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Purpose – The purpose of this paper is to help optimize sustainment logistics for US Army brigade combat teams, which may face challenges in transporting their assigned assets. Design/methodology/approach – This paper develops a simulation framework with an integrated integer programming optimization model. The integer-programming model optimizes sustainment outcomes of supported battalions on a daily basis, whereas the simulation framework analyzes risk associated with shortfalls that may arise over the entire duration of a conflict. Findings – This work presents a scenario reflecting the steady resupply of an infantry brigade combat team during combat operations and presents an in-depth risk analysis for possible fleet compositions. Originality/value – The risk curves obtained allow decision-makers and commanders to optimize vehicle fleet design in advance of a conflict.

Selecting the sizes of distributed energy resources is a central planning element when designing a microgrid. Decision makers may consider several important factors, including, but not limited to, capacity, cost, reliability and sustainability. We introduce a method for rightsizing capacity that presents a range of potential microgrid design solutions, allowing decision makers to weigh their upsides and downsides based on a variety of measurable factors. We decouple component-specific modeling assumptions, energy management system logic and objective measurements from our simulation-based nested binary search method for rightsizing to meet power loads. In doing so, we develop a flexible, customizable and extensible approach to microgrid design planning. Aspects which have traditionally been incorporated directly in optimization-centric frameworks, such as resilience and reliability, can be treated as complementary analyses in our decoupled approach. This enables decision makers to gain exposure to a wide range of relevant information and actively participate in the microgrid design assessment process.

In this protocol, we describe a method to visualize and map dural lymphatic vessels in-vivo using magnetic resonance imaging (MRI) and ex-vivo using histopathological techniques. While MRI protocols for routine imaging of meningeal lymphatics include contrast-enhanced T2-FLAIR and T1-weighted black-blood imaging, a more specific 3D mapping of the lymphatic system can be obtained by administering two distinct gadolinium-based MRI contrast agents on different days (gadofosveset and gadobutrol) and subsequently processing images acquired before and after administration of each type of contrast. In addition, we introduce methods for optimal immunostaining of lymphatic and blood vessel markers in human dura mater ex-vivo.

Abstract Radiological imaging is a globally prevalent diagnostic method, yet the free text contained in radiology reports is not frequently used for secondary purposes. Natural Language Processing can provide structured data retrieved from these reports. This paper provides a summary of the current state of research on Large Language Model (LLM) based approaches for information extraction (IE) from radiology reports. We conduct a scoping review that follows the PRISMA-ScR guideline. Queries of five databases were conducted on August 1st 2023. Among the 34 studies that met inclusion criteria, only pre-transformer and encoder-based models are described. External validation shows a general performance decrease, although LLMs might improve generalizability of IE approaches. Reports related to CT and MRI examinations, as well as thoracic reports, prevail. Most common challenges reported are missing validation on external data and augmentation of the described methods. Different reporting granularities affect the comparability and transparency of approaches.

Abstract We present resummed predictions at next-to-leading logarithmic accuracy matched to the exact next-to-leading order results for a set of classical event-shape observables in hadronic Higgs decays, i.e., for the channels H → gg and H → b b ¯ $$ b\overline{b} $$ . We furthermore consider soft-drop grooming of the hadronic final states and derive corresponding NLO+NLL′ predictions for the groomed thrust observable. Differences in the QCD radiation pattern of gluon- and quark-initiated final states are imprinted in the event-shape distributions, offering separation power for the two decay channels. In particular, we show that ungroomed event shapes in H → gg decays develop a considerably harder spectrum than in H → b b ¯ $$ b\overline{b} $$ decays. We highlight that soft-drop grooming can substantially alter this behaviour, unless rather inclusive grooming parameters are chosen.

Abstract We study jet angularities for dijet production at the Relativistic Heavy Ion Collider (RHIC) in proton-proton (pp) and nucleus-nucleus (AA) collisions at 200 GeV nucleon-nucleon center-of-mass collision energy. In particular, we provide NLL resummed predictions for angularity observables of groomed and ungroomed jets produced in pp collisions matched to next-to-leading order QCD calculations resulting in NLO + NLL ′ accuracy. Our parton-level predictions are corrected for non-perturbative effects, such as hadronization and underlying event, using parton-to-hadron level transfer matrices obtained with the Sherpa event generator. Furthermore, we use the Q-Pythia and Jewel generators to estimate the impact of the interaction between quarks and gluons produced by the parton shower with the dense medium formed in heavy-ion collisions on the considered jet angularities.

IntroductionRadiologists frequently lack direct patient contact due to time constraints. Digital medical interview assistants aim to facilitate the collection of health information. In this paper, we propose leveraging conversational agents to realize a medical interview assistant to facilitate medical history taking, while at the same time offering patients the opportunity to ask questions on the examination.MethodsMIA, the digital medical interview assistant, was developed using a person-based design approach, involving patient opinions and expert knowledge during the design and development with a specific use case in collecting information before a mammography examination. MIA consists of two modules: the interview module and the question answering module (Q&A). To ensure interoperability with clinical information systems, we use HL7 FHIR to store and exchange the results collected by MIA during the patient interaction. The system was evaluated according to an existing evaluation framework that covers a broad range of aspects related to the technical quality of a conversational agent including usability, but also accessibility and security.ResultsThirty-six patients recruited from two Swiss hospitals (Lindenhof group and Inselspital, Bern) and two patient organizations conducted the usability test. MIA was favorably received by the participants, who particularly noted the clarity of communication. However, there is room for improvement in the perceived quality of the conversation, the information provided, and the protection of privacy. The Q&A module achieved a precision of 0.51, a recall of 0.87 and an F-Score of 0.64 based on 114 questions asked by the participants. Security and accessibility also require improvements.ConclusionThe applied person-based process described in this paper can provide best practices for future development of medical interview assistants. The application of a standardized evaluation framework helped in saving time and ensures comparability of results.

IntroductionSoil drought during summer in Central Europe has become more frequent and severe over the last decades. European forests are suffering increasing damage, particularly Norway spruce. Douglas-fir (Pseudotsuga menziesii (Mirbel) Franco), a non-native tree species, is considered as a promising alternative to build drought-resilient forests. The main goal of this study was to investigate the intraannual radial stem growth and sap flow performance of Douglas-fir along a precipitation gradient across Germany under severe drought.Material and methodsSap flow and stem radial changes of up to ten trees each at four sites with different precipitation regimes were measured in combination with volumetric soil water content during the growing season of 2022. Measurements of stem radial changes were used to calculate the trees’ stem water deficit, a proxy for tree water status and drought stress.ResultsThe severe summer drought of 2022 led to an early growth cessation and a significant reduction in daily sap flow at all four sites monitored. We could identify a site-specific threshold in soil water availability ranging between 21.7 and 29.6% of relative extractable water (REW) under which stem water reserves cannot be replenished and thereby inhibiting radial growth. We could also demonstrate that at this threshold, sap flow is heavily reduced to between 43.5 and 53.3%, and for a REW below 50%, sap flow linearly decreases by 1.1–2.0% per 1% reduction in REW. This reduction tends to follow the humidity gradient, being more pronounced at the most oceanic characterized site and suggesting an adaptation to site conditions. Even though Douglas-fir is considered to be more drought stress resistant than Norway spruce, growth and sap flow are greatly reduced by severe summer drought, which became more frequent in recent years and their frequency and intensity is likely to increase.ConclusionsOur results suggest that timber production of Douglas-fir in Central Europe will decline considerably under projected climate change, and thus pointing to site specific growth constraints for a so far promising non-native tree species in Europe.

Abstract Aims Cardiomyopathies (CMPs) are a heterogeneous group of diseases that are defined by structural and functional abnormalities of the cardiac muscle. Dilated cardiomyopathy (DCM), the most common CMP, is defined by left ventricular dilation and impaired contractility and represents a common cause of heart failure. Different phenotypes result from various underlying genetic and acquired causes with variable effects on disease development and progression, prognosis, and response to medical treatment. Current treatment algorithms do not consider these different aetiologies, due to lack of insights into treatable drivers of cardiac failure in patients with DCM. Our study aims to precisely phenotype and genotype the various subtypes of DCM and hereby lay the foundation for individualized therapy. Methods and results The Geno‐ And Phenotyping of PrImary Cardiomyopathy (GrAPHIC) is a currently ongoing prospective observational monocentric cohort study that recruits patients with DCM after exclusion of other causes such as coronary artery disease, valvular dysfunction, myocarditis, exposure to toxins, and peripartum CMP. Patients are enrolled at our heart failure outpatient clinic or during hospitalization at the University Hospital Hamburg. Clinical parameters, multimodal imaging and functional assessment, cardiac biopsies, and blood samples are obtained to enable an integrated genomic, functional, and biomarker analysis. Conclusions The GrAPHIC will contribute to a better understanding of the heterogeneous nature of primary CMPs focusing on DCM and provide improved prognostic approaches and more individualized therapies.

Abstract We present a novel strategy for the simultaneous measurement of Higgs-boson branching ratios into gluons and light quarks at a future lepton collider operating in the Higgs-factory mode. Our method is based on template fits to global event-shape observables, and in particular fractional energy correlations, thereby exploiting differences in the QCD radiation patterns of quarks and gluons. In a constrained fit of the deviations of the light-flavour hadronic Higgs-boson branching ratios from their Standard Model expectations, based on an integrated luminosity of $$5\,\text {ab}^{-1}$$ 5 ab - 1 , we obtain $$68\%$$ 68 % confidence level limits of $$\mu _{gg}=1 \pm 0.05$$ μ gg = 1 ± 0.05 and $$\mu _{q\bar{q}}

Recent developments related to tools based on artificial intelligence (AI) have raised interests in many areas, including higher education. While machine translation tools have been available and in use for many years in teaching and learning, generative AI models have sparked concerns within the academic community. The objective of this paper is to identify the strengths, weaknesses, opportunities and threats (SWOT) of using AI-based tools (ABTs) in higher education contexts. We employed a mixed methods approach to achieve our objectives; we conducted a survey and used the results to perform a SWOT analysis. For the survey, we asked lecturers and students to answer 27 questions (Likert scale, free text, etc.) on their experiences and viewpoints related to AI-based tools in higher education. A total of 305 people from different countries and with different backgrounds answered the questionnaire. The results show that a moderate to high future impact of ABTs on teaching, learning and exams is expected by the participants. ABT strengths are seen as the personalization of the learning experience or increased efficiency via automation of repetitive tasks. Several use cases are envisioned but are still not yet used in daily practice. Challenges include skills teaching, data protection and bias. We conclude that research is needed to study the unintended consequences of ABT usage in higher education in particular for developing countermeasures and to demonstrate the benefits of ABT usage in higher education. Furthermore, we suggest defining a competence model specifying the required skills that ensure the responsible and efficient use of ABTs by students and lecturers.

Abstract We present a simple parton-shower model that replaces the explicit angular ordering of the coherent branching formalism with a differentially accurate simulation of soft-gluon radiation by means of a non-trivial dependence of the splitting functions on azimuthal angles. We introduce a global kinematics mapping and provide an analytic proof that it satisfies the criteria for next-to leading logarithmic accuracy. In the new algorithm, initial and final state evolution are treated on the same footing. We provide an implementation for final-state evolution in the numerical code Alaric and present a first comparison to experimental data.

Abstract The possibility to reanalyse data taken by the HERA experiments offers the chance to study modern QCD jet and event-shape observables in deep-inelastic scattering. To address this, we compute resummed and matched predictions for the 1-jettiness distribution in neutral current DIS with and without grooming the hadronic final state using the soft-drop technique. Our theoretical predictions also account for non-perturbative corrections from hadronisation through parton-to-hadron level transfer matrices extracted from dedicated Monte Carlo simulations with Sherpa. To estimate parameter uncertainties in particular for the beam-fragmentation modelling we derive a family of replica tunes to data from the HERA experiments. While NNLO QCD normalisation corrections to the NLO+NLL’ prediction are numerically small, hadronisation corrections turn out to be quite sizeable. However, soft-drop grooming significantly reduces the impact of non-perturbative contributions. We supplement our study with hadron-level predictions from Sherpa based on the matching of NLO QCD matrix elements with the parton shower. Good agreement between the predictions from the two calculational methods is observed.