A Dynamic Deformation based Lubrication Model between the Piston Rings and Cylinder Liner

The piston ring-cylinder liner friction pair is one of the most important friction pair in IC engines. In previous modelling studies, most researches were carried out based on a hypothesis that the inner surface of liner is an ideal cylindrical shell without considering the effects of dynamic deformation on oil film distribution. To investigate the potential influences of structural deformations on tribological behaviors of cylinder assemblies, the dynamic deformation of liner surface was obtained by FEM-based dynamic simulation, and then introduced into the lubrication model. Different from the traditional lubrication model where the pressure stress factor and shear stress factor are regarded as constant, this paper calculated these factors in real time by numerical integration to achieve more realistic simulation results. This study shows that the friction force obtained from the improved model manifests obvious fluctuations, and shows a significant reduction compared to original model

Bayesian Generational Population-Based Training

Reinforcement learning (RL) offers the potential for training generally capable agents that can interact autonomously in the real world. However, one key limitation is the brittleness of RL algorithms to core hyperparameters and network architecture choice. Furthermore, non-stationarities such as evolving training data and increased agent complexity mean that different hyperparameters and architectures may be optimal at different points of training. This motivates AutoRL, a class of methods seeking to automate these design choices. One prominent class of AutoRL methods is Population-Based Training (PBT), which have led to impressive performance in several large scale settings. In this paper, we introduce two new innovations in PBT-style methods. First, we employ trust-region based Bayesian Optimization, enabling full coverage of the high-dimensional mixed hyperparameter search space. Second, we show that using a generational approach, we can also learn both architectures and hyperparameters jointly on-the-fly in a single training run. Leveraging the new highly parallelizable Brax physics engine, we show that these innovations lead to large performance gains, significantly outperforming the tuned baseline while learning entire configurations on the fly. Code is available at https://github.com/xingchenwan/bgpbt.Comment: AutoML Conference 2022. 10 pages, 4 figure, 3 tables (28 pages, 10 figures, 7 tables including references and appendices

Biochanin a Enhances the Defense Against Salmonella enterica Infection Through AMPK/ULK1/mTOR-Mediated Autophagy and Extracellular Traps and Reversing SPI-1-Dependent Macrophage (MΦ) M2 Polarization

A novel treatment regimen for bacterial infections is the pharmacological enhancement of the host's immune defenses. We demonstrated that biochanin A (BCA), an isoflavone constituent in some plants, could enhance both intra- and extracellular bactericidal activity of host cells. First, BCA could induce a complete autophagic response in nonphagocytic cells (HeLa) or macrophages (MΦ) via the AMPK/ULK1/mTOR pathway and Beclin-1-dependent manner, and BCA enhanced the killing of invading Salmonella by autophagy through reinforcing ubiquitinated adapter protein (LRSAM1, NDP52 and p62)-mediated recognition of intracellular bacteria and through the formation of autophagolysosomes. Second, we demonstrated that BCA could enhance the release of MΦ extracellular traps (METs) to remove extracellular Salmonella also via the AMPK/ULK1/mTOR pathway, not through reactive oxygen species (ROS) pathway. Furtherly, in a Salmonella-infected mouse model, BCA treatment increased intra- and extracellular bactericidal activity through the strengthening autophagy and MET production, respectively, in peritoneal MΦ, liver and spleen tissue. Additionally, our findings showed that BCA downregulated SPI-1 (Salmonella pathogenicity island 1) expression during Salmonella infection in vitro and in vivo to reverse the MΦ M2 polarization, which was different from the MΦ M1 phenotype caused by most of bacteria infection. Together, these findings suggest that BCA has an immunomodulatory effect on Salmonella-infected host cells and enhances their bactericidal activity in vitro and in vivo through autophagy, extracellular traps and regulation of MΦ polarization

Enhanced room-temperature Na+ ionic conductivity in Na4.92_{4.92}Y0.92_{0.92}Zr0.08_{0.08}Si4_{4}O12_{12}

Developing cost-effective and reliable solid-state sodium batteries with superior performance is crucial for stationary energy storage. A key component in facilitating their application is a solid-state electrolyte with high conductivity and stability. Herein, we employed aliovalent cation substitution to enhance ionic conductivity while preserving the crystal structure. Optimized substitution of Y3+ with Zr4+ in Na5YSi4O12 introduced Na+ ​ion vacancies, resulting in high bulk and total conductivities of up to 6.5 and 3.3 ​mS ​cm−1, respectively, at room temperature with the composition Na4.92Y0.92Zr0.08Si4O12 (NYZS). NYZS shows exceptional electrochemical stability (up to 10 ​V vs. Na+/Na), favorable interfacial compatibility with Na, and an excellent critical current density of 2.4 ​mA ​cm−2. The enhanced conductivity of Na+ ​ions in NYZS was elucidated using solid-state nuclear magnetic resonance techniques and theoretical simulations, revealing two migration routes facilitated by the synergistic effect of increased Na+ ​ion vacancies and improved chemical environment due to Zr4+ substitution. NYZS extends the list of suitable solid-state electrolytes and enables the facile synthesis of stable, low-cost Na+ ion silicate electrolytes

RING finger 138 deregulation distorts NF-кB signaling and facilities colitis switch to aggressive malignancy

Prolonged activation of nuclear factor (NF)-кB signaling significantly contributes to the development of colorectal cancer (CRC). New therapeutic opportunities are emerging from targeting this distorted cell signaling transduction. Here, we discovered the critical role of RING finger 138 (RNF138) in CRC tumorigenesis through regulating the NF-кB signaling, which is independent of its Ubiquitin-E3 ligase activity involved in DNA damage response. RNF138(−/−) mice were hyper-susceptible to the switch from colitis to aggressive malignancy, which coincided with sustained aberrant NF-кB signaling in the colonic cells. Furthermore, RNF138 suppresses the activation of NF-кB signaling pathway through preventing the translocation of NIK and IKK-Beta Binding Protein (NIBP) to the cytoplasm, which requires the ubiquitin interaction motif (UIM) domain. More importantly, we uncovered a significant correlation between poor prognosis and the downregulation of RNF138 associated with reinforced NF-кB signaling in clinical settings, raising the possibility of RNF138 dysregulation as an indicator for the therapeutic intervention targeting NF-кB signaling. Using the xenograft models built upon either RNF138-dificient CRC cells or the cells derived from the RNF138-dysregulated CRC patients, we demonstrated that the inhibition of NF-кB signaling effectively hampered tumor growth. Overall, our work defined the pathogenic role of aberrant NF-кB signaling due to RNF138 downregulation in the cascade events from the colitis switch to colonic neoplastic transformation and progression, and also highlights the possibility of targeting the NF-кB signaling in treating specific subtypes of CRC indicated by RNF138-ablation

Emissive Platinum(II) Cages with Reverse Fluorescence Resonance Energy Transfer for Multiple Sensing

It is quite challenging to realize fluorescence resonance energy transfer (FRET) between two chromophores with specific positions and directions. Herein, through the self-assembly of two carefully selected fluorescent ligands via metal-coordination interactions, we prepared two tetragonal prismatic platinum(II) cages with a reverse FRET process between their faces and pillars. Bearing different responses to external stimuli, these two emissive ligands are able to tune the FRET process, thus making the cages sensitive to solvents, pressure, and temperature. First, these cages could distinguish structurally similar alcohols such as n-butanol, t-butanol, and i-butanol. Furthermore, they showed decreased emission with bathochromic shifts under high pressure. Finally, they exhibited a remarkable ratiometric response to temperature over a wide range (223–353 K) with high sensitivity. For example, by plotting the ratio of the maximum emission (I600/I480) of metallacage 4b against the temperature, the slope reaches 0.072, which is among the highest values for ratiometric fluorescent thermometers reported so far. This work not only offers a strategy to manipulate the FRET efficiency in emissive supramolecular coordination complexes but also paves the way for the future design and preparation of smart emissive materials with external stimuli responsiveness

Artificial intelligence : A powerful paradigm for scientific research

Y Artificial intelligence (AI) coupled with promising machine learning (ML) techniques well known from computer science is broadly affecting many aspects of various fields including science and technology, industry, and even our day-to-day life. The ML techniques have been developed to analyze high-throughput data with a view to obtaining useful insights, categorizing, predicting, and making evidence-based decisions in novel ways, which will promote the growth of novel applications and fuel the sustainable booming of AI. This paper undertakes a comprehensive survey on the development and application of AI in different aspects of fundamental sciences, including information science, mathematics, medical science, materials science, geoscience, life science, physics, and chemistry. The challenges that each discipline of science meets, and the potentials of AI techniques to handle these challenges, are discussed in detail. Moreover, we shed light on new research trends entailing the integration of AI into each scientific discipline. The aim of this paper is to provide a broad research guideline on fundamental sciences with potential infusion of AI, to help motivate researchers to deeply understand the state-of-the-art applications of AI-based fundamental sciences, and thereby to help promote the continuous development of these fundamental sciences.Peer reviewe

Existence of positive periodic solutions for Liénard equations with an indefinite singularity of attractive type

Abstract In this paper, we study the periodic problem for the Liénard equation with an indefinite singularity of attractive type x″+f(x)x′+φ(t)x+r(t)xμ=0, $$x''+f(x)x'+\varphi (t)x+\frac{r(t)}{x^{\mu }}=0,$$ where f:(0,+∞)→R $f:(0,+\infty )\rightarrow R$ is continuous and may have singularities at zero, r, φ:R→R $\varphi : R\rightarrow R$ are T-periodic functions, and μ is a positive constant. Using the method of upper and lower functions, we obtain some new results on the existence of positive periodic solutions to the equation

Periodic solutions for second order differential equations with indefinite singularities

In this paper, the problem of periodic solutions is studied for second order differential equations with indefinite singularitie