This work demonstrates the development of room-temperature curable and durable anti-soiling coating using fluorine functionalized mesoporous silica (F-SiO2) and silicone resin-based hydrophobic coatings. The use of silicone resin with a catalyst enabled room-temperature curing of the coating and enhanced its mechanical properties. The coating prepared from mesoporous silica and F-SiO2 exhibited contact angles of 102 degrees and 122 degrees, indicating a significant improvement in the wettability of F-SiO2-based coatings. Additionally, the transmittance values were 93 % and 94 %, respectively, which are comparable to those of bare PV cover glass. A soiling study of the fabricated coating was conducted in an outdoor environment for over one month. The results confirmed that the F-SiO2-based hydrophobic coatings showed a minimal transmittance loss compared to non-coated PV cover glass. The durability of the F-SiO2-based coating was confirmed by mechanical properties like adhesive strength (1.86 MPa) and hardness (4H). The photo-conversion efficiency of the F-SiO2 coated PV module was measured in an indoor soiling environment using wind cleaning action. It was observed that the module regained its photoconversion efficiency after only one minute of wind cleaning. These results indicate that the prepared coatings have a significant potential for practical application in PV industry.

Radish is a widely cultivated popular and economically important vegetable that can be consumed both as raw as well as in cooked form. However, its production is severely impacted by flea beetles almost round the year. The adults feed on leaves and larvae on roots. Numerous small shot holes on the leaves and dark stripes on the roots are the typical damage symptoms caused by beetle infestation. The biology, molecular taxonomy, damage severity and management of the Phyllotreta striolata along with economics have been studied. In the present study, an integrated organic pest management module was evaluated to control this nefarious pest in the present experiment which includes the following approaches: soil application of neem cake @ 500 kg/ha before radish seed sowing, inter-cropping with Indian mustard every alternate 8 rows as a trap crop 15 days before radish sowing, application of vermicompost enriched with Metarhizium anisopliae @ 10 g/kg of vermicompost during seed sowing; soil application of Heterorhabditis indica @ 10 kg/ha mixed with moist sand with light irrigation, need-based foliar spraying of Metarhizium anisopliae + Neem oil @ 2.5 g/lit + 2.5 ml/lit at 25 and 45 days after sowing (DAS) and Azadirachtin 300 ppm @ 5 ml/lit at 35 DAS were found significantly effective (P < 0.0001) in reducing number of shot holes (37.64/leaf), stripes on radish (7.37/root), population of adults (2.61/plant) and larvae (2.9 on radish root and rhizosphere) compared to farmers' practices (58.09, 16.48, 3.67 and 5.6, respectively) and untreated control plots (139.37, 32.46, 7.58 and 8.3, respectively) at 21 DAS. The organic IPM module had highest root yield (19.3 t/ha) accompanied by highest incremental cost benefit ratio (ICBR) of 1:2.81 followed by farmers' practices (13.9 t/ha and ICBR = 1:2.29) and untreated control (8.4 t/ha and ICBR = 1:1.92). The developed organic pest management module was found highly promising in management of radish flea beetle.

Detecting faults in solar photovoltaic modules (PVM) is crucial for enhancing their longevity, power output, and overall reliability. Visual anomalies such as soiling, partial shading, cell damage, and glass breakage pose significant challenges for fault identification, particularly in harsh environmental conditions. Therefore, it is essential to maintain healthy PV systems with extended lifecycles and optimal performance through the quick and efficient detection of faults. This work introduces a comprehensive approach that encompasses dataset creation, preprocessing, and PV fault classification utilizing the EfficientNet B0 model. Processed RGB images serve as input for the model, enabling the classification of visual faults in PVM. The performance evaluation of the proposed deep neural network model includes metrics such as classification accuracy, F1 score, specificity, and recall. The results highlight the exceptional performance of the proposed model, achieving a classification accuracy of 97.24% for visual fault identification in PV modules. Moreover, the study underscores the model's robustness and efficacy through a comparative analysis with other classification techniques reported in the literature.

Annual freeze-thaw (F-T) cycles can cause significant damage to soil structures, particularly roads. This study explored the effectiveness of adding carbon fibers (CF) to clay to enhance its performance during F-T cycles. The CF were mixed with clay at varying rates, ranging from 0.1 to 0.4%, based on the weight of the dry soil. Dynamic tests were conducted on unreinforced and reinforced samples after subjecting them to 0, 3, 6, and 9 F-T cycles under 100 kPa and 300 kPa confining pressure. The findings revealed that the inclusion of CF led to an increase in both the shear modulus and damping ratio. Specifically, the sample containing 0.3% CF demonstrated a significant 30% increase in shear modulus compared to the pure sample at the same cyclic stress level. Moreover, while the shear modulus decreased with the number of F-T cycles, this reduction was less pronounced in samples reinforced with CF compared to pure samples.

Road infrastructure construction in developing countries such as Vietnam requires an enormous amount of natural sand. The scarcity of river sand is becoming increasingly severe, with predictions indicating a sustained drop in its supply. Hence, it is essential for the construction industry to implement a sustainable strategy by combining waste materials with abundant resources in order to effectively address this challenging situation. The objective of this study is to investigate the mechanical properties and evaluate the potential application of mixtures comprising rock quarry dust and sea sand for the roadbed layers of expressways. The researchers conducted a series of experiments, including the moisture content, specific gravity, angle of repose of material, and triaxial tests to study the composition and mechanical behaviors of mixtures at different ratios. Extensive parametric investigations in conjunction with the calibration in Plaxis' soil-test module obtain the Young's modulus E50 and confining pressure curves. Based on the assessment of materials utilized in roadbed layer of highway, as determined by the California bearing ratio (CBR) coefficient, it demonstrates that combining sea sand and quarry dust can generate the mixtures possessing appropriate properties for application in the construction of the roadbed of highway.

The increasing global demand for renewable energy necessitates a comprehensive understanding of solar photovoltaic (PV) system performance and reliability, particularly in harsh climates such as Iraq. Despite ambitious targets to diversify its energy sector, Iraq faces challenges in the deployment of PV projects due to limited field experience. In this study, we assess the reliability and performance of two different PV systems installed in Basrah and Baghdad, aged 3.5 and 8 years, respectively. Field analysis reveals prevalent issues including glass and cell breakage, delamination, solder bond fatigue, and encapsulant discoloration, contributing to medium degradation rates of 0.91 %/year and 2.6 %/year in Basrah and Baghdad, respectively. Our investigation attributes higher degradation rates not only to ageing but also to suboptimal operation and maintenance (O&M) practices. Additionally, since the two systems are from different manufacturers, we verify that the measured higher degradation rates are mainly attributed to harsh operating conditions rather than differences in manufacturing processes. To extrapolate our findings countrywide, we employ a physics-based model to simulate the degradation rates. Based on the simulated degradation, we proposed four degradation rate zones across the country with degradation rates ranging from 0.62 %/year to 0.96 %/year. By applying these rates to estimate lifetime energy yield across different zones, we demonstrate the trade-offs between higher irradiance zones with reduced PV lifetime and low irradiance zones with longer PV lifetimes. In the study, we compared energy yield simulations using fixed degradation rates with those employing climate-dependent degradation rates. Our analysis revealed that in certain locations in Iraq, employing a fixed degradation rate underestimates the yield by approximately 9.7 %. Conversely, in other locations, it results in overestimations ranging from approximately 10.5 %-31.1 %, highlighting the importance of accurate degradation rate modelling for PV system assessment. Furthermore, we simulate the impact of soiling losses on energy yield, revealing potential losses of up to 70 % depending on location and cleaning schedules. Our findings contribute valuable insights into PV system degradation across harsh climates, addressing critical gaps in global degradation rate data and facilitating more accurate climate-dependent assessments of PV performance and reliability.

Wildfires are unplanned conflagrations perceived as a threat by humans. However, fires are essential for the survival of fire-adapted plants. On the one hand, wildfires cause major damage worldwide, burning large areas of forests and landscapes, threatening towns and villages, and generating high levels of air pollution. On the other hand, fire-adapted plants (pyrophytes) in the fire landscapes of the Earth are able to survive exposure to heat (e.g., because of their thick bark, which protects their living tissue) and benefit from fire directly (e.g., fire initiates cone opening and seed release) or indirectly (e.g., fewer competing plants of fire-sensitive species remain, seeds germinate in the ash-fertilized soil). We present the experimental set-up and results of a fire experiment on bark samples used as a basis to assess the fire tolerance of various trees. Fire tolerance is defined as the ability of a tree to survive a surface fire (up to 200 degrees C and 5 min duration). The measure of the fire tolerance for a tree species is the time taken for the vascular cambium under the insulating bark to reach the critical temperature of 60 degrees C. Within an educational module, we provide worksheets for teachers and students enabling them to analyze the fire tolerance of various tree barks.

Perovskite solar cells (PSCs) are emerging photovoltaic (PV) technologies capable of matching power conversion efficiencies (PCEs) of current PV technologies in the market at lower manufacturing costs, making perovskite solar modules (PSMs) cost competitive if manufactured at scale and perform with minimal degradation. PSCs with the highest PCEs, to date, are lead halide perovskites. Lead presents potential environmental and human health risks if PSMs are to be commercialized, as the lead in PSMs are more soluble in water compared to other PV technologies. Therefore, prior to commercialization of PSMs, it is important to highlight, identify, and establish the potential environmental and human health risks of PSMs as well as develop methods for assessing the potential risks. Here, we identify and discuss a variety of international standards, U.S. regulations, and permits applicable to PSM deployment that relate to the potential environmental and human health risks associated with PSMs. The potential risks for lead and other hazardous material exposures to humans and the environment are outlined which include water quality, air quality, human health, wildlife, land use, and soil contamination, followed by examples of how developers of other PV technologies have navigated human health and environmental risks previously. Potential experimentation, methodology, and research efforts are proposed to elucidate and characterize potential lead leaching risks and concerns pertaining to fires, in-field module damage, and sampling and leach testing of PSMs at end of life. Lastly, lower technology readiness level solutions to mitigate lead leaching, currently being explored for PSMs, are discussed. PSMs have the potential to become a cost competitive PV technology for the solar industry and taking steps toward understanding, identifying, and creating solutions to mitigate potential environmental and human health risks will aid in improving their commercial viability.

Numerical modeling serves as a widely utilized method for addressing geotechnical concerns. A pivotal aspect of this modeling process is the accurate characterization of material behavior. The connection between stress and strain tensors within soil is explicated by the soil constitutive equation, which is reliant on factors like soil type and deformation circumstances. One notable model is hypoplasticity, which has been in use for more than three decades. This research aims to calibrate the hypoplastic parameters for Danube sand using the SoilTest Module of PLAXIS. The constitutive hypoplastic model for Danube sand was fine-tuned through a series of numerical simulations. The parameter calibration occurred twice: initially according to 5 cycles of hysteresis loop of stress-strain diagram of cyclic triaxial testing, and then subsequently in accordance with strain trends observed after ten thousand cycles. A comparison was drawn between parameters determined from the overall strain trends and those calibrated based on the five cycles. The findings indicate that while the model calibrated during a specific segment of testing can accurately predict strain values during compression and extension, it falls short in forecasting the accumulated settlement following prolonged cyclic loading. This suggests the model's limited capability in anticipating long-term cyclic load effects on settlement behavior.

The contributions of long-lived nitrous oxide (N2O) to global climate and environment have received increasing attention. Especially, atmospheric nitrogen (N) deposition has substantially increased in recent decades due to the extensive use of fossil fuels in industry, which strongly stimulates the N2O emissions of terrestrial ecosystem. Several models have been developed to simulate the impacts of environmental factors on N2O emission from soil, but there are still large differences in the simulations of N2O emission and their responses to atmospheric deposition over global or regional scales. Using observations from N addition experiments in a subtropical forest, this study compared five widely-used N2O modules or algorithms (i.e. the N2O modules of DayCENT, PnET-NDNDC and DyN, and the algorithm of NOE and NGAS) to investigate their performances for reproducing N2O emission, and especially the impacts of two forms of N additions (i.e. NH4+-N and NO3--N, respectively) of two levels (low and high) on N2O emission. In general, the five modules reproduced the seasonal variations of N2O emission. Under the high levels of N addition compared to low ones for both NH4+-N and NO3--N, however, not all modules can reproduce larger N2O emission. Relatively larger N2O emissions in measurements due to NH4+N compared to NO3--N additions were not indicated neither in all the modules. Moreover, there were substantial differences in simulating the ratios of N2O emission from nitrification and denitrification processes due to disagreements in the structure of these modules or algorithms. The comparison highlights the need to improve the representation of N2O production and diffusion processes. At the same time, it also highlights the application of WFPS in the model methodology as a key scheme that mediates the two microbial processes, i.e. nitrification and denitrification, could probably improve the performances of N2O models in future research.