Characterization Of Class Research Articles

Pulse characterization at the single-photon level through chronocyclic Q-function measurements

The characterization of the complex spectral amplitude, that is, the spectrum and spectral phase, of single-photon-level light fields is a crucial capability for modern photonic quantum technologies. Since established pulse characterization techniques are not applicable at low intensities, alternative approaches are required. Here, we demonstrate the retrieval of the complex spectral amplitude of single-photon-level light pulses through measuring their chronocyclic Q −function. Our approach draws inspiration from quantum state tomography by exploiting the analogy between quadrature phase space and time-frequency phase space. In the experiment, we perform time-frequency projections with a quantum pulse gate (QPG), which directly yield the chronocyclic Q −function. We evaluate the complex spectral amplitude from the measured chronocyclic Q −function data with maximum likelihood estimation (MLE), which is the established technique for quantum state tomography. The MLE yields not only an unambigious estimate of the complex spectral amplitude of the state under test that does not require any a priori information, but also allows for, in principle, estimating the spectral-temporal coherence properties of the state. Our method accurately recovers features such as jumps in the spectral phase and is resistant against regions with zero spectral intensity, which makes it immediately beneficial for classical pulse characterization problems.

Black hole from entropy maximization

One quantum characterization of a black hole motivated by (local) holography and thermodynamics is that it maximizes thermodynamic entropy for a given surface area. In the context of quantum gravity, this could be more fundamental than the classical characterization by a horizon. As a step, we explore this possibility by solving the 4D semiclassical Einstein equation with many matter fields. For highly excited spherically symmetric static configurations, we apply local typicality and estimate the entropy including self-gravity to derive its upper bound. The saturation condition uniquely determines the entropy-maximized configuration: self-gravitating quanta condensate into a radially uniform dense configuration with no horizon, where the self-gravity and a large quantum pressure induced by the curvatures are balanced and no singularity appears. The interior metric is a self-consistent and nonperturbative solution in Planck’s constant. The maximum entropy, given by the volume integral of the entropy density, agrees with the Bekenstein-Hawking formula through self-gravity, deriving the Bousso bound for thermodynamic entropy. Finally, 10 future prospects are discussed, leading to a speculative view that the configuration represents a quantum-gravitational condensate in a semiclassical manner. Published by the American Physical Society 2025

Leveraging molecular scale free volume generation to improve gas separation performance of carbon molecular sieve membranes

Carbon molecular sieve (CMS) membranes have proven to be promising candidates for next-generation gas separations. Modification of polymeric precursors is a critical tool that permits fine-tuning of CMS structure and performance for a wide variety of gas mixtures. Here, we make a targeted alteration to a polyimide CMS precursor through substitution of free-volume-generating trifluoromethyl groups for aliphatic methyl groups on the polymer backbone. Gas separation performance shows a vast improvement, demonstrated by up to an eightfold increase in gas permeability as well as higher mixed gas separation factors in some cases. We investigate these properties, and their dependence on pyrolysis temperature, with detailed measurements of gas sorption and permeation in CMS dense film membranes with additional analysis through classical materials characterization methods. Our observations indicate that addition of free-volume-generating groups into polymeric precursors is a powerful tool for developing state-of-the-art CMS membranes, especially in cases when high permeability is an important design parameter.

A room of one’s own? The consequences of living density on individual well-being and social anomie

Abstract The global housing affordability crisis and COVID shutdowns have put living space inequality back on the political agenda. Drawing on Durkheim’s theory of anomie and density, this paper argues that on how many square meters a society lives matters for how stable or anomic it develops. Using data from the Swiss Household Panel, we examine the selection, short-term, and dynamic effects associated with transitions to overcrowded and under-occupied dwellings. We conceptualize these transitions as disruptive events that require a reconfiguration of personal and social equilibria in individuals’ lives. While overcrowded housing leads to a heightening of emotional states and more tense internal household dynamics, people respond by adjusting their leisure activities and restructuring their support networks from strong to weak ties. Conversely, moving to an under-occupied dwelling is associated with melancholic emotional stabilization, but improves household balance and leads to consolidation of the core network of relatives at the expense of outer social circles. We conclude that the classical characterization of anomie as a mismatch between personal means and societal ends should be understood as a multifaceted phenomenon in which meso-level social networks can be a crucial means to cope with disruptions that arise at other levels.

Some constructions of 3-pre-Lie-Rinehart algebras

3-Lie-Rinehart algebras are an algebraic axiomatization of the basic properties of Filippov algebroids (for n = 3). The purpose of this paper is to introduce the notion of relative Rota-Baxter operators on a 3-Lie-Rinehart algebra and give some classical characterizations. Next, we define 3-pre-Lie-Rinehart algebras which can be seen as a dendrification of 3-Lie-Rinehart algebras by means of relative Rota-Baxter operators. Moreover, we introduce the notion of trace functions on Lie-Rinehart algebra and pre-Lie-Rinehart algebra to construct their induced 3-Lie-Rinehart algebra and 3-pre-Lie-Rinehart algebra, respectively.

Emotional parameter estimation from emo-soundscapes dataset using Deep Convolutional Autoencoders

AbstractPredicting the emotional responses of humans to acoustic features in the surrounding environment has a highly potential of applications in different fields, ranging from videogames, therapeutic use of virtual reality to the emotional design of spaces according to their expected use. In this paper we model the estimation process of the classical emotion characterization parameters (arousal and valence) from sounds. By means of convolutional neural networks and convolutional autoencoders, the model is adjusted for the prediction of these parameters from a standard dataset [1], improving the results obtained in previous literature. The relevance of the work, apart from improving the results due to the use of autoencoders, is that it eliminates the need to compute handcrafted features, thus demonstrating the ability of convolutional neural networks to treat raw information. Other main contributions of the paper is a new way to visualize the errors in the joint estimation of arousal and valence that facilitates the evaluation of the results obtained by the models. Finally, the use of bootstrap to estimate the confidence intervals of the MSE and r2 of Deep Learning models shows that in comparison to non-overlapping samples, overlapping samples introduces performance bias.

Corynebacterium pseudotuberculosis: Whole genome sequencing reveals unforeseen and relevant genetic diversity in this pathogen.

Corynebacterium pseudotuberculosis (CPS) is an important bacterial animal pathogen. CPS causes chronic, debilitating and currently incurable infectious diseases affecting a wide range of livestock and wild herbivores including camelids worldwide. Belonging to the Corynebacterium diphtheriae complex, this pathogen can also infect humans. The classical characterization of CPS is typically based on the testing of nitrate reductase activity, separating the two biovars Equi and Ovis. However, more refined resolutions are required to unravel routes of infection. This was realized in our study by generating and analyzing whole genome sequencing (WGS) data. Using newly created core genome multilocus sequence typing (cgMLST) profiles we were the first to discover isolates grouping in a cluster adjacent to clusters formed by CPS biovar Equi isolates. This novel cluster includes CPS isolates from alpacas, llamas, camels and dromedaries, which are characterized by a lack of nitrate reductase activity as encountered in biovar Ovis. This is of special interest for molecular epidemiology. Nevertheless, these isolates bear the genes of the nitrate locus, which are characteristic of biovar Equi isolates. However, sequence analysis of the genes narG and narH of the nitrate locus revealed indels leading to frameshifts and inactivity of the enzymes involved in nitrate reduction. Interestingly, one CPS isolate originating from another lama with an insertion in the MFS transporter (narT) is adjacent to a cluster formed by ovine CPS isolates biovar Equi. Based on this knowledge, the combination of biochemical and PCR based molecular biological nitrate reductase detection can be used for a fast and uncomplicated classification of isolates in routine diagnostics in order to check the origin of camelid CPS isolates. Further analysis revealed that partial sequencing of the ABC transporter substrate binding protein (CP258_RS07935) is a powerful tool to assign the biovars and the novel genomovar.

Determination of Thermal Properties of Carbon Materials above 2000 °C for Application in High Temperature Crystal Growth

AbstractThis work reports on the determination of the heat conductivity of high temperature stable carbon materials in the temperature range well above 2000 °C where classic material characterization methods fail. Dense graphite (DG) materials as well as rigid and soft felt isolation (RFI/SFI) components have been investigated which are used during crystal growth of SiC by the physical vapor transport method (PVT) in the temperature regime of 2000 and 2400 °C. The applied materials characterization methods include low temperature physical heat conductivity measurements using laser flash analysis (LFA) in the temperature range 25–1200 °C, data extrapolation to elevated temperatures up to 2400 °C, and a correlation of heating processes and computer simulation of the temperature field of different hot zone designs. Using this approach, the calculated temperatures and experimentally determined values with an error of less than ± 2% at 2400 °C can be merged.

Grape (Vitis labrusca L.) juices, cv. Bordô, from vineyards in organic production systems and conventional production: Similarities and differences

The similarities and differences between foods produced under organic (OP) and conventional (CP) systems remain a controversial topic. In order to contribute to the evolution of this theme, grapes and juices were produced from vineyards in OP (n = 20) and CP (n = 20). All juices were elaborated using the same processing technology. Grape productivity was evaluated, and the classic characterization of juices was performed, followed by an in-depth characterization of mineral composition, pesticide residues, volatile compounds, phenolic compounds, and anthocyanins, as well as sensory analysis. In total, 101 dependent variables were monitored. From this set of variables, it was observed that grape productivity and the overall classic composition of juices from OP and CP systems are equivalent. Similarly, the mineral composition was equivalent, exception of the presence of a high concentration of Al in only one juice from the CP. As expected, pesticide occurrence was more frequent in CP juices (14/20), however, in all cases at much lower levels (1600 times lower or more) than the limits allowed by regulations. Residue occurrence also occurred in OP juices (2/20), which are not allowed by current regulations. In terms of volatile compounds profiles, 40 compounds were identified and quantified in OP juices, and 34 in CP juices. Regarding total phenolic compounds and total anthocyanins, the juices were equivalent. OP juices had a higher sensory preference. In conclusion, among101 variables evaluated, 75 indicate that the juices are equivalent. The 26 variables leading to technical differences are related to: 1) a higher frequency of residues in CP juices compared to OP juices; 2) a greater diversity of volatile compounds in OP juices; 3) differences in minor phenolic compounds and anthocyanins; and, 4) preference for OP juices.

SEM Image Processing Assisted by Deep Learning to Quantify Mesoporous γ-Alumina Spatial Heterogeneity and Its Predicted Impact on Mass Transfer.

The pore network architecture of porous heterogeneous catalyst supports has a significant effect on the kinetics of mass transfer occurring within them. Therefore, characterizing and understanding structure-transport relationships is essential to guide new designs of heterogeneous catalysts with higher activity and selectivity and superior resistance to deactivation. This study combines classical characterization via N2 adsorption and desorption and mercury porosimetry with advanced scanning electron microscopy (SEM) imaging and processing approaches to quantify the spatial heterogeneity of γ-alumina (γ-Al2O3), a catalyst support of great industrial relevance. Based on this, a model is proposed for the spatial organization of γ-Al2O3, containing alumina inclusions of different porosities with respect to the alumina matrix. Using original, advanced SEM image analysis techniques, including deep learning semantic segmentation and porosity measurement under gray-level calibration, the inclusion volume fraction and interphase porosity difference were identified and quantified as the key parameters that served as input for effective tortuosity factor predictions using effective medium theory (EMT)-based models. For the studied aluminas, spatial porosity heterogeneity impact on the effective tortuosity factor was found to be negligible, yet it was proven to become significant for an inclusion content of at least 30% and an interphase porosity difference of over 20%. The proposed methodology based on machine-learning-supported image analysis, in conjunction with other analytical techniques, is a general platform that should have a broader impact on porous materials characterization.

Printing, Characterizing, and Assessing Transparent 3D Printed Lenses for Optical Imaging

AbstractHigh‐quality lens production has involved subtractive manufacturing methods for centuries. These methods demand specialist equipment and expertise that often render custom high‐grade glass optics inaccessible. A low‐cost, accessible, and reproducible method is developed to manufacture high‐quality three dimensional (3D) printed lenses using consumer‐grade technology. Various planoconvex lenses are produced using a consumer‐grade 3D printer and low‐cost spin coating setup, and printed lenses are compared to commercial glass counterparts. A range of mechanical and optical methods are introduced to determine the surface quality and curvature of 3D printed lenses. Amongst others, high‐resolution interference reflection microscopy methods are used to reconstruct the convex surface of printed lenses and quantify their radius of curvature. The optical throughput and performance of 3D printed lenses are assessed using optical transmissivity measurements and classical beam characterization methods. It is determined that 3D printed lenses have comparable curvature and performance to commercial glass lenses. Finally, the application of 3D printed lenses is demonstrated for brightfield transmission microscopy, resolving sub‐cellular structures over a 2.3 mm field‐of‐view. The high reproducibility and comparable performance of 3D printed lenses present great opportunities for additive manufacturing of bespoke optics for low‐cost rapid prototyping and improved accessibility to high‐quality optics in low‐resource settings.

From words to pictures: Row-column combinations and Chomsky-Schützenberger theorem

The row-column combination RCC maps two (word) languages over the same alphabet onto the set of rectangular arrays, i.e., pictures, such that each row/column is a word of the first/second language. The resulting array is thus a crossword of the component words. Depending on the family of the components, different picture (2D) language families are obtained: e.g., the well-known tiling-system recognizable languages are the alphabetic projection of the crossword of local (regular) languages. We investigate the effect of the RCC operation especially when the components are context-free, also with application of an alphabetic projection. The resulting 2D families are compared with others defined in the past. The classical characterization of context-free languages, known as Chomsky-Schützenberger theorem, is extended to the crosswords in this way: the projection of a context-free crossword is equivalent to the projection of the intersection of a 2D Dyck language and the crossword of strictly locally testable language. The definition of 2D Dyck language relies on a new more flexible so-called Cartesian RCC operation on Dyck languages. The proof involves the version of the Chomsky-Schützenberger theorem that is non-erasing and uses a grammar-independent alphabet.

Attack semantics and collective attacks revisited

In the current paper we re-examine the concepts of attack semantics and collective attacks in abstract argumentation, and examine how these concepts interact with each other. For this, we systematically map the space of possibilities. Starting with standard argumentation frameworks (which consist of a directed graph with nodes and arrows) we briefly state both node semantics and arrow semantics (the latter a.k.a. attack semantics) in both their extensions-based form and labellings-based form. We then proceed with SETAFs (which consist of a directed hypergraph of nodes and arrows, to take into account the notion of collective attacks) and state both node semantics and arrow semantics, in both their extensions-based and labellings-based form. We then show equivalence between the extensions-based and labellings-based form, for node semantics and arrow semantics of AFs, as well as for node semantics and arrow semantics of SETAFs. Moreover, we show equivalence between node semantics and arrow semantics for AFs, and equivalence between node semantics and arrow semantics for SETAFs (with the notable exception of semi-stable). We also provide a novel way of converting a SETAF to an AF such that semantics are preserved, without the use of any “meta arguments”. Although the main part of our work is on the level of abstract argumentation, we do provide an application of our theory on the instantiated level. More specifically, we show that the classical characterisation of Assumption-Based Argumentation (ABA) can be seen as an instantiation based on a SETAF, whereas the contemporary characterisation of ABA can be seen as an instantiation based on a standard AF. Our theory of how to convert a SETAF to an AF can then be used to account for both the similarities and the differences between the classical and contemporary characterisations of ABA. Most prominently, our theory is able to explain the semantic mismatch for semi-stable semantics that arises in the ABA instantiation process.

Valuative dimension, constructive points of view

There are several classical characterisations of the valuative dimension of a commutative ring. Constructive versions of this dimension have been given and proven to be equivalent to the classical notion within classical mathematics, and they can be used for the usual examples of commutative rings. To the contrary of the classical versions, the constructive versions have a clear computational content. This paper investigates the computational relationship between three possible constructive definitions of the valuative dimension of a commutative ring. In doing so, it proves these constructive versions to be equivalent within constructive mathematics.

A Characterization of Simultaneous Optimization, Majorization, and (Bi-)Submodular Polyhedra

Motivated by resource allocation problems (RAPs) in power management applications, we investigate the existence of solutions to optimization problems that simultaneously minimize the class of Schur-convex functions, also called least-majorized elements. For this, we introduce a generalization of majorization and least-majorized elements, called (a, b)-majorization and least (a, b)-majorized elements, and characterize the feasible sets of problems that have such elements in terms of base and (bi-)submodular polyhedra. Hereby, we also obtain new characterizations of these polyhedra that extend classical characterizations in terms of optimal greedy algorithms from the 1970s. We discuss the implications of our results for RAPs in power management applications and derive a new characterization of convex cooperative games and new properties of optimal estimators of specific regularized regression problems. In general, our results highlight the combinatorial nature of simultaneously optimizing solutions and provide a theoretical explanation for why such solutions generally do not exist.

A New Notion of Fuzzy Function Ideal Convergence

P.M. Pu and Y.M. Liu extended Moore-Smith’s convergence of nets to fuzzy topology and Y.M. Liu provided analogous results to J. Kelley’s classical characterization theorem of net convergence by introducing the notion of fuzzy convergence classes. In a previous paper, the authors of this study provided modified versions of this characterization by using an alternative notion of convergence of fuzzy nets, introduced by B.M.U. Afsan, named fuzzy net ideal convergence. Our main scope here is to generalize and simplify the preceding results. Specifically, we insert the concept of a fuzzy function ideal convergence class, L, on a non-empty set, X, consisting of triads (f,e,I), where f is a function from a non-empty set, D, to the set FP(X) of fuzzy points in X, which we call fuzzy function, e∈FP(X), and I is a proper ideal on D, and we provide necessary and sufficient conditions to establish the existence of a unique fuzzy topology, δ, on X, such that (f,e,I)∈L iff fI-converges to e, relative to the fuzzy topology δ.

BIOCHEMICAL EVALUATION OF INDUS VIVA I PULSE NATURAL AYURVEDIC SYRUP AND IT’S IN SILICO – INTERACTION ANALYSIS

Objectives: In developing countries like India, diabetes mellitus and human bone cancer are progressively increasing which is global encumbrance. The objective of the study is to find out the phytoconstituents of Indus Viva I Pulse health drink extract that has undergone classical chemical characterization, molecular docking, anti-diabetic, anticancer, antibacterial and antifungal studies used as traditional and complementary medicine. The study aimed to evaluate the Gas Chromatography–Mass Spectrometry (GC-MS), High-Performance Liquid Chromatography (HPLC), Liquid Chromatography–High Resolution Mass Spectrometry (LC-HRMS), anticancer, antidiabetic and spectral studies that are used to disclose phytochemicals and their medicinal properties. Methods: Infrared (IR), Ultraviolet (UV), 1H-NMR spectroscopic methods, GC-MS, HPLC and LC-HRMS instrumental detections were employed. Molecular docking, anti-diabetic, anticancer, antibacterial and antifungal studies were carried out using AutoDock 4.2.6. software program, α- Amylase method, Mosmann and Disk diffusion method respectively. Results: GC-MS and HPLC chromatogram of methanol extracts exhibited 12 and 6 peaks, respectively, confirming the presence of 12 phytoconstituents in Indus Viva I Pulse health drink (1I–12I). The total phenol and flavonoid content found in the extracted sample of Indus Viva I Pulse health drink were 0.16 and 0.36 mg/mL, respectively. It is a polyherbal formulation of brown-colored liquid of the UV spectrum in methanol is characteristic of an aromatic compound with λ max of 319 and 412 nm. IR spectrum gave peaks at 3,457, 2,922, 2,857, 2,121, 1,641, 1,055, 1,033 and 621 cm-1 indicating the presence of an alcoholic, alkyl, aldehyde or ketone, alkyne, carbonyl, anhydride and methyl group, respectively. Liquid Chromatography- High Resolution Mass Spectrometry (LC-HRMS) study gave these molecular weights (m/z): 1134. 7017, 1150.6475 and 1168.6797. Aromatic characteristics were confirmed through UV, IR, 1H-NMR, 13C-NMR and LC-HRMS spectral studies. 1H-NMR study indicates the presence of aromatic protons and methyl protons. Aqueous extract of Indus Viva I Pulse health drink was tested for Cytotoxicity Assay of human bone cancer (MG-63) cell lines and ptyalin prevent characters that exhibited a valid inhibitory value of 90.87% in 10 μg/mL for MG-63 and value of 74.41% in 500 μg/mL for alpha-amylase which is comparatively more efficient than the available standard drug. Cytotoxicity assay for human bone cancer (MG-63) cell lines and alpha-amylase both showed the inhibitory activity of IC50 68.95 and IC50 36.18 μg/mL, respectively. Conclusion: Based on the result of this research, it can be proposed that Indus Viva I Pulse health drink may serve as a potential remedy for human bone cancer (MG-63) cell line and that alpha-amylase inhibitory activity is proportional to the dose.

Topological Ordered Rings and Measures

Given a ring endowed with a ring order, we provide sufficient conditions for the order topology induced by the ring order to become a ring topology (analogous results for module orders are consequently derived). Finally, the notions of Radon and regular measures are transported to the scope of module-valued measures through module orders. Classical characterizations of these measures are obtained as well as the hereditariness of regularity for conditional ring-valued measures.

Match-reinforcement learning with time frequency selection for bearing fault diagnosis

Rolling bearings play a vital role in ensuring the safe operation of rotating machinery. However, in many application scenarios, the collected data has a low signal-to-noise ratio and the samples with faults are rare, which affects the generalization capability of the model, making it impossible to achieve accurate diagnosis. To solve this problem, the selection of time-frequency (TF) maps was considered in this paper through reinforcement learning. The TF maps are built by four classical TF characterization methods such as short-time Fourier transform and synchro squeezing transform. And the match-reinforcement learning time frequency selection (MRLTFS) fault diagnosis model is proposed to extract the fault-related features. Experiments show that the proposed MRLTFS method is superior to existing methods in robustness, generalization and feature selection capability.

Moving toward a better understanding of the model bacterial predator Bdellovibrio bacteriovorus.

The bacterial predator Bdellovibrio bacteriovorus is a model for the wider phenomenon of bacteria:bacteria predation, and the specialization required to achieve a lifestyle dependent on prey consumption. Bdellovibrio bacteriovorus is able to recognize, enter and ultimately consume fellow Gram-negative bacteria, killing these prey from within their periplasmic space, and lysing the host at the end of the cycle. The classic phenotype-driven characterization (and observation of predation) has benefitted from an increased focus on molecular mechanisms and fluorescence microscopy and tomography, revealing new features of several of the lifecycle stages. Herein we summarize a selection of these advances and describe likely areas for exploration that will push the field toward a more complete understanding of this fascinating 'two-cell' system.