Neuroimaging Correlates of 3 Distinct Physical-Cognitive Phenotypes in Cognitively Normal Older Adults : The Gothenburg H70 Cohort Study.

BACKGROUND AND OBJECTIVES: Individuals aged 70 and older frequently experience an increased risk of deficits in both physical and cognitive functions. However, the natural progression and interrelationship of these deficits, as well as their neurologic correlates, remain unclear. We aimed to classify the data-driven physical-cognitive phenotypes and then investigate their associations with neuroimaging markers. METHODS: This cross-sectional study included 70-year-old participants from the Gothenburg H70 Birth Cohort (2014-2016). Based on physical performance (grip strength, balance, walking speed, and chair stand) and cognitive measures (episodic memory, perceptual speed, executive function, verbal fluency, and visuospatial abilities), we applied latent class analysis to identify physical-cognitive phenotypes. Based on the brain MRI measurements, 3 groups of neuroimaging markers were involved-neurodegeneration, cerebral small vessel disease (cSVD), and microstructural white matter (WM) integrity. We performed multinomial logistic regressions to examine the differences between the physical-cognitive phenotypes. RESULTS: In total, 1,140 participants (female: 53.3%) without dementia and disability were included in the study, with 721 (female: 52.2%) undergoing MRI scans. Three physical-cognitive phenotypes were identified: an "optimal" group characterized by high performance in both physical and cognitive functions, an "intermediate" group showing a slight reduction in both domains, and a "physical deficit" group marked by a significant reduction in physical performance. Compared with the optimal group, the other 2 groups were more likely to present with vascular risk factors. The physical deficit group had higher odds of experiencing depression compared with the intermediate group (adjusted odds ratio [aOR] 2.9, 95% CI 1.4-5.9). Compared with the optimal group, the odds of presenting all 3 severe neuroimaging markers were higher in both the intermediate (aOR 3.4, 95% CI 1.5-7.9) and physical deficit (aOR 10.3, 95% CI 2.4-45.0) groups. DISCUSSION: This study highlights the variability in physical and cognitive performance among older adults and suggests that neuroimaging markers of neurodegeneration, cSVD, and microstructural WM integrity may account for these variations. Our findings indicate the potential for developing group-based strategies to prevent and manage age-related functional decline. Further research with larger sample sizes is needed to deepen our understanding of physical-cognitive decline patterns

Old and new on the Peetre K-functional and its relations to real interpolation theory, quasi-monotone functions and wavelets

The Peetre K-functional is a key object in the development of the real method of interpolation. In this paper we point out a less known relation to wavelet theory and its applications to approximation theory and engineering applications. As a new basis for further development of these studies we present some known properties in the form appropriate for further applications and then derive new information and prove some new results concerning the K-functional and its close relation to (almost) quasi-monotone functions, various indices and interpolation theory. In particular, we extend and unify some known function parameter generalizations of the standard real interpolation spaces (A0,A1)θ,q

Automatic detection of grains in partially recrystallized microstructures using deep learning

Precise identification of recrystallizing grains in partially recrystallized microstructures is essential to obtain quantitative information regarding the recrystallization process. Automatic, robust, user-friendly, and unbiased identification methods that do not rely on hard-coded, preselected values would be highly advantageous. In this study, we test convolutional neural network instance segmentation models to achieve automatic segmentation of individual recrystallizing grains in partially recrystallized microstructures. Our training dataset includes micrographs obtained using electron backscattered diffraction from five alloys with different thermal-mechanical histories and more than 100,000 recrystallizing grains. We adapt and train two state of the art deep learning models, namely Mask R-CNN and PointRend. Both models provide instance segmentation results of good quality, enabling quantitative determination of the microstructural parameters. The PointRend model demonstrates better performance for grains with irregular shapes than Mask R-CNN. Compared to conventional methods, the trained deep learning approach is easier to use, more flexible, and applicable to a wide range of materials.

Freshwater mollusc community screening - Classical and eDNA monitoring methods to detect rare, indicator and invasive species

Freshwater habitats and their quality have always been of utmost importance for human subsistence. Water quality assessment is an important tool, covering biological, chemical and hydromorphological aspects. Bioindicators such as the bivalves can be used as evidence for good water quality, but widespread groups such as species of the family Sphaeriidae Deshayes,1855 (1822) and genus Pisidium/Euglesa/Odhneripidisium also known as ‘pea clams’ are poorly known and lack taxonomic expertise. The situation is similar for many other benthic macroinvertebrate species used in biomonitoring. In this study, we tested if pea clams can be detected using eDNA metabarcoding methods applied to sediment and plankton samples from 15 lakes and rivers in Sweden. Additionally, we detected benthic macroinvertebrates, so-called indicator species used in freshwater monitoring, as well as rare or red-listed and invasive species. We created a COI reference barcode library of 22 species of Swedish freshwater molluscs, of which one species is new, and five species have less than five records on NCBI and BOLD. From 272 sediment and plankton samples, we detected 497 benthic macroinvertebrate indicator species, 20 mollusc species and 3 invasive species in 15 freshwater environments in Sweden using eDNA metabarcoding. We show that one of the sediment sampling methods (M42) can detect slightly more species in autumn compared to the plankton or sediment kick-net methods, or to collecting samples in spring. A clear advantage is that biological water quality indices formerly calculated using taxa identified to the family level can now be calculated using the species level, giving higher precision. We suggest that future freshwater monitoring efforts can be greatly improved and sped up through large-scale and strategic habitat screening using barcoding and metabarcoding methods to support decision-making and help fulfill the goals of the UN 2030 Agenda.CC BY 4.0Corresponding author: E-mail address: [email protected] (S. Leidenberger).This study was financed by the Swedish research council for sustainable development FORMAS End biodiversity loss through improved tracking of threatened invertebrates (grant nr. 2018-01003, 2019-2023). We want to thank U. Bjelke, Swedish Species Information Centre, SLU, Sweden for different information about freshwater monitoring in Sweden. We thank A. Jonsson, University of Skövde, Sweden, for assistance during field sampling. We thank B. Nümann, A. Scherges, L. von der Mark and C. Etzbauer, LIB Museum Koenig, Bonn, Germany, for assistance in the molecular lab. We thank T. von Proschwitz of Gothenburg Natural History Museum, Sweden for bivalve reference material from the museum, help with the storage of our material and insider knowledge about this special bivalve group. The manuscript was improved by the comments of two unknown reviewers.</p

A case study of railway curve squeal radiated from both the outer and inner wheel

This case study is presented after observations were made that partially contrast the prevailing picture of railway curve squeal given in the literature. These are observations with significance both for modelling and condition monitoring. The current case study will be followed by a subsequent investigation focused on the validation and application of a simulation model to investigate root-causes for curve squeal at the Stockholm metro. Curve squeal in a 213 m radius curve on the Stockholm metro is studied. Data includes track characteristics (rail profile, rail roughness and gauge width) and noise measured at the trackside as well as by two vehicles equipped with an on-board mounted noise monitoring system. The current case study contrasts field measurements of curve squeal reported in the literature by a relative shift of emitted noise towards higher frequencies. Wayside noise measurements in the studied curve during a few hours showed squeal generation for all vehicle passages with dominating 1/3 octave band centre frequencies in the range between 6.3–15.8  kHz. Noise data measured during one year of regular traffic of two vehicles equipped with a monitoring system were obtained. The occurrence of curve squeal was analysed through an implementation of the curve squeal detection algorithm in operation at the Stockholm metro. This algorithm was also applied to search for events of squeal noise radiation from the outer wheel. Results show emissions of squeal noise from the inner and outer wheel for 65 % and 8 % of the vehicle passages through the studied curve, respectively. Further, the occurrence of curve squeal radiated from the inner wheel was found to increase by 10 % after rail grinding. In the literature, squeal radiated from the outer wheel is described as having an intermittent character with magnified spectral components in the frequency range between 5–10  kHz. In contrast, the current work presents sustained tonal squeal generated from the outer wheel with similar noise characteristics as typically related to ordinary curve squeal. Curve squeal – Influence of track design and maintenance statu

Numerical integration of mechanical forces in center-based models for biological cell populations

Center-based models are used to simulate the mechanical behavior of biological cells during embryonic development or cancer growth. To allow for the simulation of biological populations potentially growing from a few individual cells to many thousands or more, these models have to be numerically efficient, while being reasonably accurate on the level of individual cell trajectories. In this work, we increase the robustness, accuracy, and efficiency of the simulation of center-based models by choosing the time steps adaptively in the numerical method and comparing five different integration methods. We investigate the gain in using single rate time stepping based on local estimates of the numerical errors for the forward and backward Euler methods of first order accuracy and a Runge-Kutta method and the trapezoidal method of second order accuracy. Properties of the analytical solution such as convergence to steady state and conservation of the center of gravity are inherited by the numerical solutions. Furthermore, we propose a multirate time stepping scheme that simulates regions with high local force gradients (e.g. as they happen after cell division) with multiple smaller time steps within a larger single time step for regions with smoother forces. These methods are compared for a model system in numerical experiments. We conclude, for example, that the multirate forward Euler method performs better than the Runge-Kutta method for low accuracy requirements but for higher accuracy the latter method is preferred. Only with frequent cell divisions the method with a fixed time step is the best choice

Strategic digital product management : Nine approaches

Context: The role of product management (PM) is key for building, implementing and managing softwareintensive systems. Whereas engineering is concerned with how to build systems, PM is concerned with 'what' to build and 'why' we should build the product. The role of PM is recognized as critical for the success of any product. However, few studies explore how the role of PM is changing due to recent trends that come with digitalization and digital transformation. Objectives: Although there is prominent research on PM, few studies explore how this role is changing due to the digital transformation of the software-intensive industry. In this paper, we study how trends such as DevOps and short feedback loops, data and artificial intelligence (AI), as well as the emergence of digital ecosystems, are changing current product management practices. Methods: This study employs a qualitative approach using multi-case study research as the method. For our research, we selected five case companies in the software-intensive systems domain. Through workshop sessions, frequent meetings and interviews, we explore how DevOps and short feedback loops, data and artificial intelligence (AI), and digital ecosystems challenge current PM practices. Results: Our study yielded an in-depth understanding of how digital transformation of the software-intensive systems industry is changing current PM practices. We present empirical results from workshops and from interviews in which case company representatives share their insights on how software, data and AI impact current PM practices. Based on these results, we present a framework organized along two dimensions, i.e. a certainty dimension and an approach dimension. The framework helps structure the approaches product managers can employ to select and prioritize development of new functionality. Contributions: The contribution of this paper is a framework for 'Strategic Digital Product Management' (SDPM). The framework outlines nine approaches that product managers can employ to maximize the return on investment (RoI) of R&amp;D using new digital technologies

Stability estimates for radial basis function methods applied to linear scalar conservation laws

We derive stability estimates for three commonly used radial basis function (RBF) methods to solve hyperbolic time-dependent PDEs: the RBF generated finite difference (RBF-FD) method, the RBF partition of unity method (RBF-PUM) and Kansa's (global) RBF method. We give the estimates in the discrete l(2)-norm 2-norm intrinsic to each of the three methods. The results show that Kansa's method and RBF-PUM can be l(2)-stable 2-stable in time under a sufficiently large oversampling of the discretized system of equations. The RBF-FD method in addition requires stabilization of the spurious jump terms due to the discontinuous RBF-FD cardinal basis functions. Numerical experiments show an agreement with our theoretical observations

A growing concern : Online access to minors’ health records

Healthcare worldwide is undergoing a transition where patients are increasingly granted access to their electronic health records (EHRs). However, online record access (ORA) for vulnerable groups like children and adolescents remains a topic of active debate. Minors’ experiences of patient-accessible electronic health records (PAEHRs) and related ethical questions remain underexplored. The thesis aim was to explore stakeholder experiences of online access to minors’ EHRs, through six papers: 1) a case study comparing minors’ and guardian use of PAEHRs in Sweden and Finland and the use of country-specific access control practices; 2) a literature review summarising knowledge about stakeholder views and experiences on ORA for minors and parents; 3-4) two survey studies examining Swedish adolescents’ reasons for reading EHRs, utility, the link between use frequency and encouragement, as well as views on EHR security and privacy, attitudes toward information-sharing, and definitions of sensitive information; and 5-6) two mixed-methods studies exploring the views, awareness and benefits and risks with respect to ORA regulations among Swedish adolescents with serious health issues, their parents, and paediatric oncology HCPs. Findings were analysed using a framework of biomedical ethical principles. Adolescents in Finland, who receive ORA earlier, showed higher PAEHR use than their Swedish counterparts. In Sweden, few applications for extended access were found. Most prior work was US-based that left minors’ experiences, especially beyond chronic illness, largely underexplored. Swedish adolescent portal users viewed information as useful and higher use was related to HCP encouragement. Although security was rated highly, many wished to manage who could access their EHRs. Mental healthcare was the most cited as sensitive. Adolescents with serious health issues, their parents, and oncology HCPs criticised the current gap in ORA during adolescence. Parents were concerned about early adolescent ORA, while HCPs worried about the impact of parental ORA on EHR quality, and lacked knowledge of access extension. In conclusion, while ORA showed potential for engaging adolescents in their care early and facilitating parental support, risks remain for EHR quality. Education and dialogue among stakeholders, along with addressing HCP concerns, are essential efforts to make ORA an effective tool for enhancing adolescent health outcomes.NORDeHEALT

Cybersäkerhetsmekanismer i DNS-resolvrar : Ett perspektiv med internetmätningar

Using the Internet today, both end-users and automated systems rely on the Domain Name System (DNS) to translate human-readable domain names to IP addresses for communication between machines. This system from 1985 has only in recent years seen Internet standards addressing security and privacy concerns. In the position as a machine-in-the-middle between the client and the distributed hierachical system of authoritative name servers, we find the DNS resolver. Due to its purpose of forwarding, looking up, and caching queries and responses, in addition to its location between the clients and the name servers, the DNS resolver becomes a critical point for implementing these security and privacy features. The widespread adoption of these features, their variation in implementation, and impact on both clients and other name servers remain as interesting topics in the research community. The goal of this thesis is to analyze servers in the wild and conduct a comprehensive investigation into the security and privacy mechanisms configured on DNS resolvers. Using an Internet measurement approach, we explore the trends in the adoption and implementation of these features by generating and observing our own queries to and from the resolvers. We also investigate how clients and the DNS ecosystem as a whole are impacted by resolver configurations. We use and improve methods for measuring adoption of various security and privacy related features. Based on these measurements we report the current level of adoption and adoption over time, investigate anomalies, and identify limitations with measurement approaches. We fingerprint the software and version of popular open-source DNS resolvers by classifying query patterns. Comparing the ingress and egress resolvers we analyze forwarding behaviors and their impact on the availability and effectiveness of security and privacy features. We also cross-analyze features in DNS resolvers to find correlations, which could help us understand obstacles and find solutions to feature adoption.För att maskiner ska kunna kommunicera på Internet idag så bygger det på att domännamnssystemet (DNS) översätter domännamn till IP-adresser för både användare och automatiska system. Internetstandardiseringar som behandlar säkerhet och personlig integritet i detta system från 1985 har huvudsakligen dykt upp på senare år. Mellan klienter och den distribuerade hierakin av auktoritativa namnservrar finner vi DNS-resolvern. På grund av dess syfte att vidarebefodra och slå upp klienternas frågor samt cacha svar, och dess position som en låda-i-mitten blir den en kritisk punkt för säkerhet och personlig integritet. Hur antagna dessa mekanismer är, deras variation vid implementering samt påverkan på både klienter och andra namnservrar är fortfarande intressanta ämnen i forskningsvärlden. Målet med denna avhandling är att analysera DNS-resolvrar på internet för att genomföra en omfattande utvärdering av relaterade mekanismer runt säkerhet och personlig integritet. Vi utforskar trenderna i antagandet och och implementeringen av dessa funktioner, och analyserar hur de påverkar klienter och ekosystemet som helhet genom att observera trafik från DNS-frågor. Vi använder och förbättrar metoder för att mäta antagning av olika funktioner relaterade till säkerhet och personlig integritet. Baserat på dessa mätningar rapporterar vi den nuvarande nivån av antagning och antagning över tid. Vi undersöker även intressanta avvikelser i resultaten och identifierar begränsningar med mätmetoderna som används. Genom att klassifiera trafikmönster, lyckas vi identifiera versioner av programmvara från populära DNS-resolvrar med öppen källkod. När vi observerar resolvrar involverade i en uppslagning så analyserar vi hur de vidarebefodrar och hur detta påverkar tillgängligheten och effektiviteten av olika mekanismer. Vi undersöker även samband mellan olika mekanismer, vilket skulle kunna leda till en djupare förståelse om utmaningar och lösningar till högre antagande