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Background: The characteristics of Parkinson's disease (PD) include postural instability and resting tremor. However, reductions of tremor amplitude do not always improve postural stability. Research question: What is the effect of deep brain stimulation (DBS) of the subthalamic nucleus (STN) on spectral analysis of body movement in patients with PD when tested without anti-PD medication? The effe
Hälften av alla pengar på börsen är våra pensionspengar. Det är fullständigt oacceptabelt att AP-fonderna placerar dem i fossilbranchen, skriver 37 forskare och debattörer.Half of all our pension money are invested in stocks. These funds support fossil fuel companies, which is totally inacceptable. 37 researcerhs and debaters demand divestification of these stocks.
Importance Tracheal intubation is one of the most commonly performed and high-risk interventions in critically ill patients. Limited information is available on adverse peri-intubation events.Objective To evaluate the incidence and nature of adverse peri-intubation events and to assess current practice of intubation in critically ill patients.Design, Setting, and Participants The International
The standard approach to the evaluation of tremor in medical practice is subjective scoring. The objective of this study was to show that signal processing of physiological data, that are known to be altered by tremor in Parkinson's disease (PD), can quantify the postural dynamics and the effects of DBS. We measured postural control and its capacity to adapt to balance perturbations with a force p
The Knee injury and Osteoarthritis Outcome Score (KOOS) is a self-administered instrument measuring outcome after knee injury at impairment, disability, and handicap level in five subscales. Reliability, validity, and responsiveness of a Swedish version was assessed in 142 patients who underwent arthroscopy because of injury to the menisci, anterior cruciate ligament, or cartilage of the knee. The
Introduction: Antimicrobial resistance (AMR) represents a persistent and ascensive global threat influenced by antibiotic misuse and overuse. In the Romanian context, patterns of antibiotic consumption and resistance within the healthcare system are marked in the red scenario on the European map. General practitioners and pharmacists, among others, play a major role in stewardship towards AMR.Aim:
Non-traditional stable isotope systems are increasingly used to study micronutrient cycling and acquisition in terrestrial ecosystems. We previously proposed for zinc (Zn) a conceptual model linking observed isotope signatures and fractionations to biogeochemical processes occurring in the rice soil environment and we suggested that 2’deoxymugineic acid (DMA) could play an important role for rice
Interpretability has become a crucial component in the Machine Learning (ML) domain. This is particularly important in the context of medical and health applications, where the underlying reasons behind how an ML model makes a certain decision are as important as the decision itself for the experts. However, interpreting an ML model based on limited local data may potentially lead to inaccurate co
Integrating low-power wearable systems into routine health monitoring is an ongoing challenge. Recent advances in the computation capabilities of wearables make it possible to target complex scenarios by exploiting multiple biosignals and using high-performance algorithms, such as Deep Neural Networks (DNNs). However, there is a tradeoff between the algorithms' performance and the low-power requir
Code review is a well-established and valued practice in the software engineering community contributing to both code quality and interpersonal benefits. However, there are challenges in both tools and processes that give rise to misalignments and frustrations. Recent research seeks to address this by automating code review entirely, but we believe that this risks losing the majority of the interp
Forward-only algorithms offer a promising memory-efficient alternative to Backpropagation (BP) for on-device training. However, state-of-the-art forward-only algorithms, e.g., Forward-Forward (FF), still require a substantial amount of memory during the training process, often exceeding the limits of mobile edge and Internet of Things (IoT) devices. At the same time, existing memory-optimization t
[Background/Context] AI assistants like GitHub Copilot are transforming software engineering; several studies have highlighted productivity improvements. However, their impact on code quality, particularly in terms of maintainability, requires further investigation. [Objective/Aim] This study aims to examine the influence of AI assistants on software maintainability, specifically assessing how the
Tool-based code review has been an established software engineering practice for at least a decade. However, while software development environments have improved significantly during this time with advanced features for code comprehension, refactoring, and AI support, code review tools have remained more static and are still centered around a two-way textual diff view with features similar to whe
Despite extensive research on Quality-of-Services (QoS) analysis of 5G networks, practical applications remain limited. This gap may be attributed to the lack of available tools and the complexity of developing or configuring technical systems to implement theoretical approaches. To address this, we developed an edge control system within a private 5G base station, utilizing Precision Time Protoco
The ability to encode, imagine, and remember coherent representations of the world is crucial for everyday life and depends on a brain network involving the hippocampal region. Scene construction tasks, which measure spatial coherence, have been shown to be sensitive to hippocampal integrity in amnesic patients. Hippocampal dysfunction has been implicated in posttraumatic stress disorder (PTSD), a
Machine learning techniques often lack formal correctness guarantees, evidenced by the widespread adversarial examples that plague most deep-learning applications. This lack of formal guarantees resulted in several research efforts that aim at verifying Deep Neural Networks (DNNs), with a particular focus on safety-critical applications. However, formal verification techniques still face major sca
Background: Patients with heart failure and left bundle branch block (LBBB) may receive cardiac resynchronization therapy (CRT), but current selection criteria are imprecise, and many patients have limited treatment response. Hemodynamic forces (HDF) have been suggested as a marker for CRT response. The aim of this study was therefore to investigate left ventricular (LV) HDF as a predictive marker
Cellular user positioning is a promising service provided by Fifth Generation New Radio (5G NR) networks. Besides, Machine Learning (ML) techniques are foreseen to become an integrated part of 5G NR systems improving radio performance and reducing complexity. In this paper, we investigate ML techniques for positioning using 5G NR fingerprints consisting of uplink channel estimates from the physica
