Research works

Work patterns and time allocation in multidisciplinary home hospice: a time-motion study

Abstract Introduction : The delivery of home hospice care involves complex logistical and clinical demands. Standard administrative metrics fail to capture the nuanced workload of this distributed ecosystem. This study aimed to characterize the workday structure and identify oper...

Efficient coding predicts synaptic conductance

Abstract Retinothalamic and thalamocortical synapses are efficient in the sense that each synapse conveys as many bits per Joule as possible, but efficiency falls rapidly if synaptic conductance deviates from its natural value Harris et al. (2015, 2019). However, the manner in wh...

Cloud-based Electronic Health Records (EHR) adoption rate in Nigeria: barriers and performance bottlenecks

Abstract Background While cloud-based Electronic Health Records (EHRs) are crucial to improving service quality and operational efficiency, uptake is still variable across low-income and middle-income countries (LMICs). There is a significant research gap in Nigeria in terms of e...

Asymptotics of ruin probabilities in a subordinated Cramér-Lundberg model

We study a dynamic model of a non-life insurance portfolio. The foundation of the model is a compound Poisson process that represents the claims side of the insurer. To introduce clusters of claims appearing, e.g. with catastrophic events, this process is time-changed by a Lévy s...

A Non‐Isothermal Viscoplastic Framework for Assessing Shaft Resistance in Energy Geostructures

ABSTRACT This study presents a coupled thermo‐hydro‐mechanical (THM) num erical investigation of shaft resistance degradation in geothermal piles embedded in low‐permeability clays. A thermo‐viscoplastic constitutive model is developed to simulate the pile–soil interface behavior...

Humans in the Loop: The Next Frontier in the Credibility Revolution

Something is amiss in empirical economics. Despite the advances of the credibility revolution, published estimates tend to be inflated and overconfident. We argue that this stems from a weakness in the dominant econometric framework: treating the researcher like a calculator that...

Analysis of Eigenvalue Clustering Leads to Optimal Scaling in Numerical Radiative Transfer

ABSTRACT We consider a multidimensional polychromatic radiative transfer (RT) problem, accounting for scattering processes in a general form, that is, anisotropic (dipole) scattering with partial frequency redistribution. Given a discrete ordinates () discretization, we report th...

Universal Functions for Topological Correlators

Abstract We consider correlation functions of topologically twisted, $$\mathcal {N}=2$$ N = 2 supersymmetric Yang–Mills theory with gauge group $$\textrm{SU}(2)$$ SU ( 2 ) and $$N_f\le 3$$ N f ≤ 3 massive hypermultiplets in the fundamental representation. For a smooth, oriented,...

Mapping spatial colleague connectivity patterns from individual-level registry data to inform regional pandemic interventions

A concern in infectious disease modelling is how accurately population mixing is incorporated, as it shapes the type and frequency of contacts through which infection spreads, and consequently, estimated intervention effectiveness. Although synthesizing mixing patterns from diary...

Knowledge, Attitudes and Practices (KAP) on Dengue Fever in Burkina Faso: Findings from the national household survey in Burkina Faso

Abstract Background Dengue fever is an emerging public health concern in Burkina Faso, with increasing outbreaks and data gaps in population awareness. This study assessed knowledge, attitudes, and practices (KAP) related to dengue fever in all health regions of the country. Meth...

Ontology-Guided Neuro-Symbolic Inference: Grounding Language Models with Mathematical Domain Knowledge

Language models exhibit fundamental limitations---hallucination, brittleness, and lack of formal grounding---that are particularly problematic in high-stakes specialist fields requiring verifiable reasoning. I investigate whether formal domain ontologies can enhance language mode...

INPP5E interactome reveals novel connections to growth factor signaling

Abstract Primary cilia are sensory cell membrane protrusions whose malfunction causes diseases known as ciliopathies. Joubert syndrome (JBTS) is a rare recessive ciliopathy causing brain malformations and kidney cysts, among other manifestations. A key player in JBTS is INPP5E, a...

Causal Memory Gravity V: Continuum Limit and Emergent Quantum Dynamics from Discrete Planck Networks

Causal Memory Gravity V develops the conditional continuum-limit and emergent quantum-dynamics sector of the CMG/DPN framework. It identifies the assumptions under which Dynamic Planck Network dynamics can produce effective continuum fields, conformal geometry, wave equations, an...

Resolving systematic errors in sulfate source apportionment: a field-validated kinetic isotope fractionation framework

Abstract. Sulfates are critical constituents of atmospheric fine particulate matter (PM2.5) that significantly influence air quality and climate dynamics. While stable isotope fractionation analysis is a powerful tool for tracing atmospheric sulfate formation mechanisms, conventi...

Mean regression for (0, 1) responses via beta scale mixtures

Abstract To achieve greater flexibility for modelling heavy-tailed responses on the unit interval, a beta scale mixture (BSM) regression model is proposed. The conditional response is assigned a mean-parameterised beta distribution whose variability parameter is scaled by a mixin...

Taxation, legitimacy, and media discourse in Jordan

This study investigates how taxation is discursively constructed in Jordanian media as a contested domain of legitimacy, authority, and citizenship. Using qualitative Critical Discourse Analysis, it integrates a dialectical–relational and a socio-cognitive perspective to examine...

Full event interpretation with machine-learning-based particle-flow reconstruction in the CMS detector

Abstract The particle-flow (PF) algorithm constructs a global description of each particle collision by producing a comprehensive list of final-state particles, and is central to event reconstruction in the CMS experiment at the CERN LHC. The existing PF implementation relies on...

How to train your resistive network: Generalized equilibrium propagation and analytical learning

Machine learning is a powerful method of extracting meaning from data; unfortunately, current digital hardware is extremely energy-intensive. There is interest in an alternative analog computing implementation that could match the performance of traditional machine learning while...

Mass univariate aggregation methods for machine learning in neuroscience

Machine learning is a ubiquitous part of the modern neuroimaging toolkit, particularly for research aimed towards precision medicine goals of improving individual-level diagnosis and treatment. However, the high dimensionality of neuroimaging data poses significant challenges for...

Affect labeling down-regulates amygdala only in a dominant native language

A successful strategy to down-regulate emotions is to simply label them (e.g., saying “I’m sad” when feeling sad). It however remains unresolved which mechanism is responsible for the efficacy of this approach known as affect labeling. Here, we constrain the proposed mechanisms o...