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Surgery and positive Bakry–Émery Ricci curvature
Get PDFWe consider the problem of preserving weighted Riemannian metrics of positive Bakry-Émery Ricci curvature along surgery. We establish two theorems of this type: One for connected sums, and one for surgeries along higher-dimensional spheres. In contrast to known surgery results for positive Ricci curvature, these results are local, i.e. we only impose assumptions on the weighted metric locally around the sphere along which the surgery is performed. As application we then show that all closed, simply-connected spin 5-manifolds admit a weighted Riemannian metric of positive Bakry-Émery Ricci curvature. By a result of Lott, this also provides new examples of manifolds with a Riemannian metric of positive Ricci curvature
A consensus statement on the management of vertebral fractures in CKD stages G4–G5D
Get PDFSkeletal fragility has long been overlooked by the nephrology community despite patients with chronic kidney disease (CKD) facing double the risk of hip fracture compared with the general population. Consequently, the term CKD-associated osteoporosis was recently coined to increase awareness. In this context, vertebral fractures are even less studied. Vertebral fractures predict increased fracture risk, and especially in advanced CKD, show a strong association with aortic and iliac vascular calcifications and cardiovascular events such as myocardial infarction. The scope of the present consensus paper is to comprehensively discuss the management of skeletal fragility in CKD patients, from diagnosis to treatment, with a particular focus on vertebral fractures in CKD G4–G5D
A multivariate decomposition analysis of drivers of overweight and obesity among Ghanaian women
Get PDFBackground
Overweight and obesity are rising globally, with Ghana experiencing significant increases among women over the past two decades, raising public health concerns. This study aimed to identify and quantify the key drivers of overweight and obesity among women of reproductive age in Ghana, analysing how these factors have contributed to prevalence changes over time.
Methods
Data from the 2003, 2008, 2014, and 2022 Ghana Demographic and Health Surveys were analysed using binary logistic regression to assess associations with factors such as age, wealth, and education. Multivariate decomposition analysis quantified the contributions of these factors to the observed increases in overweight and obesity prevalence over time.
Results
Here we show overweight and obesity among Ghanaian women rise significantly, reaching 43% in 2022. Key drivers of change in overweight and obesity include wealth, education, urban residence, age, and region. Women in the wealthiest quintile have three times the odds of overweight (aOR: 3.07 [2.02–4.67]) and over six times the odds of obesity (aOR: 6.73 [3.80–11.91]) compared to the poorest quintile. Decomposition analysis shows that 22.5% of the increase in prevalence was due to changes in population characteristics, such as marital and educational status.
Conclusions
Our findings reveal that socio-demographic changes in society, beyond individual behavioural factors, drive the rising overweight and obesity prevalence among Ghanaian women of childbearing age. These findings highlight the dynamic factors influencing weight outcomes and the need for tailored strategies addressing the diverse and evolving determinants of overweight and obesity in Ghanaian women
Historical data-driven self-learning control of battery charging with convex mapping constraints
Get PDFThermal conditions significantly influence the battery performance and degradation, and thermal management is vital for the safe, efficient, and reliable operation of battery-powered systems such as grid-tied energy storage and electric vehicles. However, it is challenging to achieve rapid charging while minimizing the thermal impact on battery health, particularly the more critical internal battery temperature is often overlooked. Therefore, an intelligent charging control strategy is essential for effectively managing the thermal effects and enhancing charging efficiency. Given that battery charging is a highly repetitive process throughout the entire life of battery-powered systems, the historical operation data has a significant potential in the design of an effective charging control strategy. This paper proposes a novel historical data-driven self-learning control approach to iteratively optimize the battery charging strategy by applying convex mapping constraints derived from historical state information. This approach introduces a historical state convex mapping constraint, combined with a memory function to quantify the potential contribution of historical system state information and input data to improve the future control performance. The formulated historical data-based constraints and the memory function-enhanced cost function are then integrated into a model predictive control framework to optimize the battery charging current trajectories iteratively. Furthermore, to ensure that the constraints imposed on the battery electrical and thermal states are compatible with the self-learning control framework, a cascading linearized thermoelectric battery model is introduced to characterize the battery dynamics. Particularly, the internal temperature of the battery, which is not directly measurable in practical applications. Extensive simulation studies have been conducted, and the results demonstrate that the proposed control strategy can effectively regulate the internal temperature within a safe range while continuously optimizing the charging efficiency. In addition, the computation time variability is significantly reduced, with the standard deviation being decreased by approximately 80% compared to the standard MPC. The desirable control performance and continuous optimization capability make the proposed control strategy highly applicable to repetitive and complex engineering control problems
Bilateral internal jugular vein (BIJV) sampling during surgery for primary hyperparathyroidism (PHPT) – scoping review of evidence and search for an optimal definition for lateralisation
Get PDFPurpose
Accurate localisation of hyperfunctioning parathyroid glands is crucial for successful parathyroid surgery. In patients with inconclusive imaging, intraoperative bilateral internal jugular venous sampling (BIJVS) has been reported; but its utility remains unclear. The purpose of the review is to evaluate published techniques and reported effectiveness of BIJVS in parathyroid surgery.
Methods
PubMed, Ovid and Cochrane databases were searched for articles on intraoperative BIJVS in parathyroid surgery. All original English language human studies reporting on lateralisation rates, diagnostic accuracy or cure rates following use of intraoperative BIJVS were included. Exclusion criteria included case reports, reviews, IJV sampling in non-parathyroid pathology and IJV sampling for confirming cure. Data on patient numbers, definitions used for lateralisation and correlation with clinical outcomes were extracted by one reviewer and cross-checked by a second reviewer. The review was prospectively registered on the Open Science Framework (OSF; DOI: https://doi.org/10.17605/OSF.IO/TSQA6).
Results
Of 753 screened, 12 studies including 502 patients where BIJVS was performed were included. Lateralisation definitions were reported in 7 studies. Among studies with relevant data, lateralisation gradient was defined as ranging from 5 to 20% and lateralisation rates varied from 51 to 100%. The positive and negative predictive values ranged from 76 to 100% (6 studies) and 0–53% respectively (3 studies). Reported cure rates following BIJVS guided surgery were high (> 98%), but the definition for cure was only reported in 8 studies.
Conclusions
BIJVS can aid localisation in parathyroid surgery. A significant lateralisation gradient may permit unilateral surgery, but a lack of gradient does not imply bilateral disease. However, the absence of a standard definition for lateralisation and inconsistent reporting limits widespread adoption of this technique
PROspectiVe Imaging research DEsign and coNducT (PROVIDENT): Considerations for clinical trials and studies using imaging (Part II)
Get PDFObjectives
Imaging is used in a wide range of contexts in clinical research projects, but adds complexity to the design, conduct and analysis. This paper is the second of two in which we use a consensus approach to combine multidisciplinary perspectives on the challenges in conducting prospective clinical trials and other research studies involving imaging. Here we consider challenges in image interpretation and quantification, quality assurance and quality control (QA/QC); scanner imaging acquisition, data flow and storage, health economics (HE) decision modelling, costings for running a trial; and commercialisation.
Key findings
Availability of scanners and staff can impact deliverability. Pre-specification of key procedures, roles and responsibilities via appropriate documentation is important; ensuring compatibility across different sites and machines is challenging and requires advance input from multiple stakeholders. Testing critical procedures, including the flow of images and derived data between participating sites and/or external legal entities, can avoid delays. Effective QA/QC is conducted at regular intervals; relevant staff should be involved at the planning stage. Identifying appropriately qualified readers and arranging for image hosting takes time; this should be done prior to image acquisition. Testing image interpretation burden informs feasibility and costings. Cost estimates for research involving imaging and HE modelling of imaging interventions can be complex due to the interplay between local and national policies, and the extent to which the research imaging is integrated with standard care.
Conclusion
These considerations derived from a multidisciplinary team will be useful for funding applications, protocol design, trial implementation, conduct and commercialisation and uptake of new imaging techniques.
Implications for practice
Many prospective imaging studies could be improved by the upfront awareness of potential challenges and understanding of real-world examples these considerations provide
Storing quantum coherence in a quantum dot nuclear spin ensemble for over 100 milliseconds
Get PDFStates with long coherence are a crucial requirement for qubits and quantum memories. Nuclear spins in epitaxial GaAs/AlGaAs quantum dots are a great candidate, offering excellent isolation from external environments and on-demand coupling to optical flying qubits. However, coherence times are limited to ≲ 1 ms by the dipole-dipole interactions between the nuclei and by the nuclear quadrupolar coupling to inhomogeneous crystal strain. Here, we combine strain engineering of the nuclear spin ensemble and tailored dynamical decoupling sequences to achieve nuclear spin coherence times exceeding 100 ms. Recently, a reversible transfer of quantum information into nuclear spin ensembles has been demonstrated in quantum dots: our results provide a path to develop this concept into a functioning solid-state quantum memory suitable for quantum repeaters in optical quantum communication networks
Scalable Voltage Control for DC Microgrids: Robustness to Network Structural Variations
Get PDFFrequent plug-in/-out operations result in structural variations of DC microgrids (DCmGs), posing challenges to scalable control and often requiring costly redesigns to maintain stability. To address this issue, this paper proposes a scalable voltage control strategy for uncertain DCmGs, enabling plug-and-play functionality without controller redesign or system reconfiguration. A polytopic uncertain DCmG model is first formulated to simultaneously capture parameter uncertainties in distributed generation units (DGUs), power lines, and ZIP (i.e., impedance, current, and power) loads. A structured free-weight matrix technique is then developed to mitigate the adverse effects of line and load uncertainties on DGUs while yielding a more tractable linear matrix inequality formulation. The proposed scalable control method is implemented locally to ensure the dissipative voltage stability of each DGU, thereby preserving the dissipativity of the entire network. Numerical simulations validate the effectiveness of the proposed strategy in achieving faster convergence and reduced overshoot
Synthesis of the Proposed Structure of Celacarfurine and Analogues Using Sequential Cascade Ring Expansion Reactions
Get PDFThe first synthesis of the proposed structure of spermidine derived macrocyclic alkaloid celacarfurine is described. A versatile synthetic strategy has been developed based on sequential cascade ring expansion reactions, with high dilution conditions not needed for any of the steps. The same general strategy was also used to generate a series of macrocyclic analogues. The physical properties and spectroscopic data obtained for our synthetic product do not match those reported for the isolated alkaloid
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