Basic Properties Research Articles

High-level visual processing in the lateral geniculate nucleus revealed using goal-driven deep learning.

High-level visual processing in the lateral geniculate nucleus revealed using goal-driven deep learning.

Electrophysiological comparison of left versus right stellate ganglia neurons.

Electrophysiological comparison of left versus right stellate ganglia neurons.

Estimating hearing thresholds in rodents using the parallel auditory brainstem response.

ABR thresholds are traditionally measured for one sound frequency at a time, but a new approach, the parallel ABR (pABR), has recently been developed. The pABR allows thresholds to be measured for multiple frequencies simultaneously and has been shown to be more efficient than the traditional approach for humans. This study explored the applicability of the pABR approach for threshold measurement in gerbils. The basic properties of the estimated ABRs were analyzed and the dependence of the signal-to-noise ratio (SNR) and the reliability of measured thresholds on the number of trials was assessed. For a subset of ears, direct comparisons were made between the pABR and the traditional approach. The results suggest that the pABR approach can be more efficient for rodents than the traditional ABR approach, particularly for threshold estimation. To facilitate its use, software toolboxes in Matlab and Python are provided for the design of the pABR sounds and the analysis of recordings.

Generalized Eddington–Finkelstein coordinates and exact Vaidya-type solutions in Weyl conformal gravity

We study Vaidya-type solutions in Weyl conformal gravity (WCG) using Eddington–Finkelstein-like coordinates. Our considerations focus on spherical as well as hyperbolic and planar symmetries. In particular, we find all vacuum dynamical solutions for the aforementioned symmetries. These are, in contrast to general relativity, structurally quite non-trivial. We provide a thorough analysis of their basic properties, such as, relation to other known WCG solutions, algebraic types, singularities, horizons, and symmetries. In the same vein, we also derive, classify, and discuss non-vacuum solutions with the Coulombic electric field and null dust. Other salient issues, such as the gauge equivalence of WCG solutions to Einstein spaces and the role of the Birkhoff–Riegert theorem, are also addressed.

"Aspects and Applications of p-Integer-Based Meyer-König-Zeller Durrmeyer Operators"

Within this paper, our study presents a novel class of Meyer-König-Zeller Durrmeyer (MKZD) type operators integrated with the concept of ppp-integers, which adds a new dimension to the approximation process in the context of positive linear operators. The introduction of ppp-integers in the construction of MKZD operators allows greater flexibility and adaptability in handling different functional behaviors, particularly in scenarios requiring finer approximation properties. This generalization opens up new avenues for theoretical development and practical applications in numerical analysis and approximation theory. We rigorously define the newly constructed operators and investigate their basic properties, including linearity, positivity, and preservation of certain test functions. The core objective of this work is to analyze the rate of convergence of these ppp-MKZD operators, especially in terms of the modulus of continuity and Peetre’s K-functional. Emphasis is placed on the confluence behavior of the operators — that is, how effectively they approximate continuous functions as the parameters approach their limiting values. We derive upper bounds for the approximation error and support our theoretical results with illustrative examples. Additionally, the study highlights how the involvement of ppp-integers enhances the convergence behavior of the operators under various function spaces, thereby demonstrating their applicability in solving practical problems in computational mathematics. This work not only deepens the understanding of MKZD-type operators but also offers a foundation for future investigations into more generalized operator forms and their applications. The proposed operators could be particularly useful in approximation scenarios involving functions with varying smoothness and bounded variation.

Accretion structures around Kerr black holes in a swirling background

In this paper, we investigate thick accretion structures around a Kerr black hole in a swirling background, that is, a rotating black hole immersed in a rotating background. This is a novel solution characterized by the black hole mass in addition to two distinct rotational parameters, the Kerr parameter a, which identifies the rotation of the black hole, and the swirling parameter j, which describes the background rotation. The swirling background is characterized by an odd Z2 symmetry, where the northern and southern hemispheres rotate in opposite directions. The rotation of the black hole embedded into this swirling background leads to non-trivial spin–spin interactions with the background rotation. The spacetime properties in the vicinity of the black hole are significantly influenced by this spin–spin interaction. In order to study the influence on the basic properties of this spacetime, we analyze circular orbits and geometrically thick disks for different spacetime solutions, which are classified by the black hole and swirling spins. We identify stabilizing effects on prograde circular orbits and destabilizing effects on retrograde circular orbits, which originate from the spin–spin interaction and depend mainly on the Kerr rotation. Furthermore, we discover the emergence of static orbits, which appears due to the background rotation. The symmetry breaking of the spacetime rotation with regard to the equatorial plane highly influences the spatial distribution of circular orbits. This asymmetry causes a concave (convex) distribution of the prograde (retrograde) circular orbits and accordingly, bowl-like deformations of the accretion disk solutions. Moreover, due to the destabilizing effect of the swirling rotation, an outer marginally stable orbit appears, which heavily limits the range of the parameter space in which disk solutions can exist. Due to the possibility of an outer and inner disk cusp, different types of disk solutions are possible. We classify the different types of disk solutions, which differ from each other by the properties of their cusps. Four different scenarios can be identified in which different accretion dynamics could arise.

Explainability of Protein Deep Learning Models.

Protein embeddings are the new main source of information about proteins, producing state-of-the-art solutions to many problems, including protein interaction prediction, a fundamental issue in proteomics. Understanding the embeddings and what causes the interactions is very important, as these models lack transparency due to their black-box nature. In the first study of its kind, we investigate the inner workings of these models using XAI (explainable AI) approaches. We perform extensive testing (3.3 TB of total data) involving nine of the best-known XAI methods on two problems: (i) the prediction of protein interaction sites using the current top method, Seq-InSite, and (ii) the production of protein embedding vectors using three methods, ProtBERT, ProtT5, and Ankh. The results are evaluated in terms of their ability to correlate with six basic amino acid properties-aromaticity, acidity/basicity, hydrophobicity, molecular mass, van der Waals volume, and dipole moment-as well as the propensity for interaction with other proteins, the impact of distant residues, and the infidelity scores of the XAI methods. The results are unexpected. Some XAI methods are much better than others at discovering essential information. Simple methods can be as good as advanced ones. Different protein embedding vectors can capture distinct properties, indicating significant room for improvement in embedding quality.

Assessing Soil Degradation: A Comprehensive Study Using Soil Degradation Index (SDI) in Godrahav Watershed

Soil degradation is an important problem for watersheds that contain agricultural and natural areas within their border. This study was conducted to assess soil degradation using soil degradation index (SDI). The watershed was divided into transects at 500m intervals in the north-south and the east-west directions. Except for the hard-to-reach points because of topography, disturbed and undisturbed soil samples were taken from 138 sample points at the intersections of the transects. The SDI was calculated using the measured soil parameters including particle size distribution, aggregate stability, aggregation rate, mean weight diameter, dispersion rate, bulk density, porosity, field capacity, wilting point, organic matter content, pH and electrical conductivity. The spatial distribution patterns of these parameters were defined using geostatistical analyses. Slope, elevation, aspect and land use type of the watershed were also mapped using the Geographic Information System (GIS) technique. The results of the study showed that soil degradation can be quantified using an index value, and that basic soil properties can serve as parameters for this index. These parameters affect index values with different weighting, and these weighting values can be calculated by correlation analysis. Moreover, according to the distribution maps, SDI showed spatial variability due to the land use, altitude, and aspect, but it did not vary regularly due to the slope. Based on the findings, it is recommended to implement land use-specific soil management strategies across the watershed. Regular SDI-based monitoring and geospatial analysis can support early detection of degradation and guide sustainable land use planning.

The m-CCE Inverse in Minkowski Space and Its Applications

In this paper, we introduce a new generalized inverse called m-CCE inverse which presents a generalization of the CCE inverse in Minkowski space by using the m-core-EP decomposition and the Minkowski inverse. We first show the existence and the uniqueness of the generalized inverse. Then, a number of basic properties and diverse characterizations are derived for the m-CCE inverse as well as its limit and integral expressions. Additionally, applications of the m-CCE inverse are given in solving a system of linear equations. Applying the generalized inverse, we introduce a binary relation based on the m-CCE inverse.

Discharge modes of self-pulsing discharges in argon at atmospheric pressure

Abstract Self-pulsing discharges are an intriguing method to generate non-thermal plasma using DC high voltages. However, the sophisticated interaction between the electrical circuit and the actual plasma characteristics is still not well explored. Therefore, this study presents a modelling study on self-pulsing discharges in pure argon at atmospheric pressure in a 1.5 mm gas gap. A time-resolved, one-dimensional fluid-Poisson model coupled to an equivalent circuit with variable parameters is applied to analyse the impact of circuit parameters like internal resistance and applied negative DC high voltage on basic discharge properties. This includes the analysis of the spatio-temporal development of the densities of charge carriers and excited species, the electric field and ionisation rates in combination with the synchronised electrical quantities like discharge current, discharge voltage and self-pulsing frequency. In particular, three distinct periodic self-pulsing modes of the discharge are found, i.e., a transient spark, a transient glow and a modulated DC glow mode. The transition between these modes is related to different recharging times of the circuit capacitance for different external resistances in series with the gas gap. It leads to changes in the predominance of the different ionisation processes together with the crucial impact of pre-ionisation on the discharge inception. These insights provide essential knowledge on tunability within a selection of self-pulsing DC discharge modes for generating non-thermal plasma with desired effects, e.g. for material processing and environmental or medical applications.

Application of high-resolution ultrasound / photoacoustic imaging for medicine and biology

Abstract Because the frequency is inversely proportional to the wavelength or beamwidth of the ultrasound, very high-resolution imaging is available by high frequency ultrasound. The application of ultrasound microscopy in medicine and biology has three main purposes. The first is rapid diagnosis, the second is to collect the basic acoustic properties necessary to understand clinical ultrasound imaging and the third is to gather information about the biomechanics of the tissue.
In photoacoustic imaging, very short pulsed light emitted to the material evoked thermal expansion to generate photoacoustic signal. A number of photoacoustic systems have been devised and put into practical use to efficiently irradiate light and receive photoacoustic signal. Those systems can be broadly classified into acoustical resolution photoacoustic microscopy (AR-PAM), optical resolution photoacoustic microscopy (OR-PAM), optical resolution photoacoustic microscopy (AR-PAM) and optical acoustic microscopy (PAM). There is a need for more compact systems with stable prices for clinical applications.

A novel approach to explore common prime divisor graphs and their degree based topological descriptor.

For the construction of a common prime divisor graph, we consider an integer [Formula: see text] with its prime factorization, where [Formula: see text] are distinct primes and [Formula: see text] are fixed positive integers. Every divisor of the integer [Formula: see text] has the form [Formula: see text], with [Formula: see text]. There are [Formula: see text] distinct divisors of integer [Formula: see text]. Let [Formula: see text] be the collection of all positive divisors of [Formula: see text] other than integer 1. Then we can define a simple graph on the set of divisors [Formula: see text] of [Formula: see text], called a common prime divisor graph [Formula: see text] with [Formula: see text] as the vertex set, and we insert an edge between two distinct divisors x and y of [Formula: see text] if the [Formula: see text]. In this article, we will introduce and discuss some basic properties of common prime divisor graphs and we will compute some indices of symmetries associated with a class of such graphs. This study will open a new domain of graphs to investigate their invariant and to explore such indices on the different classes of common prime divisor graphs.

Nearness Modules

Abstract Near set theory, a generalization of rough set theory, constructs the universal set based on the properties of objects and the available information about these objects. Considering this fundamental property, the main aim of this paper is to introduce the concept of a nearness R-module, an algebraic structure containing objects with multiple properties, defined on a nearness ring R, based on near set theory. Additionally, we define nearness R-module homomorphisms and examine their basic properties.

Floodplain Forest Soil Nematode Communities as Influenced by Non-Native Acer negundo L. Invasion

Invasive plants can significantly alter the composition and functioning of soil ecosystems, which in turn affects soil fauna such as microorganisms; mesofauna including mites, springtails, nematodes, and insects; and other invertebrates. We used clusters of three different tree species to investigate how they affect the composition of belowground soil nematode communities. The clusters included Acer negundo (L.) (an invasive, non-native species), Fraxinus excelsior (L.), and Alnus glutinosa (Gaertn.) (both as native representatives) in floodplain forest habitats of the Morava River. We investigated the families, genera, trophic groups, and functional guilds of soil nematodes in each tree cluster to assess the usefulness of nematodes as indicators of the impact of alien tree species on native communities. The study was complemented by measuring basic soil physico-chemical properties. The data show that nematode communities were not sensitive to A. negundo invasion, as clusters of invasive trees had similar nematode abundance, genus richness, diversity, family and genus composition, and trophic structure compared to species-specific clusters of two native tree species. A cumulative total of 96 nematode genera, belonging to 52 families, were recorded in the investigated floodplain forest sites. The most abundant families across all clusters were Alaimidae, Cephalobidae, Hoplolaimidae, and Rhabditidae for all tree clusters. Among the genera, Helicotylenchus, Pratylenchus, Paratylenchus (as obligate plant parasites), Filenchus, and Malenchus (as facultative plant parasites), as well as Acrobeloides, Eucephalobus, Plectus, and Rhabditis (as bacterivores), were the most dominant taxa. The measured soil properties did not differ significantly among tree species (p < 0.05). Nevertheless, redundancy analysis identified a significant correlation between soil moisture content and abundance of several nematode genera, nematode trophic groups, and functional guilds. The results indicate that the presence of invasive ash-leaved maple trees in the studied floodplain forests had no adverse effect on the diversity and functional structure of soil nematode communities. This study offers initial insights into nematode communities in Acer negundo invaded habitats, but further studies are needed to verify these findings.

Conductive Nanomaterials in Printed Electronics

AbstractPrinted electronics is based on the application of 2D and 3D printing technologies to fabricate electronic devices. To fabricate the printed electronic 2D and 3D devices with the required performance, it is necessary to properly select and tailor the conductive inks, which are often composed of nanomaterials, The main nanomaterials in conductive inks for 2D and 3D printed electronics contain conductive nanomaterials such as metal nanoparticles (NPs) and nanowires and carbon based nanomaterials: carbon black, graphene sheets, and carbon nanotubes (CNTs). All these materials were successfully applied for the fabrication of various electronic devices such as electrical circuits, transparent electrodes, flexible thin film transistors, RFID antennas, photovoltaic devices, and flexible touch panels. In this paper, we focus on the basic properties of these nanomaterials, in view of their application in conductive inks, on obtaining conductive patterns by 2D and 3D printing, and on various methods of post‐printing treatment. In the last section, a perspective on future needs and applications will be presented, including emerging technologies.

A Comparative Analysis of Machine Learning and Pedotransfer Functions Under Varying Data Availability in Two Greek Regions

The current study evaluates the performance of pedotransfer functions (PTFs) and machine learning (ML) algorithms in predicting the soil bulk density (BD) across two distinct regions in Greece—Kozani and Veroia—using both limited and extended sets of soil parameters. The results reveal significant regional differences in prediction accuracy. In the full dataset scenario, Veroia consistently exhibits superior predictive performance across all models (PDF RMSE: 0.104, ML RMSE: 0.095) compared to Kozani (PDF RMSE: 0.133, ML RMSE: 0.122). Generally, ML models outperform PTFs in terms of the RMSE and MAE in both regions with the full dataset. However, PTFs occasionally demonstrate higher R2 values (Veroia PTF R2: 0.35 vs. ML R2: 0.28), suggesting a better explanation of the overall variance despite larger errors. Notably, the effectiveness of ML appears to be affected by the availability of data. In Kozani, when restricted to basic soil properties, ML’s performance (RMSE: 0.129, R2: 0.16) becomes similar to that of PTFs (RMSE: 0.133, R2: 0.16). However, incorporating the full dataset substantially enhances ML’s predictive power (RMSE: 0.122, R2: 0.26). Conversely, in Veroia, the inclusion of more variables paradoxically results in a slight decline in ML performance (ML_min RMSE: 0.093, R2: 0.31 vs. ML RMSE: 0.095, R2: 0.28). These contrasting results emphasize the need for context-specific modeling strategies, careful feature selection, and caution against the assumption that more data or complexity inherently improves the predictive performance.

Two‐Dimensional Phosphorene for Solution‐Processed Thin‐Film Solar Cells

Two‐dimensional phosphorene (2D phosphorene) exhibits significant advantages in the field of solar cells due to its tunable bandgap, high carrier mobility, and high light absorption. They can serve as electrodes, hole transport layers (HTLs), electron transport layers (ETLs), and functional additives in the active layer, significantly enhancing the optoelectronic performance of devices. This paper reviews the basic properties and provides a comprehensive summary of the synthesis methods of 2D phosphorene. Furthermore, the impact of 2D phosphorene as an electrode, charge transport layer, and additive in the active layer of solution‐processed thin‐film solar cells is highlighted. Although the application of phosphorene in solar cells has achieved initial success, its stability issues and challenges of large‐scale preparation still need to be further addressed. It is believed that 2D phosphorene is anticipated to have a significant impact on the commercial application of high‐efficiency solar cells.

Enhancing the Thermostability of Phospholipase C by Structural-Based Proline Incorporation to Improve Its Degumming Performance.

Thermostability can be improved by introducing prolines into targeted sites, enhancing enzyme performance in specific reactions. In our present study, a novel fungal phospholipase C derived from Talaromyces islandicus (TiPLC) was first heterologously expressed in Pichia pastoris and biochemically characterized. Given the poor thermal stability of TiPLC, a structure-based proline incorporation strategy was used to enhance its thermostability further. Two single-site (E92P and A375P) mutants were selected from seven designs, exhibiting improved stability while retaining wild-type's basic properties (optimum reaction pH and temperature). Compared to the wild-type, the t1/2 of E92P and A375P under 40°C extended by 1.62 and 1.27 times, respectively. Meanwhile, the E92P and A375P mutants exhibited a 20% increase in activity using p-NPPC as substrate. Moreover, double mutant E92P-A375P exhibited 2.43 times enhancement compared to the wild-type. Results of the oil degumming experiment further confirmed that the double mutant significantly improved the performance of TiPLC, with a reduction in residual phosphorus to 78ppm, while for the wild-type, the residual phosphorus was 131 ppm under the same reaction. Molecular simulations indicated that proline incorporation into 92 and 375 sites significantly improved the rigidity of partial flexible regions, thus contributing to the increased thermostability.

Patient-Specific Highly Realistic Spine Surgery Phantom Trainers.

A realistic phantom created from a three-dimensional (3D)-reconstructed digital patient model would enable researchers to investigate the morphological aspects of the pathological spine, thereby resolving the issue of scarce cadaveric specimens. We designed a patient-specific, human-like, reliable, and cost-effective prototype of the examined pathological spine through open-source editing software analysis, a desktop 3D printer, and alginate material. We aimed to validate that the major surgical steps and anatomy replicated the real surgery as it would be conducted in actual patients.We cover the fundamental principles and procedures involved in 3D printing, from spine imaging to phantom manufacturing. Three representative simulation cases were included in the study. All phantoms were sequentially evaluated by surgeons for fidelity. Following each surgery, participants were given a survey that included 20 questions regarding the fidelity of the training phantom.We validated this simulation model by analyzing neurosurgeons' performance on the phantom trainer. Based on a 20-item survey to test content validity and reliability, there was little variation among participants' ratings, and the feedback was consistently positive. The gross appearance of the phantom was analogous to the cadaveric specimen and the phantoms demonstrated an excellent ability to imitate the intraoperative condition. The plastic material expenditure ranged from 170 to 470 g, and the alginate expenditure was 450 g. The total cost of acrylonitrile butadiene styrene (ABS) varied from $5.1 to $17.6 ($0.03 per gram of ABS), whereas the total cost of alginate was $14.3. The average cost of our phantoms was approximately $25.7, and the 3D printer used in this study costs approximately $200.The basic properties of this phantom were similar to cadaveric tissue during manipulation. We believe our phantoms have the potential to improve skills and minimize risk for patients when integrated into trainee education.

Synthetic spectra from particle-in-cell simulations of relativistic jets containing an initial toroidal magnetic field

ABSTRACT The properties of relativistic jets, their interaction with the environment, and their emission of radiation can be self-consistently studied by using collisionless particle-in-cell (PIC) numerical simulations. Using three-dimensional relativistic PIC simulations, we present the first self-consistently calculated synthetic spectra of head-on and off-axis emission from electrons accelerated in cylindrical relativistic plasma jets containing an initial toroidal magnetic field. The jet particles are initially accelerated during the linear stage of growing plasma instabilities, which are the Weibel instability (WI), kinetic Kelvin–Helmholtz instability (kKHI), and mushroom instability (MI). In the non-linear stage, these instabilities are dissipated and generate turbulent magnetic fields, which accelerate particles further. We calculate the synthetic spectra by tracing a large number of jet electrons in the non-linear stage, near the jet head where the magnetic fields are turbulent. Our results show the basic properties of jitter-like radiation emitted by relativistic electrons when they travel through a magnetized plasma with the plasma waves driven by kinetic instabilities (WI, kKHI, and MI) growing into the non-linear regime. At low frequencies, the slope of the spectrum is $\sim 0.94$, which is similar to that of the jitter radiation, rather than that of the classical synchrotron radiation, which is $\sim 1/3$. Although we start with a weak magnetized plasma, the plasma magnetization increases locally in regions where the magnetic field becomes stronger due to kinetic instabilities. The results of this study may be relevant for probing photon emission from low energies up to, at least, low energies in the X-ray domain in active galactic nucleus/blazar and gamma-ray burst jets, as the peak frequency of synthetic spectra increases as the Lorentz factor of the jet increases from 15 to 100.