Browse Articles

Bubble phase induced by odd interactions in chiral systems

We study a chiral system of particles subject to both odd interactions and standard repulsive interactions. The interplay between oddness and inertia induces a non-equilibrium phase transition from a homogeneous to a non-homogeneous phase, characterized by the emergence of bubbles due to odd interactions. This phenomenon occurs in the absence of attractions and results from the competition between pressures, arising from particle repulsion, which tends to shrink the bubble, and an effective surface force that promotes its expansion. The latter is an effective centrifugal force associated with the circular motion of particles along the bubble’s surface, driven by transverse interactions. As a signature of the phase transition, the system exhibits vortex structures and oscillating spatial velocity correlations, which emerge near the analytically predicted transition point. Our findings can be tested in granular experiments involving odd interactions, such as spinners and active granular particles, and could be crucial for characterizing the emergent properties of metamaterials.

Spatiotemporal heterogeneity of bicycle ridership based on GTWR model

As a low-carbon, green and environmentally friendly mode of travel, bicycles possess significant advantages in short-distance trips. In previous studies on the relationship between the built environment and bicycle behavior, the built environment variable only took into account the number or density of facilities. However, due to their different grades and formats, the attractions of similar facilities of the same size to residents vary considerably. Therefore, this paper constructs a comprehensive index of POI (Point of Interest) facility quality to reflect the influence of the number of facilities and preferences on bicycle trips. In addition, two types of riding safety indicators, namely the proportion of non-isolation bars and the proportion of non-motor vehicle lane parking, are added to the road safety facilities. On this basis, GWR and GTWR models are established to explored the temporal and spatial distribution characteristic of cycling, and identifies the relationship between cycling behavior and built environments based on 2022 Daily Trip Survey in Xianyang, China. The model results demonstrate the following: (1) The GTWR model exhibits a better fit compared to the GWR model. (2) There are significant differences between the urban central area and the marginal area, which verifies that similar facilities have diverse impacts on the cycling frequency in distinct regions. (3) The promoting or inhibiting effects of the urban built environment on the cycling frequency are highly congruent with the temporal characteristics of commuting, and these effects typically reach their maximum during commuting rush hours. (4) Cycling safety facilities constitute a significant factor influencing the cycling frequency. These results can not only offer guidance for urban planning and design but also foster the sustainable development of green transportation.

Author Correction: Low intensity pulsed ultrasound alleviates synovial fibrosis in osteoarthritis via the PI3K/AKT pathway

Hydrogen scrambling and high propensity for multiple neutral emissions from 1,3-butadiene dication

The two-body dissociation of the dications formed after double ionization of the smallest conjugated diene, the 1,3-butadiene, C4H6, is studied using the coincidence time-of-flight technique and quantum chemistry calculations. The dication was formed by ion-impact ionization using energetic Xe3+ projectiles. Our results show that butadiene dication has a high propensity of neutral particle emission (H/H2/C2H2) prior to two-body dissociation into two singly charged fragments. The asymmetric two-body breakup, after the emission of neutral fragments from parent butadiene dication, is observed to be twice as probable as the asymmetric two-body breakup of intact butadiene dication. Our experimental results suggest that multiple structures may be formed for several different precursor dications formed after loss of neutral particles, which is indicative of the strong role of hydrogen scrambling. The internal energy dependence and time evolution of the interplay between neutral particle emission, hydrogen scrambling, and hydrogen migration are explored using ab initio molecular dynamics simulations to support the experimental observations.

Outcomes and predictors of in-hospital mortality among patients admitted to the intensive care or step-down unit after a rapid response team activation: A retrospective cohort study

Introduction It has been demonstrated that the implementation of rapid response teams (RRT) may improve clinical outcomes. Nevertheless, predictors of mortality among patients admitted to the intensive care unit (ICU) or to the step-down unit (SDU) after a RRT activation are not fully understood. Objective To describe clinical characteristics, resource use, main outcomes, and to address predictors of in-hospital mortality among patients admitted to the ICU/SDU after RRT activation. Methods Retrospective single-center cohort study conducted in a medical-surgical ICU/SDU located in a private quaternary care hospital. Adult patients admitted to the ICU or SDU between 2012 and 2020 were compared according to in-hospital mortality. A multivariate logistic regression analysis was performed to identify independent predictors of in-hospital mortality. Results Among the 3841 patients included in this analysis [3165 (82.4%) survivors and 676 (17.6%) non-survivors], 1972 (51.3%) were admitted to the ICU and 1869 (48.7%) were admitted to the SDU. Compared to survivors, non-survivors were older [76 (64–87) yrs. vs. 67 (50–81) yrs.; p < 0.001], had a higher SAPS 3 score [64 (56–72) vs. 49 (40–57); p < 0.001], and had a longer length of stay (LOS) before unit admission [8 (3–19) days vs. 2 (1–7) days; p < 0.001). Non-survivors used more non-invasive ventilation (NIV) (42.2% vs. 20.9%; p < 0.001), mechanical ventilation (MV) (36.7% vs. 9.3%; p < 0.001), vasopressors (39.2% vs. 12.3%; p < 0.001), renal replacement therapy (15.5% vs. 4.3%; p < 0.001), and blood components transfusion (34.9% vs. 14.0%; p < 0.001). Independent predictors of in-hospital mortality were the SAPS 3 score, the Charlson Comorbidity Index, LOS before unit admission, immunosuppression, respiratory rate < 8 or > 28 ipm criteria for RRT activation, RRT activation during the night shift, and the need for high-flow nasal cannula, NIV, MV, vasopressors, and blood components transfusion. Conclusion Multiple factors may affect outcomes of ICU/SDU-admitted patients after RRT activation. Therefore, efforts should be made to boost RRT effectiveness to improve patient safety.

Curcumin attenuates neuroinflammation and improves cognitive function in a rat model of febrile convulsions

Many-body approach to projective solution of generalized operators: Formulation and application to quantum computing

In this paper, we propose a novel many-body approach for determining the amplitudes of generalized operators in a projection-based formalism. To implicitly account for the effects of higher-order excitations, we begin with the well-established double-exponential coupled-cluster (CC) ansatz, parametrized by both one- and two-body excitation operators, complemented by a set of vacuum-annihilating two-body generalized operators with effective excitation rank of one. A systematic formalism is developed that effectively bypasses the constraints due to the vacuum-annihilation property of the generalized operators toward a set of closed-form residual equations for their optimization. Such a strategy requires the removal of the underlying redundancy in high-rank excited determinants, generated due to the presence of the generalized operators in the ansatz, by projecting them onto an internally contracted lower-dimensional manifold. This many-body formalism is integrated with the near-term projective quantum eigensolver (PQE) framework that leverages the conventional CC-like residual minimization to iteratively decouple the excited manifold from the reference. With the application of several molecular systems within PQE architecture, we demonstrate that the developed methodology enables us to achieve similar accuracy to the disentangled unitary coupled cluster with singles, doubles, and triples ansatz while utilizing an order of magnitude fewer quantum resources. Furthermore, when simulated under stochastic Gaussian noise or depolarizing hardware noise, our method shows significantly improved noise resilience compared to the other members of PQE family and the state-of-the-art variational quantum eigensolver.

The canine vaginal microbiome during heat and fertility in healthy breeding dogs

A healthy and balanced vaginal microbiome is often thought to be an important prerequisite for successful breeding and healthy litters. Previous studies investigating the influence of canine vaginal bacteria on fertility mostly relied on aerobic culturing. In recent years, culture-independent methods, such as next-generation sequencing (NGS), have become popular. With the ability to analyze the microbiome as a whole, research in this field has made notable advances. This is the first study to correlate NGS data of the canine vaginal microbiome in heat with fertility data. Healthy breeding bitches (n=80) presented for routine pre-breeding examination were sampled during early heat and mated after ovulation. A vaginal sample was taken for NGS analysis and microbiological culture. Additionally, a blood sample was collected. Fertility data (mating, pregnancy, delivery, litter size) were assessed. NGS revealed a diverse microbiome in all the samples. Bioinformatics and statistical analysis did not provide evidence of larger differences in the microbiome of those bitches that became pregnant and those that did not.

Innovative cross-layer defense mechanisms for blackhole and wormhole attacks in wireless ad-hoc networks

Abstract Wireless ad-hoc networks operate independently of existing infrastructure, using devices like access points to connect end-user computing devices. Current methods face issues such as low detection accuracy, structural deviation, and extended processing times. This paper proposes a cross-layer approach that leverages knowledge from the physical and Medium Access Control (MAC) layers, which is then shared with higher layers to effectively mitigate wormhole and blackhole attacks. A wormhole attack disrupts communication through tunneling, while a blackhole attack manipulates network traffic by impersonating the source. The proposed cross-layer framework integrates the network, MAC, and physical layers, and is independent of specific network protocols. The physical layer handles channel interference, the network layer manages process handling, and the MAC layer oversees bandwidth information and tracks failed transmissions. Performance metrics are measured in seconds. The Enhanced Support Vector Machine (E-SVM) algorithm, implemented using NS3 software, demonstrates superior performance compared to traditional SVM techniques across multiple metrics, including average energy consumption, average remaining energy, packets received, packet delivery ratio, delay, jitter, throughput, normalized overhead, dropping ratio, and goodput. Simulation results show that E-SVM achieves a 12.5% dropping ratio, 98.459% energy consumption, and an 89.2879% packet delivery ratio, outperforming existing SVM techniques across various network sizes.

Exploring the high sensitivity of DFT thermochemistry for protonation states of a ferredoxin model complex [CH3S4Fe2IIIS2H]−

Density functional theory (DFT) thermochemistry of 3d transition-metal complexes is well-known to be sensitive to the amount of exact Hartree–Fock exchange incorporated into the exchange–correlation functional. For example, relative energies of different protonation states of iron–sulfur complexes may vary by hundreds of kJ/mol among different DFT methods. In the present study, we examine the relative energies of four protonation isomers of the [CH3S4Fe2IIIS2H]− [2Fe–2S] ferredoxin model. Compared to many-body ab initio phaseless auxiliary-field quantum Monte Carlo with multi-Slater determinant trial wavefunctions and fully connected singles and doubles coupled-cluster with perturbative triples methods, the r2SCAN12-D4, B3LYP-D4, and B97-1-D3(OP) approaches perform the best. We also demonstrate that density-corrected DFT on top of KS-CCSD electronic densities provides reliable results with the r2SCAN functional. Moreover, the direct random phase approximation on top of the TPSSh, O3LYP, and r2SCAN12 hybrid functionals performs well.

Environmental persistence of nontyphoidal Salmonella in an urban informal settlement in Nairobi, Kenya

Non-typhoidal Salmonella (NTS) presents a considerable health threat to children in low-resource settings, where clean water, sanitation, and hygiene are often inadequate. However, the environmental factors influencing NTS persistence and spread remain poorly understood. We utilized a case-control approach to investigate environmental factors associated with NTS infection in children living in Nairobi’s informal settlements between August 2022 and July 2023. Stool samples were collected from febrile children, with or without diarrhea, who visited healthcare facilities. The study included 42 laboratory-confirmed NTS-positive cases and 42 NTS-negative children from the same community. Environmental samples, including drinking water, open drains, soil, and household effluent, were collected from both case and control households, in addition to raw sewage from main sewer-line convergence points. Conventional microbiological culture and quantitative Polymerase Chain Reaction techniques were employed for NTS detection, with genomic sequencing used for strain characterization. Environmental samples from case households showed a higher NTS contamination rate of 33.3% (42/126) compared to control households of 7.2% (9/126). Higher odds of NTS infection in children were associated with household environmental factors, particularly exposure to household effluent (OR = 7.7, 95% CI: 2.18–34.82, p = 0.0005), drinking water (OR = 6.4, 95% CI: 1.57–37.76, p = 0.0055), and soil (OR = 5.4, 95% CI: 1.01–54.28, p = 0.0485). Genomic analysis revealed a common strain, Salmonella Enteritidis ST11, in clinical and environmental isolates. These findings highlight the plausible role of the household environment as a reservoir for NTS, perpetuating infection cycles within the community. Addressing this challenge requires a multifaceted approach, including improved sanitation infrastructure, environmental monitoring, and integrated public health interventions to reduce NTS exposure and transmission in high-risk populations.

Synthesis, characterization and bio-evaluation of novel series of pyrazoline derivatives as potential antifungal agents

Utilizing hybridization effects to tune morphology and electron mobility of Y6 through asymmetric small- and large-scale modifications of terminal groups

While exploring molecular modifications of the high-performance acceptor Y6 with an A-DA′D-A framework, researchers have discovered that asymmetric modification of terminal groups (TGs) appears to be a promising approach as it frequently enhances the photovoltaic performance of organic solar cells (OSCs) effectively. However, the underlying mechanism about how asymmetric TG modifications influence morphology and charge carrier mobility remains unclear. We have conducted a systematic study in this work to investigate the morphology and electron mobility of two asymmetric Y6 derivatives with the A1-DA′D-A2 framework: Y6-asym-IM2O (A1 = IM-2F and A2 = IM2O, representing small-scale TG modification) and Y6-asym-BR (A1 = IM-2F and A2 = BR, representing large-scale TG modification), along with their symmetric counterparts (A1 = A2 = IM-2F/BR/IM2O). The results demonstrate that small-scale asymmetric TG modifications such as Y6-asym-IM2O fine-tune molecular packing, while large-scale modifications such as Y6-asym-BR drastically alter stacking patterns. In addition, hybridization effects are found in the frontier molecular orbital energy, electrostatic potential, and electron mobility of the asymmetric molecules, which fall between the values of their symmetric counterparts. In particular, the results of small-scale asymmetric modification of Y6 reveal that the introduction of promising TGs in an asymmetric manner can further improve electron mobility by tuning reorganization energy and morphology, and vice versa. While previous studies focused on symmetric modifications, this work systematically investigates asymmetric substitution patterns and further elucidates the impact of these methods on charge transfer for the first time. These discoveries underscore the potential of utilizing asymmetric modification of TGs as a quantitative means to regulate electron mobility in Y6-based OSCs.

Memory Monitoring Recognition Test (MMRT), a new measurement of stimular source monitoring: Software and comprehension

Background Reality monitoring allows the evaluation and monitoring of reality through the assignment of information to internal or external sources, which is crucial to differentiate real events from imaginary ones. In schizophrenics, monitoring seems to be related to an error in the allocation processes, giving rise to false perceptions such as visual hallucinations, which are associated with a poor prognosis. This error can appear almost imperceptibly at an early age in life, making carrying out predictive or evaluation tests with paper and pencil unattractive. The computerization of technical resources that allow the monitoring of reality offers a new tool to evaluate the attribution process, in an effective and agile way and with easy understanding of cognitive deficits in a friendly environment. Objective Computerize the Memory Monitoring and Recognition Test (MMRT) evaluate reality monitoring through verbal memory tasks, improving its implementation, optimizing interaction with the user and perfecting the recording of memory errors that could indicate psychotic symptoms. Method The MMRT was developed using Python and Kivy, facilitating the creation of cross-platform user interfaces. The test is structured in stages, allows voice accessibility for people with visual disabilities and provides comprehensive user management. The test data is stored in the cloud using MongoDB as the database system. Additionally, the software incorporates speech recognition using the gTTS library and generates a performance report in PDF format, documenting external, internal and global attribution errors. Result The computerized version of the MMRT allowed the detection of specific errors in memory monitoring, as well as the performance of repeated measurements to evaluate long-term memory and working memory. Conclusion Preliminary applications suggest its usefulness in identifying early cognitive markers of schizophrenia, facilitating the measurement of reality monitoring through attribution errors. Developed with open-source technology and an interface adaptable to various platforms, the MMRT represents an accessible and efficient tool for psychological evaluation, with innovative potential in the study of reality monitoring.

Deep multiscale feature fusion network with dual attention for rolling bearing remaining useful life prediction

Abstract Aiming at the existing life prediction methods for rolling bearing degradation information mining is not sufficient, the critical time step information degree is insufficient, resulting in the loss of key degradation information, model prediction accuracy and model generalization ability is insufficient, this paper proposes a novel deep multiscale feature fusion network with dual attention for rolling bearing remaining useful life (RUL) prediction. First, multi-domain feature sets of rolling bearing vibration signals are acquired. Subsequently, it is proposed to use Squeeze-and-Excitation (SE) attention mechanism to calibrate and weigh temporal significance of feature sequences, thereby capturing critical temporal information. Then, a multi-scale feature extraction and fusion module with deep network is constructed, consisting of multiple identical multi-scale residual pyramid layers connected in series to further delve into the state information of rolling bearings. Additionally, a relative position encoding method suitable for time series prediction is introduced within the multi-head attention mechanism, a network architecture based on a dual attention-enhanced Transformer encoding layer is established. This enhancement significantly improves model prediction accuracy, generalization capability, and sequence data comprehension ability. Finally, the high-level features output from the feed-forward layer are mapped through a regression layer to obtain the final prediction results. Experimental results demonstrate the superior performance of the proposed method in terms of both prediction accuracy and generalization capability for rolling bearing life prediction. A more robust and accurate framework for RUL prediction in rolling bearings is provided.

Data efficient learning of molecular slow modes from nonequilibrium metadynamics

Enhanced sampling simulations help overcome free energy barriers and explore molecular conformational space by applying external bias potential along suitable collective variables (CVs). However, identifying optimal CVs that align with the slow modes of complex molecular systems with many coupled degrees of freedom can be a significant challenge. Deep time-lagged independent component analysis (Deep-TICA) addresses this issue by employing an artificial neural network that generates non-linear combinations of molecular descriptors to learn the slowest degrees of freedom. Training Deep-TICA CVs, however, typically requires long equilibrium simulations that can sample multiple recrossing events across various metastable conformations of the molecule. This requirement can often be prohibitively expensive, thereby limiting its widespread application. In this study, we present an algorithm that enables the training of Deep-TICA CVs using a limited amount of trajectory data obtained from short, non-equilibrium metadynamics simulations that only sample one forward transition from the initial to the final state. We achieve this by utilizing the variational Koopman algorithm, which reweights short off-equilibrium trajectories to reflect the equilibrium probability densities. We demonstrate that enhanced sampling simulations conducted along the Koopman reweighted Deep-TICA CV can accurately and efficiently converge the free energy surface for systems such as the Müller–Brown potential, alanine dipeptide, and the chignolin mini-protein. Our approach, therefore, addresses the key challenge of inferring slow modes from limited trajectory data, making it more feasible to use deep learning CVs to study molecular processes of practical relevance.

Platelet-rich plasma: A promising therapy for mitigating sperm oxidative stress and mitochondrial dysfunction in subfertile men

Platelet-rich plasma (PRP) is a pioneering therapy widely used in various medical fields, showing promising outcomes. However, its impact on human sperm quality remains poorly explored among emerging therapies. This study aims to investigate the effect of autologous PRP supplementation on oxidative stress levels and mitochondrial activity in human sperm. PRP was freshly prepared from venous blood and added to each ejaculated semen sample at different concentrations of 2%, 5%, and 10%. Reactive oxygen species (ROS) in spermatozoa were measured after 24 hours of incubation at 37° (5% CO2), using nitro-blue tetrazolium (NBT) test. The MTT test was used to measure the mitochondrial succinate deshydrogenase activity. A total of 180 semen samples were obtained from 15 patients. The supplementation with PRP significantly reduced the reactive oxidative species levels and improved mitochondrial activity in spermatozoa. The level of oxidative stress in sperm was significantly decreased after 24h of incubation with PRP at 2% (p = 0.001), 5% (p = 0.001) and 10% (p = 0.001) when compared to the control group. The succinate dehydrogenase activity was enhanced in the three groups when compared to the control group. It increased from 0.667 ± 0.313 to 0.952 ± 0.499 (p = 0.018), 1.201 ± 0.657 (p = 0.002) and 1.159 ± 0.607 (p = 0.001) after incubation with 2%, 5% and 10% of PRP, respectively. This study has shown that PRP supplementation could be a promising tool to enhance sperm quality against oxidative stress and mitochondrial dysfunction. These findings could be a starting point to investigate the usefulness of PRP in ART procedures.

Author Correction: Circulating microRNA-155-3p levels predicts response to first line immunotherapy in patients with metastatic renal cell carcinoma

Path-integral Monte Carlo simulations of solid parahydrogen using two-body, three-body, and four-body <i>ab initio</i> interaction potential energy surfaces

We present path integral Monte Carlo simulation results for the equation of state of solid parahydrogen between 0.024 and 0.1Å−3 at T = 4.2 K. The simulations are performed using non-additive isotropic ab initio two-body, three-body, and four-body potential energy surfaces (PESs). We apply corrections to account for both the finite size simulation errors and the Trotter factorization errors. Simulations that use only the two-body PES during sampling yield an equation of state similar to that of simulations that use both the two-body and three-body PESs during sampling. With the four-body interaction energy, we predict an equilibrium density of 0.02608Å−3, very close to the experimental result of 0.0261Å−3. The inclusion of the four-body interaction energy also brings the simulation results in excellent agreement with the experimental pressure–density data until around 0.065Å−3, beyond which the simulation results overestimate the pressure. These PESs overestimate the average kinetic energy per molecule at the equilibrium density by about 7% compared to the experimental result. Our findings suggest that, at higher densities, we require five-body and higher-order many-body interactions to quantitatively improve the agreement between the pressure-density curve produced by simulations and that of the experiment. Using the four-body PES during sampling at excessively high densities, where such higher-order many-body interactions are likely to be significant, causes an artificial symmetry breaking in the hcp lattice structure of the solid.

RWOA: A novel enhanced whale optimization algorithm with multi-strategy for numerical optimization and engineering design problems

Whale Optimization Algorithm (WOA) is a biologically inspired metaheuristic algorithm with a simple structure and ease of implementation. However, WOA suffers from issues such as slow convergence speed, low convergence accuracy, reduced population diversity in the later stages of iteration, and an imbalance between exploration and exploitation. To address these drawbacks, this paper proposed an enhanced Whale Optimization Algorithm (RWOA). RWOA utilized Good Nodes Set method to generate evenly distributed whale individuals and incorporated Hybrid Collaborative Exploration strategy, Spiral Encircling Prey strategy, and an Enhanced Spiral Updating strategy integrated with Levy flight. Additionally, an Enhanced Cauchy Mutation based on Differential Evolution was employed. Furthermore, we redesigned the update method for parameter a to better balance exploration and exploitation. The proposed RWOA was evaluated using 23 classical benchmark functions and the impact of six improvement strategies was analyzed. We also conducted a quantitative analysis of RWOA and compared its performance with other state-of-the-art (SOTA) metaheuristic algorithms. Finally, RWOA was applied to nine engineering design optimization problems to validate its ability to solve real-world optimization challenges. The experimental results demonstrated that RWOA outperformed other algorithms and effectively addressed the shortcomings of the canonical WOA.