic conditions where maybe life does not exist.

Nanobubbles have been applied in many fields, such as environmental cleaning, material production, agriculture, and medicine. However, the measured nanobubble sizes differed among the measurement methods, such as dynamic light scattering, particle trajectory, and resonance mass methods. Additionally, the measurement methods were limited with respect to the bubble concentration, refractive index of liquid, and liquid color. Here, a novel interactive force measurement method for bulk nanobubble size measurement was developed by measuring the force between two electrodes filled with bulk nanobubble-containing liquid under an electric field when the electrode distance was changed in the nm scale with piezoelectric equipment. The nanobubble size was measured with a bubble gas diameter and also an effective water thin film layer covered with a gas bubble that was estimated to be approximately 10 nm based on the difference between the median diameter of the particle trajectory method and this method. This method could also be applied to the solid particle size distribution measurement in a solution.

A ball-on-disc machine was employed in a highly idealised setting to study the interplay between oil film formation and surface irregularities in single-sided rough elasto-hydrodynamic lubricated (EHL) conjunctions. The tests were operated under GPa pressures and high slide-to-roll ratios in a situation where the separating gap was smaller than the combined surface roughness height. Under the initial state of solid contact interference and with the operating conditions held fixed, surfaces were found to gradually conform such that a fully separating oil film of nanometre thickness eventually developed—a thin film lubrication state known as micro-EHL. Additionally, with a previously developed approach for 3D surface re-location analysis, we were able to very precisely specify the pertained nature of surface transformations, even at the asperity scale, by comparing the post-test surfaces to those in the virgin state. The surface roughness Sq was reduced by up to 17% after running-in, while the speed required for full film EHL was reduced by a remarkable 90%. Hence, full film EHL is possible even in cases where the Λ-ratio falsely suggests boundary lubrication. This discrepancy was attributed to the way surfaces are deformed inside the contact, i.e., through the establishment of micro-EHL.

There has been an increasing interest in recent years in isolating cellulose nanofibers from unbleached cellulose pulps for economic, environmental, and functional reasons. In the current work, cellulose nanofibers isolated from high-lignin unbleached neutral sulfite pulp were compared to those isolated from bleached rice straw pulp in making thin-film ultrafiltration membranes by vacuum filtration on hardened filter paper. The prepared membranes were characterized in terms of their microscopic structure, hydrophilicity, pure water flux, protein fouling, and ability to remove lime nanoparticles and purify papermaking wastewater effluent. Using cellulose nanofibers isolated from unbleached pulp facilitated the formation of a thin-film membrane (with a shorter filtration time for thin-film formation) and resulted in higher water flux than that obtained using nanofibers isolated from bleached fibers, without sacrificing its ability to remove the different pollutants.

Many nanotechnological applications, using single-walled carbon nanotubes (SWNTs), are only possible with a uniform product. Thus, direct control over the product during chemical vapor deposition (CVD) growth of SWNT is desirable, and much effort has been made towards the ultimate goal of chirality-controlled growth of SWNTs. We have used density functional theory (DFT) to compute the stability of SWNT fragments of all chiralities in the series representing the targeted products for such applications, which we compare to the chiralities of the actual CVD products from all properly analyzed experiments. From this comparison we find that in 84% of the cases the experimental product represents chiralities among the most stable SWNT fragments (within 0.2 eV) from the computations. Our analysis shows that the diameter of the SWNT product is governed by the well-known relation to size of the catalytic nanoparticles, and the specific chirality is normally determined by the product’s relative stability, suggesting thermodynamic control at the early stage of product formation. Based on our findings, we discuss the effect of other experimental parameters on the chirality of the product. Furthermore, we highlight the possibility to produce any tube chirality in the context of recent published work on seeded-controlled growth.

Intelligent control of friction is an attractive but challenging topic and it has rarely been investigated for full size engineering applications. In this work, it is instigated if it would be possible to adjust friction by controlling viscosity in a lubricated contact. By exploiting the ability to adjust the viscosity of the switchable ionic liquids, 1,8-Diazabicyclo (5.4.0) undec-7-ene (DBU)/ glycerol mixture via the addition of CO2, the friction could be controlled in the elastohydrodynamic lubrication (EHL) regime. The friction decreased with increasing the amount of CO2 to the lubricant and increased after partial releasing CO2. As CO2 was absorbed by the liquid, the viscosity of the liquid increased which resulted in that the film thickness increased. At the same time the pressure-viscosity coefficient decreased with the addition of CO2. When CO2 was released again the friction increased and it was thus possible to control friction by adding or removing CO2.

Ferulic acid esterases (FAE, EC 3.1.1.73) cleave the arabinose hydroxycinnamate ester in plant hemicellulose and other related substrates. FAE are commonly categorised as type A-D based on catalytic activities towards model, short alkyl chain esters of hydroxycinnamates. However, this system correlates poorly with sequence and structural features of the enzymes. In this study, we investigated the basis of the type A categorisation of an FAE from Aspergillus niger, AnFaeA, by comparing its activity toward methyl and arabinose hydroxycinnamate esters. kcat/Km ratios revealed that AnFaeA hydrolysed arabinose ferulate 1600-fold, and arabinose caffeate 6.5 times more efficiently than their methyl ester counterparts. Furthermore, small docking studies showed that while all substrates adopted a catalytic orientation with requisite proximity to the catalytic serine, methyl caffeate and methyl p-coumarate preferentially formed alternative non-catalytic conformations that were energetically favoured. Arabinose ferulate was unable to adopt the alternative conformation while arabinose caffeate preferred the catalytic orientation. This study demonstrates that use of short alkyl chain hydroxycinnnamate esters can result in activity misclassification. The findings of this study provide a basis for developing a robust classification system for FAE and form the basis of sequence-function relationships for this class.

Water scarcity contributes to the poverty of around one-third of the world's people. Despite many benefits, tree planting in dry regions is often discouraged by concerns that trees reduce water availability. Yet relevant studies from the tropics are scarce, and the impacts of intermediate tree cover remain unexplored. We developed and tested an optimum tree cover theory in which groundwater recharge is maximized at an intermediate tree density. Below this optimal tree density the benefits from any additional trees on water percolation exceed their extra water use, leading to increased groundwater recharge, while above the optimum the opposite occurs. Our results, based on groundwater budgets calibrated with measurements of drainage and transpiration in a cultivated woodland in West Africa, demonstrate that groundwater recharge was maximised at intermediate tree densities. In contrast to the prevailing view, we therefore find that moderate tree cover can increase groundwater recharge, and that tree planting and various tree management options can improve groundwater resources. We evaluate the necessary conditions for these results to hold and suggest that they are likely to be common in the seasonally dry tropics, offering potential for widespread tree establishment and increased benefits for hundreds of millions of people

The utilization of Self-compacting Concrete (SCC) has escalated worldwide due to its superior properties in comparison to normal concrete such as compaction without vibration, increased flowability and segregation resistance. Various other desirable properties like ductile behaviour, increased strain capacity and tensile strength etc. can be imparted to SCC by incorporation of fibres. Thus, this study presents a novel approach to predict 28-day compressive strength (C–S) of FR-SCC using Gene Expression Programming (GEP) and Multi Expression Programming (MEP) for fostering its widespread use in the industry. For this purpose, a dataset had been compiled from internationally published literature having six input parameters including water-to-cement ratio, silica fume, fine aggregate, coarse aggregate, fibre, and superplasticizer. The predictive abilities of developed algorithms were assessed using error metrices like mean absolute error (MAE), a20-index, and objective function (OF) etc. The comparison of MEP and GEP models indicated that GEP gave a simple equation having lesser errors than MEP. The OF value of GEP was 0.029 compared to 0.031 of MEP. Thus, sensitivity analysis was performed on GEP model. The models were also checked using some external validation checks which also verified that MEP and GEP equations can be used to forecast the strength of FR-SCC for practical uses.