Search Results (239)

Background: Electrochemical impedance spectroscopy (EIS) is indispensable for disentangling charge-transfer, capacitive, and diffusive phenomena, yet reproducible parameter estimation and objective model selection remain unsettled. Methods: We derive closed-form impedances and analytical Jacobians for seven equivalent-circuit models (Randles, constant-phase element (CPE), and Warburg impedance (ZW) variants), enforce physical bounds, and fit synthetic spectra with 2.5% and 5.0% Gaussian noise using hybrid optimization (Differential Evolution (DE) → Levenberg–Marquardt (LM)). Uncertainty is quantified via non-parametric bootstrap; parsimony is assessed with root-mean-square error (RMSE), Akaike Information Criterion (AIC), and Bayesian Information Criterion (BIC); physical consistency is checked by Kramers–Kronig (KK) diagnostics. Results: Solution resistance ($R_s$) and charge-transfer resistance ($R_{ct}$) are consistently identifiable across noise levels. CPE parameters $(Q,n)$ and diffusion amplitude $\left(\sigma \right)$ exhibit expected collinearity unless the frequency window excites both processes. Randles suffices for ideal interfaces; Randles+CPE lowers AIC when non-ideality and/or higher noise dominate; adding Warburg reproduces the ${45}^{\circ }$ tail and improves likelihood when diffusion is present. The $(R_{ct}+Z_W)\Vert \mathrm{CPE}$ architecture offers the best trade-off when heterogeneity and diffusion coexist. Conclusions: The framework unifies analytical derivations, hybrid optimization, and rigorous statistics to deliver traceable, reproducible EIS analysis and clear applicability domains, reducing subjective model choice. All code, data, and settings are released to enable exact reproduction. Full article

The growing need for safe, cheap and sustainable earthquake-resistant buildings means that efficient methods for optimal seismic design must be found. The complexity and nonlinearity of the problem can be addressed using advanced automated techniques. This paper presents an intelligent three-step procedure for optimally designing earthquake-resistant buildings based on the training (1st step) and successive inversion (2nd step) of Multi-Layer Perceptron Neural Networks. This involves solving the inverse problem of determining the optimal design parameters that meet pre-assigned, code-based performance targets, by means of a gradient-based optimization algorithm (3rd step). The effectiveness of the procedure was tested using an archetypal multistory, moment-resisting, concentrically braced steel frame with active tension diagonal bracing. The input dataset was obtained by varying four design parameters. The output dataset resulted from performance variables obtained through non-linear dynamic analyses carried out under three earthquakes consistent with the Chilean code spectrum, for all cases considered. Three spectrum-consistent records are sufficient for code-based seismic design, while each seismic excitation provides a wealth of information about the behavior of the structure, highlighting potential issues. For optimization purposes, only information relevant to critical sections was used as a performance indicator. Thus, the dataset for training consisted of pairs of design parameter sets and their corresponding performance indicator sets. A dedicated MLP was trained for each of the outputs over the entire dataset, which greatly reduced the total complexity of the problem without compromising the effectiveness of the solution. Due to the comparatively low number of cases considered, the leave-one-out method was adopted, which made the validation process more rigorous than usual since each case acted once as a validation set. The trained network was then inverted to find the input design search domain, where a cost-effective gradient-based algorithm determined the optimal design parameters. The feasibility of the solution was tested through numerical analyses, which proved the effectiveness of the proposed artificial intelligence-aided optimal seismic design procedure. Although the proposed methodology was tested on an archetypal building, the significance of the results highlights the effectiveness of the three-step procedure in solving complex optimization problems. This paves the way for its use in the design optimization of different kinds of earthquake-resistant buildings. Full article

Tourism marketing videos can lead to positive emotions and visit intention. This study investigated the impact of VR and 2D tourism videos on user engagement, perception, and emotional responses. This research adopted a priori coding, analyzed 52 interviews using thematic analysis, and concluded a framework with six dimensions, including interactivity, authenticity, presence, cognitive value, hedonic value, and learning value. Findings indicate that VR videos compared to 2D allow users to explore the environment actively and feel an increased sense of presence. However, challenges such as rapid movement, lack of control, and distractions were also reported. VR does not necessarily lead to a higher sense of authenticity because the fast-paced sequences and distracting elements may negatively affect the experiences. Regarding cognitive values, participants mentioned that the videos increased their knowledge of the destination, particularly the 2D format video maintained viewers’ focus. VR facilitates exploration and may enhance learning value. Videos can also generate hedonic value, as many participants reported the emotions of excitement, happiness, and relaxation while watching videos. The findings extend the literature on immersive experiences in the video context. This research also offers practical insights into tourism marketers to design more engaging and effective tourism videos. Full article

A novel long-lasting luminescent composite material based on the (Ca,Sr)-Al-O system was synthesized using a solution combustion method. (Ca,Sr)₃Al₂O₆ is the primary phase, with SrAl₂O₄ as a controllable secondary phase. Compared to conventional single-phase SrAl₂O₄ phosphors, the introduction of a calcium-rich hexaaluminate matrix creates additional defects and a specific trap distribution at the composite interface, significantly improving carrier storage and release efficiency. Eu²⁺ + Nd³⁺ synergistic doping enables precise control of the trap depth and number. Under 365 nm excitation, Eu²⁺ emission is located at ~515 nm, with Nd³⁺ acting as an effective trap center. Under optimal firing conditions at 700 °C (Eu²⁺ = 0.02, Nd³⁺ = 0.003), the afterglow lifetime exceeds 30 s. Furthermore, The (Ca,Sr)₃Al₂O₆ host stabilizes the lattice and optimizes defect states, while synergizing with the SrAl₂O₄ secondary phase to improve the afterglow performance. This composite phosphor exhibits excellent dual-mode anti-counterfeiting properties: long-lasting green emission under 365 nm excitation and transient blue-violet emission under 254 nm excitation. Based on this, a screen-printing ink was prepared using the phosphor and ethanol + PVB, enabling high-resolution QR code printing. Pattern recognition and code verification can be performed both in the UV on and off states, demonstrating its great potential in high-security anti-counterfeiting applications. Compared to traditional single-phase SrAl₂O₄ systems, this study for the first time constructed a composite trap engineering of the (Ca,Sr)₃Al₂O₆ primary phase and the SrAl₂O₄ secondary phase, achieving the integration of dual-mode anti-counterfeiting functionality with a high-resolution QR code fluorescent ink. Full article

Catalysis plays a pivotal role in green chemistry practices, particularly in reducing waste generated during chemical synthesis. Decatungstate (DT) emerges as a potent photocatalyst for Type I oxidations, exhibiting remarkable resilience to oxygen quenching, a characteristic that sets it apart from other excited triplet state photocatalysts. While homogeneous DT catalysis demonstrates effectiveness, its solubility poses challenges for its separation and recycling. To address these limitations, we focus on the development and comparison of heterogeneous DT photocatalysts, aiming to optimize their yield, recovery, and reusability. We synthesized tetrabutylammonium decatungstate (TBADT)-supported catalysts using silica, alumina, titanium dioxide, and glass wool and characterized them using diffuse reflectance measurements. Subsequently, we evaluated their photocatalytic performance by monitoring the oxidation of 1-phenylethanol and cyclohexanol under UVA irradiation. Our findings reveal that TBADT@silica emerges as the most effective catalyst, achieving approximately 20% conversion of cyclohexanol and 50% conversion of 1-phenylethanol with good reusability. Interestingly, we observed that 3-aminopropyl-triethoxysilane (APTES) treatment, intended to enhance DT anchoring, unexpectedly quenches the ³DT* triplet state, reducing catalytic activity. This unexpected finding underscores the importance of careful consideration in designing robust and recyclable heterogeneous decatungstate catalysts. Our research contributes significantly to the advancement of heterogeneous photocatalysis, paving the way for future applications in flow photochemistry. Further, we share a Python code (Google 3.12.11) to correct spectra obtained in Cary spectrometers. Full article

Voltage-gated Na⁺ channels (Nav) are the molecular determinants of action potential initiation and propagation. Among the nine voltage-gated Na⁺ channel isoforms (Nav1.1–Nav1.9), Nav1.2 and Nav1.6 are of particular interest because of their developmental expression profile throughout the central nervous system (CNS) and their association with channelopathies. Although the α-subunit coded by each of the nine isoforms can sufficiently confer transient Na⁺ currents (I_Na), in vivo these channels are modulated by auxiliary proteins like intracellular fibroblast growth factor (iFGFs) through protein–protein interaction (PPI), and probes developed from iFGF/Nav PPI complexes have been shown to precisely modulate Nav channels. Previous studies identified ZL0177, a peptidomimetic derived from a short peptide sequence at the FGF14/Nav1.6 PPI interface, as a functional modulator of Nav1.6-mediated I_Na⁺. However, the isoform specificity, binding sites, and putative physiological impact of ZL0177 on neuronal excitability remain unexplored. Here, we used automated planar patch-clamp electrophysiology to assess ZL0177’s functional activity in cells stably expressing Nav1.2 or Nav1.6. While ZL0177 was found to suppress I_Na in both Nav1.2- and Nav1.6-expressing cells, ZL0177 elicited functionally divergent effects on channel kinetics that were isoform-specific and supported by differential docking of the compound to AlphaFold structures of the two channel isoforms. Computational modeling predicts that ZL0177 modulates Nav1.2 and Nav1.6 in an isoform-specific manner, eliciting phenotypically divergent effects on action potential discharge. Taken together, these results highlight the potential of PPI derivatives for isoform-specific regulation of Nav channels and the development of therapeutics for channelopathies. Full article

Ultrasonic testing (UT) is a vital nondestructive testing (NDT) technique used to evaluate the integrity of materials and structures. However, conventional excitation signals often suffer from significant attenuation in highly attenuative materials, resulting in low signal energy and poor signal interpretation. Coded excitation techniques, such as the Barker code and the complementary Golay code (CGC), have been used to enhance signal energy and signal-to-noise ratio. Yet, Barker codes are limited by short sequence lengths, while CGC requires two transmission events, reducing time efficiency. This paper proposes a novel excitation method: the Barker-convolved mutually orthogonal Golay complementary code (BMOGCC). By convolving the Barker code with the mutually orthogonal Golay complementary code (MOGCC), BMOGCC combines the advantages of both, including flexibility in code length, improved signal amplitude, low sidelobe levels, and enhanced time efficiency. Performance was evaluated using numerical simulations and laboratory experiments, with key indices including the peak sidelobe level (PSL), mainlobe gain (MG), and temporal resolution. The results show that BMOGCC achieves a significantly higher MG than either the Barker code or MOGCC alone while maintaining a low PSL and preserving the temporal resolution. These findings demonstrate that BMOGCC is effective and efficient for coding excitation signals in ultrasonic testing, offering improved signal quality and measurement time efficiency. Full article

In the earthquakes that occurred in the Pazarcık (Mw = 7.7) and Elbistan (Mw = 7.6) districts of Kahramanmaraş Province on 6 February 2023, many buildings collapsed in the Hayrullah neighborhood of the Onikişubat district. In this study, we investigated whether there was a soil amplification effect on the damage occurring in the Hayrullah neighborhood of the Onikişubat district of Kahramanmaraş Province. Firstly, borehole, SPT, MASW (multi-channel surface wave analysis), microtremor, electrical resistivity tomography (ERT), and vertical electrical sounding (VES) tests were carried out in the field to determine the engineering properties and behavior of soil. Laboratory tests were also conducted using samples obtained from bore holes and field tests. Then, an idealized soil profile was created using the laboratory and field test results, and site dynamic soil behavior analyses were performed on the extracted profile. According to The Turkish Building Code (TBC 2018), the earthquake level DD-2 design spectra of the project site were determined and the average design spectrum was created. Considering the seismicity of the project site and TBC (2018) criteria (according to site-specific faulting, distance, and average shear wave velocity), 11 earthquake ground motion sets were selected and harmonized with DD-2 spectra in short, medium, and long periods. Using scaled motions, the soil profile was excited with 22 different earthquake scenarios and the results were obtained for the equivalent and non-linear models. The analysis showed that the soft soil conditions in the area amplified ground shaking by up to 2.8 times, especially for longer periods (1.0–2.5 s). This level of amplification was consistent with the damage observed in mid- to high-rise buildings, highlighting the important role of local site effects in the structural losses seen during the Kahramanmaraş earthquakes. Full article

Neuropathic pain is a significant global clinical issue that poses substantial challenges to both public health and the economy due to its complex underlying mechanisms. It has emerged as a serious health concern worldwide. Recent studies involving dorsal root ganglion (DRG) stimulation have provided strong evidence supporting its effectiveness in alleviating chronic pain and its potential for sustaining long-term pain relief. In addition to that, there has been ongoing research with clinical evidence relating to the role of small non-coding ribonucleic acids known as microRNAs in regulating gene expressions affecting pain signals. The signal pathway involves alterations in neuronal excitation, synaptic transmission, dysregulated signaling, and subsequent pro-inflammatory response activation and pain development. When microRNAs are dysregulated in the dorsal root ganglia neurons, they polarize macrophages from anti-inflammatory M2 to inflammatory M1 macrophages causing pain signal generation. By reversing this polarization, a therapeutic activity can be induced. However, the direct delivery of these nucleotides has been challenging due to limitations such as rapid clearance, degradation, and reduction in half-life. Therefore, safe and efficient carrier vehicles are fundamental for microRNA delivery. Here, we present a comprehensive analysis of miRNA-based nano-systems for chronic neuropathic pain, focusing on their impact in dorsal root ganglia. This review provides a critical evaluation of various delivery platforms, including viral, polymeric, lipid-based, and inorganic nanocarriers, emphasizing their therapeutic potential as well as their limitations in the treatment of chronic neuropathic pain. Innovative strategies such as hybrid nanocarriers and stimulus-responsive systems are also proposed to enhance the prospects for clinical translation. Serving as a roadmap for future research, this review aims to guide the development and optimization of miRNA-based therapies for effective and sustained neuropathic pain management. Full article

Bottlenose dolphins’ broadband click vocalisations are well-studied in the literature concerning their echolocation function. Their potential use for communication among conspecifics has long been speculated but has yet to be conclusively established. In this study, we first categorised dolphins’ click production based on their amplitude contour and then analysed the distribution of individual clicks and click sequences against their duration and length. The results show that the repertoire and composition of clicks and click sequences adhere to the three essential linguistic laws of efficient communication: Zipf’s rank–frequency law, the law of brevity, and the Menzerath–Altmann law. Conforming to the rank–frequency law suggests that clicks may form a linguistic code subject to selective pressures for unification, on the one hand, and diversification, on the other. Conforming to the other two laws also implies that dolphins use clicks according to the compression criterion or minimisation of code length without losing information. Such conformity of dolphin clicks might indicate that these linguistic laws are more general, which produces an exciting research perspective on animal communication. Full article

Cable-suspended photovoltaic (PV) systems have gained traction due to their lightweight structure and adaptability to complex terrains. However, the wind-induced vibration behavior of these systems, particularly the contribution of glass–glass PV modules to structural stiffness, remains inadequately addressed in current design codes. This study presents a comprehensive finite element analysis to investigate the mechanical role of glass–glass PV modules in cable-suspended PV systems. A high-fidelity model (HFM) capturing detailed structural features of the PV module is established and used as a reference to develop an equivalent stiffness model (ESM). Through modal decomposition under wind excitation, it is shown that module deformation primarily manifests as torsion, which significantly contributes to the overall stiffness of the support structure. Comparative simulations reveal that conventional modeling approaches, including the inaccurate simplified model (ISM), overestimate stiffness, potentially compromising structural safety. The ESM, by accurately replicating the HFM’s torsional response, enables efficient and reliable wind-induced vibration analysis. The results also indicate that modules at the cable span edges experience greater torsional deformation, especially under suction forces, highlighting a critical zone for structural reinforcement. Full article

Air-coupled ultrasound overcomes the limitations of traditional contact-based ultrasonic methods that rely on liquid couplants. Still, it faces challenges due to the acoustic impedance mismatch between air and wood, causing significant signal scattering and attenuation. This results in weak transmission signals contaminated by clutter and noise, compromising measurement accuracy. This study proposes a coded pulse air-coupled ultrasonic method for detecting defects in wood. The method utilizes Golay code complementary sequences (GCCSs) to generate excitation signals, with its feasibility validated through mathematical analysis and simulations. A-scan imaging was performed to analyze the differences in signal characteristics between defective and non-defective areas, while C-scan imaging facilitated a quantitative assessment of defects. Experimental results demonstrated that GCCS-enhanced signals improved the ultrasonic penetration and axial resolution compared to conventional multi-pulse excitation. The method effectively identified defects such as knots and pits, achieving a coincidence area of 85% and significantly enhancing the detection accuracy. Full article

Pituitary neuroendocrine tumors (PitNETs) are slow-growing neoplasms with various clinical presentations, often leading to diagnostic challenges. While neuroimaging assessment and histopathological evaluation remain the gold standard for diagnosis, emerging research highlights the potential of liquid biopsy, mainly through the analysis of circulating non-coding RNAs (ncRNAs), as a promising diagnostic and prognostic tool. Recent studies have demonstrated distinct expression profiles in different types and subtypes of tumors, with implications in assessing tumor aggressiveness and predicting treatment response. The current article summarizes data about potential biofluid markers implicated in PitNET development, mainly circulating tumor DNA (ctDNA), cell-free RNAs (cfRNA), circulating tumor cells (CTCs), and exosomes. Many studies on genetic and molecular markers in PitNET tissue samples provide exciting information about tumor biology, but to date, specific studies on liquid biopsy biomarkers are still few. Over the past years, a certain understanding of the mechanisms involved in pituitary tumorigenesis has been gained, including the landscape of genomic alterations, changes in epigenetic profile, crucial molecules involved in specific signaling pathways, and non-coding RNA molecules with critical roles in malignant transformation. Genetic and molecular characterization of the PitNETs could help distinguish between functional and non-functional PitNETs, different types and subtypes of pituitary tumors, and invasive and non-invasive forms. Further studies are required to identify and validate innovative biomarkers or therapeutic targets for treating PitNET. Integrating liquid biopsy into clinical workflows could revolutionize the management of pituitary adenomas, enabling more personalized and less invasive diagnostic and therapeutic strategies. Full article

Neuropathic pain is a chronic condition resulting from injury or dysfunction in the somatosensory nervous system, which leads to persistent pain and a significant impairment of quality of life. Research has highlighted the complex molecular mechanisms that underlie neuropathic pain and has begun to delineate the roles of microRNAs (miRNAs) in modulating pain pathways. miRNAs, which are small non-coding RNAs that regulate gene expression post-transcriptionally, have been shown to influence key cellular processes, including neuroinflammation, neuronal excitability, and synaptic plasticity. These processes contribute to the persistence of neuropathic pain, and miRNAs have emerged as critical regulators of pain behaviors by modulating signaling pathways that control pain sensitivity. miRNAs can influence neuropathic pain by targeting genes that encode protein kinases involved in pain signaling. This review focuses on miRNAs that have been demonstrated to modulate neuropathic pain behavior through their effects on protein kinases or their immediate upstream regulators. The relationship between miRNAs and neuropathic pain behaviors is characterized as either an upregulation or a downregulation of miRNA levels that leads to a reduction in neuropathic pain. In the case of miRNA upregulation resulting in an alleviation of neuropathic pain behaviors, protein kinases exhibit a positive correlation with neuropathic pain, whereas decreased protein kinase levels correlate with diminished neuropathic pain behaviors. The only exception is GRK2, which shows an inverse correlation with neuropathic pain. In the case of miRNA downregulation resulting in a reduction in neuropathic pain behaviors, protein kinases display mixed relationships to neuropathic pain, with some kinases exhibiting positive correlation, while others exhibit negative correlation. By exploring how protein kinases mediate miRNA modulation of neuropathic pain, valuable insight may be gained into the pathophysiology of neuropathic pain, offering potential therapeutic targets for developing more effective strategies for pain management. Full article

In this study, the solution model based on the stochastic harmony search algorithm was proposed to obtain real ground motion (GM) records for nonlinear dynamic analysis of structures. Obtaining the GM record problem was formulated as a constrained engineering optimization problem. The solution model ensures spectral compatibility between the mean horizontal spectrum of selected ground motion (GM) records and the target horizontal spectrum, as well as the mean vertical spectrum of the selected GMs with the target vertical spectrum. This model also allows the management of record-to-record variability in both horizontal and vertical components of the selected GMs. Moreover, the model effectively addresses the period-dependent record-to-record variability in all orientations of seismic excitations simultaneously using a single-scale value, preserving the relative amplitude and phasing of actual GM components. The efficiency of the model has been demonstrated through numerical examples with various uniform hazard spectra, specifically those based on Eurocode-8 and the Turkish Building Earthquake Code, as well as scenario-based target spectra. The results demonstrate that through using the proposed model it is possible to obtain GM records with the desired spectral compatibility and spectral dispersion for both horizontal and vertical GM components. Thus, the model can be used as an efficient way to obtain appropriate GM records for nonlinear dynamic analyses of both two- and three-dimensional structural models for performance-based designs and/or evaluation frameworks, considering seismic excitations in both horizontal and vertical directions. Full article