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Exploring the allometric characteristics and driving mechanisms of economic development (ED) and carbon emissions (CE) is significant for promoting regional sustainable development. This study applied the panel grey relational model and the Driscoll–Kraay estimation method to investigate the internal mechanism of economic development and carbon emissions, to analyse their spatiotemporal correlation and allometric characteristics, and finally to characterize the impact mechanism of their allometric growth of the Yangtze River Delta urban agglomeration (YRDUA). The results show that (1) the spatiotemporal distribution patterns of economic development and carbon emissions are coincident and positively correlated, with the strength of the time-series correlation between them being less than the average value of 0.757 from 2016 onward. (2) The economic development-carbon emissions vertical allometric growth coefficient showed a trend of increasing and then decreasing and was always in a negative allometric growth state. The relative growth rate of carbon emissions was lower than that of economic development, and the per unit GDP carbon emissions decreased slightly. The horizontal allometric growth coefficient showed that more than 90% of the cities are in the negative allometric growth state, and that the negative allometric II and III levels are the main ones. (3) Per capita GDP, industrial structure, and energy structure are the boosting factors of the allometric growth coefficient, while population density and environmental regulation play a restraining role. Trade openness showed a restraining effect in 2010–2015 and turned into a promoting effect in 2016–2020. In both stages, the energy structure is one of the most crucial driving factors. The findings reported in this study can provide support for urban agglomerations to achieve low-carbon city development goals. [ABSTRACT FROM AUTHOR]

Exhausted CD8+ T lymphocytes and tumor-associated macrophages play critical roles in determining cancer prognosis and the efficacy of immunotherapy. Our study revealed a negative correlation between exhausted CD8+ T lymphocytes and prognosis in thyroid carcinoma (THCA). Consensus clustering divided patients into two subgroups of exhaustion with different prognoses, as defined by marker genes of exhausted CD8+ T cells. Subsequently, we constructed an eight-gene prognostic signature, and developed a risk score named the exhaustion-related gene score (ERGS) to forecast both prognosis and immunotherapy response in THCA. Bulk RNA sequencing analysis revealed a higher prevalence of M2 macrophages, indicative of an immunosuppressive tumor microenvironment (TME), in the high-ERGS group. Single-cell RNA sequencing showed that SPP1+ macrophages and CD14+ monocytes infiltrations were positively associated with higher ERGS. Functionally, it was determined that SPP1+ macrophages exert an immunosuppressive role, while CD14+ monocytes were implicated in promoting tumor progression and angiogenesis. Analysis of cell–cell interactions between SPP1+ macrophages and T cells highlighted the activation of the SPP1-CD44 and MIF-CD74 axes, both of which could foster an immunosuppressive TME. Therapeutic strategies that target SPP1+ macrophages, CD14+ monocytes, and the SPP1-CD44 and MIF-CD74 axes may potentially improve the prognosis and amplify the immunotherapy response in THCA patients. [ABSTRACT FROM AUTHOR]

We introduce a construct called "humanness sensitivity," which we define as the ability to recognize uniquely human characteristics. To evaluate the construct, we used a "concurrent study design" to conduct an internet-based study with a convenience sample of 42,063 people from 88 countries (52.4% from the U.S. and Canada).We sought to determine to what extent people could identify subtle characteristics of human behavior, thinking, emotions, and social relationships which currently distinguish humans from non-human entities such as bots. Many people were surprisingly poor at this task, even when asked simple questions about human relationships or anatomy. Participants were best at identifying subtle aspects of human cognition and worst at identifying subtle aspects of human communication. Test scores were good predictors of whether someone was employed and modest predictors of other self-reported criterion measures. We also found that people identifying themselves in marginal societal categories (e.g., in the "other" category for gender or sexual orientation) identified themselves as less human and also scored lower on our test. As computers continue to become more human-like, our study suggests that the vast majority of humankind will likely have great difficulty distinguishing them from people. Can methods be devised for improving this ability? Might humanness sensitivity help people to make such distinctions? Will people who excel at differentiating humans and non-human entities—like the "blade runners" in the 1982 and 2017 feature films—someday hold a special place in society? [ABSTRACT FROM AUTHOR]

Nickel–Zirconium co-doped Y-type nickel ferrites (Ba2Ni2 + xZrxFe12−2xO22, 0 ≤ x ≤ 0.75 with step of 0.25) have been synthesized by solid -state reaction method. The crystal structure, microstructure, magnetic, and dielectric properties of these ceramics are characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), vibrating sample magnetometer (VSM), and LCR meter. The experimental results show that Ni–Zr ions replace the crystal sites of Fe3+ irons by forming a homogenous solid solution for low doping region, while impurity phases gradually appear with the doping content increases. Lattice constant gradually expands as the Ni–Zr content increases except for x = 0.75. Magnetization measurements indicate that all samples display a typical ferromagnetic characteristic with a maximum saturation magnetization at x = 0.5 with considerable value of 26.4 emu/g. The dielectric constant is substantially enhanced by Ni–Zr co-doping for nickel Y-type hexaferrite. The dielectric constant for the doped sample shows a maximum value of about 300 at low frequency, which is about ten times larger compared with the undoped sample. [ABSTRACT FROM AUTHOR]