A Story of Three Levels of Sophistication in SCF/KS-DFT Orbital Optimization Procedures.

In this work, three versions of self-consistent field/Kohn-Sham density functional theory (SCF/KS-DFT) orbital optimization are described and benchmarked. The methods are a modified version of the geometry version of the direct inversion in the iterative subspace approach (which we call r-GDIIS), the modified restricted step rational function optimization method (RS-RFO), and the novel subspace gradient-enhanced Kriging method combined with restricted variance optimization (S-GEK/RVO). The modifications introduced are aimed at improving the robustness and computational scaling of the procedures.

Unveiling the language of scars: A patient-centric themed framework for comprehensive scar morphology.

Background: Scarring, a pervasive issue spanning across medical disciplines, lacks a comprehensive terminology for effective communication, patient engagement, and outcome assessment. Existing scar classification systems are constrained by specific pathologies, physician-centric features, and inadequately account for emerging technologies. This study refrains from proposing yet another classification system and instead revisits the foundational language of scar morphology through a theme analysis of primary patient complaints.

Sharps and needlestick injuries within the operating room: Risk prone procedures and prevalence meta-analysis.

Background: Sharps and needlestick injuries pose a serious risk to operating theatre personnel with considerable morbidity, mortality and healthcare implications. The cost of prophylaxis and post-exposure treatment is a significant institutional economic burden.

Aim: The aim of the review was to identify the prevalence of sharps and needlestick injury within the operating theatre and to establish the most common critical steps.

Exploring a hospital's response to children who have no fixed address.

Objective: To explore how a tertiary metropolitan public healthcare provider supported children who presented with 'no fixed address' (NFA).

Methods: A retrospective data mining of the electronic medical records of patients with an NFA classification, over 12 months period.

Results: Data mining identified 475 NFA patients, 6% were children.