Asymptotic CRB Analysis of Random RIS-Assisted Large-Scale Localization Systems

This paper studies the performance of a randomly RIS-assisted multi-target localization system, in which the configurations of the RIS are randomly set to avoid high-complexity optimization. We first focus on the scenario where the number of RIS elements is significantly large, and then obtain the scaling law of Cram\'er-Rao bound (CRB) under certain conditions, which shows that CRB decreases in the third or fourth order as the RIS dimension increases. Second, we extend our analysis to large systems where both the number of targets and sensors is substantial. Under this setting, we explore two common RIS models: the constant module model and the discrete amplitude model, and illustrate how the random RIS configuration impacts the value of CRB. Numerical results demonstrate that asymptotic formulas provide a good approximation to the exact CRB in the proposed randomly configured RIS systems

A Wi-Fi Signal-Based Human Activity Recognition Using High-Dimensional Factor Models

Passive sensing techniques based on Wi-Fi signals have emerged as a promising technology in advanced wireless communication systems due to their widespread application and cost-effectiveness. However, the proliferation of low-cost Internet of Things (IoT) devices has led to dense network deployments, resulting in increased levels of noise and interference in Wi-Fi environments. This, in turn, leads to noisy and redundant Channel State Information (CSI) data. As a consequence, the accuracy of human activity recognition based on Wi-Fi signals is compromised. To address this issue, we propose a novel CSI data signal extraction method. We established a human activity recognition system based on the Intel 5300 network interface cards (NICs) and collected a dataset containing six categories of human activities. Using our approach, signals extracted from the CSI data serve as inputs to machine learning (ML) classification algorithms to evaluate classification performance. In comparison to ML methods based on Principal Component Analysis (PCA), our proposed High-Dimensional Factor Model (HDFM) method improves recognition accuracy by 6.8%

Wireless Regional Imaging through Reconfigurable Intelligent Surfaces: Passive Mode

In this paper, we propose a multi-RIS-aided wireless imaging framework in 3D facing the distributed placement of multi-sensor networks. The system creates a randomized reflection pattern by adjusting the RIS phase shift, enabling the receiver to capture signals within the designated space of interest (SoI). Firstly, a multi-RIS-aided linear imaging channel modeling is proposed. We introduce a theoretical framework of computational imaging to recover the signal strength distribution of the SOI. For the RIS-aided imaging system, the impact of multiple parameters on the performance of the imaging system is analyzed. The simulation results verify the correctness of the proposal. Furthermore, we propose an amplitude-only imaging algorithm for the RIS-aided imaging system to mitigate the problem of phase unpredictability. Finally, the performance verification of the imaging algorithm is carried out by proof of concept experiments under reasonable parameter settings

Design of Reconfigurable Intelligent Surfaces for Wireless Communication: A Review

Existing literature reviews predominantly focus on the theoretical aspects of reconfigurable intelligent surfaces (RISs), such as algorithms and models, while neglecting a thorough examination of the associated hardware components. To bridge this gap, this research paper presents a comprehensive overview of the hardware structure of RISs. The paper provides a classification of RIS cell designs and prototype systems, offering insights into the diverse configurations and functionalities. Moreover, the study explores potential future directions for RIS development. Notably, a novel RIS prototype design is introduced, which integrates seamlessly with a communication system for performance evaluation through signal gain and image formation experiments. The results demonstrate the significant potential of RISs in enhancing communication quality within signal blind zones and facilitating effective radio wave imaging

Weakly activated core neuroinflammation pathways were identified as a central signaling mechanism contributing to the chronic neurodegeneration in Alzheimer\u27s disease

OBJECTIVES: Neuroinflammation signaling has been identified as an important hallmark of Alzheimer\u27s disease (AD) in addition to amyloid β plaques (Aβ) and neurofibrillary tangles (NFTs). However, the molecular mechanisms and biological processes of neuroinflammation remain unclear and have not well delineated using transcriptomics data available. Our objectives are to uncover the core neuroinflammation signaling pathways in AD using integrative network analysis on the transcriptomics data. MATERIALS AND METHODS: From a novel perspective, i.e., investigating weakly activated molecular signals (rather than the strongly activated molecular signals), we developed integrative and systems biology network analysis to uncover potential core neuroinflammation signaling targets and pathways in AD using the two large-scale transcriptomics datasets, i.e., Mayo Clinic (77 controls and 81 AD samples) and ROSMAP (97 controls and 260 AD samples). RESULTS: Our analysis identified interesting core neuroinflammation signaling pathways, which are not systematically reported in the previous studies of AD. Specifically, we identified 7 categories of signaling pathways implicated on AD and related to virus infection: immune response, x-core signaling, apoptosis, lipid dysfunctional, biosynthesis and metabolism, and mineral absorption signaling pathways. More interestingly, most of the genes in the virus infection, immune response, and x-core signaling pathways are associated with inflammation molecular functions. The x-core signaling pathways were defined as a group of 9 signaling proteins: MAPK, Rap1, NF-kappa B, HIF-1, PI3K-Akt, Wnt, TGF-beta, Hippo, and TNF, which indicated the core neuroinflammation signaling pathways responding to the low-level and weakly activated inflammation and hypoxia and leading to the chronic neurodegeneration. It is interesting to investigate the detailed signaling cascades of these weakly activated neuroinflammation signaling pathways causing neurodegeneration in a chronic process, and consequently uncover novel therapeutic targets for effective AD treatment and prevention. CONCLUSIONS: The potential core neuroinflammation and associated signaling targets and pathways were identified using integrative network analysis on two large-scale transcriptomics datasets of AD

Group Buying of Competing Retailers with Strategic Inventory

Group buying involves cooperation and competition among multiple retailers, and strategic inventory can affect this relationship. To investigate the interaction between them, we consider a two-tier distribution channel consisting of one supplier and two competing retailers who can hold strategic inventory, and explore the effect of strategic inventory on the operational decisions and profits of all members of the supply chain. In this research, we make a major contribution by integrating strategic inventory into group buying. Furthermore, we make another major contribution by examining the impact of strategic inventory on the operational decisions of the supplier and the retailers in a competing environment. We construct a Stackelberg game, where the supplier is the leader and the retailers are followers. We find that the retailers will hold strategic inventory under group buying only when the holding cost is low or the basic wholesale price is high. Moreover, a higher holding cost is detrimental to the retailers while beneficial to the supplier, and intensified competition is detrimental to both the retailers and the supplier. Interestingly, contrary to the common view that inventory should be reduced or not held, the retailers have incentives to hold strategic inventory. The supplier also prefers that because strategic inventory benefits her. Therefore, strategic inventory achieves a win–win outcome for the supplier and the retailers. In addition, strategic inventory can improve supply chain performance and consumer surplus

Group Buying of Competing Retailers with Strategic Inventory

Group buying involves cooperation and competition among multiple retailers, and strategic inventory can affect this relationship. To investigate the interaction between them, we consider a two-tier distribution channel consisting of one supplier and two competing retailers who can hold strategic inventory, and explore the effect of strategic inventory on the operational decisions and profits of all members of the supply chain. In this research, we make a major contribution by integrating strategic inventory into group buying. Furthermore, we make another major contribution by examining the impact of strategic inventory on the operational decisions of the supplier and the retailers in a competing environment. We construct a Stackelberg game, where the supplier is the leader and the retailers are followers. We find that the retailers will hold strategic inventory under group buying only when the holding cost is low or the basic wholesale price is high. Moreover, a higher holding cost is detrimental to the retailers while beneficial to the supplier, and intensified competition is detrimental to both the retailers and the supplier. Interestingly, contrary to the common view that inventory should be reduced or not held, the retailers have incentives to hold strategic inventory. The supplier also prefers that because strategic inventory benefits her. Therefore, strategic inventory achieves a win–win outcome for the supplier and the retailers. In addition, strategic inventory can improve supply chain performance and consumer surplus

Effect of Biochar on Soil Temperature under High Soil Surface Temperature in Coal Mined Arid and Semiarid Regions

High soil surface temperature and loosened soil are major limiting factors of plant productivity in arid and semi-arid coal mining areas of China. Moreover, the extensive and illegitimate burning of crop residues is causing environmental pollution; whereas, these residues could be converted to biochar to benefit soil quality. In this study, the effect of wheat straw biochar (WSB) at rates of 0% (control, CK), 1% (low, LB), 2% (medium, MB) and 4% (high, HB) on soil temperature at different depths (5, 10, 15, and 20 cm) and moisture levels (10 and 20%) was investigated under high soil surface temperature of 50 °C and air humidity of 40%. Our data suggested that soil bulk density was inversely, and soil moisture was directly corelated with soil thermal parameters. Moreover, the increasing rate of WSB addition linearly decreased the soil thermal properties. The maximum decrease in soil bulk density at both moisture levels (10% and 20%) was measured in HB treatment compared to respective CKs. The highest decrease in soil thermal conductivity (59.8% and 24.7%) was found under HB treatment in comparison to respective controls (CK10% and CK20% moisture). The soil volumetric heat capacity was also strongly corelated with soil moisture content (r = 0.91). The WSB treatments displayed differential responses to soil temperature. Under 10% soil moisture, temperature of LB, MB and HB treatments was higher as compared to CK at 5–20 cm depth, and MB treated soil had the smallest increase in temperature. At the 15-cm depth, the MB treatment decreased the temperature by 0.93 °C as compared to the CK20%. Therefore, the effect of WSB on soil temperature was influenced by soil moisture content, soil depth and WSB application rates. It suggested that MB treatment could be a useful farming practice for mitigating soil temperature fluctuation