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A bstract Previous research showed that the chaos bound proposed in [1] can be violated under specific conditions within the scalar fields surrounding black holes. In this paper, we explore motions of spinning particles orbiting a Reissner-Nordström black hole and examine whether this bound is violated in the spinor field of this black hole. For the neutral particle, when its spin magnitude surpasses a specific threshold, the value of the exponent exceeds the surface gravity, resulting in a violation of the bound. Given a fixed total angular momentum of the particle, when its spin direction is anti-aligned with the angular momentum direction, the exponent value is greater than that when the two directions are aligned. For the charged particle, taking into account the influence of the electromagnetic force, we find that for relatively large angular momenta, although the electromagnetic force does not change the trend of the exponent’s variation with respect to spin and angular momentum, and only modifies its values, it still leads to the violation. Therefore, the chaos bound violations are observed in the spinor field.

The rapid advancement and widespread implementation of digital technology have created opportunities for the e-commerce transformation of agricultural wholesale markets. The building of e-commerce platforms in this process is of utmost importance and should be approached methodically. This article analyzes the interests and behavioral choices of the agricultural wholesale markets, local government, and wholesalers by establishing a tripartite evolutionary game model. It applies replicator dynamics equations to describe the evolutionary strategies of each party. The findings of the study indicate that the behavioral choices of agricultural wholesale markets, local government, and wholesalers are influenced by their initial intentions. Furthermore, there exists a degree of alignment between the choices made by agricultural wholesale markets and wholesalers. The building of e-commerce platforms by agricultural wholesale markets can be facilitated through direct and indirect government subsidies; this also motivates wholesalers to adopt and utilize these platforms. Agricultural wholesale markets may further incentivize wholesalers to utilize their own e-commerce platforms by offering additional benefits. On the other hand, if the agricultural wholesale markets demonstrate strong initial inclinations toward using third-party e-commerce platforms. In this scenario, the local government has the potential to promote the widespread use of these platforms by providing both direct and indirect financial incentives to these markets, as well as actively encouraging wholesalers to participate in them. This study presents policy recommendations for agricultural wholesale markets and local government to support the effective implementation of e-commerce platforms in the agricultural wholesaler markets and facilitate a smooth transition to e-commerce in agricultural wholesale markets.

The intracellular metabolism of organelles, like lysosomes and mitochondria, is highly coordinated spatiotemporally and functionally. The activities of lysosomal enzymes significantly rely on the cytoplasmic temperature, and heat is constantly released by mitochondria as the byproduct of adenosine triphosphate (ATP) generation during active metabolism. Here, we developed temperature-sensitive LysoDots and MitoDots to monitor the in situ thermal dynamics of lysosomes and mitochondria. The design is based on upconversion nanoparticles (UCNPs) with high-density surface modifications to achieve the exceptionally high sensitivity of 2.7% K−1 and low uncertainty of 0.8 K for nanothermometry to be used in living cells. We show the measurement is independent of the ion concentrations and pH values. With Ca2+ ion shock, the temperatures of both lysosomes and mitochondria increased by ∼2 to 4°C. Intriguingly, with chloroquine (CQ) treatment, the lysosomal temperature was observed to decrease by up to ∼3 °C, while mitochondria remained relatively stable. Lastly, with oxidative phosphorylation inhibitor treatment, we observed an ∼3 to 7°C temperature increase and a thermal transition from mitochondria to lysosomes. These observations indicate different metabolic pathways and thermal transitions between lysosomes and mitochondria inside HeLa cells. The nanothermometry probes provide a powerful tool for multimodality functional imaging of subcellular organelles and interactions with high spatial, temporal, and thermal dynamics resolutions.

Optical tweezers are widely used in materials assembly 1 , characterization 2 , biomechanical force sensing 3 , 4 and the in vivo manipulation of cells 5 and organs 6 . The trapping force has primarily been generated through the refractive index mismatch between a trapped object and its surrounding medium. This poses a fundamental challenge for the optical trapping of low-refractive-index nanoscale objects, including nanoparticles and intracellular organelles. Here, we report a technology that employs a resonance effect to enhance the permittivity and polarizability of nanocrystals, leading to enhanced optical trapping forces by orders of magnitude. This effectively bypasses the requirement of refractive index mismatch at the nanoscale. We show that under resonance conditions, highly doping lanthanide ions in NaYF 4 nanocrystals makes the real part of the Clausius–Mossotti factor approach its asymptotic limit, thereby achieving a maximum optical trap stiffness of 0.086 pN μm –1  mW –1 for 23.3-nm-radius low-refractive-index (1.46) nanoparticles, that is, more than 30 times stronger than the reported value for gold nanoparticles of the same size. Our results suggest a new potential of lanthanide doping for the optical control of the refractive index of nanomaterials, developing the optical force tag for the intracellular manipulation of organelles and integrating optical tweezers with temperature sensing and laser cooling 7 capabilities. The resonance of highly doping lanthanide ions in NaYF 4 nanocrystals enhances the permittivity and polarizability of nanocrystals, leading to enhanced optical trapping forces by orders of magnitude, bypassing the trapping requirement of refractive index mismatch.

Marine fish larvae are vulnerable during the early life period. The early intervention using probiotics may be a promising method to improve growth of fish larvae. In this study, a 30-day feeding trial was conducted to evaluate the effects of early life intervention using probiotic Clostridium butyricum (CB) on growth performance, intestinal development, immune response and gut microbiota of large yellow croaker ( Larimichthys crocea ) larvae. Four isonitrogenous and isolipidic diets were formulated with the supplementation of four different levels of CB (5 × 10 9 CFU g −1 ), 0.00% (Control), 0.10% (CB1), 0.20% (CB2), and 0.40% (CB3). Results showed that larvae fed diets with CB had significant higher final length than the control group. Meanwhile, larvae fed the diet with 0.10% CB had significant higher final weight and specific growth rate (SGR) than the control group. However, no significant difference in survival rate was observed among dietary treatments. CB supplementation significantly increased the height of intestinal villus and the length of intestinal enterocyte. Similarly, CB supplementation significantly increased the expression of tight zonula occludens-2 ( zo-2 ) and ornithine decarboxylase ( odc ) than the control group. Larvae fed the diet with 0.20% CB had significant higher lipase and leucine-aminopeptidase (LAP) activity than the control group. Moreover, CB supplementation significantly improved immune enzyme activities than the control group. Sequencing of bacterial 16S rRNA V4-5 region indicated that dietary CB altered intestinal microbiota profile and decreased intestinal microbial diversities of larvae. CB supplementation could effectively increase the abundance of CB, and decrease the abundance of some potential pathogenic bacteria in larval gut. These results revealed that early life intervention using 0.10–0.20% CB could promote growth of large yellow croaker larvae probably through promoting intestinal development, improving immune enzyme activities and modulating gut microbiota.

Multiphoton fluorescence microscopy (MPM), using near infrared excitation light, provides increased penetration depth, decreased detection background, and reduced phototoxicity. Using stimulated emission depletion (STED) approach, MPM can bypass the diffraction limitation, but it requires both spatial alignment and temporal synchronization of high power (femtosecond) lasers, which is limited by the inefficiency of the probes. Here, we report that upconversion nanoparticles (UCNPs) can unlock a new mode of near-infrared emission saturation (NIRES) nanoscopy for deep tissue super-resolution imaging with excitation intensity several orders of magnitude lower than that required by conventional MPM dyes. Using a doughnut beam excitation from a 980 nm diode laser and detecting at 800 nm, we achieve a resolution of sub 50 nm, 1/20th of the excitation wavelength, in imaging of single UCNP through 93 μm thick liver tissue. This method offers a simple solution for deep tissue super resolution imaging and single molecule tracking. Upconversion nanoparticles offer the potential for deep tissue biological imaging. Here, Chen et al. develop super resolution optical imaging in the near-infrared for imaging with sub-50 nm resolution through almost 100 microns of tissue.

Many researchers use life cycle assessment methodology to investigate the energy and environmental impacts of energy-saving and new energy vehicles. However, in the context of China, the life cycle energy-saving and emission-reduction effects of extended-range electric vehicles (EREVs), and the optimal applicable vehicle size and driving conditions for EREVs have been rarely studied. In this study, based on the life cycle assessment theory, the resource consumption, energy exhaustion, and environmental impact of EREVs were comprehensively analyzed. In addition, a differential evaluation model of ecological benefits was established for comparing EREVs with other vehicles with different power sources. Finally, scenario analysis was performed in terms of different vehicle sizes and driving conditions. The results have shown that EREV has great advantages in reducing mineral resource consumption and fossil energy consumption. The consumption of mineral resources of EREV is 14.68% lower than that of HEV, and the consumption of fossil energy is 34.72% lower than that of ICEV. In terms of environmental impact, EREV lies in the middle position. The scenario analysis has revealed that, for EREV in China, the optimal vehicle size is the passenger car and the optimal driving condition is the suburban condition. This work helps to understand the environmental performance of EREVs in China and may provide a decision-making reference for the government.

The extraordinary optoelectronic performance of hybrid organic–inorganic perovskites has resulted in extensive efforts to unravel their properties. Recently, observations of ferroic twin domains in methylammonium lead triiodide drew significant attention as a possible explanation for the current–voltage hysteretic behaviour in these materials. However, the properties of the twin domains, their local chemistry and the chemical impact on optoelectronic performance remain unclear. Here, using multimodal chemical and functional imaging methods, we unveil the mechanical origin of the twin domain contrast observed with piezoresponse force microscopy in methylammonium lead triiodide. By combining experimental results with first principles simulations we reveal an inherent coupling between ferroelastic twin domains and chemical segregation. These results reveal an interplay of ferroic properties and chemical segregation on the optoelectronic performance of hybrid organic–inorganic perovskites, and offer an exploratory path to improving functional devices.

Deformation prediction is an important part of concrete dam safety monitoring. In recent years, the random forest (RF) algorithm has attracted more and more attention in the field of dam safety monitoring because of its fast speed and strong generalization ability. However, the performance of RF is easily affected by many factors, such as the drift of measured value in displacement and the inappropriate setting of parameters of RF. To solve the above problems, the indicator variable model (IVM) is used to identify and eliminate the drift of measured values in this paper, and the sand cat swarm optimization (SCSO) is applied to optimize RF for the first time. On the grounds of this, a deformation prediction system of a concrete dam based on the IVM and RF algorithm optimized by SCSO is proposed. The case study shows that IVM can correct the interference of monitoring data accurately, and the maximum error rate is less than 3%; in the aspect of parameter optimization of RF, the results of the SCSO algorithm are obviously better than those of the TAE method and PSO algorithm, and the corresponding OOB error is the minimum; in terms of prediction performance, compared with TAE-RF, PSO-RF, LSTM and SVM, SCSO-RF has higher accuracy and stronger stability, and its SSE and MSE are reduced by at least 91%, MAE and RMSE are reduced by at least 71%, and R2 is very close to 1. The results of study provide a new method for the automatic online evaluation of dam safety performance.

With the advent of large language models (LLMs), in both the open source and proprietary domains, attention is turning to how to exploit such artificial intelligence (AI) systems in assisting complex scientific tasks, such as material synthesis, characterization, analysis and discovery. Here, we explore the utility of LLMs, particularly ChatGPT4, in combination with application program interfaces (APIs) in tasks of experimental design, programming workflows, and data analysis in scanning probe microscopy, using both in-house developed APIs and APIs given by a commercial vendor for instrument control. We find that the LLM can be especially useful in converting ideations of experimental workflows to executable code on microscope APIs. Beyond code generation, we find that the GPT4 is capable of analyzing microscopy images in a generic sense. At the same time, we find that GPT4 suffers from an inability to extend beyond basic analyses for more in-depth technical experimental design. We argue that an LLM specifically fine-tuned for individual scientific domains can potentially be a better language interface for converting scientific ideations from human experts to executable workflows. Such a synergy between human expertise and LLM efficiency in experimentation can open new doors for accelerating scientific research, enabling effective experimental protocols sharing in the scientific community.