Canonical System Research Articles

Influence of In-induced resonant level on the normal-state and superconducting properties of Sn1.03Te

Normal-state transport properties (2--300 K) of the polycrystalline series ${\mathrm{Sn}}_{1.03\ensuremath{-}\ensuremath{\delta}\ensuremath{-}x}{\mathrm{In}}_{x}\mathrm{Te} (0\ensuremath{\le}x\ensuremath{\le}0.07$; $\ensuremath{\delta}\ensuremath{\le}0.0025$) were investigated by means of electrical resistivity, thermopower, Hall effect, and thermal conductivity measurements. The distortion of the valence-band structure by the In-induced resonant level (RL) has a profound influence on the evolution of the normal-state properties with $x$ and on the emergence of superconductivity evidenced by specific-heat measurements down to 0.35 K. In addition to a nearly 40-fold increase in the residual electrical resistivity ${\ensuremath{\rho}}_{0}$ on going from $x=0.0$ to 0.05, the thermopower $\ensuremath{\alpha}$ shows a nonlinear, complex behavior as a function of both temperature and $x$. While Hall measurements indicate a dominant holelike response across the entire composition and temperature ranges, $\ensuremath{\alpha}$ changes sign below about 100 K and remains negative down to 5 K for $0.0015\ensuremath{\le}x\ensuremath{\le}0.0045$. Additional measurements under magnetic fields ${\ensuremath{\mu}}_{0}H$ of up to 14 T further shows that $\ensuremath{\alpha}({\ensuremath{\mu}}_{0}H)$ gradually shifts towards positive values, suggestive of a dominant holelike contribution to $\ensuremath{\alpha}$. Superconductivity emerges for $x=0.02$ at a critical temperature ${T}_{\mathrm{c}}=0.67$ K, with ${T}_{\mathrm{c}}$ increasing with $x$ to reach 1.73 K for $x=0.07$. The variations in the superconducting parameters with $x$, notably the specific-heat jump at ${T}_{\mathrm{c}}$, confirm the results reported in prior studies and suggests a nontrivial role of the RL on the electron-phonon coupling strength. The striking similarities between this series and the canonical resonant system ${\mathrm{Pb}}_{1\ensuremath{-}x}{\mathrm{Tl}}_{x}\mathrm{Te}$ provide an excellent experimental opportunity to gain a deeper understanding of the close interplay between resonant level, anomalous transport properties, and superconductivity.

Asymptotic approximations for the phase space Schrödinger equation

We consider semi-classical time evolution for the phase space Schrödinger equation and present two methods of constructing short time asymptotic solutions. The first method consists of constructing a semi-classical phase space propagator in terms of semi-classical Gaussian wave packets on the basis of the anisotropic Gaussian approximation, related to the nearby orbit approximation, which is identified with the phase space representation of the Littlejohn semi-classical propagator. By means of the semi-classical propagator, we derive an asymptotic solution for configuration space WKB initial data. The second method consists of constructing a phase space narrow beam asymptotic solution, following the complex WKB theory developed by Maslov, on the basis of a canonical system in double phase space, analogous to the Berezin–Shubin–Marinov Hamilton–Jacobi and transport equations. We illustrate the methods for sub-quadratic potentials in .

Pulsar PSR B0943$$+$$10 as an isotropic Vaidya–Tikekar-type compact star

In this paper, we have constructed a model for well behaved isotropic compact star in the presence of charged perfect fluid, by considering a static and spherically symmetric metric in Schwarzschild's canonical coordinate system. To put the resulting differential equations into a closed system, we have employed the Vaidya & Tikekar (J. Astrophys. Astron. 3:325, 1982) form of the metric potential grr. The resulting energy-momentum components, i.e., energy density and pressure contain six constants; two of these are determined through the junction condition (matching the interior with the exterior Schwarzschild solution) and by the property of vanishing pressure on the boundary. The remaining constants are constrained by requirements of a real compact star. The physical acceptability of our model is tested using the data of the pulsar PSR B0943+10. Using graphical analysis and tabular information we have shown that our model obeys all the physical requirements. The stability of this model is evaluated using the Tolman-Oppenheimer-Volkoff equation, the adiabatic index and the Harrison-Zeldovich-Novikov Criterion and it has passed the evaluation.

The impact of caloric availability on eating behavior and ultra-processed food reward

The food environment has changed rapidly and dramatically in the last 50 years. While industrial food processing has increased the safety and stability of the food supply, a rapid expansion in the scope and scale of food processing in the 1980's has resulted in a market dominated by ultra-processed foods. Here, we use the NOVA definition of category 4 ultra-processed foods (UPFs) as they make up around 58% of total calories consumed in the US and 66% of calories in US children. UPFs are formulated from ingredients with no or infrequent culinary use, contain additives, and have a long shelf-life, spending long periods in contact with packaging materials, allowing for the absorption of compounds from those materials. The full implications of this dietary shift to UPFs on human health and disease outcomes are difficult, if not impossible, to quantify. However, UPF consumption is linked with various forms of cancer, increased cardiovascular disease, and increased all-cause mortality. Understanding food choice is, therefore, a critical problem in health research. Although many factors influence food choice, here we focus on the properties of the foods themselves. UPFs are generally treated as food, not as the highly refined, industrialized substances that they are, whose properties and components must be studied. Here, we examine one property of UPFs, that they deliver useable calories rapidly as a potential factor driving UPF overconsumption. First, we explore evidence that UPFs deliver calories more rapidly. Next, we examine the role of the gut-brain axis and its interplay with canonical reward systems, and last, we describe how speed affects both basic learning processes and drugs of abuse.

A new dawn beyond lysine ubiquitination.

The ubiquitin system has become synonymous with the modification of lysine residues. However, the substrate scope and diversity of the conjugation machinery have been underappreciated, bringing us to an epoch in ubiquitin system research. The striking discoveries of metazoan enzymes dedicated toward serine and threonine ubiquitination have revealed the important role of nonlysine ubiquitination in endoplasmic reticulum-associated degradation, immune signaling and neuronal processes, while reports of nonproteinaceous substrates have extended ubiquitination beyond the proteome. Bacterial effectors that bypass the canonical ubiquitination machinery and form unprecedented linkage chemistry further redefine long-standing dogma. While chemical biology approaches have advanced our understanding of the canonical ubiquitin system, further study of noncanonical ubiquitination has been hampered by a lack of suitable tools. This Perspective aims to consolidate and contextualize recent discoveries and to propose potential applications of chemical biology, which will be instrumental in unraveling this new frontier of ubiquitin research.

Multiple geometry representations for 6D object pose estimation in occluded or truncated scenes

Deep learning-based 6D object pose estimation methods from a single RGBD image have recently received increasing attention because of their powerful representation learning capabilities. These methods, however, cannot handle severe occlusion and truncation. In this paper, we present a novel 6D object pose estimation method based on multiple geometry representations. Specifically, we introduce a network to fuse the appearance and geometry features extracted from input color and depth images. Then, we utilize these per-point fusion features to estimate keypoint offsets, edge vectors, and dense symmetry correspondences in the canonical coordinate system. Finally, a two-stage pose regression module is applied to compute the 6D pose of an object. Relative to the unitary 3D keypoint-based strategy, such combination of multiple geometry representations provides sufficient and diverse information, especially for occluded or truncated scenes. To show the robustness to occlusion and truncation of the proposed method, we conduct comparative experiments on the Occlusion LineMOD, Truncation LineMOD, and T-LESS datasets. Results reveal that the proposed method outperforms state-of-the-art techniques by a large margin.

Data-driven discovery of the governing equations of dynamical systems via moving horizon optimization

Discovering the governing laws underpinning physical and chemical phenomena entirely from data is a key step towards understanding and ultimately controlling systems in science and engineering. Noisy measurements and complex, highly nonlinear underlying dynamics hinder the identification of such governing laws. In this work, we introduce a machine learning framework rooted in moving horizon nonlinear optimization for identifying governing equations in the form of ordinary differential equations from noisy experimental data sets. Our approach evaluates sequential subsets of measurement data, and exploits statistical arguments to learn truly parsimonious governing equations from a large dictionary of basis functions. The proposed framework reduces gradient approximation errors by implicitly embedding an advanced numerical discretization scheme, which improves robustness to noise as well as to model stiffness. Canonical nonlinear dynamical system examples are used to demonstrate that our approach can accurately recover parsimonious governing laws under increasing levels of measurement noise, and outperform state of the art frameworks in the literature. Further, we consider a non-isothermal chemical reactor example to demonstrate that the proposed framework can cope with basis functions that have nonlinear (unknown) parameterizations.

Broadening prime editing toolkits using RNA-Pol-II-driven engineered pegRNA

The prime editor is a versatile tool for targeted precise editing to generate point mutations, small insertions, or small deletions in eukaryotes. However, canonical PE3 system is less efficient, notably in primary cells or pluripotent stem cells. Here, we employed RNA polymerase II promoter instead of RNA polymerase III promoter, whose application is limited by specific DNA contexts, to produce Csy4-processed intronic prime editing guide RNAs (pegRNAs) and, together with other optimizations, achieved efficient targeting with poly(T)-containing pegRNAs, as well as combinatorial and conditional genetic editing. We also found simultaneous suppression of both DNA mismatch repair and DNA damage response could achieve efficient and accurate editing in human embryonic stem cells. These findings relieve the restrictions of RNA polymerase III (RNA-Pol-III)-based base editors and broadened the applications of prime editing.

Canonical systems in the ring of integers

Canonical systems in the ring of integers

Interval-filling sequences of order $N$ and a representation of real numbers in canonical number systems

Interval-filling sequences of order $N$ and a representation of real numbers in canonical number systems

Integral domains with canonical number systems

Integral domains with canonical number systems

Experimental investigation on the synchronization characteristics of a pitch-plunge aeroelastic system exhibiting stall flutter.

This study focuses on characterizing the bifurcation scenario and the underlying synchrony behavior in a nonlinear aeroelastic system under deterministic as well as stochastic inflow conditions. Wind tunnel experiments are carried out for a canonical pitch-plunge aeroelastic system subjected to dynamic stall conditions. The system is observed to undergo a subcritical Hopf bifurcation, giving way to large-amplitude limit cycle oscillations (LCOs) in the stall flutter regime under the deterministic flow conditions. At this condition, we observe intermittent phase synchronization between pitch and plunge modes near the fold point, whereas synchronization via phase trapping is observed near the Hopf point. Repeating the experiments under stochastic inflow conditions, we observe two different aeroelastic responses: low amplitude noise-induced random oscillations (NIROs) and high-amplitude random LCOs (RLCOs) during stall flutter. The present study shows asynchrony between pitch and plunge modes in the NIRO regime. At the onset of RLCOs, asynchrony persists even though the relative phase distribution changes. With further increase in the flow velocity, we observe intermittent phase synchronization in the flutter regime. To the best of the authors' knowledge, this is the first study reporting the experimental evidence of phase synchronization between pitch and plunge modes of an aeroelastic system, which is of great interest to the nonlinear dynamics community. Furthermore, given the ubiquitous presence of stall behavior and stochasticity in a variety of engineering systems, such as wind turbine blades, helicopter blades, and unmanned aerial vehicles, the present findings will be directly beneficial for the efficient design of futuristic aeroelastic systems.

Output feedback full-order sliding mode control for a three-tank system

A robust output feedback nonlinear control method is proposed for output tracking of an uncertain three-tank system by using only the level sensor of the target tank. By using a coordinate transformation, we first transform the system model into a canonical form with uncertainties. The canonical system’s state variables are estimated by a higher-order sliding mode differentiator based on the measurement of the target tank’s liquid level. Then based on the estimated state variables, a continuous full-order sliding mode controller is constructed which can eliminate the effects of both the additive and multiplicative uncertainties. Rigorous analysis is carried out to clarify the control performance. And the effectiveness of the proposed method is verified by experimental studies on the Inteco Multi-tank system.

EditVAE: Unsupervised Parts-Aware Controllable 3D Point Cloud Shape Generation

This paper tackles the problem of parts-aware point cloud generation. Unlike existing works which require the point cloud to be segmented into parts a priori, our parts-aware editing and generation are performed in an unsupervised manner. We achieve this with a simple modification of the Variational Auto-Encoder which yields a joint model of the point cloud itself along with a schematic representation of it as a combination of shape primitives. In particular, we introduce a latent representation of the point cloud which can be decomposed into a disentangled representation for each part of the shape. These parts are in turn disentangled into both a shape primitive and a point cloud representation, along with a standardising transformation to a canonical coordinate system. The dependencies between our standardising transformations preserve the spatial dependencies between the parts in a manner that allows meaningful parts-aware point cloud generation and shape editing. In addition to the flexibility afforded by our disentangled representation, the inductive bias introduced by our joint modeling approach yields state-of-the-art experimental results on the ShapeNet dataset.

FGDB: a comprehensive graph database of ligand fragments from the Protein Data Bank.

This work presents Fragment Graph DataBase (FGDB), a graph database of ligand fragments extracted and generated from the protein entries available in the Protein Data Bank (PDB). FGDB is meant to support and elicit campaigns of fragment-based drug design, by enabling users to query it in order to construct ad hoc, target-specific libraries. In this regard, the database features more than 17 000 fragments, typically small, highly soluble and chemically stable molecules expressed via their canonical Simplified Molecular Input Line Entry System (SMILES) representation. For these fragments, the database provides information related to their contact frequencies with the amino acids, the ligands they are contained in and the proteins the latter bind to. The graph database can be queried via standard web forms and textual searches by a number of identifiers (SMILES, ligand and protein PDB ids) as well as via graphical queries that can be performed against the graph itself, providing users with an intuitive and effective view upon the underlying biological entities. Further search mechanisms via advanced conjunctive/disjunctive/negated textual queries are also possible, in order to allow scientists to look for specific relationships and export their results for further studies. This work also presents two sample use cases where maternal embryonic leucine zipper kinase and mesotrypsin are used as a target, being proteins of high biomedical relevance for the development of cancer therapies. Database URL: http://biochimica3.bio.uniroma3.it/fragments-web/

The set of zeros of the Riemann zeta function as the point spectrum of an operator

A possible way of proving the Riemann hypothesis consists of constructing a selfadjoint operartor whose spectrum coincides with the set { z : | Im ⁡ z | > 1 2 , ζ ( 1 2 − i z ) = 0 } \{z\,: \, |\operatorname {Im}z|>\frac 12, \ \zeta \big (\frac {1}{2}-iz\big )=0\} . In the paper we construct a rank-one perturbation of a selfadjoint operator related to a certain canonical system for which a similar property is fulfilled.

Rotational thermodynamic parameters for asymmetric-top molecules: classical vs. quantum approaches and new analytical partition function

We investigated classical and quantum rotational partition functions, rotational energies and rotational entropies for asymmetric-top molecules in a canonical system within a wide range of temperatures under the rigid rotor approximation. We then derived the temperature, , below which classical approach is not valid, and the complex quantum approach is strongly recommended. This temperature certainly increases with the inertia moment of the molecule and follows a power function when rotational partition functions are considered. As for linear-, spherical- and symmetric-top molecules, quantum approach is not needed at all for energetic rotational parameters, whatever the temperature for asymmetric-top molecules. Therefore, there is no real frontier between the classical and quantum approaches when energetic rotational parameters are concerned, though the frontier is naturally a bounded decreasing sequence converging to zero when rotational partition functions are rather concerned. Particularly, classical approach fails describing rotational partition functions for light molecules or molecules at low temperatures. Moreover, all the closed-form expressions proposed in the whole literature fail drastically approaching quantum and exact results for light molecules or molecules at low temperatures. In regard to the importance of partition functions in the evaluation of rate constants for chemical reactions and accurate intensities lines in spectroscopy, we proposed new accurate and simple analytic expression of the rotational partition functions of asymmetric-top molecules, valid at all temperatures.

Involvement of the Renin-Angiotensin System in Stress: State of the Art and Research Perspectives.

Along with other canonical systems, the renin-angiotensin system (RAS) has shown important roles in stress. This system is a complex regulatory proteolytic cascade composed of various enzymes, peptides, and receptors. Besides the classical (ACE/Ang II/AT1 receptor) and the counter-regulatory (ACE2/Ang-(1-7)/Mas receptor) RAS axes, evidence indicates that nonclassical components, including Ang III, Ang IV, AT2 and AT4, can also be involved in stress. This comprehensive review summarizes the current knowledge on the participation of RAS components in different adverse environmental stimuli stressors, including air jet stress, cage switch stress, restraint stress, chronic unpredictable stress, neonatal isolation stress, and post-traumatic stress disorder. In general, activation of the classical RAS axis potentiates stress-related cardiovascular, endocrine, and behavioral responses, while the stimulation of the counter-regulatory axis attenuates these effects. Pharmacological modulation in both axes is optimistic, offering promising perspectives for stress-related disorders treatment. In this regard, angiotensin-converting enzyme inhibitors and angiotensin receptor blockers are potential candidates already available since they block the classical axis, activate the counter-regulatory axis, and are safe and efficient drugs.

Revisiting TSHβ's Role in Avian Seasonal Reproduction, Insights, and Challenges from Mammalian Models.

The core neuroendocrine pathways regulating seasonal reproduction in vertebrates were characterized over a decade ago. This has led to the development of a "consensus" model of seasonal reproduction that appears to be largely conserved across mammals, birds, amphibians, reptile and fish. This model centers around the photoinduced increase in TSHβ expression in the pars tuberalis of the anterior pituitary gland as the key transducer of photic information from sensory cells to the critical switch in hypothalamic deiodinase enzyme expression that drives changes in localized thyroid hormone signaling. These changes in localized thyroid hormone signaling in the medial basal hypothalamus ultimately activate the reproductive axis. This model has in turn, been consistently supported by studies in a variety of taxa. As such, it has become the standard against which subsequent work is compared, particularly in the non-mammalian literature. However, as new studies move away from the handful of canonical model systems and begin to explore the effects of naturalistic rather than artificial photoperiod manipulations, a more nuanced picture has begun to emerge. Yet, progress in elucidating the detailed events of reproductive photostimulation has been uneven across the research community. In this perspective, I draw on emerging data from studies in free living animals that challenges some of the established assumptions of the avian consensus model of reproduction. Specifically, the role of TSHβ and its dissociation from deiodinase signaling. I then discuss how these apparently surprising findings can be contextualized within the context of the mammalian seasonal literature. In turn, this ability to contextualize from the mammalian literature highlights the breadth of the current gap versus our understanding of the molecular neuroendocrine mechanisms of seasonality in mammals versus birds and other non-mammalian seasonal breeders.

Nanoscale resolution of microbial fiber degradation in action.

The lives of microbes unfold at the micron scale, and their molecular machineries operate at the nanoscale. Their study at these resolutions is key toward achieving a better understanding of their ecology. We focus on cellulose degradation of the canonical Clostridium thermocellum system to comprehend how microbes build and use their cellulosomal machinery at these nanometer scales. Degradation of cellulose, the most abundant organic polymer on Earth, is instrumental to the global carbon cycle. We reveal that bacterial cells form 'cellulosome capsules' driven by catalytic product-dependent dynamics, which can increase the rate of hydrolysis. Biosynthesis of this energetically costly machinery and cell growth are decoupled at the single-cell level, hinting at a division-of-labor strategy through phenotypic heterogeneity. This novel observation highlights intrapopulation interactions as key to understanding rates of fiber degradation.