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The celestial rubbish dump
No full textAbstract
Mike Lockwood explores the frontier mentality and what it means for astronomy and access to space in his President's Address, given in May 202
Synthesis and investigation of albumin nanoparticles loaded with anti-tuberculosis drug Isoniazid
No full textThe development of novel treatment strategies for tuberculosis (TB), including its multidrug-resistant forms, remains a global health priority. Conventional first- and second-line anti-TB drugs are often incorporated into polymer-based delivery systems to improve efficacy and reduce side effects. Among biodegradable, non-toxic, and biocompatible polymers, human serum albumin (HSA) stands out as a highly promising drug carrier. In this study, isoniazid (INH)-loaded human serum albumin nanoparticles were synthesized via the reaction of HSA macromolecules with cysteine in the presence of urea. Key nanoparticles characteristics—including size, polydispersity, drug loading efficiency, and drug binding capacity—were systematically evaluated and optimized. The effects of various formulation parameters, such as solution pH and concentration of urea, cysteine, albumin, and isoniazid, were investigated. Conformational changes in the protein structure were assessed using spectrofluorometric analysis. Additionally, the physicochemical properties and in vitro drug release profiles of HSA-INH nanoparticles were characterized. The antimicrobial activity of the nanoparticles was tested against the wild-type Mycobacterium tuberculosis H37Rv strain at isoniazid concentrations of 5, 25, and 50 mg/mL. The minimum inhibitory concentration of isoniazid when delivered via HSA nanoparticles was also determined
The overlooked impact of background diet and adherence in nutrition trials
Get PDFRandomised controlled trials in nutrition (RCTN) face unique challenges, including the considerable influence of the background diet and the challenge of assuring intervention adherence by participants. The impact of these factors on the outcome of RCTNs has been difficult to quantify, but nutritional biomarkers represent a valuable tool to address these challenges. Using flavanols as a model dietary intervention and a set of recently validated flavanol biomarkers, we here investigated the impact of background diet and adherence on the outcomes of a subcohort of the COcoa Supplement and Multivitamin Outcomes Study (COSMOS, NCT 02422745). We found that 20% of participants in the placebo and cocoa-extract intervention arms had a flavanol background intake as high as the intervention, and only 5% did not consume any flavanols. Approximately 33% of participants in the intervention group did not achieve expected biomarker levels from the assigned intervention – more than the 15% estimated with pill-taking questionnaires usually implemented in RCTN. Taking these factors into account resulted in a larger effect size for all observed endpoints (HR (95% CI)) estimated using intention-to-treat vs. per-protocol vs. biomarker-based analyses: total cardiovascular disease (CVD) events 0.83 (0.65; 1.07); 0.79 (0.59; 1.05); 0.65 (0.47; 0.89) – CVD mortality 0.53 (0.29; 0.96); 0.51 (0.23; 1.14); 0.44 (0.20; 0.97) – all-cause mortality 0.81 (0.61; 1.08); 0.69 (0.45; 1.05); 0.54 (0.37; 0.80) –– major CVD events 0.75 (0.55; 1.02); 0.62 (0.43; 0.91); 0.48 (0.31; 0.74). These results highlight the importance of taking background diet and adherence into consideration in RCTN to obtain more reliable estimates of outcomes through nutritional biomarker-based analyses
Advancing landscape characterisation: a comparative study of machine learning and manual classification methods
Get PDFThis study evaluates and compares three automated classification methods for Landscape Character Assessment (LCA) to assess their suitability for consistent, objective, and scalable mapping. We applied One-pass Multi-view Clustering (OPMC), Self-Organising Feature Map clustering (SOFM), and Swin Transformer Segmentation Clustering (STSC) to classify Landscape Character Types in Bannau Brycheiniog National Park, Wales, UK. Their outputs were compared against an expert-based manual classification (EBMC) using pixel-by-pixel accuracy assessment. To interpret model outputs, we used SHapley Additive exPlanations analysis to quantify the influence of key landscape character elements on classification outcomes. STSC showed the highest agreement with EBMC, followed by SOFM and OPMC. Across all models, geology, historic landscape, and soil type were the most influential variables, while habitat and landform contributed less. The automated methods demonstrated strong spatial coherence and boundary delineation comparable to expert-based mapping. Our findings demonstrate the potential of automated approaches to improve the consistency, efficiency, and objectivity of LCA and support their integration into scalable landscape characterisation frameworks for planning and management applications. Source code and datasets are available on GitHub (https://github.com/TingtingHwang/BBNP_LCA)
Wavenumber-explicit bounds on boundary integral operators for acoustic scattering by bounded sound-soft obstacles
No full textRecently, a new first kind boundary integral equation (BIE) formulation was
obtained in (Caetano et al 2025, Proc. R. Soc. A, 481: 20230650) for sound-soft scattering
by an arbitrary compact scatterer Γ ⊂ R
n. The operator Ak : H
−1
Γ → (H
−1
Γ
)
∗
, introduced in that paper, where H
−1
Γ
:= {ϕ ∈ H−1
(R
n) : supp(ϕ) ⊂ Γ} and (H
−1
Γ
)
∗
is its dual
space, relates to the acoustic Newtonian potential in free space. Furthermore, existence and
uniqueness of a solution to the scattering problem holds if and only if Akϕ = g has a solution
ϕ ∈ H
−1
Γ
for a given g which is directly related to the Dirichlet boundary conditions on Γ.
The invertibility of Ak, for various values of k, depends on whether Γ
c
:= R
n \ Γ has any
bounded components. Although, in general, Ak is not invertible for all k > 0, we obtain
wavenumber-explicit bounds “for most wavenumbers” for the norm of the inverse operator
A
−1
k
, which depend both on a resolvent estimate for the Dirichlet Laplacian on bounded
components of Γ
c
, and an improved version of the cut-off resolvent estimate for unbounded
domains of (Lafontain et al 2021, Comm. Pure Appl. Math., 74: 2025-2063)
Cooperative learning in sixth form supervised study
Get PDFThis research study investigated the effectiveness of the cooperative learning method, Stratified Team
Achievement Divisions (STAD), in improving student progress and motivation within Sixth Form
Supervised Study lessons outside of a traditional classroom setting. The study took place in a large
secondary school in the UK and focused on students from a Year 13 A Level Business Studies class.
Supervised study lessons were identified as an area where this intervention could have a positive impact,
as students who attended these sessions often lacked motivation and direction in this timetabled study
lesson, resulting in limited academic progress to be made. This study aimed to address this issue through
the implementation of Stratified Team Achievement Divisions (STAD) (Slavin, 1989) within these
supervised study periods.
The 20 students from the researcher’s Year 13 A Level Business class were divided into five equal groups,
organised by when their individual supervised study schedules matched. Following initial training on how
to work as a group, each group met as a collective over the six-week cycle to work on a range of stimulus
provided by the subject teacher. Students were then assessed through weekly quizzes, with scores
contributing to the group total positive points based on individual improvements each week. In addition
to the quiz data, other factors were analysed using group observations and focus groups with select
student participants. Data, including attendance figures and attitude to learning scores, were also used
to triangulate the findings.
The findings suggest that the STAD model positively impacted student motivation and progress for some
in the intervention. Higher ability students, for example, often helped lower ability peers, fostering a
supportive learning environment. Attendance and active participation within the groups were critical
factors in the success of the intervention. Variability in student attendance and engagement affected
overall group performance. Higher ability students also sometimes felt they were not benefiting as much
from the group work, and the absence of continuous teacher support during group meetings was also a
significant limitation, resulting in disengagement from some participants.
Recommendations for future research and practice include encouraging consistent attendance and active
participation in group STAD meetings when conducted outside of the classroom. It is also suggested that
there is an essential requirement for continuous additional training and guidance for students on effective
group work strategies to maximise this intervention’s effectiveness. Other Sixth Forms looking to use this
cooperative approach might also consider incorporating additional support and supervision from those
who run the supervised study area to enhance the effectiveness of the STAD model. Overall, the study
concludes that while the STAD cooperative learning method can improve student motivation and progress
in a supervised study setting, its success is highly dependent on student engagement, attendance, and
the level of teacher support provided
Noncausal AR-ARCH model and its applications to financial time series
Get PDFWe extend the noncausal autoregressive models by introducing noncausality into the variance component, allowing the volatility to depend on future prices as well. We refer this model as noncausal AR-ARCH model, and it enables us to account for shocks arsing from market agents who possess more information and engage in forward-looking trading behaviors, leading to a better fit for financial time series. In terms of parameter estimation, we develop a quasi-maximum likelihood estimation method and establish its asymptotic properties. Building on this, we propose three hypothesis testing statistics to determine whether the data exhibits a noncausal AR structure and whether the innovation term follows a noncausal ARCH model. The simulation results demonstrate the consistency of the parameter estimation as well as the good size control and high power of the hypothesis tests in detecting noncausal structures. In our empirical applications, we employ the proposed model in both stock markets and crude oil futures markets. Our empirical findings indicate that the variance is causal in the US stock market but noncausal in the Chinese stock market. Furthermore, we observe a noticeable distinction between Brent and WTI crude oil futures, as Brent exhibits noncausality in both its mean and variance, whereas WTI follows a purely causal process
Toward a marginal Arctic sea ice cover: changes to freezing, melting and dynamics
Get PDFAs the summer Arctic sea ice extent has retreated, the marginal ice zone (MIZ) has been widening. The MIZ is defined as the region of the ice cover that is influenced by waves and for convenience here is defined as the region of the ice cover between sea ice concentrations (SIC) of 15 % to 80 %. The MIZ is projected to become a larger percentage of the summer ice cover, as the Arctic transitions to ice-free summers. Using numerical simulations, we explicitly compare, for the first time, individual processes of ice volume gain and loss in the ice pack (SIC > 80 %) to those in the MIZ to establish and contrast their relative importance and examine how these processes change as the summer MIZ fraction increases over time. We use an atmosphere-forced, physics-rich, sea-ice-mixed layer model based on CICE, that includes a joint prognostic floe size and ice thickness distribution (FSTD) model including brittle fracture and form drag. We demonstrate that this model is realistic using satellite observations of sea ice extent and PIOMAS (the Pan-Arctic Ice Ocean Modeling and Assimilation System) estimates of thickness. A comparable setup has also been compared to floe size distribution (FSD) observations in prior studies. The MIZ fraction of the July sea ice cover, when the MIZ is at its maximum extent, increases by a factor of 2 to 3, from 14 % (20 %) in the 1980s to 46 % (50 %) in the 2010s in NCEP (HadGEM2-ES) atmosphere-forced simulations. In a HadGEM2-ES forced projection, the July sea ice cover is almost entirely MIZ (93 %) in the 2040s. Basal melting accounts for the largest proportion of melt in regions of pack ice and MIZ for all time periods. During the historical period, top melt is the next largest melt term in pack ice, but in the MIZ, top melt and lateral melt are comparable. This is due to a relative increase of lateral melting and a relative reduction of top melting by a factor of 2 in the MIZ compared to the pack ice. The volume fluxes due to dynamic processes decrease due to the reduction in ice volume in both the MIZ and pack ice. For areas of sea ice that transition to being MIZ in summer, we find an earlier melt season: in the region that was pack ice in the 1980s and became MIZ in the 2010s, the peak in the total melt volume flux occurs 20(12) d earlier. This continues in the projection where melting in the region that becomes MIZ in the 2040s shifts 14 d earlier compared to the 2010s. Our analysis shows that a different balance of processes controls the volume budget of the MIZ versus the pack ice. We also find that the balance of processes is different for the MIZ in the 2040s compared to the 1980s, and conclude that we cannot understand the disposition between basal, lateral and top melt in a future Arctic solely based on increased MIZ fraction, since changes in surface energy balance remain a strong control on these behaviours