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Background: The distribution of bacteria isolated from bloodstream infections and cumulative antimicrobial susceptibility data are the basis for empirical decisions regarding antibiotics as an initial treatment. Therefore, it is important to consistently collect blood culture results of individual patients and analyze them correctly. Methods: The blood culture results of patients at Gachon University Gil Medical Center from 2016 to 2020 were analyzed retrospectively to determine the bacterial distributions and antibiotic resistance patterns. Duplicates were eliminated by including only the first isolate of each species per patient. Results: Escherichia coli (27.1%) was the most commonly isolated bacterium from blood cultures, followed by Klebsiella pneumoniae (10.1%) and Staphylococcus aureus (8.6%). The methicillin resistance rate of S. aureus was 49.2%, and the vancomycin resistance rate of Enterococcus faecium was 39.5%; with no significant changes over the study period. The cefotaxime, ciprofloxacin, and ertapenem resistance rates of E. coli were 35.0%, 46.8%, and 0.7%, respectively. Seventeen carbapenem-resistant E. coli strains were isolated, of which 11 produced carbapenemase. The cefotaxime, ciprofloxacin, and ertapenem resistance rates of K. pneumoniae were 29.5%, 31.7%, and 5.4%, respectively. Forty-eight carbapenem-resistant K. pneumoniae strains were isolated, of which 37 produced carbapenemase. The imipenem resistance rates of Acinetobacter baumannii and Pseudomonas aeruginosa were 72.3% and 23.4%, respectively. Conclusion: In the blood culture results from 2016 to 2020, the isolation frequency of E. coli, K. pneumoniae, and E. faecium showed an increasing trend, whereas that of S. aureus was stable. Over the 5 year study period, the ciprofloxacin resistance rate of E. coli and P. aeruginosa and ampicillin/sulbactam resistance rate of A. baumannii significantly increased.

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Plants are remarkable in their ability to adapt to changing environments, with receptor-like kinases (RLKs) playing a pivotal role in perceiving and transmitting environmental cues into cellular responses. Despite extensive research on RLKs from the plant kingdom, the function and activity of many kinases, i.e., their substrates or “clients”, remain uncharted. To validate a novel client prediction workflow and learn more about an important RLK, this study focuses on P2K1 (DORN1), which acts as a receptor for extracellular ATP (eATP), playing a crucial role in plant stress resistance and immunity. We designed a Kinase-Client (KiC) assay library of 225 synthetic peptides, incorporating previously identified P2K phosphorylated peptides and novel predictions from a deep-learning phosphorylation site prediction model (MUsite) and a trained hidden Markov model (HMM) based tool, HMMER. Screening the library against purified P2K1 cytosolic domain (CD), we identified 46 putative substrates, including 34 novel clients, 27 of which may be novel peptides, not previously identified experimentally. Gene Ontology (GO) analysis among phosphopeptide candidates revealed proteins associated with important biological processes in metabolism, structure development, and response to stress, as well as molecular functions of kinase activity, catalytic activity, and transferase activity. We offer selection criteria for efficient further in vivo experiments to confirm these discoveries. This approach not only expands our knowledge of P2K1’s substrates and functions but also highlights effective prediction algorithms for identifying additional potential substrates. Overall, the results support use of the KiC assay as a valuable tool in unraveling the complexities of plant phosphorylation and provide a foundation for predicting the phosphorylation landscape of plant species based on peptide library results.

The proliferation of small electronic devices has significantly increased the demand for self-powered sensors. This study introduces a triboelectric frequency sensor (TFS) that combines the frequency-responsive characteristics of triboelectric nanogenerators with a simple one-dimensional structure for sustainable vibration measurement. This sensor is specifically designed to aid in the tuning of string instruments, capable of detecting frequency responses up to 330 Hz generated by string vibrations. Structural optimization was achieved by setting a non-contact mode with a gap distance of 3 mm and utilizing perfluoroalkoxy alkane (PFA) as the contact dielectric material. The TFS exhibits dynamic response characteristics by varying the vibrating frequency and the tension of the string, facilitated by a custom-built testing setup. Frequency data captured by the sensor can be visualized on a monitor through the integration of a microcontroller unit (MCU) and dedicated coding. The practical applicability and effectiveness of this sensor in real-world scenarios are demonstrated experimentally. This innovation represents a significant step forward in the development of self-sustaining sensing technologies for precision instrument tuning.

An increase in the number of small electronics is anticipated, requiring the preparation of an adequate powering method. A triboelectric nanogenerator, capable of scavenging ambient mechanical energy, is proposed as an efficient means to reduce power consumption for self-sustainable sensors, although its electrical output needs enhancement to broaden its technological applicability. In this work, a magnetic composite comprising iron oxide and polyaniline was synthesized to augment triboelectricity through the modulation of magnetic field intensity using physical chemistry. The crystallinity of the composite, chemical bonding, and structure of the surface are analyzed. The surface potential of the composite, embedded into polydimethylsiloxane, is quantitatively evaluated by using Kelvin probe force microscopy. By amalgamating magnetic flux density and triboelectric outputs, the optimization of the triboelectric layer is achieved, yielding output values of 93.86 V, 6.9 µA, and 127.5 µW. Following a reduction in surface adhesion after the powder coating process, a wind-based triboelectric nanogenerator is fabricated. Its excellent sensitivity to wind and exceptional long-term endurance are assessed, confirming its suitability as a sensor. The practicality of employing this device in intrusion detection, leveraging a wireless door-opening sensor, is demonstrated using synthesized composite materials.

Issues of size and power consumption in IoT devices can be addressed through triboelectricity-driven energy harvesting technology, which generates electrical signals without external power sources or batteries. This technology significantly reduces the complexity of devices, enhances installation flexibility, and minimizes power consumption. By utilizing shear thickening fluid (STF), which exhibits variable viscosity upon external impact, the sensitivity of triboelectric nanogenerator (TENG)-based sensors can be adjusted. For this study, the highest electrical outputs of STF and sponge-hybrid TENG (SSH-TENG) devices under various input forces and frequencies were generated with an open-circuit voltage (VOC) of 98 V and a short-circuit current (ISC) of 4.5 µA. The maximum power density was confirmed to be 0.853 mW/m2 at a load resistance of 30 MΩ. Additionally, a lying state detection system for use in medical settings was implemented using SSH-TENG as a hybrid triboelectric motion sensor (HTMS). Each unit of a 3 × 2 HTMS array, connected to a half-wave rectifier and 1 MΩ parallel resistor, was interfaced with an MCU. Real-time detection of the patient’s condition through the HTMS array could enable the early identification of hazardous situations and alerts. The proposed HTMS continuously monitors the patient’s movements, promptly identifying areas prone to pressure ulcers, thus effectively contributing to pressure ulcer prevention.

To enhance security in the semiconductor industry’s globalized production, the Defense Advanced Research Projects Agency (DARPA) proposed an authentication protocol under the Supply Chain Hardware Integrity for Electronics Defense (SHIELD) program. This protocol integrates a secure hardware root-of-trust, known as a dielet, into integrated circuits (ICs). The SHIELD protocol, combined with the Advanced Encryption Standard (AES) in counter mode, named CTR-SHIELD, targets try-and-check attacks. However, CTR-SHIELD is vulnerable to desynchronization attacks on its counter blocks. To counteract this, we introduce the DTR-SHIELD protocol, where DTR stands for double counters. DTR-SHIELD addresses the desynchronization issue by altering the counter incrementation process, which previously solely relied on truncated serial IDs. Our protocol adds a new AES encryption step and requires the dielet to transmit an additional 100 bits, ensuring more robust security through active server involvement and message verification.

Extracellular ATP (eATP) in plants plays a crucial role as a ligand for purinoreceptors, mediating purinergic signaling and regulating diverse biological functions, including responses to abiotic and biotic stresses. DORN1/P2K1 (LecRK I.9) was the first identified plant purinoreceptor. P2K2 (LecRK I.5) was subsequently identified as an additional plant purinoreceptor and shown to directly interact with P2K1. Recently, we reported that P2K1 interacts with Integrin-linked kinase 5 (ILK5), a Raf-like MAPKKK protein, and phosphorylates ILK5 to regulate purinergic signaling in relation to plant innate immunity. Here, we report that P2K2 also interacts with the ILK5 protein in planta. Furthermore, we demonstrate that P2K2 phosphorylates ILK5 in the presence of [γ-32P] ATP, similar to P2K1. However, unlike P2K1, P2K2 exhibits strong phosphorylation even when the Serine 192 residue of ILK5 is mutated to Alanine (ILK5S192A), suggesting the possibility of phosphorylation of other residues to fully regulate ILK5 protein function.

Additive manufacturing (AM) technology has recently seen increased utilization due to its versatility in using functional materials, offering a new pathway for next-generation conformal electronics in the smart sensor field. However, the limited availability of polymer-based ultraviolet (UV)-curable materials with enhanced piezoelectric properties necessitates the development of a tailorable process suitable for 3D printing. This paper investigates the structural, thermal, rheological, mechanical, and piezoelectric properties of a newly developed sensor resin material. The polymer resin is based on polyvinylidene fluoride (PVDF) as a matrix, mixed with constituents enabling UV curability, and boron nitride nanotubes (BNNTs) are added to form a nanocomposite resin. The results demonstrate the successful micro-scale printability of the developed polymer and nanocomposite resins using a liquid crystal display (LCD)-based 3D printer. Additionally, incorporating BNNTs into the polymer matrix enhanced the piezoelectric properties, with an increase in the voltage response by up to 50.13%. This work provides new insights for the development of 3D printable flexible sensor devices and energy harvesting systems.

Background: Rapid antimicrobial susceptibility testing (RAST) is important for the appropriate treatment of bloodstream infections. The QMAC-dRAST system (QuantaMatrix Inc., Korea) can directly perform RAST using positive blood culture samples with microscopic imaging. This study aimed to evaluate the performance of the QMAC-dRAST system for AmpC-β-lactamase-producing Enterobacterales. Methods: Eighty isolates (20 Morganella morganii, 20 Serratia marcescens, 10 Klebsiella aerogenes, 10 Enterobacter cloacae, and 20 Citrobacter freundii) and 14 antimicrobial agents were included in the antimicrobial susceptibility testing (AST). The performance of the QMAC-dRAST system was evaluated by simulating the clinical blood culturing process. We conducted a comparative evaluation of the QMAC-dRAST and Vitek 2 systems (bioM.rieux Inc., France). Broth microdilution tests were performed as the reference method to resolve any discrepancies in the AST results between the two systems. Results: For 20 M. morganii and 20 S. marcescens, the categorical agreement (CA) between the QMAC-dRAST and Vitek 2 systems increased from 55.4% to 83.8% after AST algorithm optimization. Moreover, the discrepancy rates decreased as follows: from 19.1% to 5.4% very major errors (VME), from 38.3% to 4.3% major errors (ME), and from 14.6% to 12.1% minor errors (mE) for the QMAC-dRAST system compared to the Vitek 2 system. For all 80 tested isolates, the QMAC-dRAST system showed 93.0% CA, 1.7% VME, 2.3% ME, and 4.9% mE. Conclusion: The QMAC-dRAST system was comparable to the Vitek 2 system after AST algorithm optimization for AmpC β-lactamase-producers, which are major pathogens and require time to express the enzyme. However, further modifications of the AST algorithm are still warranted.

We synthesized the hierarchical ZnO/SnO2@NiCo2O4 core–shell nanorod sheet arrays (NRSAs) grown on a flexible conductive carbon cloth (CC) substrate by a hydrothermal method. The amalgamation and formation mechanism were proposed. The as obtained ZnO/SnO2@NiCo2O4 core–shell heterostructures is investigated using X-ray diffraction, X-ray photoelectron spectroscopy, high resolution transmission electron microscopy, field emission scanning electron microscopy, and nitrogen adsorption and desorption isotherm analysis. The SnO2 layer which is conducting between ZnO and NiCo2O4 may effectively boost the electrical conductivity of the electrodes and also defend the ZnO from corrosion in the alkaline solution. Benefitting from the core–shell heterostructure formation, the hybrid ZnO/SnO2@NiCo2O4//CC electrode delivered a high specific capacity of 244.5 mA h/g, enhanced cycling stability with a 94.5% retention in specific capacitance even after 10,000 continuous charge–discharge cycles and good rate capability. To utilize the high specific capacity and ultra-long cycling stability, the PVA-KOH gel electrolyte based solid-state hybrid supercapacitor device was assembled with AC//CC as a negative electrode and ZnO/SnO2@NiCo2O4//CC as a positive electrode. The fabricated HSC device delivered a specific capacitance of 117.5 F/g with high energy density (41.7 Wh/kg) and power density (6400 W/kg) along with the outstanding capacitance retention of 94.6% even after 10,000 continuous charging and discharging cycles. With exceptional electrochemical performance, a facile and cost-effective preparation, such ZnO/SnO2@NiCo2O4//CC core–shell heterostructured electrode show a great potential for high-performance electrochemical supercapacitor applications in future.

ABSTRACT We newly detected two (sinking and floating) phenotypes of Candida parapsilosis among bloodstream infection (BSI) isolates from Korean hospitals and assessed their microbiological and clinical characteristics. During the performance of a Clinical and Laboratory Standards Institute (CLSI) broth microdilution antifungal susceptibility testing, the sinking phenotype had a characteristic smaller button-like appearance because all yeast cells sank to the bottoms of the CLSI U-shaped round-bottom wells, whereas the floating phenotype comprised dispersed cells. Phenotypic analysis, antifungal susceptibility testing, ERG11 sequencing, microsatellite genotyping, and clinical analysis were performed on C. parapsilosis isolates from 197 patients with BSI at a university hospital during 2006 to 2018. The sinking phenotype was detected in 86.7% (65/75) of the fluconazole-nonsusceptible (FNS) isolates, 92.9% (65/70) of the isolates harboring the Y132F ERG11 gene substitution, and 49.7% (98/197) of all isolates. Clonality was more frequently observed for the Y132F-sinking isolates (84.6% [55/65]) than for all other isolates (26.5% [35/132]; P

The ubiquitin/26S proteasome system is a crucial regulatory mechanism that governs various cellular processes in plants, including signal transduction, transcriptional regulation, and responses to biotic and abiotic stressors. Our study shows that the RING-H2-type E3 ubiquitin ligase, Arabidopsis Tóxicos en Levadura 2 (ATL2), is involved in response to fungal pathogen infection. Under normal growth conditions, the expression of the ATL2 gene is low, but it is rapidly and significantly induced by exogenous chitin. Additionally, ATL2 protein stability is markedly increased via chitin treatment, and its degradation is prolonged when 26S proteasomal function is inhibited. We found that an atl2 null mutant exhibited higher susceptibility to Alternaria brassicicola, while plants overexpressing ATL2 displayed increased resistance. We also observed that the hyphae of A. brassicicola were strongly stained with trypan blue staining, and the expression of A. brassicicola Cutinase A (AbCutA) was dramatically increased in atl2. In contrast, the hyphae were weakly stained, and AbCutA expression was significantly reduced in ATL2-overexpressing plants. Using bioinformatics, live-cell confocal imaging, and cell fractionation analysis, we revealed that ATL2 is localized to the plasma membrane. Further, it is demonstrated that the ATL2 protein possesses E3 ubiquitin ligase activity and found that cysteine 138 residue is critical for its function. Moreover, ATL2 is necessary to successfully defend against the A. brassicicola fungal pathogen. Altogether, our data suggest that ATL2 is a plasma membrane-integrated protein with RING-H2-type E3 ubiquitin ligase activity and is essential for the defense response against fungal pathogens in Arabidopsis.

Recent developments in micro-scale additive manufacturing (AM) have opened new possibilities in state-of-the-art areas, including microelectromechanical systems (MEMS) with intrinsically soft and compliant components. While fabrication with soft materials further complicates micro-scale AM, a soft photocurable polydimethylsiloxane (PDMS) resin, IP-PDMS, has recently entered the market of two-photon polymerization (2PP) AM. To facilitate the development of microdevices with soft components through the application of 2PP technique and IP-PDMS material, this research paper presents a comprehensive material characterization of IP-PDMS. The significance of this study lies in the scarcity of existing research on this material and the thorough investigation of its properties, many of which are reported here for the first time. Particularly, for uncured IP-PDMS resin, this work evaluates a surface tension of 26.7 ± 4.2 mN/m, a contact angle with glass of 11.5 ± 0.6°, spin-coating behavior, a transmittance of more than 90% above 440 nm wavelength, and FTIR with all the properties reported for the first time. For cured IP-PDMS, novel characterizations include a small mechanical creep, a velocity-dependent friction coefficient with glass, a typical dielectric permittivity value of 2.63 ± 0.02, a high dielectric/breakdown strength for 3D-printed elastomers of up to 73.3 ± 13.3 V/µm and typical values for a spin coated elastomer of 85.7 ± 12.4 V/µm, while the measured contact angle with water of 103.7 ± 0.5°, Young’s modulus of 5.96 ± 0.2 MPa, and viscoelastic DMA mechanical characterization are compared with the previously reported values. Friction, permittivity, contact angle with water, and some of the breakdown strength measurements were performed with spin-coated cured IP-PDMS samples. Based on the performed characterization, IP-PDMS shows itself to be a promising material for micro-scale soft MEMS, including microfluidics, storage devices, and micro-scale smart material technologies.

The flexible energy storage device of high demand in wearable and portable electronics. Flexible supercapacitors have benefits over flexible batteries, and their development relies on the use of flexible components. Gel polymer electrolytes have the merits of liquid and solid electrolytes and are used in flexible devices. In this study, a gel derived from chia seed was used as a flexible electrolyte material, and its rheological, thermal, and electrochemical properties were investigated. High thermal stability and shear thinning behavior were observed via the electrolyte state of the chia mucilage gel. Compared to the conventional salt electrolyte, the chia mucilage gel electrolyte-based supercapacitor exhibited a more rectangular cyclic voltammetry (CV) curve, longer discharging time in galvanostatic charge–discharge (GCD) analysis, and low charge transfer resistance in electrochemical impedance spectroscopy (EIS). The maximum specific capacitance of 7.77 F g−1 and power density of 287.7 W kg−1 were measured, and stable capacitance retention of 94% was achieved after 10,000 cycles of charge/discharge with harsh input conditions. The biodegradability was also confirmed by the degraded mucilage film in soil after 30 days. The plant-driven chia mucilage gel electrolyte can facilitate the realization of flexible supercapacitors for the energy storage devices of the future.

As an urgent international challenge, the sudden change in climate due to global warming needs to be addressed in the near future. This can be achieved through a reduction in fossil fuel utilization and through carbon sequestration, which reduces the concentration of CO2 in the atmosphere. In this study, a self-sustainable impact sensor is proposed through implementing a triboelectric nanogenerator with a CaCO3 contact layer fabricated via a CO2 absorption method. The triboelectric polarity of CaCO3 with the location between the polyimide and the paper and the effects of varying the crystal structure are investigated first. The impact sensing characteristics are then confirmed at various input frequencies and under applied forces. Further, the high mechanical strength and strong adherence of CaCO3 on the surface of the device are demonstrated through enhanced durability compared to the unmodified device. For the intended application, the as-fabricated sensor is used to detect the turning state of the paper Ddakji in a slap match game using a supervised learning algorithm based on a support vector machine presenting a high classification accuracy of 95.8%. The robust CaCO3-based triboelectric device can provide an eco-friendly advantage due to its self-powered characteristics for impact sensing and carbon sequestration.

Products of the mevalonate pathway support plant development. Here the authors show that the extracellular ATP receptor P2K1 phosphorylates mevalonate kinase and this affects the mevalonate pathway.

Dielectric elastomer actuator (DEA) is a smart material that holds promise for soft robotics due to the material’s intrinsic softness, high energy density, fast response, and reversible electromechanical characteristics. Like for most soft robotics materials, additive manufacturing (AM) can significantly benefit DEAs and is mainly applied to the unimorph DEA (UDEA) configuration. While major aspects of UDEA modeling are known, 3D printed UDEAs are subject to specific material and geometrical limitations due to the AM process and require a more thorough analysis of their design and performance. Furthermore, a figure of merit (FOM) is an analytical tool that is frequently used for planar DEA design optimization and material selection but is not yet derived for UDEA. Thus, the objective of the paper is modeling of 3D printed UDEAs, analyzing the effects of their design features on the actuation performance, and deriving FOMs for UDEAs. As a result, the derived analytical model demonstrates dependence of actuation performance on various design parameters typical for 3D printed DEAs, provides a new optimum thickness to Young’s modulus ratio of UDEA layers when designing a 3D printed DEA with fixed dielectric elastomer layer thickness, and serves as a base for UDEAs’ FOMs. The FOMs have various degrees of complexity depending on considered UDEA design features. The model was numerically verified and experimentally validated through the actuation of a 3D printed UDEA. The fabricated and tested UDEA design was optimized geometrically by controlling the thickness of each layer and from the material perspective by mixing commercially available silicones in non-standard ratios for the passive and dielectric layers. Finally, the prepared non-standard mix ratios of the silicones were characterized for their viscosity dynamics during curing at various conditions to investigate the silicones’ manufacturability through AM.

Jinhae Bay in South Korea is a common typhoon shelter, but there are no established criteria for the area or vessel capacity. The aim of this study was to determine the optimal capacity and arrangement of typhoon shelters for vessels in the sea area surrounding Jinhae Bay. The study identified several areas that could serve as typhoon shelters and conducted a survey with experienced VTS operators and ship operators to identify the best typhoon avoidance areas. The study found that the Japanese and Spanish design criteria for anchoring in strong winds were useful in computing the optimal capacity of typhoon shelters. A nesting algorithm based on the genetic algorithm and the No-Fit-Polygon theory was used to optimize the arrangement of shelters. The study found that the Jinhae Bay typhoon shelter can be effectively managed by arranging shelter-seeking vessels based on the nesting algorithm. The study contributes to supporting quantitative methodology-based decision-making and has practical significance for managing typhoon shelters in the Jinhae Bay area. Further research is needed to evaluate the proposed arrangement plan for typhoon shelters and confirm the validity of the results through simulation and practical implementation. Additionally, the time complexity for vessels to approach the anchorage should be considered in future studies.

The demand for deep learning frameworks capable of running in edge computing environments is rapidly increasing due to the exponential growth of data volume and the need for real-time processing. However, edge computing environments often have limited resources, necessitating the distribution of deep learning models. Distributing deep learning models can be challenging as it requires specifying the resource type for each process and ensuring that the models are lightweight without performance degradation. To address this issue, we propose the Microservice Deep-learning Edge Detection (MDED) framework, designed for easy deployment and distributed processing in edge computing environments. The MDED framework leverages Docker-based containers and Kubernetes orchestration to obtain a pedestrian-detection deep learning model with a speed of up to 19 FPS, satisfying the semi-real-time condition. The framework employs an ensemble of high-level feature-specific networks (HFN) and low-level feature-specific networks (LFN) trained on the MOT17Det dataset, achieving an accuracy improvement of up to AP50 and AP0.18 on MOT20Det data.

Inflammation is an indispensable part of the human body’s self-defense mechanism against external stimuli. The interactions between Toll-like receptors and microbial components trigger the innate immune system via NF-κB signaling, which regulates the overall cell signaling including inflammatory responses and immune modulations. The anti-inflammatory effects of Hyptis obtusiflora C. Presl ex Benth, which has been used as a home remedy for gastrointestinal disorders and skin disease in rural areas of Latin America, have not yet been studied. Here, we investigate the medicinal properties of Hyptis obtusiflora C. Presl ex Benth methanol extract (Ho-ME) for inflammatory response suppression. Nitric oxide secretion in RAW264.7 cells triggered by TLR2, 3, or 4 agonists was reduced by Ho-ME. Reduction of inducible nitric oxide synthase (iNOS), cyclooxygenase (COX)-2, and interleukin (IL)-1b mRNA expression was observed. Decreased transcriptional activity in TRIF- and MyD88-overexpressing HEK293T cells was detected with a luciferase assay. Additionally, serially downregulated phosphorylation of kinase in the NF-κB pathway by Ho-ME was discovered in lipopolysaccharide-treated RAW264.7 cells. Together with the overexpression of its constructs, AKT was identified as a target protein of Ho-ME, and its binding domains were reaffirmed. Moreover, Ho-ME exerted gastroprotective effects in an acute gastritis mouse model generated by the administration of HCl and EtOH. In conclusion, Ho-ME downregulates inflammation via AKT targeting in the NF-κB pathway, and the combined results support Hyptis obtusiflora as a new candidate anti-inflammatory drug.

Magnetorheological (MR) fluid is a smart material utilized for semi-active damping devices thanks to its ability to become viscoelastic solid under a magnetic field and provide variable damping. While most of these devices primarily utilize the fluid’s drastic increase in viscosity, its variable stiffness is rarely utilized. A MR fluid filled spring is a novel device with variable stiffness and damping and is the subject of the present study. First, the derived analytical model and the device’s controllable stiffness capability were experimentally validated by performing tensile tests with a fabricated hollow polymer spring filled with MRF-132DG. The analytical model was proved to describe the MR fluid static effect of increased spring stiffness accurately. Secondly, dynamic testing demonstrated the device’s controllable damping and capability to shift natural frequencies. In addition, the testing unveiled an enhanced dynamic performance of the spring due to the cumulative effect of MR fluid activation and specifically aligned uniform magnetic field. Finally, the hollow spring design was optimized through analytical and non-linear finite element buckling analysis to maximize MR fluid stiffness effect. The resulting critical parameters of the optimized design were used to estimate the effects of hollow spring material and operating conditions on the variable stiffness of the device.

Abstract Background Cancer is a highly heterogeneous disease with varying responses to anti-cancer drugs. Although several attempts have been made to predict the anti-cancer therapeutic responses, there remains a great need to develop highly accurate prediction models of response to the anti-cancer drugs for clinical applications toward a personalized medicine. Patient derived xenografts (PDXs) are preclinical cancer models in which the tissue or cells from a patient’s tumor are implanted into an immunodeficient or humanized mouse. In the present study, we develop a bioinformatics analysis pipeline to build a predictive gene expression model (GEM) for cancer patients’ drug responses based on gene expression and drug activity data from PDX models. Results Drug sensitivity biomarkers were identified by performing an association analysis between gene expression levels and post-treatment tumor volume changes in PDX models. We built a drug response prediction model (called PDXGEM) in a random-forest algorithm by using a subset of the drug sensitvity biomarkers with concordant co-expression patterns between the PDXs and pretreatment cancer patient tumors. We applied the PDXGEM to several cytotoxic chemotherapies as well as targeted therapy agents that are used to treat breast cancer, pancreatic cancer, colorectal cancer, or non-small cell lung cancer. Significantly accurate predictions of PDXGEM for pathological response or survival outcomes were observed in extensive independent validations on multiple cancer patient datasets obtained from retrospective observational studies and prospective clinical trials. Conclusion Our results demonstrated the strong potential of using molecular profiles and drug activity data of PDX tumors in developing a clinically translatable predictive cancer biomarkers for cancer patients. The PDXGEM web application is publicly available at http://pdxgem.moffitt.org .

16S rRNA gene-targeted next-generation sequencing (NGS) can detect microorganisms in a comprehensive reference database. To date, NGS has been successfully applied to samples such as urine, blood, and synovial fluid. However, there is no data for continuous ambulatory peritoneal dialysis (CAPD) fluid. The purpose of this study was to evaluate the clinical usefulness of microbiome analysis of CAPD fluids for the diagnosis of CAPD peritonitis.We included 21 patients with high suspicion of CAPD peritonitis. Routine CAPD fluid culture was performed using a pellet of 50 mL CAPD fluid onto the chocolate and blood agar for two days, and thioglycollate broth for one week. 16S rRNA gene-targeted NGS of pellets, stored at -70°C was performed with MiSeq (Illumina, USA). Many colonized or pathogenic bacteria were detected from CAPD fluids using NGS and the microbiomes were composed of 1 to 29 genera with a cut-off 1.0. Compared to the culture results, NGS detected the same pathogens in 6 of 18 valid results (three samples failed with low read count). Additionally, using NGS, anaerobes such as Bacteroides spp. and Prevotella spp. were detected in six patients. In two of five samples in which no bacterial growth was detected, possible pathogens were detected by NGS.To our knowledge, this is the first report about the application of 16S rRNA gene-targeted NGS for diagnosis of CAPD peritonitis. Etiology of culture-negative CAPD peritonitis can be better defined in NGS. Furthermore, it also helped the detection of anaerobic bacteria.

We extended the density-gradient (DG) model to include a second-order quantum correction (SOQC) term. The DG model has been widely used as a device simulation model capable of simulating quantum effects in efficient way. However, when only the first order quantum correction term is considered in the DG model, it is difficult to accurately describe device characteristics such as carrier density or potential fluctuation in the narrow region due to discrete charges such as dopants and interface traps. Thus, we extended the DG model to the SOQC, implemented it as a three-dimensional (3D) simulator, and compared the simulation results for sub-10-nm devices, which have a single point charge, in the DG model and the 3D Schrödinger–Poisson (SP) solver. Through this, we identified that the DG extended to SOQC well reproduces the SP simulation results in terms of both capacitance–voltage (C–V) and local fluctuation in electron density.

Recently, considerable research efforts to achieve advanced design of promising electroactive materials as well as unique structures in supercapacitor electrodes have been explored for high-performance energy storage systems. We suggest the development of novel electroactive materials with an enlarged surface area for sandpaper materials. Based on the inherent micro-structured morphologies of the sandpaper substrate, nano-structured Fe-V electroactive material can be coated on it by facile electrochemical deposition technique. A hierarchically designed electroactive surface is covered with FeV-layered double hydroxide (LDH) nano-flakes on Ni-sputtered sandpaper as a unique structural and compositional material. The successful growth of FeV-LDH is clearly revealed by surface analysis techniques. Further, electrochemical studies of the suggested electrodes are carried out to optimize the Fe-V composition as well as the grit number of the sandpaper substrate. Herein, optimized Fe0.75V0.25 LDHs coated on #15000 grit Ni-sputtered sandpaper are developed as advanced battery-type electrodes. Finally, along with the negative electrode of activated carbon and the FeV-LDH electrode, it is utilized for hybrid supercapacitor (HSC) assembly. The fabricated flexible HSC device indicates high energy and power density by showing excellent rate capability. This study is a remarkable approach to improving the electrochemical performance of energy storage devices using facile synthesis.

The preparation of metal organic frameworks (MOFs) has come to the forefront in recent years because of their outstanding physical and chemical properties. Many MOFs such as Zn, Co, Ni, Fe, and Ag, etc., have been successfully synthesized. In this work, we followed the solvothermal assisted route to synthesize Ag-MOF (abbreviated as AMOF) nanosheets and then applied them as a photocatalyst to remove different organic pollutants, namely methyl orange (MO), crystal violet (CV), and methylene blue (MB). Chemical composition, optical properties, morphology, and microstructural analysis were analyzed using XPS, UV-visible spectrophotometer, FESEM, TEM, and EDS, respectively. The structural properties of AMOF nanosheets were studied by X-ray diffraction (XRD). Nitrogen adsorption and desorption isotherm analysis were utilized to evaluate the specific surface area and pore size of the AMOF nanosheets. Further, AMOF nanosheets showed notable photocatalytic performance for various dye pollutants degradation. The results confirmed 74.5, 85.5, and 90.7% of MO, CV, and MB dye pollutants removal after 120 min of irradiation with the rate constants (k) of 0.0123, 0.0153, and 0.0158 min−1, respectively. The effect of superoxide radicals (O2−) and photogenerated holes (h+) on the organic dye pollutants removal was investigated using radical scavenger trapping studies. Moreover, the stability study also confirmed the recyclability of the photocatalyst. Therefore, the findings of this research present a realizable method to grow AMOF photocatalyst for successful degradation of various dye pollutants.

Recently, there is a need to explore the utilization of various heterostructures using the designed nanocomposites and tuning the surfaces of electrodes for improving the electrochemical performance of supercapacitors (SC). In this work, a novel approach is successfully employed through a facile two-step synthetic route with the assistance of a microwave for only 1 min. Depending on the glass transition of a polystyrene (PS) substrate and electrochemical deposition (ECD) of electroactive Ni-Co layered double hydroxides (LDHs), a hierarchically designed flake-like morphology can be readily prepared to enhance the surface-active sites, which allows a rhombohedral Ni-Co LDHs electrode to obtain superior electrochemical properties. Further, the interactions between electrode and electrolyte during the diffusion of ions are highly simplified using multiple enhanced electroactive sites and shorter pathways for electron transfer. The unique surface architecture of the PS substrate and the synergistic effect of the bimetallic components in Ni-Co LDHs enable this substrate to obtain desired electrochemical activity in charge storage systems. The optimized MWC Co0.5Ni0.5 electrode exhibited an areal capacity of 100 µAh/cm2 at a current density of 1 mA/cm2 and a remarkable capacity retention of 91.2% over 5000 continuous charging and discharging cycles due to its remarkable synergistic effect of abundant faradaic redox reaction kinetics. The HSC device is assembled with the combination of optimized MWC Co0.5Ni0.5 and activated carbon as a positive and negative electrode, respectively. Further, the electrochemical test results demonstrated that MWC Co0.5Ni0.5 //AC HSC device showed a high areal capacitance of 531.25 mF/cm2 at a current density of 5 mA/cm2. In addition, the fabricated an aqueous HSC device showed a power density of 16 mW/cm2 at an energy density of 0.058 mWh/cm2, along with the remarkable capacity retention of 82.8% even after 10,000 continuous charging and discharging cycles. Moreover, the assembled hybrid supercapacitor (HSC) device is integrated with a triboelectric nanogenerator (TENG) for the development of energy conversion and storage systems. Not only an extensive survey of materials but also an innovative solution for recent progress can confirm the wide range of potential SC applications. Remarkably, this study is a new way of constructing self-powered energy storage systems in the field of sustainable wearable electronics and future smart sensing systems.

A novel inhibitable and firing threshold voltage tunable vertical nanowire (NW) single transistor neuron device with core–shell dual-gate (CSDG) was realized and verified by TCAD simulation. The CSDG NW neuron is enclosed by an independently accessed shell gate and core gate to serve an excitatory–inhibitory transition and a firing threshold voltage adjustment, respectively. By utilizing the shell gate, the firing of specific neuron can be inhibited for winner-takes-all learning. It was confirmed that the independently accessed core gate can be used for adjustment of the firing threshold voltage to compensate random conductance variation before the learning and to fix inference error caused by unwanted synapse conductance change after the learning. This threshold voltage tuning can also be utilized for homeostatic function during the learning process. Furthermore, a myelination function which controls the transmission rate was obtained based on the inherent asymmetry between the source and drain in vertical NW structure. Finally, using the CSDG NW neuron device, a letter recognition test was conducted by SPICE simulation for a system-level validation. This multi-functional neuron device can contribute to construct a high-density monolithic SNN hardware combining with the previously developed vertical synapse MOSFET devices.

Inflammation is a critically important barrier found in innate immunity. However, severe and sustained inflammatory conditions are regarded as causes of many different serious diseases, such as cancer, atherosclerosis, and diabetes. Although numerous studies have addressed how inflammatory responses proceed and what kinds of proteins and cells are involved, the exact mechanism and protein components regulating inflammatory reactions are not fully understood. In this paper, to determine the regulatory role of mixed lineage kinase 3 (MLK3), which functions as mitogen-activated protein kinase kinase kinase (MAP3K) in cancer cells in inflammatory response to macrophages, we employed an overexpression strategy with MLK3 in HEK293 cells and used its inhibitor URMC-099 in lipopolysaccharide (LPS)-treated RAW264.7 cells. It was found that overexpressed MLK3 increased the mRNA expression of inflammatory genes (COX-2, IL-6, and TNF-α) via the activation of AP-1, according to a luciferase assay carried out with AP-1-Luc. Overexpression of MLK3 also induced phosphorylation of MAPKK (MEK1/2, MKK3/6, and MKK4/7), MAPK (ERK, p38, and JNK), and AP-1 subunits (c-Jun, c-Fos, and FRA-1). Phosphorylation of MLK3 was also observed in RAW264.7 cells stimulated by LPS, Pam3CSK, and poly(I:C). Finally, inhibition of MLK3 by URMC-099 reduced the expression of COX-2 and CCL-12, phosphorylation of c-Jun, luciferase activity mediated by AP-1, and phosphorylation of MAPK in LPS-treated RAW264.7 cells. Taken together, our findings strongly suggest that MLK3 plays a central role in controlling AP-1-mediated inflammatory responses in macrophages and that this enzyme can serve as a target molecule for treating AP-1-mediated inflammatory diseases.

Background: Respiratory tract infections are major public health threats, and the identification of their causative microbes helps clinicians to initiate timely and appropriate antimicrobial therapy and prevent the secondary spread of infection. The main goal of this study was to compare two multiplex real-time polymerase chain reaction (PCR) assays used to detect respiratory viral pathogens in nasopharyngeal swab specimens.Methods: Between September and October 2017, a total of 84 nasopharyngeal specimens were obtained consecutively from patients in a tertiary hospital using a flocked swab with 3 mL universal transport medium (COPAN Diagnostics, USA). A total of 64 positive and 20 negative sample results from the LG AdvanSure RV real-time RT-PCR kit (LG Life Sciences, Korea) were further retested using a new AdvanSure RV-plus a real-time RT-PCR kit to compare their performance.Results: Statistical analysis of positive and negative agreement between the two different kits was conducted between the newly introduced AdvanSure RV-plus real-time RT-PCR kit and the AdvanSure RV real-time RT-PCR. The overall agreement was 96.4%, with positive agreement of 98.4% and negative agreement of 90%. The evaluated sensitivity and specificity of AdvanSure RV-plus real-time RT-PCR were 96.9% and 94.7%, respectively, with a kappa value of 0.9 (P

A two-dimensional visibility estimation model was developed, based on random forest (RF), a machine learning-based technique. A geostatistical method was introduced into the visibility estimation model for the first time to interpolate point measurement data to gridded data spatially with a pixel size of 10 km. The RF-based model was trained using gridded visibility data, as well as meteorological and air pollution input variable data, for each location in South Korea, which were characterized by complex geographical features and high air pollution levels. Generally, relative humidity was the most important input variable for the visibility estimation (average mean decrease accuracy: 35%). However, PM2.5 tended to be the most crucial variable in polluted regions. The spatial interpolation was found to result in an additional visibility estimation error of 500 m in locations where no adjacent visibility observations within 0.2° were available. The performance of the proposed model was preliminarily assessed. Generally, the best detection performance was achieved in good visibility conditions (visibility range: 10 to 20 km). This study is the first to demonstrate a visibility estimation model based on a geostatistical method and machine learning, which can provide visibility information in locations for which no observations exist.

Daily sleep monitoring is limited by the needs for specialized equipment and experts. This study combines a mask-shaped triboelectric nanogenerator (M-TENG) and machine learning for facile daily sleep monitoring without the specialized equipment or experts. The fabricated M-TENG demonstrates its excellent ability to detect respiration, even distinguishing oral and nasal breath. To increase the pressure sensitivity of the M-TENG, the reactive ion etching is conducted with different tilted angles. By investigating each surface morphology of the polytetrafluoroethylene films according to the reactive ion etching with different tilted angles, the tilted angle is optimized with the angle of 60° and the pressure sensitivity is increased by 5.8 times. The M-TENG can also detect changes in the angle of head and snoring. Various sleep stages can be classified by their distinctive electrical outputs, with the aid of a machine learning approach. As a result, a high averaged-classification accuracy of 87.17% is achieved for each sleep stage. Experimental results demonstrate that the proposed combination can be utilized to monitor the sleep stage in order to provide an aid for self-awareness of sleep disorders. Considering these results, the M-TENG and machine learning approach is expected to be utilized as a smart sleep monitoring system in near future.

In an era of rapidly evolving artificial intelligence and 5G communications technologies, massive data storage and processing are required for the real-time operation of digital processors in conventional wearable devices. However, classical von-Neumann architecture computers are limited by bottleneck-related issues. As a solution, resistive random-access memory (RRAM) devices are being considered as next generation in-memory computing devices. Among various materials, a polydopamine (PDA) is an attractive candidate for the fabrication of wearable and flexible RRAM devices. Herein, an aluminum/PDA/aluminum structure is proposed to investigate the influence of the PDA layer on resistive switching. The resistance-switching characteristics of an Al/PDA/Al structure are investigated by changing the PDA’s coating time and an on/off ratio of 2.48 × 103 is recorded. X-ray photoelectron spectroscopy reveals the presence of an Al2O3 layer in Al/PDA/Al structure, and the contents of oxygen vacancies are changed according to PDA coating time. Conductive filaments in the PDA/Al structure are confirmed by conductive atomic-force microscopy. As an application, a flexible Al/PDA/Al structure is fabricated using polyethylene terephthalate substrate and its operation is successfully confirmed. These results describe the resistive-switching characteristics, including oxygen vacancies, of Al/PDA/Al structures and provide new ways of understanding the resistive-switching mechanism of PDA-based RRAM devices.

Supercapacitor (SC) electrodes fabricated with the combination of carbon nanotubes (CNTs) and metal oxides are showing remarkable advancements in the electrochemical properties. Herein, NiO decorated CNT/ZnO core-shell hybrid nanocomposites (CNT/ZnO/NiO HNCs) are facilely synthesized by a two-step solution-based technique for the utilization in hybrid supercapacitors. Benefitting from the synergistic advantages of three materials, the CNT/ZnO/NiO HNCs based electrode has evinced superior areal capacity of ~67 µAh cm−2 at a current density of 3 mA cm−2 with an exceptional cycling stability of 112% even after 3000 cycles of continuous operation. Highly conductive CNTs and electrochemically active ZnO contribute to the performance enhancement. Moreover, the decoration of NiO on the surface of CNT/ZnO core-shell increases the electro active sites and stimulates the faster redox reactions which play a vital role in augmenting the electrochemical properties. Making the use of high areal capacity and ultra-long stability, a hybrid supercapacitor (HSC) was assembled with CNT/ZnO/NiO HNCs coated nickel foam (CNT/ZnO/NiO HNCs/NF) as positive electrode and CNTs coated NF as negative electrode. The fabricated HSC delivered an areal capacitance of 287 mF cm−2 with high areal energy density (67 µWh cm−2) and power density (16.25 mW cm−2). The combination of battery type CNT/ZnO/NiO HNCs/NF and EDLC type CNT/NF helped in holding the capacity for a long period of time. Thus, the systematic assembly of CNTs and ZnO along with the NiO decoration enlarges the application window with its high rate electrochemical properties.

Maritime Autonomous Surface Ships (MASS), an emerging area of digital advancement in shipping and shipbuilding industries, presents a different legal paradigm from that of existing ships. Existing maritime-related industries, including shipping, shipbuilding, and logistics, based on large hardware called ships, are rapidly changing into highly autonomous software-centered structures. This study is focused on analyzing the legal issues in preparation for MASS’ commercial operations in the future by applying comparative methods centered on the Republic of Korea and the United Kingdom. The study’s results contribute to the criteria for the manufacturing responsibility of autonomous ship-embedded software and a desirable legal policy improvement plan. Various legal issues and macro legal policy directions related to software product liability were identified. The study also presents concrete implementation strategies to achieve an ideological harmony and a balance between equitable damage relief and the advancement of related technologies to ensure maritime safety in the maritime industry. Based on the issues identified and their legal policy alternatives, it is hoped that the institutional ideal of product liability, which promotes technological advancement and protects consumer rights, is realized in the software domain as well.

With aging, disability of the body can easily occur because the function of the body is degraded. Especially, swallowing disorder is regarded as a crucial issue because patients cannot obtain the nutrients from food by swallowing it. Hence, the rehabilitation of swallowing disorder is urgently required. However, the conventional device for swallowing rehabilitation has shown some limitations due to its external power source and internal circuit. Herein, a self-powered triboelectric nanogenerator for swallowing rehabilitation (TSR) is proposed. To increase the electrical output and pressure sensitivity of the TSR, the tilted reactive ion etching is conducted and the electrical output and pressure sensitivity are increased by 206% and 370%, respectively. The effect of the tilted reactive ion etching into the electrical output generated from the TSR is systematically analyzed. When the tongue is pressing, licking, and holding the TSR, each motion is successfully detected through the proposed TSR. Based on these results, the smart swallowing rehabilitation monitoring system (SSRMS) is implemented as the application and the SSRMS could successfully detect the pressing by the tongue. Considering these results, the SSRMS can be expected to be utilized as a promising smart swallowing rehabilitation monitoring system in near future.

Recently, tremendous research on small energy supply devices is gaining popularity with the immerging Internet of Things (IoT) technologies. Especially, energy conversion and storage devices can provide opportunities for small electronics. In this research, a micro-nano structured design of electrodes is newly developed for high performing hybrid energy systems with the improved effective surface area. Further, it could be simply fabricated through two-steps synthesis of electrospinning and glass transition of a novel polystyrene (PS) substrate. Herein, the electro-spun nanofiber of polyacrylonitrile (PAN) and Nylon 66 (Nylon) are applied to the dielectric layer of a triboelectric generator (TENG), while the PAN and polyaniline (PANI) composites is utilized as an electroactive material of supercapacitor (SC). As a result, the self-charging power system is successfully integrated with the wrinkled PAN/PS (W-PAN/PS@PANI)-SC and W-TENG by using a rectifier. According to the fabricated hybrid energy systems, the electrical energy produced by W-TENG can be successfully stored into as-fabricated W-PAN/PS@PANI-SC and can also turn on a commercial green LED with the stored energy. Therefore, the micro-nano structured electrode designed for hybrid energy systems can contribute to improve the energy conversion and storage performance of various electronic devices.

A surface acoustic wave (SAW), device composed of polymer and ceramic fillers, exhibiting high piezoelectricity and flexibility, has a wide range of sensing applications in the aerospace field. The demand for flexible SAW sensors has been gradually increasing due to their small size, wireless capability, low fabrication cost, and fast response time. This paper discusses the structural, thermal, and electrical properties of the developed sensor, based on different micro- and nano-fillers, such as lead zirconate titanate (PZT), calcium copper titanate (CCTO), and carbon nanotubes (CNTs), along with polyvinylidene fluoride (PVDF) as a polymer matrix. The piezocomposite substrate of the SAW sensor is fabricated using a hot press, while interdigital transducers (IDTs) are deposited through 3D printing. The piezoelectric properties are also enhanced using a non-contact corona poling technique under a high electric field to align the dipoles. Results show that the developed passive strain sensor can measure mechanical strains by examining the frequency shifts of the detected wave signals.

Extracellular ATP acts as a damage-associated molecular pattern that triggers signaling responses to wounding and environmental stimuli in plants. Here Chen et al. show that ATP perception by DORN1 can trigger stomatal closure mediated via RBOHD phosphorylation and ROS production.

The ocean covers 70% of the earth’s surface and is one of the largest uncultivated resources still available for harvesting energy. The triboelectric energy harvesting technology has the potential to effectively convert the ocean’s “blue energy” into electricity. A half-cylinder structure including rollers floating on the water has already been used, in which the pendulum motion of the rollers is driven by the waveform. For the stable motion of the rollers, the printed surface of the device was treated with acetone for attaining hydrophilicity. The electrical outputs with the proposed device were enhanced by increasing the contact surface area by simply implementing the double roller structure with double side-covered electrodes. With the optimized structure, the maximum power density reached a value of 69.34 µW m−2 at a load resistance of 200 MΩ with the device’s high output durability. Finally, the fabricated device was also applied to the artificial water waves to demonstrate the possibility of using this device in the ocean. By simply modifying the electrode structure and adding a roller, this device demonstrated the ability to generate over 160% of electrical output with the same covered area of the ocean by the triboelectric nanogenerators (TENGs) and potential ocean application.

With advances in internet of things technology and fossil fuel depletion, energy harvesting has emerged rapidly as a means of supplying small electronics with electricity. As a method of enhancing the electrical output of the triboelectric nanogenerator, specialized for harvesting mechanical energy, structural modification to amplify the input force is receiving attention due to the limited input energy level. In this research, a lever structure was employed for delivering the amplified input force to a triboelectric nanogenerator. With structural optimization of a 2.5 cm : 5 cm distance ratio of the first and second parts using two lever structures, the highest electrical outputs were achieved: a VOC of 51.03 V, current density of 3.34 mA m−2, and power density of 73.5 mW m−2 at 12 MΩ in the second part. As applications of this triboelectric generator, a vertical vibration sensor and a wearable reloading trigger in a gun shooting game were demonstrated. The possibility for a wearable finger bending sensor with low-level input was checked using a minimized device. Enhanced low-detection limit with amplified input force from the structural advantage of this lever-based triboelectric nanogenerator device can expand its applicability to the mechanical trigger for wearable electronics.

Integrating nano- to micro-sized dielectric fillers to elastomer matrices to form dielectric composites is one of the commonly utilized methods to improve the performance of dielectric elastomer actuators (DEAs). Barium titanate (BaTiO3) is among the widely used ferroelectric fillers for this purpose; however, calcium copper titanate CaCu3Ti4O12 (CCTO) has the potential to outperform such conventional fillers. Despite their promising performance, CCTO-based dielectric composites for DEA application are studied to a relatively lower degree. Particularly, the composites are characterized for a comparably small particle loading range, while critical DEA properties such as breakdown strength and nonlinear elasticity are barely addressed in the literature. Thus, in this study, CCTO was paired with polydimethylsiloxane (CH3)3SiO[Si(CH3)2O]nSi(CH3)3 (PDMS), Sylgard 184, to gain a comprehensive understanding of the effects of particle loading and size on the dielectric composite properties important for DEA applications. The dielectric composites’ performance was described through the figures of merit (FOMs) that consider materials’ Young’s modulus, dielectric permittivity, and breakdown strength. The optimum amounts of the ferroelectric filler were determined through the FOMs to maximize composite DEA performance. Lastly, electromechanical testing of the pre-stretched CCTO-composite DEA validated the improved performance over the plain elastomer DEA, with deviations from prediction attributed to the studied composites’ nonlinearity.

Colitis is a frequent, clinically-significant immune-related adverse event caused by anti-programmed death-1 (PD-1). The clinical features, timing, and management of colitis with anti-PD-1-based regimens are not well-characterized. Patients with advanced melanoma that received either anti-PD-1 monotherapy (“monotherapy”) or combined with ipilimumab (“combination therapy”) were screened from 8 academic medical centers, to identify those with clinically-relevant colitis (colitis requiring systemic steroids). Of 1261 patients who received anti-PD-1-based therapy, 109 experienced colitis. The incidence was 3.2% (30/937) and 24.4% (79/324) in the monotherapy and combination therapy cohorts, respectively. Patients with colitis from combination therapy had significantly earlier symptom onset (7.2 weeks vs 25.4 weeks, p

The spatial coverage of satellite aerosol classification was improved using a random forest (RF) model trained with observational data including target (aerosol type) and input (satellite measurement) variables. The AErosol RObotic NETwork (AERONET) aerosol-type dataset was used for the target variables. Satellite input variables with many missing data or low mean-decrease accuracy were excluded from the final input variable set, and good performance in aerosol-type classification was achieved. The performance of the RF-based model was evaluated on the basis of the wavelength dependence of single-scattering albedo (SSA) and fine-mode-fraction values from AERONET. Typical SSA wavelength dependence for individual aerosol types was consistent with that obtained for aerosol types by the RF-based model. The spatial coverage of the RF-based model was also compared with that of previously developed models in a global-scale case study. The study demonstrates that the RF-based model allows satellite aerosol classification with improved spatial coverage, with a performance similar to that of previously developed models.

An aluminum double-layered electrode (DE-Al) was successfully employed as two electrodes in a symmetrical supercapacitor (double-layered electrode symmetric SC (DE-SC)) and as a positive layer of a triboelectric nanogenerator (DE-TENG) with the aim of energy conversion and storage using a selfsame structured, self-powered flexible device. A facile water-assisted oxidation (WAO) process and metal sputtering after the WAO process can allow the electrodes to greatly improve the active surface area and the conductivity, leading to the enhancement of the electrochemical performances of a supercapacitor (SC). Particularly, this double-layered structure fabrication process is extremely less time-consuming and cost-effective. The electrochemical test of the proposed DE-Al was systematically conducted by cyclic voltammetry (CV), galvanostatic charge-discharge (GCD) and electrochemical impedance spectroscopy (EIS), along with the in-depth characterizations of the surface. From these studies, the DE-Al offers exceptional electrochemical properties compared with other structures, which were utilized as the electrodes in the polyvinyl alcohol/phosphoric acid (PVA/H3PO4) gel electrolyte. The improved performance apparently evidenced from the electrochemical tests of fabricated SC resulted from the enhanced electrical conductivity and large active surface area. The specific capacitance and cycle-life stability of the DE-SC were investigated by using a GCD analysis. Additionally, the EIS curves before and after stability test (for 3500 cycles) were obtained to prove the long-term endurance of DE-SC. A vertical contact and the separation mode of the TENG were also fabricated by using the same DE-Al as a positive layer and polydimethylsiloxane (PDMS) as a negative layer. Finally, the fabricated SC and TENG were successfully combined using a bridge rectifier to convert and store the mechanical energy as electrical energy. This simple design and facile fabrication of a double-layered-electrode-based structure is promising for the development of an energy conversion and storage device.

Recently, studies on enhancing the performance of triboelectric nanogenerators (TENGs) by forming nanostructures at the contacting interface have been actively reported. In this study, a double-layered bottom electrode TENG (DE-TENG) was successfully fabricated using a metal deposition layer after the water-assisted oxidation (WAO) process. As previously reported, the WAO process for the enhancement of electrical performance increases the effective contact area with an inherent surface oxidation layer (Al2O3). As a new approach for modifying deficiencies in the WAO process, a metal deposition onto the oxidation layer was successfully developed with increased device output performance by restoring the surface conductivity. The proposed metal–dielectric–metal sandwich-structured DE-TENG generated approximately twice the electrical output generated by the WAO process alone (WAO-TENG). This dramatically improved electrical output was proven by a theoretical demonstration based on a double capacitance structure. In addition, the double capacitance structure was confirmed with the aid of a field emission scanning electron microscope. The optimal point at which the DE-TENG generates the highest electrical outputs was observed at a specific Cu layer sputtering time. The exceptional durability of the DE-TENG was proved by the 1 h endurance test under various relative humidity conditions. The potential of a self-powered force sensor using this DE-TENG is demonstrated, having a comparably high sensitivity of 0.82 V/N. Considering its structure, increased electrical energy, easy fabrication, and its durability, this novel DE-TENG is a promising candidate for the self-powered energy harvesting technology in our near future.

We investigate the effects of aerosol peak height (APH) and various parameters on the air mass factor (AMF) for SO2 retrieval. Increasing aerosol optical depth (AOD) leads to multiple scattering within the planetary boundary layer (PBL) and an increase in PBL SO2 AMF. However, under high AOD conditions, aerosol shielding effects dominate, which causes the PBL SO2 AMF to decrease with increasing AOD. The height of the SO2 layer and the APH are found to significantly influence the PBL SO2 AMF under high AOD conditions. When the SO2 and aerosol layers are of the same height, aerosol multiple scattering occurs dominantly within the PBL, which leads to an increase in the PBL SO2 AMF. When the APH is greater than the SO2 layer height, aerosol shielding effects dominate, which decreases the PBL SO2 AMF. When the SO2 and aerosol layers are of the same height under low AOD and solar zenith angle (SZA) conditions, increased surface reflectance is found to significantly increase the PBL SO2 AMF. However, high AOD dominates the surface reflectance contribution to PBL SO2 AMF. Under high SZA conditions, Rayleigh scattering contributes to a reduction in the light path length and PBL SO2 AMF. For volcanic SO2 AMF, high SZA enhances the light path length within the volcanic SO2 layer, as well as the volcanic SO2 AMF, because of the negligible photon loss by Rayleigh scattering at high altitudes. High aerosol loading and an APH that is greater than the SO2 peak height lead to aerosol shielding effects, which reduce the volcanic SO2 AMF. The SO2 AMF errors are also quantified as a function of uncertainty in the input data of AOD, APH, and surface reflectance. The SO2 AMF sensitivities and error analysis provided here can be used to develop effective error reduction strategies for satellite-based SO2 retrievals.

Wind is a great sustainable energy source for harvesting due to its abundant characteristic. Typically, large space, loud noise, and heavy equipment are essential for a general wind power plant and it is solely operated by big-scale wind. However, wind energy can be efficiently harvested by utilizing the triboelectric nanogenerator due to its abundance, ubiquity, and environmentally friendliness. Furthermore, a few previously reported wind-driven triboelectric nanogenerators, which have the bulk fluttering layer by wind, still show difficulty in generating electricity under the conditions of weak wind because of the static friction arisen from the inherent structure. In this case, the output performance is deteriorated as well as the generator cannot operate completely. In this work, a wind-driven triboelectric nanogenerator (wind-TENG) based on the fluttering of the PTFE strips is proposed to solve the aforementioned problems. At the minimum operating wind pressure of 0.05 MPa, this wind-driven TENG delivers the open-circuit voltage of 3.5 V, short-circuit current of 300 nA, and the associated output power density of 0.64 mW/m2 at the external load resistance of 5 MΩ. Such conditions can be used to light up seven LEDs. Moreover, this wind-TENG has been utilized as a direction sensor which can sense the direction at which the wind is applied. This work thus provides the potential application of the wind-TENG as both self-driven electronics and a self-powered sensor system for detecting the direction under environmental wind.

Automated pig monitoring is an important issue in the surveillance environment of a pig farm. For a large-scale pig farm in particular, practical issues such as monitoring cost should be considered but such consideration based on low-cost embedded boards has not yet been reported. Since low-cost embedded boards have more limited computing power than typical PCs and have tradeoffs between execution speed and accuracy, achieving fast and accurate detection of individual pigs for “on-device” pig monitoring applications is very challenging. Therefore, in this paper, we propose a method for the fast detection of individual pigs by reducing the computational workload of 3 × 3 convolution in widely-used, deep learning-based object detectors. Then, in order to recover the accuracy of the “light-weight” deep learning-based object detector, we generate a three-channel composite image as its input image, through “simple” image preprocessing techniques. Our experimental results on an NVIDIA Jetson Nano embedded board show that the proposed method can improve the integrated performance of both execution speed and accuracy of widely-used, deep learning-based object detectors, by a factor of up to 8.7.