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Summary: The building sector is integral to climate change mitigation in China as well as the globe. By considering the impact of green innovation, we explore the long-term trend of carbon emissions in China’s building sector until 2060, encompassing its entire life cycle. Results show that CO2 emissions of China’s building sector will peak at 6.98–7.69 Bt in 2035 and maintain at 1.11 Bt in 2060 under the business-as-usual (BAU) scenario. The “3060 dual carbon goal” will only be achieved under the technological breakthrough (TB) scenario. These findings show that existing or relatively lax policies are insufficient to achieve the “3060” goal for the building sector. China should actively pursue green technological innovation throughout the building sector’s life cycle, with a focus on accelerating the green and low-carbon production of key products, such as steel and cement, at the building material production stage.

Abstract Self‐powered pressure detection using smart wearable devices is the subject of intense research attention, which is intended to address the critical need for prolonged and uninterrupted operations. Current piezoelectric and triboelectric sensors well respond to dynamic stimuli while overlooking static stimuli. This study proposes a dual‐response potentiometric pressure sensor that responds to both dynamic and static stimuli. The proposed sensor utilizes interdigital electrodes with MnO2/carbon/polyvinyl alcohol (PVA) as the cathode and conductive silver paste as the anode. The electrolyte layer incorporates a mixed hydrogel of PVA and phosphoric acid. The optimized interdigital electrodes and sandpaper‐like microstructured surface of the hydrogel electrolyte contribute to enhanced performance by facilitating an increased contact area between the electrolyte and electrodes. The sensor features an open‐circuit voltage of 0.927 V, a short‐circuit current of 6 µA, a higher sensitivity of 14 mV/kPa, and outstanding cycling performance (>5000 cycles). It can accurately recognize letter writing and enable capacitor charging and LED lighting. Additionally, a data acquisition and display system employing the proposed sensor, which facilitates the monitoring of athletes’ rehabilitation training, and machine learning algorithms that effectively guide rehabilitation actions are presented. This study offers novel solutions for the future development of smart wearable devices.

Abstract An experiment examined the potency of nostalgia—a sentimental longing for one’s past—to facilitate detection of death-related stimuli, using functional magnetic resonance imaging (fMRI) and behavioral techniques (i.e., judgmental accuracy, reaction times). We hypothesized and found that, at the neural level, nostalgic (relative to control) participants evinced more intense activation in right amygdala in response to death-related (vs. neutral) words. We also hypothesized and found that, at the behavioral level, nostalgic (relative to control) participants manifested greater accuracy in judging whether two death-related (vs. neutral) words belonged in the same category. Exploratory analyses indicated that nostalgic (relative to control) participants did not show faster reaction times to death-related (vs. neutral) words. In all, nostalgia appeared to aid in death threat detection. We consider implications for the relevant literatures.

The sequestration of carbon in forests plays a crucial role in mitigating global climate change and achieving carbon neutrality goals. Carbon use efficiency (CUE) is an essential metric used to evaluate the carbon sequestration capacity and efficiency of Vegetation. Previous studies have emphasized the importance of assessing CUE at specific regions and times to better understand its spatiotemporal variations. The southeastern region of Tibet in the Qinghai-Tibet Plateau is recognized as one of the most biodiverse areas in China and globally, characterized by diverse vegetation types ranging from subtropical to temperate. In this study, we focused on Nyingchi, which is the largest virgin forest area in southeast Tibet, to explore the spatial-temporal dynamic characteristics of regional CUE based on MODIS remote sensing products. The following results were obtained: (1) On a monthly scale, regional CUE exhibits significant seasonal variations, with varying patterns among different vegetation types. Specifically, the fluctuation of CUE is the lowest in high-altitude forest areas and the greatest in grasslands and barrens. On an annual scale, forests exhibit higher fluctuations than areas with sparse vegetation and the overall volatility of CUE increased over the past 11 years. (2) There are regional differences in the trend of CUE changes, with a substantial downward trend in the Himalayan region and a significant upward trend in the residual branches of the Gangdise Mountains. More than 75% of the regions exhibit no persistent trend in CUE changes. (3) Vegetation type is the main determinant of the range and characteristics of vegetation CUE changes, while the geographical location and climatic conditions affect the variation pattern. CUE in the southern and northern regions of Nyingchi at 28.5°N exhibits different responses to temperature and precipitation changes, with temperature having a more significant impact on CUE.

Recent advances in the synthesis of multi-functional nanoparticles have opened up tremendous opportunities for the targeted delivery of genes of interest. Cationic solid lipid nanoparticles (SLN) can efficiently bind nucleic acid molecules and transfect genes in vitro. Few reports have combined SLN with therapy using decoy oligodeoxynucleotides (ODN). In the present study, we prepared SLN to encapsulate STAT3 decoy ODN; then, the properties and in vitro behavior of SLN-STAT3 decoy ODN complexes were investigated. SLN-STAT3 decoy ODN complexes were efficiently taken up by human ovarian cancer cells and significantly suppressed cell growth. Blockage of the STAT3 pathway by SLN-STAT3 decoy ODN complexes resulted in an evident induction of cell death, including apoptotic and autophagic death. The mechanism involved the increased expression of cleaved caspase 3, Bax, Beclin-1 and LC3-II and reduced expression of Bcl-2, pro-caspase 3, Survivin, p-Akt and p-mTOR. In addition, SLN-STAT3 decoy ODN complexes inhibited cell invasion by up-regulating E-cadherin expression and down-regulating Snail and MMP-9 expression. These findings confirmed that SLN as STAT3 decoy ODN carriers can induce cell death and inhibit invasion of ovarian cancer cells. We propose that SLN represent a potential approach for targeted gene delivery in cancer therapy.