Miracle-dz/UniFAR-FTUs huggingface dataset:
Bayesian item response models for citizen science ecological data

So-called 'citizen science' data elicited from crowds has become increasingly popular in many fields including ecology. However, the quality of this information is being frequently debated by many within the scientific community. Therefore, modern citizen science implementations require measures of the users' proficiency that account for the difficulty of the tasks. We introduce a new methodological framework of item response and linear logistic test models with application to citizen science data used in ecology research. This approach accommodates spatial autocorrelation within the item difficulties and produces relevant ecological measures of species and site-related difficulties, discriminatory power and guessing behavior. These, along with estimates of the subject abilities allow better management of these programs and provide deeper insights. This paper also highlights the fit of item response models to big data via divide-and-conquer. We found that the suggested methods outperform the traditional item response models in terms of RMSE, accuracy, and WAIC based on leave-one-out cross-validation on simulated and empirical data. We present a comprehensive implementation using a case study of species identification in the Serengeti, Tanzania. The R and Stan codes are provided for full reproducibility. Multiple statistical illustrations and visualizations are given which allow practitioners the extrapolation to a wide range of citizen science ecological problems.
Template-based Unseen Instance Detection

Much of the focus in the object detection literature has been on the problem of identifying the bounding box of a particular class of object in an image. Yet, in contexts such as robotics and augmented reality, it is often necessary to find a specific object instance---a unique toy or a custom industrial part for example---rather than a generic object class. Here, applications can require a rapid shift from one object instance to another, thus requiring fast turnaround which affords little-to-no training time. In this context, we propose a generic approach to detect unseen instances based on templates rendered from a textured 3D model. To this effect, we introduce a network architecture which employs tunable filters, and leverage learned feature embeddings to correlate object templates and query images. At test time, our approach is able to successfully detect a previously unknown (not seen in training) object, even under significant occlusion. For instance, our method offers an improvement of almost 30 mAP over the previous template matching methods on the challenging Occluded Linemod (overall mAP of 50.7). With no access to the objects to be detected at training time, our method still yields detection results that are on par with existing ones that are allowed to train on the objects. By reviving this research direction in the context of more powerful, deep feature extractors, our work sets the stage for more development in the area of unseen object instance detection.
Modeling Ultrasound Propagation in the Moving Brain: Applications to Shear Shock Waves and Traumatic Brain Injury

Traumatic brain injury (TBI) studies on the living human brain are experimentally infeasible due to ethical reasons and the elastic properties of the brain degrade rapidly postmortem. We present a simulation approach that models ultrasound propagation in the human brain, while it is moving due to the complex shear shock wave deformation from a traumatic impact. Finite difference simulations can model ultrasound propagation in complex media such as human tissue. Recently, we have shown that the fullwave finite difference approach can also be used to represent displacements that are much smaller than the grid size, such as the motion encountered in shear wave propagation from ultrasound elastography. However, this subresolution displacement model, called impedance flow, was only implemented and validated for acoustical media composed of randomly distributed scatterers. Herein, we propose a generalization of the impedance flow method that describes the continuous subresolution motion of structured acoustical maps, and in particular of acoustical maps of the human brain. It is shown that the average error in simulating subresolution displacements using impedance flow is small when compared to the acoustical wavelength ( $\lambda $ /1702). The method is then applied to acoustical maps of the human brain with a motion that is imposed by the propagation of a shear shock wave. This motion is determined numerically with a custom piecewise parabolic method that is calibrated to ex vivo observations of shear shocks in the porcine brain. Then the fullwave simulation tool is used to model transmit-receive imaging sequences based on an L7-4 imaging transducer. The simulated radio frequency data are beamformed using a conventional delay-and-sum method and a normalized cross-correlation method designed for shock wave tracking is used to determine the tissue motion. This overall process is an in silico reproduction of the experiments that were previously performed to observe shear shock waves in fresh porcine brain. It is shown that the proposed generalized impedance flow method accurately captures the shear wave motion in terms of the wave profile, shock front characteristics, odd harmonic spectrum generation, and acceleration at the shear shock front. We expect that this approach will lead to improvements in image sequence design that takes into account the aberration and multiple reflections from the brain and in the design of tracking algorithms that can more accurately capture the complex brain motion that occurs during a traumatic impact. These methods of modeling ultrasound propagation in moving media can also be applied to other displacements, such as those generated by shear wave elastography or blood flow.
Perfusion index as an early predictor of hypotension following spinal anesthesia for cesarean section

Introduction: Hypotension is a common complication after spinal anesthesia for cesarean delivery which is caused by sympathetic block 1. This can result in adverse maternal and fetal outcomes. Hence prevention and early treatment of spinal hypotension early has been a key research area in obstetric anesthesia. Intermittent non-invasive blood pressure measurement is the standard practice that fails to detect episodes of hypotension in a timely fashion. Methods: Noninvasive PI and blood pressure were measured in 109 healthy parturients undergoing elective cesarean section under spinal anesthesia. Results: PI appeared to increase significantly and more quickly in parturients with significant hypotension. Discussion: Findings may be due to the thoracic sympathetic blockade. Conclusion: Perfusion index can be a useful tool to early predict hypotension following spinal anesthesia for cesarean section. Response to ephedrine can be quickly assessed by the change in the PI which helps to decide on further boluses of ephedrine. Effect on the vascular tone by oxytocin is significant with 5IU bolus, though it does not cause a significant blood pressure drop.
Web 2.0 Approaches for Active, Collaborative Learning in Medicine and Health

In recent years, advances in information and communication technology and especially the Internet have acted as catalysts for significant developments in the sector of health care, having a strong impact in supporting medical diagnosis, enabling efficient and effective patient and healthcare management and reforming medical education. There is currently an international trend to involve computers and the Internet heavily in medical curricula, in continuing life-long medical learning, as well as in general health education of the public. However, effective technology-supported interventions are usually created when there is a successful alignment of the specific requirements with the potential end use of technol - ogy. And it is just such a juncture we are currently facing with the emergent paradigm of Web 2.0. This chapter elaborates on the potential of Web 2.0 for active and, potentially, effective learning in medicine and in health and reviews current practices and trends in the field. The discussion focuses on research directions and emerging applications that fully exploit the potential of Web 2.0 for advancing medical education. Finally, the envisaged merit of merging with Web 3.
CD19+CD1dhiCD5hi B Cells Can Downregulate Malaria ITV Protection by IL-10 Secretion

Infection treatment vaccine (ITV) can lead to sterile protection against malaria infection in mice and humans. However, parasite breakthrough is frequently observed post-challenge. The mechanism of rapid decline in protection after the last immunization is unclear. Herein, C57BL/6 mice were immunized with 103, 105, or 107 ITV thice at 14-day intervals. Mice were challenged with 103 parasites at 1, 3, and 6 months after last immunization and the protection was checked using blood smear. The phenotypes of B cells were analyzed by flow cytometry. The levels of serum cytokines were quantified using cytometric bead array. The 103 ITV vaccination group exhibited 100% protection at 1 month after last immunization, and the 105 group showed sterile protection at 3 months after last immunization. However, the 107 group showed only partial protection. Further, the protection declined to 16.7% at 6 months after last immunization in 105 and 107 groups, whereas it maintained for more than 60% in 103 group. The number of memory B cells (MBC) decreased along with the decline in protection. However, programmed cell death protein 1 (PD-1) expressed on MBCs did not show significant variation among the three groups. Interestingly, CD19+CD1dhiCD5hi B cells, defined as B10 cells, exhibited negative regulation with respect to protection. The numbers of CD19+CD1dhiCD5hi B cells in the 103 group at 1 months and in the 105 group at 3 months post-immunization were the lowest compared to those in the other groups. Moreover, the serum levels of interleukin 10 (IL-10) in these two groups were also significantly lower than those in other groups. We conclude that higher immunization dose may not lead to better protection with the malaria vaccine as CD19+CD1dhiCD5hi B cells can downregulate ITV protection against malaria via IL-10 secretion. These results could facilitate the design of an effective long-lasting malaria vaccine with the aim of maintaining MBC function.
Synthesis of Flexible Accelerators for Early Adoption of Ring-LWE Post-quantum Cryptography

The advent of the quantum computer makes current public-key infrastructure insecure. Cryptography community is addressing this problem by designing, efficiently implementing, and evaluating novel public-key algorithms capable of withstanding quantum computational power. Governmental agencies, such as NIST, are promoting standardization of quantum-resistant algorithms that is expected to run for 7 years. Several modern applications must maintain permanent data secrecy; therefore, they ultimately require the use of quantum-resistant algorithms. Because algorithms are still under scrutiny for eventual standardization, the deployment of the hardware implementation of quantum-resistant algorithms is still in early stages. In this article, we propose a methodology to design programmable hardware accelerators for lattice-based algorithms, and we use the proposed methodology to implement flexible and energy efficient post-quantum cache-based accelerators for NewHope, Kyber, Dilithium, Key Consensus from Lattice (KCL), and R.EMBLEM submissions to the NIST standardization contest. To the best of our knowledge, we propose the first efficient domain-specific, programmable cache-based accelerators for lattice-based algorithms. We design a single accelerator for a common kernel among various schemes with different kernel sizes, i.e., loop count, and data types. This is in contrast to the traditional approach of designing one special purpose accelerators for each scheme. We validate our methodology by integrating our accelerators into an HLS-based SoC infrastructure based on the X86 processor and evaluate overall performance. Our experiments demonstrate the suitability of the approach and allow us to collect insightful information about the performance bottlenecks and the energy efficiency of the explored algorithms. Our results provide guidelines for hardware designers, highlighting the optimization points to address for achieving the highest energy minimization and performance increase. At the same time, our proposed design allows us to specify and execute new variants of lattice-based schemes with superior energy efficiency compared to the main application processor without changing the hardware acceleration platform. For example, we manage to reduce the energy consumption up to 2.1× and energy-delay product (EDP) up to 5.2× and improve the speedup up to 2.5×.
Prevalence and Therapies of Antibiotic-Resistance in Staphylococcus aureus

Infectious diseases are the second most important cause of human death worldwide; Staphylococcus aureus (S. aureus) is a very common human pathogenic microorganism that can trigger a variety of infectious diseases, such as skin and soft tissue infections, endocarditis, osteomyelitis, bacteremia, and lethal pneumonia. Moreover, according to the sensitivity to antibiotic drugs, S. aureus can be divided into methicillin-sensitive Staphylococcus aureus (MSSA) and methicillin-resistant Staphylococcus aureus (MRSA). In recent decades, due to the evolution of bacteria and the abuse of antibiotics, the drug resistance of S. aureus has gradually increased, the infection rate of MRSA has increased worldwide, and the clinical anti-infective treatment for MRSA has become more difficult. Accumulating evidence has demonstrated that the resistance mechanisms of S. aureus are very complex, especially for MRSA, which is resistant to many kinds of antibiotics. Therefore, understanding the drug resistance of MRSA in a timely manner and elucidating its drug resistance mechanism at the molecular level are of great significance for the treatment of S. aureus infection. A large number of researchers believe that analyzing the molecular characteristics of S. aureus can help provide a basis for designing effective prevention and treatment measures against hospital infections caused by S. aureus and further monitor the evolution of S. aureus. This paper reviews the research status of MSSA and MRSA, the detailed mechanisms of the intrinsic antibiotic resistance and the acquired antibiotic resistance, the advanced research on anti-MRSA antibiotics and novel therapeutic strategies for MRSA treatment.
Deletion of S-Layer Associated Ig-Like Domain Protein Disrupts the Lactobacillus acidophilus Cell Surface

Bacterial surface-layers (S-layers) are crystalline arrays of repeating proteinaceous subunits that coat the exterior of many cell envelopes. S-layers have demonstrated diverse functions in growth and survival, maintenance of cell integrity, and mediation of host interactions. Additionally, S-layers can act as scaffolds for the outward display of auxiliary proteins and glycoproteins. These non-covalently bound S-layer associated proteins (SLAPs) have characterized roles in cell division, adherence to intestinal cells, and modulation of the host immune response. Recently, IgdA (LBA0695), a Lactobacillus acidophilus SLAP that possesses a Group 3 immunoglobulin (Ig)-like domain and GW (Gly-Tryp) dipeptide surface anchor, was recognized for its high conservation among S-layer-forming lactobacilli, constitutive expression, and surface localization. These findings prompted its selection for examination within the present study. Although IgdA and corresponding orthologs were shown to be unique to host-adapted lactobacilli, the Ig domain itself was specific to vertebrate-adapted species suggesting a role in vertebrate adaptation. Using a counterselective gene replacement system, igdA was deleted from the L. acidophilus NCFM chromosome. The resultant mutant, NCK2532, exhibited a visibly disrupted cell surface which likely contributed to its higher salt sensitivity, severely reduced adhesive capacity, and altered immunogenicity profile. Transcriptomic analyses revealed the induction of several stress response genes and secondary surface proteins. Due to the broad impact of IgdA on the cellular physiology and probiotic attributes of L. acidophilus, identification of similar proteins in alternative bacterial species may help pinpoint next-generation host-adapted probiotic candidates.
An fMRI Study of the Brain Network Involved in Teeth Tapping in Elderly Adults

Cortical activity during jaw movement has been analyzed using various non-invasive brain imaging methods, but the contribution of orofacial sensory input to voluntary jaw movements remains unclear. In this study, we used functional magnetic resonance imaging (fMRI) to observe brain activities during a simple teeth tapping task in adult dentulous (AD), older dentulous (OD), and older edentulous subjects who wore dentures (OEd) or did not wear dentures (OE) to analyze their functional network connections. (1) To assess the effect of age on natural activation patterns during teeth tapping, a comparison of groups with natural dentition—AD and OD—was undertaken. A general linear model analysis indicated that the major activated site in the AD group was the primary sensory cortex (SI) and motor cortex (MI) (p < 0.05, family wise error corrected). In the OD group, teeth tapping induced brain activity at various foci (p < 0.05, family wise error corrected), including the SI, MI, insula cortex, supplementary motor cortex (SMC)/premotor cortex (PMA), cerebellum, thalamus, and basal ganglia in each group. (2) Group comparisons between the OD and OEd subjects showed decreased activity in the SI, MI, Brodmann’s area 6 (BA6), thalamus (ventral posteromedial nucleus, VPM), basal ganglia, and insular cortex (p ¡ 0.005, uncorrected). This suggested that the decreased S1/M1 activity in the OEd group was related to missing teeth, which led to reduced periodontal afferents. (3) A conjunction analysis in the OD and OEd/OE groups revealed that commonly activated areas were the MI, SI, cerebellum, BA6, thalamus (VPM), and basal ganglia (putamen; p < 0.05, FWE corrected). These areas have been associated with voluntary movements. (4) Psychophysiological interaction analysis (OEd vs OE) showed that subcortical and cortical structures, such as the MI, SI, DLPFC, SMC/PMA, insula cortex, basal ganglia, and cerebellum, likely function as hubs and form an integrated network that participates in the control of teeth tapping. These results suggest that oral sensory inputs are involved in the control of teeth tapping through feedforward control of intended movements, as well as feedback control of ongoing movements.
Comparison Dynamics in Population Protocols

There has recently been a surge of interest in the computational and complexity properties of the population model, which assumes n anonymous, computationally-bounded nodes, interacting at random, with the goal of jointly computing global predicates. Significant work has gone towards investigating majority or consensus dynamics in this model: that is, assuming that every node is initially in one of two states X or Y, determine which state had higher initial count. In this paper, we consider a natural generalization of majority/consensus, which we call comparison : in its simplest formulation, we are given two baseline states, X and Y, present in any initial configuration in fixed, but possibly small counts. One of these states has higher count than the other: we will assume |X_0| > C |Y_0| for some constant C > 1. The challenge is to design a protocol by which nodes can quickly and reliably decide on which of the baseline states X_0 and Y_0 has higher initial count. We begin by analyzing a simple and general dynamics solving the above comparison problem, which uses O( log n ) states per node, and converges in O(log n) (parallel) time, with high probability, to a state where the whole population votes on opinions X or Y at rates proportional to the initial concentrations of |X_0| vs. |Y_0|. We then describe how this procedure can be bootstrapped to solve comparison, i.e. have every node in the population reach the "correct'' decision, with probability 1 - o(1), at the cost of O (log log n) additional states. Further, we prove that this dynamics is self-stabilizing, in the sense that it converges to the correct decision from arbitrary initial states, and leak-robust, in the sense that it can withstand spurious faulty reactions, which are known to occur in practical implementations of population protocols. Our analysis is based on a new martingale concentration result relating the discrete-time evolution of a population protocol to its expected (steady-state) analysis, which should be a useful tool when analyzing opinion dynamics and epidemic dissemination in the population model.
An experimental analysis of the driver’s attention during train driving

Abstract The article deals with the experimental monitoring of the driver’s attention during train operation. SMI eye-tracking technology and eye-tracking glasses we used to measure the train driver’s attention. This unique experiment we performed on the Slovak railway (ŽSR) line no. 120 Bratislava - Žilina, in the section Žilina - Púchov. The measurement took place in the spring of 2017, and the passenger train was operated by the ZSSK electric unit series 671. The article analyses in detail the monitoring of the driver’s attention during train operation. We analysed two typical processes during train driver work: driving at the section (without stopping) and driving through the train station (with stopping). Realised analysis can lead to the identification of critical points on the line, to a better understanding of the driver’s way of work and to contribute to increasing railway safety. The unique measurement procedure and the used technology did not affect the safety of the train operation.