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Human emotional odours influence horses’ behaviour and physiology
Olfaction is the most widespread sensory modality animals use to communicate, yet much remains to be discovered about its role. While most studies focused on intraspecific interactions and reproduction, new evidence suggests chemosignals may influence interspecific interactions and emotional communication. This study explores this possibility, investigating the potential role of olfactory signals in human-horse interactions. Cotton pads carrying human odours from fear and joy contexts, or unused pads (control odour) were applied to 43 horses’ nostrils during fear tests (suddenness and novelty tests) and human interaction tests (grooming and approach tests). Principal component analysis showed that overall, when exposed to fear-related human odours, horses exhibited significantly heightened fear responses and reduced interaction with humans compared to joy-related and control odours. More precisely, when exposed to fear-related odours, horses touched the human less in the human approach test (effect size: Rate Ratio(RR)=0.60 ± 0.24), gazed more at the novel object (RR = 1.32 ± 0.14), and were more startled (startle intensity – Cohen’s d = −0.88 ± 0.39; and maximum heart rate – Cohen’s d = 1.16 ± 0.47) by a sudden event. These results highlight the significance of chemosignals in interspecific interactions and provide insights into questions about the impact of domestication on emotional communication. Moreover, these findings have practical implications regarding the significance of handlers’ emotional states and its transmission through odours during human-horse interactions.
AO-HEOM: A computational platform for non-Markovian quantum dissipative dynamics in atomic orbital spaces
Building upon our previous implementation for the hydrogen atom [Y. Zhang and Y. Tanimura, J. Chem. Phys. 163, 184108 (2025)], we have developed source code for atomic orbital–hierarchical equations of motion (AO-HEOM), a quantum mechanical framework based on HEOM formulated within an AO basis. This method enables numerically “exact” simulations of atomic systems coupled to three independent thermal baths, under both isotropic and anisotropic conditions, while preserving rotational symmetry. AO-HEOM rigorously accounts for system–bath entanglement, which is critical for describing the quantum nature of environmental interactions. Incorporating spatial bath degrees of freedom significantly increases the computational cost in the HEOM formalism because of the proliferation of electronic states at high temperatures and the inclusion of Matsubara frequency terms at low temperatures. To address this challenge, we developed a graphics processing unit-accelerated implementation. As a demonstration, we computed the emission spectra of He I and He II atoms. The source code is broadly applicable to atomic systems and enables detailed analysis of electronic transitions in thermal environments.
Sexual and reproductive health challenges among street adolescents in Sylhet city, Bangladesh: A cross-sectional study
Background Street adolescents often engage in early sexual activity, have multiple partners, and are at high risk of sexual abuse and exploitation. Despite the significance of this issue, there is a critical gap in understanding the sexual and reproductive health (SRH) needs, practices, and challenges of this marginalized population in Bangladesh, which this study aimed to explore. Methods A cross-sectional study was conducted from August to December 2023, involving 311 street adolescents aged 16–19 years in Sylhet City Corporation, Bangladesh. Data were collected through face-to-face interviews using a semi-structured questionnaire. The questionnaire covered sociodemographic characteristics, pubertal changes, SRH status, and SRH-seeking behaviors. Results Of all participants, 62.8% were males and 37.2% were females, with a mean age of approximately 17.3 years for both sexes. Sexual intercourse was reported by 32.56% of participants, with a significant gender disparity (76.79% females vs. 6.35% males, p < 0.001). Contraceptive use was low at 14.14%, primarily condoms. Among female participants who ever had sex, 81.13% reported pregnancy, with 50.67% having had an abortion. Knowledge of sexually transmitted diseases (STDs) was alarmingly low, with only 2.33% aware of transmission methods. Less than half (45.97%) of participants utilized SRH services. Sexual abuse was reported by 61.79% of participants. Logistic regression revealed that younger age (Adjusted Odds Ratio [AOR]: 0.62, 95% CI: 0.48–0.79), being female (AOR: 9.10, 95% CI: 3.58–25.3) and longer duration of stay on the streets (AOR: 1.14, 95% CI: 1.02 to 1.27) were associated with higher odds of experiencing sexual abuse. Conclusion Street adolescents in Sylhet City face severe SRH challenges, including high rates of sexual abuse, low contraceptive use, and limited STD knowledge, with significant gender disparities, which should be addressed through appropriate and urgent interventions.
Perturbatively corrected ring-polymer instanton rate theory rigorously captures anharmonicity and deep tunneling
We derive a perturbatively corrected instanton rate theory in the ring-polymer framework (RPI+PC), which significantly enhances the accuracy of instanton theory by using third and fourth derivatives of the potential to capture anharmonic effects. Instanton theory is a rigorous semiclassical method that extends transition-state theory by including quantum tunneling along a well-defined optimal tunneling pathway. However, the standard leading-order instanton theory (RPI) neglects anharmonicity perpendicular to this tunneling path. The RPI+PC method described here corrects this using only local information along the same instanton trajectory as the leading-order theory. Hence, RPI+PC does not require a global potential energy surface and is readily applicable in combination with ab initio electronic-structure methods. The derivation of the RPI+PC result is performed within the flux-correlation formalism using standard techniques from asymptotic analysis, and the final rate expression is shown to be independent of the choice of dividing surface. We demonstrate that RPI+PC represents a systematic improvement over RPI by analyzing its asymptotic properties in the semiclassical limit (ℏ → 0 with total thermal time τtot = βℏ kept constant) and illustrate its improved performance on a series of model systems for which exact results are available for comparison, including the collinear H + H2 reaction and its isotopic variants.
Entrepreneurial intention of students: The role of digital tools and personal factors in entrepreneurship education
Education is changing due to digital transformation, which is especially significant for entrepreneurship since students’ readiness to start their own businesses may be assessed by their proficiency with digital technologies. An experimental group educated with the AI-based digital tool KABADA, and a control group trained through traditional workshops in a quasi-experiment with 819 students from Southern and Central-Eastern Europe were compared to examine this relationship. The effects of gender, education, past entrepreneurial experience, self-evaluation, and motivation on entrepreneurial intention were tested using ordinal logistic regression. Compared to traditional workshops, the results demonstrate that digital tools significantly increase students’ entrepreneurial intention; the best indicators were self-assessment and entrepreneurial desire. While education level had no discernible impact, gender and previous entrepreneurship experience were also important factors. The findings show that one of the most effective ways to encourage entrepreneurial purpose is to incorporate digital tools into entrepreneurship education. This study emphasizes the importance of students acquiring digital skills in order to increase their preparedness for entrepreneurship in technology-driven economies.
How to efficiently characterize the interaction pathways of protein–ligand recognition? A comparative analysis on enhanced sampling approaches
It is evidenced that many elaborately designed molecules that can interact well with the binding pocket of their target fail to exhibit activity in wet-lab experiments. This may associate with the interacting process of drug-target recognition. To efficiently characterize the drug-target interacting process, various enhanced sampling technologies have been proposed; yet, very few studies have systemically investigated whether the settings of these simulations are favorable to characterize the purposed tasks. Here, by comparing two popular enhanced sampling technologies, namely, the well-temped metadynamics and random acceleration molecular dynamics (RAMD), we systemically investigate the strategies to efficiently characterize the dissociating process of protein–ligand interactions. Two target families are employed for the analysis, including the kinase family (represented by TRK1) that represents the interaction-pathway obvious systems and the nuclear receptor family (represented by THRβ) that represents the interaction-pathway unobvious systems. Our results suggest that (1) in terms of maintaining stability of the protein structure, MetaD at various simulation conditions and RAMD with a large random force are good choice; (2) drug residence time derived from both MetaD and RAMD based on various parameters shows reasonable correlation to the experimental binding strength of the ligands, but RAMD usually runs with much less simulation time; and (3) both enhanced sampling methods result in reasonably consistent pathway preference for the two target families. Taken together, it will be much time-saving to utilize RAMD with high random force for interaction pathway exploration for both the pathway obvious and unobvious systems if the protein keeps stable in the simulation; otherwise, MetaD with a high bias factor is proposed to balance the computational accuracy and efficiency for the exploration.
Effects of breathing exercise and thoracic techniques on pain and disability in low back pain: A systematic review and meta-analysis
Purpose The objective of this study was to systematically review the effectiveness of thoracic-focused interventions, including breathing exercises and thoracic manual techniques (mobilization, high-velocity low-amplitude manipulation, and release techniques), on pain and disability in patients with low back pain (LBP). Methods PubMed, Scopus, Web of Sciences, ProQuest, Ovid, Physiotherapy Evidence Database (PEDro), Cochrane Central Register of Controlled Clinical Trials (CENTRAL), and Google Scholar were searched without language restrictions. Clinical trials with control groups on pain and disability in low back pain patients focusing on the efficacy of breathing exercises or thoracic technique were included. In total, 31 studies contributed to the meta-analysis for pain and 24 for disability. Results Pooled analyses using Morris’ dppc demonstrated a statistically significant, small effect for pain reduction (dppc = −0.35, 95% CI = −0.46 to −0.23) and a large effect for disability improvement (dppc = −0.71, 95% CI = −0.86 to −0.57) when compared with control groups. Thoracic manual techniques showed larger effects on both pain and disability compare to breathing exercises. However, substantial statistical heterogeneity (I² > 85%) persisted in most analyses. Conclusion Breathing and thoracic manual techniques may be effective in reducing disability and, to a lesser extent, pain in patients with LBP, but the overall certainty of evidence is low. However, the quality of the evidence is low. Variability in treatment protocols, study quality, blinding, and outcome measures likely contributed to inconsistencies. Further high-quality trials with standardized protocols are needed to confirm these findings and inform clinical practice.
Analytic rate theory of polariton relaxation that explains long polariton lifetime
Hybridization of a molecular exciton with a quantized photon creates a polariton. Despite extensive experimental investigations, the apparent lifetime of the exciton–polariton is not well-understood. We examined the steady-state population dynamics for a Holstein–Tavis–Cumming Hamiltonian to illuminate the long-term polaritonic dynamics and lifetime of the exciton–polariton in an optical cavity. For a realistic description of polariton relaxation, cavity loss and various exciton decay channels are included in the model. We found that in the presence of weak but finite exciton loss, the apparent lifetime of the lower polariton coincides with the out-of-cavity exciton lifetime and is independent of cavity-matter detuning. This is a simple explanation for the experimentally observed lifetimes for exciton polaritons and theoretically justifies the dark state reservoir hypothesis. Furthermore, if the upper polariton is initially populated, the system reaches the steady state very quickly, leading to single-exponential polariton relaxation. Starting from the lower polariton leads to a longer pre-steady-state time period, leading to double-exponential relaxation. Finally, we considered the effect of site orientational disorders and the exciton frequency disorderers. Under the collective limit, the effects of this disorder can be included in Fermi’s golden rule population dynamics without explicit sampling. For the exciton energy disorders, numerical calculations are needed. Our theoretical framework is applicable to interpret exciton–polariton experiments, especially related to the measured apparent lifetime of polaritons.
Mobile phone MIMO antenna array miniaturization-based low SAR research in the combined EMF
Due to the diversification of media functions of mobile phones, users can make calls and access the internet simultaneously, which has significantly increased the usage time of mobile phones. The exposure dose of the users in the combined electromagnetic fields (EMF) should be further quantified to better evaluate the public exposure safety. Different from most conventional EMF safety studies that only focus on a single frequency, this work not only discusses the mobile phone simultaneously operated in fourth-generation (4G) and fifth-generation (5G) mobile communications radiation impact on users, but also verifies that the miniaturized mobile phone multiple-input multiple-output (MIMO) antenna array can significantly reduce the specific absorption rate (SAR) absorbed by users. In this article, a miniaturized mobile phone MIMO antenna array is employed as the radiation source, and multi-pose human models are established to simulate the practical utilization of a smartphone. A systematic analysis of the SAR absorbed by the human model is conducted in both single and combined EMF scenarios. The results indicate that the peak SAR in various tissues under multi-frequency exposure is 1.02 to 15.85 times higher than that under single-frequency exposure.
Thermal conductivity of commodity polymers under high pressures
Heat flow in polymers under high-pressure conditions is essential for a range of applications, from aerospace and deep-sea engineering to common lubricants. However, the complex relationship between pressure, P, the thermal transport coefficient, κ, and polymer architecture poses substantial challenges to both experimental and theoretical investigations. In this work, we study the pressure-dependent thermal transport properties of a widely used commodity polymer—poly(methyl methacrylate)—using a combination of all-atom molecular dynamics simulations and semi-analytical approaches. We report both classical and quantum-corrected estimates of κ, both of which show an increase with increasing pressure P. The quantum-corrected approach, which is directly comparable to experiment, reveals that as the pressure increases from 1 atm to 10 GPa, κ rises by nearly a factor of four, from 0.21 to 0.80 W m−1 K−1. By comparison, experimental measurements report an increase from 0.20 to 0.55 W m−1 K−1 over the same pressure range. To better understand the mechanisms behind this increase, we disentangle the contributions from bonded and nonbonded monomer interactions. Our analysis shows that nonbonded energy-transfer rates increase by a factor of six over the pressure range, while bonded interactions show a more modest increase—about a factor of three. This observation further consolidates the fact that nonbonded interactions play the dominant role in dictating the microscopic heat flow in polymers. These individual energy-transfer rates are also incorporated into a simplified heat diffusion model to predict κ. The results obtained from different approaches show internal consistency and align reasonably with available experimental data. In addition, some data for polylactic acid are presented.
Comparing snowball sampling and RDS: A methodology and case study
Both snowball sampling and Respondent Driven Sampling (RDS) are used to sample hard-to-reach populations. Snowball sampling was initially developed as a probability sampling method, but in practice, it is widely used as a non-probabilistic sampling method. RDS was developed to address the limitations of snowball sampling and can be used to approximate a probability sampling method in practice. Therefore, RDS is often recommended for bio-behavioral surveys (BBS) for surveillance of HIV, viral hepatitis, and STIs among key populations. In some settings, simpler and cheaper monitoring are desired. WHO and UNAIDS are developing a simplified and rapid bio-behavioral survey methodology, a version of snowball sampling to use when RDS is infeasible. In this paper, we use data-based simulations to examine the potential similarities and differences between results from a snowball sample with recruitment initiated from a health service and samples recruited through RDS methodology.
Fragmentation dynamics of CS2 dications and trications following S 2p ionization
We present the results from a detailed study of the fragmentation dynamics of CS22+ and CS23+, formed in intense femtosecond soft x-ray pulses above the sulfur 2p edge, primarily through single core photoionization from the S 2p site, and subsequent Auger–Meitner decay(s). By combining three-dimensional velocity map imaging with covariance analysis, we determine the relative momenta of the ions produced in each two- and three-body fragmentation channel, at significantly higher ion count rates than conventional coincidence measurements. We shed new light on the wide range of fragmentation channels observed from the CS2 dication and trication, including channels that involve ionization-induced bond formation and fragmentations producing undetected neutral cofragments. In the latter case, a “native frames” approach is used to isolate contributions from concerted and sequential fragmentations and extract dynamical information about each step of a concerted fragmentation process. While dications often fragment sequentially, the trication is dominated by concerted fragmentation. The main trication fragmentation channel into S+ + C+ + S+ can be well-approximated by classical Coulombic simulations of the ground-state geometry distribution, reflecting both the nature of the trication potential energy surface and the rapid multiple ionization prior to substantial structural dynamics. This study demonstrates ways in which fundamental insights into the fragmentation dynamics of polycations following x-ray ionization may be extracted, which will be beneficial to future studies that employ time-resolved x-ray Coulomb explosion imaging to study ultrafast photochemistry.
Transforming scholarly landscapes: The influence of large language models on academic fields beyond computer science
Large Language Models (LLMs) have ushered in a transformative era in Natural Language Processing (NLP), reshaping research and extending NLP’s influence to other fields of study. However, there is little to no work examining the degree to which LLMs influence other research fields. This work empirically and systematically examines the influence and use of LLMs in fields beyond NLP. We curate 106 LLMs and analyze ∼148k papers citing LLMs to quantify their influence and reveal trends in their usage patterns. Our analysis reveals not only the increasing prevalence of LLMs in non-CS fields but also the disparities in their usage, with some fields utilizing them more frequently than others since 2018, notably Linguistics and Engineering together accounting for ∼45% of LLM citations. Our findings further indicate that most of these fields predominantly employ task-agnostic LLMs, proficient in zero or few-shot learning without requiring further fine-tuning, to address their domain-specific problems. This study sheds light on the cross-disciplinary impact of NLP through LLMs, providing a better understanding of the opportunities and challenges.
Geometric features and a neural network classifier for detecting melting-like transitions in clusters
Melting-like transitions in clusters are normally identified by a peak in the heat capacity curve C(T) at T = Tc. Computing C(T) requires costly simulations with millions of steps. We discuss four easily calculated functions of temperature that help detect and characterize melting-like transitions. The first is WU, the width of the potential energy distribution, which shows an abrupt increase near Tc. The other three are statistics of the ordered set of N(N − 1)/2 interatomic distances rij: (i) a measure of dissimilarity to the lowest energy configuration, or global minimum; (ii) the number of rij’s found in a small interval centered around (r1 + r2)/2, where r1, r2 are the positions of the first two peaks in the pair distribution function; and (iii) a measure of non-uniformity in the distribution of the rij’s. Numerical tests with empirical potentials that model three types of bonding (van der Waals, covalent, and metallic) show that these four functions produce estimates for the middle of the melting region in general agreement with Tc. An artificial neural network classifier is used to calculate the solid fraction FS(T) and find the solid–liquid coexistence region between freezing and melting temperatures, [Tf, Tm]. Inflection points in the third function and FS(T) are very sensitive indicators of phase transitions. Estimates of Tc obtained from them converge one to three orders of magnitude faster, in simulation time, than those obtained with C(T).
Compact high power, medium energy electron accelerator for treatment of per- and polyfluoroalkyl contamination in water
Electron beam water treatment (EBWT) is a promising approach for remediating water contaminated with per- and polyfluoroalkyl substances (PFAS). In this study, we assess the feasibility of using a compact, high-average-power superconducting radio-frequency (SRF) photoinjector as a source for delivering the electron beam parameters required to initiate PFAS degradation. Our goals are twofold: first, to determine whether such a system can achieve the necessary dose and dose rate through sufficient beam energy and power; and second, to establish an experimental platform for investigating how different beam conditions affect degradation pathways. We envision a compact and mobile SRF-based accelerator that can be deployed at contamination hotspots - such as the former Berlin airport Tegel - offering significantly faster and potentially more effective treatment than conventional remediation methods. Based on theoretical analysis and computational modeling, we identify the SRF photoinjector at Helmholtz-Zentrum Berlin (HZB) as a suitable R&D platform. To support experimental validation, we developed a proof-of-concept in-air beamline optimized for balancing dose deposition and thermal management. This setup will enable the systematic study of key operational parameters, including dose rate, energy deposition, and thermal stability, under controlled beam conditions.
Ferroelectric domain relaxation enables reliable multi-bit storage in hafnia-based memristors
We demonstrate reliable triple-level cell operation in HfZrO2-based ferroelectric memristors by precisely modulating partial-switching voltages to define eight distinct polarization states. Although stable multi-bit storage is achieved, endurance degradation arising from polarization fatigue remains a major limitation. To mitigate this issue, we introduce a domain-recovery strategy that employs interleaved high-voltage pulses combined with electrically quiescent break intervals. This approach restores polarization states by alleviating domain-wall pinning, enabling endurance exceeding 106 cycles. Notably, we find that spontaneous domain relaxation during short idle periods further contributes to fatigue recovery, whereas excessively long breaks induce domain disorientation. These findings reveal the critical roles of both electrical and time-controlled recovery in stabilizing ferroelectric switching behavior. Our results provide a practical route to enhancing the reliability of high-density ferroelectric memory and yield new physical insights into fatigue dynamics under multi-level operation.
Association of handgrip strength asymmetry and weakness with successful aging among older adults in China
Background Successful aging (SA) is important for the increasing population aging. The role of handgrip strength(HGS) asymmetry and weakness in successful aging requires further clarification. This study aimed to elucidate the association of HGS asymmetry and weakness with successful aging in older adults. Methods We included participants aged ≥60 years from the 2015 China Health and Retirement Longitudinal Study (CHARLS).SA absence of major diseases, absence of major chronic diseases, no impairment in physical function, high cognitive functioning, good mental health, and active participation in life. HGS asymmetry and weakness were measured using the maximum value of the HGS. Logistic regression modeling was used to examine the association of individuals with HGS asymmetry and weakness with SA. Restricted cubic spline (RCS) modeling was used to explore potential nonlinear relationships. Results Of the 5,031 individuals included, the median age of the study population was 67 years IQR: 63−73 years, 45.6% female. Only 6.3% met the criteria for successful aging. HGS asymmetry (OR = 0.597,95% CI: 0.472–0.754) and weakness (OR = 0.643,95% CI: 0.417–0.964) were both independent influences on SA. Participants were less likely to have SA when both HGD asymmetry and weakness were present (OR = 0.426,95% CI: 0.240–0.757). Further subgroup analyses revealed significant associations between HGS status and each of the components of SA, particularly with regard to physical functioning. There was an inverse U-shaped relationship between HGS asymmetry and SA. Conclusion HGS asymmetry is associated with a reduced likelihood of weak SA. Improving or maintaining HGS symmetry and weakness may contribute to SA in older adults.
Effect of ice nucleating proteins on the structure-property relationships of ice: A molecular dynamics study
Ice-nucleating proteins (INPs) are a unique class of biological macromolecules that catalyze the freezing of supercooled water with remarkable efficiency, exceeding that of most other known heterogeneous nucleators. Their exceptional efficiency has motivated applications across diverse sectors, including agricultural frost protection, food processing and packaging, biomedical cryopreservation, and even strategies for mitigating glacier ice loss. The ice-nucleation performance of INPs and the mechanical behavior of the ice they produce depend strongly on their structural and biochemical characteristics. However, the links between INP properties, the resulting ice microstructure, and their mechanical behavior have yet to be systematically established. In this study, coarse-grained molecular dynamics (CGMD) simulations using the machine-learned ML-BOP potential are employed to investigate how varying INP configurational parameters, including INP length and number of INPs, influence the ice-nucleation temperature, the resulting ice microstructure, and the mechanical behavior of the formed ice under creep tensile loading. We find that, depending on the length and number of INPs, they can significantly raise the ice-nucleation rate while altering the grain structure of ice. Our simulations reveal that INP-assisted nucleation leads to faster stabilization of the resulting polycrystalline ice composed of hexagonal ice (ice Ih) and cubic ice (ice Ic) as compared to nucleation in pure water. Moreover, a higher number of INPs and smaller ice grain sizes reduce the overall yield stress, while promoting diffusion-accommodated grain boundary sliding creep. These findings provide molecular-level insights into how INPs influence both the nucleation process and the mechanical behavior of ice, highlighting a pathway to engineer ice with tailored stability for real-world settings, including human activities and infrastructure in polar and icy environments.
Polyester microfibers delay growth of cherry tomato (Solanum lycopersicum var. cerasiforme) throughout the lifecycle
Agroecosystems are increasingly recognized as major basins for terrestrial microplastics. Many agricultural practices have led to high loading of plastic mulch films, synthetic microfibers, and other microplastics onto fields. There is demonstrated ability for microplastics to influence soil properties and plant productivity, but these effects are highly variable by species, soil, and life stage. Here, we conduct a lifecycle assessment of how polyester microfibers, a dominant biosolid contaminant, affect the development of cherry tomato ( Solanum lycopersicum var. cerasiforme ) in peaty growing medium. We distinguish the importance of physical and chemical characteristics of microfibers by comparing plants in soil containing microfibers at 0.5% soil weight, or soil watered with leachate isolated from microfibers. We find that polyester microfibers reduce emergence success by 11%, delay flowering and ripening time by several days, and lead to a reduction in biomass in adult plants. However, we observe no effect of chemical additives from microfibers on plant development. We also note a decrease in soil water holding capacity from microfibers. Overall, we conclude that physical microfiber properties or physical/chemical interactions are the likely drivers of biological effects. These findings emphasize that microfibers have impacts beyond mineral soils, and consequences at every stage of plant development.
Dynamic slowdown and spatial correlations in viscous silica melt: Perspectives from dynamic disorder
The dynamic slowdown in glass-forming liquids remains a central topic in condensed matter science. Here, we report a theoretical investigation of the microscopic origin of the slowdown in amorphous silica, a prototypical strong glass former with a tetrahedral network structure. Using molecular dynamics simulations, we analyze atomic jump dynamics, the elementary structural change processes underlying relaxation. We find that the jump statistics deviate from Poisson behavior with decreasing temperature, reflecting the emergence of dynamic disorder in which slowly evolving variables modulate the jump motion. The slowdown is species-dependent: for silicon, the primary constraint arises from the fourth-nearest oxygen neighbor, while at lower temperatures, the fourth-nearest silicon also becomes relevant; for oxygen, the dominant influence comes from the second-nearest silicon neighbors. As the system is cooled, the jump dynamics become increasingly slow and intermittent, proceeding in a higher-dimensional space of multiple slow variables that reflect cooperative rearrangements of the network. Species-resolved point-to-set correlations further reveal that the spatial extent of cooperative relaxation grows differently for silicon and oxygen, directly linking their relaxation asymmetry to the extent of collective motion. Together, these results provide a microscopic framework linking dynamic disorder, species-dependent constraints, and cooperative correlations, offering deeper insight into the slowdown of strong glass-forming networks.