Miracle-dz/UniFAR-FTUs huggingface dataset:
Procalcitonin and lung ultrasonography point-of-care testing to determine antibiotic prescription in patients with lower respiratory tract infection in primary care: pragmatic cluster randomised trial

Abstract Objective To assess whether point-of care procalcitonin and lung ultrasonography can safely reduce unnecessary antibiotic treatment in patients with lower respiratory tract infections in primary care. Design Three group, pragmatic cluster randomised controlled trial from September 2018 to March 2020. Setting 60 Swiss general practices. Participants One general practitioner per practice was included. General practitioners screen all patients with acute cough; patients with clinical pneumonia were included. Interventions Randomisation in a 1:1:1 of general practitioners to either antibiotics guided by sequential procalcitonin and lung ultrasonography point-of-care tests (UltraPro; n=152), procalcitonin guided antibiotics (n=195), or usual care (n=122). Main outcomes Primary outcome was proportion of patients in each group prescribed an antibiotic by day 28. Secondary outcomes included duration of restricted activities due to lower respiratory tract infection within 14 days. Results 60 general practitioners included 469 patients (median age 53 years (interquartile range 38-66); 278 (59%) were female). Probability of antibiotic prescription at day 28 was lower in the procalcitonin group than in the usual care group (0.40 v 0.70, cluster corrected difference −0.26 (95% confidence interval −0.41 to −0.10)). No significant difference was seen between UltraPro and procalcitonin groups (0.41 v 0.40, −0.03 (−0.17 to 0.12)). The median number of days with restricted activities by day 14 was 4 days in the procalcitonin group and 3 days in the usual care group (difference 1 day (95% confidence interval −0.23 to 2.32); hazard ratio 0.75 (95% confidence interval 0.58 to 0.97)), which did not prove non-inferiority. Conclusions Compared with usual care, point-of-care procalcitonin led to a 26% absolute reduction in the probability of 28 day antibiotic prescription without affecting patients’ safety. Point-of-care lung ultrasonography did not further reduce antibiotic prescription, although a potential added value cannot be excluded, owing to the wide confidence intervals. Trial registration ClinicalTrials.gov NCT03191071.
Why Drivers Feel the Way they Do:An On-the-Road Study Using Self-Reports and Geo-Tagging

In automotive research, the current hot topic of emotion recognition is mainly technology-driven, focusing on the development of sensors and algorithms that ensure recognition accuracy and reliability. Often, a subjective reference, i.e., information about what drivers actually feel, is missing for the interpretation of the data collected. Thus, this paper explores the subjective component of drivers’ emotions, focusing on when, where, and why they occur. In an on-the-road study, 34 drivers tracked their emotions and the triggers of these experiences in-situ. In total, 367 verbal self-reports were captured, providing insights into the spatial-temporal distribution of drivers’ emotions and their determinants. Results show, for example, that intersections are emotional hotspots, and that positive emotions arise especially at the beginning and at the end of the drive. The results can help to understand emotion recognition data and to infer drivers’ emotions from contextual information if no emotion data is available.
Understanding Drone Landing on the Human Body

We envision the human body as a platform for fast take-off and landing of drones in entertainment and professional uses such as medical emergencies, rescue missions, or supporting police units. This new interaction modality challenges our knowledge of human-drone experiences, in which interaction usually occurs at a distance from the body. This work explores important factors for understanding the interplay between drones and humans. We first investigated the suitability of various body locations for landing in an online study (N = 159). Our results, presented as body maps, show that the hand and upper back are particularly well-suited body locations. We further tested these findings in a follow-up study (N = 12), in which participants experienced drones landing on their bodies through carefully designed and pre-recorded 360°videos. This immersion into the landing scenarios helped us to identify common themes and research approaches for different body parts. Taken together, the findings provide first insights into location preferences and themes for drones landing on the human body.
MOTUS: Rendering Emotions with a Wrist-worn Tactile Display

This paper investigates whether tactile texture patterns on the wrists can be interpreted as particular emotions. A prototype watch-back tactile display, MOTUS, was implemented to press different texture patterns in various frequencies onto a wrist to convey emotions. We conducted a preliminary guessability study with the prototype. The result reveals the wearers’ agreement in interpreting the emotional states from the tactile texture patterns.
What Makes a Good Team? - Towards the Assessment of Driver-Vehicle Cooperation.

With the introduction of driving automation, the driving task has become a shared task between driver and vehicle. Today, an increasing amount of driving tasks can be performed by the automation and the view of driver and automation acting as collaborative partners has been well established. Although this notion has been adopted in the research and design domains, means to assess the quality of the driver-automation interaction in a structured way are still lacking. Moreover, most design evaluations are usually addressed either from a technical stance or from a human factors viewpoint, which does not comply with a general acknowledged view of a unified driver-vehicle system. The aim of the current study is therefore to investigate the possibility to quantitatively evaluate the quality of the driver and vehicle cooperation. Seven dimensions indicative for the quality of cooperation are identified, based on a literature survey and expert input during focus groups. This work potentially supports road authorities, legislation, regulation and original equipment manufacturers to monitor, evaluate and design driver-vehicle cooperation.
Investigating the Effects of Feedback Communication of Autonomous Vehicles

Autonomous vehicles (AVs) are expected to communicate to vulnerable road users as a substitution of, for example, driver-pedestrian communication, leading to increased safety and acceptance. This communication is currently one-directional, i.e., from the AV to the pedestrian. However, today’s communication between drivers and pedestrians in crossing scenarios is bidirectional. Pedestrians gesture “thank you’’ or wave drivers through in case they do not want to cross. Human drivers often acknowledge this, for example, with a nod. We present an experiment in Virtual Reality (N=20), in which the effect of such acknowledgment of the AVs via its external communication is investigated for the two described scenarios and concerning pedestrian presence. Results show that such feedback is perceived as highly necessary, depends on the scenario, and improves the perceived intelligence of the AV, confirming a Halo-Effect.
MagneTrack: Magnetic Field Separation Method for Continuous and Simultaneous 1-DOF Tracking of Two-magnets

This paper presents a method to track two magnets using one magnetometer on a smart device (e.g., smartphone), which detects the locations of the magnets around the device. A magnetometer measures the overlapping data signals generated by the two magnets. Thus, a data-separation technique is required to separately track the continuous and simultaneous signals generated by the two magnets. In this study, we develop a separation algorithm based on nonnegative matrix factorization to continuously and simultaneously track two magnets, and then conduct an experiment to validate our concept. We then compare our method in both simulated and actual environments. In the actual environment, we observe real data signals arising from the two magnets on a magnetometer. Finally, we present example applications to demonstrate the use cases of our model in human–computer interaction systems.
Mode Awareness Interfaces in Automated Vehicles, Robotics, and Aviation: A Literature Review

With increasing automation capabilities and a push towards full automation in vehicles, mode awareness, i.e., the driver’s awareness of the vehicle’s current automation mode, becomes an important factor. While issues surrounding mode awareness are known, research concerning and design towards mode awareness appears to not yet be a focal point in the automated driving domain. In this paper, we provide a state-of-the art on mode awareness from the related domains of automated driving, aviation, and Human-Robot Interaction. We present a summary of existing mode awareness interface solutions as well as existing techniques and recognized gaps concerning mode awareness. We found that existing interfaces are often simple, sometimes outdated, yet are difficult to meaningfully expand without overloading the user. We also found predictive approaches as a promising strategy to lessen the need for mode awareness via separate indicators.
Analysis of the rheological property and crystallization behavior of polylactic acid (Ingeo™ Biopolymer 4032D) at different process temperatures

Abstract The aim of this study was to determine the rheological property and crystallization behavior of polylactic acid (PLA) with improved heat resistance (Ingeo™ Biopolymer 4032D) through investigation of the melt viscosity and crystallization kinetics of PLA at different process temperatures. The viscosity was measured using a rotational rheometer under conditions of shear rates of 0.01, 0.1, and 1/s. The obtained rheological data show that the viscosity tended to decrease slightly as the shear rate increases and decrease sharply as the temperature increases from 180°C to 210°C. To investigate the effect of the process temperature on the crystallization kinetics and final crystallinity of PLA, thermal analysis using isothermal differential scanning calorimetry (DSC) were also performed. The Avrami equation was successfully applied for the isothermal crystallization kinetics model. From crystallization temperature of 85°C to 120°C, we found that the Ingeo™ Biopolymer 4032D PLA had the fastest crystallization rate (t 1/2: 26.0 min) and the largest crystallinity (47.4%) at 100°C.
Establishment of a Machine Learning Model for Early and Differential Diagnosis of Pancreatic Ductal Adenocarcinoma Using Laboratory Routine Data

Early diagnosis and clear differentiation of pancreatic ductal adenocarcinoma (PDAC) from chronic pancreatitis (CP) is clinically challenging. A machine learning model is developed for the diagnosis of PDAC. The model is induced using a dataset of 13 987 participants, of which 12 402 are used for training the model and the remaining 1585 for testing purposes. One thousand sixty‐six laboratory variables are reduced to 18 measures using standard filtering and feature importance methods. Then, five machine learning classifiers are evaluated for the study. Hyperparameter optimization for each classifier is carried out, and the optimal algorithm is established using a tenfold cross validation on the training data. Finally, gradient boosting decision tree‐based ternary classifier composed of 18 routine laboratory variables (GBDT‐TC18) is established. In the test cohort, GBDT‐TC18 differentiates PDAC from CP and healthy control (HC) with an accuracy better than carbohydrate antigen 19‐9 (CA19‐9)‐based diagnosis. It also maintains a high diagnostic accuracy for stages I, IIA, and IIB PDAC, small‐sized PDAC, body and tail adenocarcinoma, CA19‐9‐negative PDAC, and nonjaundice PDAC. What's more, GBDT‐TC18 shows a higher accuracy than CA19‐9 in distinguishing PDAC from CP. GBDT‐TC18 can be used to augment the capability of doctors for early and differential diagnosis of PDAC.
Angiocrine IGFBP3 Spatially Coordinates IGF Signaling During Neonatal Cardiac Regeneration

To identify non-cell-autonomous effectors of cardiomyocyte mitosis, we analyzed a transcriptomic screen of regenerating and non-regenerating neonatal hearts for differentially-expressed secreted proteins – which we hypothesized could include candidate mitogens. We identified and validated IGFBP3, which has a Janus-like stabilizing and sequestering effect on IGF growth factors, as a neonatal injury-associated secreted protein. IGFBP3 is expressed by and secreted from vascular cells in the neonatal heart after cardiac injury, notably in the infarct border zone. We found that global deletion of IGFBP3 blunted neonatal regeneration, while gain-of-function experiments using recombinant IGFBP3 and a transgenic mouse model uncovered a pro-mitotic effect of IGFBP3 on cardiomyocytes in vitro and in the adult heart. We show that site-specific expression of an IGFBP3 protease (PAPP-A2) and its inhibitor (STC2) coordinate the spatial release of IGF2 in the infarct zone to regio-selectively activate the INSR-ERK-AKT cell growth pathways in cardiomyocytes. Collectively, our work highlights the spatiotemporal orchestration of endothelial-cardiomyocyte interactions that are required for neonatal cardiac regeneration.
Determination of m6A frequency utilizing 4SedTTP-RT Ligation Assisted PCR (SLAP) in viral and cellular long non-coding RNAs

N6-methyladenosine is one of the most abundant epitranscriptomic signatures that can affect every aspect of RNA biology, from structure and stability to intra- and intermolecular interactions. The accurate quantitative assessment of RNA stoichiometry at single-nucleotide resolution is a prerequisite to evaluate the biological significance of m6A in the context of specific RNA. We have developed a new method, termed 4-Selenothymidine 5’-triphosphate reverse transcription and Ligation Assisted PCR analysis (SLAP), for quantitative and unbiased assessment of the m6A fraction on target RNA. The inclusion of thymidine triphosphate derivative during reverse transcription discourages base pair formation with m6A resulting in the reaction’s cessation, while maintaining normal A-T base pairing. The site-specific ligation of the resulting cDNAs with adapters, followed by amplification, generates two distinct products that reflect the modified and unmodified fraction of the analyzed RNA. These PCR products are subsequently separated by gel electrophoresis and quantified using densitometric analysis. We applied the SLAP to verify the position and assess the frequency of m6A sites present on two exemplary long non-coding RNAs. We assessed the SLAP specificity, accuracy, and sensitivity, proving the applicability of this method for the m6A analysis on less abundant transcripts. Overall, this method constitutes an extension of the bird’s-eye view of RNA m6A landscape provided by epitranscriptome-wide analyses by delivering quantitative assessment of modification frequency and can therefore aid the understanding of the consequences of m6A on biological processes. Graphical Abstract
Mutation rate variation shapes genome-wide diversity in Drosophila melanogaster

What shapes the distribution of nucleotide diversity along the genome? Attempts to answer this question have sparked debate about the roles of neutral stochastic processes and natural selection in molecular evolution. However, the mechanisms of evolution do not act in isolation, and integrative models that simultaneously consider the influence of multiple factors on diversity are lacking; without them, confounding factors lurk in the estimates. Here we present a new statistical method that jointly infers the genomic landscapes of genealogies, recombination rates and mutation rates. In doing so, our model captures the effects of genetic drift, linked selection and local mutation rates on patterns of genomic variation. Guided by our causal model, we use linear regression to estimate the individual contributions of these micro-evolutionary forces to levels of nucleotide diversity. Our analyses reveal the signature of selection in Drosophila melanogaster, but we estimate that the mutation landscape is the major driver of the distribution of diversity in this species. Furthermore, our simulation study suggests that in many evolutionary scenarios the mutation landscape will be a crucial force shaping diversity, depending notably on the genomic window size used in the analysis. We argue that incorporating mutation rate variation into the null model of molecular evolution will lead to more realistic inference in population genomics.
Bulk Heterojunction Tandem Photoelectric Cell Based on p-Si and Phthalocyanine

An organic-inorganic (p-Si and phthalocyanine) hybrid tandem heterojunction Ag/p-Si/AlPc:H2Pc/ITO photoelectric cell was fabricated by pressing technology using preliminary vapor deposited heterojunction films of mixed aluminum-phthalocyanine (AlPc) and metal free phthalocyanine (H2Pc) on p-Si substrate and on ITO coated plastic substrate. By keeping organic films face to face both substrates were pressed and fixed together by adhesive at elevated temperature. Total thickness of the AlPc and H2Pc films were equal to 300 nm. On the back side of p-Si substrate the Ag film was deposited. The device architecture was the following: Ag/p-Si/AlPc:H2Pc/ITO. The morphology of the organic semiconductors film was investigated by AFM. The optical properties of the AlPc:H2Pc film were studied by UV-visible spectroscope. Current-Voltage characteristics were measured in dark and also illumination conditions. Under illumination of 296 W/m(2) the values of V-oc, I-SC, FF and efficiency were equal to 0.5 V, 4 mA, 0.45 and 0.61 %, respectively. The I-V and P-V characteristics of the solar cell were simulated by using Shockley equation and its Newton Raphson solution, respectively for dark and illumination conditions. The obtained simulated results were in good agreement with the experimental results.
Zoonotic potential of a novel bat morbillivirus

Bats are significant reservoir hosts for many viruses with zoonotic potential1. SARS-CoV-2, Ebola virus, and Nipah virus are examples of such viruses that have caused deadly epidemics and pandemics when spilled over from bats into human and animal populations2,3. Careful surveillance of viruses in bats is critical for identifying potential zoonotic pathogens. However, metagenomic surveys in bats often do not result in full-length viral sequences that can be used to regenerate such viruses for targeted characterization4. Here, we identify and characterize a novel morbillivirus from a vespertilionid bat species (Myotis riparius) in Brazil, which we term myotis bat morbillivirus (MBaMV). There are 7 species of morbilliviruses including measles virus (MeV), canine distemper virus (CDV) and rinderpest virus (RPV)5. All morbilliviruses cause severe disease in their natural hosts6–10, and pathogenicity is largely determined by species specific expression of canonical morbillivirus receptors, CD150/SLAMF111 and NECTIN412. MBaMV used Myotis spp CD150 much better than human and dog CD150 in fusion assays. We confirmed this using live MBaMV that was rescued by reverse genetics. Surprisingly, MBaMV replicated efficiently in primary human myeloid but not lymphoid cells. Furthermore, MBaMV replicated in human epithelial cells and used human NECTIN4 almost as well as MeV. Our results demonstrate the unusual ability of MBaMV to infect and replicate in some human cells that are critical for MeV pathogenesis and transmission. This raises the specter of zoonotic transmission of a bat morbillivirus.
DYNAMICS OF NEUROMUSCULAR TRANSMISSION REPRODUCED BY CALCIUM-DEPENDENT SERIAL TRANSITIONS IN THE VESICLE FUSION COMPLEX

Neuromuscular transmission, from spontaneous release to facilitation and depression was accurately reproduced by a mechanistic kinetic model of sequential maturation transitions in the molecular fusion complex. The model incorporates three predictions. First, sequential calcium-dependent forward transitions take vesicles from docked to pre-primed to primed states, followed by fusion. Second, pre-priming and priming are reversible. Third, fusion and recycling are unidirectional. The model was fed with experimental data from previous studies while the backward (β) and recycling (ρ) rate constant values were fitted. Classical experiments were successfully reproduced when every forward (α) rate constant had the same value, and both backward rate constants were 50-100 times larger. Such disproportion originated an abruptly decreasing gradient of resting vesicles from docked to primed states. Simulations also predict that: i. Spontaneous release reflects primed to fusion spontaneous transitions. ii. Calcium elevations synchronize the series of forward transitions that lead to fusion. iii Facilitation reflects a transient increase of priming following calcium-dependent transitions. iv. Backward transitions and recycling restore the resting state. v. Depression reflects backward transitions and slow recycling after intense release. Such finely-tuned kinetics offers a mechanism for collective non-linear transitional adaptations of a homogeneous vesicle pool to an ever-changing pattern of electrical activity.
Collective dynamics support group drumming, reduce variability, and stabilize tempo drift

Humans are social animals who engage in a variety of collective activities requiring coordinated action. Among these, music is a defining and ancient aspect of human sociality. Human social interaction has largely been addressed in dyadic paradigms and it is yet to be determined whether the ensuing conclusions generalize to larger groups. Studied more extensively in nonhuman animal behaviour, the presence of multiple agents engaged in the same task space creates different constraints and possibilities than in simpler dyadic interactions. We addressed whether collective dynamics play a role in human circle drumming. The task was to synchronize in a group with an initial reference pattern and then maintain synchronization after it was muted. We varied the number of drummers, from solo to dyad, quartet, and octet. The observed lower variability, lack of speeding up, smoother individual dynamics, and leader-less inter-personal coordination indicated that stability increased as group size increased, a sort of temporal wisdom of crowds. We propose a hybrid continuous-discrete Kuramoto model for emergent group synchronization with pulse-based coupling that exhibits a mean field positive feedback loop. This research suggests that collective phenomena are among the factors that play a role in social cognition.