Key Parameters Research Articles

Continuous inline monitoring of glucose in an organ-on-chip using FreeStyle™ libre glucometers

Introduction: Organ-on-chips have become an effective platform for studying the physiology of tissues and organs and for evaluating the safety and efficacy of drugs. In these systems, the inline monitoring of key parameters of biological performance (i.e., glucose, oxygen, or lactic acid concentrations) provides valuable information regarding the cell/tissue physiological state. However, significant limitations still exist when attempting to obtain inline information in these systems, and the microsensing technology of on-chip measurement of key parameters is still limited by size, cost, and availability.Methods: Here, we demonstrate the use of a commercially available glucometer (FreestleTM Libre; Abbott), normally used for continuous determination of blood glucose levels, to provide continuous inline measurements of the glucose concentration in tumor-on-chips. Here, we employed a colorectal tumor-on-chip as a first demonstration model and measured the on-chip concentration of glucose continuously for extended culture times (2 weeks).Results and Discussion: We show that inline glucose readings are reproducible and enable the accurate determination of glucose consumption rates (GCRs) by a tumor cell culture. In turn, the GCR measurements provide valuable information regarding the changes in the metabolic activity of the on-chip cultures following inlet perturbations (i.e., delivery of pulses of glucose, culture media additives, and drugs). Inline continuous glucose sensors will be useful tools in organ-on-chip research and will greatly enable cancer research in tumor-on-chip systems.

Application of Minerals for the Characterization of Geothermal Reservoirs and Cap Rock in Intracontinental Extensional Basins and Volcanic Islands in the Context of Subduction

Whether from the near-surface or at great depths, geothermal energy aims to harness the heat of the Earth to produce energy. Herein, emphasis is put on geothermal reservoirs and their cap rock in crystalline rocks, in particular, the basements of sedimentary basins and volcanic islands in the context of subduction. This study is based on a case study of three examples from around the world. The aim of this paper is to show how the study of newly formed minerals can help the exploration of geothermal reservoirs. The key parameters to define are the temperature (maximum temperature reached formerly), fluid pathways, and the duration of geothermal events. To define these parameters, numerous methods are used, including optical and electronic microscopy, X-ray diffraction, microthermometry on fluid inclusions, chlorite geothermometry, and geochemistry analysis, including that of isotopes. The key minerals that are studied herein are phyllosilicates and, in particular, clay minerals, quartz, and carbonates. They are formed because of hydrothermal alterations in fracture networks. These minerals can have temperatures of up to 300 °C (and they can cool down to 50 °C), and sometimes, they allow for one to estimate the cooling rate (e.g., 150 °C/200 ka). The duration of a hydrothermal event (e.g., at least 63 Ma or 650 ka, depending on the site) can also be established based on phyllosilicates.

Early-stage hepatocellular carcinoma screening in patients with chronic hepatitis B in China: a cost-effectiveness analysis.

Aim: To evaluate the cost-effectiveness of seven screening strategies for chronic hepatitis B (CHB) patients in China. Methods: A discrete event simulation model combining a decision tree and Markov structure was developed to simulate a CHB cohort aged ≥40years on a lifetime horizon and evaluate the costs and health outcomes (quality-adjusted life years [QALYs] gained) of ultrasonography (US), alpha-fetoprotein (AFP), protein induced by vitamin K absence-II (PIVKA-II), AFP+US, AFP+PIVKA-II, GAAD (a diagnostic algorithm based on gender and age combined with results of AFP and PIVKA-II) and GAAD+US. Epidemiologic, clinical performance, utility and cost data were obtained from the literature, expert interviews and real-world data. Uncertainties on key parameters were explored through deterministic and probabilistic sensitivity analyses (DSA and PSA). Results: Compared with other strategies, GAAD+US detected the most HCC patients at early stage, and GAAD was the screening strategy with the lowest average cost per HCC case diagnosed. Using 3× China's 2022 GDP per capita ($38,233.34) as the threshold, the three strategies of US, GAAD and GAAD+US formed a cost-effectiveness frontier. Screening with US, GAAD, or GAAD+US was associated with costs of $6110.46, $7622.05 and $8636.32, and QALYs of 13.18, 13.48 and 13.52, respectively. The ICER of GAAD over US was $4993.39/QALY and the ICER of GAAD+US over GAAD was $26,691.45/QALY, which was less than 3× GDP per capita. Both DSA and PSA proved the stability of the results. Conclusion: GAAD+US was the most cost-effective strategy for early HCC diagnosis among CHB patients which could be considered as the liver cancer screening scheme for the high-risk population in China.

Palm oil-based biodiesel industry sustainability model using dynamic systems to balance food, energy, and export allocations

Indonesia stands as one of the foremost global palm oil producers, contributing to 85 % of the world's total production. Given the substantial output of Crude Palm Oil (CPO), these raw materials find diverse applications in daily life. In a bid to decrease reliance on fossil fuels, Indonesia initiated the blending of fossil fuels with biodiesel in 2006. Beyond energy purposes, CPO raw materials are crucial for both domestic consumption and exportation. However, improper management could lead to raw material shortages. This study employs dynamic system modeling to assess the availability of biodiesel, CPO production, and their equilibrium concerning Indonesia's blended biodiesel target. Key parameters, such as available land, anticipated land expansion, optimized CPO production on less productive land, Indonesian CPO exports, and the mandatory biodiesel program, will be considered. Various scenarios or tests will be applied to gauge the continuity of CPO and biodiesel production. The results will undergo validation using the MAPE method. The simulation's results reveal that the rate of new land expansion and the optimization of unproductive land have negligible effects on meeting the blended diesel target. Intensified optimization of unproductive land, particularly in community plantations, is crucial, necessitating incentives for enhanced replanting funds. A reduction of 8 % in CPO export level, in turn, has a noteworthy impact on achieving the blended diesel target in Indonesia.

Seismic performance of rocking braced frames with double base plate connections

This paper presents a rocking system for concentrically braced frames (CBFs) to mitigate the seismic demands induced by seismic motions. The proposed system incorporates double base plate connections (DBPCs) at the base of the braced-bay columns, enabling them to uplift and initiate a rocking motion. The DBPC comprised two base plates: the upper one is thin, connected to the column and designed to yield under uplift loading, while the lower one primarily distributes compressive loads to the foundation. The DBPC was modeled using a combination of spring and gap elements in SAP2000 software. A comparative study was performed to investigate the seismic performance of the proposed rocking system against a conventional CBF system. Key parameters such as the thickness of the upper base plate and the arrangement of anchor rods were considered. Four prototype frames of different heights (3, 6, 9, and 12 stories) were investigated under the Sylmar-x record using the nonlinear time history analysis. The results demonstrated that utilizing rocking braced frames with double base plate connections can remarkably mitigate the base shear force by softening the structural response, decreasing the seismic damage experienced by the structure. The upper base plate acted similarly to a footing damper, absorbing a substantial amount of energy by yielding. Importantly, the residual drifts caused by the plastic deformations of the upper base plate remained within the acceptable performance limits for self-centering systems. Moreover, the self-centering mechanism was achieved solely through the structure’s self-weight, eliminating the need for additional re-centering devices.

Design and investigation of novel gradient flow fields for proton exchange membrane fuel cell

Ensuring sufficient gas supply and high distribution uniformity are crucial issues in the flow field design to improve the performance and durability of proton exchange membrane fuel cell (PEMFC). However, previous studies often ignore the gas-water distribution variations along the flow direction and adopt identical design for the entire flow field, resulting in unsatisfactory performance. To fill in this gap, this paper innovatively proposes two types of gradient flow field (gradient narrowing and gradient droplet) considering the gas-water distribution characteristics. The channel of the gradient narrowing flow field gradually decreases in all directions along the flow direction, and the gradient droplet flow field is composed of staggered droplet blocks, and the distribution density gradually decreases along the flow direction. The Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method is used for the comprehensive evaluation of flow fields. The results demonstrate that the gradient flow field can significantly improve the performance and physical field distribution. The gradient narrowing flow field has the best performance, with 11.39 % improvement in peak power density, 77.96 % increment in average oxygen mass fraction, and 43.11 % improvement in oxygen uniformity compared to parallel flow field. Further, the key geometric parameters sensitivity analysis of gradient narrowing flow field is carried out. This study contributes to understanding the underlying mechanism of mass transfer properties in the novel gradient flow field, and exploring its potential for high-performance flow fields design.

A process knowledge-based hybrid method for univariate time series prediction with uncertain inputs in process industry

In process industry, accurate and efficient univariate time series prediction (TSP) of key process parameters is crucial for optimizing production processes. However, noisy data and varying working conditions introduce uncertainties that hinder the modeling process. Data-driven methods have been proposed to address input-uncertain TSP models, but they often fail to obtain sufficient and high-quality industrial data for model establishment in complex and dynamic production process. The paper presents a process knowledge-based hybrid method for univariate TSP that handles noisy inputs in different working conditions. Primarily, a knowledge-embedded deep kernel network (KE-DKN) model is proposed that approximates the outputs to the knowledge space in noisy industrial environment, by embedding instantiated process knowledge as soft constraints into the conventional DKN network. Further, a two-stage training schema is designed for KE-DKN to reduce the interference superposition on the predicted variable from random noisy data and operational interferences. Moreover, the pre-trained parameters transferring is conducted from stable working conditions to mitigate the low modeling efficiency in unstable working conditions. In two cases from process industry, the proposed method delivers higher prediction accuracy and robustness than baseline methods in both working conditions, and the knowledge transfer significantly enhances the modeling efficiency in unstable working conditions.

Disinfection by-products control in wastewater effluents treated with ozone and biological activated carbon followed by UV/Chlor(am)ine processes

Sequential utilization of ozone (O3) and biological activated carbon (BAC) followed by UV/chlor(am)ine advanced oxidation process (AOP) has drawn attention in water reuse. However, the formation of disinfection by-products (DBPs) in this process is less evaluated. This study investigated the DBP formation and the relevant toxicity during the O3-BAC-UV/chlor(am)ine treatment of sand-filtered municipal secondary effluent. DBP formation in UV/chlorine and UV/dichloramine (NHCl2) processes were compared, where the impact of key operational parameters (e.g., UV wavelength, pH) on DBP formation were comprehensively evaluated. O3-BAC significantly reduced DBP formation potential (DBPFP) (58.2 %). Compared to UV/chlorine AOP, UV/NHCl2 AOP reduced DBP formation by 29.7 % in short-time treatment, while insignificantly impacting on DBPFP (p > 0.05). UV/NHCl2 AOP also led to lower calculated cytotoxicity (67.7 %) and genotoxicity (55.9 %) of DBPs compared to UV/chlorine AOP. Compared to 254 nm UV light, the utilization of 285 nm UV light decreased the formation of DBPs in wastewater treated with the UV/chlorine AOP and UV/NHCl2 AOP by 31.3 % and 19.2 %, respectively. However, the cytotoxicity and genotoxicity in UV/NHCl2 AOP using 285 nm UV light increased by 83.4 % and 58.5 %, respectively, compared to 254 nm. The concentration of DBPs formed in the UV/NHCl2 AOP at pH 8 was 54.3 % lower than that at pH 7, suggesting a better control of DBPs at alkaline condition. In the presence of bromide, UV/NHCl2 AOP tended to generate more brominated DBPs than UV/chlorine AOP. Overall, UV/NHCl2 AOP resulted in lower concentration and toxicity of DBPs compared to UV/chlorine AOP.

Extraction Kinetics of Pyridine, Quinoline, and Indole from the Organic Phase with Natural Deep Eutectic Solvents and Separation Study Using a Centrifugal Extractor

In this study, the kinetics of extracting pyridine, quinoline, and indole from model fuels using natural deep eutectic solvents (NaDES) composed of carboxylic acids, xylitol, and water were investigated under static conditions. This research marks the first examination of extraction kinetics in this context. The key kinetic parameters of the extraction process were identified. Notably, it was observed that the mass transfer coefficient for indole was in the range of 3.4 × 10−6 to 1.2 × 10−6, depending on NaDES. That is significantly lower, by an order of magnitude, than for pyridine and quinoline under identical experimental conditions. The study revealed that, under specific conditions, where thermodynamic equilibrium for indole cannot be reached, it becomes possible to achieve kinetic separation of the components. The presented experimental data obtained on a centrifugal extractor showed a decrease in the degree of indole extraction with increasing flow: Extraction efficiency decreased from 63% at a flow rate of 0.05 L/h to 18% at 0.8 L/h. Moreover, the research indicated that, during indole extraction, the mass transfer coefficient in a centrifugal extractor was 1.3 × 10−4, which is two orders of magnitude higher than under static conditions. The study underscores the potential utility of the proposed extraction systems based on environmentally friendly NaDES, comprised of carboxylic acids and xylitol, for the kinetic separation of various classes of heterocyclic compounds. Overall, the research provides valuable insights into the kinetics of extraction and the potential applications of ‘green’ NaDES in the separation of heterocyclic compounds from organic liquids.

Research and Application of Carbon Capture, Utilization, and Storage–Enhanced Oil Recovery Reservoir Screening Criteria and Method for Continental Reservoirs in China

CCUS-EOR is a crucial technology for reducing carbon emissions and enhancing reservoir recovery. It enables the achievement of dual objectives: improving economic efficiency and protecting the environment. To explore a set of CCUS-EOR reservoir screening criteria suitable for continental reservoirs in China, this study investigated and compared the CCUS-EOR reservoir screening criteria outside and in China, sorted out the main reservoir parameters that affect CO2 flooding, and optimized the indices and scope of CCUS-EOR reservoir screening criteria in China. The weights of parameters with respect to their influences on CCUS-EOR were determined through principal component analysis. The results show that there are 14 key parameters affecting CO2 flooding, which can be categorized into four levels. For the first level, the crude oil-CO2 miscibility index holds the greatest weight of 0.479. It encompasses seven parameters: initial formation pressure, current formation pressure, temperature, depth, C2–C15 molar content, residual oil saturation, and minimum miscibility pressure. The second level consists of the crude oil mobility index, which has a weight of 0.249. This index includes four parameters: porosity, permeability, density, and viscosity. The third level pertains to the index of reservoir tectonic characteristics, with a weight of 0.141. It comprises two parameters: permeability variation coefficient and average effective thickness. Lastly, the fourth level focuses on the index of reservoir property change, with a weight of 0.131, which solely considers the pressure maintenance level. Based on the CCUS-EOR reservoir screening criteria and index weights established in this study, comprehensive scores for CCUS-EOR were calculated for six blocks in China. Among these, five blocks are deemed suitable for CCUS-EOR. Based on the comprehensive scoring results, a planning for field application of CCUS-EOR is proposed. The study provides a rational method to evaluate the CCUS-EOR reservoir screening and field application in continental reservoirs in China.

Calculation and Analysis of Key Parameters of Underwater Optical Imaging System.

When photographing objects underwater, it is important to utilize an optical window to isolate the imaging device from the water. The properties of the entire imaging system will change, and the imaging quality will decrease due to the refraction impact of the water and the window. The theoretical calculation method for air imaging is no longer relevant in this context. To analyze the unique rule, this research derives the formulas for key parameters of underwater imaging systems under paraxial circumstances. First, the optical window is modeled, then the formula for the optical window's focal length in the underwater environment is derived, and the change rule for the focal length of various window forms underwater is condensed. For the ideal imaging system using a domed optical window, the equivalent two-optical group model of the imaging system is established, and the formula for calculating the focal length, working distance, and depth of field of the underwater imaging system is derived through paraxial ray tracing. The accuracy of the formula is verified through the comparative analysis of the formula calculation results and the Zemax modeling simulation results. It provides an important theoretical basis for the in-depth study of underwater imaging technology.

Calibration for Space Solar Cells: Progress, Prospects, and Challenges

Space solar cells, have been providing a consistent supply of energy for various spacecraft for decades. Currently, the third‐generation solar cells, such as perovskite solar cells (PSCs) and organic solar cells, have demonstrated significant potential for space applications. However, their real performance in space environments is not yet clear. To assess crucial performance parameters, solar cells need to be calibrated under the standard space spectral irradiance before deployment in space. This is known as AM0 calibration. This review article focuses on the calibration techniques and methods for space solar cells. The topics covered include space environment and standard testing condition for solar cells, the measurements of key parameters for traditional solar cells, advancements in PSCs and organic solar cells for space applications, and a comprehensive review of diverse calibration methods. The discussion spans from near‐ground calibration to near‐space calibration and space calibration, encompassing approaches, key technologies, developmental milestones, and the respective merits of each calibration methods, especially focus on high altitude balloon calibration. Finally, the article addresses the challenges and future trends of space solar cell calibration based on the aforementioned discussions.

Improving the OWC Wave Energy Converter Power Take-Off Efficiency throughout Experimental and Numerical Characterisation of an SCIG

The increasing interest in the use of renewable energy technologies is directing attention towards the potential contribution of marine energy technologies, especially ocean wave energy, to world energy demand. While open-sea demonstrations of full-scale devices have been carried out to validate several technologies, the focus now is shifting to optimising the components for efficiency and reliability. The efficiency of the electrical generator plays a crucial role in wave-to-wire numerical models for converting wave energy into usable electricity. It provides essential data that enables the industry to reduce technical risks and uncertainties. Wave-to-wire models typically simplify the generator’s efficiency through assuming a single curve based on the load. This curve is usually provided by the machine manufacturers for the nominal rotational speed. However, the rotational speed varies in the case of air turbines used in OWC devices. Therefore, to accurately estimate decision variables derived from these models, a comprehensive efficiency map is necessary. This map should demonstrate the performance at different rotational speeds and loads, as it directly influences the estimation of key parameters. The main objective of the present work is to improve the generator behaviour of an OWC for different generator operation regimes. For this purpose, a numerical model of the generator’s efficiency will be developed throughout the segregation of losses and validated experimentally. Finally, an optimal control law will be presented to maximise the electrical power output of the wave energy converter, considering the efficiency of both the generator and the turbine.

Numerical studies of manipulation and separation of microparticles in ODEP-based microfluidic chips.

A novel optical-induced dielectrophoresis (ODEP) method employing a pressure-driven flow for the continuous separation of microparticles is presented in this study. By applying alternate current electric field on conductive indium tin oxide substrate and projecting the light geometry into the photoconductive layer, an inhomogeneous electric field is locally induced. The particles experience the dielectrophoretic force when passing through the lighting area, where the strongest electrical field gradient exists. By optimizing the structure of the lighting pattern, a stronger nonuniform electric field gradient is generated which predicts the separation of 1 and 3µm polystyrene particles. Moreover, the effects of key parameters, including the light pattern geometry, applied voltage, and flow rate, were investigated in this study, leading to the successful sorting of 700nm and 1µm particles. To further examine the separation sensitivity and practicability of the proposed ODEP microfluidic method, the isolation of two different types of circulating tumor cells from T-cells and red blood cells are demonstrated, providing a novel method for the manipulation and separation of microparticles and nanoparticles.

Addressing the long-standing limitations of double exponential and non-rectangular hyperbolic models in quantifying light-response of electron transport rates in different photosynthetic organisms under various conditions.

The models used to describe the light response of electron transport rate in photosynthesis play a crucial role in determining two key parameters i.e., the maximum electron transport rate (J max) and the saturation light intensity (I sat). However, not all models accurately fit J-I curves, and determine the values of J max and I sat. Here, three models, namely the double exponential (DE) model, the non-rectangular hyperbolic (NRH) model, and a mechanistic model developed by one of the coauthors (Z-P Ye) and his coworkers (referred to as the mechanistic model), were compared in terms of their ability to fit J-I curves and estimate J max and I sat. Here, we apply these three models to a series of previously collected Chl a fluorescence data from seven photosynthetic organisms, grown under different conditions. Our results show that the mechanistic model performed well in describing the J-I curves, regardless of whether photoinhibition/dynamic down-regulation of photosystem II (PSII) occurs. Moreover, both J max and I sat estimated by this model are in very good agreement with the measured data. On the contrary, although the DE model simulates quite well the J-I curve for the species studied, it significantly overestimates both the J max of Amaranthus hypochondriacus and the I sat of Microcystis aeruginosa grown under NH4 +-N supply. More importantly, the light intensity required to achieve the potential maximum of J (J s) estimated by this model exceeds the unexpected high value of 105 μmol photons m-2 s-1 for Triticum aestivum and A. hypochondriacus. The NRH model fails to characterize the J-I curves with dynamic down-regulation/photoinhibition for Abies alba, Oryza sativa and M. aeruginosa. In addition, this model also significantly overestimates the values of J max for T. aestivum at 21% O2 and A. hypochondriacus grown under normal condition, and significantly underestimates the values of J max for M. aeruginosa grown under NO3 -N supply. Our study provides evidence that the 'mechanistic model' is much more suitable than both the DE and NRH models in fitting the J-I curves and in estimating the photosynthetic parameters. This is a powerful tool for studying light harvesting properties and the dynamic down-regulation of PSII/photoinhibition.

Characterizing the 3-D structure of each building in the conterminous United States

The three-dimensional building structure is crucial for understanding human activities and environmental interactions. Previous studies have estimated building height on a grid-scale, lacking height estimation results concurrently over large areas and at fine resolution. Here we mapped the height of each building in the conterminous US in 2020, using integrated multi-source datasets (i.e., satellite observations and geometry features). Our proposed model for height estimation is proven reliable (i.e., The model's R2 is 0.82, and RMSE is 3.35 m in the conterminous US) and superior in cross-validation with other existing datasets at different scales. We found an explicit pattern of buildings decaying from the urban core to rural areas, which is more noticeable in big cities (e.g., New York). Furthermore, we proposed the seamless and explicit Urban Canopy Parameters (UCPs) datasets, including six UCPs (e.g., building area fraction and height -to-width ratio) based on our height dataset. As key parameters used in climate models, our UCPs improved the fine-grained description of 3-D urban structures compared with those traditionally used. Overall, our building-by-building height dataset and UCP datasets reveal the significant heterogeneity of urban underlying surface, which can help socioeconomic and climatological urban studies.

Fluid based sandwich panel core structure for blast load mitigation

Researchers have extensively explored various approaches to enhance the blast resistance of structures, concentrating on optimizing structural designs and employing a wide range of materials. This research investigates the impact of incorporating water as a fluid within the core of tubular sandwich panels on blast mitigation effectiveness. The study systematically analyzes various panel configurations by altering key design parameters: the thickness of the face sheets, spacing between the core elements, and proportion of fluid within the core. These variables are scrutinized through metrics such as elastic strain energy, the amount of work applied externally, and the movement of the panel. Utilizing finite element analysis, 27 distinct numerical experiments were conducted to gather data. The findings demonstrate that panels with a water-filled core exhibit superior blast resistance compared to their non-fluid counterparts. Specifically, panels with completely filled cores showed the lowest levels of panel displacement and external work, whereas those with half-filled cores recorded the highest elastic strain energy. Furthermore, regression analysis revealed that plate thickness predominantly influences panel displacement and external work, whereas the fluid volume fraction within the core most significantly affects elastic strain energy. This study contributes to the understanding of fluid-structure interactions in blast-resistant design, offering valuable insights for optimizing structural defenses against blast impacts.

The Lagrangian Atmospheric Radionuclide Transport Model (ARTM) – sensitivity studies and evaluation using airborne measurements of power plant emissions

Abstract. The Atmospheric Radionuclide Transport Model (ARTM) operates at the meso-γ scale and simulates the dispersion of radionuclides originating from nuclear facilities under routine operation within the planetary boundary layer. This study presents the extension and validation of this Lagrangian particle dispersion model and consists of three parts: (i) a sensitivity study that aims to assess the impact of key input parameters on the simulation results, (ii) the evaluation of the mixing properties of five different turbulence models using the well-mixed criterion, and (iii) a comparison of model results to airborne observations of carbon dioxide (CO2) emissions from a power plant and the evaluation of related uncertainties. In the sensitivity study, we analyse the effects of the stability class, roughness length, zero-plane displacement factor, and source height on the three-dimensional plume extent as well as the distance between the source and maximum concentration at the ground. The results show that the stability class is the most sensitive input parameter as expected. The five turbulence models are the default turbulence models of ARTM 2.8.0 and ARTM 3.0.0, one alternative built-in turbulence model of ARTM, and two further turbulence models implemented for this study. The well-mixed condition tests showed that all five turbulence models are able to preserve an initially well-mixed atmospheric boundary layer reasonably well. The models deviate only 6 % from the expected uniform concentration below 80 % of the mixing layer height, except for the default turbulence model of ARTM 3.0.0 with deviations of up to 18 %. CO2 observations along a flight path in the vicinity of the lignite power plant Bełchatów, Poland, measured by the Deutsches Zentrum für Luft- und Raumfahrt (DLR) Cessna aircraft during the Carbon Dioxide and Methane Mission (CoMet) campaign in 2018 allowed for evaluation of model performance for the different turbulence models under unstable boundary layer conditions. All simulated mixing ratios are of the same order of magnitude as the airborne in situ data. An extensive uncertainty analysis using probability distribution functions, statistical tests, and direct spatio-temporal comparisons of measurements and model results help to quantify the model uncertainties. With the default turbulence setups of ARTM versions 2.8.0 and 3.0.0, the plume widths are underestimated by up to 50 %, resulting in a strong overestimation of the maximum plume CO2 mixing ratios. The comparison of the three alternative turbulence models shows good agreement of the peak plume CO2 concentrations, the CO2 distribution within the plumes, and the plume width, with a 30 % deviation in the peak CO2 concentration and a less than 25 % deviation in the measured CO2 plume width. Uncertainties in the simulations may arise from the different spatial and temporal resolutions of simulations and measurements in addition to the turbulence parametrisation and boundary conditions. The results of this work may help to improve the accurate representation of real plumes in very unstable atmospheric conditions through the selection of distinct turbulence models. Further comparisons at different stability regimes are required for a final assessment of model uncertainties.

Performance of off-season Okra under Protected Structures in Semi-Arid Region

Okra is a staple vegetable in Indian cuisine which is extensively cultivated year-round due to its rich composition of essential minerals, vitamins, carbohydrates, proteins and dietary fiber. The primary objective of this research was to investigate the impact of mulching and protective structures on okra cultivation during the winter period (off-season). Consequently, okra seeds were planted in three distinct environments: a Net-cum-poly house equipped with a ridge vent, Net-cum-poly house lacking a ridge vent and an open field. These environments were combined with three different mulch conditions: silver-black plastic mulch, black plastic mulch, and no-mulch. The experiment employed a two-factor large-plot design with four replications. The findings of this study revealed the substantial influence of mulching and protective structures on off-season okra cultivation. Key agronomic parameters, including stem diameter (17.20 mm), plant height (164 cm), internode length (18 cm), the number of fruits per plant (35), fruit weight per plant (367.31gm) and overall fruit yield (19755 kg/ha) exhibited statistically significant improvements in the combination of a Net-cum-poly house without a ridge vent and silver-black plastic mulch. In terms of water management, irrigation volumes delivered under mulched and non-mulched conditions were 387 mm and 446 mm respectively for the open field, while the corresponding figures for the protected environment were 319 mm and 366 mm. The highest water use efficiency was observed 61.97 kg/ha-mm in treatment combination with silver black plastic mulch and Net-cum-poly house without ridge vent. Notably, mulching resulted in a 13.34% reduction in water consumption compared to the non-mulched open field. In the protected environment, water savings reached 28.43% under mulch and 17.76% under no-mulch conditions relative to the non-mulched open field.

Microcapsules of mesoporous silica and cyclodextrin modified loaded with nonanal and decanal for effective control of Sitotroga cerealella in grain storage environments.

The Angoumois grain moth, Sitotroga cerealella, is a destructive pest of maize, wheat, and rice, causing economic losses and threatening food security. This study aimed to develop and characterize microcapsules of mesoporous silica nanospheres (MSN) and cyclodextrin-modified mesoporous silica nanospheres (CDMSN) containing two aldehydes, nonanal and decanal, found in plant essential oils, to assess their attractiveness to S. cerealella populations. Microcapsules with 2:1 ratio of nonanal and decanal exhibited an average encapsulation efficiency of 39.82% for MSN loaded with nonanal and decanal (MSN-ND) and 46.10% for CDMSN loaded with nonanal and decanal (CDMSN-ND). They have an elliptical shape with particle sizes of 115 nm for MSN and 175 nm for CDMSN. Gas chromatography-mass spectrometry analysis revealed in vitro release of nonanal in MSN at 96.24% and decanal at 96.42% by the 36th day. CDMSN showed releases of 93.83% for nonanal and 93.74% for decanal by the 50th day. CDMSN-ND attracted adult S. cerealella for 43 days, while MSN-ND remained effective for 29 days. In mass trapping assays in simulated grain warehouse, both MSN-ND and CDMSN-ND trapped over 50% of the adult population within 7 days, significantly reducing grain infestation rates below 10% by inhibiting F1 adult emergence. At temperatures ranging from 20 °C to 35 °C, both microcapsules exhibited significant and effective attraction rates for S. cerealella. Stored wheat seeds treated with CDMSN and CDMSN-ND over 1 year showed no significant differences in key germination parameters. Microencapsulated nonanal and decanal offer a promising, sustainable approach for controlling S. cerealella infestation in stored grains, contributing to global food security. © 2024 Society of Chemical Industry.