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As the global energy landscape transitions towards a more sustainable future, hydrogen has emerged as a promising energy carrier due to its potential to decarbonize various sectors. However, the economic competitiveness of hydrogen production by water electrolysis strongly depends on renewable energy source (RES) availability. Thus, it is necessary to overcome the challenges related to the intermittent nature of RESs. This paper presents a comprehensive techno-economic analysis of complementing green hydrogen production with grid electricity. An evaluation model for the levelized cost of hydrogen (LCOH) is proposed, considering both CO2 emissions and the influence of RES fluctuations on electrolyzers. A minimum load restriction is required to avoid crossover gas. Moreover, a new operation strategy is developed for hydrogen production plants to determine optimal bidding in the grid electricity market to minimize the LCOH. We evaluate the feasibility of the proposed approach with a case study based on data from the Kyushu area in Japan. The results show that the proposed method can reduce the LCOH by 11% to 33%, and increase hydrogen productivity by 86% to 140%, without significantly increasing CO2 emission levels.

This paper proposes a scheme for enhancing covert communication in cognitive radio networks (CRNs) using a reconfigurable intelligent surface (RIS), which ensures that transmissions by secondary users (SUs) remains statistically undetectable by adversaries (e.g., wardens like Willie). However, there exist stringent challenges in CRNs due to the dual constraints of avoiding detection and preventing harmful interference to primary users (PUs). Leveraging the RIS’s ability to dynamically reconfigure the wireless propagation environment, our scheme jointly optimizes the SU’s transmit power, communication block length, and RIS’s passive beamforming (phase shifts) to maximize the effective covert throughput (ECT) under rigorous covertness constraints quantified by detection error probability or relative entropy while strictly adhering to PU interference limits. Crucially, the RIS configuration is explicitly designed to simultaneously enhance signal quality at the legitimate SU receiver and degrade signal quality at the warden, thereby relaxing the inherent trade-off between covertness and throughput imposed by the fundamental square root law. Furthermore, we analyze the impact of unequal transmit prior probabilities (UTPPs), demonstrating their superiority over equal priors (ETPPs) in flexibly balancing throughput and covertness, and extend the framework to practical scenarios with Poisson packet arrivals typical of IoT networks. Extensive results confirm that RIS assistance significantly boosts ECT compared to non-RIS baselines and establishes the RIS as a key enabler for secure and spectrally efficient next-generation cognitive networks.

This literature review covers the solubility and processability of fluoropolymer polyvinylidine fluoride (PVDF). Fluoropolymers consist of a carbon backbone chain with multiple connected C–F bonds; they are typically nonreactive and nontoxic and have good thermal stability. Their processing, recycling and reuse are rapidly becoming more important to the circular economy as fluoropolymers find widespread application in diverse sectors including construction, automotive engineering and electronics. The partially fluorinated polymer PVDF is in strong demand in all of these areas; in addition to its desirable inertness, which is typical of most fluoropolymers, it also has a high dielectric constant and can be ferroelectric in some of its crystal phases. However, processing and reusing PVDF is a challenging task, and this is partly due to its limited solubility. This review begins with a discussion on the useful properties and applications of PVDF, followed by a discussion on the known solvents and diluents of PVDF and how it can be formed into membranes. Finally, we explore the limitations of PVDF’s chemical and thermal stability, with a discussion on conditions under which it can degrade. Our aim is to provide a condensed overview that will be of use to both chemists and engineers who need to work with PVDF.

The fifth generation (5G) wireless communication networks are being deployed worldwide from 2020 and more capabilities are in the process of being standardized, such as mass connectivity, ultra-reliability, and guaranteed low latency. However, 5G will not meet all requirements of the future in 2030 and beyond, and sixth generation (6G) wireless communication networks are expected to provide global coverage, enhanced spectral/energy/cost efficiency, better intelligence level and security, etc. To meet these requirements, 6G networks will rely on new enabling technologies, i.e., air interface and transmission technologies and novel network architecture, such as waveform design, multiple access, channel coding schemes, multi-antenna technologies, network slicing, cell-free architecture, and cloud/fog/edge computing. Our vision on 6G is that it will have four new paradigm shifts. First, to satisfy the requirement of global coverage, 6G will not be limited to terrestrial communication networks, which will need to be complemented with non-terrestrial networks such as satellite and unmanned aerial vehicle (UAV) communication networks, thus achieving a space-air-ground-sea integrated communication network. Second, all spectra will be fully explored to further increase data rates and connection density, including the sub-6 GHz, millimeter wave (mmWave), terahertz (THz), and optical frequency bands. Third, facing the big datasets generated by the use of extremely heterogeneous networks, diverse communication scenarios, large numbers of antennas, wide bandwidths, and new service requirements, 6G networks will enable a new range of smart applications with the aid of artificial intelligence (AI) and big data technologies. Fourth, network security will have to be strengthened when developing 6G networks. This article provides a comprehensive survey of recent advances and future trends in these four aspects. Clearly, 6G with additional technical requirements beyond those of 5G will enable faster and further communications to the extent that the boundary between physical and cyber worlds disappears.

Although epidermal growth factor receptor tyrosine kinase inhibitors (EGFR‐TKIs), especially third‐generation TKIs, have significantly improved the progression‐free survival and overall survival of non‐small cell lung cancer (NSCLC) patients with EGFR mutation, TKI resistance is inevitable for most patients. Over the past few years, immune checkpoint inhibitors (ICIs) have significantly improved the survival for EGFR‐wild type NSCLC patients. However, no significantly improved benefits were observed with ICI monotherapy in EGFR‐mutated patients. EGFR‐mutated NSCLC shows more heterogeneity in tumor mutational burden (TMB), programmed cell death‐ligand 1 (PD‐L1), and immune microenvironment characteristics. Whether ICIs are suitable for EGFR‐mutated NSCLC patients remains to be elucidated. In this review, we summarized clinical trials of ICIs or combined therapy in EGFR‐mutated NSCLC patients. We further discussed the factors determining the efficacy of ICIs in EGFR‐mutated NSCLC patients, the mutation subtypes and microenvironment characteristics of potential responders. More importantly, we provided insights into areas worth further investigation in the future. In this review, we summarized clinical trials of immune checkpoint inhibitors (ICIs) or combined therapy in EGFR‐mutated NSCLC patients. We further discussed the factors determining the efficacy of ICIs in EGFR‐mutated NSCLC patients, the mutation subtypes, and microenvironment characteristics of potential responders. More importantly, we provided insights into areas worth further investigation in the future.

Due to the noncentered, self-organizing, and self-healing characteristics, mobile ad hoc networks (MANET) have been more and more widely used as an alternative access technology for regions having no fixed infrastructure. On-demand routing protocols (e.g., ad hoc on-demand distance vector (AODV)) are used to cope with the rapidly changing topology of MANET and reduce the network overhead. Taking delay, stability, and remaining energy of nodes into consideration, a fuzzy-logic-assisted AODV (FL-AODV) routing algorithm is proposed in this paper to further improve the reliability of the route in MANET. In the route discovery phase, the node with the highest reliability is selected as the relay node, and the route with the highest accumulated reliability is reserved for data transmission. Simulation results show that, compared with the traditional AODV protocol and the fuzzy logic routing algorithm (FLRA), the proposed routing protocol has higher reliability without increasing delay, i.e., better link connectivity and longer route life. The average routing reliability is about 18% higher than AODV while the average delay is the same low when the number of node greater than 70.

Background Protein-protein interactions play a fundamental role in elucidating the molecular mechanisms of biomolecular function, signal transductions and metabolic pathways of living organisms. Although high-throughput technologies such as yeast two-hybrid system and affinity purification followed by mass spectrometry are widely used in model organisms, the progress of protein-protein interactions detection in plants is rather slow. With this motivation, our work presents a computational approach to predict protein-protein interactions in Oryza sativa . Results To better understand the interactions of proteins in Oryza sativa , we have developed PRIN, a Predicted Rice Interactome Network. Protein-protein interaction data of PRIN are based on the interologs of six model organisms where large-scale protein-protein interaction experiments have been applied: yeast ( Saccharomyces cerevisiae ), worm ( Caenorhabditis elegans ), fruit fly ( Drosophila melanogaster ), human ( Homo sapiens ), Escherichia coli K12 and Arabidopsis thaliana . With certain quality controls, altogether we obtained 76,585 non-redundant rice protein interaction pairs among 5,049 rice proteins. Further analysis showed that the topology properties of predicted rice protein interaction network are more similar to yeast than to the other 5 organisms. This may not be surprising as the interologs based on yeast contribute nearly 74% of total interactions. In addition, GO annotation, subcellular localization information and gene expression data are also mapped to our network for validation. Finally, a user-friendly web interface was developed to offer convenient database search and network visualization. Conclusions PRIN is the first well annotated protein interaction database for the important model plant Oryza sativa . It has greatly extended the current available protein-protein interaction data of rice with a computational approach, which will certainly provide further insights into rice functional genomics and systems biology. PRIN is available online at http://bis.zju.edu.cn/prin/ .

Hydrogel-based flexible sensors have demonstrated significant advantages in the fields of flexible electronics and human–machine interactions (HMIs), including outstanding flexibility, high sensitivity, excellent conductivity, and exceptional biocompatibility, making them ideal materials for next-generation smart HMI sensors. However, traditional hydrogel sensors still face numerous challenges in terms of reliability, multifunctionality, and environmental adaptability, which limit their performance in complex application scenarios. Nanomaterial-based composite hydrogels significantly improve the mechanical properties, conductivity, and multifunctionality of hydrogels by incorporating conductive nanomaterials, thereby driving the rapid development of wearable sensors for HMIs. This review systematically summarizes the latest research progress on hydrogels based on carbon nanomaterials, metal nanomaterials, and two-dimensional MXene nanomaterials, and provides a comprehensive analysis of their sensing mechanisms in HMI, including triboelectric nanogenerator mechanism, stress-resistance response mechanism, and electrophysiological acquisition mechanism. The review further explores the applications of composite hydrogel-based sensors in personal electronic device control, virtual reality/augmented reality (VR/AR) game interaction, and robotic control. Finally, the current technical status and future development directions of nanomaterial composite hydrogel sensors are summarized. We hope that this review will provide valuable insights and inspiration for the future design of nanocomposite hydrogel-based flexible sensors in HMI applications.

Grout veins formed by advance grouting influence bulk stiffness and permeability. We present a width‑centric, image‑to‑mechanics framework that performs SES preprocessing (HDMR‑based multi‑feature fusion and a moment‑based sub‑pixel localizer), extracts graph‑theoretic centerlines, and estimates vein widths via T MSE -adaptive segmentation, which directly supports property estimation. On a lab‑scale image set, SES improves segmentation across seven backbones, and the resulting width/orientation statistics yield laboratory‑scale estimates of elastic modulus and permeability. Worst‑case errors are 8.83% (modulus) and 10.42% (permeability); these do not meet design‑grade tolerances. The method is therefore positioned for screening/monitoring under controlled conditions, not for design decisions. We clarify assumptions (local monotonic edge profile, 2‑D effective analysis), provide stopping criteria and parameters for reproducibility.

Obesity is a risk factor for breast cancer and also predicts poor clinical outcomes regardless of menopausal status. Contributing to the poor clinical outcomes is the suboptimal efficacy of standard therapies due to dose limiting toxicities and obesity-related complications, highlighting the need to develop novel therapeutic approaches for treating obese patients. We recently found that obesity leads to an increase in tumor-infiltrating macrophages with activated NLRC4 inflammasome and increased interleukin (IL)−1β production. IL-1β, in turn, leads to increased angiogenesis and cancer progression. Using Next Generation RNA sequencing, we identified an NLRC4/IL-1β-dependent upregulation of angiopoietin-like 4 (ANGPTL4), a known angiogenic factor in cancer, in tumors from obese mice. ANGPTL4-deficiency by genetic knockout or treatment with a neutralizing antibody led to a significant reduction in obesity-induced angiogenesis and tumor growth. At a mechanistic level, ANGPTL4 expression is induced by IL-1β from primary adipocytes in a manner dependent on NF-κB- and MAP kinase-activation, which is further enhanced by hypoxia. This report shows that adipocyte-derived ANGPTL4 drives disease progression under obese conditions and is a potential therapeutic target for treating obese breast cancer patients.