Insights into the seasonal characteristics of single particle aerosols in Chengdu based on SPAMS.

To investigate the seasonal characteristics in air pollution in Chengdu, a single particle aerosol mass spectrometry was used to continuously observe atmospheric fine particulate matter during one-month periods in summer and winter, respectively. The results showed that, apart from O3, the concentrations of other pollutants (CO, NO2, SO2, PM2.5 and PM10) were significantly higher in winter than in summer. All single particle aerosols were divided into seven categories: biomass burning (BB), coal combustion (CC), Dust, vehicle emission (VE), K mixed with nitrate (K-NO3), K mixed with sulfate and nitrate (K-SN), and K mixed with sulfate (K-SO4) particles. The highest contributions in both seasons were VE particles (24%). The higher contributions of K-SO4 (16%) and K-NO3 (10%) particles occurred in summer and winter, respectively, as a result of their different formation mechanisms. S-containing (K-SO4 and K-SN), VE, and BB particles caused the evolution of pollution in both seasons, and they can be considered as targets for future pollution reduction. The mixing of primary sources particles (VE, Dust, CC, and BB) with secondary components was stronger in winter than in summer. In summer, as pollution worsens, the mixing of primary sources particles with 62 [NO3]- weakened, but the mixing with 97 [HSO4]- increased. However, in winter, the mixing state of particles did not exhibit an obvious evolution rules. The potential source areas in summer were mainly distributed in the southern region of Sichuan, while in winter, besides the southern region, the contribution of the western region cannot be ignored.

A comparative study on the formation of nitrogen-containing organic compounds in cloud droplets and aerosol particles.

Nitrogen-containing organic compounds (NOCs) may potentially contribute to aqueous secondary organic aerosols, yet the different formation of NOCs in aerosol particles and cloud droplets remains unclear. With the in-situ measurements performed at a mountain site (1690 m a.s.l.) in southern China, we investigated the formation of NOCs in the cloud droplets and the cloud-free particles, based on their mixing state information of NOCs-containing particles by single particle mass spectrometry. The relative abundance of NOCs in the cloud-free particles was significantly higher than those in cloud residual (cloud RES) particles. NOCs were highly correlated with carbonyl compounds (including glyoxalate and methylglyoxal) in the cloud-free particles, however, limited correlation was observed for cloud RES particles. Analysis of their mixing state and temporal variations highlights that NOCs was mainly formed from the carbonyl compounds and ammonium in the cloud-free particles, rather than in the cloud RES particles. The results support that the formation of NOCs from carbonyl compounds is facilitated in concentrated solutions in wet aerosols, rather than cloud droplets. In addition, we have identified the transport of biomass burning particles that facilitate the formation of NOCs, and that the observed NOCs is most likely contributed to the light absorption. These findings have implications for the evaluation of NOCs formation and their contribution to light absorption.

How much rainwater contributes to a spring discharge in the Guarani Aquifer System: insights from stable isotopes and a mass balance model.

Outcrops play an important role in groundwater recharge. Understanding groundwater origins, dynamics and its correlation with different water sources is essential for effective water resources management and planning in terms of quantity and quality. In the case of the Guarani Aquifer System (GAS) outcrop areas are particularly vulnerable to groundwater pollution due to direct recharge processes. This study focuses on the Alto Jacaré-Pepira sub-basin, a watershed near Brotas, a city in the central region of the state of São Paulo, Brazil, where groundwater is vital for supporting tourism, agriculture, urban water supply, creeks, river and wetlands. The area has a humid tropical climate with periods of both intense rainfall and drought, and the rivers remain perennial throughout the year. Therefore, the aim of this study is to investigate the interconnections between a spring and its potential sources of contribution, namely rain and groundwater, in order to elucidate the relationships between the different water sources. To achieve this, on-site monitoring of groundwater depth, rainfall amount, and stable isotope ratios (deuterium (2H) and oxygen-18 (18O)) from rain, spring discharge, and a monitoring well was carried out from 2013 to 2021. The results indicate that the mean and standard deviations for δ18O in rainwater exhibit higher variability, resulting in -4.49 ± 3.18 ‰ VSMOW, while δ18O values from the well show minor variations, similar to those of the spring, recording -7.25 ± 0.32 ‰ and -6.94 ± 0.28 ‰ VSMOW, respectively. The mixing model's outcomes reveal seasonal variations in water sources contribution and indicate that groundwater accounts for approximately 80 % of spring discharge throughout the year. Incorporating stable isotopes into hydrological monitoring provides valuable data for complementing watershed analysis. The values obtained support the significance of the aquifer as a primary source, thereby offering critical insights into stream dynamics of the region.

Dynamics of subsurface chlorophyll maxima in the northern Indian Ocean.

Subsurface chlorophyll maxima (SCM) significantly contributes to oceanic primary productivity, emphasizing the need to study its dynamics and governing mechanisms. We used datasets from various platforms to investigate relationships between the SCM characteristics (SCM depth (ZSCM), SCM magnitude (Chlmax), SCM thickness (TSCM)) and environmental variables modulated by various physical processes in the Northern Indian Ocean (NIO). In the Arabian Sea (western NIO), seasonal processes like convective mixing and upwelling, primarily regulated the SCM characteristics. In the Bay of Bengal (eastern NIO), SCM characteristics were jointly influenced by fresh water influx, barrier layer formation, presence of eddies, and the propagation of Kelvin and Rossby waves. Any changes in these oceanic processes, potentially driven by climate change, could therefore impact oceanic primary production. Additionally, a positive association obtained between Chlmax and downward CO2 flux, while a shallower ZSCM, associated with higher concentrations of DMS, indicated SCM's role in regulating atmospheric gases.

Regulation of warming on the mixed decomposition of Artemisia ordosica and Leymus secalinus litter in Mu Us Desert, China is time-dependent.

Warming drives material cycling in terrestrial ecosystems by affecting litter decomposition, as it can alter litter yield, quality and decomposer composition and activity. The effect of warming on the decomposition of mixed litter in arid and semi-arid zones remains unknown. We investigated the mass loss and nutrient release dynamics during 450 days of decomposition of Artemisia ordosica, Leymus secalinus, and their mixture in Mu Us Desert by open-top chambers and litter bags. The results showed interspecific differences in the responses to warming, in that warming promoted mass loss and N and P release from L. secalinus and inhibited mass loss and P but promoting N release from A. ordosica. Mixing of A. ordosica and L. secalinus litter inhibited decomposition. Warming enhanced the antagonistic effects of mixed decomposition. The total mass loss of mixed litter was decreased by 9%, and the release of N and P was decreased by 4.9% and 12.6%, respectively. The antagonistic effects of mixed litter mass loss and P release under the warming treatment gradually strengthened with time, with N release changing from a synergistic to an antagonistic effect at 150 d. The non-additive effects produced by the mixed decomposition of A. ordosica and L. secalinus litter were jointly regulated by temperature and time. Future research on mixed litter decomposition should consider the interaction between temperature and time.

Identification of the nitrate pollution in surface water of Dongshan Bay based on stable isotope technology.

Identifying and quantifying water nitrate pollution is crucial for managing aquatic environment of a bay. Dongshan Bay, a significant semi-enclosed bay in the southeastern coastal area of Fujian Province, features mangrove and coral reef ecosystems at its estuary and bay mouth, respectively. Dongshan Bay is impacted by human activities such as mariculture. We quantified and analyzed nitrate pollution status in the surface waters of Dongshan Bay by measuring physicochemical parameters, stable isotopes (δ15N-NO3-, δ18O-NO3- and δ15N-NH4+) of the surface waters, and using statistical methods including the MixSIAR isotope mixing model. The results showed that the concentrations of chlorophyll a and dissolved inorganic nitrogen in the surface waters exhibited a noticeable gradient change, decreasing from the estuary of the Zhangjiang River to the mouth of Dongshan Bay. The maximum concentrations of chlorophyll a, NH4+, NO3- and NO2- were 45.2 µg·L-1, 52.67 µmol·L-1, 379.2 µmol·L-1 and 3.93 µmol·L-1, respectively. The nitrogen and oxygen isotope values of NH4+ and NO3- in the surface waters showed significant spatial variations. According to the MixSIAR model results, nitrogen sources in the surface waters of Dongshan Bay were mainly freshwater inputs of the Zhangjiang River estuary, aquaculture wastewater, and groundwater. The freshwater input from the Zhangjiang River estuary contributed the most (25.2%), while aquaculture wastewater, groundwater and urban sewage accounted for 24.6%, 19.0%, and 15.1%, respectively. It is evident that freshwater input from the Zhangjiang River estuary is the primary source of nitrate in the surface waters of Dongshan Bay.

Spin Transport Modulation of 2D Fe3O4 Nanosheets Driven by Verwey Phase Transition.

Realizing spin transport between heavy metal and two-dimensional (2D) magnetic materials at high Curie temperature (TC) is crucial to advanced spintronic information storage technology. Here, environmentally stable 2D nonlayered Fe3O4 nanosheets are successfully synthesized using a reproducible process and found that they exhibit vortex magnetic domains at room temperature. A Verwey phase transition temperature (TV) of ≈110 K is identified for ≈3 nm thick nanosheet through Raman characterization and spin Hall device measurement of the Pt/Fe3O4 bilayer. The anisotropic magnetoresistance ratio decreases near TV, while both the spin Hall magnetoresistance ratio and spin mixing conductance (Gr) increase at TV. As the temperature approaches 112 K, the anomalous Hall effect ratio tends to become zero. The maximum Gr reaches ≈5 × 1015 Ω-1m-2 due to the clean and flat interface between Pt and 2D nanosheet. The observed spin transport behavior in Pt/Fe3O4 spin Hall devices indicates that 2D Fe3O4 nanosheets possess potential for high-power micro spintronic storage devices applications.

A unifying approach to drug-in-polymer solubility prediction: Streamlining experimental workflow and analysis.

This method paper describes currently used experimental methods to predict the drug-in-polymer solubility of amorphous solid dispersions and offers a combined approach for applying the Melting-point-depression method, the Recrystallization method, and the Melting-and-mixing method. It aims to describe and expand on the theoretical basis as well as the analytical methodology of the recently published Melting-and-mixing method. This solubility method relies on determining the relationship between drug loads and the enthalpy of melting and mixing of a crystalline drug in the presence of an amorphous polymer. This relationship is used to determine the soluble drug load of an amorphous solid dispersion from the recorded enthalpy of melting and mixing of the crystalline drug portion in a drug-polymer sample at equilibrium solubility. Due to the complex analytical methodology of the Melting-and-mixing method, a software solution called the Glass Solution Companion app was developed. Using this new tool, it is possible to calculate the predicted drug-in-polymer solubility and Flory-Huggins interaction parameter from experimental samples, as well as to generate the resulting solubility-temperature curve. This software can be used for calculations for all three experimental methods, which would be useful for comparing the applicability of the methods on a given drug-polymer system. Since it is difficult to predict the suitability of these drug-in-polymer solubility methods for a specific drug-polymer system in silico, some experimental investigation is necessary. By optimizing the experimental protocol, it is possible to collect data for the three experimental methods simultaneously for a specific drug-polymer system. These results can then be readily analyzed using the Glass Solution Companion app to find the most appropriate method for the drug-polymer system, and therefore, the most reliable drug-in-polymer solubility prediction.

Methods for Studying Fusion of Bacterial Extracellular Vesicles with Intact Bacteria and Host Cells.

Bacterial extracellular vesicles (BEVs) are nano- or micrometer-sized membrane-bound lipid vesicles released from both Gram-negative and Gram-positive bacteria. Cellular transport, communication, pathogenesis, and host-pathogen interactions are some of the major biological processes impacted by BEVs. Among these, host-pathogen interactions and bacterial pathogenesis are emerging as highly important targetable avenues underlined by the issues of antimicrobial resistance, thus demanding novel targets and approaches to treat bacterial infections. In this aspect, the study of the interaction of BEVs with bacteria and/or host cells becomes imperative and brings the membrane fusion process to the forefront. Furthermore, membrane fusion also underscores the performance of BEVs as nano-therapeutic delivery platforms. Here, we report methods to study fusion kinetics between mycobacteria-derived extracellular vesicles, which we refer to as MEVs, and intact mycobacteria or MEVs themselves. We also discuss the isolation of MEVs and their characterization. We outline critical factors that affect fusion kinetics by MEVs. The same principle can be extended for studying fusion between BEVs and mammalian host cells important for understanding how BEVs influence host-pathogen crosstalk.

Field measurements of turbulent mixing south of the Lombok Strait, Indonesia.

The Indonesian seas, with their complex passages and vigorous mixing, constitute the only route and are critical in regulating Pacific-Indian Ocean interchange, air-sea interaction, and global climate events. Previous research employing remote sensing and numerical simulations strongly suggested that this mixing is tidally driven and localized in narrow channels and straits, with only a few direct observations to validate it. The current study offers the first comprehensive temporal microstructure observations in the south of Lombok Strait with a radius of 0.05° and centered on 115.54oE and 9.02oS. Fifteen days of tidal mixing observations measured potential temperature and density, salinity, and turbulent energy dissipation rate. The results revealed significant mixing and verified the remotely sensed technique. The south Lombok temporal and depth averaged of the turbulent kinetic energy dissipation rate, and the diapycnal diffusivity from 20 to 250 m are ε  = 4.15 ± 15.9) × 10-6 W kg-1 and K ρ = (1.44 ± 10.7) × 10-2 m2s-1, respectively. This K ρ is up to 104 times larger than the Banda Sea [ K ρ  = (9.2 ± 0.55) × 10-6 m2s-1] (Alford et al. Geophys Res Lett 26:2741-2744, 1999) or the "open ocean" K ρ = 0.03 × 10-4 m2s-1 within 2° of the equator to (0.4-0.5) × 10-4 m2s-1 at 50°-70° (Kunze et al. J Phys Oceanogr 36:1553-1576, 2006). Therefore, nonlinear interactions between internal tides, tidally induced mixing, and ITF plays a critical role regulating water mass transformation and have strong implications to longer-term variations and change of Pacific-Indian Ocean water circulation and climate. Supplementary Information: The online version contains supplementary material available at 10.1186/s40562-024-00349-3.

Effects of Herd Establishment Time and Structure on Group-on-Individual Aggression Intensity in Farm Pigs.

Aggression in farm animals affects welfare. Although one-on-one aggression was studied, group-on-individual aggression remains unresolved. This study aimed to examine how herd establishment times and structures influence aggression intensity (AI) of herds towards unfamiliar pigs. Six groups of pigs were established, with a new pig added every three days. AI was measured by skin lesion severity on the new pigs. A parabolic model based on the Levenberg-Marquardt algorithm and conjoint analysis identified factors influencing AI. Results show AI was not significantly affected by herd size but was significantly influenced by the number of pens (p < 0.01). AI showed a significant association with elevated time (T) since the establishment of the herd in six pig herds (Kendall's tau-τ = 0.976, p < 0.001). The effect of T on the AI became stronger as T increased, which was consistently validated in six pig herds. Furthermore, the interaction effect indicates a significant difference in AI between herds formed with two pens and those with more than two pens when T ≤ 12 (p < 0.05). However, as T increased beyond 12, the number of pens used to form the herd did not significantly affect AI. These findings highlight the complex interactions between herd establishment time and structural composition in shaping aggression intensity towards unfamiliar pigs.

Characterization of structure and mixing in nanoparticle hetero-aggregates using convolutional neural networks: 3D-reconstruction versus 2D-projection.

Structural and chemical characterization of nanomaterials provides important information for understanding their functional properties. Nanomaterials with characteristic structure sizes in the nanometer range can be characterized by scanning transmission electron microscopy (STEM). In conventional STEM, two-dimensional (2D) projection images of the samples are acquired, information about the third dimension is lost. This drawback can be overcome by STEM tomography, where the three-dimensional (3D) structure is reconstructed from a series of projection images acquired using various projection directions. However, 3D measurements are expensive with respect to acquisition and evaluation time. Furthermore, the method is hardly applicable to beam-sensitive materials, i.e. samples that degrade under the electron beam. For this reason, it is desirable to know whether sufficient information on structural and chemical information can be extracted from 2D-projection measurements. In the present work, a comparison between 3D-reconstruction and 2D-projection characterization of structure and mixing in nanoparticle hetero-aggregates is provided. To this end, convolutional neural networks are trained in 2D and 3D to extract particle positions and material types from the simulated or experimental measurement. Results are used to evaluate structure, particle size distributions, hetero-aggregate compositions and mixing of particles quantitatively and to find an answer to the question, whether an expensive 3D characterization is required for this material system for future characterizations.

Changes in mixed ethnicity households and neighbourhood transitions in England and Wales.

Conventional explanations of neighbourhood ethnic transitions consider what drives differential growth in ethnic group populations without regard to household composition. We enrich these nonhousehold approaches by using consistent Census data on neighbourhoods and households for England and Wales for 2001, 2011 and 2021 to analyse connections between mixed-ethnicity households and neighbourhood ethnic diversity. We employ a neighbourhood typology of ethnic diversity that identifies neighbourhoods as either low- or moderate-diversity, or high-diversity, where no single ethnic group is in the majority. We focus particularly on White-majority and highly diverse neighbourhoods given the dominance of the former in residential spaces in England and Wales, and because they are the principal source of transitions to highly diverse neighbourhoods. Mixed-ethnicity households have become an increasingly important feature of the ethnic diversification of England and Wales; by 2021, almost 15% of multiperson households were mixed, a growth from 12% in 2011 and 9% in 2001. We find that higher levels of neighbourhood ethnic diversity are associated with higher shares of mixed-ethnicity households. In high-diversity neighbourhoods, for example, around 30% of multiperson households (nearly a quarter of a million households) were ethnically mixed in 2021. Levels of household mixing in moderate-diversity White neighbourhoods were considerably higher than in low-diversity White neighbourhoods. The same is found for diversifying neighbourhoods. Neighbourhoods that become more ethnically diverse were typically home to higher rates of mixed-ethnicity households. Stably moderately diverse White neighbourhoods also had a higher proportion of mixed households. Studies of neighbourhood transition that focus on individuals in neighbourhoods may be missing important processes operating in the intimate spaces of the home. Including this intermediate scale of analysis adds to our understanding of neighbourhood ethnic mixing and processes of integration.

Study on the effect of geometrical and operational parameters on performance dynamics of modified rotary blades using DEM.

The geometric features and operational parameters of rotary blades on rotary tillers significantly impact their performance characteristics. The sweepback angle is a geometric feature of the 'L'-shaped rotary blade that has remained unexplored in previous studies. This study aimed to analyze the effect of geometrical and operational parameters on the performance dynamics of the 'L'-shaped rotary blade. The investigation was conducted using the discrete element method (DEM) and further validated through experiments conducted in a soil bin. The simulation experiment was conducted by dividing the particle bed into horizontal particle zones. The effect of the geometrical (sweepback angle) and operational parameters (forward speed, rotational speed, and depth) on the power requirement, disturbance intensity, and mixing index was studied. The novel method was adopted to determine the mixing capability of rotary blades in terms of sub-domain mixing index (SMI) and overall mixing index (OMI). The results revealed that the power requirements for a sweepback angle of 18° were 26.39% and 16.50% lower than those for sweepback angles of 6° and 12°, respectively. The sweepback angle tends to have the least effect on the overall mixing index compared to operational parameters. The average particle velocity decreased by 22.19% and 29.60% with sweepback angles of 12° and 18°, respectively, compared to the sweepback angle of 6°. The relative error during the experiment varied between 1.29% and 13.51%. It was concluded that the sweepback angle was found to be a feasible option for reducing the power requirement with good mixing indices.

Aerosol mixing state, new particle formation, and cloud droplet number concentration in an urban environment.

Anthropogenically derived aerosols have been hypothesized to influence convective precipitation by increasing the available pool of cloud condensation nuclei. Here, we present a synthesis of aerosol size distribution and subsaturated hygroscopicity measurements between 15 and 250 nm diameter particles during the TRacking Aerosol Convection interactions ExpeRiment (TRACER). We found that the aerosol is externally mixed and can be described by a quasi-two-component description comprising a more and less hygroscopic mode. The mean hygroscopicity parameters for these modes across all sizes were 0.03 ± 0.04 and 0.22 ± 0.08 with no significant dependence on particle size. The number fraction of the more hygroscopic mode is 40 % for particles between 15 and 40 nm and gradually increases to ~70 % for particles >100 nm. Winds from the southerly direction feature particles with larger hygroscopicity parameters and have a larger fraction of particles in the more hygroscopic mode. The hygroscopicity parameter exhibits diurnal cycles that are consistent with condensation of a species with a hygroscopicity parameter ~0.1 which corresponds to values expected for secondary organic aerosol. We also identified nine small particle events that were attributed to particle formation by nucleation. The data are consistent with new particle formation having occurred aloft, followed by downward mixing with daytime turbulence. The species that are responsible for modal growth had hygroscopicity parameters varying between 0.05 and 0.34. These values systematically depended on the wind sector, suggesting that the chemical composition of the precursors differed. Hourly cloud condensation nuclei (CCN) and cloud droplet number concentration (CDNC) values derived from the aerosol size distribution, subsaturated hygroscopicity measurements, and adiabatic parcel model simulations showed a dynamic range of a factor of 2-3 in CDNC depending on the wind sector, with lower values associated with southerly onshore flow.

Effects of storm events on nutrient characteristics in a stratified drinking water reservoir: Behavior, transmission pathways and management strategy.

Storm events result in nutrient fluctuations and deterioration of reservoir water supply quality. Understanding of nutrient dynamics (e.g., concentration, composition, loads and transport pathways) and adoption of effective management strategies are critical for safeguarding water quality. A comprehensive monitoring was conducted for three storm events during the rainy season in 2023. Results showed nitrogen (N) and phosphorus (P) dynamics demonstrate a significant response to hydrological process. Rainfall resulted in the highest event mean concentrations (EMCs) of total nitrogen (TN), nitrate nitrogen (NO3--N), ammonia nitrogen (NH4+-N), total phosphorus (TP), and particulate phosphorus (PP) in the runoff being 1.97, 2.15, 2.30, 44.17, and 62.38 times higher than those observed in baseflow. On average, NO3--N/PP accounted for 82 %/96 % of N/P exports. Hysteresis analyses reveal that NH4+-N and PP were mainly transported by surface runoff from over-land sources, whereas TN and NO3--N were primarily delivered by subsurface runoff. Additionally, nutrient concentrations were significantly higher in the intrusive layer in reservoir compared to the pre-storm period, which gradually decreased from the tail to the head as particulate sedimentation and water column mixing occurred. Water-lifting-aerators (WLAs) were employed to alter the reservoir thermal stratification regime via artificial mixing to affect the intrusive layer of storm runoff. Comparison of the intrusive layer for three storms reveals that WLAs triggers the storm runoff to form an underflow via increasing the reservoir bottom water temperature above that the runoff, ensuring that water quality at the intake position remains unaffected by inflows. These findings serve as a reference for the response of reservoir eutrophication levels to storm events and present practical engineering experience for enhancing water quality safety during the rainy season.

To Eat or Not to Eat: Novel Stable Isotope Models Reveal a Shift in Carnivory with Nutrient Availability for Aquatic Utricularia spp.

BACKGROUND AND AIMS: Freshwater nitrogen inputs are increasing globally, altering the structure and function of wetland ecosystems adapted to low nutrient conditions. Carnivorous wetland plants, Utricularia spp., are hypothesised to reduce their reliance on carnivory and increase their assimilation of environmental nutrients when the supply of ambient nutrients increases. Despite success in using stable isotope approaches to quantify carnivory of terrestrial carnivorous plants, quantifying carnivory of aquatic Utricularia requires improvement. METHODS: We developed stable isotope mixing models to quantify aquatic plant carnivory and used these models to measure dietary changes of three Utricularia species: Utricularia australis, U. gibba, and U. uliginosa in 11 wetlands across a 794 km gradient in eastern Australia. Diet was assessed using multiple models that compared variations in the natural abundance nitrogen isotope composition (δ15N) of Utricularia spp. with that of non-carnivorous plants, and environmental and carnivorous nitrogen sources. KEY RESULTS: Carnivory supplied 40 - 100 % of plant nitrogen. The lowest carnivory rates coincided with the highest availability of ammonium and dissolved organic carbon. CONCLUSIONS: Our findings suggest that Utricularia populations may adapt to high nutrient environments by shifting away from energetically costly carnivory. This has implications for species conservation as anthropogenic impacts continue to affect global wetland ecosystems.

Excipient-Induced Lattice Disorder in Active Pharmaceutical Ingredient: Implications on Drug Product Continuous Manufacturing.

Our previous work (Mol Pharm, 20 (2023) 3427) showed that crystalline excipients, specifically anhydrous dibasic calcium phosphate (DCPA), facilitated the dehydration of carbamazepine dihydrate (CBZDH) and the formation of an amorphous product phase during the mixing stage of continuous tablet manufacturing. Understanding the mechanism of this excipient-induced effect was the object of this study. Blending with DCPA for 15 min caused pronounced lattice disorder in CBZDH. This was evident from the 190% increase in the apparent lattice strain determined by the Williamson-Hall plot. The rapid dehydration was attributed to the increased reactivity of CBZDH caused by this lattice disorder. Lattice disorder in CBZDH was induced by a second method, cryomilling it with DCPA. The dehydration was accelerated in the milled sample. Annealing the cryomilled sample reversed the effect, thus confirming the effect of lattice disorder on the dehydration kinetics. The hardness of DCPA appeared to be responsible for the disordering effect. DCPA exhibited a similar effect in other hydrates, thereby revealing that the effect was not unique to CBZDH. However, its magnitude varied on a case-by-case basis. The high shear powder mixing was necessary for rapid and efficient powder mixing during continuous drug product manufacturing. The mechanical stress imposed on the CBZDH, and exacerbated by DCPA, caused this unexpected destabilization.

Image data augmentation techniques based on deep learning: A survey.

In recent years, deep learning (DL) techniques have achieved remarkable success in various fields of computer vision. This progress was attributed to the vast amounts of data utilized to train these models, as they facilitated the learning of more intricate and detailed feature information about target objects, leading to improved model performance. However, in most real-world tasks, it was challenging to gather sufficient data for model training. Insufficient datasets often resulted in models prone to overfitting. To address this issue and enhance model performance, generalization ability, and mitigate overfitting in data-limited scenarios, image data augmentation methods have been proposed. These methods generated synthetic samples to augment the original dataset, emerging as a preferred strategy to boost model performance when data was scarce. This review first introduced commonly used and highly effective image data augmentation techniques, along with a detailed analysis of their advantages and disadvantages. Second, this review presented several datasets frequently employed for evaluating the performance of image data augmentation methods and examined how advanced augmentation techniques can enhance model performance. Third, this review discussed the applications and performance of data augmentation techniques in various computer vision domains. Finally, this review provided an outlook on potential future research directions for image data augmentation methods.

Mechanistic insights into how mixing factors govern polyelectrolyte-surfactant complexation in RNA lipid nanoparticle formulation.

HYPOTHESIS: Lipid nanoparticle self-assembly is a complex process that relies on ion pairing between nucleic acids and hydrophobic cationic lipid counterions for encapsulation. The chemical factors influencing this process, such as formulation composition, have been the focus of recent research. However, the physical factors, particularly the mixing protocol, which directly modulates these chemical factors, have yet to be mechanistically examined using a reproducible mixing platform comparable to the industry standard. We here utilize Flash NanoPrecipitation (FNP), a scalable rapid mixing platform, to isolate and systematically investigate how mixing factors influence this complexation step, first by using a model polyelectrolyte-surfactant system and then generalizing to a typical RNA lipid nanoparticle formulation. EXPERIMENTS: Aqueous polystyrene sulfonate (PSS) and cetrimonium bromide (CTAB) solutions are rapidly homogenized using reproducible FNP mixing and controlled flow rates at different stoichiometric ratios and total solids concentrations to form polyelectrolyte-surfactant complexes (PESCs). Then, key mixing factors such as total flow rate, inlet stream relative volumetric flow rate, and magnitude of flow fluctuation are studied using both this PESC system and an RNA lipid nanoparticle formulation. FINDINGS: Fluctuations in flow as low as ± 5 % of the total flow rate are found to severely compromise PESC formation. This result is replicated in the RNA lipid nanoparticle system, which exhibited significant differences in size (132.7 nm vs. 75.6 nm) and RNA encapsulation efficiency (34.0 % vs. 82.8 %) under fluctuating vs. steady flow. We explain these results in light of the chemical variables isolated and studied; slow or nonuniform mixing generates localized concentration gradients that disrupt the balance between the hydrophobic and electrostatic forces that drive complex formation. These experiments contribute to our understanding of the complexation stage of lipid nanoparticle formation and provide practical insights into the importance of developing controlled mixing protocols in industry.