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The surging demand for advanced fluorine corrosion-resistant materials underscores their significance in ensuring operational safety and reliability across various industries. This study investigates the corrosion behavior of the FeCoNiCrMo high-entropy alloy (HEA) via a series of 28-day immersion tests in hydrofluoric acid (HF) solutions. The results demonstrate the FeCoNiCrMo HEA's superior corrosion-resistant performance in HF environments, exhibiting remarkably low corrosion rates of 0.179 mm/y, 0.276 mm/y, and 0.352 mm/y in 20 vol%, 30 vol%, and 40 vol% HF solutions, respectively. Comprehensive phase and microstructural characterizations were conducted on samples exposed to the 40 vol% HF solution to elucidate the corrosion mechanisms. The study revealed that localized pitting corrosion preferentially initiates within the interdendritic regions of the HEA matrix upon HF exposure. During the intermediate stage, micro-galvanic corrosion occurs between the dendritic arms and interdendritic regions, leading to the formation of a uniform and compact corrosion product film on the alloy surface. This film, enriched with Mo, Cr, and O, provides temporary protection. However, as corrosion progresses, the partial detachment of particulate corrosion products compromises the integrity of the film, resulting in increased dissolution within the interdendritic regions and the formation of irregular corrosion grooves in the later stage. These insights significantly enhance the understanding of the corrosion mechanisms of FeCoNiCrMo HEA in HF environments and provide valuable guidance for developing innovative protective materials designed for fluorine-rich engineering applications.

Background Acute respiratory distress syndrome (ARDS) is a severe complication that can lead to fatalities in multiple trauma patients. Nevertheless, the incidence rate and early prediction of ARDS among multiple trauma patients residing in high-altitude areas remain unknown. Methods This study included a total of 168 multiple trauma patients who received treatment at Shigatse People’s Hospital Intensive Care Unit (ICU) between January 1, 2019 and December 31, 2021. The clinical characteristics of the patients and the incidence rate of ARDS were assessed. Univariable and multivariable logistic regression models were employed to identify potential risk factors for ARDS, and the predictive effects of these risk factors were analyzed. Results In the high-altitude area, the incidence of ARDS among multiple trauma patients was 37.5% (63/168), with a hospital mortality rate of 16.1% (27/168). Injury Severity Score (ISS) and thoracic injuries were identified as significant predictors for ARDS using the logistic regression model, with an area under the curve (AUC) of 0.75 and 0.75, respectively. Furthermore, a novel predictive risk score combining ISS and thoracic injuries demonstrated improved predictive ability, achieving an AUC of 0.82. Conclusions This study presents the incidence of ARDS in multiple trauma patients residing in the Tibetan region, and identifies two critical predictive factors along with a risk score for early prediction of ARDS. These findings have the potential to enhance clinicians’ ability to accurately assess the risk of ARDS and proactively prevent its onset.

High-content interstitial carbon addition has been proven to regulate the dislocation behavior in high-entropy alloys (HEAs) during deformation, thereby overcoming the strength-ductility trade-off, but its exact mechanism is still unclear. In this work, the dislocation generation at incipient plasticity in a high carbon-added Al10(FeNiCoMn)90 HEA was investigated by instrumented nanoindentation. It was found that interstitial carbon addition could increase the atomic cohesion, which induced a higher maximum shear stress and activation volume required to trigger the incipient plasticity related to dislocation nucleation. However, it decreased the activation energy for a critical dislocation loop during deformation, increasing the dislocation density and facilitating dislocations multiplication. Consequently, the plastic zone underneath the indenter expanded and pop-in events occurred in the carbon-added HEAs. These findings contribute to understanding how interstitial carbon regulates the dislocation behavior in HEAs.

In this work, Fe–20Mn–9Al–3Cr-xC (wt.%, x = 0.8–1.4) steels were designed to investigate the microstructure, mechanical properties and strain hardening behavior of Cr-containing Triplex low-density steel with different C content. Due to the presence of 3 wt% Cr, all the steel strips with different C content consisted of ferrite and austenite matrix with κ-carbide precipitation. With increasing the C content from 0.8 wt% to 1.4 wt%, the ferrite content decreased from 36 vol% to 4 vol%. Simultaneously, the precipitation and growth of κ-carbides in austenite was accelerated significantly. Quantitative analysis of the yield strength indicated that the strength contribution by κ-carbides increased from 36.3 MPa in 0.8C steel strip to 409.4 MPa in 1.4C steel strip, and became the primary strengthening factor when the C content exceeded 1.0 wt%. Fortunately, due to Cr addition, no intergranular κ-carbide was observed even in the 1.4C steel strip, and the steel strip demonstrated a good elongation of more than 33%. During plastic deformation, the slip band-dominated dislocation substructure made the 0.8C steel strip show a three-stage strain hardening, whereas a four-stage strain hardening occurred in the 1.0C, 1.2C and 1.4C steel strips due to the successive formation of slip band and microband. In addition, it was found that the plastic deformation in ferrite was prior to that in austenite, and the formation of ferrite improved the strain hardening capacity of steel strips at the early deformation stage. The findings provided valuable insights into the design of high-performance Triplex low-density steels by composition optimization.

Abstract Cooperative behaviour can evolve through conditional strategies that direct cooperation towards interaction partners who have themselves been cooperative in the past. Such strategies are common in human cooperation, but they can be vulnerable to manipulation: individuals may try to exaggerate their past cooperation to elicit reciprocal contributions or improve their reputation for future gains. Little is known about the prevalence and the ramifications of misrepresentation in human cooperation, neither in general nor about its cultural facets (self-sacrifice for the group is valued differently across cultures). Here, we present a large-scale interactive decision making experiment (N = 870), performed in China and the USA, in which individuals had repeated cooperative interactions in groups. Our results show that (1) most individuals from both cultures overstate their contributions to the group if given the opportunity, (2) misrepresentation of cooperation is detrimental to cooperation in future interactions, and (3) the possibility to build up a personal reputation amplifies the effects of misrepresentation on cooperation in China, but not in the USA. Our results suggest that misrepresentation of cooperation is likely to be an important factor in (the evolution of) human social behaviour, with, depending on culture, diverging impacts on cooperation outcomes.

The effect of nanoscale intragranular premature κ-carbide precipitates, having an ordered structure but without chemical partitioning, on the incipient plasticity behavior of austenite in Fe-Mn-Al-(Cr)-C low-density steels was investigated by nanoindentation. We found that the incipient plasticity was dominated by a heterogeneous dislocation nucleation mechanism via atom-vacancy exchange. Although the content of κ-carbide decreased with Cr addition, its negligible effect on incipient plasticity strength was witnessed by the slightly increased shear stress for dislocation nucleation. Comparatively, the increased interstitial C atoms with Cr content in austenite enhanced lattice cohesions which impeded the nucleation events by increasing the requisite shear stress.

Abstract Background Tumour repopulation initiated by residual tumour cells in response to cytotoxic therapy has been described clinically and biologically, but the mechanisms are unclear. Here, we aimed to investigate the mechanisms for the tumour‐promoting effect in dying cells and for tumour repopulation in surviving tongue cancer cells. Methods Tumour repopulation in vitro and in vivo was represented by luciferase activities. The differentially expressed cytokines in the conditioned medium (CM) were identified using a cytokine array. Gain or loss of function was investigated using inhibitors, neutralising antibodies, shRNAs and ectopic overexpression strategies. Results We found that dying tumour cells undergoing cytotoxic therapy increase the growth of living tongue cancer cells in vitro and in vivo. Dying tumour cells create amphiregulin (AREG)‐ and basic fibroblast growth factor (bFGF)‐based extracellular environments via cytotoxic treatment‐induced endoplasmic reticulum stress. This environment stimulates growth by activating lysine acetyltransferase 6B (KAT6B)‐dependent nuclear factor‐kappa B (NF‐κB) signalling in living tumour cells. As direct targets of NF‐κB, miR‐22 targets KAT6B to repress its expression, but long noncoding RNAs (lncRNAs) (XLOC_003973 and XLOC_010383) counter the effect of miR‐22 to enhance KAT6B expression. Moreover, we detected increased AREG and bFGF protein levels in the blood of tongue cancer patients with X‐box binding protein‐1 (XBP1) activation in tumours under cytotoxic therapy and found that XBP1 activation is associated with poor prognosis of patients. We also detected activation of miR‐22/lncRNA/KAT6B/NF‐κB signalling in recurrent cancers compared to paired primary tongue cancers. Conclusions We identified the molecular mechanisms of cell death‐induced tumour repopulation in tongue cancer. Such insights provide new avenues to identify predictive biomarkers and effective strategies to address cancer progression.

High-entropy alloys (HEAs) have become an interesting research area for the novel alloying design paradigm. Interstitial carbon has usually been introduced to enhance mechanical properties of HEAs. To achieve addition of high carbon, this work designed a dual-phase Al10(FeNiCoMn)90 HEA without strong carbide-forming elements. The results showed that adding 3 at.% carbon did not cause the precipitation of carbides in this HEA, and its yield strength and plasticity increased by 237 MPa and 26.2 %, respectively, which was due to the increase of fcc phase fraction, the distribution change of bcc phase and interstitial strengthening. Addition of 4 at.% carbon only caused the precipitation of nano-scale carbides in the matrix and the yield strength and plasticity increased by 455 MPa and 5.5 %, respectively, resulted from phase modulation, interstitial strengthening and precipitation strengthening. Simultaneously, the transition from wavy slip to planar slip and the formation of microbands after carbon addition, which also led to an increase of plasticity. This work provides a promising method that if coarse carbides can be avoided, high carbon addition enhances both strength and plasticity in a dual-phase HEA by multi-effects including phase modulation, interstitial strengthening, precipitation strengthening and deformation mechanism transition.

Elastic least-squares reverse time migration (ELSRTM) describes the reflectivity of the underground media more accurately than acoustic LSRTM in theory while suffering from the P- and S-waves crosstalk artifacts. We propose a new wavefield decomposed ELSRTM scheme to alleviate these crosstalk artifacts, which is different from conventional methods. In our new scheme, we implement the wavenumber domain elastic wavefield vector decomposition equivalently in the time-space domain to decompose source wavefield without Fourier transform, but with high precision. Then we decompose adjoint wavefield by constructing the shear component in a decoupled adjoint wave equation. Finally, based on elastic impedance parameterization, we derive the gradients with respect to elastic reflectivity in the wavefield-decomposed ELSRTM. Numerical examples show that our method is feasible even when applied to models with complex and uncorrelated P- and S-wave velocity structures.

To explore how pilots’ distribution of visual attention affects flight performance, twenty male pilots (novices and experts with 407 ± 11.3 h and 4127 ± 77 h of flight experience, respectively) were enlisted to complete the instrument holding pattern and approach procedure on the DA-42 simulator. The distribution of visual attention was based on eye movement data recorded during the flight to investigate how pilots scan the flight instrument panel, which was divided into six areas of interest (AOIs). To evaluate the pilots’ flight performance an expert scoring method was used. During the outbound-leg stage, experts paid significantly more visual attention to the airspeed indicator, altimeter and reference system, whereas for the approach phase, they devoted more attention to the airspeed indicator, altimeter and vertical speed indicator. Results showed that experts’ proportions of gaze duration on different AOIs contributed to their better performance. An effective visual attention model can be developed on this study to improve air traffic safety.

A model of co-evolution between individual strategy and gaming environment is proposed here. Different from the general evolutionary game dynamics, the gaming system developed here is deeply coupled with the strategy choices and the environment state. The game state, payoff matrices and gaming environment of the system will influence each other dynamically. We firstly analyse the co-evolution between two populations with two strategies and derive the sufficient condition under which the state of strategy and environment will evolve periodically. Then we extend the model to multiple populations and strategies to study a more complicated and realistic system. In this framework, we verify whether and how the convergence will take place among groups in the multi-strategy case. Our results provide some inspirations to tackle with the cooperation dilemma and research on the self-organized evolution in multi-behaviour populations in the real-world situations.

Glioma is the most common primary brain tumor with poor prognosis and high mortality. The purpose of this study was to use the epigenetic signature to predict prognosis and evaluate the degree of immune infiltration in gliomas. We integrated gene expression profiles and DNA methylation data of lower-grade glioma and glioblastoma to explore epigenetic differences and associated differences in biological function. Cox regression and lasso analysis were used to develop an epigenetic signature based on eight DNA methylation sites to predict prognosis of glioma patients. Kaplan–Meier analysis showed that the overall survival time of high- and low-risk groups was significantly separated, and ROC analysis verified that the model had great predictive ability. In addition, we constructed a nomogram based on age, sex, 1p/19q status, glioma type, and risk score. The epigenetic signature was obviously associated with tumor purity, immune checkpoints, and tumor-immune infiltrating cells (CD8+ T cells, gamma delta T cells, M0 macrophages, M1 macrophages, M2 macrophages, activated NK cells, monocytes, and activated mast cells) and thus, it may find application as a guide for the evaluation of immune infiltration or in treatment decisions in immunotherapy.

The effects of Cr addition on microstructures, mechanical properties and deformation behavior of near-rapidly solidified low-density Fe-20Mn-9Al-1.2C (wt. %) steel strips were investigated. It was found that Cr addition increased the volume fraction and size of δ-ferrite, and decreased the precipitation of κ-carbides in this low-density steel strip. The yield strength of the near-rapidly solidified steel strips was decreased significantly, but the ultimate tensile strength and the total elongation didn't obviously change. However, after cold rolling with 20% reduction, the yield strength and ultimate tensile strength of Cr-containing steel strips were significantly higher than that of the Cr-free steel strip. It was attributed to the fact that the decrease of κ-carbides caused by Cr addition facilitated the formation of high-density slip bands during cold rolling deformation. The ultimate tensile strength and total elongation of cold-rolled 3Cr (wt. %) steel strip were 1270 MPa and 21%, respectively. A double (Slip-band and Microband) hardening mechanism was proposed for the strain hardening behavior of the low-density steel strips, and the number of nanoscale κ-carbides played a crucial role in the strain hardening rate at the early strain stage. Keywords: Low-density steel, Deformation structures, κ-carbides, Slip band, Cr

Abstract Background Parkinson disease (PD) is the most common movement disturbance characterized by the loss of dopaminergic (DA) neurons in midbrain. Metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) is aberrantly expressed in neurons and is involved in the dendritic and synapse development. However, the role of MALAT1 and its underlying mechanism in PD remain to be defined. Methods The expressions of MALAT1 and miR-124 were evaluated by qRT-PCR. N-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced PD mice and SH-SY5Y cells subjected to N-methyl-4-phenylpyridinium (MPP+) were utilized to investigate the effect of MALAT1 on PD. TUNEL assay was performed to detect apoptosis of DA neurons in PD mice. Flow cytometry analysis was carried out to measure apoptosis of SH-SY5Y cells. Caspase3 activity and Cleaved Caspase3 expression were tested by caspase3 assay kit and western blot, respectively. TargetScan software and luciferase reporter assay were used to explore the relationship between MALAT1 and miR-124. Results MALAT1 was up-regulated and miR-124 was down-regulated in MPTP-induced PD mice and MPP+-treated SH-SY5Y cells. MALAT1 knockdown attenuated MPTP-induced apoptosis of DA neurons in MPTP-induced PD mouse model. MALAT1 interacted with miR-124 to negatively regulate its expression. MALAT1 knockdown suppressed MPP+-induced apoptosis in SH-SY5Y cells, while miR-124 downregulation abrogated this effect. Moreover, MALAT1 knockdown improved miR-124 expression in MPTP/MPP+ induced models of PD. Conclusions MALAT1 promotes the apoptosis by sponging miR-124 in mouse models of PD and in vitro model of PD, providing a potential theoretical foundation for the clinical application of MALAT1 against PD.

This paper proposes a novel faulted section location method for power distribution networks based on the status information collected by fault-indicating equipments. It has an advantage that it does not need to analyze and calculate any electrical parameters, and it is not affected by fault types and system parameters, so this method can be easily applied to power distribution networks. Firstly, a novel method for automatically constructing a line list is proposed in this paper—it can represent the topology structure of the power distribution line and the status information of fault-indicating equipment. Based on the line list, a topology search algorithm is proposed in the method to locate the faulted section. Considering that information loss will cause errors in the line list, an information loss detection algorithm is proposed to detect and correct the wrong status of fault-indicating equipments. Then, different fault conditions such as single fault, multiple faults, distributed generations in system and information loss condition are tested in power distribution networks with different topologies, and the simulation results indicate that the proposed method can deal with each case well. Moreover, the proposed fault location method has an advantage that the running time does not necessarily increase when the node scale is expanded.

To study the main molecular mechanisms responsible for itraconazole resistance in clinical isolates of Candida krusei.The 14α-demethylases encoded by ERG11 gene in the 16 C.krusei clinical isolates were amplified by polymerase chain reaction (PCR), and their nucleotide sequences were determined to detect point mutations. Meanwhile, ERG11 and efflux transporters (ABC1 and ABC2) genes were determined by quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR) for their expression in itraconazole-resistant (R), itraconazole-susceptible dose dependent (SDD) and itraconazole-susceptible (S) C.krusei at the mRNA level.We found 7-point mutations in ERG11 gene of all the C.krusei clinical isolates, including 6 synonymous mutations and 1 missense mutation (C44T). However, the missense mutation was found in the three groups. The mRNA levels of ERG11 gene in itraconazole-resistant isolates showed higher expression compared with itraconazole-susceptible dose dependent and itraconazole-susceptible ones (P = 0.015 and P = 0.002 respectively). ABC2 gene mRNA levels in itraconazole-resistant group was significantly higher than the other two groups, and the levels of their expression in the isolates appeared to increase with the decrease of susceptibility to itraconazole (P = 0.007 in SDD compared with S, P = 0.016 in SDD with R, and P

We study the evolution of cooperation in a structured population, combining insights from evolutionary game theory and the study of interaction networks. In earlier studies it has been shown that cooperation is difficult to achieve in homogeneous networks, but that cooperation can get established relatively easily when individuals differ largely concerning the number of their interaction partners, such as in scale-free networks. Most of these studies do, however, assume that individuals change their behaviour in response to information they receive on the payoffs of their interaction partners. In real-world situations, subjects do not only learn from their interaction partners, but also from other individuals (e.g. teachers, parents, or friends). Here we investigate the implications of such incongruences between the 'interaction network' and the 'learning network' for the evolution of cooperation in two paradigm examples, the Prisoner's Dilemma game (PDG) and the Snowdrift game (SDG). Individual-based simulations and an analysis based on pair approximation both reveal that cooperation will be severely inhibited if the learning network is very different from the interaction network. If the two networks overlap, however, cooperation can get established even in case of considerable incongruence between the networks. The simulations confirm that cooperation gets established much more easily if the interaction network is scale-free rather than random-regular. The structure of the learning network has a similar but much weaker effect. Overall we conclude that the distinction between interaction and learning networks deserves more attention since incongruences between these networks can strongly affect both the course and outcome of the evolution of cooperation.

In social dilemmas, cooperation among randomly interacting individuals is often difficult to achieve. The situation changes if interactions take place in a network where the network structure jointly evolves with the behavioral strategies of the interacting individuals. In particular, cooperation can be stabilized if individuals tend to cut interaction links when facing adverse neighborhoods. Here we consider two different types of reaction to adverse neighborhoods, and all possible mixtures between these reactions. When faced with a gloomy outlook, players can either choose to cut and rewire some of their links to other individuals, or they can migrate to another location and establish new links in the new local neighborhood. We find that in general local rewiring is more favorable for the evolution of cooperation than emigration from adverse neighborhoods. Rewiring helps to maintain the diversity in the degree distribution of players and favors the spontaneous emergence of cooperative clusters. Both properties are known to favor the evolution of cooperation on networks. Interestingly, a mixture of migration and rewiring is even more favorable for the evolution of cooperation than rewiring on its own. While most models only consider a single type of reaction to adverse neighborhoods, the coexistence of several such reactions may actually be an optimal setting for the evolution of cooperation.

We study the evolution of cooperation in the spatial prisoner's dilemma game where players are allowed to establish new interactions with others. By employing a simple coevolutionary rule entailing only two crucial parameters, we find that different selection criteria for the new interaction partners as well as their number vitally affect the outcome of the game. The resolution of the social dilemma is most probable if the selection favors more successful players and if their maximally attainable number is restricted. While the preferential selection of the best players promotes cooperation irrespective of game parametrization, the optimal number of new interactions depends somewhat on the temptation to defect. Our findings reveal that the "making of new friends" may be an important activity for the successful evolution of cooperation, but also that partners must be selected carefully and their number limited.

We study the evolution of cooperation among selfish individuals in the stochastic strategy spatial prisoner's dilemma game. We equip players with the particle swarm optimization technique, and find that it may lead to highly cooperative states even if the temptations to defect are strong. The concept of particle swarm optimization was originally introduced within a simple model of social dynamics that can describe the formation of a swarm, i.e., analogous to a swarm of bees searching for a food source. Essentially, particle swarm optimization foresees changes in the velocity profile of each player, such that the best locations are targeted and eventually occupied. In our case, each player keeps track of the highest payoff attained within a local topological neighborhood and its individual highest payoff. Thus, players make use of their own memory that keeps score of the most profitable strategy in previous actions, as well as use of the knowledge gained by the swarm as a whole, to find the best available strategy for themselves and the society. Following extensive simulations of this setup, we find a significant increase in the level of cooperation for a wide range of parameters, and also a full resolution of the prisoner's dilemma. We also demonstrate extreme efficiency of the optimization algorithm when dealing with environments that strongly favor the proliferation of defection, which in turn suggests that swarming could be an important phenomenon by means of which cooperation can be sustained even under highly unfavorable conditions. We thus present an alternative way of understanding the evolution of cooperative behavior and its ubiquitous presence in nature, and we hope that this study will be inspirational for future efforts aimed in this direction.