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The assessment of residual lymphovascular invasion (LVI) in breast cancer patients undergoing neoadjuvant therapy may be a critical factor influencing prognosis and treatment decisions. However, there is a notable discrepancy between the RCB, UICC/AJCC, and ICCR guidelines regarding how LVI should be evaluated and reported in this context. ICCR recommends including LVI in the invasive tumor size f
Fully bio-based spirocyclic monomers with high reactivity and thermal stability in polycondensations, and scalable production from low-cost reactants are attractive alternatives to replace fossil-based terephthalate monomers. To this end, we carefully design and synthesize a dicarboxylate ester monomer with a spiroacetal structure from bio-based pentaerythritol and glyoxylic acid. Polycondensation
This paper advances a model of moral ambiguity in entrepreneurial action. Our model specifies the mechanisms surrounding moral responsibility, moral motivation, and the moral threshold through which perceived moral ambiguity shapes action. Specifically, we theorize (a) the interpretative elements that steer how the entrepreneur attributes moral responsibility and establishes moral motivation, (b)
Decarbonization in several countries is now linked to the prospect of implementing a national hydrogen economy. In countries with extensive natural gas infrastructure, hydrogen may provide a real opportunity to decarbonize space heating. While this approach may prove technically and economically feasible in the long-term, it is unclear whether consumers will be willing to adopt hydrogen-fueled app
This study investigates the impacts of a range of interventions aimed at reducing in emissions in three high-impact sectors in cities: built environment, mobility, and sustainable energy systems. It does so by focusing on four cities around the world that are pioneering circular economy solutions (Bogotá, Glasgow, Genoa and Milan), and uses a GTAP-modelling approach developed by C40, Arup and the
To predict major pressure losses from pumping shear thinning liquid foods and beverage, rheometer-measured flow behaviour (n) and flow consistency (K) indices are needed. These are always obtained with some measurement uncertainty. This contribution develops a tool that allows for quantitatively estimating how a given measurement uncertainty in the rheological parameters translate to predictio
BakgrundPrimärvården utgör den första linjen av vård och stöd för personer med psykisk ohälsa. Verksamheten är i huvudsak inriktad på diagnostik, medicinsk behandling och symtomlindring. Tillgången till denna vård upplevs emellertid som utmanande både av patienter och vårdgivare. En fördjupad förståelse av den levda erfarenheten av mötet med primärvården kan bidra till utvecklingen av mer individaBackground: Primary health care is in the unique position of being a first level of support and care to individuals with mental health problems. The focus in this service is on diagnosis, medical treatment, and symptom reduction. However, to access it is perceived as challenging by both patients and providers. An increased understanding of the lived experience of encountering primary health care m
The European species of the Cheilosia subgen. Neocheilosia Barkalov, 1983 (Diptera,Syrphidae) are revised. The identities of Cheilosia morio (Zetterstedt, 1838) and of its synonyms are reviewed, and C. scanica Ringdahl, 1937 is established as a junior synonym of C. morio. Cheilosia luteicornis (Zetterstedt, 1838) is re-installed as the name for C. morio of authors pro parte, not Zetterstedt. Cheil
Phage collections are essential tools for discovering and dissecting bacterial anti-phage defense systems. Here, we report the isolation, characterization, and annotated genome sequences of five environmental Escherichia coli-infecting phages, obtained during the 2023 Fundamentals of Basic and Applied Phage Biology course at Lund University. The phages were isolated using a motile E. coli K-12 B
In order to avoid extensive machine learning models selection and optimizations, Automated Machine Learning (AutoML) has arisen as a practical and efficient way to apply machine learning to many different application areas. Data poisoning is a real threat to the accuracy of machine learning models in different settings, and it has in recent research studies been shown that the usage of AutoML can
Background: Expanding access to self-management via Digital Health Technologies may supplement traditional care, mitigating pressures on primary care through self-management. Primary Care Physicians (PCP) can play a critical role in the integration of digital health technologies into patient care, but it is unclear what factors influence PCPs’ recommendation of such technologies. Aims: To identify
Full-duplex (FD) communication improves spectral efficiency by allowing simultaneous transmission and reception on the same frequency band. This paper analyzes a two-tier network consisting of macrocells and picocells, where base stations (BSs) operate in FD mode while users operate in half-duplex (HD) mode. However, interference remains a major challenge in these systems, significantly impacting
Permanent Magnet Synchronous Motors (PMSMs) are becoming increasingly popular in traction applications. PMSMs have gained popularity due to their efficiency, compactness and excellent features related to control. This is mainly because of the permanent magnet placement in the rotor, which negates any additional rotor excitation, hence reducing energy losses considerably. This makes them more effic
Background and objective: Prostate-specific membrane antigen (PSMA) positron emission tomography/computed tomography (PET/CT) is an evolving diagnostic tool for prostate cancer. There is a need to harmonise existing guidelines and reporting recommendations for PSMA PET/CT. The Standardised PSMA PET/CT Analysis and Reporting Consensus (SPARC) project aims to consolidate classifications and recommen
Federated Learning (FL) enables decentralized training of neural networks across multiple hospitals or patients while preserving data privacy. However, FL schemes typically assume data is independent and identically distributed (IID) while healthcare data can be highly heterogeneous. To address this, we propose Interpretable Personalized Federated Learning (IPFL), a novel framework that allows pat
