Frequency comb measurements for 6G terahertz nano/microphotonics and metamaterials.

Next-generation 6G communication holds the potential to revolutionize data transfer, enabling the realization of eXtended Reality (XR) with enhanced sensory experiences. To achieve this, advanced components such as high-performance intensity/phase modulators, waveguides, multiplexers, splitters, combiners, and filters operating in terahertz (THz) regime, specifically within the frequency range of 0.1-1 THz, are essential.

A Federated Reinforcement Learning Framework via a Committee Mechanism for Resource Management in 5G Networks.

This paper proposes a novel decentralized federated reinforcement learning (DFRL) framework that integrates deep reinforcement learning (DRL) with decentralized federated learning (DFL). The DFRL framework boosts efficient virtual instance scaling in Mobile Edge Computing (MEC) environments for 5G core network automation. It enables multiple MECs to collaboratively optimize resource allocation without centralized data sharing.

Evaluating sustainability of CO-mediated pyrolysis of lignocellulose.

Despite the growing interest in biomass as a carbon-neutral resource, technical challenges have limited its comprehensive utilization. Pyrolysis has emerged as a promising method for reducing the carbon footprint by more effectively valorizing carbon in biomass. This study investigated the use of carbon dioxide (CO) in the pyrolysis of pine cone (PC), a lignocellulosic biomass.

Dynamic Bandwidth Slicing in Passive Optical Networks to Empower Federated Learning.

Federated Learning (FL) is a decentralized machine learning method in which individual devices compute local models based on their data. In FL, devices periodically share newly trained updates with the central server, rather than submitting their raw data. The key characteristics of FL, including on-device training and aggregation, make it interesting for many communication domains.

Enhanced Intratumoral Delivery of Immunomodulator Monophosphoryl Lipid A through Hyperbranched Polyglycerol-Coated Biodegradable Nanoparticles.

Immunomodulatory agents have significant potential to enhance cancer treatment but have demonstrated limited efficacy beyond the preclinical setting owing to poor pharmacokinetics and toxicity associated with systemic administration. Conversely, when locally delivered, immunomodulatory agents require repeated administration to optimize immune stimulation. To overcome these challenges, we encapsulated the toll-like receptor 4 agonist monophosphoryl lipid A (MPLA) within hyperbranched polyglycerol-coated biodegradable nanoparticles (NPs) engineered for gradual drug release from the NP core, resulting in a more persistent stimulation of antitumor immune responses while minimizing systemic side effects.

TBHQ Alleviates Particulate Matter-Induced Pyroptosis in Human Nasal Epithelial Cells.

Pyroptosis represents a type of cell death mechanism notable for its cell membrane disruption and the subsequent release of proinflammatory cytokines. The Nod-like receptor family pyrin domain containing inflammasome 3 (NLRP3) plays a critical role in the pyroptosis mechanism associated with various diseases resulting from particulate matter (PM) exposure. Tert-butylhydroquinone (tBHQ) is a synthetic antioxidant commonly used in a variety of foods and products.

Adaptive Dataset Management Scheme for Lightweight Federated Learning in Mobile Edge Computing.

Federated learning (FL) in mobile edge computing has emerged as a promising machine-learning paradigm in the Internet of Things, enabling distributed training without exposing private data. It allows multiple mobile devices (MDs) to collaboratively create a global model. FL not only addresses the issue of private data exposure but also alleviates the burden on a centralized server, which is common in conventional centralized learning.

Deep Reinforcement Learning-Empowered Cost-Effective Federated Video Surveillance Management Framework.

Video surveillance systems are integral to bolstering safety and security across multiple settings. With the advent of deep learning (DL), a specialization within machine learning (ML), these systems have been significantly augmented to facilitate DL-based video surveillance services with notable precision. Nevertheless, DL-based video surveillance services, which necessitate the tracking of object movement and motion tracking (e.

CYR61 confers chemoresistance by upregulating survivin expression in triple-negative breast cancer.

Cysteine-rich angiogenic inducer 61 (CYR61) is a protein from the CCN family of matricellular proteins that play diverse regulatory roles in the extracellular matrix. CYR61 is involved in cell adhesion, migration, proliferation, differentiation, apoptosis, and senescence. Here, we show that CYR61 induces chemoresistance in triple-negative breast cancer (TNBC).

Design optimization and implementation of a Fourier transform spectrometer with rotating motion for 0.1 cm resolution spectroscopy.

In this paper, we present the design optimization and implementation of a high-resolution near-infrared Fourier transform spectrometer (FTS) based on a rotating motion. The FTS system incorporates a rotating mirror-pair for scanning the optical path length (OPL). The design optimization process is performed to maximize the scanning range to obtain a resolution of 0.

Phase-Locked Synthetic Wavelength Interferometer Using a Femtosecond Laser for Absolute Distance Measurement without Cyclic Error.

We present a phase-locked synthetic wavelength interferometer that enables a complete elimination of cyclic errors in absolute distance measurements. With this method, the phase difference between the reference and measurement paths is fed back into a phase lock-in system, which is then used to control the synthetic wavelength and set the phase difference to zero using an external cavity acousto-optic modulator. We validated the cyclic error removal of the proposed phase-locked method by comparing it with the conventional phase-measuring method of the synthetic wavelength interferometer.

Novel Latent Heat Storage Systems Based on Liquid Metal Matrices with Suspended Phase Change Material Microparticles.

Phase change materials (PCMs) are considered useful tools for efficient thermal management and thermal energy utilization in various application fields. In this study, a colloidal PCM-in-liquid metal (LM) system is demonstrated as a novel platform composite with excellent latent heat storage capability, high thermal and electrical conductivities, and unique viscoelastic properties. In the proposed formulation, eutectic Ga-In is utilized as a high-thermal-conductivity and high-fluidity liquid matrix in which paraffinic PCM microparticles with various solid-liquid phase transition temperatures are suspended as fillers.

Ultra-thin light-weight laser-induced-graphene (LIG) diffractive optics.

The realization of hybrid optics could be one of the best ways to fulfill the technological requirements of compact, light-weight, and multi-functional optical systems for modern industries. Planar diffractive lens (PDL) such as diffractive lenses, photonsieves, and metasurfaces can be patterned on ultra-thin flexible and stretchable substrates and be conformally attached on top of arbitrarily shaped surfaces. In this review, we introduce recent research works addressed to the design and manufacturing of ultra-thin graphene optics, which will open new markets in compact and light-weight optics for next-generation endoscopic brain imaging, space internet, real-time surface profilometry, and multi-functional mobile phones.

High-Thermal-Conductivity and High-Fluidity Heat Transfer Emulsion with 89 wt % Suspended Liquid Metal Microdroplets.

Colloidal suspensions of thermally conductive particles in a carrier fluid are considered promising heat transfer fluids for various thermal energy transfer applications, such as transportation, plants, electronics, and renewable energy systems. The thermal conductivity () of the particle-suspended fluids can be improved substantially by increasing the concentration of conductive particles above a "thermal percolation threshold," which is limited because of the vitrification of the resulting fluid at the high particle loadings. In this study, eutectic Ga-In liquid metal (LM) was employed as a soft high- filler dispersed as microdroplets at high loadings in paraffin oil (as a carrier fluid) to produce an emulsion-type heat transfer fluid with the combined advantages of high thermal conductivity and high fluidity.

Cognitive Video Surveillance Management in Hierarchical Edge Computing System with Long Short-Term Memory Model.

Nowadays, deep learning (DL)-based video surveillance services are widely used in smart cities because of their ability to accurately identify and track objects, such as vehicles and pedestrians, in real time. This allows a more efficient traffic management and improved public safety. However, DL-based video surveillance services that require object movement and motion tracking (e.

Deep-Reinforcement-Learning-Based IoT Sensor Data Cleaning Framework for Enhanced Data Analytics.

The Internet of things (IoT) combines different sources of collected data which are processed and analyzed to support smart city applications. Machine learning and deep learning algorithms play a vital role in edge intelligence by minimizing the amount of irrelevant data collected from multiple sources to facilitate these smart city applications. However, the data collected by IoT sensors can often be noisy, redundant, and even empty, which can negatively impact the performance of these algorithms.

Acute depletion of human core nucleoporin reveals direct roles in transcription control but dispensability for 3D genome organization.

The nuclear pore complex (NPC) comprises more than 30 nucleoporins (NUPs) and is a hallmark of eukaryotes. NUPs have been suggested to be important in regulating gene transcription and 3D genome organization. However, evidence in support of their direct roles remains limited.

Direct-Writable and Thermally One-Step Curable "Water-Stained" Epoxy Composite Inks.

In this study, a simple method for preparing direct-writable and thermally one-step curable epoxy composite inks was proposed. Specifically, colloidal inks containing a mixture of ordinary epoxy resin and anhydride-type hardener with the suspended alumina microplates, as exemplary fillers, are "stained" with small amounts of water. This increases the elasticity of the ink via the interparticle capillary attraction and promotes curing of the epoxy matrix in low-temperature ranges, causing the three-dimensional (3D) printed ink to avoid structural disruption during one-step thermal curing without the tedious pre-curing step.

3D-printable, lightweight, and electrically conductive metal inks based on evaporable emulsion templates jammed with natural rheology modifiers.

Conductive metal inks with 3D-printable rheological properties have gained considerable attention, owing to their potential for manufacturing 3D electronics. Typically, such inks are formulated with high volume fractions of metal particles to achieve both rheological and electrical percolation. However, this leads to a high product cost and weight, making this approach potentially undesirable for practical application.

A Sustainable Business Model for a Neutral Host Supporting 5G and beyond (5GB) Ultra-Dense Networks: Challenges, Directions, and Architecture.

With the deployment of the fifth generation (5G) mobile network systems and the envisioned heterogeneous ultra-dense networks (UDNs), both small cell (SmC) and distributed antenna system (DAS) technologies are required by mobile network operators (MNOs) and venue owners to support multiple spectrum bands, multiple radio access technologies (RATs), multiple optical central offices (COs), and multiple MNOs. As a result, the neutral host business model representing a third party responsible for managing the network enterprise on behalf of multiple MNOs has emerged as a potential solution, mainly influenced by the desire to provide a high user experience without significantly increasing the total cost of ownership (TCO). However, designing a sustainable business model for a neutral host is a nontrivial task, especially when considered in the context of 5G and beyond (5GB) UDNs.

EggBlock: Design and Implementation of Solar Energy Generation and Trading Platform in Edge-Based IoT Systems with Blockchain.

In this paper, to balance power supplement from the solar energy's intermittent and unpredictable generation, we design a solar energy generation and trading platform (EggBlock) using Internet of Things (IoT) systems and blockchain technique. Without a centralized broker, the proposed EggBlock platform can promote energy trading between users equipped with solar panels, and balance demand and generation. By applying the second price sealed-bid auction, which is one of the suitable pricing mechanisms in the blockchain technique, it is possible to derive truthful bidding of market participants according to their utility function and induce the proceed transaction.