Saturation Factor Research Articles

Application of the Analytic Network Process for Sub-Watershed Prioritization in the Huehuetan River Basin, Chiapas, Mexico

Sub-watershed prioritization is essential for developing watershed management plans that maximize impact with minimal resources. This study used a multicriteria decision-making approach to rank sub-watersheds by degradation status in the Huehuetan River Basin, Chiapas, Mexico. The eight sub-watersheds in the basin were classified using the Analytic Network Process (ANP) model, evaluating morphometry, hydrology, hillslope stability, soil water saturation, land-use change, and socioeconomic factors. The results identified hydrology and land-use change as the most influential criteria, with weights of 20.62% and 19.82%, respectively, driven mainly by surface runoff and deforestation. Swtr 08 and Swtr 07 were identified as the highest-priority sub-watersheds, covering 24.31% of the basin area, with 55.31% of Swtr 08 classified as unstable and showing a combined high-vegetation loss of 16.46 km2. The entire watershed showed an annual vegetation loss rate of 146 ha year−1. Increasing the weighting by 50% resulted in greater variability in priority rankings, with runoff and low vegetation showing maximum global ranges of −44.33% and 30.25%, respectively, instability decreasing by 33.94%, and peak flow increasing by 18.20%. These findings emphasize the need for focused interventions in the vulnerable subwatersheds of the upper basin to manage runoff, curb deforestation, and reduce soil instability.

Robust Adaptive Control System of Variable Sampling Period for Cement Raw Mix Quality Control

The advanced quality control of the raw mix remains a priority for the cement industry, particularly in recent years, where large quantities of alternative fuels and raw materials are used in clinker production, aiming to reduce the CO2 footprint. This study presents an adaptive control system with a variable sampling period for regulating raw mix quality in the raw mill (RM) output in a process with four independent inputs and four outputs: the lime saturation factor (LSF), silica modulus (SM), alumina modulus (AM), and SO3. The three pillars of the system are (1) mill dynamics calculation using exclusively industrial data, (2) the design of the controllers to meet robustness criteria, and (3) performance enhancement through simulators. Our technique periodically adjusts the gains of the controllers based on the mill’s dynamic parameters, which are computed from raw mix laboratory analyses. The presented results correspond to more than 14,000 h of mill operation. The standard deviation of the LSF at the mill outlet ranged from 1.5 to 3, which is equivalent to 1 to 2 standard deviations of LSF reproducibility. The standard deviation of the other moduli was close to the corresponding reproducibility of each. The presented adaptive gain-scheduling controller for LSF can be applicable to a broad range of raw meal grinding systems.

Formation of build-up in a cement kiln preheater: qualitative and quantitative mineral characterisation

Extracting more information about the reactions and parameters governing the formation of build-up in the preheater systems of clinker burning lines could be an efficient way of better attenuating build-up formation. In order to control the appearance of build-up, diagnosis steps of mineralogical analysis application for process optimisation (MAA-PO) are suggested. Mineralogical characterisation was carried out on three samples taken from different layers of the same build-up. Qualitative and quantitative X-ray diffraction, chemical analysis and Fourier transform infrared spectroscopy revealed that ternesite is the key mineralogical phase responsible for the growth and consolidation of build-up. Its appearance is governed by solid–solid reactions promoted by the available sulfate liquid phases, mainly calciolangbeinite, as well as C12A7 and C4AF. The hot-powder calcination degree, amount of sulfur trioxide, lime saturation factor, silica ratio and alumina ratio are the operational data that were correlated to the mineralogical analysis of build-up. Based on this correlation, it is possible to predict the reaction kinetics involved in each layer formation and to estimate the development time of each. The results showed that MAA-OP is a promising novel approach to optimise the process parameters in clinker production.

Bayesian linearized inversion for petrophysical and pore-connectivity parameters with seismic elastic data of carbonate reservoirs

Abstract Carbonate reservoirs are important targets for promoting the oil and gas reserve exploration and production in China. However, such reservoirs usually contain the developed complex pore structures, which heavily affect the precision in seismic prediction of petrophysical parameters. As one of the most important parameters to characterize reservoir rock, pore-related parameters can not only describe the pore structure, but also be used to evaluate the oil/gas bearing capabilities of potential reservoirs. The conventional rock-physics models (e.g. Gassmann's model) are formulated assuming fully-connected pores, which is unable to accurately capture the geometrical complexity in real rocks. In order to characterize the influences of multiple pores on the elastic properties, this work presents a rock-physics modelling method for carbonates, wherein the percentage composition of connected pores is equivalently quantified as the pore-connectivity factor. The method treats the pore-connectivity factor as an objective variable to characterize the spatial variations of pore structure. Specifically, the method combines the differential equivalent medium theory and Gassmann's model, and derives a linearized forward operator to quantitatively link porosity, water saturation, and pore-connectivity factor to seismic elastic parameters. According to the Bayesian linear inverse theory, the simultaneous estimation of petrophysical and pore-connectivity parameters is achieved. To characterize the statistical variations with multiple lithofacies, the Gaussian mixture model is employed to quantify the prior distribution of the objective variables. The posterior distribution of the objective variables is analytically expressed with the linearized forward operator. Numerical experiments show that the accuracy of the proposed method in predicting elastic parameters is improved. Compared with the conventional Xu-White model and the varying pore aspect ratio method, the accuracy of predicted P-wave velocity increases by 10.29% and 1.33%, respectively, and the predicted S-wave velocity increases by 6.44% and 0.03%, in terms of correlation coefficient. The application to the field data validates the effectiveness of the method, wherein the porosity and water saturation results help indicating the spatial distribution of potential reservoirs.

Improved MTPA and MTPV Optimal Criteria Analysis Based on IPMSM Nonlinear Flux-Linkage Model

The use of interior permanent-magnet synchronous machines (IPMSMs) is prevalent in automotive and vehicle traction applications due to their high efficiency over a wide speed range. Given the high-power-density requirements of automotive IPMSMs, it is imperative to consider the effect of nonlinearities, such as saturation and cross-coupling, on the motor model. The aforementioned nonlinearities render conventional linear motor models incapable of accurately describing the operating characteristics of the IPMSM, including the maximum torque per ampere (MTPA) trajectory, the flux-weakening (FW) trajectory, and the maximum torque per volt (MTPV) trajectory. With respect to the linear motor model, the nonlinear flux-linkage model is gradually receiving attention from researchers. This modeling method represents the nonlinear behavior of the motor through the direct establishment of a bidirectional mapping relationship between flux-linkage and current. It is capable of naturally incorporating the effects of magnetic saturation and cross-coupling factors. However, the analysis of the current trajectory optimal criteria based on this model has not yet been reported. In this paper, the optimal criteria for the MTPA and MTPV current trajectories are analyzed based on the nonlinear flux-linkage model of IPMSMs. Firstly, the nonlinear flux-linkage model of the tested IPMSM is established by the experimental calibration method. The mathematical analytical expressions of the MTPA and MTPV optimal criteria are then analyzed by constructing and solving optimal problems with different objectives. Finally, the current command table applicable to actual motor control is constructed by calculating the current command for different operating conditions according to the optimal criteria proposed in this paper. The validity and feasibility of the optimal criteria proposed in this paper are verified through experimental tests on different operating conditions.

Benchmarking PathCLIP for Pathology Image Analysis.

Accurate image classification and retrieval are of importance for clinical diagnosis and treatment decision-making. The recent contrastive language-image pre-training (CLIP) model has shown remarkable proficiency in understanding natural images. Drawing inspiration from CLIP, pathology-dedicated CLIP (PathCLIP) has been developed, utilizing over 200,000 image and text pairs in training. While the performance the PathCLIP is impressive, its robustness under a wide range of image corruptions remains unknown. Therefore, we conduct an extensive evaluation to analyze the performance of PathCLIP on various corrupted images from the datasets of osteosarcoma and WSSS4LUAD. In our experiments, we introduce eleven corruption types including brightness, contrast, defocus, resolution, saturation, hue, markup, deformation, incompleteness, rotation, and flipping at various settings. Through experiments, we find that PathCLIP surpasses OpenAI-CLIP and the pathology language-image pre-training (PLIP) model in zero-shot classification. It is relatively robust to image corruptions including contrast, saturation, incompleteness, and orientation factors. Among the eleven corruptions, hue, markup, deformation, defocus, and resolution can cause relatively severe performance fluctuation of the PathCLIP. This indicates that ensuring the quality of images is crucial before conducting a clinical test. Additionally, we assess the robustness of PathCLIP in the task of image-to-image retrieval, revealing that PathCLIP performs less effectively than PLIP on osteosarcoma but performs better on WSSS4LUAD under diverse corruptions. Overall, PathCLIP presents impressive zero-shot classification and retrieval performance for pathology images, but appropriate care needs to be taken when using it.

Stability and stabilization for the hydraulic automatic gauge control system of cold rolling mill with time delay and saturation

This paper studies the stability and stabilization of hydraulic automatic gauge control (HAGC) systems with time-varying delay and actuator saturation. First, a mathematical model of HAGC systems is established considering the measurement delay and saturation factors. With the help of state transformation, the measurement delay is transformed into input delay and the generalized sector condition is adopted to deal with the saturation problem in HAGC systems. Then, a new augmented L–K functional is constructed to contain more delay information to reduce the conservativeness of the stability criteria. Furthermore, by combining the proposed L–K functional with some advanced inequalities, the stability conditions and controller are derived with the aid of linear matrix inequalities (LMIs). Finally, the effectiveness of the proposed control algorithm is verified by simulation results.

Impact of Lime Saturation Factor on Alite-Ye'Elimite Cement Synthesis and Hydration.

Alite(C3S)-Ye'elimite(C4A3$) cement is a high cementitious material that incorporates a precise proportion of ye'elimite into the ordinary Portland cement. The synthesis and hydration behavior of Alite-Ye'elimite clinker with different lime saturation factors were investigated. The clinkers were synthesized using a secondary thermal treatment process, and their compositions were characterized. The hydrated pastes were analyzed for their hydration products, pore structure, mechanical strength, and microstructure. The clinkers and hydration products were characterized using XRD, TG-DSC, SEM, and MIP analysis. The results showed that the Alite-Ye'elimite cement clinker with a lime saturation factor (KH) of 0.93, prepared through secondary heat treatment, contained 64.88% C3S and 2.06% C4A3$. At this composition, the Alite-Ye'elimite cement clinker demonstrated the highest 28-day strength. The addition of SO3 to the clinkers decreased the content of tricalcium aluminate (C3A) and the ratio of Alite/Belite (C3S/C2S), resulting in a preference for belite formation. The pore structure of the hydrated pastes was also investigated, revealing a distribution of pore sizes ranging from 0.01 to 10 μm, with two peaks on each differential distribution curve corresponding to micron and sub-micron pores. The pore volume decreased from 0.22 ± 0.03 to 0.15 ± 0.18 cm3 g-1, and the main peak of pore distribution shifted towards smaller sizes with increasing hydration time.

Nonlinear disturbance observer-based finite-time prescribed performance control for MSVs with input saturation

ABSTRACT A finite-time prescribed performance control scheme based on an improved nonlinear disturbance observer is proposed for tracking the trajectory of marine surface vessels (MSVs) under the disturbance of the marine environment. The objective of this paper is to design a nonlinear disturbance observer based on state estimation error feedback that accurately estimates and compensates for the unknown disturbance problem. An adaptive law is applied to estimate the upper bound of its error, removing the requirement of a priori knowledge of the unknown lumped disturbance upper bound. This paper also introduces a non-logarithmic performance function in order to efficiently solve the problem of considering both transient and steady state MSVs performance simultaneously. In addition, the adaptive dynamic system is introduced to overcome the adverse effects caused by nonlinear saturation factors for the input-constrained problem. With this control strategy, the system output error converges to a pre-defined region within a finite amount of time and meets the prescribed performance requirements. Finally, simulation and comparison verify the control scheme's effectiveness and superiority.

Fuzzy Neural Network Model for Intelligent Course Development in Music and Dance Education

Interactions are mandatory for online or offline music and dance education to improve understandability and learning efficacy. The course designed for such artistic education incorporates multi-point interactions and monotonous presentations. The validation of the key factor: interactivity is thus mandatory for enhancing efficiency. This article introduces an interactivity validation method (IVM) using combined fuzzy neural network (FNN) to aid artistic course development. The output of the existing course and its evaluation criteria are considered in enhancing its grade. The fuzzy performs interaction classification as mandatory and trivial based on the student’s performance. The neural network identifies the chances for maximum performance by increasing or decreasing the interaction rate. If a saturated performance is achieved at a high or low interactivity, then the further course design is performed based on the saturated interactivity factor. The failing factors are used for training the neural network for modifying the interactivity rate from the current course development suggestion. Such a process is keen on classifying and validating the impact of interactivity over artistic course design.

Distributions, sea-to-air fluxes, and biological consumption of carbon monoxide in the Bohai and Yellow Seas during winter

Carbon monoxide (CO) concentrations in the atmosphere and ocean are mainly influenced by anthropogenic inputs, abiotic photoproduction, biogenic sources, and bacterial consumption. This study, for the first time, investigated the distributions, sea-to-air fluxes, and microbial consumption rates of CO in the Bohai Sea (BS) and the Yellow Sea (YS) in winter to identify the main factors controlling CO distributions in both the atmosphere and seawater in colder temperature. Atmospheric CO mixing ratios ([CO]atm) and the concentrations of CO in surface seawater ([CO]surf) ranged from 176.8 to 1245.8 ppbv (mean value: 551.4 ± 214 ppbv) and from 0.49 to 3.1 nmol L−1 (mean value: 0.98 ± 0.55 nmol L−1), respectively. In addition, the spatial distribution of [CO]atm and [CO]surf showed that anthropogenic sources dominated the distribution of [CO]atm, but abiotic photoproduction processes were the main influencers of the distribution of [CO]surf. The surface water at most sampling stations was supersaturated with CO, with a mean saturation factor of 1.9, and the sea-to-air fluxes of CO were estimated to range from −13.88 to 123.88 nmol m−2 h−1 (12.59 ± 21.32 nmol m−2 h−1), suggesting that the BS and the YS were the source of atmospheric CO, and were estimated to contribute 0.009% to 1.4% to the global ocean emission. Microbial consumption experiments indicated that the microbial CO consumption rate constants (Kbio) ranged from 0.15 to 2.14 h−1, and showed that CO concentrations decreased exponentially with incubation time, suggesting that anaerobic CO consumption would limit CO accumulation in winter, thereby affecting the flux of [CO]surf to [CO]atm.

Using Response Surface Methodology Approach to Modeling and Optimization of the Combustion Process in Cement Kiln

AbstractIn this study, this process has been modeled and optimized using the design of experiment technique and response surface methodology (RSM). The RSM was employed to optimize the combustion process in the cement kiln. Kiln feed (X1 = 160–190 t h−1), fan speed (X2 = 840–870 rpm), kiln rotational speed (X3 = 2.8–3.4 rpm), kiln fuel rate (X4 = 3800–4150 L h−1), calciner fuel rate (X5 = 5700–6200 L h−1), pressure of kiln inlet (X6 = 98–102 Pa), and limestone saturation factor (LSF) (X7 = 94–95.8 %) as independent variables were investigated. The carbon monoxide and the kiln body temperature in RSM were considered as response variables. The absolute average error in the model predictions for the combustion process in the cement kiln, for the kiln body's temperature, is about 1.6 % and for carbon monoxide is about 15.5 %.

Fixed-time trajectory tracking for autonomous surface vehicles via output feedback under various constraints

This paper proposes a novel fixed-time output feedback trajectory tracking control method suitable for autonomous surface vehicles (ASVs). Firstly, various complex uncertainty terms, such as unknown external disturbances, unmodeled errors, and actuator faults are considered in this paper. And these terms are uniformly converted into the total uncertainty terms through model transformation for convenience. Then, a fixed-time extended state observer (FTESO) with the newly expanded state is designed to observe and estimate the total uncertainty terms. Next, the saturation dynamic filter (SDF) is adopted to address the input saturation, and the saturation factors of SDF are incorporated into the trajectory error calculation to reduce the torque mutation caused by an excessive error in the control input. Finally, a fixed-time control law is proposed by taking into account the ASV system error and FTESO estimation state. Simulation experiments show that this method has excellent control performance, and this conclusion is validated through stability proof and case comparison.

Petrography and Geochemistry of Limestone Upper Cretaceous Kometan Formation (Azmir Anticline): A Preliminary Assessment for Cement Production Suitability in the Kurdistan Region Northeast Iraq

A succession of slightly siliceous limestone of the Kometan Formation is studied geochemically and strati graphically. The studied area is located on the SW limb of the Azmir anticline at the northeastern of Sulaimaniyah city. The studied section is situated at longitudes 45°38'310"E and latitudes 35°36'129''N inside the Folded Zone, Kurdistan Region, northeastern Iraq. The exposed section is sampled for lab studies, and inspected by eyes and hand lenses in the field. In this study, petrographic and geochemical analyses of 17 limestone samples were carried out. This study aims to investigate the major oxides of the limestone samples, using the X-Ray Fluorescence (XRF), for preliminary assessment for possible cement production. A petrographic study was also carried out, in order. Depending on the petrographic study, three major microfacies were recognized: lime mudstone microfacies, lime wackestone microfacies, and lime packstone microfacies, which subdivided into four submicrofacies are planktonic foraminifera lime mudstone submicrofacies, planktonic foraminifera lime wackestone submicrofacies, and planktonic foraminifera lime packstone submicrofacies and heterohelix lime packstone submicrofacies. The geochemical analysis shows that a range of variations in constituents: LOI (35.90% to 42,72%), SiO2 (3.77% to 14.66%), CaO (42.59% to 49.95%), Al2O3 (0.44% to 2.22%), Fe2O3 (0.02% to 0.78%) and MgO (1.50% to 2.26%); K2O and Na2O are present in traces. The high CaO (49.95%) indicates that calcite is the primary carbonate mineral. Due to mineralogical considerations, CaO with LOI shows a positive correlation, whereas CaO with SiO2 shows a negative correlation. The low MgO contents in calcitic limestone and calcitic limestone with chert nodules recommend a lack of dolomitization process. The silica modulus and lime saturation factor from geochemical data indicated that the siliceous limestone samples from the Kometan Formation and Azmir Anticline can be used in the cement-making process provided they are processed for silica removal treatment to reduce its percentage to less than 8%, as required level, where the CaO can be automatically enriched. Depending on field observation, petrography, and geochemistry analysis, we conclude that the source of the chert or silica minerals is diagenetic processes and depositional environment origin.

Efficacy of Melatonin as an Adjunctive Therapy in Hospitalized Patients with Mild to Moderate COVID-19: A Randomized, Double-blind Clinical Trial

Background: Melatonin has proven antioxidant and anti-inflammatory properties that may address the pathophysiology of coronavirus disease 2019 (COVID-19). Therefore, the current study was conducted to evaluate the safety and efficacy of melatonin in COVID-19. Methods: In this single-center, randomized, double-blind, placebo-controlled clinical trial, 96 adults hospitalized with mild to moderate COVID-19 were recruited. The participants were allocated into the melatonin and the placebo groups, randomly (1:1 ratio). Results: The primary outcomes were a reduction in the length of hospital stay, the rate of ICU admissions, intubation/mechanical ventilation, and mortalities within 14 days of starting the treatment compared to the placebo group. After two weeks of follow-up, the blood oxygen saturation and the respiratory rate significantly improved in the melatonin group. C-reactive protein, erythrocyte sedimentation rate, lactate dehydrogenase, creatine phosphokinase, Ferritin, and D-dimer levels were significantly decreased in the melatonin group. Conversely, these markers were considerably increased in the placebo group. These serum marker levels also showed a significant difference in between- group comparison. The comparison of clinical endpoints between the two groups showed no significant difference. Conclusion: This clinical trial study indicated that the combination of oral melatonin tablets and standard treatment could substantially improve blood oxygen saturation and inflammatory factors in mild to moderate hospitalized COVID-19 patients.

Exploring the Impact of Petrophysical Uncertainties on Recoverable Reserves: A Case Study

Reliable estimation of critical parameters such as hydrocarbon pore volume, water saturation, and recovery factor are essential for accurate reserve assessment. The inherent uncertainties associated with these parameters encompass a reasonable range of estimated recoverable volumes for single accumulations or projects. Incorporating this uncertainty range allows for a comprehensive understanding of potential outcomes and associated risks. In this study, we focus on the oil field located in the northern part of Iraq and employ a Monte Carlo based petrophysical uncertainty modeling approach. This method systematically considers various sources of error and utilizes effective interpretation techniques. Leveraging the current state of available data, our approach generates a wide range of theoretically possible results. Furthermore, establishing a set of probabilities to indicate the likelihood of each possible outcome is of utmost importance. By implementing this approach, we aim to enhance reserve assessments by accounting for petrophysical uncertainties, thereby providing decision makers with valuable insights into the range of possible outcomes and associated risks. This study contributes to a more robust understanding of recoverable reserves and supports informed decision making in the oil and gas industry.

Automated processing of well logging data to monitor the position of the gas-water contact in underground gas storage facilities

Natural oil and gas deposits in most fields include some fluid contacts, such as oil–water, gas–water, or gas–oil. Monitoring the position of the gas–water contact in underground gas storage (UGS) facilities is crucial for monitoring the safety of the subsurface environment. As UGS facilities are geological features of long-term operation, the condition of these features must be regularly monitored for possible gas leaks due to various reasons, whether geological or technical. Periodic surveys of production wells using geophysical methods make it possible to timely detect the reasons for abnormal technical conditions and higher-than-normal water cuts of reservoirs, and to assess shifts in gas–water contact. The suite of production logging methods for surveying and monitoring underground gas storage facilities includes nuclear logging with the use of steady radiation sources (i.e., gamma ray logging and neutron logging). Analysis and interpretation of these methods make it possible to track the shift over time of the gas–water contact in gas-saturated sandstones with an interparticle porosity of >15%. Data from nuclear logging, temperature logs, and composition-based and flow-based surveying are processed and interpreted with the use of known methods and diagnostic indicators to achieve the following goals: to determine the intervals of inter-reservoir and behind-the-casing fluid movement on the base of the well log, to assess the technical condition of the wellbore, to monitor the position of the gas–water contact in the reservoir, to assess the gas saturation of the reservoir, and to monitor the thickness and integrity of the clay caprocks of UGS facilities [1]. This paper discusses the results of automated processing and interpretation of well data recorded during the survey of an UGS facility to determine the current position of the gas–water contact in the reservoir and the gas–water interface in the well. Quantitative interpretation of the neutron logging data with the use of steady radiation sources was performed, and the current gas saturation factor was estimated. Keywords: gas–water contact (GWC); gas saturation; underground gas storage; processing algorithm; gas–water interface (GWI).

Simulation of Rock-Water Interaction in the Southwestern Part of El Minya Governorate of Egypt

Abstract Twenty-one groundwater samples were picked up from the southwest of El Minya Governorate, Egypt. These samples’ physicochemical characteristics were analyzed. Using a water quality index software (WQI) and the United States Salinity Laboratory (USSL) staff chart, water samples were assessed for drinking and irrigation applications. The interaction between water and rock was assessed using the saturation index (SI), chloro-alkaline indices (CAI), Gibbs ratios (GC and GA), end-member diagram (END), corrosion ratio (CR), factor analysis, and dendrogram. Datasets elucidated that water samples were distinguished by SO42-, Na+, and Cl- dominance, excessive mineralization, hardness, and fresh to slightly saline water. The examined water is divided into two types: SO4. Ca-Cl. Mg (30%) and SO4. Na-Cl (70%). All samples were over-saturated with anhydrite, aragonite, calcite, dolomite, and gypsum minerals except for halite and sylvite minerals dissolution, according to SI. The existence of reversible ion exchange between alkaline earth’s (Ca2++Mg2+) ions in water and alkalis’ ions (Na++ K+) in solids; this is explained by the negative values of the chloro-alkaline indices, which point to recharging from rainfall. The Gibbs diagram showed that the dominant interaction is rock weathering. The silicate weathering and evaporite mineral dissolution control the water composition and salinity, which led to an excess of the dominant ions, as demonstrated by the END. Three wells in the research area are potentially unhealthy and unfit for irrigation and drinking.

Toward smart and sustainable cement manufacturing process: Analysis and optimization of cement clinker quality using thermodynamic and data-informed approaches

Cement manufacturing is widely recognized for its harmful impacts on the natural environment. In recent years, efforts have been made to improve the sustainability of cement manufacturing through the use of renewable energy, the capture of CO2 emissions, and partial replacement of cement with supplementary cementitious materials. To further enhance sustainability, optimizing the cement manufacturing process is essential. This can be achieved through the prediction and optimization of clinker phases in relation to chemical compositions of raw materials and manufacturing conditions. Cement clinkers are produced by heating raw materials in kilns, where both raw material compositions and processing conditions dictate the final chemical makeup of the clinkers. This study uses thermodynamic simulations to analyze phase assemblages of alite- and belite-enriched clinkers based on chemical compositions of raw materials and to create a database. The thermodynamic simulations can accurately reproduce clinker phases in comparison with experimental results. Subsequently, the simulated database is employed to train a data-informed model, and the predictions are used to determine the optimal composition domains that produce high quality clinker (C3S>50 %) at different calcination temperatures. Additionally, optimal lime saturation factor and alumina modulus are investigated to achieve target clinker phases. Overall, this study demonstrates the potential of using a data-informed approach to achieve smart and sustainable cement manufacturing process.

Evaluation of the new modified apnea test in confirmation of brain death.

Apnea testing is mandatory to confirm brain death; however, it is unsafe for patients who have substantial hypoxemia without ventilator support. We used a new modified apnea test without the need to disconnect the patient from the ventilator in the present study and compared the outcomes and complications of the new method to the widely used old method. The current study was conducted on people suspected of having brain death. Both the old and new apnea tests were carried out on the same individual. In the new modified method, instead of hyperventilating and then separating the brain death from the ventilator, the induced hypercapnia method was used, and instead of performing repeated arterial blood gas (ABG), the target ETCO2 was obtained, and at the time of the target ETCO2, ABG was also checked followed by comparing ETCO2 with PaCO2. Thirty patients, including 25 (83.3%) males and 5 (16.75%) females, were included in the study. The results showed significant improvement in terms of O2 saturation and heart rate (HR) using the new modified apnea test compared to the common test. Systolic blood pressure, diastolic blood pressure, and the frequency of complications were improved in the new modified test. The modified apnea test produced better results in terms of O2 saturation, HR, and other clinical factors, while it does not require disconnection from the ventilator and repeated ABG assessment. Therefore, it can be used to successfully diagnose brain death in high-risk individuals suffering from severe hypoxia.