Browse Articles

Self-consistent equations for nonempirical tight-binding theory

A new reference state for density functional theory (DFT), termed the independent atom ansatz, is introduced in this work. This ansatz allows for the formally exact representation of electron density in terms of atom-localized orbitals. Self-consistent equations for such states are derived in general and asymptotic forms. The resultant total energy functional is found to closely resemble tight-binding theory. The independent atom ansatz facilitates partial cancellation of inter-atomic electron–electron and nucleus–electron interactions, which allows for the derivation of analytical tight-binding Hamiltonian matrix elements in a weak interaction limit. The formalism provides energy decomposition and charge analyses at no additional cost and links tight-binding, localized orbital, and electronegativity concepts. Numerical accuracy of the total energy functional has been previously reported for hydrogenic systems [Mironenko, J. Phys. Chem. A 127, 7836 (2023)] and is demonstrated here for He2, Li2, Be2, B2, N2, O2, F2, and Ne2. The method accurately reproduces the shapes of potential energy curves, capturing large-basis CCSD(T)-level bond lengths and bond dissociation energies for N2, O2, and F2 using only a minimal basis set. It outperforms both CCSD(T) and some mainstream approximate restricted Kohn–Sham DFT functionals in describing bond dissociation behavior away from equilibrium geometries.

Reply to Bosten and Franklin: Children’s color qualia structure is similar to adults’

Molecularly imprinted electrochemical sensor based on copper 4-amino benzoic acid metal-organic framework for determination of pregabalin: electrochemical and DFT studies

Sit, stand, and swivel: Posture affects visual exploration of panoramic scenes in virtual reality

This 45-minute study, composed of 27 participants (20 female, 7 male) from the University of British Columbia (mean age 21.5 years), systematically examined how posture -- sitting in a stationary chair, standing, or swiveling in a chair -- affects visual exploration of immersive virtual environments. Using 360° panoramic scenes, we analysed eye, head, and torso movements to assess the spatial extent and coordination of visual behavior. Standing posture enabled the greatest movement range and scene coverage, while fixed sitting constrained exploration, resulting in compensatory eye-in-head activity. The swivel condition closely approximated standing, suggesting that rotational freedom, not upright posture alone, drives naturalistic gaze behavior. Analyses confirmed that posture significantly shapes horizontal movement distribution, especially for head and torso. Eyes led head and torso movements, revealing a dynamic, nested coordination pattern. These findings, based on the unique integration of high-precision oculomotor data with a systematic comparison of different postures, extend prior work and emphasise posture’s critical role in shaping embodied vision in virtual reality. Beyond research design implications, our results inform VR-based physical therapy and immersive skill training, highlighting the need to consider physical movement affordances in immersive contexts.

Pathway-specific nonlinear vibrational action spectroscopy with mixed frequency-time domain pulse shaping

Nonlinear spectroscopies utilizing ultrafast, broadband laser pulses are now widely used techniques for the study of molecular structures, interactions, and dynamics with ever increasing molecular specificity. Broadband laser pulses, however, result in signals produced by many overlapping nonlinear pathways that can be challenging to separate. To overcome this, we introduce a mixed time–frequency domain pulse-shaping approach that uses phase-controlled, Boxcar-frequency-filtered pulses to isolate specific nonlinear pathways in a vibrational action-spectroscopy framework. By filtering each pulse to excite a single normal mode and exploiting narrow transitions of cryogenically cooled gas-phase molecular ions, we selectively prepare and detect rephasing, nonrephasing, and two-quantum coherence pathways, the latter of which provides anharmonic information that is typically inaccessible in action-based nonlinear experiments. This strategy establishes a clear and simplified platform for resolving pathway-specific dynamics, laying the foundation for future studies of higher-order quantum control in complex molecular systems in both gas and condensed phases.

Robustness is better assessed with a few thoughtful models than with billions of regressions

Correction: A novel war strategy optimization algorithm based maximum power point tracking method for PV systems under partial shading conditions

Global convergence in a hybrid conjugate gradient projection method for finding solutions of constrained nonlinear equations with applications

In this paper, a hybrid conjugate gradient projection method for finding solutions of constrained nonlinear equations is proposed by integrating both hyperplane projection and hybrid techniques. The key features of this method are as follows: (1) It is characterized by a low storage requirement and relies solely on function values; (2) The designed search direction ensures the sufficient descent property without the need for line search approaches; (3) Under certain reasonable assumptions, the global convergence of the method is established; (4) Experimental results demonstrate that the proposed method outperforms the two existing methods about 75.71%, 85.36%, and 86.43% of benchmark problems in terms of CPU time, the number of function evaluations, and iterations. Furthermore, it is applied to successfully solve the sparse signal restoration problems.

Application of pulsed heating in time-resolved EPR spectroscopy for longitudinal relaxation measurements

Transient or time-resolved electron paramagnetic resonance spectroscopy (TR EPR) is a powerful method for studying various photogenerated paramagnetic species. The use of low-energy quanta, such as terahertz (THz) radiation, as an external stimulus in TR EPR allows the initiation of spin dynamics without generating new paramagnetic species other than those already present in the system. This spin dynamic reflects the return of the system to thermodynamic equilibrium, governed by a spin–lattice relaxation time, T1. The latter, together with a phase memory time, is of paramount importance for the practical implementation of single-molecule magnets and molecular spin qubits. In this work, we present TR EPR spectroscopy with pulsed heating by THz pulses as a versatile spectroscopic method for determining T1 in a wide range of paramagnetic systems. To define the scope of the method, we developed a numerical model based on the Liouville–von Neumann equation, with the equilibrium density matrix defined by the temperature profile of the lattice. Using experimental data obtained for [CoTp2] (cobalt(II) bis[tris(pyrazolyl)borate]) with S = 3/2, we compared the proposed method with two other commonly used techniques: alternating current (AC) magnetometry and pulsed EPR. All three methods were found to be in qualitative agreement and provided complementary information about the relaxation properties. TR EPR spectroscopy showed the orientation dependence of T1. AC magnetometry revealed the dependence of T1 on the value of the external magnetic field, which was attributed in the literature to a field-induced Raman process. Finally, pulsed EPR spectroscopy was found to be biased by strong spectral diffusion.

Investigation on performance of steel strut servo system braced deep excavation adjacent to existing buildings: a case study

Micro and macro structural brain plastic changes induced by sexual experience in male rats

Sexual behavior induces brain plastic changes such as neurogenesis, but few studies have evaluated possible changes in synaptic plasticity produced by sexual experience. In the present study, we assessed whether two aspects of sexual behavior in male rats, sexual incentive motivation and sexual execution in a partner preference test, could induce micro and macrostructural changes in brain regions involved in controlling sexual behavior belonging to the socio-sexual behavior network and the mesolimbic reward circuit. The microstructural changes were evaluated by synaptophysin immunofluorescence expression. We assessed the macrostructural changes using manganese-enhanced magnetic resonance imaging and volume changes by magnetic resonance imaging. Our results indicate that the mesolimbic reward circuit underwent plastic changes at the level of synaptophysin expression, mainly in the partner preference test group. In the socio-sexual behavior network circuit, an increase in brain activation was observed primarily in the sexual incentive motivation group. When analyzing the activation of the whole brain, the statistical map showed a significant increase in weeks 5 and 10 compared to week 1 in the sexual incentive motivation group. The results confirm that different neuroplastic changes, including synaptophysin expression, brain activation, and volume changes, occur during the acquisition of sexual experience.

Solvent-mediated mechanism and kinetics of glucose mutarotation from enhanced sampling simulations

Understanding how solvent molecules participate in chemical reaction mechanisms remains a central challenge in molecular simulations. Here, we investigate the mechanism and kinetics of glucose mutarotation in aqueous solution using a combined well-tempered metadynamics and mean force integration approach, within the framework of canonical transition state theory. We compute free energy landscapes and kinetic rate coefficients for the α → β mutarotation in pure water, as well as in systems representative of water/methanol and water/acetone mixtures. Our simulations indicate that ring opening and closure occur via concerted, solvent-assisted pathways, with ring opening identified as the rate-determining step. The temperature dependence of the predicted kinetic constant is quantitatively consistent with experimental data, while the reactivity modulation by organic co-solvents is captured qualitatively. Overall, the results provide molecular-level insight into solvent-mediated carbohydrate chemistry, demonstrating that the solvent participates in all key reactive steps and highlighting how enhanced sampling techniques can yield mechanistic and kinetic information in explicitly solvated reactive systems.

Incidence and factor for acute acalculous cholecystitis during prolonged gastrointestinal disuse in external duodenal fistula

Development of a risk predictive score for intraoperative hypothermia in pediatric patients: A retrospective cohort study

Objective This study aims to identify the risk factors and develop a risk predictive score of intraoperative hypothermia in pediatric surgery. Methods This was a retrospective cohort study of children under the age of 12 years who underwent anesthesia in 2020 at a super-tertiary care hospital, Thailand. Those with one episode of body temperature 32−35°C or 35.1–35.9°C were defined as having mild and very mild hypothermia, respectively. Data, including patient demographics, clinical information, and perioperative data, were extracted from the hospital information system and were analyzed to identify potential risk factors of hypothermia. The variables associated with intraoperative hypothermia at a p-value <0.2 then were included in the multinomial logistic regression analysis between the two outcomes (mild and very mild hypothermia) (relative risk ratio [RRR] and 95% confidence interval [CI]). The predictors of mild hypothermia were included in the multivariate logistic regression analysis where the association of each risk factor was presented as an odd ratio (OR) and 95% CI. Results Among the 940 eligible patients, 163 (17.34%) and 34 (3.62%) experienced intraoperative very mild and mild hypothermia, respectively. On multivariate analysis, intraoperative very mild hypothermia was associated with ASA physical status >3 (RRR: 6.4[2.9, 14.5]), anesthetic time >2 hours (RRR: 2.6[1.8, 3.8]), and major operation (RRR: 2.0[1.2, 3.4]) whereas intraoperative mild hypothermia was associated with ASA physical status >3 (adj OR: 8.01 [3.13, 20.5]), preoperative temperature >37.2°C (adj OR:3.3[1.5, 7.4]), anesthetic time >2 hours (adj OR:3.1[1.3, 7.4]), and no active warming (adj OR:9.3[2.9, 29.8]). A risk predictive score of mild hypothermia using a cut-point of 1.0 had a sensitivity and specificity of 85.9% and 52.53% respectively, with an area under the receiver operating characteristic curve of 0.78. Conclusions Application of forced-warming after prolonged anesthesia, especially in high morbidity child, can reduce the risk of intraoperative hypothermia during pediatric surgery.

Polarity-dependent dual-mode AlN-embedded RRAM with improved stochastic switching and synaptic modulation for neuromorphic computing

We present a Pt/Al/TaOx/AlN/Al2O3/Pt resistive random-access memory device that enables polarity-dependent, dual-mode switching within a single cell, exhibiting abrupt digital and gradual analog conductance modulation. The incorporation of an AlN layer between the TaOx switching layer and the Al2O3 tunnel barrier (with a thickness of 1.2 nm) functions as a built-in current limiter, promoting controlled filament formation and inherent self-compliance without the need for external circuitry. Under positive bias, localized soft breakdown near the Al/TaOx interface induces abrupt switching with a high ON/OFF ratio and reliable endurance over 100 cycles. Conversely, negative bias facilitates stepwise filament growth near the AlN/Al2O3 interface, enabling smooth analog switching and precise control of multilevel conductance. Using an incremental step pulse with a verify algorithm, the device achieved 6-bit resolution, excellent analog endurance over 500 cycles, and retention >10 000 s. In addition, the device successfully emulates biologically relevant forms of synaptic plasticity, including spike-amplitude-dependent, spike-rate-dependent, and spike-width-dependent—under fixed amplitude stimulation conditions. The device’s layered architecture not only ensures stable switching behavior but also enhances device reliability by suppressing current overshoots. These results highlight the device’s strong potential for energy-efficient, hardware-level neuromorphic computing, as demonstrated by a multilayer perceptron that achieved 93.5% classification accuracy on the Modified National Institute of Standards and Technology dataset using experimentally extracted conductance values without quantization or preprocessing.

Lithium chloride at environmental concentrations impairs microtubule function and promotes genotoxicity in Allium cepa

Abstract The growing demand for lithium, driven by the energy transition and widespread use of rechargeable batteries, has raised concerns about its environmental release. This study assessed the toxicological effects of lithium chloride (LiCl) at environmentally relevant concentrations using the Allium cepa bioassay. While lithium’s genotoxicity at high concentrations is known, its effects at levels typical of aquatic systems (up to 4 mg/L) remain poorly understood. A set of biomarkers was applied to evaluate cytotoxicity, genotoxicity, oxidative stress, and in silico molecular interactions. LiCl exposure significantly reduced the mitotic index, indicating cytotoxic effects via impaired cell division. Increased chromosomal aberrations and nuclear abnormalities were observed, particularly at 4 mg/L, suggesting genotoxicity. However, the Comet assay revealed minimal DNA strand breaks, pointing to an aneugenic mechanism likely caused by mitotic spindle disruption rather than clastogenic effects. Cell cycle analysis showed reduced metaphase and increased anaphase frequencies, reinforcing the hypothesis of chromosomal missegregation. In silico modeling demonstrated strong interactions between Li + ions and tubulin, potentially affecting spindle stability. Additionally, altered superoxide dismutase (SOD) activity indicated oxidative stress involvement. Overall, lithium at environmentally realistic concentrations induces cytotoxic and genotoxic effects in A. cepa , primarily through aneugenic mechanisms linked to oxidative stress and microtubule disruption.

Whole genome sequencing analysis of antibiotic resistant genes of Shigella species: A systematic review and meta-analysis

Background In developing nations, Shigella species are the leading cause of epidemic dysentery, especially among children under five. Antibiotic resistance has spread quickly among Shigella species as a result of inappropriate antibiotic use, inadequacies of diagnostic facilities, unhygienic conditions, and insufficient healthcare practices. This review aimed to describe AMR genes of Shigella species analyzed globally via whole genome sequencing (WGS). Methods Relevant papers were found via a literature search using the databases of Google Scholar, Web of Science, PubMed, and Scopus. Full-text primary studies published in English, WGS, Shigella serogroup, and AMR gene statistics had to be included in the articles. The comprehensive meta-analysis software was used for data analysis. The Der Simonian–Laird random effect model was utilized and statistical heterogeneity between studies is measured by the I 2 and Cochran’s Q test. Results Of the studies, resistant genes of S. flexneri was more studied and characterized. The overall prevalence of antibiotics resistance genes was in the range of 1.7% to 46.9% with gyrA S83 L was the most frequent isolated revealed this gene as predominant in the quinolones resistant gene of S. sonnei. It was followed by mphA (resistant to macrolides) for S. flexneri, and sul2 (resistant to folate synthesis inhibitors) for S. dysenteriae and S. boydii . Pooled prevalence of AMR gene in Shigella species significantly varied among the studies (p = 0.001). There was no significant amount of heterogeneity in S. bodyii (Q (4)) =1.938. p = 0.747, I 2  = 0%) however in S. flexneri (I 2  = 63%) and S. sonnei (I 2  = 84%) showed high heterogeneity within the studies. Conclusion Generally, there was considerable variation in the pooled prevalence of the AMR gene in Shigella species among the studies, with S. flexneri and S. sonnei showing the highest levels of heterogeneity. The effectiveness of treatment is seriously threatened by Shigella’s resistance to antibiotics. Therefore, it is imperative that Shigella species resistance be continuously monitored globally.

Revealing multiple sources of a uranyl Raman fingerprint peak in nitric acid solution through first-principles calculations

Separation of uranium in nitric acid solution is a key issue in the solvent extraction of spent fuel. However, the structures of uranyl complexes in aqueous conditions containing nitric acid remain unclear. The Raman peak generated by uranyl at 870 cm−1 is considered an important internal standard for detecting uranyl complexes, which can be used for identifying the form of uranium in solution. In this work, first-principles calculations reveal multiple origins for this vibrational feature, attributing it to simultaneous contributions from [UO22+ · 5H2O], [UO2NO3+ · 3H2O], and [UO2NO3+ · 4H2O]. Crucially, all three species share pentacoordinate uranyl centers, with interaction mechanism analysis confirming bidentate nitrate coordination in the dominant [UO2NO3+ · 3H2O] configuration. Moreover, the quantitative agreement between computed spectra and experimental benchmarks validates our solvation-corrected theoretical model and method. These findings provide atomic-level insight into the structure of uranyl complexes in nitric acid solution, establishing a predictive framework for interpreting vibrational spectroscopic signatures in complex nuclear waste streams.

ADME related patterns to predict the prognosis and immune therapy of colon cancer patients

Benchmarking large-language-model vision capabilities in oral and maxillofacial anatomy: A cross-sectional study

Background Multimodal large-language models (LLMs) have recently gained the ability to interpret images. However, their accuracy on anatomy tasks remains unclear. Methods A cross-sectional, atlas-based benchmark study was conducted in which six publicly accessible chat endpoints, including paired “deep-reasoning” and “low-latency” modes from OpenAI, Microsoft Copilot, and Google Gemini, identified 260 numbered landmarks on 26 high-resolution plates from a classical anatomic atlas. Each image was processed twice per model. Two blinded anatomy lecturers scored responses, including accuracy, run-to-run consistency, and per-label latency, which were compared with χ² and Kruskal–Wallis tests. Results Overall accuracy differed significantly among models (χ² = 73.2, P  < 0.001). OpenAI o3 achieved the highest correctness (53.1%), outperforming its sibling GPT-4o and both Copilot variants, but required the longest inference time. Musculoskeletal structures were recognised more accurately than neurovascular targets, reflecting the greater visual complexity of fine vessels and nerves. Consistency ranged from 43.5% (Gemini Flash) to 65.0% (GPT-4o); deeper modes improved stability for Copilot and Gemini but not accuracy. Median per-label latency spanned three orders of magnitude, from 0.5 s for Gemini Flash to 33 s for o3. Conclusions Currently, publicly available multimodal LLMs can only moderately identify oral and maxillofacial landmarks, and no endpoint is sufficiently reliable to serve as a stand-alone answer key. Higher accuracy was achievable with a trade-off in latency, highlighting the need for domain-specific tuning and human oversight. This atlas benchmark study introduced here provides a reproducible yardstick for future model refinement and educational integration.