Enhancing Energy Efficiency for Reconfigurable Intelligent Surfaces with Practical Power Models

Reconfigurable intelligent surfaces (RISs) are widely considered a promising technology for future wireless communication systems. As an important indicator of RIS-assisted communication systems in green wireless communications, energy efficiency (EE) has recently received intensive research interest as an optimization target. However, most previous works have ignored the different power consumption between ON and OFF states of the PIN diodes attached to each RIS element. This oversight results in extensive unnecessary power consumption and reduction of actual EE due to the inaccurate power model. To address this issue, in this paper, we first utilize a practical power model for a RIS-assisted multi-user multiple-input single-output (MU-MISO) communication system, which takes into account the difference in power dissipation caused by ON-OFF states of RIS's PIN diodes. Based on this model, we formulate a more accurate EE optimization problem. However, this problem is non-convex and has mixed-integer properties, which poses a challenge for optimization. To solve the problem, an effective alternating optimization (AO) algorithm framework is utilized to optimize the base station and RIS beamforming precoder separately. To obtain the essential RIS beamforming precoder, we develop two effective methods based on maximum gradient search and SDP relaxation respectively. Theoretical analysis shows the exponential complexity of the original problem has been reduced to polynomial complexity. Simulation results demonstrate that the proposed algorithm outperforms the existing ones, leading to a significant increase in EE across a diverse set of scenarios.Comment: Reconfigurable intelligent surface is a promising 6G technology. However, RIS power models are inaccurate. In this paper, we construct a practical power model for RIS communication systems with an SDP-relaxation algorithm, achieving optimal energy efficienc

A Hybrid of Optical Remote Sensing and Hydrological Modelling Improves Water Balance Estimation

Declining gauging infrastructure and fractious water politics have decreased available information about river flows globally. Remote sensing and water balance modelling are frequently cited as potential solutions, but these techniques largely rely on these same in-decline gauge data to make accurate discharge estimates. A different approach is therefore needed, and we here combine remotely sensed discharge estimates made via at-many-stations hydraulic geometry (AMHG) and the PCR-GLOBWB hydrological model to estimate discharge over the Lower Nile. Specifically, we first estimate initial discharges from 87 Landsat images and AMHG (1984-2015), and then use these flow estimates to tune the model, all without using gauge data. The resulting tuned modelled hydrograph shows a large improvement in flow magnitude: validation of the tuned monthly hydrograph against a historical gauge (1978-1984) yields an RMSE of 439 m3/s (40.8%). By contrast, the original simulation had an order-of-magnitude flow error. This improvement is substantial but not perfect: tuned flows have a one-to two-month wet season lag and a negative baseflow bias. Accounting for this two-month lag yields a hydrograph RMSE of 270 m3/s (25.7%). Thus, our results coupling physical models and remote sensing is a promising first step and proof of concept toward future modelling of ungauged flows, especially as developments in cloud computing for remote sensing make our method easily applicable to any basin. Finally, we purposefully do not offer prescriptive solutions for Nile management, and rather hope that the methods demonstrated herein can prove useful to river stakeholders in managing their own water

Bmi1 Is Down-Regulated in the Aging Brain and Displays Antioxidant and Protective Activities in Neurons

Aging increases the risk to develop several neurodegenerative diseases, although the underlying mechanisms are poorly understood. Inactivation of the Polycomb group gene Bmi1 in mice results in growth retardation, cerebellar degeneration, and development of a premature aging-like phenotype. This progeroid phenotype is characterized by formation of lens cataracts, apoptosis of cortical neurons, and increase of reactive oxygen species (ROS) concentrations, owing to p53-mediated repression of antioxidant response (AOR) genes. Herein we report that Bmi1 expression progressively declines in the neurons of aging mouse and human brains. In old brains, p53 accumulates at the promoter of AOR genes, correlating with a repressed chromatin state, down-regulation of AOR genes, and increased oxidative damages to lipids and DNA. Comparative gene expression analysis further revealed that aging brains display an up-regulation of the senescence-associated genes IL-6, p19Arf and p16Ink4a, along with the pro-apoptotic gene Noxa, as seen in Bmi1-null mice. Increasing Bmi1 expression in cortical neurons conferred robust protection against DNA damage-induced cell death or mitochondrial poisoning, and resulted in suppression of ROS through activation of AOR genes. These observations unveil that Bmi1 genetic deficiency recapitulates aspects of physiological brain aging and that Bmi1 over-expression is a potential therapeutic modality against neurodegeneration

Scenario set-up and forcing data for impact model evaluation and impact attribution within the third round of the Inter-Sectoral Model Intercomparison Project (ISIMIP3a)

This paper describes the rationale and the protocol of the first component of the third simulation round of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP3a, www.isimip.org) and the associated set of climate-related and direct human forcing data (CRF and DHF, respectively). The observation-based climate-related forcings for the first time include high-resolution observational climate forcings derived by orographic downscaling, monthly to hourly coastal water levels, and wind fields associated with historical tropical cyclones. The DHFs include land use patterns, population densities, information about water and agricultural management, and fishing intensities. The ISIMIP3a impact model simulations driven by these observation-based climate-related and direct human forcings are designed to test to what degree the impact models can explain observed changes in natural and human systems. In a second set of ISIMIP3a experiments the participating impact models are forced by the same DHFs but a counterfactual set of atmospheric forcings and coastal water levels where observed trends have been removed. These experiments are designed to allow for the attribution of observed changes in natural, human and managed systems to climate change, rising CH4 and CO2 concentrations, and sea level rise according to the definition of the Working Group II contribution to the IPCC AR6

The adult, pupa, and larva of a new species of Gnaptorina Reitter, 1887 (Coleoptera, Tenebrionidae, Blaptini) from the Tibetan Plateau, with molecular phylogenetic inferences

The adult, pupa and larva of a new species, Gnaptorina (Gnaptorina) lhorongica Li, sp. nov., from northeastern Xizang, China are described and illustrated. The species was identified using molecular phylogenetic analyses based on three mitochondrial fragments and one nuclear gene fragment (COI, Cytb, 16S, and 28S-D2). The taxonomic status of the new species is confirmed using a combination of molecular and morphological datasets. This study provides valuable molecular and morphological data for phylogenetic studies of the tribe Blaptini

Three specific gut bacteria in the occurrence and development of colorectal cancer: a concerted effort

Colorectal cancer (CRC), which develops from the gradual evolution of tubular adenomas and serrated polyps in the colon and rectum, has a poor prognosis and a high mortality rate. In addition to genetics, lifestyle, and chronic diseases, intestinal integrity and microbiota (which facilitate digestion, metabolism, and immune regulation) could promote CRC development. For example, enterotoxigenic Bacteroides fragilis, genotoxic Escherichia coli (pks+ E. coli), and Fusobacterium nucleatum, members of the intestinal microbiota, are highly correlated in CRC. This review describes the roles and mechanisms of these three bacteria in CRC development. Their interaction during CRC initiation and progression has also been proposed. Our view is that in the precancerous stage of colorectal cancer, ETBF causes inflammation, leading to potential changes in intestinal ecology that may provide the basic conditions for pks+ E. coli colonization and induction of oncogenic mutations, when cancerous intestinal epithelial cells can further recruit F. nucleatum to colonise the lesion site and F. nucleatum may contribute to CRC advancement by primarily the development of cancer cells, stemization, and proliferation, which could create new and tailored preventive, screening and therapeutic interventions. However, there is the most dominant microbiota in each stage of CRC development, not neglecting the possibility that two or even all three bacteria could be engaged at any stage of the disease. The relationship between the associated gut microbiota and CRC development may provide important information for therapeutic strategies to assess the potential use of the associated gut microbiota in CRC studies, antibiotic therapy, and prevention strategies