Miracle-dz/UniFAR-FTUs huggingface dataset:
The Certification Matters: A Comparative Performance Analysis of Combat Application Tourniquets versus Non-Certified CAT Look-Alike Tourniquets

Abstract Introduction: The Stop the Bleed campaign provided civilians with tourniquet application training and increased the demand for tourniquets among the general population, which led to the development of new commercially available devices. However, most widely available tourniquets have not undergone testing by regulatory bodies and their efficacy remains unknown. Study Objective: This study aimed to compare the efficacy and performance of Combat Application Tourniquets (CAT) versus uncertified tourniquets. Methods: This study compared 25 CAT with 50 commercially available “look-alike” tourniquets (LA-TQ) resembling the CAT. The CAT and the LA-TQ were compared for cost, size, and tested during one-hour and six-hour applications on a manikin’s leg. The outcomes were force applied, force variation during the application, and tourniquet rupture rate. Results: The LA-TQ were cheaper (US$6.07 versus US$27.19), shorter, and had higher inter-device variability than the CAT (90.1 [SE = 0.5] cm versus 94.5 [SE = 0.1] cm; P <.001). The CAT applied a significantly greater force during the initial application when compared to the LA-TQ (65 [SE = 3] N versus 14 [SE = 1] N; P <.001). While the initial application force was maintained for up to six hours in both groups, the CAT group applied an increased force during one-hour applications (group effect: F [1,73] = 105.65; P <.001) and during six-hour applications (group effect: F [1,12] = 9.79; P = .009). The rupture rate differed between the CAT and the LA-TQ (0% versus 4%). Conclusion: The LA-TQ applied a significantly lower force and had a higher rupture rate compared to the CAT, potentially affecting tourniquet performance in the context of public bleeding control. These findings warrant increased layperson education within the framework of the Stop the Bleed campaign and further investigations on the effectiveness of uncertified devices in real-world applications.
Creating Routes for Landmark-Training with the CompanionApp: A Pilot User Study

An important ability for participation in society is wayfinding. In this paper the findings of a pilot user study conducted to assess the usability of the CompanionApp, a mobile application aimed at providing landmark training and wayfinding assistance to individuals with cognitive impairments are presented. The study focuses on the role of caregivers in using the app and explores their level of comfort with technology. Participants engaged in a workshop where they created routes using the app, followed by a feedback session. The results indicate promising usability of the app’s user interface and route creation process. However, certain aspects require clarification and a more comprehensive introduction. These findings highlight the potential of the CompanionApp in empowering individuals with cognitive impairments to navigate independently and foster inclusion.
Design Features of a Career Guidance Platform to Promote Intrinsically Motivated Use

Many career guidance platforms are information portals that have a strong text-based approach and are used in higher grades later in the career guidance process. As part of a research project (JOLanDA) aimed at improving the career orientation of young people, we are developing a gamified platform to support younger pupils (12 years and older) in career orientation also outside of school. In this paper, we report on a moderated usability test (n = 14) with junior experts (students) to gain initial insights on how to improve the platform, as well as results from school workshops (n = 197, grade 7-9) within three field phases. Due to the playful approach, narrative structure (interactive digital storytelling), and a novel interaction concept (scroll-activated animations), the platform seems to attract great interest and has the potential to foster intrinsic user motivation. Based on the results, we provide design recommendations for online learning environments.
Characterization of a mouse-adapted strain of bat severe acute respiratory syndrome-related coronavirus

ABSTRACT Bats carry genetically diverse severe acute respiratory syndrome-related coronaviruses (SARSr-CoVs). Some of them utilize human angiotensin-converting enzyme 2 (hACE2) as a receptor and cannot efficiently replicate in wild-type mice. Our previous study demonstrated that the bat SARSr-CoV rRsSHC014S induces respiratory infection and lung damage in hACE2 transgenic mice but not wild-type mice. In this study, we generated a mouse-adapted strain of rRsSHC014S, which we named SMA1901, by serial passaging of wild-type virus in BALB/c mice. SMA1901 showed increased infectivity in mouse lungs and induced interstitial lung pneumonia in both young and aged mice after intranasal inoculation. Genome sequencing revealed mutations in not only the spike protein but the whole genome, which may be responsible for the enhanced pathogenicity of SMA1901 in wild-type BALB/c mice. SMA1901 induced age-related mortality similar to that observed in SARS and COVID-19. Drug testing using antibodies and antiviral molecules indicated that this mouse-adapted virus strain can be used to test prophylactic and therapeutic drug candidates against SARSr-CoVs. IMPORTANCE The genetic diversity of SARSr-CoVs in wildlife and their potential risk of cross-species infection highlights the importance of developing a powerful animal model to evaluate the antibodies and antiviral drugs. We acquired the mouse-adapted strain of a bat-origin coronavirus named SMA1901 by natural serial passaging of rRsSHC014S in BALB/c mice. The SMA1901 infection caused interstitial pneumonia and inflammatory immune responses in both young and aged BALB/c mice after intranasal inoculation. Our model exhibited age-related mortality similar to SARS and COVID-19. Therefore, our model will be of high value for investigating the pathogenesis of bat SARSr-CoVs and could serve as a prospective test platform for prophylactic and therapeutic candidates.
Influence of Annotation Media on Proof-Reading Tasks

Annotating and proof-reading documents are common tasks. Digital annotation tools provide easily searchable annotations and facilitate sharing documents and remote collaboration with others. On the other hand, advantages of paper, such as creative freedom and intuitive use, can get lost when annotating digitally. There is a large amount of research indicating that paper outperforms digital annotation tools in task time, error recall and task load. However, most research in this field is rather old and does not take into consideration increasing screen resolution and performance, as well as better input techniques in modern devices. We present three user studies comparing different annotation media in the context of proof-reading tasks. We found that annotating on paper is still faster and less stressful than with a PC or tablet computer, but the difference is significantly smaller with a state-of-the-art device. We did not find a difference in error recall, but the used medium has a strong influence on how users annotate.
Enhancing the Supervision of Out-of-View Robots: A Study on Multimodal Feedback and Monitoring Screens

Objective: investigating the effect of two support methods (multimodal feedback, monitoring screens, and a combination of both) on human dual-task performance, cognitive workload, and user experience when supervising an out-of-sight autonomous robot. Method: A 2x2 within-group user study was conducted in VR with 26 participants involving a cognitive-cognitive dual-task setting. Participants had to simultaneously solve math problems and supervise the robot. Different support methods were provided: multimodal feedback, a screen showing real-time robot activity, and a combination of both. Objective performance metrics and subjective feedback on cognitive load and user experience were collected using standard questionnaires. Data were statistically analyzed, and thematic analysis was performed on post-study debriefing interviews. Results: The support methods improved overall user experience and positively impacted robot collaboration performance while decreasing math task performance. Cognitive load was unaffected. Multimodal feedback with a monitoring screen was perceived as the most helpful. Conclusion: The results suggest that multimodal feedback can improve user experience and improve supervision, but may partially decrease primary task performance. The findings highlight the importance of examining the effect of support methods in specific situations, depending on task priority.
HapticCollider: Ungrounded Force Feedback for Rigid Collisions during Virtual Tool Use

Controllers are not merely the dominant interface to interact in virtual reality (VR); they also are the main resource for haptically perceiving the virtual world. As standard VR controllers fail in generating realistic haptic feedback, we designed HapticCollider, a kinetic controller rendering force feedback, e.g., to simulate a collision when hammering or hitting against a virtual object. In our user study, we demonstrated that HapticCollider significantly increases realism in tool usage compared with a standard VR controller. As key factors for tool use realism in VR, we identified force feedback, controller weight, and grip shape in combination with software solutions, namely collision prediction, and control-display ratio to render the force timing, as well as, the tool position according to the user’s expectations.
Full 3D blood velocity mapping and flow quantification from Doppler echocardiographic images

This thesis contributes to knowledge by describing two novel methods to calculate 3D blood velocity and flow within the heart using 3D colour Doppler images. The principal goal of both methods was to overcome the main limitation of Doppler systems which is that the Doppler effect only measures one component of the velocity (parallel to the beam direction). For that reason, measured velocity and calculated flow depend on the angle between the beam direction and the flow. The first method was developed to reconstruct 3D intracardiac velocity vector fields. This is the first time that such vector fields have been obtained from 3D colour Doppler images. The novelty of the proposal lies not only in the 3D velocity reconstruction, but also 1) a new noise model for colour Doppler images was proposed which improves the realism of simulation studies, 2) an efficient patch-wise implementation was introduced and 3) ventricle wall motion was used to enable full ventricular coverage. Based on simulations minimum acquisition requirements for accurate reconstruction were established. These requirements were: view angles over 20 degrees and noise below 10% of the Doppler maximum velocity. The method was tested on healthy volunteers and on paediatric patients and an accuracy of 15% compared to flow Magnetic Resonance Imaging (MRI) was obtained, when acquisition and data conditions were close to the optimum range. The second method proposes an algorithm to calculate angle-independent flow rates through surfaces within the heart and vessels. Built on the Gauss’s theorem, this method enables to increase coverage beyond the Field of View (FoV) of individual colour Doppler images by combining images acquired from multiple views. The method was validated in patients with Hypoplastic Left Heart Syndrome. Results were compared with the current clinical gold standard measurement of flow MRI, agreeing on flow values and volumes to less than 10%. The novel methods proposed in this thesis have shown encouraging results using volunteer and patient data. I hope that the methods proposed will in the future be able to offer advanced flow measurements using echo. The ability to improve the information available from echo imaging, due to its ease of use and cost effective nature, has the potential for widespread improvements in clinical care.
Promoting human rights or increasing expectations? Effects of Self-Directed Support on the realisation of human rights in Scotland

Abstract This research investigated Scottish practitioners’ reflections on how local Self-Directed Support (SDS) implementations have affected the realisation of human rights. The findings indicate that SDS increased service users’ awareness of their rights but often in rather abstract ways, with service users (and practitioners) not getting information about SDS-related systems, processes, and procedures needed to make informed choices that support their human rights. The practitioners participating in this study found SDS systems and processes overcomplicated and struggled with accessing information needed for guiding service users. Although there is evidence that some processes are gradually becoming simpler, a focus on controlling resources has created a gap between the human-right-based ethos of SDS and its local implementations, reducing the ability of SDS to promote human rights and, according to some practitioners, just increasing service users’ expectations. This gap might be further widened by insufficient engagement with independent support and advocacy organisations. Points of interests: This article looks at whether Self-Directed Support in Scotland has achieved its aims to promote the rights of people with disabilities. Self-Directed Support is legislation that aims to promote human rights, such as dignity and self-determination, by giving people with disabilities more choice and control over the care they receive. Many practical obstacles make this challenging. This study found that people with disabilities have become more aware of their rights in general, but this often has not translated into getting care in a way that promotes their human rights. This study found that limited resources have meant in practice that local social work departments have focused on how to control their spending on meeting the needs of people with disabilities. This often has meant that the rights of people with disabilities have received less attention and have been neglected.
A spiking neural network with continuous local learning for robust online brain machine interface

Objective. Spiking neural networks (SNNs) are powerful tools that are well suited for brain machine interfaces (BMI) due to their similarity to biological neural systems and computational efficiency. They have shown comparable accuracy to state-of-the-art methods, but current training methods require large amounts of memory, and they cannot be trained on a continuous input stream without pausing periodically to perform backpropagation. An ideal BMI should be capable training continuously without interruption to minimize disruption to the user and adapt to changing neural environments. Approach. We propose a continuous SNN weight update algorithm that can be trained to perform regression learning with no need for storing past spiking events in memory. As a result, the amount of memory needed for training is constant regardless of the input duration. We evaluate the accuracy of the network on recordings of neural data taken from the premotor cortex of a primate performing reaching tasks. Additionally, we evaluate the SNN in a simulated closed loop environment and observe its ability to adapt to sudden changes in the input neural structure. Main results. The continuous learning SNN achieves the same peak correlation ( ρ=0.7 ) as existing SNN training methods when trained offline on real neural data while reducing the total memory usage by 92%. Additionally, it matches state-of-the-art accuracy in a closed loop environment, demonstrates adaptability when subjected to multiple types of neural input disruptions, and is capable of being trained online without any prior offline training. Significance. This work presents a neural decoding algorithm that can be trained rapidly in a closed loop setting. The algorithm increases the speed of acclimating a new user to the system and also can adapt to sudden changes in neural behavior with minimal disruption to the user.
TRAIL promotes the polarization of human macrophages toward a proinflammatory M1 phenotype and is associated with increased survival in cancer patients with high tumor macrophage content

Background TNF-related apoptosis-inducing ligand (TRAIL) is a member of the TNF superfamily that can either induce cell death or activate survival pathways after binding to death receptors (DRs) DR4 or DR5. TRAIL is investigated as a therapeutic agent in clinical trials due to its selective toxicity to transformed cells. Macrophages can be polarized into pro-inflammatory/tumor-fighting M1 macrophages or anti-inflammatory/tumor-supportive M2 macrophages and an inbalance between M1 and M2 macrophages can promote diseases. Therefore, identifying modulators that regulate macrophage polarization is important to design effective macrophage-targeted immunotherapies. The impact of TRAIL on macrophage polarization is not known. Methods Primary human monocyte-derived macrophages were pre-treated with either TRAIL or with DR4 or DR5-specific ligands and then polarized into M1, M2a, or M2c phenotypes in vitro. The expression of M1 and M2 markers in macrophage subtypes was analyzed by RNA sequencing, qPCR, ELISA, and flow cytometry. Furthermore, the cytotoxicity of the macrophages against U937 AML tumor targets was assessed by flow cytometry. TCGA datasets were also analyzed to correlate TRAIL with M1/M2 markers, and the overall survival of cancer patients. Results TRAIL increased the expression of M1 markers at both mRNA and protein levels while decreasing the expression of M2 markers at the mRNA level in human macrophages. TRAIL also shifted M2 macrophages towards an M1 phenotype. Our data showed that both DR4 and DR5 death receptors play a role in macrophage polarization. Furthermore, TRAIL enhanced the cytotoxicity of macrophages against the AML cancer cells in vitro. Finally, TRAIL expression was positively correlated with increased expression of M1 markers in the tumors from ovarian and sarcoma cancer patients and longer overall survival in cases with high, but not low, tumor macrophage content. Conclusions TRAIL promotes the polarization of human macrophages toward a proinflammatory M1 phenotype via both DR4 and DR5. Our study defines TRAIL as a new regulator of macrophage polarization and suggests that targeting DRs can enhance the anti-tumorigenic response of macrophages in the tumor microenvironment by increasing M1 polarization.
Mouse model of atypical DAT deficiency syndrome uncovers dopamine dysfunction associated with parkinsonism and psychiatric disease

The dopamine transporter (DAT) plays a crucial role in regulating the brain’s dopamine (DA) homeostasis. Atypical DAT deficiency syndrome (DTSD) is a disease characterized by early-onset parkinsonism and comorbid psychiatric symptoms, but the pathobiological processes that link DAT dysfunction to both parkinsonism and psychiatric symptoms are unknown. Here, we present a genetic mouse model of atypical DTDS that expresses two coding DAT variants, DAT-I312F and DAT-D421N, derived from a patient diagnosed with ADHD and parkinsonism. Phenotypic characterization of the mutant mice revealed impaired DAT function and major homeostatic changes including increased ambient extracellular DA levels, decreased evoked DA release, and reduced expression of both tyrosine hydroxylase (TH) and of DA D1/D2 receptors. This was accompanied by diminished striatal dopaminergic axonal density and a psychomotor phenotype characterized by hyperactivity, enhanced exploratory activity, and pronounced clasping. Importantly, both amphetamine and anticholinergic treatment ameliorated aberrant hyperlocomotion in the mice. Summarized, by replicating core aspects of the patient’s phenotype, the mouse model not only provides insights into the mechanisms underlying atypical DTDS but also underlines the broad relevance of DA deficits for understanding the co-morbidity between neuropsychiatric diseases and parkinsonism. ONE SENTENCE SUMMARY In a new mouse disease model, we explore the behavioral consequences and dopaminergic dysfunction that arise from patient-derived mutations in the dopamine transporter associated with parkinsonism and co-morbid neuropsychiatric disease
From sequences to therapeutics: Machine learning predicts chemically modified siRNA Activity

Small interfering RNAs (siRNAs) exemplify the promise of genetic medicine in the discovery of novel therapeutic modalities. Their ability to selectively suppress gene expression makes them ideal candidates for development as oligonucleotide pharmaceuticals. Recent advancements in machine learning (ML) have facilitated unmodified siRNA design and efficacy prediction, but a model trained to predict the silencing activity of siRNAs with diverse chemical modification patterns has yet to be published, despite the importance of such chemical modifications in designing siRNAs with the potential to advance to the clinic. This study presents the first application of ML to classify efficient chemically modified siRNAs from sequence and chemical modification patterns alone. Three algorithms are evaluated at three classification thresholds and compared according to sensitivity, specificity, consistency of feature weights with empirical knowledge, and performance on an external validation dataset. Finally, possible directions for future research are proposed.
Stability of Ecologically Scaffolded Traits During Evolutionary Transitions in Individuality

Evolutionary transitions in individuality (ETIs), such as the emergence of multicellularity, are events in the history of life during which entities at one level of organisation (particles) form collective-level entities that subsequently become individuals in their own right. Recent empirical and theoretical studies advocate the importance of an externally imposed meta-population structure or “ecological scaffold” for the emergence of new levels of individuality. Such a scaffold enables survival and reproduction at the collective level and thus the possibility of selection for beneficial traits on that level. However, a long-standing difficulty for the ecological scaffolding approach has been its inability to adequately explain how collective-level trait values that evolved under scaffolding conditions can be retained once these conditions are lifted. We call this difficulty “the problem of endogenisation. ” Here, we derive general conditions for the possibility of endogenisation. Key to endogenisation is the existence of a fitness valley that can be circumvented when scaffolding occurs. Using a stochastic meta-population model, we implement two versions of ecological scaffolding (one temporal and one spatial) and study subsequent evolutionary trajectories using the modelling techniques of adaptive dynamics. Our analysis yields several important results. The temporal model reveals that only collective traits based on particle-particle interactions can be endogenised when a temporary scaffold is applied to the entire population. The spatial model shows that, given the presence of an environmental gradient of externally imposed meta-population structure, ecological scaffolding can only occur in a limited “Goldilocks” zone of the environment. Further, if endogenisation conditions are also fulfilled, scaffolded collectives can colonise non-scaffolding areas of the environment. We conjecture that Goldilocks zones could act as initiators of ETIs and help explain the near ubiquity of collective-level individuality even if the conditions that promote it prove to be rare.