Search

A neuromorphic system is composed of hardware-based artificial neurons and synaptic devices, designed to improve the efficiency of neural computations inspired by energy-efficient and parallel operations of the biological nervous system. A synaptic device-based array can compute vector–matrix multiplication (VMM) with given input voltage signals, as a non-volatile memory device stores the weight information of the neural network in the form of conductance or capacitance. However, unlike software-based neural networks, the neuromorphic system unavoidably exhibits non-ideal characteristics that can have an adverse impact on overall system performance. In this study, the characteristics required for synaptic devices and their importance are discussed, depending on the targeted application. We categorize synaptic devices into two types: conductance-based and capacitance-based, and thoroughly explore the operations and characteristics of each device. The array structure according to the device structure and the VMM operation mechanism of each structure are analyzed, including recent advances in array-level implementation of synaptic devices. Furthermore, we reviewed studies to minimize the effect of hardware non-idealities, which degrades the performance of hardware neural networks. These studies introduce techniques in hardware and signal engineering, as well as software-hardware co-optimization, to address these non-idealities through compensation approaches.

A surge in the number of anthropogenic pollutants has been caused by increasing industrial activities. Nanoplastics are spotlighted as a new aquatic pollutant that are a threat to microbes and larger organisms. Our previous study showed that the subinhibitory concentrations of aquatic pollutants such as phenol and formalin act as signaling molecules and modulate global gene expression and metabolism. In this study, we aimed to investigate the impact of a new type of anthropogenic contaminant, polystyrene (PS) nanoplastics, on the expression of key virulence factors in zoonotic pathogen Edwardsiella piscicida and the assessment of potential changes in the susceptibility of zebrafish as a model host. The TEM data indicated a noticeable change in the cell membrane indicating that PS particles were possibly entering the bacterial cells. Transcriptome analyses performed to identify the differentially expressed genes upon PS exposure revealed that the genes involved in major virulence factor type VI secretion system (T6SS) were down-regulated. However, the expression of T6SS-related genes was recovered from the PS adapted E. piscicida when nanoplastics are free. This demonstrated the hypervirulence of pathogen in infection assays with both cell lines and in vivo zebrafish model. Therefore, this study provides experimental evidence elucidating the direct regulatory impact of nanoplastics influx into aquatic ecosystems on fish pathogenic bacteria, notably influencing the expression of virulence factors.

Spiking neural networks (SNNs) have been researched as an alternative to reduce the gap with the human brain in terms of energy efficiency, due to their inherent spare event‐driven characteristics from a hardware implementation perspective. However, they still face significant challenges in learning, compared to artificial neural networks (ANNs). Recently, several algorithms have been developed to narrow the performance gap between SNNs and ANNs, including features in spiking neurons that can reduce information loss in the membrane potential. Inspired by these advancements, the current study designs and measures a neuron circuit using 180 nm complementary metal‐oxide‐semiconductor (CMOS) technology to address this information loss. The proposed circuit successfully implements these features, and their performance is validated through simulation based on the measured data.

Abstract The progress of artificial intelligence and the development of large‐scale neural networks have significantly increased computational costs and energy consumption. To address these challenges, researchers are exploring low‐power neural network implementation approaches and neuromorphic computing systems are being highlighted as potential candidates. Specifically, the development of high‐density and reliable synaptic devices, which are the key elements of neuromorphic systems, is of particular interest. In this study, an 8 × 16 memcapacitor crossbar array that combines the technological maturity of flash cells with the advantages of NAND flash array structure is presented. The analog properties of the array with high reliability are experimentally demonstrated, and vector‐matrix multiplication with extremely low error is successfully performed. Additionally, with the capability of weight fine‐tuning characteristics, a spiking neural network for CIFAR‐10 classification via off‐chip learning at the wafer level is implemented. These experimental results demonstrate a high level of accuracy of 92.11%, with less than a 1.13% difference compared to software‐based neural networks (93.24%).

The symbiotic community of microorganisms in the gut plays an important role in the health of the host. While many previous studies have been performed on the interactions between the gut microbiome and the host in mammals, studies in fish are still lacking. In this study, we investigated changes in the intestinal microbiome and pathogen susceptibility of zebrafish (Danio rerio) following chronic antibiotics exposure. The chronic antibiotics exposure assay was performed on zebrafish for 30 days using oxytetracycline (Otc), sulfamethoxazole/trimethoprim (Smx/Tmp), or erythromycin (Ery), which are antibiotics widely used in the aquaculture industry. The microbiome analysis indicated that Fusobacteria, Proteobacteria, Firmicutes, and Bacteroidetes were the dominant phyla in the gut microbiome of the zebrafish used in this study. However, in Smx/Tmp-treated zebrafish, the compositions of Fusobacteria and Proteobacteria were changed significantly, and in Ery-treated zebrafish, the compositions of Proteobacteria and Firmicutes were altered significantly. Although alpha diversity analysis showed that there was no significant difference in the richness, beta diversity analysis revealed a community imbalance in the gut microbiome of all chronically antibiotics-exposed zebrafish. Intriguingly, in zebrafish with dysbiosis in the gut microbiome, the pathogen susceptibility to Edwardsiella piscicida, a representative Gram-negative fish pathogen, was reduced. Gut microbiome imbalance resulted in a higher count of goblet cells in intestinal tissue and an upregulation of genes related to the intestinal mucosal barrier. In addition, as innate immunity was enhanced by the increased mucosal barrier, immune and stress-related gene expression in the intestinal tissue was downregulated. In this study, we provide new insight into the effect of gut microbiome dysbiosis on pathogen susceptibility.

Abstract We propose an efficient algorithm to solve inverse problems in the presence of binary clustered datasets. We consider the paradigmatic Hopfield model in a teacher student scenario, where this situation is found in the retrieval phase. This problem has been widely analyzed through various methods such as mean-field approaches or the pseudo-likelihood optimization. Our approach is based on the estimation of the posterior using the Thouless–Anderson–Palmer (TAP) equations in a parallel updating scheme. Unlike other methods, it allows to retrieve the original patterns of the teacher dataset and thanks to the parallel update it can be applied to large system sizes. We tackle the same problem using a restricted Boltzmann machine (RBM) and discuss analogies and differences between our algorithm and RBM learning.

The study of haloarchaea provides an opportunity to expand understanding of the mechanisms used by extremophiles to thrive in and respond to harsh environments, including hypersaline and oxidative stress conditions. A common strategy used to investigate molecular mechanisms of stress response involves the deletion and/or site-directed mutagenesis of genes identified through omics studies followed by a comparison of the mutant and wild-type strains for phenotypic differences. The experimental methods used to monitor these differences must be controlled and reproducible. Current methods to examine recovery of halophilic archaea from extreme stress are complicated by extended incubation times, nutrients not typically encountered in the environment, and other related limitations. Here we describe a method for assessing the function of genes during hypochlorite stress in the halophilic archaeon Haloferax volcanii that overcomes these types of limitations. The method was found reproducible and informative in identifying genes needed for H. volcanii to recover from hypochlorite stress.

Pectobacterium atrosepticum (P. atrosepticum: Pba) which causes potato soft rot and blackleg is a notorious plant pathogen worldwide. Discovery of new types of antimicrobial chemicals that target specifically to virulence factors such as bacterial motility and extracellular enzymes is required for protecting crops from pathogenic infection. A transcriptomic analysis of Pba upon hopeaphenol treatment revealed that bacterial motility-related gene expression, including a master regulator flhDC genes, was significantly influenced by hopeaphenol. We further generated a double knock-out mutant of flhDC genes by CRISPR/Cas9 system and confirmed phenotypic changes in bacterial motility, transcription of extracellular enzymes, and disease development consistent with the result of wild-type treated with hopeaphenol. The hopeaphenol-treated Pba strains, wild-type, double mutant, and complemented strain were unable to secrete the enzymes in vitro, while ΔflhDC double mutant strain reduced the secretion. Thus, our study supports that FlhDC is essential for the virulence of Pba, and proposes that hopeaphenol modulates FlhDC-dependent virulence pathways, suggesting a potential of hopeaphenol as an anti-virulence agent to manage potato soft rot and blackleg diseases.

The geomorphology of coastal lagoons has an important effect on the hydrological balance between fresh water and seawater, which exhibit a wide range of salinity from nearly fresh water to hypersaline water. The present study aimed to characterize seasonal biogeochemical properties of suspended particulate organic matter (POM) in response to environmental variability driven by hydrological dynamics in contrasting coastal lagoon systems. We selected two lagoons distinguished by their geomorphological features, a permanently open artificial lagoon (Gyeongpoho) and an intermittently open natural lagoon (Hyangho), analyzed environmental characteristics, and compared the seasonal differences in the biochemical compositions of POM. Variations in temperature and precipitation in both lagoons showed the characteristics of a typical monsoon climate but variation in salinity differed 6.5−35.0 in Gyeongpoho and 1.1−10.8 in Hyangho. A self-organizing map analysis using the environmental data revealed that the spatiotemporal variations in salinity and nutrient concentrations differed significantly between the two lagoon systems, indicating a difference in hydrologic connectivity between lagoons and marine systems. Furthermore, a canonical correlation analysis highlighted that the POM properties differed according to physicochemical factors. The differing environmental conditions may affect the spatial and temporal variations in organic matter composition, resulting in significant differences in the biochemical composition of POM between two lagoon systems. Overall, this information provides insight into the origin and transport process of POM under changing coastal lagoon environments caused by climatic and human activities.

ABSTRACT Oxidative stress causes cellular damage, including DNA mutations, protein dysfunction, and loss of membrane integrity. Here, we discovered that a TrmB (transcription regulator of mal operon) family protein (Pfam PF01978) composed of a single winged-helix DNA binding domain (InterPro IPR002831) can function as thiol-based transcriptional regulator of oxidative stress response. Using the archaeon Haloferax volcanii as a model system, we demonstrate that the TrmB-like OxsR is important for recovery of cells from hypochlorite stress. OxsR is shown to bind specific regions of genomic DNA, particularly during hypochlorite stress. OxsR-bound intergenic regions were found proximal to oxidative stress operons, including genes associated with thiol relay and low molecular weight thiol biosynthesis. Further analysis of a subset of these sites revealed OxsR to function during hypochlorite stress as a transcriptional activator and repressor. OxsR was shown to require a conserved cysteine (C24) for function and to use a CG-rich motif upstream of conserved BRE/TATA box promoter elements for transcriptional activation. Protein modeling suggested the C24 is located at a homodimer interface formed by antiparallel α helices, and that oxidation of this cysteine would result in the formation of an intersubunit disulfide bond. This covalent linkage may promote stabilization of an OxsR homodimer with the enhanced DNA binding properties observed in the presence of hypochlorite stress. The phylogenetic distribution TrmB family proteins, like OxsR, that have a single winged-helix DNA binding domain and conserved cysteine residue suggests this type of redox signaling mechanism is widespread in Archaea. IMPORTANCE TrmB-like proteins, while not yet associated with redox stress, are found in bacteria and widespread in archaea. Here, we expand annotation of a large group of TrmB-like single winged-helix DNA binding domain proteins from diverse archaea to function as thiol-based transcriptional regulators of oxidative stress response. Using Haloferax volcanii as a model, we reveal that the TrmB-like OxsR functions during hypochlorite stress as a transcriptional activator and repressor of an extensive gene coexpression network associated with thiol relay and other related activities. A conserved cysteine residue of OxsR serves as the thiol-based sensor for this function and likely forms an intersubunit disulfide bond during hypochlorite stress that stabilizes a homodimeric configuration with enhanced DNA binding properties. A CG-rich DNA motif in the promoter region of a subset of sites identified to be OxsR-bound is required for regulation; however, not all sites have this motif, suggesting added complexity to the regulatory network.

Effective antibacterial substances of Aralia continentalis have anti-biofilm and bactericidal activity to the oral pathogen Streptococcus mutans. In this study, three compounds extracted from A. continentalis were identified as acanthoic acid, continentalic acid, and kaurenoic acid by NMR and were further investigated how these diterpenoids affect the physiology of the S. mutans. When S. mutans was exposed to individual or mixed fraction of diterpenoids, severe growth defects and unique morphology were observed. The proportion of unsaturated fatty acids in the cell membrane was increased compared to that of saturated fatty acids in the presence of diterpenoids. Genome-wide gene expression profiles with RNA-seq were compared to reveal the mode of action of diterpenoids. Streptococcus mutans commonly enhanced the expression of 176 genes in the presence of the individual diterpenoids, whereas the expression of 232 genes was considerably reduced. The diterpenoid treatment modulated the expression of genes or operon(s) involved in cell membrane synthesis, cell division, and carbohydrate metabolism of S. mutans. Collectively, these findings provide novel insights into the antibacterial effect of diterpenoids to control S. mutans infection, which causes human dental caries.

In this study, we propose an analog CMOS integrate-and-fire (I & F) neuron circuit with a synaptic off-state current blocking operation. The proposed circuit prevents unintended potential changes in the membrane capacitor owing to the off-state current of synaptic devices, thereby preventing a decrease in the accuracy of the spiking neural network (SNN) inference system. Compared to the conventional I & F neuron circuit, the basic I & F and synaptic off-current blocking operations of the proposed I & F neuron circuit were confirmed in a circuit-level simulation. Furthermore, to verify the effect of the proposed circuit on the neural network, a multi-layer SNN simulation was performed, and the accuracy of the inference system was compared for the conventional and proposed I & F neuron circuits. The simulation and analysis results demonstrate the robustness of the I & F neuron circuit to the drop in accuracy of inference systems due to off-state currents in synaptic devices.

Spiking neural networks (SNNs) have attracted many researchers’ interests due to its biological plausibility and event-driven characteristic. In particular, recently, many studies on high-performance SNNs comparable to the conventional analog-valued neural networks (ANNs) have been reported by converting weights trained from ANNs into SNNs. However, unlike ANNs, SNNs have an inherent latency that is required to reach the best performance because of differences in operations of neuron. In SNNs, not only spatial integration but also temporal integration exists, and the information is encoded by spike trains rather than values in ANNs. Therefore, it takes time to achieve a steady-state of the performance in SNNs. The latency is worse in deep networks and required to be reduced for the practical applications. In this work, we propose a pre-charged membrane potential (PCMP) for the latency reduction in SNN. A variety of neural network applications (e.g., classification, autoencoder using MNIST and CIFAR-10 datasets) are trained and converted to SNNs to demonstrate the effect of the proposed approach. The latency of SNNs is successfully reduced without accuracy loss. In addition, we propose a delayed evaluation method (DE), by which the errors during the initial transient are discarded. The error spikes occurring in the initial transient is removed by DE, resulting in the further latency reduction. DE can be used in combination with PCMP for further latency reduction. Finally, we also show the advantages of the proposed methods in improving the number of spikes required to reach a steady-state of the performance in SNNs for energy-efficient computing.

Saeu-jeotgal, a Korean fermented shrimp food, is commonly used as an ingredient for making kimchi and other side dishes. The high salinity of the jeotgal contributes to its flavor and inhibits the growth of food spoilage microorganisms. Interestingly, Staphylococcus saprophyticus was discovered to be capable of growth even after treatment with 20% NaCl. To elucidate the tolerance mechanism, a genome-wide gene expression of S. saprophyticus against 0%, 10%, and 20% NaCl was investigated by RNA sequencing. A total of 831, 1314, and 1028 differentially expressed genes (DEGs) were identified in the 0% vs. 10%, 0% vs. 20%, and 10% vs. 20% NaCl comparisons, respectively. The Clusters of Orthologous Groups analysis revealed that the DEGs were involved in amino acid transport and metabolism, transcription, and inorganic ion transport and metabolism. The functional enrichment analysis showed that the expression of the genes encoding mechanosensitive ion channels, sodium/proton antiporters, and betaine/carnitine/choline transporter family proteins was downregulated, whereas the expression of the genes encoding universal stress proteins and enzymes for glutamate, glycine, and alanine synthesis was upregulated. Therefore, these findings suggest that the S. saprophyticus isolated from the saeu-jeotgal utilizes different molecular strategies for halotolerance, with glutamate as the key molecule.

In the past few decades, NAND flash memory has been one of the most successful nonvolatile storage technologies, and it is commonly used in electronic devices because of its high scalability and reliable switching properties. To overcome the scaling limit of planar NAND flash arrays, various three-dimensional (3D) architectures of NAND flash memory and their process integration methods have been investigated in both industry and academia and adopted in commercial mass production. In this paper, 3D NAND flash technologies are reviewed in terms of their architecture and fabrication methods, and the advantages and disadvantages of the architectures are compared.

A systematic device-model calibration (extraction) methodology has been proposed to reduce parameter calibration time of advanced compact model for modern nano-scale semiconductor devices. The adaptive pattern search algorithm is a variant of the direct search method, which explore in the parameter space with adaptive searching step and direction. It is very straightforward, but powerful, in high dimensional optimization problem since adaptive step and direction are decided by simple computation. The proposed method iterates less but shows superior accuracy over the conventional method. It is possible to be applied to a behavioral or empirical model correspond to emerging devices, such as tunneling field-effect transistor (TFET) and negative capacitance field-effect transistor (NCFET) due to its universality in parameter calibration for the model accuracy.

A hardware-based spiking neural network (SNN) has attracted many researcher’s attention due to its energy-efficiency. When implementing the hardware-based SNN, offline training is most commonly used by which trained weights by a software-based artificial neural network (ANN) are transferred to synaptic devices. However, it is time-consuming to map all the synaptic weights as the scale of the neural network increases. In this paper, we propose a method for quantized weight transfer using spike-timing-dependent plasticity (STDP) for hardware-based SNN. STDP is an online learning algorithm for SNN, but we utilize it as the weight transfer method. Firstly, we train SNN using the Modified National Institute of Standards and Technology (MNIST) dataset and perform weight quantization. Next, the quantized weights are mapped to the synaptic devices using STDP, by which all the synaptic weights connected to a neuron are transferred simultaneously, reducing the number of pulse steps. The performance of the proposed method is confirmed, and it is demonstrated that there is little reduction in the accuracy at more than a certain level of quantization, but the number of pulse steps for weight transfer substantially decreased. In addition, the effect of the device variation is verified.

NOR/AND flash memory was studied in neuromorphic systems to perform vector-by-matrix multiplication (VMM) by summing the current. Because the size of NOR/AND cells exceeds those of other memristor synaptic devices, we proposed a 3D AND-type stacked array to reduce the cell size. Through a tilted implantation method, the conformal sources and drains of each cell could be formed, with confirmation by a technology computer aided design (TCAD) simulation. In addition, the cell-to-cell variation due to the etch slope could be eliminated by controlling the deposition thickness of the cells. The suggested array can be beneficial in simple program/inhibit schemes given its use of Fowler–Nordheim (FN) tunneling because the drain lines and source lines are parallel. Therefore, the conductance of each synaptic device can be updated at low power level.

Phenol and formalin are major water pollutants that are frequently discharged into the aquatic milieu. These chemicals can affect broad domains of life, including microorganisms. Aquatic pollutants, unlike terrestrial pollutants, are easily diluted in water environments and exist at a sub-inhibitory concentration (sub-IC), thus not directly inhibiting bacterial growth. However, they can modulate gene expression profiles. The sub-IC values of phenol and formalin were measured by minimal inhibitory concentration (MIC) assay to be 0.146% (1.3 mM) and 0.0039% (0.38 mM), respectively, in Edwardsiella piscicida CK108, a Gram-negative fish pathogen. We investigated the differentially expressed genes (DEG) by RNA-seq when the cells were exposed to the sub-ICs of phenol and formalin. DEG analyses revealed that genes involved in major virulence factors (type I fimbriae, flagella, type III and type VI secretion system) and various cellular pathways (energy production, amino acid synthesis, carbohydrate metabolism and two-component regulatory systems) were up- or downregulated by both chemicals. The genome-wide gene expression data corresponded to the results of a quantitative reverse complementary-PCR and motility assay. This study not only provides insight into how a representative fish pathogen, E. piscicida CK108, responds to the sub-ICs of phenol and formalin but also shows the importance of controlling chemical pollutants in aquatic environments.

While cytoplasmic tRNA 2-thiolation protein 1 (Tuc1/Ncs6) and ubiquitin-related modifier-1 (Urm1) are important in the 2-thiolation of 5-methoxycarbonylmethyl-2-thiouridine (mcm5s2U) at wobble uridines of tRNAs in eukaryotes, the biocatalytic roles and properties of Ncs6/Tuc1 and its homologs are poorly understood. Here we present the first report of an Ncs6 homolog of archaea (NcsA of Haloferax volcanii) that is essential for maintaining cellular pools of thiolated tRNA(Lys)UUU and for growth at high temperature. When purified from Hfx. volcanii, NcsA was found to be modified at Lys204 by isopeptide linkage to polymeric chains of the ubiquitin-fold protein SAMP2. The ubiquitin-activating E1 enzyme homolog of archaea (UbaA) was required for this covalent modification. Non-covalent protein partners that specifically associated with NcsA were also identified including UbaA, SAMP2, proteasome activating nucleotidase (PAN)-A/1, translation elongation factor aEF-1α and a β-CASP ribonuclease homolog of the archaeal cleavage and polyadenylation specificity factor 1 family (aCPSF1). Together, our study reveals that NcsA is essential for growth at high temperature, required for formation of thiolated tRNA(Lys)UUU and intimately linked to homologs of ubiquitin-proteasome, translation and RNA processing systems.

Objective: The rich botanical biodiversity resulting from diverse climates and geographical distinctiveness offers a plethora of biological resources that can be pivotal in developing innovative biomaterials. This investigation sought to evaluate the functional properties of indigenous Korean plant species. Methods: Forty-six indigenous plants during a year-long expedition across inhabited and uninhabited Korean islands were collected. The plant specimens were divided into 5 parts (flower, fruit, stem, leaf, and whole body) and subjected to extraction using water, 30% ethanol, and 70% ethanol, followed by characterizations of anti-inflammatory, immune response, and anti-bacterial activity. Results: Thirty-eight percent of the extracts (59 extracts from 31 species) exhibited statistically significant anti-inflammatory effects. Concurrently, 22% of the extracts (35 extracts from 24 species) demonstrated notable immune boosting effects. Additionally, 17 extracts exhibited significant inhibitory effects against the growth of pathogenic bacteria. Conclusion: This study highlights the potential utility of extracts of plants from Korean islands as natural agents for next-generation pharmaceutical and medical applications by emphasizing their effectiveness in combating inflammation, enhancing immune responses, and conferring anti-bacterial benefits. [ABSTRACT FROM AUTHOR]

A new approach to investigate the current spreading effect and electrode pattern design in the multiple-quantum-well light-emitting diode (LED) is presented. The performance of the LEDs is shown to be highly affected by the different electron patterns in the devices.