Miracle-dz/UniFAR-FTUs huggingface dataset:
A fast target depth perception method based on stereo structured light

Structured light stereo vision depth perception is a key method in the fields of 3D contour reconstruction and human-computer interaction. To address the problem that the array-encoded raw image cannot be accurately localized due to artifacts when the target under test is moving rapidly, we propose a linear sparse depth perception method based on artifact analysis. Also, in order to effectively perceive the artefact parameters in motion, we design a heterogeneous coding model with grid line mode and array coding mode. To obtain the artifact width parameters of fast-moving objects under binocular vision, the artifact parameters were obtained based on a gradient ridge extraction method. Finally, to obtain the artefact analysis function required for depth perception of fast-moving targets, we used discrete artefact parameters to obtain a global artefact analysis function. Linear sparse depth information is obtained from the artifact parameter information in the binocular images, thus improving the speed and robustness of depth perception. Keywords: structured light; stereo vision; image segmentation; artifact analysis.
Brief Multimodal Intervention to Address Bedtime Procrastination and Sleep through Self-Compassion and Sleep Hygiene during Stressful Times

Bedtime procrastination is increasingly recognized as a widespread impediment to health-promoting sleep. Based on its potential malleability, bedtime procrastination is starting to be targeted for intervention using traditional health behavior models, but other cognitive and emotional factors that potentially modulate bedtime procrastination warrant more targeted intervention. The present research recruited college students (n = 93) with self-reported tendencies toward bedtime procrastination and low self-compassion early in the COVID-19 pandemic, and it examined a hybrid intervention model involving a single group meeting and home practices that focused on comprehensive sleep hygiene or intentional self-compassion practices, simultaneously leveraging social motivation and commitment. It also examined bedtime procrastination, sleep, emotion regulation, and procrastinatory cognitions. The study showed evidence for feasibility, acceptability, reduced bedtime procrastination, improved sleep, and moderated mediation whereby the relationship between increased self-compassion and decreased bedtime procrastination was mediated by improved emotion regulation for those with elevated reductions in procrastinatory cognition. Predictors of bedtime procrastination reduction and other relevant sequelae differed between self-compassion and sleep hygiene virtual trainings. Thus, the present research expands and synthesizes a burgeoning literature, suggesting that integrating effective elements into acceptable interventions may help reverse a cycle of self-criticism, emotion dysregulation, bedtime procrastination, and sleep-related difficulties for many who might benefit.
Cardiac age prediction using graph neural networks

The function of the human heart is characterised by complex patterns of motion that change throughout our lifespan due to accumulated damage across biological scales. Understanding the drivers of cardiac ageing is key to developing strategies for attenuating age-related processes. The motion of the surface of the heart can be conceived as a graph of connected points in space moving through time. Here we develop a generalisable framework for modelling three-dimensional motion as a graph and apply it to a task of predicting biological age. Using sequences of segmented cardiac imaging from 5064 participants in UK Biobank we train a graph neural network (GNN) to learn motion traits that predict healthy ageing. The GNN outperformed (mean absolute error, MAE = 4.74 years) a comparator dense neural network and boosting methods (MAE = 4.90 years and 5.08 years, respectively). We produce human-intelligible explanations of the predictions and using the trained model we also assess the effect of hypertension on biological age. This work shows how graph representations of complex motion can efficiently predict biologically meaningful outcomes.
An Interview with Kalyanmoy Deb 2022 ACM Fellow

Prof. Kalyanmoy Deb has been named one of the 2022 ACM Fellows for "Outstanding Contributions That Propel Technology Today", in particular for his "technical contributions in evolutionary multi-objective optimization algorithms and multi-criterion decision support. " Kalyanmoy kindly agreed to answer all our questions, ranging from his seminal contributions to his views and perspectives on evolutionary computation and its role within computing science and artificial Intelligence.
A Reconfigurable Architecture for Real-time Event-based Multi-Object Tracking

Although advances in event-based machine vision algorithms have demonstrated unparalleled capabilities in performing some of the most demanding tasks, their implementations under stringent real-time and power constraints in edge systems remain a major challenge. In this work, a reconfigurable hardware-software architecture called REMOT, which performs real-time event-based multi-object tracking on FPGAs, is presented. REMOT performs vision tasks by defining a set of actions over attention units (AUs). These actions allow AUs to track an object candidate autonomously by adjusting its region of attention and allow information gathered by each AU to be used for making algorithmic-level decisions. Taking advantage of this modular structure, algorithm-architecture codesign can be performed by implementing different parts of the algorithm in either hardware or software for different tradeoffs. Results show that REMOT can process 0.43–2.91 million events per second at 1.75–5.45 W. Compared with the software baseline, our implementation achieves up to 44 times higher throughput and 35.4 times higher power efficiency. Migrating the Merge operation to hardware further reduces the worst-case latency to be 95 times shorter than the software baseline. By varying the AU configuration and operation, a reduction of 0.59–0.77 mW per AU on the programmable logic has also been demonstrated.
The Slow Path Needs an Accelerator Too!

Packet-processing data planes have been continuously enhanced in performance over the last few years to the point that, nowadays, they are increasingly implemented in hardware (i.e., in SmartNICs and programmable switches). However, little attention is given to the slow path residing between the data plane and the control plane, as it is not typically considered performance-critical. In this paper, we show that the slow path is set to become a new key bottleneck in Software-Defined Networks (SDNs). This is due to the growth in physical network bandwidth (200 Gbps is becoming common in data centers) and topological complexity (e.g., virtual switches now span hundreds of physical machines). We present our vision of a new Domain Specific Accelerator (DSA) for the slow path at the end host that sits between the hardware-offloaded data plane and the logically-centralized control plane. We discuss open problems in this domain and call on the networking community to creatively address this emerging issue.
An evaluation of classifiers for reading resistor colors

A lot of effort has been devoted to reading resistor colors using image processing and pattern recognition techniques. It is not so clear which classifier or machine learning is effective for classifying colors in reading a resistance of a resistor. This paper presents an evaluation of classifiers for reading resistor's colors on an RGB color space under various illumination situations. Eight classifiers to be examined are k-nearest neighbor (k-NN) (k=1, 3, and 5), decision tree (DT), support vector machine (SVM), Gaussian naive Bayes (NB), artificial neural network (ANN), and random forest (RF). The classification performance of 8 classifiers is evaluated by the average error rate, respectively. From the experimental results, depending on the training sample size and illumination situations, the classifier to be used for reading resistor colors should be considered. Considering practical color pattern recognition problems with poor illumination conditions, the 1-NN classifier should be the more practical and usable classifier. This study will provide one of the ways for AI and robotics applications to accurately classify colors.
Real Time Fiducial Marker Localisation System with Full 6 DOF Pose Estimation

The ability to reliably determine its own position, as well as the position of surrounding objects, is crucial for any autonomous robot. While this can be achieved with a certain degree of reliability, augmenting the environment with artificial markers that make these tasks easier is often practical. This applies especially to the evaluation of robotic experiments, which often require exact ground truth data containing the positions of the robots. This paper proposes a new method for estimating the position and orientation of circular fiducial markers in 3D space. Simulated and real experiments show that our method achieved three times lower localisation error than the method it derived from. The experiments also indicate that our method outperforms state-of-the-art systems in terms of orientation estimation precision while maintaining similar or better accuracy in position estimation. Moreover, our method is computationally efficient, allowing it to detect and localise several markers in a fraction of the time required by the state-of-the-art fiducial markers. Furthermore, the presented method requires only an off-the-shelf camera and printed tags, can be quickly set up and works in natural light conditions outdoors. These properties make it a viable alternative to expensive high-end localisation systems.
The connection between cross-validation and Akaike information criterion in a semiparametric family

Both Akaike information criterion and cross-validation are important tools in model selection. Stone [(1977), ‘An Asymptotic Equivalence of Choice of Model by Cross-Validation and Akaikes Criterion’, Journal of the Royal Statistical Society, Series B, 39, 44–47] established the equivalence of these two criteria for parametric models. In this paper, we build a similar equivalence for a large semiparametric family.
Visual Analytics for Innovation and R&D Intelligence

Abstract Overview: Innovation is critical to the growth and survival of companies across industries and geographies. Over time, however, sources of innovation have become much more diverse, and a systematic understanding of the complex and dynamic innovation landscape is challenging. This paper describes the value and impact of using a data-driven, visual analytic approach for innovation and R&D intelligence. I outline a methodology with which to approach visual analytic innovation and R&D intelligence, present illustrative mini-case studies, and frame the findings into key considerations and elements of the intelligence decision space. The paper contributes to practical and theoretical understanding of how emerging computational and analytical approaches can support innovation and R&D activities. It concludes with practical implications and future research directions.
TOPOLOGIES DEFINED IN TERMS OF PRE-HAAR SYSTEMS

We start with a locally diagonally compact groupoid (G,G) in the sense of (4), a pre- Haar system  on G and a family A of left and right uniformly continuous on fibres functions on G. The purpose of this short note is to introduce a new locally diagonally compact topology (G,A,) on G such that G and (G,A,) induce the same subspace topology on the groupoid fibres and the pre-Haar system  becomes continuous for the functions in A.
Fortuitous events in the evolution of Light-dependent Protochlorophyllide Oxidoreductase

Light-dependent protochlorophyllide oxidoreductase (LPOR) is a nuclear-encoded photoenzyme in many photosynthetic organisms. LPOR originated in primitive cyanobacterial ancestors during the great oxygenation event that was detrimental to the existence of the oxygen-sensitive LIPOR that prevailed in anoxygenic Earth. Both LIPOR and LPOR catalyse reduction of protochlorophyllide to chlorophyllide in the penultimate step of chlorophyll biosynthesis. Except for angiosperms and gnetophytes several oxygenic phototrophs harbour both LIPOR and LPOR. The coexistence of LIPOR and LPOR in certain phototrophs provides niche spaces for organisms in unconducive environment. The selection pressure of increased O2 concentration, changing light quality and quantity at different depths of the ocean, nutrient status of water, gene reorganization during several endosymbiotic events, horizontal gene transfer, LIPOR gene loss and multiple duplication events played a major role in the evolution and diversification of LPOR and its isoforms in photosynthetic and non-photosynthetic organisms. In the absence of LIPOR angiosperms become vulnerable to protochlorophyllide-sensitized and light-induced oxidative stress mediated by singlet oxygen. To overcome the photo-damage PORA was expressed abundantly in the plastids of etiolated plants. PORB evolved to take over the function of vanishing PORA isoform in light. Brassicales evolved PORC to protect plants from high light and other environmental stresses. Highlights Protochlorophyllide oxidoreductase is an important photo-enzyme in angiosperms that needs light as a substrate for the synthesis of chlorophylls. Therefore, angiosperms cannot green in dark although several algae and lower green plants can synthesize chlorophyll in dark due to the presence of light-independent protochlorophyllide oxidoreductase (LIPOR). In response to climate change, during the great oxygenation event light-dependent protochlorophyllide oxidoreductase (LPOR) evolved due to the O2-induced selection pressure that inactivated the oxygen-sensitive LIPOR. Increased O2 concentration, changing light quality and quantity at different depths of ocean, gene reorganization during several endosymbiotic events, selective LIPOR gene loss and multiple duplication events played a major role in the evolution and diversification of LPOR and its isoforms in phototrophs. Phylogenetic studies indicate that LPOR genes have been overwhelmingly horizontally transferred between phototrophs and also non phototrophic organisms. Presence of LPOR in non-photosynthetic organisms, Mycobacterium and certain fungi suggests that LPOR may have some other reductive functions in these organisms.
A critical role for CaMKII in behavioral timescale synaptic plasticity in hippocampal CA1 pyramidal neurons

Behavioral timescale synaptic plasticity (BTSP) is a type of non-Hebbian synaptic plasticity reported to underlie place field formation in the hippocampal CA1 neurons. Despite this important function, the molecular mechanisms underlying BTSP are poorly understood. The α-Calcium-calmodulin-dependent protein kinase II (αCaMKII) is activated by synaptic transmission-mediated calcium influx and its subsequent phosphorylation is central to synaptic plasticity. Because the activity of αCaMKII is known to outlast the event triggering phosphorylation, we hypothesized it could be involved in the extended timescale of the BTSP process. To examine the role of αCaMKII in BTSP, we performed whole-cell in-vivo and in-vitro recordings in CA1 pyramidal neurons from mice engineered to have a point mutation at the autophosphorylation site (T286A) causing accelerated signaling kinetics. Here we demonstrate a profound deficit in synaptic plasticity, strongly suggesting that αCaMKII signaling is required for BTSP. This study elucidates part of the molecular mechanism of BTSP and provides insight into the function of αCaMKII in place cell formation and ultimately learning and memory. Teaser The molecular mechanisms of BTSP have been revealed to require the autophosphorylation of CaMKII.
Modeling DBD Plasma Actuators in Integral Boundary Layer Formulation for Application in Panel Methods

A methodology is presented to include the influence of DBD plasma actuators in panel methods used for airfoil design. The influence of the plasma body-force is modelled by performing an asymptotic expansion to the Navier-Stokes equations as to obtain a generalized form of the von Karman integral equations. New closure relations were thus derived, which account for boundary layer development in the presence of DBD actuators. To validate the modelling approach, an experimental study was carried out in which PIV was performed on an airfoil equipped with DBD plasma actuators. The airfoil section was tested at different operational Reynolds number and angles of attack, while balance measurements were also performed to evaluate the lift and drag coefficients. Results show the proposed model captures the magnitude of the variation in IBL parameters brought upon by the DBD actuator. This is verified for different operating conditions, while the model captures the magnitude of the lift coefficient variation (∆Cl). Ultimately this approach may enable the design of airfoils specifically tailored for flow control through DBD employment, potentially decreasing the power required for active flow control.
Asymmetric patterns of nucleosome positioning sequences in protein-coding regions

Although nucleosome positioning is key to epigenetic regulation, how the DNA sequence contributes to positioning remains elusive, especially in the context of transcription direction. Analysis of nucleotide bases with respect to the nucleosomal DNA coordinates requires precise nucleosomal mapping information on the genome. However, currently available base-pair-resolution nucleosome maps based on cysteine-mediated chemical cleavage do not fully satisfy the requirement due to method-specific cleavage biases. Here, we generated a chimeric nucleosomal DNA model to achieve less-biased prediction. The model revealed that yeast protein-coding sequences have higher affinity for the promoter-proximal half of nucleosomes than for the distal half. Strikingly, peaks of calculated affinity scores for the promoter-proximal half periodically matched the first few nucleosome positions. Detailed analysis of nucleotide bases revealed that the AA dinucleotide in the left side of the top strand contributes to nucleosome detection frequency in intergenic regions, while the complementary dinucleotide TT is preferred in the other side. In contrast, the sense strand is AA-rich throughout the nucleosome coordinate in protein-coding regions, which is consistent with asymmetric affinity. These data suggest that eukaryotes have evolved DNA sequences with asymmetric affinity for nucleosome formation to maintain epigenetic integrity of protein-coding regions.
Mining for a New Class of Fungal Natural Products: The Evolution, Diversity, and Distribution of Isocyanide Synthase Biosynthetic Gene Clusters

The products of non-canonical isocyanide synthase (ICS) biosynthetic gene clusters (BGCs) have notable bioactivities that mediate pathogenesis, microbial competition, and metal-homeostasis through metal-associated chemistry. We sought to enable research into this class of compounds by characterizing the biosynthetic potential and evolutionary history of these BGCs across the Fungal Kingdom. We developed the first genome-mining pipeline to identify ICS BGCs, locating 3,800 ICS BGCs in 3,300 genomes. Genes in these clusters share promoter motifs and are maintained in contiguous groupings by natural selection. ICS BGCs are not evenly distributed across fungi, with evidence of gene-family expansions in several Ascomycete families. We show that the ICS dit1/2 gene cluster family (GCF), which was thought to only exist in yeast, is present in ∼30% of all Ascomycetes, including many filamentous fungi. The evolutionary history of the dit GCF is marked by deep divergences and phylogenetic incompatibilities that raise questions about convergent evolution and suggest selection or horizontal gene transfers have shaped the evolution of this cluster in some yeast and dimorphic fungi. Our results create a roadmap for future research into ICS BGCs. We developed a website (www.isocyanides.fungi.wisc.edu) that facilitates the exploration, filtering, and downloading of all identified fungal ICS BGCs and GCFs.
Folding kinetics of an entangled protein

The possibility of the protein backbone adopting lasso-like entangled motifs has attracted increasing attention. After discovering the surprising abundance of natively entangled single-domain proteins, it was shown that misfolded entangled subpopulations might become thermosensitive or escape the homeostasis network just after translation. To investigate the role of entanglement in shaping folding kinetics, we introduce a novel indicator and analyze simulations of a coarse-grained, structure-based model for two small single-domain proteins. The model recapitulates the well-known two-state folding mechanism of a non-entangled SH3 domain. However, despite its small size, a natively entangled antifreeze RD1 protein displays a rich refolding behavior, populating two distinct kinetic intermediates: a short-lived, entangled, near-unfolded state and a long-lived, non-entangled, near-native state. The former directs refolding along a fast pathway, whereas the latter is a kinetic trap, consistently with known experimental evidence of two different characteristic times. Upon trapping, the natively entangled loop forms without being threaded by the N-terminal residues. After trapping, the native entangled structure emerges by either backtracking to the unfolded state or threading through the already formed but not yet entangled loop. Along the fast pathway, the earlier the native contacts form, the more their formation time may fluctuate. Trapping does not occur because the native contacts at the closure of the lasso-like loop form after those involved in the N-terminal thread, confirming previous predictions. Despite this, entanglement may appear already in unfolded configurations. Remarkably, a long-lived, near-native intermediate, with non-native entanglement properties, recalls what was observed in cotranslational folding. Author summary Recently, a surprisingly large fraction of protein structures was shown to host topologically entangled motifs, whereby one protein chain portion is lassoed by a second portion, that loops between two residues in non-covalent contact with each other. Moreover, there is growing evidence that failure in adopting the correct entangled motifs may produce misfolded structures with impaired biological functions. Such structures are otherwise similar to the correct ones and can escape the cell quality control system for protein expression, leading to soluble and less functional protein species. Here, we study in detail the folding kinetics of an entangled small anti-freeze protein, using a simplified representation of the protein chain. We find a very rich folding behavior, unusual for small proteins, with different folding pathways. A fast pathway is followed if a crucial set of contacts is formed before lassoing takes place. If not, a misfolded structure which acts as a kinetic trap is formed, slowing down folding; in such structure, most of the contacts are correctly in place yet the lasso is not formed. The detailed understanding that we provide for a small protein may pave the way for similar studies for larger entangled proteins.