Miracle-dz/UniFAR-FTUs huggingface dataset:
Dynamical Wasserstein Barycenters for Time-series Modeling

Many time series can be modeled as a sequence of segments representing high-level discrete states, such as running and walking in a human activity application. Flexible models should describe the system state and observations in stationary “pure-state” periods as well as transition periods between adjacent segments, such as a gradual slowdown between running and walking. However, most prior work assumes instantaneous transitions between pure discrete states. We propose a dynamical Wasserstein barycentric (DWB) model that estimates the system state over time as well as the data-generating distributions of pure states in an unsupervised manner. Our model assumes each pure state generates data from a multivariate normal distribution, and characterizes transitions between states via displacement-interpolation speciﬁed by the Wasserstein barycenter. The system state is represented by a barycentric weight vector which evolves over time via a random walk on the simplex. Parameter learning leverages the natural Riemannian geometry of Gaussian distributions under the Wasserstein distance, which leads to improved convergence speeds. Experiments on several human activity datasets show that our proposed DWB model accurately learns the generating distribution of pure states while improving state estimation for transition periods compared to the commonly used linear interpolation mixture models.
Hartle-Hawking's vacuum is full of Vilenkin's universe-antiuniverse pairs

Within the third quantisation formalism, we find solutions of the Wheeler-DeWitt in terms of two sets of modes that can be identified with the Hartle-Hawking’s no boundary condition and with the Vilenkin’s tunneling boundary condition, respectively. The two sets of modes are related by a Bogolyubov transformation so the no boundary vacuum state turns out to be equivalent to a thermal distribution of tunnelling positive and negative modes representing, in a relative sense, universes and antiuniverses.
On Some Modal Implications of the Dynamic Mode Decomposition Through the Lens of a Subcritical Prism Wake

The Dynamic Mode Decomposition (DMD) is a Koopman-based algorithm that straightforwardly isolates individual mechanisms from the compound morphology of direct measurement. However, many may be perplexed by the messages the DMD structures carry. This work investigates the modal implications of the DMD/Koopman modes through the prototypical subcritical free-shear flow over a square prism. It selected and analysed the fluid mechanics and phenomenology of the ten most dominant modes. The results showed that the reduced-order description is morphologically accurate and physically insightful. Mode 1 renders the mean-field. Modes 2 depicts the roll-up of the Strouhal vortex. Mode 3 delineates the Bloor-Gerrard vortex resulting from the Kelvin-Helmholtz instability inside shear layers, its superposition onto the Strouhal vortex, and the concurrent flow entrainment. Modes 4, 5, 7, 8, and 9 portray the harmonic excitation. Modes 6 and 10 describe the low-frequency shedding of turbulent separation bubbles (TSBs) and turbulence production, respectively, which contribute to the beating phenomenon in the lift time history and the flapping motion of shear layers. Finally, this work demonstrates the capability of the DMD in providing insights into similar fluid problems. It also serves as an excellent reference for an array of other nonlinear systems.
Signatures of electronic correlations and spin-susceptibility anisotropy in nuclear magnetic resonance

We present a methodology for probing the details of electronic susceptibility through minimally-invasive nuclear magnetic resonance techniques. Specifically, we classify electron-mediated long-range interactions in an ensemble of nuclear spins by revealing their effect on simple spin echo experiments. We find that pulse strength and applied field orientation dependence of these spin echo measurements resolves the spatial extent and anisotropy of electronic spin susceptibility. This work provides an alternate explanation to NMR results in superconducting and magnetically-ordered systems. The methodology has direct applications for sensing and characterizing emergent electronic phases.
Winning the ICCV'2021 VALUE Challenge: Task-aware Ensemble and Transfer Learning with Visual Concepts

The VALUE (Video-And-Language Understanding Evaluation) benchmark is newly introduced to evaluate and analyze multi-modal representation learning algorithms on three video-and-language tasks: Retrieval, QA, and Captioning. The main objective of the VALUE challenge is to train a task-agnostic model that is simultaneously applicable for various tasks with different characteristics. This technical report describes our winning strategies for the VALUE challenge: 1) single model optimization, 2) transfer learning with visual concepts, and 3) task-aware ensemble. The first and third strategies are designed to address heterogeneous characteristics of each task, and the second one is to leverage rich and fine-grained visual information. We provide a detailed and comprehensive analysis with extensive experimental results. Based on our approach, we ranked first place on the VALUE and QA phases for the competition.
The VLSAT-2 Benchmark Suite

This report presents VLSAT-2 (an acronym for"Very Large Boolean SATisfiability problems),the second part of a benchmark suite to be used in scientific experiments and softwarecompetitions addressing SAT-solving issues.VLSAT-2 contains 100 benchmarks (50 satisfiable and 50 unsatisfiable formulas)of increasing complexity, proposed in DIMACS CNF format undera permissive Creative Commons license.25% of these benchmarks have been used during the 2020 and 2021 editionsof the International SAT Competition.
Quantum Kolmogorov complexity and duality of unitary transformations and quantum states

The Kolmogorov complexity of a quantum state is known as quantum Kolmogorov complexity. For every unitary transformation, we construct a corresponding quantum state. Then, we define the Kolmogorov complexity of the unitary transformation via the Kolmogorov complexity of the constructed quantum state and show the consistency of such an approach. Thus, we establish the duality of unitary evolutions and quantum states in quantum computing and quantum mechanics.
A Statistical Relational Approach to Learning Distance-based GCNs

We consider the problem of learning distance-based Graph Convolutional Networks (GCNs) for relational data. Specifically, we first embed the original graph into the Euclidean space $\mathbb{R}^m$ using a relational density estimation technique thereby constructing a secondary Euclidean graph. The graph vertices correspond to the target triples and edges denote the Euclidean distances between the target triples. We emphasize the importance of learning the secondary Euclidean graph and the advantages of employing a distance matrix over the typically used adjacency matrix. Our comprehensive empirical evaluation demonstrates the superiority of our approach over $12$ different GCN models, relational embedding techniques and rule learning techniques.
Improving classification of low-resource COVID-19 literature by using Named Entity Recognition

Automatic document classification for highly interrelated classes is a demanding task that becomes more challenging when there is little labeled data for training. Such is the case of the coronavirus disease 2019 (COVID-19) clinical repository—a repository of classified and translated academic articles related to COVID-19 and relevant to the clinical practice—where a 3-way classification scheme is being applied to COVID-19 literature. During the 7th Biomedical Linked Annotation Hackathon (BLAH7) hackathon, we performed experiments to explore the use of named-entity-recognition (NER) to improve the classification. We processed the literature with OntoGene’s Biomedical Entity Recogniser (OGER) and used the resulting identified Named Entities (NE) and their links to major biological databases as extra input features for the classifier. We compared the results with a baseline model without the OGER extracted features. In these proof-of-concept experiments, we observed a clear gain on COVID-19 literature classification. In particular, NE’s origin was useful to classify document types and NE’s type for clinical specialties. Due to the limitations of the small dataset, we can only conclude that our results suggests that NER would benefit this classification task. In order to accurately estimate this benefit, further experiments with a larger dataset would be needed.
A Ti3C2Tx MXene-Based Energy-Harvesting Soft Actuator with Self-Powered Humidity Sensing and Real-Time Motion Tracking Capability.

A smart soft actuator with multiple capabilities of humidity-driven actuating, humidity energy harvesting, self-powered humidity sensing, and real-time motion tracking is reported. It is designed on the basis of an MXene/cellulose/polystyrene sulfonic acid (PSSA) composite membrane. This actuator is driven by asymmetric expansion under a moisture gradient during capture of the chemical potential of humidity to mechanical power. Meanwhile, the gradient moisture chemistry also induces directional proton diffusion to generate electricity with high power density and open-circuit voltage. A good linear correlation between the humidity sensitivity, electrical signal, and bending state of this actuator allows real-time tracking of motion modes with humidity change without an external power supply. This multifunctional soft actuator can be used for engineering smart switches, artificial fingers, and soft robots with trackable and distinguishable motion patterns, as well as sensitive noncontacting humidity sensor and breathing monitors.
Photocatalytic Degradation of Methylene Blue Using Polymeric Membranes Based on Cellulose Acetate Impregnated with ZnO Nanostructures

This paper studied the photocatalytic degradation of methylene blue (MB) using polymeric membrane impregnated with ZnO nanostructures under UV-light and sunlight irradiation. ZnO nanoparticles and ZnO nanowires were prepared using the hydrothermal technique. Cellulose acetate polymeric membranes were fabricated by the phase inversion method using dimethylformamide (DMF) as a solvent and ZnO nanostructures. The structural properties of the nanostructures and the membranes were investigated using XRD, SEM, FTIR, and TGA measurements. The membranes were tested for photocatalytic degradation of MB using a UV lamp and a sunlight simulator. The photocatalytic results under sunlight irradiation in the presence of cellulose acetate impregnated with ZnO nanoparticles (CA-ZnO-NP) showed a more rapid degradation of MB (about 75%) compared to the results obtained under UV-light irradiation degradation (about 30%). The results show that CA-ZnO-NP possesses the photocatalytic ability to degrade MB efficiently at different levels under UV-light and sunlight irradiation. Modified membranes with ZnO nanoparticles and ZnO nanowires were found to be chemically stable, recyclable, and reproducible. The addition of ZnO nanostructure to the cellulose membranes generally enhanced their photocatalytic activity toward MB, making these potential membranes candidates for removing organic pollutants from aqueous solutions.
Altered metabolic state impedes limb regeneration in salamanders

Salamanders are unique among tetrapods in their ability to regenerate the limbs throughout life. Like other poikilothermic amphibians, salamanders also show a remarkable capacity to survive long periods of starvation. Whether the physiological reserves necessary for tissue regeneration are preserved or sacrificed in starved salamanders is unknown. In the current study, we maintained Iberian ribbed newts (Pleurodeles waltl) under extreme physiological stress to assess the extent of regeneration and identify the molecular and cellular changes that may occur under such conditions. After 19 months of complete food deprivation, the animals exhibited extensive morphological and physiological adaptations but remained behaviorally active and vigilant. Autophagy was elevated in different tissues and the transformed gut microbiota indicated remodeling of the intestinal tract related to autophagy. Upon limb amputation in animals starved for 21 months, regeneration proceeded with progenitor cell proliferation and migration, leading to limb blastema formation. However, limb outgrowth and patterning were substantially attenuated. Blockage of autophagy inhibited cell proliferation and blastema formation in starved animals, but not in fed animals. Hence, tissue autophagy and the regenerative response were tightly coupled only when animals were under stress. Our results demonstrate that under adverse conditions, salamanders can exploit alternative strategies to secure blastema formation for limb regeneration.
NEP1-40 promotes myelin regeneration via upregulation of GAP-43 and MAP-2 expression after focal cerebral ischemia in rats

Axon regeneration after lesions to the central nervous system (CNS) is largely limited by the presence of growth inhibitory molecules expressed in myelin. Nogo-A is a principal inhibitor of neurite outgrowth, and blocking the activity of Nogo-A can induce axonal sprouting and functional recovery. However, there are limited data on the expression of Nogo-A after CNS lesions, and the mechanism underlying its influences on myelin growth remains unknown. The aim of the present study was to observe the time course of Nogo-A after cerebral ischemia/reperfusion in rats using immunohistochemistry and western blot techniques, and to test the effect of its inhibitor Nogo extracellular peptide 1–40 (NEP1-40) on neural plasticity proteins, growth-associated binding protein 43 (GAP-43) and microtubule associated protein 2 (MAP-2), as a possible mechanism underlying myelin suppression. A classic model of middle cerebral artery occlusion (MCAO) was established in Sprague-Dawley rats, which were divided into three groups: i) MCAO model group; ii) MCAO + saline group; and iii) MCAO + NEP1-40 group. Rats of each group were divided into five subgroups by time points as follows: days 1, 3, 7, 14 and 28. Animals that only received sham operation were used as controls. The Nogo-A immunoreactivity was located primarily in the cytoplasm of oligodendrocytes. The number of Nogo-A immunoreactive cells significantly increased from day 1 to day 3 after MCAO, nearly returning to the control level at day 7, increased again at day 14 and decreased at day 28. Myelin basic protein (MBP) immunoreactivity in the ipsilateral striatum gradually decreased from day 1 to day 28 after ischemia, indicating myelin loss appeared at early time points and continuously advanced during ischemia. Then, intracerebroventricular infusion of NEP1-40, which is a Nogo-66 receptor antagonist peptide, was administered at days 1, 3 and 14 after MCAO. It was observed that GAP-43 considerably increased from day 1 to day 7 and then decreased to a baseline level at day 28 compared with the control. MAP-2 expression across days 1–28 significantly decreased after MCAO. Administration of NEP1-40 attenuated the reduction of MBP, and upregulated GAP-43 and MAP-2 expression at the corresponding time points after MCAO compared with the MCAO + saline group. The present results indicated that NEP1-40 ameliorated myelin damage and promoted regeneration by upregulating the expression of GAP-43 and MAP-2 related to neuronal and axonal plasticity, which may aid with the identification of a novel molecular mechanism of restriction in CNS regeneration mediated by Nogo-A after ischemia in rats.
CultReal—A Rapid Development Platform for AR Cultural Spaces, with Fused Localization

Virtual and augmented reality technologies have known an impressive market evolution due to their potential to provide immersive experiences. However, they still have significant difficulties to enable fully fledged, consumer-ready applications that can handle complex tasks such as multi-user collaboration or time-persistent experiences. In this context, CultReal is a rapid creation and deployment platform for augmented reality (AR), aiming to revitalize cultural spaces. The platform’s content management system stores a representation of the environment, together with a database of multimedia objects that can be associated with a location. The localization component fuses data from beacons and from video cameras, providing an accurate estimation of the position and orientation of the visitor’s smartphone. A mobile application running the localization component displays the augmented content, which is seamlessly integrated with the real world. The paper focuses on the series of steps required to compute the position and orientation of the user’s mobile device, providing a comprehensive evaluation with both virtual and real data. Pilot implementations of the system are also described in the paper, revealing the potential of the platform to enable rapid deployment in new cultural spaces. Offering these functionalities, CultReal will allow for the fast development of AR solutions in any location.
A 0.3 V PNN Based 10T SRAM with Pulse Control Based Read-Assist and Write Data-Aware Schemes for Low Power Applications

An innovative and stable PNN based 10-transistor (10T) static random-access memory (SRAM) architecture has been designed for low-power bit-cell operation and sub-threshold voltage applications. The proposed design belongs to the following features: (a) pulse control based read-assist circuit offers a dynamic read decoupling approach for eliminating the read interference; (b) we have utilized the write data-aware techniques to cut off the pull-down path; and (c) additional write current has enhanced the write capability during the operation. The proposed design not only solves the half-selected problems and increases the read static noise margin (RSNM) but also provides low leakage power performance. The designed architecture of 1-Kb SRAM macros (32 rows × 32 columns) has been implemented based on the TSMC-40 nm GP CMOS process technology. At 300 mV supply voltage and 10 MHz operating frequency, the read and write power consumption is 4.15 μW and 3.82 μW, while the average energy consumption is only 0.39 pJ.
How to build single‐celled cnidarians with worm‐like motility: Lessons from Myxozoa

Metazoans with worm‐like morphologies across diverse and disparate groups typically demonstrate motility generated by hydrostatic skeletons involving tissue layers (muscles and epithelia). Here we present representative morphological, behavioural and molecular data for parasitic cnidarians (myxozoans) that demonstrate unprecedented variation in form and function, developing as cellular hydrostats. Motile elongate plasmodia characterise a remarkable radiation of species in the genus Ceratomyxa. The vermiform plasmodia inhabit gall bladders of a range of South American freshwater fish and exhibit undulatory motility reminiscent of nematodes but achieved at the cellular level. Collective insights from ultrastructure, confocal and light microscopy along with videos depicting movements highlight key features that we propose explain the unique motility of the plasmodia. These features include cytoskeletal elements (net forming microfilaments and microtubules), a large internal vacuole, a relatively rigid outer glycocalyx and peripherally arranged mitochondria. These constituents provide collective evidence for repurposing of the cnidarian epitheliomuscular cell to support worm‐like motility at the cellular level. The apparent restriction of vermiform ceratomyxids to South American freshwaters suggests an origination via Cretaceous or Miocene marine transgressions and subsequent radiation.
Detection of Circulating Serum microRNA/Protein Complexes in ASD Using Functionalized Chips for an Atomic Force Microscope

MicroRNAs, which circulate in blood, are characterized by high diagnostic value; in biomedical research, they can be considered as candidate markers of various diseases. Mature microRNAs of glial cells and neurons can cross the blood–brain barrier and can be detected in the serum of patients with autism spectrum disorders (ASD) as components of macrovesicles, macromolecular protein and low-density lipoprotein particles. In our present study, we have proposed an approach, in which microRNAs in protein complexes can be concentrated on the surface of AFM chips with oligonucleotide molecular probes, specific against the target microRNAs. MicroRNAs, associated with the development of ASD in children, were selected as targets. The chips with immobilized molecular probes were incubated in serum samples of ASD patients and healthy volunteers. By atomic force microscopy (AFM), objects on the AFM chip surface have been revealed after incubation in the serum samples. The height of these objects amounted to 10 nm and 6 nm in the case of samples of ASD patients and healthy volunteers, respectively. MALDI-TOF-MS analysis of protein components on the chip surface allowed us to identify several cell proteins. These proteins are involved in the binding of nucleic acids (GBG10, RT24, RALYL), in the organization of proteasomes and nucleosomes (PSA4, NP1L4), and participate in the functioning of the channel of active potassium transport (KCNE5, KCNV2).
Use of Industrial Wastes as Sustainable Nutrient Sources for Bacterial Cellulose (BC) Production: Mechanism, Advances, and Future Perspectives

A novel nanomaterial, bacterial cellulose (BC), has become noteworthy recently due to its better physicochemical properties and biodegradability, which are desirable for various applications. Since cost is a significant limitation in the production of cellulose, current efforts are focused on the use of industrial waste as a cost-effective substrate for the synthesis of BC or microbial cellulose. The utilization of industrial wastes and byproduct streams as fermentation media could improve the cost-competitiveness of BC production. This paper examines the feasibility of using typical wastes generated by industry sectors as sources of nutrients (carbon and nitrogen) for the commercial-scale production of BC. Numerous preliminary findings in the literature data have revealed the potential to yield a high concentration of BC from various industrial wastes. These findings indicated the need to optimize culture conditions, aiming for improved large-scale production of BC from waste streams.