Evidence for the existence of powder sub-populations in micronized materials : Aerodynamic size-fractions of aerosolized powders possess distinct physicochemical properties

This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.Purpose: To investigate the agglomeration behaviour of the fine ( 12.8 µm) particle fractions of salmeterol xinafoate (SX) and fluticasone propionate (FP) by isolating aerodynamic size fractions and characterising their physicochemical and re-dispersal properties. Methods: Aerodynamic fractionation was conducted using the Next Generation Impactor (NGI). Re-crystallized control particles, unfractionated and fractionated materials were characterized for particle size, morphology, crystallinity and surface energy. Re-dispersal of the particles was assessed using dry dispersion laser diffraction and NGI analysis. Results: Aerosolized SX and FP particles deposited in the NGI as agglomerates of consistent particle/agglomerate morphology. SX particles depositing on Stages 3 and 5 had higher total surface energy than unfractionated SX, with Stage 5 particles showing the greatest surface energy heterogeneity. FP fractions had comparable surface energy distributions and bulk crystallinity but differences in surface chemistry. SX fractions demonstrated higher bulk disorder than unfractionated and re-crystallized particles. Upon aerosolization, the fractions differed in their intrinsic emission and dispersion into a fine particle fraction (< 5.0 µm). Conclusions: Micronized powders consisted of sub-populations of particles displaying distinct physicochemical and powder dispersal properties compared to the unfractionated bulk material. This may have implications for the efficiency of inhaled drug deliveryPeer reviewe

Measurement of the 1S0^{1}S_{0} neutron-neutron effective range in neutron-deuteron breakup

We report the most precise determination of the $^{1}S_{0}$ neutron-neutron effective range parameter $(r_{nn})$ from neutron-neutron quasifree scattering in neutron-deuteron breakup. The experiment setup utilized a collimated beam of 15.5 MeV neutrons and an array of eight neutron detectors positioned at angles sensitive to several quasifree scattering kinematic configurations. The two neutrons emitted from the breakup reaction were detected in coincidence and time-of-flight techniques were used to determine their energies. The beam-target luminosity was measured in-situ with the yields from neutron-deuteron elastic scattering. Rigorous Faddeev-type calculations using the CD Bonn nucleon-nucleon potential were fit to our cross-section data to determine the value of $r_{nn}$. The analysis was repeated using a semilocal momentum-space regularized $N^{4}LO^{+}$ chiral interaction potential. We obtained values of $r_{nn}=2.86 \pm 0.01 (stat) \pm 0.10 (sys)$ fm and $r_{nn}=2.87 \pm 0.01 (stat) \pm 0.10 (sys)$ fm using the CD Bonn and $N^{4}LO^{+}$ potentials, respectively. Our results are consistent with charge symmetry and previously reported values of $r_{nn}$

A Bayesian Belief Network to assess rate of changes in coral reef ecosystems

It is crucial to identify sources of impacts and degradation to maintain functions and services that the physical structure of coral reef provides. Here, a Bayesian Network approach is used to evaluate effects that anthropogenic and climate change disturbances have on coral reef structure. The network was constructed on knowledge derived from the literature and elicited from experts, and parameterised on independent data. Evaluation of the model was conducted through sensitivity analyses and data integration was fundamental to obtain a balanced dataset. Scenario analyses, conducted to assess the effects of stressors on the reef framework state, suggested that calcifying organisms and carbonate production, rather than bioerosion, had the largest influence on the reef carbonate budgetary state. Despite the overall budget remaining positive, anthropogenic pressures, particularly deterioration of water quality, affected reef carbonate production, representing a warning signal for potential changes in the reef state

Formulation Pre-screening of Inhalation Powders Using Computational Atom–Atom Systematic Search Method

The synthonic modeling approach provides a molecule-centered understanding of the surface properties of crystals. It has been applied extensively to understand crystallization processes. This study aimed to investigate the functional relevance of synthonic modeling to the formulation of inhalation powders by assessing cohesivity of three active pharmaceutical ingredients (APIs, fluticasone propionate (FP), budesonide (Bud), and salbutamol base (SB)) and the commonly used excipient, α-lactose monohydrate (LMH). It is found that FP (−11.5 kcal/mol) has a higher cohesive strength than Bud (−9.9 kcal/mol) or SB (−7.8 kcal/mol). The prediction correlated directly to cohesive strength measurements using laser diffraction, where the airflow pressure required for complete dispersion (CPP) was 3.5, 2.0, and 1.0 bar for FP, Bud, and SB, respectively. The highest cohesive strength was predicted for LMH (−15.9 kcal/mol), which did not correlate with the CPP value of 2.0 bar (i.e., ranking lower than FP). High FP–LMH adhesive forces (−11.7 kcal/mol) were predicted. However, aerosolization studies revealed that the FP–LMH blends consisted of agglomerated FP particles with a large median diameter (∼4–5 μm) that were not disrupted by LMH. Modeling of the crystal and surface chemistry of LMH identified high electrostatic and H-bond components of its cohesive energy due to the presence of water and hydroxyl groups in lactose, unlike the APIs. A direct comparison of the predicted and measured cohesive balance of LMH with APIs will require a more in-depth understanding of highly hydrogen-bonded systems with respect to the synthonic engineering modeling tool, as well as the influence of agglomerate structure on surface–surface contact geometry. Overall, this research has demonstrated the possible application and relevance of synthonic engineering tools for rapid pre-screening in drug formulation and design

Participatory modelling for stakeholder involvement in the development of flood risk management intervention options

Advancing stakeholder participation beyond consultation offers a range of benefits for local flood risk management, particularly as responsibilities are increasingly devolved to local levels. This paper details the design and implementation of a participatory approach to identify intervention options for managing local flood risk. Within this approach, Bayesian networks were used to generate a conceptual model of the local flood risk system, with a particular focus on how different interventions might achieve each of nine participant objectives. The model was co-constructed by flood risk experts and local stakeholders. The study employs a novel evaluative framework, examining both the process and its outcomes (short-term substantive and longer-term social benefits). It concludes that participatory modelling techniques can facilitate the identification of intervention options by a wide range of stakeholders, and prioritise a subset for further investigation. They can help support a broader move towards active stakeholder participation in local flood risk management

Capturing Ecosystem Services, Stakeholders' Preferences and Trade-Offs in Coastal Aquaculture Decisions : A Bayesian Belief Network Application

Aquaculture activities are embedded in complex social-ecological systems. However, aquaculture development decisions have tended to be driven by revenue generation, failing to account for interactions with the environment and the full value of the benefits derived from services provided by local ecosystems. Trade-offs resulting from changes in ecosystem services provision and associated impacts on livelihoods are also often overlooked. This paper proposes an innovative application of Bayesian belief networks - influence diagrams - as a decision support system for mediating trade-offs arising from the development of shrimp aquaculture in Thailand. Senior experts were consulted (n = 12) and primary farm data on the economics of shrimp farming (n = 20) were collected alongside secondary information on ecosystem services, in order to construct and populate the network. Trade-offs were quantitatively assessed through the generation of a probabilistic impact matrix. This matrix captures nonlinearity and uncertainty and describes the relative performance and impacts of shrimp farming management scenarios on local livelihoods. It also incorporates export revenues and provision and value of ecosystem services such as coastal protection and biodiversity. This research shows that Bayesian belief modeling can support complex decision-making on pathways for sustainable coastal aquaculture development and thus contributes to the debate on the role of aquaculture in social-ecological resilience and economic development