Cyclic Modulation Research Articles

When ideals of a commutative semilocal ring decompose into cyclic modules

When ideals of a commutative semilocal ring decompose into cyclic modules

Cyclic Oligosaccharide-Induced Modulation of Immunoglobulin A Reactivity to Gut Bacteria Contributes to Alterations in the Bacterial Community Structure.

Immunoglobulin A (IgA) is a major gut antibody that coats commensal gut bacteria and contributes to shaping a stable gut bacterial composition. Although previous studies have shown that cyclic oligosaccharides, including cyclic nigerosyl-1,6-nigerose (CNN) and cyclodextrins (CDs, including αCD, βCD, and γCD), alter the gut bacterial composition, it remains unclear whether cyclic oligosaccharides modify the IgA coating of gut bacteria, which relates to cyclic oligosaccharide-induced alteration of the gut bacterial composition. To address this issue, mice were maintained for 12 weeks on diets containing CNN, αCD, βCD, or γCD; the animals' feces were evaluated for their bacterial composition and the IgA coating index (ICI), a measure of the degree of IgA coating of bacteria. We observed that the intake of each cyclic oligosaccharide altered the gut bacterial composition, with changes in the ICI found at both the phylum and genus levels. The ICI for Bacillota, Lachnospiraceae NK4A136 group, UC Lachnospiraceae, and Tuzzerella were significantly and positively correlated with the relative abundance (RA) in total bacteria for these bacteria; in contrast, significant correlations were not seen for other phyla and genera. Our observations suggest that cyclic oligosaccharide-induced modulation of the IgA coating of gut bacteria may partly relate to changes in the community structure of the gut bacteria.

Linguistic-Driven Partial Semantic Relevance Learning for Skeleton-Based Action Recognition.

Skeleton-based action recognition, renowned for its computational efficiency and indifference to lighting variations, has become a focal point in the realm of motion analysis. However, most current methods typically only extract global skeleton features, overlooking the potential semantic relationships among various partial limb motions. For instance, the subtle differences between actions such as "brush teeth" and "brush hair" are mainly distinguished by specific elements. Although combining limb movements provides a more holistic representation of an action, relying solely on skeleton points proves inadequate for capturing these nuances. Therefore, integrating detailed linguistic descriptions into the learning process of skeleton features is essential. This motivates us to explore integrating fine-grained language descriptions into the learning process of skeleton features to capture more discriminative skeleton behavior representations. To this end, we introduce a new Linguistic-Driven Partial Semantic Relevance Learning framework (LPSR) in this work. While using state-of-the-art large language models to generate linguistic descriptions of local limb motions and further constrain the learning of local motions, we also aggregate global skeleton point representations and textual representations (which generated from an LLM) to obtain a more generalized cross-modal behavioral representation. On this basis, we propose a cyclic attentional interaction module to model the implicit correlations between partial limb motions. Numerous ablation experiments demonstrate the effectiveness of the method proposed in this paper, and our method also obtains state-of-the-art results.

Near‐Infrared Afterglow Luminescence Amplification via Albumin Complexation of Semiconducting Polymer Nanoparticles for Surgical Navigation in Ex Vivo Porcine Models

AbstractAfterglow imaging, leveraging persistent luminescence following light cessation, has emerged as a promising modality for surgical interventions. However, the scarcity of efficient near‐infrared (NIR) responsive afterglow materials, along with their inherently low brightness and lack of cyclic modulation in afterglow emission, has impeded their widespread adoption. Addressing these challenges requires a strategic repurposing of afterglow materials that improve on such limitations. Here, an afterglow probe, composed of bovine serum albumin (BSA) coated with an afterglow material, a semiconducting polymer dye (SP1), called BSA@SP1 demonstrating a substantial amplification of the afterglow luminescence (≈3‐fold) compared to polymer‐lipid coated PFODBT (DSPE‐PEG@SP1) under same experimental conditions is developed. This enhancement is believed to be attributed to the electron‐rich matrix provided by BSA that immobilizes SP1 and enhances the generation of 1O2 radicals, which improves the afterglow luminescence brightness. Through molecular docking, physicochemical characterization, and optical assessments, BSA@SP1's superior afterglow properties, cyclic afterglow behavior, long‐term colloidal stability, and biocompatibility are highlighted. Furthermore, superior tissue permeation profiling of afterglow signals of BSA@SP1's compared to fluorescence signals using ex vivo tumor‐mimicking phantoms and various porcine tissue types (skin, muscle, and fat) is demonstrated. Expanding on this, to showcase BSA@SP1's potential in image‐guided surgeries, tumor‐mimicking phantoms within porcine lungs and conducted direct comparisons between fluorescence and afterglow‐guided interventions to illustrate the latter's superiority is implanted. Overall, the study introduces a promising strategy for enhancing current afterglow materials through protein complexation, resulting in both ultrahigh signal‐to‐background ratios and cyclic afterglow signals.

FTAN: Frame-to-frame temporal alignment network with contrastive learning for few-shot action recognition

Most current few-shot action recognition approaches follow the metric learning paradigm, measuring the distance of any sub-sequences (frames, any frame combinations or clips) between different actions for classification. However, this disordered distance metric between action sub-sequences ignores the long-term temporal relations of actions, which may result in significant metric deviations. What's more, the distance metric suffers from the distinctive temporal distribution of different actions, including intra-class temporal offsets and inter-class local similarity. In this paper, a novel few-shot action recognition framework, Frame-to-frame Temporal Alignment Network (FTAN), is proposed to address the above challenges. Specifically, an attention-based temporal alignment (ATA) module is devised to calculate the distance between corresponding frames of different actions along the temporal dimension to achieve frame-to-frame temporal alignment. Meanwhile, the Temporal Context module (TCM) is proposed to increase inter-class diversity by enriching the frame-level feature representation, and the Frames Cyclic Shift Module (FCSM) performs frame-level temporal cyclic shift to reduce intra-class inconsistency. In addition, we present temporal and global contrastive objectives to assist in learning discriminative and class-agnostic visual features. Experimental results show that the proposed architecture achieves state-of-the-art on HMDB51, UCF101, Something-Something V2 and Kinetics-100 datasets.

Interactions Enable Thouless Pumping in a Nonsliding Lattice

A topological “Thouless” pump represents the quantized motion of particles in response to a slow, cyclic modulation of external control parameters. The Thouless pump, like the quantum Hall effect, is of fundamental interest in physics, because it links physically measurable quantities, such as particle currents, to geometric properties of the experimental system, which can be robust against perturbations and, thus, technologically useful. So far, experiments probing the interplay between topology and interparticle interactions have remained relatively scarce. Here, we observe a Thouless-type charge pump in which the particle current and its directionality inherently rely on the presence of strong interactions. Experimentally, we utilize a two-component Fermi gas in a dynamical superlattice which does not exhibit a sliding motion and remains trivial in the single-particle regime. However, when tuning interparticle interactions from zero to positive values, the system undergoes a transition from being stationary to drifting in one direction, consistent with quantized pumping in the first cycle. Remarkably, the topology of the interacting pump trajectory cannot be adiabatically connected to a noninteracting limit, highlighted by the fact that only one atom is transferred per cycle. Our experiments suggest that Thouless charge pumps are promising platforms to gain insights into interaction-driven topological transitions and topological quantum matter. Published by the American Physical Society 2024

SCAN Algorithm to Optimize Dynamic Instructional Information Network for Predicting Student Behavior

With the integration of work, study and life on campus taking shape gradually in major universities across China, the concept of education from classroom to life is more widely accepted and the smart education model has become a trend in education informatization. However, most of the existing studies are not applicable to student behaviour data in the campus environment, and the temporal as well as cyclical characteristics in the data are not accessible in the student behaviour prediction problem. In this study, a hypergraph-based dynamic campus behaviour information network is designed to address the needs of the student behaviour prediction problem, and a student campus behaviour prediction algorithm is proposed in the dynamic campus behaviour information network-based student behaviour prediction problem. The effectiveness and rationality of the algorithm is verified through experiments with real campus data sets. The experimental results demonstrated that the periodic nature of the data acquired by the cycle gated cyclic unit module needs to be built on top of the snapshot gated cyclic unit module to help the algorithm achieve better results. The area under the curve of the algorithm proposed in the study achieves more advantageous results on both the 21-day and 35-day datasets. The cycle gated cyclic unit module of the student campus behaviour prediction algorithm proposed in this study can more effectively extract the cyclic features present in the dynamic campus behaviour information network and better accomplish the prediction of student campus behaviour.

Spectroscopic and photometric investigations of the totally eclipsing contact binary V1320 Cas

We analyzed the light curve of the total eclipse contact binary V1320 Cas, obtained reliable photometric solutions, confirmed it to be a W-type contact binary with a mass ratio of 3.404 and a contact degree of 23.9%, a cool spot is discovered on the less massive component. Orbital period analysis indicates that the period of V1320 Cas is decreasing at a rate of dPdt=1.78×10−7 day yr−1, superimposed with a cyclic modulation with a period of 1.425 yr, long-term period decrease may be caused by the combination of mass transfer and angular momentum loss, and the cyclic modulation may be caused by the third companion. Using the photometric solutions and Gaia distance, we calculated the absolute physical parameters and plotted mass-luminosity and mass–radius diagrams to analyze the evolutionary status of V1320 Cas, the more massive component is a main sequence star, while the less massive component has higher luminosity and radius than those of main sequence stars with the same mass. With the decreasing orbital period, the two components of V1320 Cas will be gradually closer, while the binary may evolve toward deep contact.

When do modules mimic arbitrary sets?

We study rings whose modules and module homomorphisms display behavior similar to that of sets and their maps. For example, whenever there is an epimorphism A → B , there is a monomorphism B → A (Artinian principal ideal rings (PIR) satisfy this property and its dual for all modules). As a byproduct of this framework, we prove that a ring every factor ring of which cogenerates its cyclic right modules (one-sided version of Kaplansky’s dual rings) is right Artinian and right serial. Consequently, R is an Artinian PIR if and only if every factor ring of R cogenerates its finitely generated right modules. These results can be viewed as partial answers to the CF problem, the FGF problem due to Faith and a question of Faith and Menal on strongly Johns rings. Some known results and the above one yield the following: A ring R is a direct sum of right Artinian right chain rings and Artinian PIR’s if and only if every factor ring of R cogenerates its (uniform) cyclic right modules (with nonzero socle); so, such rings coincide with the right CES-rings of Jain and Lopez-Pérmouth, rings whose factors are right CF and rings that satisfy the above mentioned property for their cyclic right modules A and B. Finally, a ring is either simple Artinian or a right Artinian right chain ring if and only if one of any two cyclic right modules embeds in the other.

Prototype-based sample-weighted distillation unified framework adapted to missing modality sentiment analysis

Missing modality sentiment analysis is a prevalent and challenging issue in real life. Furthermore, the heterogeneity of multimodality often leads to an imbalance in optimization when attempting to optimize the same objective across all modalities in multimodal networks. Previous works have consistently overlooked the optimization imbalance of the network in cases when modalities are absent. This paper presents a Prototype-Based Sample-Weighted Distillation Unified Framework Adapted to Missing Modality Sentiment Analysis (PSWD). Specifically, it fuses features with a more efficient transformer-based cross-modal hierarchical cyclic fusion module. Subsequently, we propose two strategies, namely sample-weighted distillation and prototype regularization network, to address the issues of missing modality and optimization imbalance. The sample-weighted distillation strategy assigns higher weights to samples that are located closer to class boundaries. This facilitates the obtaining of complete knowledge by the student network from the teacher’s network. The prototype regularization network calculates a balanced metric for each modality, which adaptively adjusts the gradient based on the prototype cross-entropy loss. Unlike conventional approaches, PSWD not only connects the sentiment analysis study in the missing modality to the full modality, but the proposed prototype regularization network is not reliant on the network structure and can be expanded to more multimodal studies. Massive experiments conducted on IEMOCAP and MSP-IMPROV show that our method achieves the best results compared to the latest baseline methods, which demonstrates its value for application in sentiment analysis.

An experimental study on thermal runaway propagation over cyclic aging lithium-ion battery modules with different electrical connections

This paper investigates the thermal runaway propagation characteristics of cyclic aging battery modules connected in series, parallel, and series-parallel configurations. Additionally, a comparative analysis of the thermal runaway characteristics among the three battery module configurations is performed. In this experiment, voltage, mass, and other parameters of cells are measured. The temperature response reveals that: when comparing the three battery module configurations, the parallel module has the highest maximum temperature of thermal runaway at 720 °C, followed by the series and series-parallel combined configurations at 683 °C and 669 °C, respectively. The parallel module also exhibits the fastest propagation rate of thermal runaway, which is further intensified by cyclic aging. Regarding the voltage response: the series configuration has five stages of voltage variation during thermal runaway, while the parallel configuration has two stages, and the series-parallel combined configuration has three stages. Cyclic aging accelerates the voltage decline during thermal runaway for all three battery module types. In terms of mass response: the 2P2S configuration experiences the highest mass loss of 55.7 g, followed by the parallel (40.8 g) and series (34.7 g) configurations. Preliminary heat transfer analysis shows that: the average heat transfer during thermal runaway is highest for the 2P2S configuration (20,161 J), followed by the 4S (18,913 J) and 4P (18,773 J) configurations. Cyclic aging reduces the overall heat transfer. Electrical connections have minimal impact on heat transfer within the battery modules. Specifically, in the 4S, 4P, and 2P2S configurations, the heat transfer attributed to electrical connections accounts for only 1.2 %, 0.4 %, and 7.3 % respectively, of the overall heat conduction through the battery shell.

Module categories, internal bimodules, and Tambara modules

AbstractWe use the theory of Tambara modules to extend and generalize the reconstruction theorem for module categories over a rigid monoidal category to the nonrigid case. We show a biequivalence between the 2‐category of cyclic module categories over a monoidal category and the bicategory of algebra and bimodule objects in the category of Tambara modules on . Using it, we prove that a cyclic module category can be reconstructed as the category of certain free module objects in the category of Tambara modules on , and give a sufficient condition for its reconstructability as module objects in . To that end, we extend the definition of the Cayley functor to the nonclosed case, and show that Tambara modules give a proarrow equipment for ‐module categories, in which ‐module functors are characterized as 1‐morphisms admitting a right adjoint. Finally, we show that the 2‐category of all ‐module categories embeds into the 2‐category of categories enriched in Tambara modules on , giving an “action via enrichment” result.

Cyclic Modulation of Active-Clamped Single Power-Conversion AC–DC Converter for Self-Loss Balancing

Cyclic Modulation of Active-Clamped Single Power-Conversion AC–DC Converter for Self-Loss Balancing

Triple Feature Disentanglement for One-Stage Adaptive Object Detection

In recent advancements concerning Domain Adaptive Object Detection (DAOD), unsupervised domain adaptation techniques have proven instrumental. These methods enable enhanced detection capabilities within unlabeled target domains by mitigating distribution differences between source and target domains. A subset of DAOD methods employs disentangled learning to segregate Domain-Specific Representations (DSR) and Domain-Invariant Representations (DIR), with ultimate predictions relying on the latter. Current practices in disentanglement, however, often lead to DIR containing residual domain-specific information. To address this, we introduce the Multi-level Disentanglement Module (MDM) that progressively disentangles DIR, enhancing comprehensive disentanglement. Additionally, our proposed Cyclic Disentanglement Module (CDM) facilitates DSR separation. To refine the process further, we employ the Categorical Features Disentanglement Module (CFDM) to isolate DIR and DSR, coupled with category alignment across scales for improved source-target domain alignment. Given its practical suitability, our model is constructed upon the foundational framework of the Single Shot MultiBox Detector (SSD), which is a one-stage object detection approach. Experimental validation highlights the effectiveness of our method, demonstrating its state-of-the-art performance across three benchmark datasets.

Injectivity and projectivity domains of a simple module over a commutative ring

Let R be a commutative ring. We determine the cyclic modules in the projectivity domain and those in the injectivity domain of a simple R-module. An R-module M is called poor (p-poor) if for every R-module N, M is N-injective (M is N-projective) only if N is semisimple. We describe the structure of simple poor R-modules and simple p-poor R-modules. We show that every simple poor R-module is p-poor and the converse holds when R is noetherian or semilocal. It is shown that every simple R-module is poor if and only if every simple R-module is p-poor if and only if R is local or semisimple. We prove that every simple R-module is either p-poor or projective if and only if R is semisimple or R has exactly one essential maximal ideal. We conclude by studying the class of commutative rings R over which every simple R-module is either poor or injective.

Tracking active nests in solar-type pulsators: Ensemble starspot modelling of Kepler asteroseismic targets

The satellite Planetary Transits and Oscillations of stars (PLATO), due to be launched late 2026, will provide us with an unprecedented sample of light curves of solar-type stars that will exhibit both solar-type oscillations and signatures of activity-induced brightness modulations. Solar-type pulsators only have moderate levels of activity because high levels of activity inhibit oscillations. This means that these targets represent a specific challenge for starspot modelling. In order to assess the possibilities that PLATO will soon open, we wish to characterise the morphology of active regions at the surface of stars for which we also have a detection of solar-like acoustic oscillations. In this context, we report the results of an ensemble starspot modelling analysis of the Sun and ten solar-type pulsators observed by the Kepler satellite. We implement a Bayesian starspot modelling approach based on a continuous-grid model, accounting for the combined starspot and facular contribution to activity-induced brightness modulations. From our analysis, we find that several stars of our sample exhibit clear signatures of stable longitudinal active nests while sharing activity levels and convection versus rotation regimes similar to the solar regime. By searching for modulations in the reconstructed starspot coverage, we found significant periodicities that we identify as possible signatures of cyclic modulations similar to the quasi-biennal oscillation or the Rieger cycle. We can infer the corresponding intensity of the magnetic field at the bottom of the convective envelope based on the hypothesis that internal magneto-Rossby waves acting on the tachocline cause these modulations.

Strongly nearly-2-absorbing submodules

Let Ɍ be a commutative ring with identity and V be a unitary left Ɍ-module. The concept of Strongly Nearly-2-Absorabing sub-modules as a generalization of Endo-2-Absorabing sub-modules and strong form of Nearly-2-Absorabing sub-modules are introduced in this paper. Many examples, basic properties of this concept are introduced. Furthermore we prove that in class of (scalar, cyclic and finitely-generated) modules the two concepts Nearly-2-Absorabing sub-modules and Strongly Nearly-2-Absorabing sub-modules are equivalent. Moreover we prove that Endo-2-Absorabing and Strongly Nearly-2-Absorabing sub-modules are equivalent in class of (semi simple, regular) modules. Also those concepts are equivalent in class of all modules over a v-ring. Finally we prove several characterizations of Strongly Nearly-2-Absorabing sub-modules in some types of modules such as (projective, faithful and content) modules in class of cyclic modules.

Preorganized cyclic modules facilitate the self-assembly of protein nanostructures.

The rational design of supramolecular assemblies aims to generate complex systems based on the simple information encoded in the chemical structure. Programmable molecules such as nucleic acids and polypeptides are particularly suitable for designing diverse assemblies and shapes not found in nature. Here, we describe a strategy for assembling modular architectures based on structurally and covalently preorganized subunits. Cyclization through spontaneous self-splicing of split intein and coiled-coil dimer-based interactions of polypeptide chains provide structural constraints, facilitating the desired assembly. We demonstrate the implementation of a strategy based on the preorganization of the subunits by designing a two-chain coiled-coil protein origami (CCPO) assembly that adopts a tetrahedral topology only when one or both subunit chains are covalently cyclized. Employing this strategy, we further design a 109 kDa trimeric CCPO assembly comprising 24 CC-forming segments. In this case, intein cyclization was crucial for the assembly of a concave octahedral scaffold, a newly designed protein fold. The study highlights the importance of preorganization of building modules to facilitate the self-assembly of higher-order supramolecular structures.

On the braided Connes–Moscovici construction

In 1998, Connes and Moscovici defined the cyclic cohomology of Hopf algebras. In 2010, Khalkhali and Pourkia proposed a braided generalization: to any Hopf algebra H in a braided category \mathcal{B} , they associate a paracocyclic object in \mathcal{B} . In this paper, we explicitly compute the powers of the paracocyclic operator of this paracocyclic object. Also, we introduce twisted modular pairs in involution for H and derive (co)cyclic modules from them. Finally, we relate the paracocyclic object associated with H to that associated with an H -module coalgebra via a categorical version of the Connes–Moscovici trace.

On the Goldie dimension of finitely generated locally cyclic modules

Let R be a commutative ring with identity. In this paper we investigate the Goldie dimension of finitely generated locally cyclic R-modules. Then, we give a characterization of rings whose finitely generated locally cyclics have finite Goldie dimension.