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In order to adapt to the demands of diverse businesses for on-demand, accurate and efficient network services, the communication-computing-caching-intelligence cooperative network (3CI-CoNet) was proposed. The hardware bases of 3CI-CoNet was built by connecting computing devices and storage devices with communication technologies. Intelligent models and algorithms were deployed on the bases to build an intelligent network environment. Simultaneously, 3CI-CoNet connected with intelligent devices, platforms, and algorithms relevant to various industries and applications to provide intelligent network services for emerging applications, ensuring the orderly and efficient operation of various services. 3CI-CoNet was designed with a hierarchical functional architecture, including the foundational resource layer, intelligent access layer, on-demand service layer, and business expression layer. These layers worked together to construct an intelligent network environment and network services. Furthermore, in conjunction with typical scenarios in autonomous driving and smart manufacturing, the functional architecture and operational mechanisms of 3CI-CoNet were discussed. Using the on-demand scheduling of multiple automated guided vehicle (AGV) in intelligent manufacturing as a prototype, a qualitative and quantitative analysis was performed to demonstrate the positive impacts of 3CI-CoNet on enhancing business efficiency. Finally, the future development trends and the technological challenges of 3CI-CoNet were summarized.

Background The incidence of prostate cancer is increasing in older males globally. Age, ethnicity, and family history are identified as the well-known risk factors for prostate cancer, but few modifiable factors have been firmly established. The objective of this study was to identify and evaluate various factors modifying the risk of prostate cancer reported in meta-analyses of prospective observational studies and mendelian randomization (MR) analyses. Methods and findings We searched PubMed, Embase, and Web of Science from the inception to January 10, 2022, updated on September 9, 2023, to identify meta-analyses and MR studies on prostate cancer. Eligibility criteria for meta-analyses were (1) meta-analyses including prospective observational studies or studies that declared outcome-free at baseline; (2) evaluating the factors of any category associated with prostate cancer incidence; and (3) providing effect estimates for further data synthesis. Similar criteria were applied to MR studies. Meta-analysis was repeated using the random-effects inverse-variance model with DerSimonian-Laird method. Quality assessment was then conducted for included meta-analyses using AMSTAR-2 tool and for MR studies using STROBE-MR and assumption evaluation. Subsequent evidence grading criteria for significant associations in meta-analyses contained sample size, P values and 95% confidence intervals, 95% prediction intervals, heterogeneity, and publication bias, assigning 4 evidence grades (convincing, highly suggestive, suggestive, or weak). Significant associations in MR studies were graded as robust, probable, suggestive, or insufficient considering P values and concordance of effect directions. Finally, 92 selected from 411 meta-analyses and 64 selected from 118 MR studies were included after excluding the overlapping and outdated studies which were published earlier and contained fewer participants or fewer instrument variables for the same exposure. In total, 123 observational associations (45 significant and 78 null) and 145 causal associations (55 significant and 90 null) were categorized into lifestyle; diet and nutrition; anthropometric indices; biomarkers; clinical variables, diseases, and treatments; and environmental factors. Concerning evidence grading on significant associations, there were 5 highly suggestive, 36 suggestive, and 4 weak associations in meta-analyses, and 10 robust, 24 probable, 4 suggestive, and 17 insufficient causal associations in MR studies. Twenty-six overlapping factors between meta-analyses and MR studies were identified, with consistent significant effects found for physical activity (PA) (occupational PA in meta: OR = 0.87, 95% CI: 0.80, 0.94; accelerator-measured PA in MR: OR = 0.49, 95% CI: 0.33, 0.72), height (meta: OR = 1.09, 95% CI: 1.06, 1.12; MR: OR = 1.07, 95% CI: 1.01, 1.15, for aggressive prostate cancer), and smoking (current smoking in meta: OR = 0.74, 95% CI: 0.68, 0.80; smoking initiation in MR: OR = 0.91, 95% CI: 0.86, 0.97). Methodological limitation is that the evidence grading criteria could be expanded by considering more indices. Conclusions In this large-scale study, we summarized the associations of various factors with prostate cancer risk and provided comparisons between observational associations by meta-analysis and genetically estimated causality by MR analyses. In the absence of convincing overlapping evidence based on the existing literature, no robust associations were identified, but some effects were observed for height, physical activity, and smoking., Author(s): Huijie Cui 1, Wenqiang Zhang 1, Li Zhang 1, Yang Qu 1, Zhengxing Xu 1, Zhixin Tan 1, Peijing Yan 1, Mingshuang Tang 1, Chao Yang 1, Yutong Wang [...]

【Background and objective】 Water ascent in plants is driven by hydraulic gradient regulated by stomatal opening and closure as well as soil water content; it is generally assumed to be approximately zero at night. However, recent findings reveal that stomata could partly open and sap continues to flow at night, making stems function as capacitors regulating transpiration in daytime. The purpose of this paper is to investigate the diurnal change in sap flow and its determinants. 【Method】 We take Ailanthus altissima as the model plant and measure sap flow through its stems, as well as variation in stem diameter, using a diffusion probe (TDP) from June to August in an urban area. We also measure environmental factors which we anticipate to affect root water uptake by the tree. 【Result】 Sap flow does occur at night; it contributes 12.1% to the total daily sap flow, of which 65% is from 20:00 to 00:00 (T1) and 35% from 00:00 to 05:00 (T2). The night sap flow rate is positively correlated to the vapor pressure deficit and wind speed, but the correlation is more significant in T2 (P

A photothermoelectric (PTE) photodetector (PD) is crucial for realizing broadband detection, which is vital for the next generation of integrated multifunctional photodetectors. Due to the limitations of the material band gap and response mechanism, spectral responses cannot be achieved. Here, we present a flexible SnS PTE PD that effectively overcomes the limitations related to the bandgap and exhibits a comprehensive spectral response, extending from 405 nm to 1550 nm. The device demonstrates impressive responsivity and detectivity of 2.1 V W−1 and 7.2 × 1010 jones, respectively, with only a 7% reduction in voltage after undergoing 300 bending cycles. Additionally, the high Seebeck coefficient (379 μW K−1) enables the device to detect infrared radiation 5 cm away, and non-contact temperature monitoring can be performed in real-time on intelligent robots or wearable electronic devices. This study investigates the thermoelectric properties of SnS to integrate temperature detection with ultra-spectrum detection capabilities, which offers a novel and effective method for detecting human radiation and other sources of thermal radiation. [ABSTRACT FROM AUTHOR]