Multiple Structures Research Articles

Firing patterns transitions and resonance effects of the extended Hindmarsh-Rose neural model with Gaussian noise and transcranial magneto-acousto-electrical stimulation

Considering the fact that the typical three-variable Hindmarsh-Rose(HR) neural model has limitations in describing the complex non-linear features and precise behavior patterns of neuron, the influences of transcranial magneto-acousto-electrical stimulation(TMAES) on firing patterns and resonance effects are analyzed based on an extended HR neural model in this paper. Obtained results show that TMAES can induce transitions in the firing patterns of extended HR neuron, such as spiking and multi-periodic bursting state, etc If appropriate parameters are selected, the multimodal discharge modes can also be observed. Coefficient of variation is calculated to further investigate the effect of TMAES and Gaussian white noise on the firing rhythm of extended HR neuron, and relevant results indicate that TMAES can induce coherent resonance phenomena in HR neuronal systems similar to the effects of Gaussian white noise, which reveals a new mechanism of coherent resonance induced by TMAES. Further more, TMAES can also regulate coefficient of variation to exhibit anti-coherent resonance and multiple anti-coherent resonance structures, exhibiting richer regulatory functions than Gaussian white noise in regulating neuronal firing rhythm. This study seeks to enhance the understanding of the processes that influence the firing patterns and coherence degree of neuron under TMAES in neuroses or psychoses.

Misorientations across interfaces in spark plasma–sintered WC–Co cemented carbides

AbstractThis interdisciplinary work concerns misorientations across various interfaces in spark plasma–sintered (SPSed) WC–Co cemented carbides, as well as how these misorientations affect the intergranular fracture. The whole boundaries in cemented carbides were divided according to the phases on the two sides of the boundary plane, and carbide/carbide grain boundaries were further divided according to the misorientation across the boundary plane. Stereological statistics and five‐parameter analysis were comprehensively performed on the concerned boundary types. For Σ2 carbide/carbide boundaries, multiple boundary structures are observed. How Σ2 twist inhibits intergranular fracture and how such boundary structure is formed are analyzed. For random carbide/carbide boundaries, the habit planes that they are terminated by are calibrated, and their responses to intergranular fracture are examined according to their energy anisotropy. For WC/α‐cobalt and WC/β‐cobalt phase boundaries, misorientations across these boundary planes and the corresponding crack propagation routines are illustrated. On these bases, approaches to improve the fracture strength of SPSed cemented carbides are suggested.

Intersectional Identity and Representative Politics

Representation scholarship has drawn from intersectionality theory 0to examine how systemic structures of oppression and privilege have created social groups with distinct political needs. Derived from Black feminist theory that recognizes that identities are mutually constitutive and interconnected, intersectionality research is rooted in the lived experiences of marginalized groups who call attention to social (in)justice. Empirical scholarship building on the insights of Black feminist theorists such as Collins and Bilge (2016), Hill Collins (1990), Crenshaw (1989; 1991), and King (1988) has constituted nothing less than a paradigm shift in the study of gender and politics. Nevertheless, there remain an array of opportunities to expand upon the potential for intersectional frameworks and methods, as well as pressing new questions concerning the operationalization of intersectionality itself. This Critical Perspectives section offers a moment to take stock of these developments and debates, as well as to highlight new pathways for scholarship committed to centering the margins and considering the nexus of multiple power structures that frame our political lives.

Lengthening Short Noses in Rhinoplasty.

Objective: Rhinoplasty aims to create a nose in harmony with an ideal face, help patients with specific aesthetic concerns, and improve the nose's function. So, learning all types of deformities and rhinoplasty procedures is essential to solving that particular problem. So, we aimed to point at a neglected nasal deformity to serve as a guide in short nose rhinoplasty. Methods: Hereditary factors usually determine the length of a nose, such as cephalo-caudal patterning. Nowadays, individuals who want a change on their nose neglect whether it suits their face. Therefore, a considerable change may cause a paradox and lead to losing the operated nose and face harmony. As a general rule, it should be remembered that short nose elongation sounds more complicated than reduction rhinoplasty. Indeed, multiple soft tissues, mucosa, and structures exist, and short noses may get fibrotic, thickened, and inflamed skin for various reasons. Results: Dorsal augmentation through autologous cartilage grafts or implants is often used in patients with short noses. This demands a primary focus on lengthening the short nasal base. The simplest method of lengthening the short nose is dorsal onlay or radix implants. Silicone implants with a reported non-negligible tendency of infection are no longer used. Autologous cartilage grafts can be harvested from the septum, auricular cartilage, or rib. In the case of short noses, the surgeon can remove the septum as a graft and increase the nasal dorsum or undertake dorsal augmentation through septal cartilage grafts. Conclusion: Dorsal augmentation through autologous cartilage grafts or implants remains valuable for patients with short noses. Surgeons can achieve the desired length and proportional rotation by employing various methods, such as dorsal onlay or radix implants, septal cartilage grafts, and careful tip rotation. Through skillful execution and a patient-centered approach, surgeons can help patients with short noses achieve improved facial harmony and self-confidence.

Large-scale annotation of biochemically relevant pockets and tunnels in cognate enzyme–ligand complexes

Tunnels in enzymes with buried active sites are key structural features allowing the entry of substrates and the release of products, thus contributing to the catalytic efficiency. Targeting the bottlenecks of protein tunnels is also a powerful protein engineering strategy. However, the identification of functional tunnels in multiple protein structures is a non-trivial task that can only be addressed computationally. We present a pipeline integrating automated structural analysis with an in-house machine-learning predictor for the annotation of protein pockets, followed by the calculation of the energetics of ligand transport via biochemically relevant tunnels. A thorough validation using eight distinct molecular systems revealed that CaverDock analysis of ligand un/binding is on par with time-consuming molecular dynamics simulations, but much faster. The optimized and validated pipeline was applied to annotate more than 17,000 cognate enzyme–ligand complexes. Analysis of ligand un/binding energetics indicates that the top priority tunnel has the most favourable energies in 75% of cases. Moreover, energy profiles of cognate ligands revealed that a simple geometry analysis can correctly identify tunnel bottlenecks only in 50% of cases. Our study provides essential information for the interpretation of results from tunnel calculation and energy profiling in mechanistic enzymology and protein engineering. We formulated several simple rules allowing identification of biochemically relevant tunnels based on the binding pockets, tunnel geometry, and ligand transport energy profiles.Scientific contributionsThe pipeline introduced in this work allows for the detailed analysis of a large set of protein–ligand complexes, focusing on transport pathways. We are introducing a novel predictor for determining the relevance of binding pockets for tunnel calculation. For the first time in the field, we present a high-throughput energetic analysis of ligand binding and unbinding, showing that approximate methods for these simulations can identify additional mutagenesis hotspots in enzymes compared to purely geometrical methods. The predictor is included in the supplementary material and can also be accessed at https://github.com/Faranehhad/Large-Scale-Pocket-Tunnel-Annotation.git. The tunnel data calculated in this study has been made publicly available as part of the ChannelsDB 2.0 database, accessible at https://channelsdb2.biodata.ceitec.cz/.

Be-dataHIVE: a base editing database

Base editing is an enhanced gene editing approach that enables the precise transformation of single nucleotides and has the potential to cure rare diseases. The design process of base editors is labour-intensive and outcomes are not easily predictable. For any clinical use, base editing has to be accurate and efficient. Thus, any bystander mutations have to be minimized. In recent years, computational models to predict base editing outcomes have been developed. However, the overall robustness and performance of those models is limited. One way to improve the performance is to train models on a diverse, feature-rich, and large dataset, which does not exist for the base editing field. Hence, we develop BE-dataHIVE, a mySQL database that covers over 460,000 gRNA target combinations. The current version of BE-dataHIVE consists of data from five studies and is enriched with melting temperatures and energy terms. Furthermore, multiple different data structures for machine learning were computed and are directly available. The database can be accessed via our website https://be-datahive.com/ or API and is therefore suitable for practitioners and machine learning researchers.

Strained GeSn laser with multiple fins structure based on SiN stress

Among the IV group materials, Germanium (Ge) stands out due to its unique bandgap structure, which can be engineered to achieve direct bandgap emission. This has important applications in the fabrication of efficient integrated light sources using IV group materials. In this paper, a strained GeSn laser with Multiple Fins structure based on SiN stress is proposed, through the Multi-fins structure, the biaxial tensile stress of about 0.7GPa is predicted to be uniformly introduced into the GeSn material in the active region and the laser is predicted to exhibit a threshold current density of 180 kA cm−2 and an emission peak wavelength at 2429 nm. The design presented in this paper provides an effective solution for silicon-based integrated light source.

Delayed Pontomesencephalic and Cervical Cord Venous Drainage Followed by Contralateral Carotid-Cavernous Fistula after Craniofacial Fractures: A Case Report.

A 24-year-old male was admitted with progressive cervical hypesthesia, tetraparesis, dyspnea, and a history of craniofacial fracture. Spinal magnetic resonance imaging (MRI) showed brainstem edema extending to the thoracic spine with multiple prominent perimedullary vascular structures. Cerebral digital-substraction angiography revealed Barrow type A carotid-cavernous fistula. Total occlusion with preservation of internal carotid artery flow was achieved using 1 detachable balloon and 6 coils. Postoperatively, immediate respiratory recovery, gradual extremities strength improvement, and right abducens nerve palsy were found. One month follow-up cervical MRI showed good recovery of spinal cord edema and perimedullary veins.

Feature analysis of 5G traffic data based on visibility graph

IntroductionAs 5G networks become widespread and their application scenarios expand, massive amounts of traffic data are continuously generated. Properly analyzing this data is crucial for enhancing 5G services.MethodsThis paper uses the visibility graph method to convert 5G traffic data into a visibility graph network, conducting a feature analysis of the 5G traffic data. Using the AfreecaTV dataset as the research object, this paper constructs visibility networks at different scales and observes the evolution of degree distribution with varying data volumes. The paper employs the Hurst index to evaluate the 5G traffic network and uses community detection to study the networks converted from 5G traffic data of different applications.ResultsExperimental results reveal significant differences in node degree distribution and topological structures of 5G traffic data across different application scenarios, such as star structures and multiple subnetwork structures. It is found that the node degree distribution of 5G traffic networks exhibits heterogeneity, reflecting the uneven growth of node degrees during network expansion. The Hurst index analysis discovers that the 5G traffic network retains the long-term dependence and trends of the original data. Through community detection, it is observed that networks converted from 5G traffic data of different applications exhibit diverse community structures, such as high centrality nodes, star-like community structures, modularity, and multilayer characteristics.DiscussionThese findings indicate that 5G traffic networks in different application scenarios exhibit complex and diverse characteristics. The heterogeneity of node degree distribution and differences in topological structures reflect the imbalance in node connection methods during network expansion. The results of the Hurst index show that the 5G traffic network inherits the long-term dependence of the original data, providing a basis for analyzing the dynamic characteristics of the network. The diverse community structures reveal the inherent modularity and hierarchy of the network, which helps to understand the performance and optimization directions of 5G networks in different applications.

Elucidating the Antiglycation Effect of Creatine on Methylglyoxal-Induced Carbonyl Stress In Vitro.

Advanced glycation end products (AGEs) with multiple structures are formed at the sites where carbonyl groups of reducing sugars bind to free amino groups of proteins through the Maillard reaction. In recent years, it has been highlighted that the accumulation of AGEs, which are generated when carbonyl compounds produced in the process of sugar metabolism react with proteins, is involved in various diseases. Creatine is a biocomponent that is homeostatically present throughout the body and is known to react nonenzymatically with α-dicarbonyl compounds. This study evaluated the antiglycation potential of creatine against methylglyoxal (MGO), a glucose metabolite that induces carbonyl stress with formation of AGEs in vitro. Further, to elucidate the mechanism of the cytoprotective action of creatine, its effect on the accumulation of carbonyl proteins in the cells and the MGO-induced cellular damage were investigated using neuroblastoma cells. The results revealed that creatine significantly inhibits protein carbonylation by directly reacting with MGO, and creatine added to the culture medium suppressed MGO-derived carbonylation of intracellular proteins and exerted a protective effect on MGO-induced cytotoxicity. These findings suggest that endogenous and supplemented creatine may contribute to the attenuation of carbonyl stress in vivo.

Influence of 5-fluorination on the structure and glycosidic bond stability of the protonated canonical DNA and RNA cytidine nucleosides: Oh, what a difference the 2′-hydroxy substituent makes?

Fluorinated nucleosides are well-established as anticancer and antiviral medications. As with many pharmaceuticals, the effects of fluorine modifications are often only partially understood. In this work, the effects of 5-fluorination of the cytosine nucleobase on the structures and glycosidic bond stabilities of the protonated canonical DNA and RNA cytidine nucleosides (dCyd and Cyd) are examined. Infrared multiple photon dissociation action spectroscopy experiments and electronic structure calculations are employed to probe the structural influences of 5-fluorination. Spectral signatures in the IR fingerprint and hydrogen-stretching regions indicate that 5-fluorination heavily directs for and solely produces O2 protonation para to the 5-fluoro substituent. This differs from the canonical cytidine nucleosides where roughly equal populations of O2 and N3 protonated structures were observed. Energy-resolved collision-induced dissociation experiments combined with survival yield analyses are performed to probe the influence of 5-fluorination on glycosidic bond stability. Trends in the energy-dependence of the survival yield curves indicate that 5-fluorination weakens the glycosidic bond, and that the influence of 5-fluorination on glycosidic bond stability is much greater for dCyd than Cyd. Theory also finds that 5-fluorination weakens the glycosidic bond but predicts that the influence of 5-fluorination on N-glycosidic bond stability is roughly the same for dCyd and Cyd. Oh, what a difference the 2′-hydroxy substituent makes?

Scaffolding Fifth Graders’ Learning with a Digital Multi-Representation Applet: Design Research on Focusing Multiplicative Structures with Dynamic Dot Arrays

AbstractDigital multi-representation applets offer promising opportunities for promoting students’ conceptual understanding by dynamically converting graphical and symbolic representations and for promoting discoveries and justifications of mathematical properties. However, learning effects of open-ended multi-representation applets seem to depend on targeted scaffolds for students’ processes of conversions, treatments, and conversions of treatments. While these design challenges have come to be well-understood for dynamic geometry and functions, more design research is needed for multi-representation applets for multiplicative reasoning. We report on a design research study in Grade 5 in which the multi-representation applet of a dynamic dot array was integrated into a digital teaching–learning environment with sequenced tasks and more targeted scaffolds. The qualitative analysis of 30 students’ processes revealed multiple potentials of the dynamic array to (a) connect static representations by articulating the underlying multiplicative unit structures (conversions), (b) describe systematic variations (coordinated treatments), (c) explain systematic variations in representations by articulating unit structures (conversions of variations), (d) discover multiplicative commutativity (treatments), and (e) go towards justifying multiplicative commutativity by restructuring the array and its unit structures (conversions of treatments). Design experiment Cycle 1 revealed that all potentials were partially addressed by some students. To enable students to exploit more of these multiple potentials, attention scaffolds and language scaffolds were integrated. In Cycle 2, more potentials were exploited while still leaving room for improvements. In total, the study shows how design research can contribute to embed multi-representation applets into teaching–learning environments with well-sequenced tasks and targeted scaffolds.

Multi-step Multiplication Structure with Low Excess Noise for the AlInAsSb Avalanche Photodiode

Multi-step Multiplication Structure with Low Excess Noise for the AlInAsSb Avalanche Photodiode

Generative AI-Driven Data Augmentation for Crack Detection in Physical Structures

The accurate segmentation of cracks in structural materials is crucial for assessing the safety and durability of infrastructure. Although conventional segmentation models based on deep learning techniques have shown impressive detection capabilities in these tasks, their performance can be restricted by small amounts of training data. Data augmentation techniques have been proposed to mitigate the data availability issue; however, these systems often have limitations in texture diversity, scalability over multiple physical structures, and the need for manual annotation. In this paper, a novel generative artificial intelligence (GAI)-driven data augmentation framework is proposed to overcome these limitations by integrating a projected generative adversarial network (ProjectedGAN) and a multi-crack texture transfer generative adversarial network (MCT2GAN). Additionally, a novel metric is proposed to evaluate the quality of the generated data. The proposed method is evaluated using three datasets: the bridge crack library (BCL), DeepCrack, and Volker. From the simulation results, it is confirmed that the segmentation performance can be improved by the proposed method in terms of intersection over union (IoU) and Dice scores across three datasets.

Superior energy storage performance in Bi0.5Na0.5TiO3 based ceramics via synergistic design of multi-size domain construction and multiple phase structures

Lead-free dielectric ceramics, as the crucial materials for the development of eco-friendly high pulse power devices, have faced limitations in achieving energy storage performance comparable to lead-based counterparts. A novel strategy was adopted to enhance the energy storage capability of Bi0.5Na0.5TiO3 based ceramics by constructing multiple phase structures and multi-size domain. An ultrahigh energy storage density of 8.0 J·cm−3 and a large efficiency of 88.9 % were achieved. The superior energy storage properties can be attributed to the synergistic effects of multiple phase structures and multi-size domain construction resulted from a significant polarization intensity difference upon Sr(Zr0.2Ti0.8)O3 doping. Even more surprising, the 0.6Bi0.5Na0.5TiO3-0.4Sr(Zr0.2Ti0.8)O3 ceramic exhibited excellent aging resistance, with variation in discharge energy density (Wd) < ±7% over a temperature range from 20 to 150°C, variations in recoverable energy density (Wrec) < ±8.3 %, and efficiency (η) < ±5.6 % over a frequency range from 1 to 50 Hz and across 105 cycles. The finding in this work not only provides an effective candidate for high power pulse capacitors, but also provides ideas for the study of high energy storage performance of BNT and the related lead-free ceramics.

MADE: Multicurvature Adaptive Embedding for Temporal Knowledge Graph Completion.

Temporal knowledge graphs (TKGs) are receiving increased attention due to their time-dependent properties and the evolving nature of knowledge over time. TKGs typically contain complex geometric structures, such as hierarchical, ring, and chain structures, which can often be mixed together. However, embedding TKGs into Euclidean space, as is typically done with TKG completion (TKGC) models, presents a challenge when dealing with high-dimensional nonlinear data and complex geometric structures. To address this issue, we propose a novel TKGC model called multicurvature adaptive embedding (MADE). MADE models TKGs in multicurvature spaces, including flat Euclidean space (zero curvature), hyperbolic space (negative curvature), and hyperspherical space (positive curvature), to handle multiple geometric structures. We assign different weights to different curvature spaces in a data-driven manner to strengthen the ideal curvature spaces for modeling and weaken the inappropriate ones. Additionally, we introduce the quadruplet distributor (QD) to assist the information interaction in each geometric space. Ultimately, we develop an innovative temporal regularization to enhance the smoothness of timestamp embeddings by strengthening the correlation of neighboring timestamps. Experimental results show that MADE outperforms the existing state-of-the-art TKGC models.

Hydrogen bonds between the oxygen-containing functional groups of biochar and organic contaminants significantly enhance sorption affinity

Sorption affinity is an essential parameter to immobilize contaminants, but the controlling structures of biochar with strong sorption affinity to organic compounds are unidentified, hindering targeted biochar modification. In the face of multiple types and structures of organic contaminants in the aquatic environment, it is urgent to prepare biochar which can remove a large number of contaminants by targeted biochar modification. This study compared the sorption and desorption of five different type organic contaminants on biochar and graphite to understand sorption affinity and to inform the structural regulation of biochar. The sorption capacity of organics on biochar was 3–7 times higher than graphite, and the desorption ratios of organics on biochar were approximately one-fourth of those on graphite. Hydrophobic areas and aromatic rings were confirmed to be low-energy sorption sites, and most pores were inaccessible. The stronger sorption affinity was thus attributed to the hydrogen bonds between biochar surface functional groups and organics. Furthermore, sorption capacity and desorption ratios correlated positively with calculated sorption thermodynamics and binding energies, aligning with theoretical models based on oxygen- and nitrogen-containing groups. Further verification experiments revealed that functionalized graphite with hydroxyl and carboxyl groups showed the most significantly increased sorption capacity and rate, and decreased desorption ratios, enhancing sorption affinity through hydrogen bonds. These findings offer valuable insights into biochar sorption affinity to organics and guide its structural regulation for organic pollution control in the aquatic environment

The long-term functional outcome of the mangled upper extremity intricate management. A single center experience

PurposeSevere injury of multiple anatomical structures of the upper extremity can be caused by an extremely violent mechanism during labor and motor vehicle accidents, gunshots and explosions. The mangled upper extremity consists of trauma of at least 3 of 4 tissue types: connective tissue (skin, subcutaneous tissue, tendons, muscles), vessels, nerves, and bones. The purpose of this study is to evaluate the medium and long-term results of the limb salvage management of those injuries in our department. MethodsSixty-seven patients with multi-injured upper limb were operated in our department between 2014 and 2022 and evaluated with clinical examination and questionnaires (PROMs) on an outpatient basis at a mean follow up of 7.4 years. Patients’ demographics, the injured anatomic structures and the surgical interventions needed, were recorded. ResultsThe overall outcome, configured by functional scores was quite acceptable concerning injuries’ severity. Nineteen patients (29 %) underwent more than one operation, 2-point discrimination test was impaired in 30 % of the patients who had an injured nerve and total loss of regional sensation was diagnosed in 2 patients. Primary amputation was necessary in 8 % of the patients. ConclusionsEven though the mangled upper extremity refers to a severe injury with often poor postoperative results and high rates of amputations, a thorough evaluation and management by expert hand surgeons is essential for maximizing the possible outcomes.

Novel CRM cosine similarity mapping strategy for simultaneous in-situ visual profiling lignocellulose in plant cell walls

Confocal Raman microscopy (CRM) is a promising in-situ visual technique that provides detailed insights into multiple lignocellulosic components and structures in plant cell walls at the micro-nano scale. In this study, we propose a novel CRM cosine similarity (CS) mapping strategy for the simultaneous in-situ visual profiling of lignin, cellulose, and hemicellulose in plant cell walls. The main stages of this strategy include: 1) a modified Otsu algorithm for extracting the regions of interest (ROI); 2) a modified subtraction method for cleaning the background signals in the ROI spectra; 3) a lignin signal subtraction method based on the pixel correction factor for eliminating the interference of strong lignin signals with weak cellulose and hemicellulose signals in the Raman full spectra of the cell walls; 4) second-order derivative spectral preprocessing for enhancing the discrimination between the characteristic peaks of cellulose and hemicellulose; 5) a CS mapping algorithm for simultaneous in-situ profiling of lignin, cellulose, and hemicellulose in plant cell walls. The effectiveness of the strategy is verified by characterizing the Brittle Culm1 (BC1) gene-mutant rice stem (IL349-BC1-KO) with known bioinformatics. This approach provides methodological support for in-situ visualization and analysis in fields such as plant or crop science at the micro-nano scale.

Double-diffusive convection in flow of Carreau fluid with variable density inside converging and diverging channels of rectilinear walls

In this article, the effects of double-diffusive convection have been seen on the flow of Carreau fluid of variable density, maintained inside straight and converging (diverging) channels. Note that the channel walls exhibit variable porosity and undergo stretching or shrinking at non-uniform velocities. In the flow domain, we have taken into account the convective transport of both heat and species mass concentrations. The pseudo-similarity solutions of previous investigation for such type flows are not used here; however, a new set of similarity transformations has been formed, which reduced the governing system (PDEs) into an exact set of ordinary differential equations (ODEs), whereas the longstanding issues of semi-similarity solutions have been successfully resolved in this particular case and in general for all situations of Carreau fluid flow. In a nutshell, a unified mathematical approach has been devised in this paper. We strictly emphasized the simulation of flow of Carreau fluid and double diffusive convection in flow inside a channel with multiple dynamical behaviours and structures (both Jeffery Hammel and Poissuielle flow types) of walls. The boundary layer approximation and stream function assumptions have not been used in the study's execution. The shear thinning and shear thickening features of Carreau fluids with variable density cause them to exhibit lower axial velocity in the centre of a horizontal channel than Newtonian fluids due to variable wall configurations and complex flow conditions. By enhancing buoyancy driven convection, which promotes effective heat dispersion, increasing the solutal and thermal Grashof numbers (GrS=GrT>0) lowers the temperature field. It has been found that in channel with diverging walls (a1=2.0), increasing the modified Reynolds numbers (σ1,σ2>0) increases concentration profiles, i.e. ϕ(η), while decreasing them in channel with rectilinear walls (a1=0.0).