Conventional Theory Research Articles

An accurate full-dimensional potential energy surface of the hydrogen sulfide dimer system and its kinetics for the hydrogen exchange channel

The hydrogen sulfide cluster exhibits weak interaction, which plays a crucial role in biomolecules, superconductivity, etc. Hydrogen sulfide dimer, (H2S)2, as a relatively simple system containing this interaction, is a preferred subject for studying this weak interaction and has attracted significant attention recently. In this work, an accurate full-dimensional potential energy surface (PES) for the (H2S)2 system is reported using the permutationally invariant polynomial-neural network (PIP-NN) method. The energies for the sampled 106,952 configurations are calculated using the CCSD(T)-F12a/AVTZ method, with the Boys-Bernardi counterpoise method used to eliminate basis set superposition errors (BSSE). The total root-mean square error (RMSE) of the final PIP-NN PES is only 0.019 kcal mol−1. The PES can reproduce well the structures, energies, and harmonic frequencies of the nine stationary points, five stationary isomers and four transition states. Two new hydrogen exchange reaction channels are included in the current PES. The rate coefficients of the hydrogen exchange channels are calculated using both conventional transition state theory (TST) and canonical variational theory (CVT) with the quantum tunneling correction treated by the zero-curvature tunneling (ZCT) and small curvature tunneling (SCT) methods.

Molecular Dynamics Simulations in Nanoscale Heat Transfer: A Mini Review

Abstract As device miniaturization advances, managing heat at the nanoscale becomes increasingly critical. Nanoscale heat transfer presents unique challenges, including size effect, ballistic transport, and complex phonon interactions, which conventional macroscopic theories cannot fully address. Molecular dynamics (MD) simulations have been a powerful tool for directly modeling atomistic motion and interactions, offering valuable insights into thermal phenomena. This article provides an overview of MD methods and their contributions to understanding thermal transport in inorganic crystals, amorphous solids, polymers, and interfaces. Additionally, we offer our perspective on the emerging trends and future research directions in MD simulations, emphasizing their potential to unravel complex thermal phenomena and guide the design of next-generation thermal materials and devices.

Chatbots and academic writing for doctoral students

AbstractThis exploratory case study examines how AI technologies, specifically a GPT-4-based synopsis chatbot, can serve as a sparring partner for doctoral students in Norway. Despite favourable conditions, only two-thirds of Norwegian PhD candidates complete their doctorates, partly due to challenges with article-based dissertations that require a comprehensive synopsis (60–90 pages). Ambiguities and unintended double standards exist across disciplines regarding this format, despite national guidelines. To address this, we developed a synopsis chatbot by training GPT-4 on Norwegian doctoral rubrics and literature about article-based dissertations, making it more domain-specific, context-specific, and multilingual. The goal was to determine if and how the chatbot could support PhD candidates in writing their synopses. Preliminary results indicate varying levels of AI acceptance among PhD supervisors, with 60% expressing scepticism about using AI for academic writing. However, the chatbot performed well in providing formative assessment and handling multimodal illustrations, proving to be a valuable sparring partner for doctoral students. This suggests the need to update conventional theories of formative assessment to include AI and chatbots as complementary "digital supervisors" in doctoral education. While the chatbot shows promise in mitigating issues related to unwritten rules and vague genre requirements, this early-phase exploratory study acknowledges several limitations and emphasizes the need to address ethical considerations regarding AI in academia.

Sociolinguistic study of kilba personal names

This paper delves into the sociolinguistic factors and semantic implications of Kilba names and naming systems. It explores how names are given in Kilba community, explaining the cultural and social meanings attached to names .The research method involves primary data collection from aged parents in the Hong local government of Adamawa State, as well as secondary sources such as books, journal articles, and online materials. Contextual and conventional theories of meaning were used as guide for the study. The analysis categorizes Kilba names names into five main groups based on their significance and origins. The findings highlight the importance of names as identifiers of individual personalities and reflect the unique circumstances or situations surrounding a child’s birth. This study concludes that the significance of names to Kilba people is beyond mere labels, but a reflection of socio-cultural values, beliefs, and experiences.

Laser-induced epoxide ring opening on graphene oxide leading to C–O single bonds: An ab initio prediction

The dynamics of the epoxide in graphene oxide under laser irradiation were investigated based on the frameworks of time-dependent density functional theory and molecular dynamics within the Ehrenfest approximation. Two combinations of the laser wavelength (λ) and full width at half-maximum (FWHM) were examined: λ=266 nm with FWHM=100 fs and λ=810 nm with FWHM=35 fs. Upon tuning the laser fluence to just below the threshold for oxygen desorption, epoxide ring opening to form a carbon–oxygen (C–O) single bond was observed. Further simulations revealed that the laser-generated C–O bonds were inert in the presence of water molecules. Conventional static density functional theory calculations and complete-active-space self-consistent field calculations indicated that the C–O bonds were (meta)stable in the electronically excited and negatively charged states. Finally, the feasibility of experimentally observing the C–O bond was considered.

Reduced striatal M4-cholinergic signaling following dopamine loss contributes to parkinsonian and l-DOPA-induced dyskinetic behaviors.

A dynamic equilibrium between dopamine and acetylcholine (ACh) is essential for striatal circuitry and motor function, as imbalances are associated with Parkinson's disease (PD) and levodopa-induced dyskinesia (LID). Conventional theories posit that cholinergic signaling is pathologically elevated in PD as a result of increased ACh release, which contributes to motor deficits. However, using approaches to measure receptor-mediated signaling, we found that, rather than the predicted enhancement, the strength of cholinergic transmission at muscarinic M4 receptor synapses on direct pathway medium spiny neurons was decreased in dopamine-depleted mice. This adaptation was due to a reduced postsynaptic M4 receptor function, resulting from down-regulated receptors and downstream signaling. Restoring M4 transmission unexpectedly led to a partial alleviation of motor deficits and LID dyskinetic behavior, revealing an unexpected prokinetic effect in addition to the canonical antikinetic role of M4 receptors. These findings indicate that decreased M4 function differentially contributes to parkinsonian and LID pathophysiology, representing a promising target for therapeutic intervention.

Observation of two-dimensional time-reversal broken non-Abelian topological states

Going beyond the conventional theory, non-Abelian band topology reveals the global quantum geometry of multiple Bloch bands and unveils a new paradigm for topological physics. However, to date, experimental studies on non-Abelian topological states beyond one dimension are still restricted to systems with time-reversal (T\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${{\\mathcal{T}}}$$\\end{document}) symmetry. Here, exploiting a designer gyromagnetic photonic crystal, we find rich T\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${{\\mathcal{T}}}$$\\end{document}-broken non-Abelian topological phases and their transitions with an unexpected connection to multigap antichiral edge states. By in-situ tuning the magnetic field in the gyromagnetic photonic crystal, we can create, braid, merge, and split the non-Abelian topological nodes in a unique way. Alongside this process, the multigap antichiral edge states can be tuned versatilely, giving rise to topological edge waveguiding with frequency-dependent directionality. These findings open a new avenue for non-Abelian topological physics and topological photonics.

Holistic model for business resource and effective social media contents on MSME’S marketing

Business in the 21st century cannot function without social media marketing. The literature n social media marketing, however, is still fragmented and mostly concerned with isolated issues like communication techniques. To describe what constitutes a successful social media marketing strategy, this research uses a qualitative, theory-building technique to develop a conceptual framework. The spectrum of conservatives and progressives, of hierarchies and networks, of total authority and full anarchy may all be found in the realm of social media marketing. This research provides a holistic framework for understanding strategic social media marketing, expanding beyond the confines of conventional marketing theory. The framework also enables business leaders to position their organizations along these four dimensions in a manner that serves their long-term objectives.

Balanced d-Band Model: A Framework for Balancing Redox Reactions in Lithium-Sulfur Batteries.

Managing the redox reactions of polysulfides is crucial for improving the performance of lithium-sulfur batteries (LSBs). Herein, we introduce a progressive theoretical framework: the balanced d-band model, which is based on classical d-band center theory. Specifically, by optimizing the position of the d-band center in the middle between the highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) of each sulfur species, balanced and fast oxidation and reduction reactions of the sulfur species can be achieved simultaneously. To validate this theory, we synthesized a catalyst featuring an in situ phosphorized heterostructure (NOP) based on nickel oxide (NiO), which effectively optimizes the d-band center at the middle between the HOMO and LUMO of each sulfur species. Aided by the balanced oxidation and reduction kinetics of the sulfur species, the NOP-based cell achieved a high reversible capacity, superior cycling stability, and prolonged cycle life. This study extends the conventional d-band center theory and introduces an innovative theoretical model to expand our understanding of the internal reaction mechanisms in LSBs.

Polarization-selective metamaterial absorber using tailored Y-shaped SRR for UWB device and Doppler navigation aids applications

In this paper, we present an unprecedented metamaterial absorber design exhibiting exceptional characteristics in electromagnetic wave absorption. The proposed bent Y-shaped structure, fabricated on an FR-4 substrate with copper patches, showcases remarkable performance across a diverse frequency spectrum. Through exhaustive simulations in CST, this design manifests eight distinct resonant frequencies, achieving absorption rates exceeding 90 % at each resonance. The resonances, strategically spanning from L-band (3.728 GHz) through S-band, C-band, X-band, Ku-band, and K-band up to 22.664 GHz, signify unparalleled versatility and efficacy in mitigating electromagnetic radiation. It investigates the equivalent circuit parameters of a proposed metamaterial absorber design, focusing on inductance (L), capacitance (C), and resistance (R). This paper investigates the applications of UWB devices at 3.728 GHz and Doppler navigation aids at the 13.4 GHz frequency as regulated by the Federal Communications Commission. It includes a discussion on near-zero refractive Index Metamaterials (NZRIM), highlighting their potential utilization in achieving extraordinary control over wave behaviour. Notably, the absorber's inherent polarization insensitivity fortifies its adaptability in various applications. Additionally, the metamaterial exhibits near-zero or negative permittivity, altering electric response, while simultaneously demonstrating permeability absolute zero throughout all frequency bands sparking new avenues for exploration and challenging conventional electromagnetic theories.

Emergence of global value chains as key driver behind industrial development: evidence from participating African countries

Purpose The purpose of this paper is to examine the role of global value chains (GVC) in industrial development of emerging economies, with particular focus on participating African countries. The findings of this study are expected to provide insight on the need for more developing countries to participate in GVC. Design/methodology/approach This study is built upon the neoclassical and endogenous growth theories, which postulate that savings, physical capital and human capital are the fundamental drivers of development in productive sectors of the economy. The investigation, covering the period 1980–2021, is carried out by using the unrestricted error correction model and dynamic ordinary least squares model. Findings The results of this study reveal that GVC stands as the dominant factor driving industrial development, compared to savings, physical capital and human capital. The findings, therefore, seem to contradict the postulation of conventional theories. The policy implications of the findings are not far-fetched. First, industrial development in the participating African countries has benefited largely from GVC; hence, it is necessary to encourage more participation. Second, industrial development also benefited from the control variables (savings, physical capital and human capital), hence the need to sustain their complementary role. Thirdly, only three African countries are actively participating in GVC, which suggests that more countries need to join, to facilitate industrial development. Originality/value Previous studies have not given adequate attention to African countries that participate in GVC, thus creating a void that needs to be filled. This study, therefore, produced results that are relevant to policy-making on industrial development in African countries.

Vehicle Lane Changing Game Model Based on Improved SVM Algorithm

In order to improve the autonomous lane-changing performance of unmanned vehicles, this paper aims to solve the problem of inaccurate decision classification in traditional support vector machine (SVM) algorithms applied to the lane-changing decision-making stage of intelligent driving vehicles. By using game theory-related theories and combining the improved support vector machine (SSA-SVM) method, a vehicle autonomous lane-changing strategy based on game theory is established. The optimized SVM method has certain advantages for vehicle lane-changing decision-making with a small sample size in actual production processes. The lane-changing decision judgment accuracy rate of the SSA-SVM algorithm model can reach 93.6% compared with the SVM algorithm model without algorithm optimization; the SSA-SVM algorithm model has obvious advantages in decision performance and running speed. Therefore, the proposed new algorithm can effectively solve the problem of the objective consideration of the payoff function in conventional decision game theory.

Systematic study on the hydrogen abstraction reactions from oxygenated compounds by H and HO2

AbstractTo extend the rule‐based approach for hydrogen abstraction reactions from oxygenated compounds, a systematic investigation was performed to examine the reactivity of gas‐phase hydrogen abstraction reactions from alkyl groups (methyl and ethyl groups) bound to oxygen atoms in five types of oxygenated compounds (alcohols, ethers, formate esters, acetate esters, and carbonate esters) by H atoms and HO2 radicals comprehensively considering rotational conformers. Quantum chemical calculations were conducted at the CBS‐QB3 level for stationary points. Rate constants were determined employing conventional transition state theory (TST). For hydrogen abstraction reactions by H, the rotational conformer distribution partition function was employed to approximate partition functions, owing to the similarity in vibrational energy‐level structures among conformers. In hydrogen abstraction reactions by HO2, the vibrational structures of transition‐state (TS) conformers varied significantly due to the hydrogen bonding, leading to an inappropriate evaluation of rate constants when using the lowest‐energy conformer as a representative. Therefore, the rate constants were calculated by the multi‐structural TST. It was revealed that the differences in functional groups containing O atoms mainly affect the bond dissociation energies of the C–H bonds and the activation energies of hydrogen abstraction reactions only when the C atoms are adjacent to the O atoms. Additionally, it was found that hydrogen bonds formed in the TSs show minor effect on rate parameters for the overall rate constants, apart from the reduction of the pre‐exponential factors for the H‐abstraction reactions from the methylene position of ethyl groups. The comparison with the rate constants from previous studies showed reasonable results, indicating that the rate constants in this study, which thoroughly consider rotational conformers, can be the current best estimates.

Exploring nonlinear correlations among transition metal nanocluster properties using deep learning: a comparative analysis with LOO-CV method and cosine similarity

A novel approach is introduced for the rapid and accurate correlation analysis of nonlinear properties in Transition Metal (TM) clusters utilizing the Deep Leave-One-Out Cross-Validation technique. This investigation demonstrates that the Deep Neural Network (DNN)-based approach offers a more efficient predictive method for various properties of fourth-row TM nanoclusters compared to conventional Density Functional Theory methods, which are computationally intensive and time-consuming. The feature space, also known as descriptors, is established based on a broad spectrum of electronic and physical characteristics. Leveraging the similarities among these clusters, the DNN-based model is employed to explore the correlations among TM cluster properties. The proposed method, in conjunction with cosine similarity, achieves remarkable accuracy up to 10-9 for predicting total energy, lowest vibrational mode, binding energy, and HOMO-LUMO energy gap of TM2, TM3, and TM4nanoclusters. By analyzing correlation errors, the most closely coupled TM clusters are identified. Notably, Mn and Ni clusters exhibit the highest and lowest levels of energy coupling with other TMs, respectively. Generally, energy prediction for TM2, TM3, and TM4clusters exhibit similar trends, while an alternating behavior is observed for vibrational modes and binding energies. Furthermore, Ti, V, and Co demonstrate the highest binding energy correlations with TM2, TM3, and TM4sets, respectively. Regarding energy gap predictions, Ni exhibits the strongest correlation in the smallest TM2clusters, while Cr shows the highest dependence in TM3and TM4sets. Lastly, Zn displays the largest error in HOMO-LUMO energy gap across all sets, indicating distinctive independent energy gap characteristics.

Making a difference with matter in researchers’ positionality dynamics in qualitative inquiry

Scholars have increasingly highlighted the usefulness of new materialist theories and methodologies in attempts to address the perceived shortcomings of conventional theories inspired by social constructionism and post-structuralism. Contributing to these discussions, we utilize a new materialist theory which rests on a monistic ontology drawn from Spinozian and Deleuzian assemblage theory to examine the constitutive role of material elements (e.g. audio recorders, video cameras, and dress/shirts worn during interviews), spatial, and discursive forces in co-creating fluid nonstatic researcher positionalities in qualitative research process. This article is part of a larger ethnographic study conducted by the first author among fisherfolk in Ghana's coastal fishing communities. Our results show that the researcher's fluid positionalities during interview encounters were brought to bear and sustained in space and time through the joint effort of material, discursive, and spatial forces. As qualitative researchers seek ways to ensure better understanding of their study communities through intimate interactions, an attention to the assemblage of material-discursive forces in interview encounters may highlight some of the opportunities and obstacles in qualitative inquiry beyond human agency and negotiations.

ALMA Observations of Proper Motions of the Dust Clumps in the Protoplanetary Disk MWC 758

To study the dust dynamics in the dust-trapping vortices in the protoplanetary disk around MWC 758, we analyzed the 1.3 mm continuum images of the MWC 758 disk obtained with the Atacama Large Millimeter/submillimeter Array in 2017 and 2021. We detect proper motions of 22 mas and 24 mas in the two dust clumps at radii of 0.″32 and 0.″54 in the disk on the plane of the sky, respectively. On the assumption that the dust clumps are located in the disk midplane, the velocities of the observed proper motions along the azimuthal direction of the inner and outer dust clumps are sub- and super-Keplerian, respectively, and both have angular velocities corresponding to the Keplerian angular velocity at a radius of 0.″46 ± 0.″04. This deviation from the Keplerian motion is not expected in the conventional theory of vortices formed by the Rossby wave instability. The observed non-Keplerian proper motions of the dust clumps are unlikely due to the disk warp and eccentricity, nor are they associated with any predicted planets. The two dust clumps are likely spatially coincident with the infrared spirals. In addition, we detect the changes in the intensity profiles of the dust clumps over the 4 yr span. Therefore, we suggest that the observed proper motions are possibly due to changes in the density distributions in the dust clumps caused by their interaction with the spirals in the disk.

Does the Meissner effect violate the second law of thermodynamics?

In Entropy 24, 83 (2022) (Nikulov 2022), titled “The Law of Entropy Increase and the Meissner Effect”, its author Alexey Nikulov argues that the Meissner effect exhibited by type I superconductors violates the second law of thermodynamics. Contrary to this claim, I show that the Meissner effect is consistent with the second law of thermodynamics provided that a mechanism exists for the supercurrent to start and stop without generation of Joule heat. The theory of hole superconductivity provides such a mechanism, the conventional theory of superconductivity does not. It requires the existence of hole carriers in the normal state of the system.

Electrically tunable graded photonic crystal lens based on graphene plasmons.

Controlling the nonlinear relationship between surface plasmon polariton (SPP) mode index and chemical potential of graphene can be used in the field of active transformation optics. Here, we propose an electrically tunable 2D Graded Photonic Crystal (GPC) lens based on graphene SPP platform. Our platform comprises a graphene monolayer integrated into a back-gated structure with nano-patterned gate insulators. When the chemical potential of the graphene surface is designed to operate in the nonlinear region, the designed GPC lens can be continuously transformed between a Maxwell's fish-eye lens and a Luneburg lens by tuning the gate voltage. The range of the lens background chemical potential for allowing this transformation is systematically studied. To compensate for the significant errors inherent in the conventional effective medium theory (EMT) during the homogenization of photonic crystals (PCs), we propose a generalized effective medium theory (GEMT). The validity and accuracy of this approach are verified through comparisons with true values (based on rigorous eigenvalue solutions) and EMT values. Due to its advantages of on-site controls and easy fabrication characteristics, the proposed graphene GPC provides a new way for practical on-chip light manipulation.

Implications of Artificial Intelligence (AI) and machine learning-based fintech for the financial assets related traditional investment theories

New technologies always have an impact on traditional theories. Finance theories are no exception to that. In this paper, we have concentrated on the traditional investment theories in finance. The study examined five investment theories, their assumptions, and their limitation from different works of literature. The study considered Artificial Intelligence (AI) and Machine Learning (ML) as representative of financial technology (fintech) and tried to find out from the literature how these new technologies help to reduce the limitations of traditional theories. We have found that fintech does not have an equal impact on every conventional finance theory. Fintech outperforms all five traditional theories but on a different scale.

Long-range enhancement for fluorescence and Raman spectroscopy using Ag nanoislands protected with column-structured silica overlayer

We demonstrate long-range enhancement of fluorescence and Raman scattering using a dense random array of Ag nanoislands (AgNIs) coated with column-structured silica (CSS) overlayer of over 100 nm thickness, namely, remote plasmonic-like enhancement (RPE). The CSS layer provides physical and chemical protection, reducing the impact between analyte molecules and metal nanostructures. RPE plates are fabricated with high productivity using sputtering and chemical immersion in gold(I)/halide solution. The RPE plate significantly enhances Raman scattering and fluorescence, even without proximity between analyte molecules and metal nanostructures. The maximum enhancement factors are 107-fold for Raman scattering and 102-fold for fluorescence. RPE is successfully applied to enhance fluorescence biosensing of intracellular signalling dynamics in HeLa cells and Raman histological imaging of oesophagus tissues. Our findings present an interesting deviation from the conventional near-field enhancement theory, as they cannot be readily explained within its framework. However, based on the phenomenological aspects we have demonstrated, the observed enhancement is likely associated with the remote resonant coupling between the localised surface plasmon of AgNIs and the molecular transition dipole of the analyte, facilitated through the CSS structure. Although further investigation is warranted to fully understand the underlying mechanisms, the RPE plate offers practical advantages, such as high productivity and biocompatibility, making it a valuable tool for biosensing and biomolecular analysis in chemistry, biology, and medicine. We anticipate that RPE will advance as a versatile analytical tool for enhanced biosensing using Raman and fluorescence analysis in various biological contexts.