Mixing Rate Research Articles

Assessment of Ablation Rates with Artificial Urinary Stones Appropriate for Simulation Training.

Introduction: Artificial urinary calculi are an essential tool for research and training in endourology. The goal of the study was to evaluate different types of artificial stones and how they behave to laser treatment, to finally determine which is the optimal one for training purposes. Materials and Methods: The stones were produced with a mix of Bego Stone powder and water, at mixing rates of 15:03, 15:04, and 15:06. They were evaluated in an in vitro experimental setting using the Quanta Cyber 150 W high-power laser lithotripter. Dusting was set to 0.5 J × 20 Hz = 10 W and fragmentation was set to 0.8 J × 8 Hz = 6.4 W. Stone weights were assessed in dry and wet conditions. Results: The ablation rates in the dusting modality were similar for the three stone types tested. In the fragmentation mode, the mean ablation rate for 15:04 artificial stones was greater than those of 15:03 and 15:06 stones. Overall, the mean weight difference between the wet and dry stones was 0.03 g. Consequently, within the stone types tested, 15:04 artificial are probably the most convenient ones for training purposes because they get disintegrated similarly to 15:03 and 15:06 Bego Stones on a dusting setting, and ablation is faster on a fragmentation setting. Conclusions: The 15:04 Bego Stones may be considered as the optimal option for use in simulation training models of the endourological education programs.

Analysis of Entropy Generation for Mass and Thermal Mixing Behaviors in Non-Newtonian Nano-Fluids of a Crossing Micromixer.

This work's objective is to investigate the laminar steady flow characteristics of non-Newtonian nano-fluids in a developed chaotic microdevice known as a two-layer crossing channels micromixer (TLCCM). The continuity equation, the 3D momentum equations, and the species transport equations have been solved numerically at low Reynolds numbers with the commercial CFD software Fluent. A procedure has been verified for non-Newtonian flow in studied geometry that is continuously heated. Secondary flows and thermal mixing performance with two distinct intake temperatures of nano-shear thinning fluids is involved. For an extensive range of Reynolds numbers (0.1 to 25), the impact of fluid characteristics and various concentrations of Al2O3 nanoparticles on thermal mixing capabilities and pressure drop were investigated. The simulation for performance enhancement was run using a power-law index (n) at intervals of different nanoparticle concentrations (0.5 to 5%). At high nano-fluid concentrations, our research findings indicate that hydrodynamic and thermal performances are considerably improved for all Reynolds numbers because of the strong chaotic flow. The mass fraction visualization shows that the suggested design has a fast thermal mixing rate that approaches 0.99%. As a consequence of the thermal and hydrodynamic processes, under the effect of chaotic advection, the creation of entropy governs the second law of thermodynamics. Thus, with the least amount of friction and thermal irreversibilities compared to other studied geometries, the TLCCM arrangement confirmed a significant enhancement in the mixing performance.

Modification of Ceritinib Crystal Morphology via Spherical Crystallization

The formulation process for some drugs can be challenging, due to their unfavorable physical and mechanical properties and poor water solubility. Powder technology has made a significant impact in regard to the modification of the particles in active pharmaceutical ingredients (APIs) to produce high-quality granules. Spherical particles are preferred over other shapes, due to their high tap and bulk density, reduced dustiness, better flowability, strong anti-caking properties, and better mechanical performance during tableting. The present study investigates the possibility of obtaining spherical crystals of ceritinib, a drug used for the treatment of anaplastic lymphoma kinase (ALK)-positive advanced non-small cell lung cancer, which belongs to BCS class IV drugs and has a platy crystal structure. Ceritinib spheres were prepared by spherical agglomeration, in a ternary system, and quasi-emulsion solvent diffusion, with the addition of polyvinylpyrrolidone, as well as a combination of these two methods. With the combined method of spherical crystallization, crystals with the most favorable morphology and the narrowest distribution of particle sizes were obtained, which was the reason for further optimization. The influence of different impeller geometries and mixing rates on the morphology of the obtained crystals was examined and the optimal conditions for the process were selected. Using empirical correlations and a visual criterion, the process was scaled up from a 0.1 L to a 1 L batch crystallizer. The obtained crystals were characterized by light and scanning electron microscopy. The addition of a bridging liquid and/or a polymer additive did not change the internal structure of the ceritinib crystals, which was confirmed by X-ray powder diffraction.

Long-distance migrations, population mixing, and growth rate of lumpfish (Cyclopterus lumpus) revealed from tag-recaptures.

We reveal that lumpfish (Cyclopterus lumpus) frequently migrate over long distances between their summer feeding area in the open ocean and their spring spawning sites in coastal areas, through applying tag-recapture methodology. A total of 2750 C. lumpus were tagged in the Irminger Sea around Iceland and in the Norwegian Sea over 6 years, of which 17 C. lumpus were recaptured. Interestingly, four individuals were recaptured more than 1000 km distant from where they were tagged. C. lumpus tagged in the Irminger Sea and north of Iceland were recaptured around Iceland, whereas none of the fish tagged in other areas of the Norwegian Sea were recaptured in Iceland. This difference in recapture rate from different areas suggests that a higher proportion of C. lumpus from the Irminger Sea and north of Iceland spawns around Iceland in comparison with C. lumpus in other areas. Two fish tagged east of Iceland were recaptured on the coast of Denmark, with one fish having a displacement distance of 1612 km. The recapture of these two fish in Denmark demonstrates that part of the C. lumpus population spawning in Denmark utilizes the Norwegian Sea as a major feeding area and that the Norwegian Sea is a common feeding area for several distinct populations of C. lumpus. The growth rate of tagged fish varied from 1.2 to 11.1 cm year-1, indicating that males that are >20 cm and females that are >25 cm during the summer are capable of sufficient growth to achieve a suitable size for spawning (≥25 and ≥35 cm for males and females, respectively) the following spring.

Performance of Risk Models for Antimicrobial Resistance in Adult Patients With Sepsis

The results of prediction models that stratify patients with sepsis and risk of resistant gram-negative bacilli (GNB) infections inform treatment guidelines. However, these models do not extrapolate well across hospitals. To assess whether patient case mix and local prevalence rates of resistance contributed to the variable performance of a general risk stratification GNB sepsis model for community-onset and hospital-onset sepsis across hospitals. This was a retrospective cohort study conducted from January 2016 and October 2021. Adult patients with sepsis at 10 acute-care hospitals in rural and urban areas across Missouri and Illinois were included. Inclusion criteria were blood cultures indicating sepsis, having received 4 days of antibiotic treatment, and having organ dysfunction (vasopressor use, mechanical ventilation, increased creatinine or bilirubin levels, and thrombocytopenia). Analyses were completed in April 2024. The model included demographic characteristics, comorbidities, vital signs, laboratory values, procedures, and medications administered. Culture results were stratified for ceftriaxone-susceptible GNB (SS), ceftriaxone-resistant but cefepime-susceptible GNB (RS), and ceftriaxone- and cefepime-resistant GNB (RR). Negative cultures and other pathogens were labeled SS. Deep learning models were developed separately for community-onset (patient presented with sepsis) and hospital-onset (sepsis developed ≥48 hours after admission) sepsis. The models were tested across hospitals and patient subgroups. Models were assessed using area under the receiver operating characteristic curve (AUROC) and area under precision recall curve (AUPRC). A total of 39 893 patients with 85 238 sepsis episodes (43 207 [50.7%] community onset; 42 031 [48.3%] hospital onset) were included. Median (IQR) age was 65 (54-74) years, 21 241 patients (53.2%) were male, and 18 830 (47.2%) had a previous episode of sepsis. RS contributed to 3.9% (1667 episodes) and 5.7% (2389 episodes) of community-onset and hospital-onset sepsis episodes, respectively, and RR contributed to 1.8% (796 episodes) and 3.9% (1626 episodes), respectively. Previous infections and exposure to antibiotics were associated with the risk of resistant GNB. For example, in community-onset sepsis, 375 RR episodes (47.1%), 420 RS episodes (25.2%) and 3483 of 40 744 (8.5%) SS episodes were among patients with resistance to antimicrobial drugs (P < .001). The AUROC and AUPRC results varied across hospitals and patient subgroups for both community-onset and hospital-onset sepsis. AUPRC values correlated with the prevalence rates of resistant GNB (R = 0.79; P = .001). In this cohort study of 39 893 patients with sepsis, variable model performance was associated with prevalence rates of antimicrobial resistance rather than patient case mix. This variability suggests caution is needed when using generalized models for predicting resistant GNB etiologies in sepsis.

Systematic analysis of mixing and segregation patterns of binary mixtures in fluidised beds for multi-functional processes

Fluidized beds are increasingly used in renewable energy and chemical production due to their versatility in handling different solids for multi-functional industrial applications. The diversity in size and density of solid particles impacts fluidization, influencing mixing and segregation behaviours critical for optimizing chemical processes and reactor design. This study investigates the expansion and segregation behaviours of mixed Geldart group powders in binary systems, simulating polydispersed beds with different materials and catalysts. By applying a modified Cheung equation and an adapted Gibilaro-Rowe model, the study analyzes segregation behaviours of Geldart Group A and B materials at varying mixing rates and gas flow velocities. Results show a good match between experimental data and model predictions. Using novel non-invasive X-ray imaging, the study provides real-time analysis of mixing and segregation at different fluidization regimes and temperatures. These findings aid in designing and optimizing advanced thermochemical conversion technologies, enhancing process efficiency and resilience.

Online Learning of Entrainment Closures in a Hybrid Machine Learning Parameterization

AbstractThis work integrates machine learning into an atmospheric parameterization to target uncertain mixing processes while maintaining interpretable, predictive, and well‐established physical equations. We adopt an eddy‐diffusivity mass‐flux (EDMF) parameterization for the unified modeling of various convective and turbulent regimes. To avoid drift and instability that plague offline‐trained machine learning parameterizations that are subsequently coupled with climate models, we frame learning as an inverse problem: Data‐driven models are embedded within the EDMF parameterization and trained online in a one‐dimensional vertical global climate model (GCM) column. Training is performed against output from large‐eddy simulations (LES) forced with GCM‐simulated large‐scale conditions in the Pacific. Rather than optimizing subgrid‐scale tendencies, our framework directly targets climate variables of interest, such as the vertical profiles of entropy and liquid water path. Specifically, we use ensemble Kalman inversion to simultaneously calibrate both the EDMF parameters and the parameters governing data‐driven lateral mixing rates. The calibrated parameterization outperforms existing EDMF schemes, particularly in tropical and subtropical locations of the present climate, and maintains high fidelity in simulating shallow cumulus and stratocumulus regimes under increased sea surface temperatures from AMIP4K experiments. The results showcase the advantage of physically constraining data‐driven models and directly targeting relevant variables through online learning to build robust and stable machine learning parameterizations.

Aerosol Vertical Turbulent Mass Flux Retrievals Through Novel Remote Sensing Algorithm

AbstractIntegrated measurements of aerosol, radiation, cloud, and turbulent transport in the planetary boundary layer (PBL) are essential for understanding and modeling climate and air quality. Here, we developed a new technique for the identification of convective turbulent regions and deriving the vertical distribution of aerosol turbulent mass fluxes within PBL. The algorithm uses retrievals from coherent Doppler lidars and a high spectral resolution lidar. The technique was applied to study particle mass fluxes over 2 months (November–December 2020) during the campaign conducted at the DOE Atmospheric Radiation Measurement Southern Great Plains (SGP) site in Lamont, Oklahoma. The algorithm developed here is capable of continuously deriving vertically resolved (curtains) aerosol mass fluxes. Our data analysis shows that at the site, the 30‐min averaged fluxes at 135 m above the surface were mainly positive (upward) at ∼1 μg m−2 s−1, suggesting that the surface is the primary source of the particle mass supplied to the boundary layer at the SGP site. Analyses of the individual case studies have revealed that not all the derived fluxes can be linked to surface emissions. Both positive and negative values in a range of ±5 μg m−2 s−1 can be caused by convective thermals interacting between the residual layer and the mixed layer and by rotation of the horizontal wind with the height. Large erroneous negative fluxes can also be caused by drizzling/precipitating clouds. We anticipate that the application of the current technique will lead to a more realistic representation of aerosol mass budgets and bidirectional mixing rates.

Mixing enhancement with minimal thrust loss for the Mach 1.76 jet issuing from different beveled collar nozzles

The main objective of the present investigation is to enhance the jet mixing by introducing a nozzle collar exit inclination having bevel angles of 30°, 45°, and 60°. In addition to this, the present study also addresses the problem of investigating the jet which attains maximum mixing from beveled collar nozzle with the imposition of a minimal overall thrust loss penalty. The nozzles of the present study have been designed to deliver a uniform Mach 1.76 jet at the nozzle collar exit. The results thus obtained through numerical computations have been compared with that of the reference nozzle which has zero exit inclination. The investigations have been performed under both design and off-design conditions of the jet by varying the nozzle pressure ratio (NPR) from 4.5 to 6.5 with unit step size. It is seen that the rate of jet mixing is augmented with the increase in the bevel angle. Thus, the 60° beveled collar nozzle demonstrated the highest jet mixing in comparison to the reference nozzle, 30° and 45° beveled collar nozzle at each nozzle pressure ratio. However, 60° beveled collar nozzle has been substantially penalized with the highest thrust loss of about 6.5% at nozzle pressure ratio 4.5 and about 3.5% at nozzle pressure ratio 5.5 with respect to the reference nozzle and other nozzles of the present study. The 45° and 30° beveled collar nozzles reported the thrust penalty below 2.3% and 1%, respectively. The overall performance, which includes mixing enhancement along with the minimal thrust loss, has been found in the 45° beveled collar nozzle, which clearly justifies its preference over the other investigated nozzle configurations.

Enhancing methods engineering education with a digital platform: usability and educational impact on industrial engineering students

IntroductionWork study aims to comprehend the potential of human work by assessing the duration of tasks and identifying methods for reducing them to enhance productivity and efficiency. On the other hand, methods engineering analyzes job processes to determine the most efficient and cost-effective techniques, resulting in improved operations. These areas are essential in the field of industrial engineering. Traditionally, they are taught using printed manuals and classroom-based instruction. Nevertheless, these conventional strategies frequently encounter difficulties engaging students and generating solid comprehension of the topics.MethodsThis study involved the development of a digital platform to improve methods engineering education. The platform adapts the curriculum of the methods engineering course offered at Universidad Panamericana. Each laboratory's practice includes detailed instructions and tasks for students to complete. Upon finishing, students submit their reports, which the professor then assesses. If the report meets the required standards, it is approved; otherwise, students must repeat the activities. An experience system serves as a tracker for course completion and keeps track of the student's progress.ResultsAn experimental group of 26 students who responded to Doll and Torkzadeh's end-user computer satisfaction survey tested the platform. Participants responded positively, particularly regarding the platform's accuracy (73.08% high satisfaction), ease of use (majority rated 5 for user-friendliness), and timeliness (majority satisfied with up-to-date information). However, the format dimension received mixed ratings, indicating areas for improvement. Additionally, participants appreciated the platform's ability to track progress and motivate the completion of laboratories, with 61.54% finding the content relevant and valuable for learning methods engineering concepts.DiscussionThe results suggest that integrating digital platforms into educational settings could significantly enhance educational settings, particularly in engineering courses where conventional approaches struggle to maintain student interest and engagement. Participants' positive responses support digital platforms' potential to complement and improve teaching methods. Future research will focus on integrating adaptive learning and generating micro-credentials to certify student expertise.

Spatio-temporal and depth-oriented evaluation of hyporheic zone processes in headwater catchments

The hyporheic zone (HZ) is vital for nutrient cycling and overall stream ecosystem health across groundwater-surface water interfaces, with biogeochemical and physical variations influencing exchange processes. To gain a depth-oriented insight into the various hyporheic functioning, isotopic (18O and 2H) and chemical analyses, along with physical parameters, were performed in two streams named Ahna and Losse in North Hesse, Germany. Multi-level interstitial probes were installed to extract subsurface pore water samples up to 0.45 m depth. We identified three distinct HZ in Ahna upstream, downstream and Losse. The Ahna upstream HZ was a less permeable barrier with low water fluxes but reactive, while the downstream HZ was less reactive with higher permeability and vertical fluxes. The Losse HZ, remained non-reactive but well-mixed with good hydraulic circulation due to fast downward flows. Isotopic composition revealed distinctive features, indicating increased evaporation and intricate mixing with other water sources and intensified subsurface flow in Ahna downstream compared to upstream. Hydro-chemical dynamics in Ahna exposed increased ion concentrations downstream, driven by anthropogenic factors along the course. Upstream denitrification was dominant under low oxygen conditions due to the slow infiltration and low mixing rates. The primary water source for both streams and HZs was groundwater, with the potential for rainwater to serve as a secondary source. This study shows the spatial heterogeneity of HZ processes and highlights that the specific HZ conditions need to be examined locally.

Air and Thermally Stable Fluoride Bridged Rare-Earth Clusters Showing Intense Photoluminescence and Potential LED Application.

Fluoride based lattice is attractive for reducing phonon-induced quenching in rare-earth (RE) based luminescent materials. However, due to the strong affinity betweenRE and oxygen, the synthesis of fluoride-based complexes has to be protected under anhydrous conditions,and many known fluoride bridged RE clusters are unstable in air. Here, by using the "mixed-ligand" strategy a family of fluoride bridged RE clusters is synthesized, namely RE16(μ4-F)6(μ3-F)12(tBuCOO)18[N(CH2CH2O)3]4 (RE = Eu, EuFC-16; RE = Tb, TbFC-16), which are highly stable in air and decomposed thermally only when heating above 435°C. Moreover, both clusters exhibit high photoluminescence quantum yields (PLQYEuFC-16 = 87.7%, PLQYTbFC-16 = 99.0%). Upon warming, EuFC-16 and TbFC-16 displayexcellent structural, thermal, and chroma stability. Thus, EuFC-16 and TbFC-16 have the potential to be used in light-emitting diode (LED) devices, offering many advantages over commercial phosphors. First, both clusters are soluble in UV-curable resin at any mixing rate, and the emission colors can be tuned from magenta, turquoise, willow green, and ivory to pure white if mixing blue phosphor BAM:Eu2+. Second, the clusters are hydrophobic, and the LEDs work well after soaking in water, indicating a good quality for outdoor lighting.

In situ treatment of contaminated soil using persulfate activated by sulfidated zero-valent iron

Soil contamination with hazardous substances like phenol poses significant environmental and health risks. In situ soil mixing can be a promising technological solution to this challenge. A persulfate and sulfidated zero-valent iron (S-ZVIbm) system for remediating contaminated soil was developed and tested to be suited to in situ soil mixing. S-ZVIbm was synthesized using a ball mill process, and the optimal sulfur to iron molar ratio for effectively removing phenol from soil removal without pyrophoric risks was 0.12. Soil slurry experiments were performed, and the best phenol oxidation results (high stoichiometric efficiency and sustained oxidation after mixing) were achieved at a persulfate to S-ZVIbm molar ratio of 2:1 and a persulfate to phenol molar ratio of 8:1. A high organic matter content of the silty clay fraction of the soil strongly suppressed persulfate activation, so suppressed phenol removal and increased persulfate consumption. Electron spin resonance and radical scavenging tests confirmed that hydroxyl and sulfate radicals were present during the degradation of phenol. While sulfate radicals predominantly facilitated degradation in the soil, both sulfate and hydroxyl radicals were crucial in the aqueous phase in the absence of soil organic matter. In situ soil mixing simulation tests indicated that the persulfate and S-ZVIbm doses and the mixing rate and duration strongly affected the efficacy of the system, and the optimal conditions for phenol removal were determined. The results indicated that the persulfate/S-ZVIbm system could be tuned to achieve sustained persulfate activation and to remediate contaminated soil employing in situ soil mixing technique.

A well-balanced vegan diet does not compromise daily mixed muscle protein synthesis rates when compared to an omnivorous diet in active older adults: a randomized controlled cross-over trial

A well-balanced vegan diet does not compromise daily mixed muscle protein synthesis rates when compared to an omnivorous diet in active older adults: a randomized controlled cross-over trial

Meals Containing Equivalent Total Protein from Foods Providing Complete, Complementary, or Incomplete Essential Amino Acid Profiles do not Differentially Affect 24-h Skeletal Muscle Protein Synthesis in Healthy, Middle-Aged Women

BackgroundDietary protein quality can be assessed by skeletal muscle protein synthesis (MPS) stimulation. Limited knowledge exists on how consuming isonitrogenous meals with varied protein qualities affects postprandial and 24-h MPS. ObjectivesWe assessed the effects of protein quality and complementary proteins on MPS. We hypothesized that meals containing a moderate amount of high-quality, complete protein would stimulate postprandial and 24-h MPS. Meals containing two complementary, plant-based incomplete proteins would stimulate MPS less, and meals containing plant-based incomplete proteins at each meal, but complementary over 24 h would not stimulate MPS. MethodsThis quasi-experimental study included a randomized, crossover design to assess protein quality and a nonrandomized low-protein control. We measured postprandial and 24-h MPS responses of healthy middle-aged women (n = 9, age 56 ± 4 y), to 3 dietary conditions: isonitrogenous meals containing 23 g protein/meal from 1) complete protein (lean beef), 2) 2 incomplete, but complementary protein sources (navy/black beans and whole wheat bread), and 3) single incomplete protein sources (black beans or whole wheat bread at 1 meal), but providing a complete amino acid profile over 24 h. In the low-protein group women (n = 8, 54 ± 5 y) consumed a single breakfast meal containing 5 g of protein. Venous blood and vastus lateralis samples were obtained during primed, constant infusions of L-[ring-13C6]phenylalanine to measure mixed muscle fractional synthetic rates (FSR). ResultsMeals containing complete, complementary, or incomplete proteins did not differentially influence FSR responses after breakfast (P = 0.90) or 24 h (P = 0.38). At breakfast, the complete (P = 0.030) and complementary (P = 0.031) protein meals, but not the incomplete protein meal (P = 0.38), had greater FSR responses compared with the low-protein control meal. ConclusionsIsonitrogenous meals containing a moderate serving of total protein from foods providing complete, complementary, or incomplete essential amino acid profiles do not differentially stimulate muscle protein synthesis after a meal and daily. Trial registration numberThis clinical trial was registered at clinicaltrials.gov as NCT03816579. URLhttps://www.clinicaltrials.gov/ct2/show/NCT03816579?term=NCT03816579&draw=2&rank=1.

The Rapid Response of Southern Ocean Biological Productivity to Changes in Background Small Scale Turbulence

AbstractBackground subsurface vertical mixing rates in the Southern Ocean (SO) are known to vary by an order of magnitude temporally and spatially, due to variability in their generating mechanisms, which include winds and shear instabilities at the surface, and the interaction of tides and lee waves with rough bottom topography. There is great uncertainty in the parameterization of this mixing in coarse resolution Earth System Models (ESM), and in the impact that this has on SO biological productivity on sub decadal timescales. Using a data assimilating biogeochemical ocean model we show that SO phytoplankton productivity is highly sensitive to differences in background diapycnal mixing over short timescales. Changes in the background vertical mixing rates alter key biogeochemical and physical conditions. The greatest changes to the distribution of physical and biogeochemical tracers occur in regions with very strong tracer vertical gradients. A combination of reduced nutrient limitation and reduced light limitation causes a strong increase in SO phytoplankton productivity with higher background mixing. This leads to increased summer carbon export but reduced wintertime export over the mixed layer depth, which could alter the strength of the SO biological carbon pump and atmospheric concentrations on centennial to millennial timescales. This study demonstrates the importance of accurately representing diapycnal mixing in ESM to predict SO biogeochemical dynamics and their broader climatic implications.

Comparison of the natural and surfactant-modified zeolites in the adsorption efficiency of sunset yellow food dye from aqueous solutions

The removal of Sunset Yellow (E110) on natural zeolite and zeolite modified with the cationic surfactant cetyl pyridinium chloride (CPC) was studied using the adsorption method. The structural characteristics of the surfactant-modified zeolite (SMZ-CPC) were investigated using X-ray diffraction(XRD), Fourier transform infrared spectroscopy (FTIR), Brunauer–Emmett–Teller (BET) analysis, and the scanning electron microscopy (SEM) images. The effect of different parameters on the adsorption process, such as equilibration time and amount of adsorbent at 298 K, were determined using UV–Vis spectroscopy. The maximum dye removal percentage on SMZ-CPC was obtained with 0.08 g of adsorbent in 30 min. The results show that the zeolite modified with CPC surfactant (SMZ) has a higher adsorption capacity for Sunset Yellow than the unmodified zeolite (natural form). The experimental adsorption data were nonlinearly analyzed using isotherm equations such as Langmuir, Freundlich, Temkin, Langmuir-Freundlich (or Sips), and Extended Langmuir (EL). The experimental data were better fitted with the Sips isotherm. The adsorption kinetic data were analyzed using eight models in nonlinear forms: the pseudo-first-order (PFO), pseudo-second-order (PSO), integrated kinetic Langmuir (IKL), Elovich, intraparticle diffusion (IPD), mixed order rate equation (MOE), fractal-like pseudo-first-order (FL-PFO) and fractal-like pseudo-second-order (FL-PSO). According to the results of the coefficient of determination (R2), Elovich kinetic model well expressed E110 adsorption onto SMZ-CPC. Most of the dye removal takes place in less than 5 min and the maximum adsorption capacity is 5.06 mg/g. The results of this study show that zeolite modified with cationic surfactant is an effective adsorbent for removal anionic dyes from an aqueous solution.

N-doped LiNi0.65Co0.15Mn0.2O2 ternary cathode materials for improved electrochemical performance

LiNi0.65Co0.15Mn0.2O2 (NCM) has some advantages of high specific capacity, low cost, and environmental friendliness, but its high nickel content leads to serious cationic mixing and poor cycling and rate performance. The N doping LiNi0.65Co0.15Mn0.2O2 (NCM-x%N) is prepared by co-precipitation method. It is indicated by various representational means that N doping can reduce the particle size, effectively inhibit the cationic mixing degree, and increase lattice spacing. The means can improve the diffusion rate of lithium ions, among which N doping LiNi0.65Co0.15Mn0.2O2 (NCM-3%N) of x = 3 has the best electrochemical performance. After 100 cycles at 0.1C, the specific discharge capacity was 137.8 mA·h·g−1 (85.80 % capacity retention rate), which is 15.87 % higher than other NCM. The magnification performance is tested at 0.1C, 0.2C, 0.5C, 1C, and 2C. After 25 cycles, the capacity retention rate of NCM-3%N was 92.1 %, 11.11 % higher than that of NCM. Reaction kinetics showed that NCM-3%N has a lithium-ion diffusion coefficient that is higher than NCM.

Invasive mussels reduce community bioturbation but do not affect oxygen penetration or nutrient fluxes in organic‐poor Great Lakes sediments

Abstract Invasive zebra and quagga (dreissenid) mussels have disrupted nutrient cycling and benthic macrofauna communities in the Laurentian Great Lakes and other invaded ecosystems. Dreissenids are now the dominant benthic macroinvertebrate in the Great Lakes, replacing the formerly dominant native bioturbating amphipod Diporeia spp. Dreissenids and Diporeia interact with their environment in fundamentally different ways, and the consequences of this functional shift in benthic community structure on benthic–pelagic coupling are not well understood, particularly in unproductive offshore lake regions. To determine how functional biology and benthic community structure impact sediment mixing and biogeochemistry in low particulate organic matter (POM) lake regions, we conducted a 6‐week sediment microcosm experiment with dreissenids, Diporeia and oligochaete worms—the second most common Great Lakes benthic macroinvertebrate. We found that sediment mixing rate and depth varied significantly among the taxa. Diporeia mixed sediment the deepest and strongest, followed by oligochaetes, while dreissenids did not appreciably mix sediment. Despite these differences, we found no significant variations among treatments in sediment oxygen penetration depth, sediment respiration (oxygen uptake) or nutrient dynamics. Our results suggest that dreissenids mix sediment less than native Great Lakes taxa, but that differential mixing rates may not measurably affect nutrient and oxygen dynamics in low‐POM sediments. Therefore, mussel effects in these areas may be manifested more through direct mechanisms rather than via altered sediment geochemistry.

Fast Computer Model Calibration using Annealed and Transformed Variational Inference

Computer models play a crucial role in numerous scientific and engineering domains. To ensure the accuracy of simulations, it is essential to properly calibrate the input parameters of these models through statistical inference. While Bayesian inference is the standard approach for this task, employing Markov chain Monte Carlo methods often encounters computational hurdles due to the costly evaluation of likelihood functions and slow mixing rates. Although variational inference (VI) can be a fast alternative to traditional Bayesian approaches, VI has limited applicability due to boundary issues and local optima problems. To address these challenges, we propose flexible VI methods based on deep generative models that do not require parametric assumptions on the variational distribution. We embed a surjective transformation in our framework to avoid posterior truncation at the boundary. Additionally, we provide theoretical conditions that guarantee the success of the algorithm. Furthermore, our temperature annealing scheme and fine-tuning can prevent being trapped in local optima through a series of intermediate posteriors and weight adjustment. We apply our method to infectious disease models and a geophysical model, illustrating that the proposed method can provide fast and accurate inference compared to its competitors.