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Abstract Stretchable optoelectronic devices are typically realized through a 2D integration of rigid components and elastic interconnectors to maintain device performance under stretching deformation. However, such configurations inevitably sacrifice the area ratio of active components to enhance the maximum interconnector strain. We herein propose a 3D buckled height-alternant architecture for stretchable OLEDs that enables the high active-area ratio and the enhanced maximum strain simultaneously. Along with the optimal dual serpentine structure leading to a low critical buckling strain, a pop-up assisting adhesion blocking layer is proposed based on an array of micro concave structures for spatially selective adhesion control, enabling a reliable transition to a 3D buckled state with OLED-compatible processes. Consequently, we demonstrate stretchable OLEDs with both the high initial active-area ratio of 85% and the system strain of up to 40%, which would require a lateral interconnector strain of up to 512% if it were attained with conventional 2D rigid-island approaches. These OLEDs are shown to exhibit reliable performance under 2,000 biaxial cycles of 40% system strain. 7 × 7 passive-matrix OLED displays with the similar level of the initial active-area ratio and maximum system strain are also demonstrated.

Abstract Stretchable organic light-emitting diodes (OLEDs) have emerged as promising optoelectronic devices with exceptional degree of freedom in form factors. However, stretching OLEDs often results in a reduction in the geometrical fill factor (FF), that is the ratio of an active area to the total area, thereby limiting their potential for a broad range of applications. To overcome these challenges, we propose a three-dimensional (3D) architecture adopting a hidden active area that serves a dual role as both an emitting area and an interconnector. For this purpose, an ultrathin OLED is first attached to a 3D rigid island array structure through quadaxial stretching for precise, deformation-free alignment. A portion of the ultrathin OLED is concealed by letting it ‘fold in’ between the adjacent islands in the initial, non-stretched condition and gradually surfaces to the top upon stretching. This design enables the proposed stretchable OLEDs to exhibit a relatively high FF not only in the initial state but also after substantial deformation corresponding to a 30% biaxial system strain. Moreover, passive-matrix OLED displays that utilize this architecture are shown to be configurable for compensation of post-stretch resolution loss, demonstrating the efficacy of the proposed approach in realizing the full potential of stretchable OLEDs.

Abstract Microglia play a crucial role in synaptic elimination by engulfing dystrophic neurons via triggering receptors expressed on myeloid cells 2 (TREM2). They are also involved in the clearance of beta‐amyloid (Aβ) plaques in Alzheimer's disease (AD); nonetheless, the driving force behind TREM2‐mediated phagocytosis of beta‐amyloid (Aβ) plaques remains unknown. Here, using advanced 2D/3D/4D co‐culture systems with loss‐of‐function mutations in TREM2 (a frameshift mutation engineered in exon 2) brain organoids/microglia/assembloids, it is identified that the clearance of Aβ via TREM2 is accelerated by externalized phosphatidylserine (ePtdSer) generated from dystrophic neurons surrounding the Aβ plaques. Moreover, it is investigated whether microglia from both sporadic (CRISPR‐Cas9‐based APOE4 lines) and familial (APPNL‐G‐F/MAPT double knock‐in mice) AD models show reduced levels of TREM2 and lack of phagocytic activity toward ePtdSer‐positive Aβ plaques. Herein new insight is provided into TREM2‐dependent microglial phagocytosis of Aβ plaques in the context of the presence of ePtdSer during AD progression.

When addressing large-scale electromagnetic problems using the finite element method (FEM), the resulting matrices are typically sparse, necessitating numerous sparse matrix-vector multiplication (SpMV) operations. To handle this efficiently, research has focused on leveraging large-scale parallel processing with graphics processing units (GPUs). These GPUs can be controlled directly using NVIDIA’s Compute Unified Device Architecture (CUDA). In this paper, we analyze electromagnetic scattering for dielectric and dielectric-coated structures using iterative solvers with FEM. To accelerate the handling of the large-scale matrices generated during this process, we employ compressed sparse row (CSR) format, various preconditioners, and CUDA-based GPU parallelization. We verify the accuracy of our results by comparing them with those obtained using the commercial electromagnetic software High Frequency Structure Simulator (HFSS) and our custom-developed MATLAB-based FEM code. Performance improvements are assessed by comparing these results with those from MATLAB’s backslash direct solver under single-core processing conditions.

Abstract Background Fragmentomics, the investigation of fragmentation patterns of cell-free DNA (cfDNA), has emerged as a promising strategy for the early detection of multiple cancers in the field of liquid biopsy. However, the clinical application of this approach has been hindered by a limited understanding of cfDNA biology. Furthermore, the prevalence of hematopoietic cell-derived cfDNA in plasma complicates the in vivo investigation of tissue-specific cfDNA other than that of hematopoietic origin. While conventional two-dimensional cell lines have contributed to research on cfDNA biology, their limited representation of in vivo tissue contexts underscores the need for more robust models. In this study, we propose three-dimensional organoids as a novel in vitro model for studying cfDNA biology, focusing on multifaceted fragmentomic analyses. Results We established nine patient-derived organoid lines from normal lung airway, normal gastric, and gastric cancer tissues. We then extracted cfDNA from the culture medium of these organoids in both proliferative and apoptotic states. Using whole-genome sequencing data from cfDNA, we analyzed various fragmentomic features, including fragment size, footprints, end motifs, and repeat types at the end. The distribution of cfDNA fragment sizes in organoids, especially in apoptosis samples, was similar to that found in plasma, implying occupancy by mononucleosomes. The footprints determined by sequencing depth exhibited distinct patterns depending on fragment sizes, reflecting occupancy by a variety of DNA-binding proteins. Notably, we discovered that short fragments (

Abstract We present an in-depth single-cell atlas of in vitro multiculture systems on human primary airway epithelium derived from normal and diseased lungs of 27 individual donors. Our large-scale single-cell profiling identified new cell states and differentiation trajectories of rare airway epithelial cell types in human distal lungs. By integrating single-cell datasets of human lung tissues, we discovered immune-primed subsets enriched in lungs and organoids derived from patients with chronic respiratory disease. To demonstrate the full potential of our platform, we further illustrate transcriptomic responses to various respiratory virus infections in vitro airway models. Our work constitutes a single-cell roadmap for the cellular and molecular characteristics of human primary lung cells in vitro and their relevance to human tissues in vivo.

Abstract Near-infrared organic light-emitting diodes (NIR OLEDs) with heavy metals are regularly reported due to the advantages of their various applications in healthcare services, veil authentication, and night vision displays. For commercial applications, it is necessary to look at radiance capacity (RC) instead of radiance because of power consumption. However, recent papers still reported only simple high radiance performance and do not look at device from the point of view of RC. To overcome this hurdle, we designed Ir(III)-based heteroleptic NIR materials with two types of auxiliary ligand. The proposed emitters achieve a highly oriented horizontal dipole ratio (Ir(mCPDTiq)2tmd, complex 1: 80%, Ir(mCPDTiq)2acac, complex 2: 81%) with a short radiative lifetime (1: 386 ns, 2: 323 ns). The device also shows an extremely low turn-on voltage (Von) of 2.2 V and a high RC of 720 mW/sr/m2/V. The results on the Von and RC of the device is demonstrated an outstanding performance among the Ir(III)-based NIR OLEDs with a similar emission peak.

Abstract Background Although single-cell RNA sequencing of xenograft samples has been widely used, no comprehensive bioinformatics pipeline is available for human and mouse mixed single-cell analyses. Considering the numerous homologous genes across the human and mouse genomes, misalignment errors should be evaluated, and a new algorithm is required. We assessed the extents and effects of misalignment errors and exonic multi-mapping events when using human and mouse combined reference data and developed a new bioinformatics pipeline with expression-based species deconvolution to minimize errors. We also evaluated false-positive signals presumed to originate from ambient RNA of the other species and address the importance to computationally remove them. Result Error when using combined reference account for an average of 0.78% of total reads, but such reads were concentrated to few genes that were greatly affected. Human and mouse mixed single-cell data, analyzed using our pipeline, clustered well with unmixed data and showed higher k-nearest-neighbor batch effect test and Local Inverse Simpson’s Index scores than those derived from Cell Ranger (10 × Genomics). We also applied our pipeline to multispecies multisample single-cell library containing breast cancer xenograft tissue and successfully identified all samples using genomic array and expression. Moreover, diverse cell types in the tumor microenvironment were well captured. Conclusion We present our bioinformatics pipeline for mixed human and mouse single-cell data, which can also be applied to pooled libraries to obtain cost-effective single-cell data. We also address misalignment, multi-mapping error, and ambient RNA as a major consideration points when analyzing multispecies single-cell data.

Gastric cancer is commonly treated by chemotherapy using 5-fluorouracil derivatives and platinum combination, but predictive biomarker remains lacking. Here, the authors develop a 30-gene prediction model to determine the responsiveness to 5-fluorouracil and oxaliplatin-based chemotherapy through the integrative profiling of patient-derived xenografts

Abstract Vertical sleeve gastrectomy (VSG) is the most commonly performed bariatric/metabolic surgery, exhibiting a high rate of diabetes remission in humans. To elucidate the molecular mechanisms of VSG, we performed transcriptomic analysis of the liver, fat, and muscle in VSG mice. C57BL/6 mice fed a high-fat diet were randomly assigned to sham or VSG surgery. The sham-operated mice were fed ad libitum (sham group) or pair-fed (sham-PF group) matching their food intake to the VSG-operated mice. Comparative transcriptomic analysis of the liver, fat, and muscle using RNA sequencing was performed. VSG reduced body weight and improved glucose tolerance compared to the sham group, but not more than the sham-PF group. Improvement in fatty liver and adipose tissue inflammation was comparable between VSG and sham-PF. However, global gene expression profiles showed distinctive changes in the liver, fat, and muscle of the VSG group compared to both the sham or sham-PF groups. The liver showed the most prominent gene expression changes. Immune response-related pathways were commonly upregulated in the three organs of the VSG group compared to the sham or sham-PF. VSG induces organ-specific gene expression changes in the liver, fat, and muscle, which may play critical roles in metabolic improvements after VSG.

While organic light‐emitting diodes (OLEDs) have seen huge success as light sources in high‐end displays, efforts are being made to extend their spectral coverage beyond the visible region. Among such endeavors, the development of ultraviolet (UV) OLEDs is particularly of interest due to the unique applications of UV light in a variety of areas such as security, sterilization, phototherapy, etc. However, OLEDs that emit UV light are very challenging to realize due to limitations such as high‐energy‐induced molecular instability, the rarity of adequate emitting layers, and material optical properties that are very different from those of visible OLEDs. Herein, UV OLEDs are realized using 3‐(Biphenyl‐4‐yl)‐5‐(4‐tert‐butylphenyl)‐4‐phenyl‐4 H‐1,2,4‐triazole (TAZ) as emitters in both top‐emitting and bottom‐emitting configurations. High absorption of common plastic substrates is carefully considered, and semitransparent refractory characteristics of metals under UV are exploited to form flexible dielectric−metal−dielectric electrodes with high transparency in UV. As a result, highly flexible UV OLEDs with a peak wavelength of 371 nm and a full width half maximum as small as 13 nm are realized.

Hair follicles (HFs) are sensitive to chemotherapy but recover from quiescent HF stem cells, although sometimes chemotherapy results in permanent loss. Here, Kim et al. establish a model of permanent chemotherapy-induced alopecia to uncover the underlying mechanisms depleting human HF stem cells.

We investigate how different types of haptic feedback to hand affect the perceived size of a virtual object. Multiple haptic interfaces are designed to deliver different types of haptic feedback to hand. In the preliminary experiment, we investigated the effect of cutaneous feedback on the perceived size of the virtual object. The experimental results indicate that the availability of cutaneous feedback resulted in an insignificant effect on the perceived size of the virtual object. On the other hand, the availability of cutaneous feedback led the participants to exert significantly smaller grip force than when there is only force feedback. In the main experiment, we provided haptic feedback to the dorsum of the hand to modulate the hand kinesthesia at the moment of contact with the virtual object. For the reference stimuli, skin-stretch or vibrotactile feedback was provided to a participant's hand along with cutaneous and force feedback to the fingertips. Reference stimuli were rendered only with cutaneous and force feedback to the fingers. The experimental results indicate a significant effect of the type of haptic feedback to the dorsum of a hand. The skin-stretch feedback led the participants to feel virtual objects with a size of 40 mm, larger than without the feedback. The vibrotactile feedback resulted in the perceived size of virtual objects with a size of 20 or 40 mm, smaller than without the vibrotactile feedback.

We propose the conditions for maximum overall efficiency at the constraint of satisfying asymmetric load power requirements for each receiver, for multiple-receivers wireless power transfer. Previously, the limitation of multiple-receiver analysis was that only the efficiency was maximized, whereas the requirements of load power were neglected. In many cases, conventional efficiency maximization assigns insufficient power to receivers far from the transmitter, while supplying excessive power to receivers near the transmitter. To resolve this limitation, we maximize the efficiency at the constraints of specified load power for each receiver. The proposed closed-form equation provides an optimum TX coil current amplitude, and the optimum load resistances of each receiver, to achieve the maximum efficiency at the load power regulation.

We propose a novel wearable robotic glove or exo-glove design scalable to the variation of the hand kinematics. While most of the traditional robot hand is driven by rotating the joint directly with a rigid body, our exo-glove deforms a robotic finger's skin and, thus, the hand skeleton joints. Multiple tendons woven on the exo-glove's surface can make multi-DOF finger joint motions. We allocated tendons to mimic a hand's intrinsic and extrinsic muscles. Thus, a robotic hand actuated with the exo-glove can perform natural finger motions, including abduction/adduction and flexion/extension of finger joints. Moreover, additional tendons for the thumb enable power grips and the robotic hand's human-like motion. The proposed design approach places all the actuators on the surface without directly actuating any of the hand skeleton's joint. Therefore, a random hand skeleton can work as a robotic hand by putting the wearable robotic glove on it. Thus, the proposed model provides a high degree of freedom on choosing hand skeletons. We expect the aforementioned biomimetic features of our proposed method will benefit not only traditional robotic hands design but also the design of prosthetic hands and robot power-assisted hand glove.

We report the impact of boron acceptors on the thermally activated delayed fluorescence (TADF) properties of ortho-donor-appended triarylboron compounds. Different boryl acceptor moieties, such as 9-boraanthryl (1), 10H-phenoxaboryl (2), and dimesitylboryl (BMes2, 3) groups have been introduced into an ortho donor (D)–acceptor (A) backbone structure containing a 9,9-diphenylacridine (DPAC) donor. X-ray crystal diffraction and NMR spectroscopy evidence the presence of steric congestion around the boron atom along with a highly twisted D–A structure. A short contact of 2.906 Å between the N and B atoms, which is indicative of an N → B nonbonding electronic interaction, is observed in the crystal structure of 2. All compounds are highly emissive (PLQYs = 90–99%) and display strong TADF properties in both solution and solid state. The fluorescence bands of cyclic boryl-containing 1 and 2 are substantially blue-shifted compared to that of BMes2-containing 3. In particular, the PL emission bandwidths of 1 and 2 are narrower than that of 3. High-efficiency TADF-OLEDs are realized using 1–3 as emitters. Among them, the devices based on the cyclic boryl emitters exhibit pure blue electroluminescence (EL) and narrower EL bands than the device with 3. Furthermore, the device fabricated with emitter 1 achieves a high external quantum efficiency of 25.8%.

The demand for realistic haptic feedback actuators has increased as mobile devices have increased in popularity. However, most current haptic actuators provide limited 1-DOF tactile sensations, such as vibrations. This paper presents a 2-DOF haptic impact actuator that can provide planar directional (e.g., x and y directional) and magnitude tactile cues to a user. We built an impact actuator that was designed to be of such a size that a user can grasp it with one hand. Multiple electromagnets of the actuator drive a permanent magnet to hit the actuator housing, creating an impact. For the control of the impact direction, we assumed the direction of a magnetic field vector at the centre of the actuator would follow that of a reference vector formed by voltage heading into the electromagnet array. The results of magnetic field measurements support our assumption by showing that the trend of the magnetic field vector coincided with that of the reference voltage vector. Furthermore, the measurement of the impact acceleration showed the trend that the impact direction follows the reference voltage vector.

The acquisition of physiological data are essential to efficiently predict and treat cardiac patients before a heart attack occurs and effectively expedite motor recovery after a stroke. This goal can be achieved by using wearable wireless sensor network platforms for real-time healthcare monitoring. In this paper, we present a wireless physiological signal acquisition device and a smartphone-based software platform for real-time data processing and monitor and cloud server access for everyday ECG/EMG signal monitoring. The device is implemented in a compact size (diameter: 30 mm, thickness: 4.5 mm) where the biopotential is measured and wirelessly transmitted to a smartphone or a laptop for real-time monitoring, data recording and analysis. Adaptive digital filtering is applied to eliminate any interference noise that can occur during a regular at-home environment, while minimizing the data process time. The accuracy of ECG and EMG signal coverage is assessed using Bland–Altman analysis by comparing with a reference physiological signal acquisition instrument (RHS2116 Stim/Recording System, Intan). Signal coverage of R-R peak intervals showed almost identical outcome between this proposed work and the RHS2116, showing a mean difference in heart rate of 0.15 ± 4.65 bpm and a Wilcoxon’s p value of 0.133. A 24 h continuous recording session of ECG and EMG is conducted to demonstrate the robustness and stability of the device based on extended time wearability on a daily routine.

This paper proposes a wireless power transfer (WPT) system by placing repeater coils to transfer power to multiple loads for the internet of things (IoT) devices and sensors in smart grid applications. The proposed system intermediate resonators (repeaters) not only function as power relays to enhance the transfer distance but also supplies power to its load attached to them. Equal power distribution and load-independent characteristics were obtained without efficiency degradation when any one of the loads was changed during system operation. Identical high-quality factor coils were designed using Litz-wire to reduce the skin effect. The coil size was 15.5 cm × 15.5 cm and the four relays achieved total efficiency of 51.7%, delivering 2 W power and output voltage of 5 V to each load with a total power transfer distance of 62 cm.

With the growing interest in big data technology, mobile IoT devices play an essential role in data collection. Generally, IoT sensor nodes are randomly distributed to areas where data cannot be easily collected. Subsequently, when data collection is impossible (i.e., sensing holes occurrence situation) due to improper placement of sensors or energy exhaustion of sensors, the sensors should be relocated. The cluster header in the sensing hole sends requests to neighboring cluster headers for the sensors to be relocated. However, it can be possible that sensors in the specific cluster zones near the sensing hole are continuously requested to move. With this knowledge, there can be a ping-pong problem, where the cluster headers in the neighboring sensing holes repeatedly request the movement of the sensors in the counterpart sensing hole. In this paper, we first proposed the near-uniform selection and movement scheme of the sensors to be relocated. By this scheme, the energy consumption of the sensors can be equalized, and the sensing capability can be extended. Thus the network lifetime can be extended. Next, the proposed relocation protocol resolves a ping-pong problem using queues with request scheduling. Another crucial contribution of this paper is that performance was analyzed using the fully-customed OMNeT++ simulator to reflect actual environmental conditions, not under over-simplified artificial network conditions. The proposed relocation protocol demonstrates a uniform and energy-efficient movement with ping-pong free capability.

Recent advances in big data technology collecting and analyzing large amounts of valuable data have attracted a lot of attention. When the information in non-reachable areas is required, IoT wireless sensor network technologies have to be applied. Sensors fundamentally have energy limitations, and it is almost impossible to replace energy-depleted sensors that have been deployed in an inaccessible region. Therefore, moving healthy sensors into the sensing hole will recover the faulty sensor area. In rough surfaces, hopping sensors would be more appropriate than wheel-driven mobile sensors. Sensor relocation algorithms to recover sensing holes have been researched variously in the past. However, the majority of studies to date have been inadequate in reality, since they are nothing but theoretical studies which assume that all the topology in the network is known and then computes the shortest path based on the nonrealistic backing up knowledge—The topology information. In this paper, we first propose a distributed hopping sensor relocation protocol. The possibility of movement of the hopping sensor is also considered to recover sensing holes and is not limited to applying the shortest path strategy. Finally, a performance analysis using OMNeT++ has demonstrated the solidification of the excellence of the proposed protocol.

Mobile sensor nodes such as hopping sensors are of critical importance in data collection. However, the occurrence of sensing holes is unavoidable due to the energy limitation of the nodes. Thus, it is evident that the relocation of mobile sensors is the most desirable method to recover the sensing holes. The previous research conducted by the authors so far demonstrated the most realistic hopping sensor relocation scheme, which is suitable for the distributed environment. In previous studies, the cluster header plays an essential role in detecting the sensing hole and requesting the neighboring cluster to recover the sensing hole that occurred in the sensor node. However, the limitations of the cluster header in the previously proposed relocation protocol are not fully considered. Because the cluster header jumps more frequently than non-header nodes, its energy consumption is relatively high compared to other nodes. Therefore, it is most likely to lead to header node failure and can lead to data loss on the network. In this paper, the jumping ability and energy consumption of the cluster header are seriously considered. Additional ability to replace cluster headers in case of failure is also implemented. Simulation results show that the data collection time can be further increased, which demonstrates the validity of the proposed algorithms. [ABSTRACT FROM AUTHOR]

The finite element method is a key player in computational electromagnetics for designing RF (Radio Frequency) components such as waveguides. The frequency-domain analysis is fundamental to identify the characteristics of the components. For the conventional frequency-domain electromagnetic analysis using FEM (Finite Element Method), the system matrix is complex-numbered as well as indefinite. The iterative solvers can be faster than the direct solver when the solver convergence is guaranteed and done in a few steps. However, such complex-numbered and indefinite systems are hard to exploit the merit of the iterative solver. It is also hard to benefit from matrix factorization techniques due to varying system matrix parts according to frequency. Overall, it is hard to adopt conventional iterative solvers even though the system matrix is sparse. A new parallel iterative FEM solver for frequency domain analysis is implemented for inhomogeneous waveguide structures in this paper. In this implementation, the previous solution of the iterative solver of Matlab (Matrix Laboratory) employing the preconditioner is used for the initial guess for the next step's solution process. The overlapped parallel stage using Matlab's Parallel Computing Toolbox is also proposed to alleviate the cold starting, which ruins the convergence of early steps in each parallel stage. Numerical experiments based on waveguide structures have demonstrated the accuracy and efficiency of the proposed scheme. [ABSTRACT FROM AUTHOR]

The occurrence of 'sensing holes' not only hinders seamless data collection but also leads to misinterpretation of information in certain areas under extensive data analysis. In order to overcome this, various sensor relocation strategies have been proposed, but the existing relocation strategies revealed problems such as the ping-pong, shaded area, network disconnection, etc. This paper conducted research on relocation protocols in a distributed environment that is very suitable for real-world situations and efficiently recovering the problem of sensing holes. First, a simulation was performed on the distribution of the shaded area for data collection, which is a problem with the existing representative relocation protocol. After that, a data collection capability was newly added to the relay node, which had been in charge of only communication between cluster zones so far, and with this additional functionality, the performance of the revised sensor relocation algorithm was dramatically improved to overcome the existing problems. In addition, the performance and validity of the proposed algorithm were verified through various simulations. [ABSTRACT FROM AUTHOR]

Artificial intelligence has emerged as the core of the 4th industrial revolution, and large amounts of data processing, such as big data technology and rapid data analysis, are inevitable. The most fundamental and universal data interpretation technique is an analysis of information through regression, which is also the basis of machine learning. Ridge regression is a technique of regression that decreases sensitivity to unique or outlier information. The time-consuming calculation portion of the matrix computation, however, basically includes the introduction of an inverse matrix. As the size of the matrix expands, the matrix solution method becomes a major challenge. In this paper, a new algorithm is introduced to enhance the speed of ridge regression estimator calculation through series expansion and computation recycle without adopting an inverse matrix in the calculation process or other factorization methods. In addition, the performances of the proposed algorithm and the existing algorithm were compared according to the matrix size. Overall, excellent speed-up of the proposed algorithm with good accuracy was demonstrated. [ABSTRACT FROM AUTHOR]

Small-sized IoT wireless sensing devices can be deployed with small aircraft such as drones, and the deployment of mobile IoT devices can be relocated to suit data collection with efficient relocation algorithms. However, the terrain may not be able to predict its shape. Mobile IoT devices suitable for these terrains are hopping devices that can move with jumps. So far, most hopping sensor relocation studies have made the unrealistic assumption that all hopping devices know the overall state of the entire network and each device's current state. Recent work has proposed the most realistic distributed network environment-based relocation algorithms that do not require sharing all information simultaneously. However, since the shortest path-based algorithm performs communication and movement requests with terminals, it is not suitable for an area where the distribution of obstacles is uneven. The proposed scheme applies a simple Monte Carlo method based on relay nodes selection random variables that reflect the obstacle distribution's characteristics to choose the best relay node as reinforcement learning, not specific relay nodes. Using the relay node selection random variable could significantly reduce the generation of additional messages that occur to select the shortest path. This paper's additional contribution is that the world's first distributed environment-based relocation protocol is proposed reflecting real-world physical devices' characteristics through the OMNeT++ simulator. We also reconstruct the three days-long disaster environment, and performance evaluation has been performed by applying the proposed protocol to the simulated real-world environment. [ABSTRACT FROM AUTHOR]

With the recent development of big data technology that collects and analyzes various data, the technology that continuously collects and analyzes the observed data is also drawing attention. Moreover, its importance is growing in data collection in areas where people cannot access. In general, it is not easy to properly deploy IoT wireless devices for data collection in these areas, and it is also inappropriate to use general wheelbased mobile devices for relocation. Recently, researches have been actively carried out on hopping moving models in place of wheel-based movement for the inaccessible regions. The majority of studies, however, so far have unrealistic assumptions that all IoT devices know the overall state of the network and the current state of each device. Moreover, various physical terrain environments, such as coarse gravel and sand, can change from time to time, and it is impossible for all devices to recognize these changes in real-time. In this paper, with the migration success rate of IoT hopping devices being relocated, the method of estimating the varying environment is proposed. This method can actively reflect the changing environment in real-time and is a realistic distributed environment-based relocation protocol on behalf of non-realistic, theory-based relocation protocols. Also, one of the significant contributions of this paper is to evaluate its performance using the OMNeT++ simulation tool for the first time in the world to reflect actual physical environmental conditions. Compared to previous studies, the proposed protocol was able to actively reflect the state of the surrounding environment, which resulted in improved migration success rates and higher energy efficiency. [ABSTRACT FROM AUTHOR]

In Wireless Sensor Networks (WSNs) for Internet of Things (IoT) environment, fault tolerance is a most fundamental issue due to strict energy constraint of sensor node. In this paper, a robust energy saving data dissemination protocol for IoT-WSNs is proposed. Minimized energy consumption and dissemination delay time based on signal strength play an important role in our scheme. The representative dissemination protocol SPIN (Sensor Protocols for Information via Negotiation) overcomes overlapped data problem of the classical Flooding scheme. However, SPIN never considers distance between nodes, thus the issue of dissemination energy consumption is becoming more important problem. In order to minimize the energy consumption, the shortest path between sensors should be considered to disseminate the data through the entire IoT-WSNs. SPMS (Shortest Path Mined SPIN) scheme creates routing tables using Bellman Ford method and forwards data through a multi-hop manner to optimize power consumption and delay time. Due to these properties, it is very hard to avoid heavy traffic when routing information is updated. Additionally, a node failure of SPMS would be caused by frequently using some sensors on the shortest path, thus network lifetime might be shortened quickly. In contrast, our scheme is resilient to these failures because it employs energy aware concept. The dissemination delay time of the proposed protocol without a routing table is similar to that of shortest path-based SPMS. In addition, our protocol does not require routing table, which needs a lot of control packets, thus it prevents excessive control message generation. Finally, the proposed scheme outperforms previous schemes in terms of data transmission success ratio, therefore our protocol could be appropriate for IoT-WSNs environment. [ABSTRACT FROM AUTHOR]

The article focuses on developing efficient deep-blue organic light-emitting diodes (OLEDs) by designing multiresonance-induced thermally activated delayed fluorescence (TADF) molecules. It mentions the researchers propose a molecular modification approach to reduce intermolecular interactions and suppress excimer formation, resulting in deep-blue OLEDs with high external quantum efficiency and narrow emission spectrum.