MSD (Finland)

There are advantages and challenges to using microsatellite SAR constellations for SAR Interferometry (InSAR). The agile satellite design enables high-resolution and high-revisit imaging. However, it is challenging to maintain a near-frozen orbit that is typically required by many interferometric applications. This paper provides an overview of InSAR capability using the ICEYE microsatellite SAR constellation with examples from a number of real-world applications and results from validation campaigns.

BackgroundLung cancer (LC) remains the leading cause of cancer-related mortality worldwide. Early detection through targeted screening significantly improves patient outcomes. However, identifying high-risk individuals remains a critical challenge.PurposeThis systematic review evaluates externally validated LC risk prediction models to assess their performance and potential applicability in screening strategies.MethodsOf the 11,805 initial studies, 66 met inclusion criteria and 38 published mainly between 2020 and 2024 were included in the final analysis. Model methodologies, validation approaches, and performance metrics were extracted and compared.ResultsThe review identified 18 models utilising conventional machine learning, six employing neural networks, and 14 comparing different predictive frameworks. The Prostate Lung Colorectal and Ovarian Cancer Screening Trial (PLCOm2012) demonstrated superior sensitivity across diverse populations, while newer models, such as Optimized Early Warning model for Lung cancer risk (OWL) and CanPredict, showed promising results. However, differences in population demographics and healthcare systems may limit the generalisability of these models.InterpretationWhile LC risk prediction models have advanced, their applicability to specific healthcare systems, such as Finland’s, requires further adaptation and validation. Future research should focus on optimising these models for local contexts to improve clinical impact and cost-effectiveness in targeted screening programmes.Systematic review registrationPROSPERO CRD42022321391.

We compare, following Pati, global symmetries our topological supersymmetric preon model with the heterotic E_8 x E_8 string theory. We include Pati's supergravity based preon model in this work and compare the preon interactions of his model to ours. Based on preon-string symmetry comparison and preon phenomenological results we conclude that the fundamental particles are likely preons rather than standard model particles.

A previous supersymmetric preon scenario for visible matter particles is extended to the dark sector. In addition, the scenario is reformulated as a Double Field Theory (DFT) with four extra dimensions, to avoid a singular Big Bang in cosmology. T-duality and doubled local Lorentz symmetry of the model are genuine stringy properties. It is proposed that DFT preons may be an approximate pointlike projection of string theory.

BackgroundThe Multiple Sclerosis Impact Scale‐29 (MSIS‐29) has been increasingly used to evaluate the self‐perceived impact of multiple sclerosis (MS) on a patient.ObjectivesThe aim of this study was to evaluate the psychometric properties of the Finnish version of MSIS‐29 in patients with MS.MethodsA total of 553 patients with MS completed the MSIS‐29 and self‐administered questionnaires capturing information on demographics, disease characteristics and severity, perceived quality of life (EuroQol 5D‐3L instrument), and fatigue (Fatigue Severity Scale).ResultsThe data quality for MSIS‐29 was excellent, with 99.5% computable scores for the MSIS‐29 physical scale and 99.3% for the MSIS‐29 psychological scale. Floor and ceiling effects were minimal. Excellent Cronbach's alpha values of 0.97 and 0.90 were seen for MSIS‐29 physical and psychological subscales, respectively. The physical subscale showed highest correlations with measures of physical functioning, such as disease severity and the mobility domain of the quality of life. Similarly, the psychological subscale showed highest correlations with self‐reported fatigue and the anxiety/depression domains of the quality of life. MSIS‐29 physical scores related strongly to disease severity, whereas the MSIS‐29 psychological scores increased in mild disease but declined in more severe disease forms.ConclusionThe Finnish version of MSIS‐29 has satisfactory psychometric properties. Consistent with the previous recommendations, the use of two MSIS‐29 subscale scores instead of a total score was supported.

We present a method for measuring beat-to-beat heart rate from ballistocardiograms acquired with force sensors. First, a model for the heartbeat shape is adaptively inferred from the signal using hierarchical clustering. Then, beat-to-beat intervals are detected by finding positions where the heartbeat shape best fits the signal. The method was validated with overnight recordings from 46 subjects in varying setups (sleep clinic, home, single bed, double bed, two sensor types). The mean beat-to-beat interval error was 13 ms and on an average 54% of the beat-to-beat intervals were detected. The method is part of a home-use e-health system for an unobtrusive sleep measurement.

Vehicular communication has recently become popular for delivering traffic information and broadband services to the commuters. The feasibility of using the opportunistic short interval connections between vehicles and between vehicles and the roadside infrastructure is under scrutiny. The main motivation behind writing this review is that several survey works addressing inter-vehicle communications are available in literature but hardly any survey article on roadside-to-vehicle (R2V) communication is known to the authors. Here, we discuss the latest standards and protocols which can allow the use of already available WLAN infrastructure in the vehicular context. The use of roadside WLAN APs would provide the same services as those envisaged by the intelligent transportation systems using the dedicated roadside base stations. In this paper, we give an overview of the recent developments, limitations, standards and protocols that can facilitate 802.11-based R2V communication.

Measuring the variation of the respiratory rate makes it possible to analyze the structure of sleep. The variation is high when awake or in REM sleep, and decreases in deep sleep. With sleep apnea, the respiratory variation is disturbed. We present a novel method for extracting respiratory rate variation from indirect measurements of respiration. The method is particularly suitable for force sensor signals, because, in addition to the respiratory phenomenon, they typically contain also other disturbing features, which makes the accurate detection of the respiratory rate difficult. Respiratory variation is calculated by low-pass filtering a force sensor signal at different cut-off frequencies and, at every time instant, selecting one of them for the determination of respiration cycles. The method was validated with a single-night reference recording, which showed that the proposed method detects the respiratory variation accurately. Of the 3421 calculated respiration cycle lengths, 95.9% were closer than 0.5 seconds to the reference.