Miracle-dz/UniFAR-FTUs huggingface dataset:
Visual Comparison of Eye Movement Patterns

In eye tracking research, finding eye movement patterns and similar strategies between participants’ eye movements is important to understand task solving strategies and obstacles. In this application paper, we present a graph comparison method using radial graphs that show Areas of Interest (AOIs) and their transitions. An analyst investigates a single graph based on dwell times, directed transitions, and temporal AOI sequences. Two graphs can be compared directly and temporal changes may be analyzed. A list and matrix approach facilitate the analyst to contrast more than two graphs guided by visually encoded graph similarities. We evaluated our approach in case studies with three eye tracking and visualization experts. They identified temporal transition patterns of eye movements across participants, groups of participants, and outliers.
Histone Demethylation Maintains Prdm14 and Tsix Expression and Represses Xist in Embryonic Stem Cells

Epigenetic reprogramming is exemplified by the remarkable changes observed in cellular differentiation and X-chromosome inactivation (XCI) in mammalian female cells. Histone 3 lysine 27 trimethylation (H3K27me3) is a modification that suppresses gene expression in multiple contexts including embryonic stem cells (ESCs) and decorates the entire inactive X-chromosome. The conversion of female somatic cells to induced pluripotency is accompanied by X-chromosome reactivation (XCR) and H3K27me3 erasure. Here, we show that the H3K27-specific demethylase Utx regulates the expression of the master regulators for XCI and XCR: Prdm14, Tsix, and Xist. Female ESC transcriptome analysis using a small molecule inhibitor for H3K27 demethylases, GSK-J4, identifies novel targets of H3K27 demethylation. Consistent with a recent report that GSK-J4 can inhibit other histone demethylase, we found that elevated H3K4me3 levels are associated with increased gene expression including Xist. Our data suggest multiple regulatory mechanisms for XCI via histone demethylation.
Autonomous Vehicle Lane Change Maneuver: A Comprehensive Analysis

The two main parts of an autonomous vehicle lane change maneuver system are a lane change planner and a lane change controller. This paper describes a model-based design strategy for developing such a system. This means that the lane change planner is in charge of creating a lane change trajectory that is both safe and efficient. The lane-changing controller is tasked with the actual execution of the trajectory, involving the management of the vehicle’s steering, acceleration, and braking. The lane change planner utilizes several strategies to craft trajectories that prioritize safety and efficiency. The planner starts with a time-to-collision analysis to determine which targets are safe or hazardous. If the present lane is considered safe, it then generates terminal states that are specific for the front automobile following modes. The lane changing maneuver system underwent evaluation within a simulation environment. The results of this assessment demonstrate the system’s capability to adeptly and securely execute lane change maneuvers across diverse driving scenarios.
The long necks of sauropods did not evolve primarily through sexual selection

It has recently been argued that the elongate necks of sauropod dinosaurs evolved primarily through selection for their use as sexual and dominance signals, and not as an adaptation for accessing a large ‘feeding envelope’ as traditionally thought. Here we explore this idea and show that all six arguments that have been advanced in support of the sexual selection hypothesis are flawed: there is no evidence for sexual dimorphism in the necks of sauropods; neither is there any evidence that they were used in dominance displays; long necks provided significant survival benefits in allowing high browsing and energetically efficient grazing; their fitness cost was likely less than has been assumed; their positive allometry through ontogeny is uninformative given that ontogenetic allometry is common in animals; apparent lack of correlation between neck and leg length across phylogeny is illusory due to over-representation of mamenchisaurids in a previously analysed dataset, and in any case is not informative as the unique morphology of sauropod necks suggests they, rather than legs, may have been cheaper to elongate when evolving increased vertical reach. In no speciose, morphologically varied, longlived tetrapod clade has sexual selection consistently acted on a single part of the body, and it is unlikely that Sauropoda is the exception to this. In summary, there is no convincing evidence that sexual selection was the primary force driving the evolution of sauropod necks. While a subsidiary role for sexual selection cannot be discounted, the traditional hypothesis that sauropod necks evolved primarily due to the feeding benefits that they conferred is, by comparison, far better supported.
A Framework for Multi-Grade Classification of Ulcerative-Colitis Using Deep Neural Networks

Endoscopic disease severity assessment is a critical component in the management of ulcerative colitis patients. Endoscopic evaluation, on the other hand, suffers from significant intra-observer and inter-observer differences, reducing the reliability of individual assessments. As a result, we set out to create a deep-learning model capable of distinguishing between distinct endoscopic disease severity levels. Initially, we preprocessed the dataset and then applied data augmentations on the images using various geometric transformations. Subsequently, we have utilized the transfer learning concept by applying modified ResNet-50 by stacking additional layers which further improves the classification performance. Our proposed model achieved an accuracy of 84.21%, 81.06% recall, and 88.33% precision.
Light Pulse Duration Differentially Regulates Mouse Locomotor Suppression and Phase Shifts

Brief exposure of mice to nocturnal light causes circadian rhythm phase shifts, simultaneously inducing locomotor suppression, a drop in body temperature, and associated sleep. The exact nature of the relationship between these light-induced responses is uncertain, although locomotor suppression and phase shift magnitudes are related to stimulus irradiance. Whether stimulus duration has similar effects is less clear. Here, the relationship between stimulus duration and response magnitude was evaluated further using 100 µW/cm2 white light-emitting diode pulses administered for 30, 300, 1200, or 3000 sec. The results show that, in general, shorter pulses yielded smaller responses and larger pulses yielded larger responses. However, the 300-sec pulse failed to augment locomotor suppression compared with the effect of a 30-sec pulse (44.7 ± 4.8 vs 40.6 ± 2.0 min) but simultaneously induced much larger phase shifts (1.28 ± 0.20 vs 0.52 ± 0.11 h). The larger phase shifts induced by the 300-sec stimulus did not differ from those induced by either the 1200- or 3000-sec pulses (1.43 ± 0.10 and 1.30 ± 0.17 h, respectively). The results demonstrate differential photic regulation of the two response types. Pulses ranging from 300 to 3000 sec produce equal phase shifts (present data); pulses ranging from 30 to 600 sec produce equal locomotor suppression levels. Greater suppression can occur additively in response to pulses of 1200 sec or more (present data), but this is not true for phase shifts. Nocturnal light appears to trigger a fixed duration event, locomotor suppression, or phase shift, with the latter followed by a light-refractory interval during which locomotor suppression can additively increase. The results also provide further support for the view that temporal integration of photic energy applies, at best, across a limited set of stimulus durations for both light-induced locomotor suppression/sleep and phase shift regulation.
Evaluating cross-sensory perception of superimposing virtual color onto real drink: toward realization of pseudo-gustatory displays

In this research, we aim to realize a gustatory display that enhances our experience of enjoying food. However, generating a sense of taste is very difficult because the human gustatory system is quite complicated and is not yet fully understood. This is so because gustatory sensation is based on chemical signals whereas visual and auditory sensations are based on physical signals. In addition, the brain perceives flavor by combining the senses of gustation, smell, sight, warmth, memory, etc. The aim of our research is to apply the complexity of the gustatory system in order to realize a pseudo-gustatory display that presents flavors by means of visual feedback. This paper reports on the prototype system of such a display that enables us to experience various tastes without changing their chemical composition through the superimposition of virtual color. The fundamental thrust of our experiment is to evaluate the influence of cross-sensory effects by superimposing virtual color onto actual drinks and recording the responses of subjects who drink them. On the basis of experimental results, we concluded that visual feedback sufficiently affects our perception of flavor to justify the construction of pseudo-gustatory displays.
Chemical Vapor Deposited Graphene/PDMS based Flexible Strain Sensor for Human Motion Detection Application

This study presents the development and characterization of a flexible Graphene/PDMS-based strain sensor for human motion detection applications. The sensor is fabricated using chemical vapor deposited (CVD) graphene onto a Polydimethylsiloxane (PDMS) substrate. The proposed sensor offers a promising solution for capturing and quantifying the complex deformations associated with human movements. The strain-induced changes in the graphene’s electrical conductivity are monitored and correlated with the applied mechanical strain. The sensor exhibits excellent sensitivity, repeatability, and linearity, making it suitable for accurate and reliable human motion detection. The proposed strain sensor holds great promise for various human-centric applications. Its integration into wearable devices or clothing could provide real-time monitoring of body movements and posture, enabling applications in sports performance analysis, health monitoring, and rehabilitation.
A Pose Association Method for Multi-Agent System Based on LiDAR Pointcloud Registration Algorithm

Pose association is an important problem in intelligent agents, especially in multi-agent systems, because the introduced supplementary pose information can help the localization algorithm and upper-layer modules to improve performances. This paper proposes a new method to build pose association with considerable accuracy and reliability into a multi-agent system. The proposed method utilizes LiDAR pointcloud registration to calculate the pose relationship and has good potential to be applied to most multi-agent systems as long as they are equipped with LiDAR. Modified on Iterative Closest Point (ICP) algorithm, a stepwise registration strategy based on decreased thresholds called DT-ICP is proposed. It can significantly improve the performance of pointcloud registration. Furthermore, we design an additional confidence evaluation module to avoid counter-productive pose associations caused by unreliable registration. The method has been proven to perform well in both simulation test environments and real scenarios.
Continuous Episodic Memory Based Speech Recognition Using Articulatory Dynamics

In this paper we present a speech recognition system based on articulatory dynamics. We do not extend the acoustic feature with any explicit articulatory measurements but instead the ar- ticulatory dynamics of speech are structurally embodied within episodic memories. The proposed recognizer is made of differ- ent memories each specialized for a particular articulator. As all the articulators do not contribute equally to the realization of a particular phoneme, the specialized memories do not per- form equally regarding each phoneme. We show, through phone string recognition experiments that combining the recognition hypotheses resulting from the different articulatory specialized memories leads to significant recognition improvements.
The essence of compiling with continuations

In order to simplify the compilation process, many compilers for higher-order languages use the continuation-passing style (CPS) transformation in a first phase to generate an intermediate representation of the source program. The salient aspect of this intermediate form is that all procedures take an argument that represents the rest of the computation (the “continuation”). Since the nai¨ve CPS transformation considerably increases the size of programs, CPS compilers perform reductions to produce a more compact intermediate representation. Although often implemented as a part of the CPS transformation, this step is conceptually a second phase. Finally, code generators for typical CPS compilers treat continuations specially in order to optimize the interpretation of continuation parameters. A thorough analysis of the abstract machine for CPS terms show that the actions of the code generator invert the nai¨ve CPS translation step. Put differently, the combined effect of the three phases is equivalent to a source-to-source transformation that simulates the compaction phase. Thus, fully developed CPS compilers do not need to employ the CPS transformation but can achieve the same results with a simple source-level transformation.
Open Set Masked Face Identification system

From healthcare workers to working professionals, wearing a facial mask became a new normal owing to the COVID-19 pandemic, and hence, the need for reliable and efficient open set masked face identification systems has never been more critical. In this research, we successfully developed and implemented a robust model capable of identifying individuals and accurately detecting imposters even when facial coverings are present. To achieve this, we endeavored to create a custom dataset by combining two publicly available datasets and experimented with various state-of-the-art models through transfer learning to get the best solution. The results demonstrate the effectiveness of our approach, showcasing the potential of open set masked face identification systems in addressing security challenges in diverse domains, from healthcare facilities to corporate environments. We saw a 65% accuracy in closed set identification along with a False Accept Rate (FAR) of 0.096 and False Reject Rate (FRR) 0.102 of at a threshold of 0.94 for open set identification. Our findings aspire to contribute to a safer and more secure future as we navigate the new normal of mask-wearing in a post COVID-19 world.
Mixed Precision Quantization with Hardware-Friendly Activation Functions for Hybrid ViT Models

As hardware devices have advanced recently, various artificial intelligence tasks including convolutional neural networks (CNNs) have achieved high accuracy. Especially in computer vision tasks, vision transformer (ViT) based models have achieved unprecedented progress, and CNN + ViT hybrid models have also been proposed that take advantage of both CNNs and ViTs. However, the numerous parameters of hybrid ViTs are unsuitable for resource-constrained mobile/edge environments. In addition, the nonlinear activation functions in hybrid ViTs (e.g., GeLU and Swish) require more resources and computational cost compared to integer operation functions (e.g., ReLU) when using dedicated hardware accelerators. To address these issues, we propose a technique to efficiently compress the prominent hybrid ViT model, MobileViT, by applying the mixed precision quantization and the Shift-Swish activation function. Compressing the MobileViT-s, MobileViT-xs, and MobileViT-xxs models with the proposed method on the ImageNet dataset resulted in minimal accuracy drops of 0.41%, 0.18%, and 0.86%, respectively, while achieving effective quantization and activation function approximation at the average 7.9-bit level.
Absorption Properties of Polyimide Films with Various Macromolecular Rigidity

This work focuses on the effect of macromolecular rigidity on the absorption characteristics of polyimide (PI) films. The absorption currents were measured for 4 hours in a broad temperature range (from 25 to 175 °C). The temperature dependences and activation energies of conductivity for PI films with different macromolecular rigidity were achieved. The experimental data were analyzed to determine Voigt equivalent circuits’ parameters. Using these parameters, dielectric permittivity, dielectric loss factor and absorption coefficient were calculated and compared for PI films in a low frequency range.
Weekend Effect in Children With Stroke in the Nationwide Inpatient Sample

Background and Purpose— Studies have demonstrated differences in clinical outcomes in adult patients with stroke admitted on weekdays versus weekends. The study’s objective was to determine whether a weekend impacts clinical outcomes in children with ischemic stroke and hemorrhagic stroke. Methods— Children aged 1 to 18 years admitted to US hospitals from 2002 to 2011 with a primary discharge diagnosis of ischemic stroke or hemorrhagic stroke were identified by International Classification of Disease, 9th Revision, codes. Logistic regression estimated odds ratios and 95% confidence intervals for in-hospital mortality and discharge to a nursing facility among children admitted on weekends (Saturday and Sunday) versus weekdays (Monday to Friday), adjusting for potential confounders. Results— Of 8467 children with ischemic stroke, 28% were admitted on a weekend. Although children admitted on weekends did not have a higher in-hospital mortality rate than those admitted on weekdays (4.1% versus 3.3%; P=0.4), children admitted on weekends had a higher rate of discharge to a nursing facility (25.5% versus 18.6%; P=0.003). After adjusting for age, sex, and confounders, the odds of discharge to a nursing facility remained increased among children admitted on weekends (odds ratio, 1.5; 95% confidence interval, 1.1–1.9; P=0.006). Of 10 919 children with hemorrhagic stroke, 25.3% were admitted on a weekend. Children admitted on weekends had a higher rate of in-hospital mortality (12% versus 8%; P=0.006). After adjusting for age, sex, and confounders, the odds of in-hospital mortality remained higher among children admitted on weekends (odds ratio, 1.4; 95% confidence interval, 1.1–1.9; P=0.04). Conclusions— There seems to be a weekend effect for children with ischemic and hemorrhagic strokes. Quality improvement initiatives should examine this phenomenon prospectively.
Interpolated n-grams for model based testing

Models - in particular finite state machine models - provide an invaluable source of information for the derivation of effective test cases. However, models usually approximate part of the program semantics and capture only some of the relevant dependencies and constraints. As a consequence, some of the test cases that are derived from models are infeasible. In this paper, we propose a method, based on the computation of the N-gram statistics, to increase the likelihood of deriving feasible test cases from a model. Correspondingly, the level of model coverage is also expected to increase, because infeasible test cases do not contribute to coverage. While N-grams do improve existing test case derivation methods, they show limitations when the N-gram statistics is incomplete, which is expected to necessarily occur as N increases. Interpolated N-grams overcome such limitation and show the highest performance of all test case derivation methods compared in this work.
A Universal Software Package for Research and Development of Various Types of Natural Universal and Error-Correcting Codes

In modern communication systems and computer networks, using advanced methods of forming natural, error-correction, and effective codes, as well as combining these types of codes, is very important. The original software package, intended for forming the sequences of different types of codes and for their decoding, has been developed using the programming and graphic means of the MATLAB computer system for scientific and technical calculations. The distinguishing feature of elaborated software is the convenient graphical user interface and the possibility of forming and decoding all well-known advanced types of codes, as well as their combinations. An analysis of specters of digital signals for corresponded natural codes in the communication channel is also possible. Elaborated computer software is a complete software product that can be used both to study the theory of digital signal coding and to develop communication equipment for telecommunication systems and computer networks.
NoisyDECOLLE: Robust Local Learning for SNNs on Neuromorphic Hardware

Based on their biological archetype, spiking neural networks (SNNs) promise substantial energy savings at massively increased performance. However, best-performing SNNs in supervised learning scenarios often fall short of their potential efficiency gains as they rely on backpropagation, which entails issues like weight update locking until forward and backward passes are finished, and critical resource & computation requirements. These challenges can be tackled by drawing inspiration from biological synapses which rely largely on more local information to adapt. Local learning algorithms adopt this idea by employing local classifiers in each layer of an SNN that use only spatially and temporally local information to update synaptic weights. However, mapping these algorithms to neuromorphic systems to unleash their potential can be impaired by various kinds of noise. In this work, we review prior art to derive realistic noise scenarios on neuromorphic systems. Based on these results, we introduce NoisyDEColle, a framework for applying various noise models on locally learned SNNs using the DECOLLE network architecture. We show that both noise-aware training and additional regularization techniques allow NoisyDECOLLE to reach competitive performance, even under challenging conditions as for example posed by resistive devices. Using quantization-aware training, NoisyDECOLLE reaches 98.6% (94.1%) accuracy on N-MNIST (DVSGesture) with 3b (8b) weights ($> 4-10\mathrm{x}$ memory and energy savings compared to 32b). To analyze our results, we provide the first time-driven implementation of spike activation maps, aiding the explainability of neuromorphic computing.
Automation of the Experimental Setup for Studying the Field Electron Emission Properties of Materials

Field electron emission is a relevant problem in vacuum electronics. A complex of studies with large volume of measurements is required in order to obtain complete information about this phenomenon. Therefore, it is necessary to optimize the experimental work through appropriate equipment. But modern high-tech equipment is very expensive; hence, there is a demand for the development of simple research methods on cheap and easily accessible devices. Automation of experimental data acquisition from the installation for studying the field electron emission properties of materials was carried out. Field emission is initiated by a high voltage source, which is controlled by a potential of 0 - 5 V. Devices with a digital-to-analog converters can easily solve the issue of high voltage regulation. But this work shows a method for current-voltage characteristics recording and experimental data processing by means of registration systems consisting of a computer, programmable laboratory power supply and L-Card input module not equipped with the digital-to-analog converter. Such devices are available, widely used and cheap enough to allow experiments to be carried out in most scientific institutions. Processing of the data array and calculation of experimental dependence points are realized due to analyzing the dynamics of the control signal.