Miracle-dz/UniFAR-FTUs huggingface dataset:
Tell Me When Users Leave: Predicting Users’ Abandonment of A Task-Oriented Chatbot Service using Explainable Deep Learning

Task-oriented chatbots have been widely used by businesses to support users in accomplishing predefined tasks. Yet, conversation breakdowns could result in users abandoning the chatbot service. Detecting or early predicting signals of users’ chatbot abandonment could help businesses know when to provide assistance. Based on an annotated conversation log involving 1,837 users, we built two models, one end-to-end model built on top of pre-trained BERT models, and the other being an attention-based deep learning model trained from 102 different handcrafted features derived from annotated messages. The former achieved an AUROC of 90%. The latter explainable model, despite the extra effort of adding annotations, achieved a higher AUROC of 95.7% and provided additional insights into important features indicative of service abandonment, such as input types, error types, and presence of users’ information-request within recently exchanged messages.
Digital biomarkers from sweat analysis for therapeutic drug monitoring in soft tissue infections

Antimicrobial resistance is increasing morbidity and mortality and significantly affecting global health. Inappropriate use of antimicrobial drugs can lead to antimicrobial resistances and serious side effects. Therapeutic drug monitoring (TDM) at the point of need has been proven to be a valuable tool to prevent the emergence of antimicrobial resistances. However, TDM focuses on blood levels rather than concentrations at the source of infection. There is no reliable TDM monitoring approach in soft tissue infections, despite significant interpersonal differences in antibiotic tissue penetration, e.g., in patients with peripheral arterial disease. The excretion of a variety of antibiotics into sweat has been a very promising surrogate marker for tissue penetration. Novel wearable on-skin sweat analysing biosensors are increasingly available. Those biosensors are based on different sensing approaches such as electrochemical or aptameric sensors. They are connectable mostly through Bluetooth with the users' device and enable a lab-independent point-of-care analysis. Despite that a specific on-skin detecting device for antibiotics remains lacking yet, wearable sweat analysis is a very promising, novel approach to provide antimicrobial TDM in soft tissue infections and needs further investigation.
End-user feedback in multi-user workflow systems

Workflow systems are more and more common due to the automation of business processes. The automation of business processes enables organizations to simplify their processes, improve services and contain costs. A problem with using workflow systems is that processes once known by heart, are now hidden from the user. This, combined with time pressure, lack of experience and an abundance of options, makes it harder for a user to make the right choices. To aid users of these systems, we have developed a multi-user rule-based problem-solving framework that can be instantiated for many workflow systems. It provides hints to the end user on how to achieve her goals and makes life for the programmer easier, as she only needs to instantiate the framework instead of programming an ad-hoc solution. Our approach consists of two parts. First, we present a domain-specific language (DSL) that offers commonly used constructs for combining components of different rule-based problems. Second, we use generic search algorithms to solve various kinds of problems. We show a practical implementation with an example workflow system. We show that this system fulfills several desirable properties.
Punishing for the Past (Sometimes): Judicial Perspectives on Criminal History Enhancements

Prior criminal record is routinely cited as one of the primary determinants of sentencing, and the common view is that prior record was a leading factor in non-guidelines jurisdictions going back decades. Yet, recent findings from a non-guidelines state failed to conform to this account. This study uses interviews with judges from a non-guidelines state to understand the role of prior record in sentencing in an unstructured sentencing state. This study also reexamines some of the early sentencing guidelines formation literature and finds some indications that pre-guidelines, prior record was not universally an instrumental predictor of sentence length.
Exploring the Differences in Macrocognition between Experts and Non-CHD experts managing Congenital Heart Disease (CHD)

Background and aims: Children with congenital heart disease (CHD) are at risk of deterioration in the face of common childhood illnesses, and their resuscitation and acute management is often best achieved with the guidance of CHD experts. Access to such expertise may be limited outside specialty heart centers and the fragility of these patients is cause for discomfort among many emergency medicine physicians. An understanding of the differences in macrocognition of these clinicians could shed light on some of the causes of discomfort and facilitate the development of a sociotechnological solution to this problem. Methods: Cardiac intensivists (CHD experts) and pediatric emergency medicine physicians (non-CHD experts) in a major academic cardiac center were interviewed using the critical decision method. Interview transcripts were coded deductively based on Klein’s macrocognitive framework and inductively to allow for new or modified characterization of dimensions. Results: While both CHD-experts and non-CHD experts relied on the macrocognitive functions of sensemaking, naturalistic decision making and detecting problems, the specific data and mental models used to understand the patients and course of therapy differed between CHD-experts and non-CHD experts. Conclusion: Characterization of differences between the macrocognitive processes of CHD experts and non-CHD experts can inform development of sociotechnological solutions to augment decision making pertaining to the acute management of pediatric CHD patients.
Evaluating Psychosocial Support Provided by an Augmented Reality Device for Children with Type 1 Diabetes

Type 1 diabetes (T1D), previously known as juvenile diabetes, has a large impact on everyday life and can pose a number of challenges for both children and their parents. A patient-centered design company, Sproutel, has designed and developed Jerry the Bear®—an interactive augmented reality (AR) stuffed animal toy bear designed to provide children with T1D with comfort and education about their diabetes management through play. We evaluated the AR device in a research study that involved participation over the course of approximately two weeks; the overall research project spanned three years and involved a variety of partners. We investigated whether Jerry the Bear offered psychosocial support to children with T1D and their parents and whether a new prototype version (equipped with audio feedback) offered any additional benefits. We conducted two versions of the study—a lab study (n = 11) and a remote study without any in-person component (n = 14). We found two major takeaways: (1) The results from the remote study closely paralleled the more time- and effort-intensive lab study, pointing to a promising avenue of research for hard-to-reach populations. (2) Jerry the Bear had a positive impact on children with T1D and their parents in almost all cases—in some the impact was more neutral, but never markedly negative. We did not find evidence for a consistent preference between the current Jerry the Bear and the new prototype. We also discuss the challenges of conducting rigorous research in highly specific target populations.
Examining the Influence of Power Distance on Psychological Safety Within Healthcare Teams

Cultivating good teamwork practices within healthcare teams is important for providing effective patient care and preventing adverse health outcomes. Psychological safety is one factor which is instrumental in developing a positive team environment, which fosters effective teamwork. The historically hierarchical nature of healthcare ascribes status to individuals based on profession, and this power differential is a contributing factor to a team member’s psychological safety. This study seeks to identify relationships between cultural backgrounds and teamwork in healthcare through examining how power distance influences psychological safety within healthcare teams. A cross-sectional questionnaire containing the Psychological Safety Scale and the Personal Cultural Orientation Scale was fielded to sets of Internal medicine teams working in a health system located in the Midwest region of the United States (n=17). Levels of power-distance and psychological safety were similar amongst leaders and their team members. Upon comparison, there was no correlation found between power distance and psychological safety. Moderate to significant correlations were found between other deep cultural constructs.
LinkIt: A Tool for Assessing and Providing Formative Feedback for Structural Knowledge

It is challenging to assess the effectiveness of learning and training. Most evaluators rely on multiple choice, fill-in-the-blank, and essay questions. These are time-consuming, provide little formative value, and provide no visualization of the knowledge domain. LinkIt uses constrained concept mapping to elicit, score, represent visually, and provide immediate feedback on student knowledge networks by comparing them to expert networks.
Programmable spintronic logic devices for reconfigurable computation and beyond - History and outlook

Non-volatile and programmable logic devices are desirable for future reconfigurable computer on chip. Spintronic logic devices, which use both electron spin and charge, can satisfy these requirements. Moreover, small device size, low power consumption, fast switching speed and programmable "on the fly" make it the most promising candidate for the next generation logic devices. First, this paper reviews the different types of spintronic logic devices. Secondly, we review the proposal and experimental demonstration of the magnetic tunnel junction (MTJ) and giant magnetoresistance element (GMR) based logic devices with the focus on the development of single MTJ logic device with programmable functions and a MTJ-based full-adder logic circuit. Thirdly, a new generation of spintronic logic devices based on spin torque transfer switching mechanism (or so-called current-induced-magnetization switching) is introduced. The last part gives an outlook of future prospective of spintronic logic devices and challenges.
ME2 Promotes Proneural–Mesenchymal Transition and Lipogenesis in Glioblastoma

Malic enzyme 2 (ME2) catalyzes the formation of pyruvate from malic acid and is abnormally expressed in some tumors. However, the exact effects of ME2 on proneural–mesenchymal transition (PMT) and lipogenesis in glioblastoma multiforme (GBM) remain unexplored. Here, we found that ME2 expression was significantly higher in GBM than in normal brain tissues and negatively correlated with overall survival of patients with GBM. Furthermore, we demonstrated that ME2 was positively correlated with mesenchymal features in GBM and promoted proliferation, migration, and invasion of glioma cells. Moreover, ME2 upregulated the expression of mesenchymal markers (N-cadherin, vimentin, YKL40, and MET), whereas it inhibited the expression of proneural maker OLIG2, indicating that ME2 might promote PMT in GBM. We also found that ME2 inhibited the production of mitochondrial reactive oxygen species and AMPK phosphorylation, resulting in SREBP-1 maturation and nuclear localization and enhancing the ACSS2 lipogenesis pathway. Taken together, these results suggest that ME2 promotes PMT and is linked with reprogramming of lipogenesis via AMPK–SREBP-1–ACSS2 signaling in GBM. Therefore, ME2 has potential as a new classification marker in GBM and could provide a new approach to glioma treatment.
Rapamycin microparticles induce autophagy, prevent senescence and are effective in treatment of Osteoarthritis

Trauma to the knee joint is associated with significant cartilage degeneration and erosion of subchondral bone, which eventually leads to osteoarthritis (OA), resulting in substantial morbidity and healthcare burden. With no disease-modifying drugs in clinics, the current standard of care focuses on symptomatic relief and viscosupplementation. Modulation of autophagy and targeting senescence pathways are emerging as potential treatment strategies. Rapamycin has shown promise in OA disease amelioration by autophagy upregulation, yet its clinical use is hindered by difficulties in achieving therapeutic concentrations, necessitating multiple weekly injections. Here, we have synthesized rapamycin - loaded poly (lactic-co-glycolic acid) microparticles (RMPs) that induced autophagy, prevented senescence and sustained sulphated glycosaminoglycans(sGAG) production in primary human articular chondrocytes from OA patients. RMPs were potent, nontoxic, and exhibited high retention time (up to 35 days) in mice joints. Intra-articular delivery of RMPs effectively mitigated cartilage damage and inflammation in surgery-induced OA when administered as a prophylactic or therapeutic regimen. Together, our studies demonstrate the feasibility of using RMPs as a potential clinically translatable therapy to prevent and treat post-traumatic osteoarthritis. Graphical Abstract
A Single Oral Immunization with a Replication-Competent Adenovirus-Vectored Vaccine Protects Mice from Influenza Respiratory Infection

Given the constant threat of pandemics and the need for annual vaccination against influenza and possibly emerging agents such as SARS-CoV-2, new types of vaccines that are easier to administer and therefore more widely accepted are a critical public health need. Here, using a relevant animal model, we have shown that replicative oral AdV vaccine vectors can help make vaccination against major respiratory diseases more available, better accepted, and therefore more effective. ABSTRACT The development of effective and flexible vaccine platforms is a major public health challenge, especially in the context of influenza vaccines that have to be renewed every year. Adenoviruses (AdVs) are easy to produce and have a good safety and efficacy profile when administered orally, as demonstrated by the long-term use of oral AdV-4 and -7 vaccines in the U.S. military. These viruses therefore appear to be the ideal backbone for the development of oral replicating vector vaccines. However, research into these vaccines is limited by the ineffectiveness of human AdV replication in laboratory animals. The use of mouse AdV type 1 (MAV-1) in its natural host allows infection to be studied under replicating conditions. Here, we orally vaccinated mice with a MAV-1 vector expressing influenza hemagglutinin (HA) to assess the protection conferred against an intranasal challenge of influenza. We showed that a single oral immunization with this vaccine generates influenza-specific and -neutralizing antibodies and completely protects mice against clinical signs and viral replication, similar to traditional inactivated vaccines. IMPORTANCE Given the constant threat of pandemics and the need for annual vaccination against influenza and possibly emerging agents such as SARS-CoV-2, new types of vaccines that are easier to administer and therefore more widely accepted are a critical public health need. Here, using a relevant animal model, we have shown that replicative oral AdV vaccine vectors can help make vaccination against major respiratory diseases more available, better accepted, and therefore more effective. These results could be of major importance in the coming years in the fight against seasonal or emerging respiratory diseases such as COVID-19.
Degradation of red blood cell deformability during cold storage in blood bags

Red blood cells (RBCs) stored in blood bags develop a storage lesion that include structural, metabolic, and morphologic transformations resulting in a progressive loss of RBC deformability. The speed of RBC deformability loss is donor-dependent, which if properly characterized, could be used as a biomarker to select high-quality RBC units for sensitive recipients or to provide customized storage timelines depending on the donor. We used the microfluidic ratchet device to measure the deformability of red blood cells stored in blood bags every 14 days over a span of 56 days. We observed that storage in blood bags generally prevented RBC deformability loss over the current standard 42-day storage window. However, between 42 and 56 days, the deformability loss profile varied dramatically between donors. In particular, we observed accelerated RBC deformability loss for a majority of male donors, but for none of the female donors. Together, our results suggest that RBC deformability loss could be used to screen for donors who can provide stable RBCs for sensitive transfusion recipients or to identify donors capable of providing RBCs that could be stored for longer than the current 42-day expiration window.
Gram-positive bacteria secrete RNA aptamers to activate human STING for IL-1β release

Molecular mechanisms through which Gram-positive bacteria induce the canonical inflammasome are poorly understood. Here, we studied the effects of Group B streptococci (GBS) and Staphylococcus aureus (SA) on inflammasome activation in human macrophages. Dinucleotide binding small RNA aptamers released by SA and GBS were shown to trigger increased IL-1β generation by inflammasomes. The stimulator of interferon genes-STING as a central mediator of innate immune responses has been identified as the key target of pathogenic RNA. Multi-lamellar lipid bodies (MLBs) produced by SA function as vehicles for the RNA aptamers. Notably, expression of RNA aptamers is controlled by an accessory gene regulator quorum sensing system of the bacteria. These findings have been translated to patients with Gram-positive sepsis showing hallmarks of MLB-RNA-mediated inflammasome activation. Together our findings may provide a new perspective for the pathogenicity of Gram-positive bacterial infection in man.
Rewiring phospholipid biosynthesis reveals robustness in membrane homeostasis and uncovers lipid regulatory players

Intracellular transport of lipids by Lipid Transport Proteins (LTPs) is thought to work alongside vesicular transport to shuttle lipids from their place of synthesis to their destinations. Whereas many LTPs have been identified, it is largely unknown which routes and which LTPs a given lipid utilizes to navigate the multiple membranes of eukaryotic cells. The major and essential phospholipids, phosphatidylethanolamine (PE) and phosphatidylcholine (PC) can be produced by multiple pathways and, in the case of PE, also at multiple locations. Here, we present an approach in which we simplify and rewire yeast phospholipid synthesis by redirecting PE and PC synthesis reactions to distinct subcellular locations using chimeric enzymes fused to specific organelle targeting motifs. In rewired conditions, viability is expected to depend on homeostatic adaptation to the ensuing lipostatic perturbations and on efficient interorganelle lipid transport. We therefore performed genetic screens to identify factors involved in both of these processes. Among the candidates identified, we find genes linked to transcriptional regulation of lipid homeostasis, lipid metabolism and transport. In particular, we identify a requirement for Csf1 –an uncharacterized protein harboring a Chorein-N lipid transport domain- for survival under certain rewired conditions as well as lipidomic adaptation to cold, implicating Csf1 in interorganelle lipid transport and homeostatic adaptation.
Neural Collision Detection: an open source library to study the three-dimensional interactions of neurons and other tree-like structures

The analysis of neuronal structure and its relation to function has become a fundamental pillar in neuroscience since its earliest days, with the underlying premise that morphological properties can modulate neuronal computations. It is often the case that the rich three-dimensional structure of neurons is quantified by tools developed in other fields, such as graph theory and computational geometry; nevertheless, some of the more advanced tools developed in these fields have not yet been made accessible to the neuroscience community. Here we present Neural Collision Detection, a library providing high-level interfaces to collision-detection routines and alpha shape calculations, as well as statistical analysis and visualizations for 3D objects, with the aim to lower the entry gap for neuroscientists into these worlds. Our work here also demonstrates a variety of use cases for the library and exemplary analysis and visualizations that were carried out with it on real neuronal and vascular data.
PD-Based Optimal ADRC with Improved Linear Extended State Observer

Taking dead-zone nonlinearlity and external disturbances into account, an active disturbance rejection optimal controller based on a proportional-derivative (PD) control law is proposed by connecting the proportional-integral-derivative (PID) control, the active disturbance rejection control (ADRC) and particle swarm optimization (PSO), with the purpose of providing an efficient and practical technology, and improving the dynamic and steady-state control performances. Firstly, in order to eliminate the negative effects of the dead-zone, a class of 2-order typical single-input single-out system model is established after compensating the dead-zone. Following that, PD control law is introduced to replace the state error feedback control law in ADRC to simplify the control design. By analyzing the characteristics of the traditional linear extended state observer, an improved linear extended state observer is designed, with the purpose of improving the estimation performance of disturbances. Moreover, employing PSO with a designed objective function to optimize parameters of controller to improve control performance. Finally, ten comparative experiments are carried out to verify the effectiveness and superiority of the proposed controller.
Implementation and Accuracy Evaluation of Fixed Camera-Based Object Positioning System Employing CNN-Detector

Today, different positioning applications such as location-based services and autonomous navigation are requiring more and more precision. Especially fully autonomous navigation requires accurate positioning solution, not only for the vehicle but also for the surrounding objects. Thus, many new positioning techniques, algorithms and fusion schemes have been developed. One essential technique is visual positioning. Thanks to intensive research in neural networks and deep learning, Convolutional Neural Network-based (CNN) object detectors have evolved greatly in recent years. This paper proposes a widely deployable scheme of fixed camera-based (e.g. surveillance camera) object positioning utilizing the CNN-detector. The accuracy of the implemented positioning solution is evaluated with precise Real-Time Kinematic (RTK) satellite positioning receiver. The implemented system can be used in indoors and outdoors, and it can estimate simultaneously positions from multiple camera views for multiple objects in real-time. When positioning a person, the measured mean positioning error was 10.7–15.6 cm with a simple bias correction and a standard deviation was 6.7–8.7 cm. Thus, the accuracy is excellent and would be sufficient to wide variety of applications.