Search Results (1,874)

This paper presents a theoretical study of the structural, electronic, and elastic properties of gallium-doped CuInSe₂ using the GGA exchange-correlation functional with the Hubbard correction for five Ga compositions: 0, 0.25, 0.5, 0.75, and 1. The found lattice parameters decrease with gallium composition and obey Vegard’s law. Traditional DFT calculations fail to explain the band structure of Copper Indium Gallium Selenide compounds (CIGS). The use of Hubbard corrections of d-electrons of copper, indium, gallium, and p-electrons of selenium opens the gap, showing a semiconductor’s behavior of CuInGaSe2 alloys in the range 1.04 eV to 1.88 eV, which are in good agreement with available experimental data and current theory using an expensive hybrid exchange-correlation functional. The obtained formation energies for the different gallium compositions are close to −1 eV/atom, and the phonon spectra indicate the thermodynamic stability of these alloys. The values of the elastic constant satisfy the Born elastic stability conditions, suggesting that these compounds are mechanically stable. Moreover, we compute the bulk modulus (B), shear modulus (G), Young’s modulus (E), Poisson ratio (p), Pugh’s ratio (r), and average Debye speed ($v$), and the Debye temperature (${\mathsf{\Theta }}_{\mathrm{D}}$) with the Ga composition. There is a symmetry between our results and the experimental data, as well as earlier simulation results. Full article

Cognitive deterioration and the transition to neurodegenerative disease does not develop through simple, linear regression; it develops as rapid and global transitions from one state to another within the neural network. Developing understanding and control over these events is among the largest tasks facing contemporary neuroscience. This paper will discuss a conceptual reframing of cognitive decline as a transitional phase of the functional state of complex neural networks resulting from the intertwining of molecular degradation, vascular dysfunction and systemic disarray. The paper will integrate the latest findings that have demonstrated how the disruptive changes in glymphatic clearance mechanisms, aquaporin-4 polarity, venous output, and neuroimmune signaling increasingly correlate with the neurophysiologic homeostasis landscape, ultimately leading to the destabilization of the network attraction sites of memory, consciousness, and cognitive resilience. Furthermore, the destabilizing processes are exacerbated by epigenetic silencing; neurovascular decoupling; remodeling of the extracellular matrix; and metabolic collapse that result in accelerating the trajectory of neural circuits towards the pathological tipping point of various neurodegenerative diseases including Alzheimer’s disease; Parkinson’s disease; traumatic brain injury; and intracranial hypertension. New paradigms in systems neuroscience (connectomics; network neuroscience; and critical transition theory) provide an intellectual toolkit to describe and predict these state changes at the systems level. With artificial intelligence and machine learning combined with single cell multi-omics; radiogenomic profiling; and digital twin modeling, the predictive biomarkers and early warnings of impending collapse of the system are beginning to emerge. In terms of therapeutic intervention, the possibility of reprogramming the circuitry of the brain into stable attractor states using precision neurointervention (CRISPR-based neural circuit reprogramming; RNA guided modulation of transcription; lineage switching of glia to neurons; and adaptive neuromodulation) represents an opportunity to prevent further progression of neurodegenerative disease. The paper will address the ethical and regulatory implications of this revolutionary technology, e.g., algorithmic transparency; genomic and other structural safety; and equity of access to advanced neurointervention. We do not intend to present a list of the many vertices through which the mechanisms listed above instigate, exacerbate, or maintain the neurodegenerative disease state. Instead, we aim to present a unified model where the phenomena of molecular pathology; circuit behavior; and computational intelligence converge in describing cognitive decline as a translatable change of state, rather than an irreversible succumbing to degeneration. Thus, we provide a framework for precision neurointervention, regenerative brain medicine, and adaptive intervention, to modulate the trajectory of neurodegeneration. Full article

Octachlorinated metal phthalocyanines (MPcCl₈, M = Co, Zn, VO) represent an underexplored class of functional materials with promising potential for chemiresistive sensing applications. This work is the first to determine the structure of single crystals of CoPcCl₈, revealing a triclinic (P-1) packing motif with cofacial molecular stacks and an interplanar distance of 3.381 Å. Powder XRD, vibrational spectroscopy, and elemental analysis confirm phase purity and isostructurality between CoPcCl₈ and ZnPcCl₈, while VOPcCl₈ adopts a tetragonal arrangement similar to its tetrachlorinated analogue. Thin films were fabricated via physical vapor deposition (PVD) and spin-coating (SC), with SC yielding highly crystalline films and PVD resulting in poorly crystalline or amorphous layers. Electrical measurements demonstrate that SC films exhibit n-type semiconducting behavior with conductivities 2–3 orders of magnitude higher than PVD films. Density functional theory (DFT) calculations corroborate the experimental findings, predicting band gaps of 1.19 eV (Co), 1.11 eV (Zn), and 0.78 eV (VO), with Fermi levels positioned near the conduction band, which is consistent with n-type character. Chemiresistive sensing tests reveal that SC-deposited MPcCl₈ films respond reversibly and selectively to ammonia (NH₃) and hydrogen sulfide (H₂S) at room temperature. ZnPcCl₈ shows the highest NH₃ response (45.3% to 10 ppm), while CoPcCl₈ exhibits superior sensitivity to H₂S (LOD = 0.3 ppm). These results suggest that the films of octachlorinated phthalocyanines produced by the SC method are highly sensitive materials for gas sensors designed to detect toxic and corrosive gases. Full article

In the current digital competition environment, e-commerce platforms have increased their investment in targeted advertising, improving advertising efficiency while also influencing the choice of product sales modes. This study aims to deeply explore the investment made by platforms in targeted technology and the impact of the choice of sales modes under the asymmetry of power structures. Based on game theory and optimization theory, we develop a decision-making model for targeted technology investments and sales mode selection. Through equilibrium analysis and numerical simulation, the results show that (1) targeted advertising leads to price increases, a reduction in advertising investment, and a decline in demand. Additionally, targeted advertising boosts the seller’s profit while negatively affecting the profit of the other party. (2) When in platform-led sales mode, if the unit advertising cost is low, the platform favors the resale mode; otherwise, it opts for the agency mode. When in manufacturer-led sales mode, regardless of the advertising mode, if the unit advertising cost is low, the manufacturer prefers the agency mode; otherwise, it selects the resale mode. (3) Under different power structures, the conditions and scope for platform-targeted technology investments were provided, and for different advertising models, suggestions were provided for the sales mode selection of the platform and the manufacturer. Full article

This paper develops a unified synchronization framework for octonion-valued fractional-order neural networks (FOOVNNs) subject to mixed delays, Lévy disturbances, and topology switching. A fractional sliding surface is constructed by combining $I^{1-\mu }{e}_g$ with integral terms in powers of $|e_g|$. The controller includes a nonsingular term $-{\rho }_{2g}{s}_g^{c_2}\mathrm{sign}\left(s_g\right)$, a disturbance-compensation term $-{\widehat{\theta }}_g\mathrm{sign}\left(s_g\right)$, and a delay-feedback term $-{\lambda }_g{e}_g(t-\tau )$, while dimension-aware adaptive laws ${\phantom{,}}^C{D}_t^{\mu }{\rho }_g=k_{1g}N{\parallel s_g\parallel }^{c_2}$ and ${\phantom{,}}^C{D}_t^{\mu }{\widehat{\theta }}_g=k_{2g}N\parallel s_g\parallel$ ensure scalability with network size. Fixed-time convergence is established via a fractional stochastic Lyapunov method, and predefined-time convergence follows by a time-scaling of the control channel. Markovian switching is treated through a mode-dependent Lyapunov construction and linear matrix inequality (LMI) conditions; non-Gaussian perturbations are handled using fractional Itô tools. The architecture admits observer-based variants and is implementation-friendly. Numerical results corroborate the theory: (i) Two-Node Baseline: The fixed-time design drives ${\parallel e\left(t\right)\parallel }_1$ to $\mathcal{O}\left({10}^{-4}\right)$ by $t\approx 0.94\mathrm{s}$, while the predefined-time variant meets a user-set $T_p=0.5\mathrm{s}$ with convergence at $t\approx 0.42\mathrm{s}$. (ii) Eight-Node Scalability: Sliding surfaces settle in an $\mathcal{O}\left(1\right)$ band, and adaptive parameter means saturate well below their ceilings. (iii) Hyperspectral (Synthetic): Reconstruction under Lévy contamination achieves a competitive PSNR consistent with hypercomplex modeling and fractional learning. (iv) Switching Robustness: under four modes and twelve random switches, the error satisfies ${max}_t{\parallel e\left(t\right)\parallel }_1\le 0.15$. The results support octonion-valued, fractionally damped controllers as practical, scalable mechanisms for robust synchronization under non-Gaussian noise, delays, and time-varying topologies. Full article

The present research examines how employees perceive their firms’ CSR initiatives that ultimately translate into desired attitudes and behaviors, i.e., employee environmental commitment (EEC) and knowledge sharing (KS) at the workplace, by underpinning social identity theory. However, when do undesired working conditions, i.e., Perception of Politics (POP), adversely influence these desired outcomes? We deliberately selected 45 firms in the services and manufacturing sectors of Pakistan operating in larger metropolitan cities and prevalent tourist destinations, and actively participating in CSR activities. Thereafter, three self-administered surveys were conducted by employing a time-lagged design with two temporal breaks. A total of 655 surveys were distributed among middle managers across selected firms. Accordingly, it is found that employees who strongly identify with their organizations tend to align their personal values with organizational sustainability efforts and actively participate in environmentally responsible practices. They also demonstrate a greater willingness to share knowledge and enhance the organization’s collective intelligence. However, when employees perceive a high level of political behavior within the organization, their trust in its ethical standards diminishes, leading to various negative attitudes and behaviors in the workplace. This research contributed in two ways to the existing literature: (a) by examining the employees’ understandings of firms’ CSR engagements and their trickle-down effect on EEC and KS, (b) and studying when POP adversely effects the above relationship. Full article

Modern romantic relationships face increasing internal and external pressures that may leave partners emotionally depleted and overwhelmed, yet empirical tools for assessing relationship burnout remain limited, mononormative, and psychometrically underdeveloped. Across two studies, we developed and validated the Antecedents of Relationship Burnout Scale (ARBS), a multidimensional measure grounded in the Job Demands–Resources (JD–R) model and designed to capture the relational demands and resource deficits that precipitate burnout. Study 1 generated and evaluated an initial 51-item pool using a sample of 175 partnered adults. Exploratory factor analysis revealed a clear and robust two-factor structure: Relationship Depletion and Exhaustion (e.g., emotional detachment, diminished appreciation, unmet emotional/sexual needs) and Relational Overload (e.g., external stressors, partner demands, role strain). Study 2 sought to confirm this structure and establish the ARBS’s psychometric validity via a sample of 288 adults. A confirmatory factor analysis supported a 36-item two-factor model with strong internal consistency, full measurement invariance across gender, and theory-consistent associations with relationship satisfaction, therapy participation, and infidelity urge, demonstrating both convergent and predictive validity. Together, these studies introduce the ARBS as the first comprehensive, theoretically grounded measure of the antecedents of relationship burnout, offering a rigorous foundation for future research, assessment, and intervention. Full article

The emergence of multidrug-resistant Staphylococcus aureus underscores the urgent need for novel therapeutic agents targeting essential bacterial pathways. The lipoteichoic acid synthase (LtaS) is crucial for the synthesis of lipoteichoic acid in the cell wall of Gram-positive bacteria and represents a promising and vulnerable target for antimicrobial drug development. This study employed a comprehensive computational pipeline to identify potent inhibitors of the LtaS enzyme. A library of natural compounds was retrieved from the COCONUT database and screened against the crystal structure of the extracellular domain of LtaS (eLtaS) (PDB ID: 2W5R, obtained from the Protein Data Bank) through a multi-stage molecular docking strategy. This process started with High-Throughput Virtual Screening (HTVS), followed by Standard Precision (SP) docking, and culminated in Extra Precision (XP) docking to refine the selection of hits. The top-ranking compounds from XP docking were subsequently subjected to MM-GBSA binding free energy calculations for further filtration. The stability and dynamic behavior of the resulting candidate complexes were then evaluated using 100 ns molecular dynamics (MD) simulations, which confirmed the structural integrity and binding stability of the ligands. Density Functional Theory calculations revealed that screened ligands exhibit improved electronic stabilization and charge-transfer characteristics compared to a reference compound, suggesting enhanced reactivity and stability relevant for hit identification. Finally, ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) profiling was conducted to assess the drug-likeness and pharmacokinetic safety of the lead compounds. These findings support them as promising orally active leads for further optimization. Our integrated approach shortlisted eight initial hits (A–H) that showed interesting scaffold diversity and finally identified two compounds, herein referred to as Compound A and Compound B, which demonstrated stable binding, favorable free energy, and an acceptable Absorption, Distribution, Metabolism, and Excretion, and Toxicity (ADMET) profile. These candidates emerge as promising starting points for developing novel anti-staphylococcal agents targeting the LtaS enzyme that cand be further proved by experimental validation. Full article

Continuous ethanol fermentation is crucial for renewable bio-manufacturing, but delay-induced ethanol inhibition triggers self-oscillations via Hopf bifurcations, undermining productivity and stability. This study investigates instability mechanisms and proposes a washout-filter-aided control strategy. Using Hopf bifurcation theory, the critical delay time τ_c (20.97 h) was quantified, and it confirmed that τ > τ_c (intrinsic τ = 21.72 h) induces oscillations. Closed-loop analysis reveals that the filter extends τ_c to 25.57 h (e.g., K = 2, d = 0.5), expanding the stability margin by modulating ethanol dynamics through phase-shifted feedback. Numerical simulations and experimental validation demonstrate effective oscillation suppression, maintaining steady-state substrate (S* = 84.32 g/L), biomass (X* = 6.92 g/L), and ethanol (P* = 22.02 g/L) concentrations without sacrificing productivity. Unlike conventional methods, the strategy retains the system’s equilibrium structure, resists noise, and requires no additional hardware. This work bridges bifurcation analysis with practical control, offering a robust, scalable solution for industrial continuous ethanol production to mitigate delay-induced instabilities. Full article

Servicescape, the physical and social environment of a service setting, is a critical strategic tool for creating competitive advantage. While its influence on customer loyalty and electronic word-of-mouth (e-WOM) is established, the underlying psychological mechanisms remain inadequately specified. This study addresses this gap by proposing and testing a dual-mediation model grounded in an integrated Stimulus–Organism–Response (S-O-R) framework, with cognitive evaluations informed by Expectancy-Disconfirmation Theory (EDT), distinguishing between affective (service experience) and cognitive (customer satisfaction) pathways. Data were collected from 420 patrons of nature-themed cafés in Nakhon Ratchasima, Thailand, and analyzed using structural equation modeling (SEM-PLS). The results confirm that servicescape significantly enhances both service experience (β = 0.805, p < 0.001) and customer satisfaction (β = 0.816, p < 0.001). However, its effects on customer loyalty and e-WOM are fully mediated through these parallel pathways. Customer satisfaction demonstrated a stronger influence on loyalty than service experience, while both were significant drivers of e-WOM. The findings suggest theoretical contributions by delineating the distinct affective and cognitive processes through which the service environment translates into digital advocacy and loyalty. For managers, this study suggests a strategic framework for allocating resources to foster both shareable experiences and satisfaction-driven loyalty. Full article

This study systematically reviewed 38 peer-reviewed articles (2020–2024) on social media and environmental communication in China following the PRISMA 2020 guidelines. It identified dominant research patterns across themes, theories, methods, and platforms. The field is heavily shaped by behavioral models (e.g., TPB, NAT) and survey-based designs, while institutional dynamics, platform governance, and cross-platform processes remain underexamined. Weibo and WeChat dominate as research sites, whereas short-video platforms like TikTok and Bilibili are emerging but undertheorized. Cross-level frameworks are frequently reduced to individual-level predictors, and social media are often treated as neutral delivery tools. The review highlights the need for multi-level approaches linking individual cognition, media architectures, and governance contexts to better capture how environmental publics form and operate in China’s platformed ecology. This study contributes to the realization of the Sustainable Development Goals by revealing how social media infrastructures mediate environmental awareness, engagement, and systemic change. Full article

Quantum mechanics postulates wave–particle duality and assigns amplitudes of the form $e^{iS/\hslash }$, yet no existing formulation explains why physical observables depend only on the phase of the action. Here we show that if the quantum of action ${\hslash }_{\mathrm{geom}}$ is finite, the classical action manifold $\mathbb{R}$ becomes compact under the identification $S\equiv S+2\pi {\hslash }_{\mathrm{geom}}$, yielding a $U\left(1\right)$ action space on which only modular action is observable. Wave interference then follows as a geometric necessity: a finite action quantum forces physical amplitudes to live on a circle, while the classical limit arises when the modular spacing $2\pi {\hslash }_{\mathrm{geom}}$ becomes negligible compared with macroscopic actions. We formulate this as a compact-action theorem. Chronon Field Theory (ChFT) provides the physical origin of ${\hslash }_{\mathrm{geom}}$: its causal field ${\Phi }^{\mu }$ carries a quantized symplectic flux $\oint \omega ={\hslash }_{\mathrm{geom}}$, making Planck’s constant a geometric topological invariant rather than an imposed parameter. Within this medium, the Real–Now–Front (RNF) supplies a local reconstruction rule that reproduces the structure of the Feynman path integral, the Schrödinger evolution, the Born rule, and macroscopic definiteness as consequences of geometric compatibility rather than supplemental postulates. Phenomenologically, identifying the electron as the minimal chronon soliton—carrying the fundamental unit of symplectic flux—links its spin, charge, and stability to topological properties of the chronon field, yielding concrete experimental signatures. Thus the compact-action/RNF framework provides a unified geometric origin for quantum interference, measurement, and matter, together with falsifiable predictions of ChFT. Full article

Agricultural intensification in greenhouse systems leads to a substantial accumulation of pesticides, yet its role in reshaping soil microbial interactions and their network stability remains poorly understood. This study reveals a critical ecological paradox: contrary to classical theory, greenhouse soils under chronic pesticide contamination exhibit significantly enhanced network stability (quantified as the robustness of network global efficiency under targeted node removal simulations) despite a concurrent sharp decline in bacterial diversity. We investigated this counter-intuitive phenomenon by integrating 16S rRNA sequencing, motif-based network analysis, and resilience modeling. Our findings suggest that this enhanced stability is not explained by species richness but, rather, coincides with a fundamental restructuring of the network’s local interaction architecture. Pesticide residues, acting as a strong deterministic selection pressure, shaped the microbial community into a “low-aggregation, high-redundancy” network topology. This was characterized by a decrease in highly clustered, “brittle” interaction motifs (e.g., M3-2) and an increase in sparse triangular anti-motifs (e.g., M3-1). This new architecture mitigates the risk of cascading failures, thereby elevating the network’s collapse threshold. Triazole fungicides (e.g., Tricyclazole and Hexaconazole) were significantly associated with this structural shift. Our study establishes a novel mechanistic link from pesticide stress to motif-level restructuring and enhanced system stability, offering new insights for assessing the health of highly stressed agricultural ecosystems. Full article

Countermovement jump (CMJ) testing is widely used to monitor neuromuscular function, but trial-to-trial reliability depends on the population and testing ecology. Previous reliability prescriptions have often been derived from male cohorts, risking misapplication to female athletes, whose anthropometry, movement strategies, and testing environments differ. This study applied Generalizability Theory (G-Theory) to quantify the within-session reliability of CMJ metrics in NCAA Division I women’s volleyball, softball, soccer, and lacrosse, aiming to isolate the measurement precision independent of day-to-day biological variance. A fully crossed person × trial G-Theory analysis was performed, with the G-study phase estimating variance components and the D-study phase determining the number of trials required to reach actionable dependability (Φ ≥ 0.80). Force–time data from 103 athletes across 282 jumps were analyzed for 14 commonly monitored metrics. Results show that six concentric and takeoff indices, including force at zero velocity, phase-1 concentric impulse, total concentric impulse, jump height, takeoff velocity, and scaled power, achieved Φ ≥ 0.80 from a single trial across all sports. Second-tier variables, such as eccentric duration, phase-2 impulse, and the modified reactive strength index, stabilized within two to three trials, whereas braking impulse, countermovement depth, and deceleration RFD asymmetry required impractical sampling and were deemed fragile (i.e., requiring a greater number of trials to reach acceptable reliability). Compared with the male data, women exhibited larger between-subject variance and higher single-trial dependability for 11 of the 14 studied metrics. Findings support concise, sex-specific trial prescriptions that prioritize stable metrics and minimize unnecessary testing. Full article

This theoretical paper introduces the Verbal–Cognitive Scaffold (VCS) Model, a cognitively inclusive framework which proposes the cognitive architectures underlying computational thinking (CT). Moving beyond monolithic theories of cognition (e.g., executive-function and metacognitive control models), the VCS Model posits inner speech (InSp) as the predominant cognitive pathway supporting CT operations in neurotypical populations. Synthesizing interdisciplinary scholarship across cognitive science, computational theory, neurodiversity research, and others, this framework articulates distinct mechanisms through which InSp supports CT. The model specifies four primary pathways linking InSp to CT components: verbal working memory supporting decomposition, symbolic representation facilitating pattern recognition and abstraction, sequential processing enabling algorithmic thinking, and dialogic self-questioning enhancing debugging processes. Crucially, the model posits these verbally mediated pathways as modal rather than universal. Although non-verbal architectures are acknowledged as possible alternative routes, their precise mechanisms remain underspecified in the existing literature and, therefore, are not the focus of the current theoretical exploration. Given this context, this manuscript focuses on the well-documented verbal support provided by InSp. The VCS Model’s theoretical contributions include the following: (1) specification of nuanced cognitive support systems where distinct InSp functions selectively enable particular CT operations; (2) generation of empirically testable predictions regarding aptitude–pathway interactions in computational training and performance; and (3) compatibility with future empirical efforts to inquire into neurodivergent strategies that may diverge from verbal architectures, while acknowledging that these alternatives remain underexplored. Individual variations in InSp phenomenology are theorized to predict distinctive patterns of CT engagement. This comprehensive framework, thus, elaborates and extends existing verbal mediation theories by specifying how InSp supports and enables CT, while laying the groundwork for possible future inquiry into alternative, non-verbal cognitive pathways. Full article