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An intelligent approach for early smoke/fire detection using vision sensors in smart cities

Radiological characteristics in coronal and sagittal planes and short-term postoperative outcomes in patients with lumbar disc herniation accompanied by sciatic scoliosis

Bioanalysis of amphetamines in alternative matrices using a sensitive and validated liquid chromatography-tandem mass spectrometry method and its application to real samples

Abstract Amphetamines abuse remains a major concern in both clinical and forensic toxicology. While conventional matrices like blood and urine are commonly used, their detection window is limited. This study aimed to validate a UHPLC-ESI-MS/MS method for amphetamines detection across both conventional and alternative biological specimens and apply it to real patient samples. A validated UHPLC-ESI-MS/MS method was used to quantify amphetamines in whole blood, urine, oral fluid, scalp hair, and fingernail specimens collected from fifty amphetamine abusers. Method validation followed international guidelines, assessing parameters including linearity, sensitivity, precision, and carry-over. Decontamination protocols and wash analyses were performed to exclude external contamination for keratinized matrices. The method demonstrated excellent linearity (r² = 0.995–0.998) and sensitivity (LOD = 2 ng/mL or ng/mg) across all matrices. Oral fluid showed strong correlation with recent drug use and was a reliable non-invasive alternative to blood and urine. Hair yielded the highest amphetamine concentrations due to melanin binding, whereas nail showed lower levels but provided a complementary window for retrospective exposure. Simultaneous quantification of amphetamines in five matrices provides a comprehensive assessment of both recent and chronic drug use. Hair remains the superior matrix for long-term detection, but nail offers valuable supplementary information. Oral fluid emerged as a practical and reliable tool for recent exposure monitoring. This is the first study to report amphetamine concentrations in all five matrices from the same individuals, offering critical insights for toxicological interpretations.

Effects of skewing collision cells on transport properties in multiparticle collision dynamics simulations

Multiparticle collision dynamics (MPCD) is a mesoscale simulation technique that uses a simplified solvent to model hydrodynamic interactions. Rather than interacting through pairwise forces, MPCD solvent particles undergo momentum-exchanging collisions within spatially localized cells according to prescribed rules. The conventional MPCD algorithm employs cubic collision cells, but this choice is not optimal for systems that are most naturally described using skewed simulation boxes. Here, we investigate the behavior of an MPCD scheme in which the collision cells are aligned with the vectors that define a triclinic (parallelepiped) simulation box. We find that skewing the collision cells has a small but statistically significant impact on the transport properties of the pure solvent. Similar but more pronounced effects are found for nearly hard spheres in solution, including a significant decrease in their nominal self-diffusion coefficient and unphysical anisotropy in their self-diffusion tensor. Thus, our analysis indicates that skewed MPCD collision cells may result in spurious behavior and should be used with caution. We posit that these artifacts may be mitigated by grid-free schemes for placing particles into collision cells.

Fractional spatiotemporal Hahnfeldt tumor model with convergence analysis and optimal control

Unveiling the entropic role of hydration water in SOD1 partitioning within FUS condensate

Biological processes such as the sequestration of superoxide dismutase 1 (SOD1) into biomolecular condensates, including fused in sarcoma and stress granules, are vital for understanding disease mechanisms, including amyotrophic lateral sclerosis. Moreover, protein–crowder interactions within these condensates are recognized as fundamental to cellular phase separation and disease-related processes. However, the specific role of the hydration environment in governing SOD1’s behavior and transition dynamics within these condensates remains poorly understood, limiting our ability to accurately model these critical biological systems. Therefore, we incorporate explicit water into an implicit solvent model (OPEP) to investigate how water influences SOD1’s behavior, residence times, and transition rates among associative states. We employ the advanced CVF (Coronas, Vilanova, Franzese) water model, which accurately captures hydrogen-bond networks at the molecular level. While the OPEP model indicates that bovine serum albumin (BSA) crowders reduce SOD1’s partition coefficient (PC) primarily through non-specific interactions, our explicit-water approach points to hydration entropy in BSA as a key contributor to the observed PC reduction. This result offers a new perspective on the system’s free-energy landscape, complementing those obtained from OPEP alone. Our research supports the notion that explicitly modeling water can enhance our understanding of protein–crowder interactions and their biological implications, further emphasizing the potential role of water in cellular phase separation and disease-related processes.

Peer aesthetic and social perceptions of anterior open bite in children

Liquid–vapor coexistence of platinum from <i>ab initio</i> simulations

Platinum is a standard material for high pressure experiments, yet estimates of the liquid–vapor critical temperature and density span nearly 7000 K and 2 g/cm3. Here, we present the results of the first systematic investigation of liquid–vapor coexistence and critical behavior of platinum using density functional theory based molecular dynamics. We compare critical point parameters and liquid–vapor phase boundaries obtained from a fit to an equation of state spanning liquid and vapor states and a subsequent Maxwell construction and, separately, from an instantaneous interface calculation from which we estimated the densities of coexisting liquid and vapor. We find good agreement in the estimated critical point obtained from these calculations but the binodal shows considerably more variation, especially at lower temperatures. Overall, our estimated critical point of ρc = 5.03 g/cm3, Tc = 7690 K, and Pc = 2.17 kbar is significantly cooler than many previous estimates based on more indirect methods.

Influence of vegetation types on soil physicochemical and biochemical properties in naturally recovering riverbank sand mining sites

Cross-linking driven collapse dynamics of polyelectrolyte single-chain in good solvents

Electrostatics-mediated intramolecular cross-linking is proven effective for large-scale synthesis of single-chain nanoparticles (SCNPs) from polyelectrolyte chains in concentrated solutions. However, the underlying mechanism of cross-linking-driven collapse dynamics remains insufficiently explored. Here, we perform coarse-grained dissipative particle dynamics simulations to unveil the cross-linking-driven collapse dynamics of polyelectrolyte single-chain, which is dependent on chain length and electrostatic strength. It is shown that the timescale of the cross-linking-driven collapse follows a power-law dependence on chain length with a negative scaling exponent, which is fundamentally different from the solvent-induced collapse dynamics. We further explain this distinction by developing a Model A-type dynamics theory. A non-monotonic dependence of collapse timescale on electrostatic strength is identified with the power-law scaling exponents being positive and negative in the weak and strong electrostatic coupling regime, respectively. This is understood by the effect of counterion condensation within our dynamics model. The theoretical result helps understand the electrostatics-mediated intramolecular cross-linking-driven collapse of single-chain and precisely control the microstructure of derived SCNPs.

Surfactants promote the transport of hydrophilic compounds through hydrophobic nanopores in leaves: mechanistic insights

Abstract Conventional wisdom identifies two pathways for the uptake of active ingredients through the wax layers found on plant leaf surfaces: (1) lipophilic ingredients dissolve into the waxy substrate, and (2) hydrophilic ingredients are transported through hypothetical hydrophilic channels. Using molecular dynamics simulations, we reveal an additional mechanism by which surfactants with specific molecular structures - known as accelerators or penetrators - can enable the uptake of hydrophilic active ingredients. Depending on their structures, accelerator surfactants can penetrate nanometer-scale hydrophobic voids in the topmost wax layer, known as the epicuticular wax, promoting the formation of water nanoclusters that facilitate the uptake of hydrophilic molecules. This mechanism enables the uptake of hydrophilic nutrients such as methylglucose and certain types of electrolytes. The computational findings explain experimentally observed antagonistic effects in hard water (containing Ca $$^{2+}$$ ), which arise from selective ion binding to the waxy leaf surface. This study establishes a framework for designing next-generation agrichemical delivery systems to optimize active ingredient uptake through plant leaves by spray application.

Detection of hexagonal fluid crystalline phase in polymer suspensions as suggested by de Gennes via anomalous small-angle x-ray scattering. I. Theory and results from semi-dilute concentration of 25 mM polyacrylate suspensions

Element specific scattering techniques known as anomalous small-angle x-ray scattering have been employed in the analysis of the thallium counterion distribution in aqueous salt-free polyacrylate solutions with the molar concentration of 25 mM. The pure-resonant scattering contribution of the Tl+-counterions was deduced explicitly, thereby revealing the existence of a hexagonal lattice structure, as suggested by de Gennes et al. About 75% of the Tl+-counterions are localized in the cylinders of the hexagonal lattice structure. A cylinder axis of 12.1 nm was deduced, giving, in combination with the amount of monomer units inside the cylinder, a length of the monomer unit of 0.66 nm, indicating strong stretching of the polyanions. The stability criterion of Lindemann is served, thus explaining the stability of the liquid crystalline phase. From the mixed-resonant and the non-resonant scattering contribution, the monomer volume of 0.1111 nm3 was deduced.

Impact of treated wash water from ready mix concrete plants on concrete properties and durability

Abstract Concrete production consumes nearly 16% of global freshwater resources, highlighting the urgent need for sustainable alternatives to potable water. This study investigates the feasibility of using treated wash water from ready-mix concrete plants as a partial or full replacement for mixing water. Concrete mixes were prepared with 25%, 50%, 75%, and 100% wash water replacement ratios to evaluate the impacts on fresh and hardened properties as well as durability. Electrical resistivity testing was integrated into the experimental programme to assess the durability performance of concrete containing varying wash water contents. The results showed a reduction in workability of up to 50% compared to the control mix prepared with potable water. At 28 days, compressive strength decreased by 15.9%, 17.3%, and 18.3% for mixes containing 25%, 75%, and 100% wash water replacement, respectively. Electrical resistivity increased significantly with higher wash water replacement by 44% and 60% for mixes with 25% and 50% wash water replacement, and by up to six times at full replacement, indicating enhanced durability and resistance to corrosion. Furthermore, empirical equations were developed and validated against the experimental data to estimate the reduction in compressive strength of concrete mixes incorporating treated water. These findings provide performance-based guidance for the broader adoption of treated wash water as a sustainable alternative in concrete production while maintaining acceptable structural and durability performance.

Toward accurate mixed quantum classical simulations of vibrational polaritonic chemistry

Interest in vibrational polaritonic chemistry, where ground-state chemical kinetics are modified via confined optical modes in a cavity, has surged in recent years. Although models have been developed to understand cavity-modified reactions, fully quantum mechanical simulations remain out of reach for the collective regime that involves many molecules, a critical aspect of the phenomenon. Mixed quantum–classical (MQC) simulations offer a scalable alternative, but their accuracy requires testing and potential improvements even in the single-molecule limit. In this work, we take this step by first introducing the mapping approach to surface hopping (MASH) to address the limitations of traditional MQC methods. Second, we incorporate a quantum treatment of the cavity mode, moving beyond the classical approximations often employed in previous studies. Results for a single-molecule model of vibrational polaritonic chemistry show that combining MASH with a quantum cavity mode yields the most accurate rates. However, this scheme may produce different long-time population dynamics at zero coupling depending on whether the cavity mode is quantized; a problem known as size-inconsistency in MASH. We address this problem by proposing the ɛ-MASH approach, which forbids hopping between states with negligible nonadiabatic couplings (NACs). Combining MASH with a quantum cavity mode thus provides a promising approach for scalable and accurate MQC simulations in the collective regime.

Harnessing fano-like line shape resonance in a rectangular waveguide for filtering applications

Shadow excited state molecular dynamics with the ΔSCF method

We present an extension of the shadow extended Lagrangian Born–Oppenheimer molecular dynamics method to excited state molecular dynamics (ESMD) in the context of ΔSCF Kohn–Sham density functional theory, with demonstrations performed using self-consistent charge density functional tight binding (SCC-DFTB) theory. In this shadow ESMD approach, the approximate iterative solution to the exact potential in conventional ESMD is replaced by an exact single-step solution to an approximate shadow excited-state potential. The energy functional that defines this shadow excited-state potential as a stationary (non-aufbau) solution is obtained from a linearization about an approximate excited state density, which would become a progressively worse approximation as the dynamics ensue if it were static. To avoid this, we propagate the approximate excited-state (charge) density as an additional dynamical variable in an extended Lagrangian approach. We show that, in addition to offering significant improvement in computational cost relative to direct ESMD, our shadow ESMD method provides enhanced stability and robustness relative to its “exact” counterpart. Our implementation is carried out in the context of SCC-DFTB theory but should be broadly generalizable, both to ab initio electronic structure methods and to other semi-empirical quantum chemistry approaches.

Smart wastewater management in hydro-technical systems using digital twin technology

Prefetch parallelization and optimization of Monte Carlo in the grand canonical, isothermal-isobaric, and Gibbs ensemble

Parallelization of Monte Carlo (MC) is required to observe the same growth as molecular dynamics because computer processor clock speeds have plateaued while the number of cores has increased. Although prefetch parallelization can speed up an Monte Carlo molecular simulation by a factor of 3 using four parallel threads for simultaneous single-particle displacements in the canonical ensemble, other ensembles require multiple trial types that impact efficiency when threads wait for the other threads with more time-consuming trials, such as volume changes or particle insertions and deletions in the isothermal-isobaric, grand canonical, and Gibbs ensemble. Load balancing increases efficiency by attempting the same trial in each thread of a parallel batch but violates detailed balance if done incorrectly. By computing standard deviations as a function of processor time, efficiency is systematically investigated over a variety of ensembles, load balancing algorithms, and trial attempt and acceptance probabilities for dense liquids of Lennard-Jones and an extended simple point charge model of water, to reveal numerous efficiency gains, including in serial simulations. Parallel efficiency in these ensembles approached the theoretical maximum by reducing overhead costs with improved algorithms and data structures released in the open-source Monte Carlo software called FEASST.

Prevalence of musculoskeletal injuries and associated risk factors in Brazilian esports players: a cross-sectional study

Abstract Electronic sports (esports) are competitive video game activities with varying physical demands depending on the game modality. Despite their growing popularity, limited research has addressed the prevalence and risk factors of musculoskeletal injuries in this population. This cross-sectional observational study aimed to determine the prevalence and distribution of injuries by body region in Brazilian esports players and to identify associations with injury occurrence. A total of 365 players completed an online form covering sociodemographic information, duration of esports practice, daily hours played, and injury history over the previous 12 months. Statistical analyses included descriptive measures, group comparisons (t-test, Mann-Whitney, Chi-square), binary and multiple logistic regression, and Receiver Operating Characteristic (ROC) curve analysis. Among participants, 318 (87.12%) were male, and 113 (30.96%) reported injuries within the past year. The upper limb was the most commonly affected region, with the wrist accounting for 28.49% of reported injuries. Multiple logistic regression revealed significant associations between injury occurrence and both years of practice (OR = 1.110; p  = 0.005) and weekly practice frequency (OR = 1.183; p  = 0.032). Although the ROC curve showed limited discriminative ability, these factors were linked to higher wrist injury risk. Preventive strategies should consider training volume and practice frequency.

Defect-mediated carrier trapping and nonradiative recombination in two-dimensional sliding ferroelectrics

Two-dimensional (2D) sliding ferroelectrics have garnered significant attention as potential candidates for next-generation electronic devices, including non-volatile memories and optoelectronic neuromorphic devices. However, the impact of defects on photoinduced carrier dynamics in these materials remains largely underexplored. Here, we systematically investigate the role of sulfur (S) vacancies in rhombohedral-stacked MoS2 bilayers and their influences on carrier trapping and nonradiative recombination. Our results demonstrate that S vacancies introduce localized electron trap states within the bandgap. While suppressing direct recombination, these trap states open a highly efficient two-step nonradiative channel. This new pathway, mediated by low-frequency phonon modes, accelerates the overall recombination, reducing the carrier lifetime. The findings are crucial for engineering defects and controlling carrier dynamics in 2D ferroelectrics. This study not only advances fundamental understanding of defect-related processes in MoS2 bilayers but also paves the way for the design of more efficient optoelectronic devices.