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Introduction: Ambient temperature-induced hypocotyl elongation in Arabidopsis seedlings is sensed by the epidermis-localized phytochrome B (phyB) and transduced into auxin biosynthesis via a basic helix-loop-helix transcription factor, phytochrome-interacting factor 4 (PIF4). Once synthesized, auxin travels down from the cotyledons to the hypocotyl, triggering hypocotyl cell elongation. Thus, the phyB–PIF4 module involved in thermosensing and signal transduction is a potential genetic target for engineering warm temperature-insensitive plants. Objectives: This study aims to manipulate warm temperature-induced elongation of plants at the post-translational level using phyB variants with dark reversion, the expression of which is subjected to heat stress. Methods: The thermosensitive growth response of Arabidopsis was manipulated by expressing the single amino acid substitution variant of phyB (phyB[G515E]), which exhibited a lower dark reversion rate than wild-type phyB. Other variants with slow (phyB[G564E]) or rapid (phyB[S584F]) dark reversion or light insensitivity (phyB[G767R]) were also included in this study for comparison. Warming-induced transient expression of phyB variants was achieved using heat shock-inducible promoters. Arabidopsis PHYB[G515E] and PHYB[G564E] were also constitutively expressed in rice in an attempt to manipulate the heat sensitivity of a monocotyledonous plant species. Results: At an elevated temperature, Arabidopsis seedlings transiently expressing PHYB[G515E] under the control of a heat shock-inducible promoter exhibited shorter hypocotyls than those expressing PHYB and other PHYB variant genes. This warm temperature-insensitive growth was related to the lowered PIF4 and auxin responses. In addition, transgenic rice seedlings expressing Arabidopsis PHYB[G515E] and PHYB[G564E] showed warm temperature-insensitive shoot growth. Conclusion: Transient expression of phyB variants with altered dark reversion rates could serve as an effective optogenetic technique for manipulating PIF4–auxin-mediated thermomorphogenic responses in plants.

Abstract The chloroplast (cp.) genome, also known as plastome, plays crucial roles in plant survival, adaptation, and evolution. The stable genetic structure of cp. genomes provides an ideal system for investigating species evolution. We sequenced three complete cp. genome sequences of Capsicum species and analyzed them using sequences of various Capsicum species retrieved from the NCBI database. The cp. genome of Capsicum species maintains a well-preserved quadripartite structure consisting of two inverted repeats (IRs) flanked by a large single copy (LSC) region and a small single copy (SSC) region. The sizes of cp. genome sequences ranged from 156,583 bp (C. lycianthoides) to 157,390 bp (C.pubescens). A total of 127–132 unique genes, including 83–87 protein-coding, 36–37 tRNA, and eight rRNA genes, were predicted. Comparison of cp. genomes of 10 Capsicum species revealed high sequence similarity in genome-wide organization and gene arrangements. Fragments of trnT-UGU/trnL-UAA, ccsA, ndhD, rps12, and ycf1 were identified as variable regions, and nucleotide variability of LSC and SSC was higher than that of IR. Phylogenetic speciation analysis showed that the major domesticated C. annuum species were the most extensively divergent species and closely related to C. tovarii and C. frutescens. Analysis of divergent times suggested that a substantial range of speciation events started occurring ~ 25.79 million years ago (Mya). Overall, comparative analysis of cp. genomes of Capsicum species not only offers new insights into their genetic variation and phylogenetic relationships, but also lays a foundation for evolutionary history, genetic diversity, conservation, and biological breeding of Capsicum species.

Abstract Neuromorphic computing research is being actively pursued to address the challenges posed by the need for energy-efficient processing of big data. One of the promising approaches to tackle the challenges is the hardware implementation of spiking neural networks (SNNs) with bio-plausible learning rules. Numerous research works have been done to implement the SNN hardware with different synaptic plasticity rules to emulate human brain operations. While a standard spike-timing-dependent-plasticity (STDP) rule is emulated in many SNN hardware, the various STDP rules found in the biological brain have rarely been implemented in hardware. This study proposes a CMOS-memristor hybrid synapse circuit for the hardware implementation of a Ca ion-based plasticity model to emulate the various STDP curves. The memristor was adopted as a memory device in the CMOS synapse circuit because memristors have been identified as promising candidates for analog non-volatile memory devices in terms of energy efficiency and scalability. The circuit design was divided into four sub-blocks based on biological behavior, exploiting the non-volatile and analog state properties of memristors. The circuit was designed to vary weights using an H-bridge circuit structure and PWM modulation. The various STDP curves have been emulated in one CMOS-memristor hybrid circuit, and furthermore a simple neural network operation was demonstrated for associative learning such as Pavlovian conditioning. The proposed circuit is expected to facilitate large-scale operations for neuromorphic computing through its scale-up.

Abstract As there is an increasing need for an efficient solver of combinatorial optimization problems, much interest is paid to the Ising machine, which is a novel physics-driven computing system composed of coupled oscillators mimicking the dynamics of the system of coupled electronic spins. In this work, we propose an energy-efficient nano-oscillator, called OTSNO, which is composed of an Ovonic Threshold Switch (OTS) and an electrical resistor. We demonstrate that the OTSNO shows the synchronization behavior, an essential property for the realization of an Ising machine. Furthermore, we have discovered that the capacitive coupling is advantageous over the resistive coupling for the hardware implementation of an Ising solver by providing a larger margin of the variations of components. Finally, we implement an Ising machine composed of capacitively-coupled OTSNOs to demonstrate that the solution to a 14-node MaxCut problem can be obtained in 40 µs while consuming no more than 2.3 µJ of energy. Compared to a previous hardware implementation of the phase-transition nano-oscillator (PTNO)-based Ising machine, the OTSNO-based Ising machine in this work shows the performance of the increased speed by more than one order while consuming less energy by about an order.

Abstract A tokamak relies on the axisymmetric magnetic fields to confine fusion plasmas and aims to deliver sustainable and clean energy. However, misalignments arise inevitably in the tokamak construction, leading to small asymmetries in the magnetic field known as error fields (EFs). The EFs have been a major concern in the tokamak approaches because small EFs, even less than 0.1%, can drive a plasma disruption. Meanwhile, the EFs in the tokamak can be favorably used for controlling plasma instabilities, such as edge-localized modes (ELMs). Here we show an optimization that tailors the EFs to maintain an edge 3D response for ELM control with a minimized core 3D response to avoid plasma disruption and unnecessary confinement degradation. We design and demonstrate such an edge-localized 3D response in the KSTAR facility, benefiting from its unique flexibility to change many degrees of freedom in the 3D coil space for the various fusion plasma regimes. This favorable control of the tokamak EF represents a notable advance for designing intrinsically 3D tokamaks to optimize stability and confinement for next-step fusion reactors.

Abstract Designing robust blue organic light-emitting diodes is a long-standing challenge in the display industry. The highly energetic states of blue emitters cause various degradation paths, leading to collective luminance drops in a competitive manner. However, a key mechanism of the operational degradation of organic light-emitting diodes has yet to be elucidated. Here, we show that electron-induced degradation reactions play a critical role in the short lifetime of blue organic light-emitting diodes. Our control experiments demonstrate that the operational lifetime of a whole device can only be explained when excitons and electrons exist together. We examine the atomistic mechanisms of the electron-induced degradation reactions by analyzing their energetic profiles using computational methods. Mass spectrometric analysis of aged devices further confirm the key mechanisms. These results provide new insight into rational design of robust blue organic light-emitting diodes.

Abstract Coordination complexes, particularly metalloproteins, highlight the significance of metal-sulfur bonds in biological processes. Their unique attributes inspire efforts to synthetically reproduce these intricate metal-sulfur motifs. Here, we investigate the synthesis and characterization of copper(I)-thioether coordination complexes derived from copper(I) halides and the chiral cyclic β-amino acid trans-4-aminotetrahydrothiophene-3-carboxylic acid (ATTC), which present distinctive structural properties and ligand-to-metal ratios. By incorporating ATTC as the ligand, we generated complexes that feature a unique chiral conformation and the capacity for hydrogen bonding, facilitating the formation of distinct geometric structures. Through spectroscopic analyses and density functional theory (DFT) calculations, we studied the complexes’ optical properties, including their emission bands and variable second-harmonic generation (SHG) efficiencies, which vary based on the halide used. Our findings underscore the potential of the ATTC ligand in creating unusual coordination complexes and pave the way for further investigations into their potential applications, particularly within materials science.

Abstract The force-balanced state of magnetically confined plasmas heated up to 100 million degrees Celsius must be sustained long enough to achieve a burning-plasma state, such as in the case of ITER, a fusion reactor that promises a net energy gain. This force balance between the Lorentz force and the pressure gradient force, known as a plasma equilibrium, can be theoretically portrayed together with Maxwell’s equations as plasmas are collections of charged particles. Nevertheless, identifying the plasma equilibrium in real time is challenging owing to its free-boundary and ill-posed conditions, which conventionally involves iterative numerical approach with a certain degree of subjective human decisions such as including or excluding certain magnetic measurements to achieve numerical convergence on the solution as well as to avoid unphysical solutions. Here, we introduce GS-DeepNet, which learns plasma equilibria through solely unsupervised learning, without using traditional numerical algorithms. GS-DeepNet includes two neural networks and teaches itself. One neural network generates a possible candidate of an equilibrium following Maxwell’s equations and is taught by the other network satisfying the force balance under the equilibrium. Measurements constrain both networks. Our GS-DeepNet achieves reliable equilibria with uncertainties in contrast with existing methods, leading to possible better control of fusion-grade plasmas.

Abstract Various memristive devices have been proposed for use in neuromorphic computing systems as artificial synapses. Analog synaptic devices with linear conductance updates during training are efficiently essential to train neural networks. Although many different analog memristors have been proposed, a more reliable approach to implement analog synaptic devices is needed. In this study, we propose the memristor of a Cu/SiOx/implanted a-SiGex/p++ c-Si structure containing an a-Si layer with properly controlled conductance through Ge implantation. The a-SiGex layer plays a multifunctional role in device operation by limiting the current overshoot, confining the heat generated during operation and preventing the silicide formation reaction between the active metal (Cu) and the Si bottom electrode. Thus, the a-SiGex interface layer enables the formation of multi-weak filaments and induces analog switching behaviors. The TEM observation shows that the insertion of the a-SiGex layer between SiOx and c-Si remarkably suppresses the formation of copper silicide, and reliable set/reset operations are secured. The origin of the analog switching behaviors is discussed by analyzing current-voltage characteristics and electron microscopy images. Finally, the memristive-neural network simulations show that our developed memristive devices provide high learning accuracy and are promising in future neuromorphic computing hardware.

Abstract Real world settings are seldomly just composed of level surfaces and stairs are frequently encountered in daily life. Unfortunately, ~ 90% of the elderly population use some sort of compensation pattern in order to negotiate stairs. Because the biomechanics required to successfully ascend stairs is significantly different from level walking, an independent training protocol is warranted. Here, we present as a preliminary investigation with 11 able-bodied subjects, prior to clinical trials, whether Myosuit could potentially serve as a stair ascent training robot. Myosuit is a soft wearable exosuit that was designed to assist the user via hip and knee extension during the early stance phase. We hypothesized that clinical studies could be carried out if the lower limb kinematics, sensory feedback via plantar force, and electromyography (EMG) patterns do not deviate from the user’s physiological stair ascent patterns while reducing hip and knee extensor demand. Our results suggest that Myosuit conserves the user’s physiological kinematic and plantar force patterns. Moreover, we observe approximately 20% and 30% decrease in gluteus maximus and vastus medialis EMG levels in the pull up phase, respectively. Collectively, Myosuit reduces the hip and knee extensor demand during stair ascent without any introduction of significant compensation patterns.

Background: Nitrogen (N) is an essential macronutrient for plant growth and development. To support agricultural production and enhance crop yield, two major N sources, nitrate and ammonium, are applied as fertilizers to the soil. Although many studies have been conducted on N uptake and signal transduction, the molecular genetic mechanisms of N-mediated physiological roles, such as the secondary growth of storage roots, remain largely unknown. Methods: One-year-old P. ginseng seedlings treated with KNO3 were analyzed for the secondary growth of storage roots. The histological paraffin sections were subjected to bright and polarized light microscopic analysis. Genome-wide RNA-seq and network analysis were carried out to dissect the molecular mechanism of nitrate-mediated promotion of ginseng storage root thickening. Results: Here, we report the positive effects of nitrate on storage root secondary growth in Panax ginseng. Exogenous nitrate supply to ginseng seedlings significantly increased the root secondary growth. Histological analysis indicated that the enhancement of root secondary growth could be attributed to the increase in cambium stem cell activity and the subsequent differentiation of cambium-derived storage parenchymal cells. RNA-seq and gene set enrichment analysis (GSEA) revealed that the formation of a transcriptional network comprising auxin, brassinosteroid (BR)-, ethylene-, and jasmonic acid (JA)-related genes mainly contributed to the secondary growth of ginseng storage roots. In addition, increased proliferation of cambium stem cells by a N-rich source inhibited the accumulation of starch granules in storage parenchymal cells. Conclusion: Thus, through the integration of bioinformatic and histological tissue analyses, we demonstrate that nitrate assimilation and signaling pathways are integrated into key biological processes that promote the secondary growth of P. ginseng storage roots.

Duty-cycle distortion may occur due to variations in the process, voltage, and temperature, or if the clock signal passes through clock buffers. To compensate duty-cycle distortion, a digital duty-cycle corrector (DCC) with counter-based half-cycle delay line (HCDL) is introduced. The HCDL of conventional edge combiner type DCC requires a large area and make the DCC unsuitable for applications that operate in a wide-range frequency. The proposed counter-based HCDL reduces the silicon cost by repeating the delay line, while maintaining the performance of conventional DCC. A prototype chip fabricated in a 65nm CMOS process has an area of 0.0064mm2 and consumes 2.1mW at 1.6GHz. The measurement results show that the duty-cycle error is less than 0.89% over an input duty-cycle range of 20-80% for 50-1600MHz.

Post-stroke gait is characterized by slow and asymmetrical hemiparetic gait. This is attributed to the paretic lower limb which has limited plantar propulsion. The most effective method to restore paretic limb function is constraint-induced movement therapy (CIMT), which promotes the usage of the paretic limb by restricting the movement of the unafflicted limb. However, due to the necessity of both lower limbs to perform gait, CIMT methods could not be directly applied for gait rehabilitation. In this study, we explore the feasibility of utilizing a knee scooter as a means to facilitate CIMT gait training. We hypothesize that if lower limb kinematics and muscle activation patterns during gait with a knee scooter match that of natural gait, the knee scooter could be utilized for CIMT gait training. We measured the lower-limb joint angles, plantar force, EMG patterns, stride length, and step times of 13 healthy subjects during gait with a knee scooter and natural gait. The results suggest that the gait patterns while using the knee scooter closely resemble those of natural gait.

It is vital for rehabilitating patients to perform as many task-related exercises as possible. These patients often need either force or trajectory assistance in order to perform gait. While this can be provided in the form of traditional gait rehabilitation or currently emerging robot-assisted gait training, there is a need for an affordable means to assist gait training. In this study, we present a passive gait assistance device that is composed of a spring-bar system attached to an elastic cord and a specialized shoe. The shoe has two straps attached such that both plantar and dorsiflexion torque can be applied to the user depending on the angle of the pulling force. The merit of the devices is that it is an affordable means to provide the user with gait assistance while allowing some freedom of one’s foot movement. We show that, with 20 community-dwelling seniors, our system successfully produces plantar flexion and dorsiflexion torque according to the gait cycle. Furthermore, electromyography analysis suggests that plantar flexor demand during the late stance phase and dorsiflexor demand during the swing phase are significantly reduced.

In-memory computing facilitates efficient parallel computing based on the programmable memristor crossbar array. Proficient hardware image processing can be implemented by utilizing the analog vector-matrix operation with multiple memory states of the nonvolatile memristor in the crossbar array. Among various materials, 2D materials are great candidates for a switching layer of nonvolatile memristors, demonstrating low-power operation and electrical tunability through their remarkable physical and electrical properties. However, the intrinsic device-to-device (D2D) variation of memristors within the crossbar array can degrade the accuracy and performance of in-memory computing. Here, we demonstrate hardware image processing using the fabricated 2D hexagonal boron nitride-based memristor to investigate the effects of D2D variation on the hardware convolution process. The image quality is evaluated by peak-signal-to-noise ratio, structural similarity index measure, and Pratt’s figure of merit and analyzed according to D2D variations. Then, we propose a novel two-step gradual reset programming scheme to enhance the conductance uniformity of multiple states of devices. This approach can enhance the D2D variation and demonstrate the improved quality of the image processing result. We believe that this result suggests the precise tuning method to realize high-performance in-memory computing.

Conventional filamentary memristors are limited in dynamics by the high electric-field dependence of the conductive filament. Here, Jeong et al. presents a method which creates a cluster-type memristor, enabling large conductance range and long data retention.

M. incognita, a root-knot nematode (RKN), infects the roots of several important food crops, including sweet potato (Ipomoea batatas Lam.), and severely reduces yields. However, the molecular mechanisms underlying infection remain unclear. Previously, we investigated differential responses to RKN invasion in susceptible and resistant sweet potato cultivars through RNA-seq-based transcriptome analysis. In this study, gene expression similarities and differences were examined in RKN-susceptible sweet potato cultivars during the compatible response to RKN infection. Three susceptible cultivars investigated in previous research were used: Dahomi (DHM), Shinhwangmi (SHM), and Yulmi (YM). Of the three cultivars, YM had the highest number of genes with altered expression in response to infection. YM was also the cultivar with the highest susceptibility to RKN. Comparisons among cultivars identified genes that were regulated in more than one cultivar upon infection. Pairwise comparisons revealed that YM and DHM shared the most regulated genes, whereas YM and SHM shared the lowest number of regulated genes. Five genes were up-regulated, and two were down-regulated, in all three cultivars. Among these, four genes were highly up-regulated in all cultivars: germin-like protein, anthranilate synthase α subunit, isocitrate lyase, and uncharacterized protein. Genes were also identified that were uniquely regulated in each cultivar in response to infection, suggesting that susceptible cultivars respond to infection through shared and cultivar-specific pathways. Our findings expand the understanding of the compatible response to RKN invasion in sweet potato roots and provide useful information for further research on RKN defense mechanisms.

Abstract Heel raise is widely prescribed to patients with chronic ankle instability in order to strengthen the Peroneus Longus muscle (PL) which supports the weakened lateral collateral ligaments. While the exercise itself is intuitive, ankle orientation is of particular importance because heel raises performed with inversion do not well recruit the PL. This implies that proper execution is imperative and a means to assess heel raise training sessions is needed. In this study we present a smart insole system capable of identifying heel raise events and its corresponding rise, hold and drop phases, which allows for a more descriptive analysis. The results from our heel raise sessions, which consist of four different variants performed by five healthy subjects, suggest that medial–lateral foot pressure distribution and foot orientation are needed to differentiate heel raises performed with ankle eversion and inversion. We go further and substantiate that proper execution, detected by our system, indeed leads to increased PL activation by analyzing the electromyography signals. We believe that the proposed system may provide clinicians with invaluable information regarding onsite as well as at-home training and possibly, with biofeedback, serve as foundation for software as a medical device.

Neuromorphic hardware is a system with massive potential to enable efficient computing by mimicking the human brain. The novel system processes information using neuron spikes (Action Potentials) and the synaptic connections between neurons are trained using biologically plausible methods like spike-timing-dependent plasticity (STDP). Memristor is one of the promising candidates to implement such neuromorphic hardware. Two types of memristors, diffusive and drift, have been proposed to form a synapse showing faithful emulation of STDP, where the diffusion effect is used to trace the spike timing history crucial for STDP and the drift memristor keeps the weight information in a longer time scale. The purpose of this paper is to systematically investigate STDP characteristics in such a synapse with serially connected two memristors using SPICE models. The results show that STDP properties are strongly dependent on device parameters and even the shape of STDP curves is modified. Different shapes of the STDP curve were identified. The results and analysis could support the design of emerging device-based synapses, which can faithfully mimic biological STDP characteristics for future neuromorphic systems.

Ni_{2}Mo_{3}O_{8} is a pyroelectric honeycomb antiferromagnet exhibiting peculiar changes in its electric polarization at magnetic transitions. Ni_{2}Mo_{3}O_{8} stands out from isostructural magnetic compounds, showing an anomalously low magnetic transition temperature and unique magnetic anisotropy. We determine the magnetic structure of Ni_{2}Mo_{3}O_{8} utilizing high-resolution powder and single-crystal neutron diffraction. A noncollinear stripy antiferromagnetic order is found in the honeycomb planes. The magnetic space group is P_{C}na2_{1}. The in-plane magnetic connection is of the stripy type for both the ab-plane and c-axis spin components. This is a simpler connection than the one proposed previously. The ferromagnetic interlayer order of the c-axis spin components in our model is also distinct. The magnetic anisotropy of Ni_{2}Mo_{3}O_{8} is characterized by orientation-dependent magnetic susceptibility measurements on a single crystal, consistent with neutron diffraction analysis. The local magnetoelectric tensor analysis using our magnetic models provides insights into its magnetoelectric coupling and polarization. Thus, our results deliver essential information for understanding both the unusual magnetoelectric properties of Ni_{2}Mo_{3}O_{8} and the prospects for observing exotic nonreciprocal, Hall, and magnonic effects characteristic of this compound family.

This study aims to evaluate the dynamic responses of the jacket-type offshore wind turbine using FAST software (Fatigue, Aerodynamics, Structures, and Turbulence). A systematic series of simulation cases of a 5 MW jacket-type offshore wind turbine, including wind-only, wave-only, wind & wave load cases are conducted. The dynamic responses of the wind turbine structure are obtained, including the structure displacement, rotor speed, thrust force, nacelle acceleration, bending moment at the tower bottom, and shear force on the jacket leg. The calculated time-domain results are transformed to frequency domain results using FFT and the environmental load with more impact on each dynamic response is identified. It is confirmed that the dynamic displacements of the wind turbine are dominant in the wave frequency under the incident wave alone condition, and the rotor thrust, nacelle acceleration, and bending moment at the bottom of the tower exhibit high responses in the natural frequency band of the wind turbine. In the wind only condition, all responses except the vertical displacement of the wind turbine are dominant at three times the rotor rotation frequency (considering the number of blades) generated by the wind. In a combined external force with wind and waves, it was observed that the horizontal displacement is dominant by the wind load. Additionally, the bending moment on the tower base is highly affected by the wind. The shear force of the jacket leg is basically influenced by the wave loads, but it can be affected by both the wind and wave loads especially under the turbulent wind and irregular wave conditions.

Toroidal moments arise from vortex like spin arrangements. These moments can then interact, giving rise to ferri- or ferro-toroidal order, though controlling such order is difficult. Here, the authors demonstrate a ferri-toroidal state in BaCoSiO4, which under an applied magnetic field exhibits multiple toroidal and metamagnetic transitions.

The risk management framework (RMF) applied by the United States combines the concepts of information security and risk management in the product development process. This includes the systematic structure of equipment, parts, other construction systems, facilities, and personnel, as well as the related security of cyberspace. This concept has been a concept that has been systematically applied for the completion of information security from the requirement planning stage to the destruction of the weapon system. The RMF, which should be reflected in the project of power enhancement to ensure the perfect performance of the weapons system that our military will use in the future, is unfamiliar to Republic of Korea Army (ROK). RMF is a step-level field that has not yet been based on detailed research and measures in any ROK military, such as the Army, Navy, and Air Force. However, the USFK, which is stationed in the Republic of Korea during peacetime, and the United States’ wartime reinforcement forces [Flexible Deterrence Option (FDO), Force Module Package (FMP), Time Phased Forces Deployment Data (TPFDD)], which are deployed at the request of the CFC Commander in the event of a crisis situation on the Korean peninsula and under the direction of the Joint Chiefs of Staff, are thoroughly prepared for cyber threats by applying the RMF procedure. Therefore, the military should also create and apply the corresponding procedures during combined and joint operations as soon as possible. This study aims to provide a direction for the development of a categorization system, which is the most basic and important step 1 system in the RMF process, and I hope that it will help in the implementation of the Korean Risk Management Framework (KRMF) that should be applied in the future.

This study investigates the triple-level cell (TLC) memory retention of a MoS2-channel based charge trap flash (CTF) device. A top-gated CTF device with a high-κ gate dielectric is found to have a high coupling ratio, which enhances the tunneling efficiency for programming. The fabricated devices show the long memory retention performance for each state, demonstrating the feasibility of a robust TLC CTF memory device based on a CVD grown 2D material.

Basic human ambulation relies on a bipedal gait, which has been reported to be directly related to quality of life. However, injuries to the lower limb can cause an inability to walk and require non-weightbearing periods to heal. Among the many ambulatory aids, standard axillary crutches are prescribed. However, due to the disadvantages of having to use both hands, a slow gait, pain, nerve damage, and gait patterns that differ from that of healthy subjects, currently, a new generation of ambulatory aids has emerged. Among such aids, hands-free crutches (HFCs) are of particular interest due to their form factor, which does not require the use of the hands and facilitates a bipedal gait. In this study, we present an assessment of whether any different gait patterns, compared to overground gait, appeared on the unaffected limb during walking with an HFC. The spatiotemporal parameters, plantar force, lower-limb joint angles, and EMG patterns were evaluated. In conclusion, the results from 10 healthy subjects suggest that wearing an HFC causes only slight changes in the biomechanical gait patterns examined in the unaffected limb compared with overground walking without an HFC.

The PIF4 transcription factor along with the phyB photoreceptor, regulates growth responses to elevated temperature in plants. Here the authors show that PIF4 expression in the epidermis, rather than the vasculature, stimulates auxin responses and thermoresponsive growth in Arabidopsis.

Current gait rehabilitation strategies rely heavily on motor learning principles, which involve facilitating active patient participation, high-doses of biomechanical task-related motor activities and accurate feedback. Furthermore, appropriate muscle groups need to be recruited for the joint movements that constitute the biomechanical task-related activities in order to effectively promote motor learning. Recently, exoskeleton-type robots utilizing crutches have been incorporated into overground gait rehabilitation programs. However, it is unclear which gait-related tasks are being trained because the joint movements and muscle recruitment patterns deviate from those of natural gait. This raises concerns because repetitive training with these devices may not lead to desirable rehabilitative gains. In this study, we compare the lower limb joint angles and electromyography patterns of healthy subjects walking with and without ReWalk in accordance with the three major biomechanical tasks required by bipedal gait: weight acceptance (WA), single-limb support, and limb advancement. Furthermore, we investigate whether the physical constraints of ReWalk, most noticeably the use of crutches and fixed ankle joints, were responsible for the specific changes by conducting additional walking sessions with either crutches or ankle foot orthoses. The results from the six healthy male volunteers suggest that the gait patterns observed with ReWalk deviate significantly from those of natural gait, particularly during the WA, and closely resemble those of crutch gait.

Plant endophyte and epiphyte communities cooperatively interact with their host plants and play crucial roles in sustaining plant fitness. In Korea, a variety of studies have been conducted to elucidate the reasons for the declining population of the endangered Korean fir (Abies koreana), but the relationship between microbiota and the healthy condition of trees remains unclear. Here, we conducted bacterial 16S rRNA gene and fungal ITS sequence analyses to dissect the composition of endophytic and epiphytic microbiota in both live and dead trees located in the same Mt. Jiri habitat. In the live trees, the bacterial class Armatimonadia and the lichenized fungi groups were significantly dominant, whereas many bacterial and fungal taxa mainly found in rotten wood were enriched in the dead trees. Functional prediction of the microbial communities in live trees suggested the possibility that bacterial endophytes and epiphytes play a role in inorganic nutrient metabolism and fungal endophytes and epiphytes produce biologically active secondary metabolites, thereby contributing to the healthy condition of Korean fir trees. The ecological function of endophytes and epiphytes in dead trees was predicted to be involved in the decomposition of wood for nutrient recycling. Our analyses revealed a distinct difference in microbial communities depending on the health condition of Korean fir trees. The results from this study would be useful for understanding the ecological function of endophytic and epiphytic microorganisms to conserve and manage this endangered species from ecologically vulnerable environments.

Black ice on the road can be dangerous, as it renders the road slippery and is difficult to identify, owing to its transparency. Although studies on black ice detection using cameras, optical sensors, and infrared sensors have been conducted, these sensors have limitations, as they are affected by low light conditions and sunlight. To detect black ice regardless of low light conditions or sunlight, in this study, we incorporate a mmWave sensor that is consistent with varying light conditions. In the proposed method, a frequency modulated continuous wave is transmitted to the surface by the mmWave sensor, and the mmWave sensor backscattering is modulated by the surface medium and roughness. The proposed method also includes preprocessing to calculate the Range-FFT result of the mmWave sensor backscattering and a classification based on a 1-dimensional convolutional neural network to precisely detect the presence of black ice from the Range-FFT result. As a result of the indoor experiment, the proposed black ice detection method achieves an accuracy of 98.2% on dry, wet, and black ice surfaces. Additionally, under low light conditions and in an outdoor environment with sunlight, the proposed method achieves accuracies of 95.6% and 98.5%, respectively.

High temperature is one of the most significant abiotic stresses reducing crop yield and quality by inhibiting plant growth and development. Global warming has recently increased the frequency of heat waves, which negatively impacts agricultural fields. Despite numerous studies on heat stress responses and signal transduction in model plant species, the molecular mechanism underlying thermomorphogenesis in Panax ginseng remains largely unknown. Here, we investigated the high temperature response of ginseng at the phenotypic and molecular levels. Both the primary shoot growth and secondary root growth of ginseng plants were significantly reduced at high temperature. Histological analysis revealed that these decreases in shoot and root growth were caused by decreases in cell elongation and cambium stem cell activity, respectively. Analysis of P. ginseng RNA-seq data revealed that heat-stress-repressed stem and root growth is closely related to changes in photosynthesis, cell wall organization, cell wall loosening, and abscisic acid (ABA) and jasmonic acid (JA) signaling. Reduction in both the light and dark reactions of photosynthesis resulted in defects in starch granule development in the storage parenchymal cells of the main tap root. Thus, by combining bioinformatics and histological analyses, we show that high temperature signaling pathways are integrated with crucial biological processes that repress stem and root growth in ginseng, providing novel insight into the heat stress response mechanism of P. ginseng.

Starch granules in the endodermis of plant hypocotyls act as statoliths that promote hypocotyl negative gravitropism—the directional growth of hypocotyls against gravity—in the dark. To identify the molecular components that regulate hypocotyl negative gravitropism, we performed a mutagenesis screen and isolated reduced gravitropic 1 (rgv1) mutants that lack starch granules in their hypocotyl endodermis and show reduced hypocotyl negative gravitropism in the dark. Using whole genome sequencing, we identified three different rgv1 mutants that are allelic to the previously reported early starvation 1 mutant, which is rapidly depleted of starch just before the dawn. ESV1 orthologs are present in starch-producing green organisms, suggesting ESV1 is a functionally conserved protein necessary for the formation of starch granules. Consistent with this, we found that liverwort and rice ESV1 can complement the Arabidopsis ESV1 mutant phenotype for both starch granules and hypocotyl negative gravitropism. To further investigate the function of ESV1 in other plants, we isolated rice ESV1 mutants and found that they show reduced levels of starch in their leaves and loosely packed starch granules in their grains. Both Arabidopsis and rice ESV1 mutants also lack starch granules in root columella and show reduced root gravitropism. Together, these results indicate ESV1 is a functionally conserved protein that promotes gravitropic responses in plants via its role in starch granule formation.

Agaricus bisporus is one of the world’s most popular edible mushrooms, including in South Korea. We performed de novo genome assembly with a South Korean white-colored cultivar of A. bisporus, KMCC00540. After generating a scaffold-level genomic sequence, we inferred chromosome-level assembly by genomic synteny analysis with the representative A. bisporus strains H97 and H39. The KMCC00540 genome had 13 pseudochromosomes comprising 33,030,236 bp mostly covering both strains. A comparative genomic analysis with cultivar H97 indicated that most genomic regions and annotated proteins were shared (over 90%), ensuring that our cultivar could be used as a representative genome. However, A. bisporus suffers from browning even from only a slight mechanical stimulus during transportation, which significantly lowers its commercial value. To identify which genes respond to a mechanical stimulus that induces browning, we performed a time-course transcriptome analysis based on the de novo assembled genome. Mechanical stimulus induces up-regulation in long fatty acid ligase activity-related genes, as well as melanin biosynthesis genes, especially at early time points. In summary, we assembled the chromosome-level genomic information on a Korean strain of A. bisporus and identified which genes respond to a mechanical stimulus, which provided key hints for improving the post-harvest biological control of A. bisporus.

An FDA-approved soft wearable robot, the Myosuit, which was designed to provide hip and knee extension torque has recently been commercialized. While studies have reported reductions in metabolic costs, increased gait speeds, and improvements in clinical test scores, a comprehensive analysis of electromyography (EMG) signals and joint kinematics is warranted because the recruitment of appropriate muscle groups during physiological movement patterns facilitates effective motor learning. Here, we compared the lower limb joint kinematics and EMG patterns while wearing the Myosuit with that of unassisted conditions when performing level overground and incline treadmill gait. The level overground gait sessions (seven healthy subjects) were performed at self-selected speeds and the incline treadmill gait sessions (four healthy subjects) were performed at 2, 3, 4, and 5 km/h. In order to evaluate how the user is assisted, we conducted a biomechanical analysis according to the three major gait tasks: weight acceptance (WA), single-limb support, and limb advancement. The results from the gait sessions suggest that Myosuit not only well preserves the users’ natural patterns, but more importantly reduce knee extensor demand during the WA phase for both level and incline gait.

In spite of remarkable progress in machine learning techniques, the state-of-the-art machine learning algorithms often keep machines from real-time learning (online learning) due, in part, to computational complexity in parameter optimization. As an alternative, a learning algorithm to train a memory in real time is proposed, named the Markov chain Hebbian learning algorithm. The algorithm pursues efficient use in memory during training in that: 1) the weight matrix has ternary elements (-1, 0, 1) and 2) each update follows a Markov chain-the upcoming update does not need past weight values. The algorithm was verified by two proof-of-concept tasks: image (MNIST and CIFAR-10 datasets) recognition and multiplication table memorization. Particularly, the latter bases multiplication arithmetic on memory, which may be analogous to humans' mental arithmetic. The memory-based multiplication arithmetic feasibly offers the basis of factorization, supporting novel insight into memory-based arithmetic.

Contact charge electrophoresis (CCEP) is an electrically controllable manipulation technique of conductive droplets and particles by charging and discharging when in contact with the electrode. Given its straightforward operation mechanism, low cost, and ease of system construction, it has gained traction as a versatile and potential strategy for the realistic establishment of lab-on-a-chip (LOC) in various engineering applications. We present a CCEP-based digital microfluidics (DMF) platform with two parallel electrode modules comprising assembled conventional pin header sockets, allowing for efficient mixing through horizontal and vertical shaking via droplet reciprocating motions. The temporal chromic change caused by the chemical reaction between the pH indicator and base solutions within the shaking droplets is quantitatively analyzed under various CCEP actuation conditions to evaluate the mixing performance in shaking droplets by vertical and horizontal reciprocating motions on the DMF platform. Furthermore, mixing flow patterns within shaking droplets are successfully visualized by a high-speed camera system. The suggested techniques can mix samples and reagents rapidly and efficiently in droplet-based microreactors for DMF applications, such as biochemical analysis and medical diagnostics.

Among many artificial neural networks, the research on Spike Neural Network (SNN), which mimics the energy-efficient signal system in the brain, is drawing much attention. Memristor is a promising candidate as a synaptic component for hardware implementation of SNN, but several non-ideal device properties are making it challengeable. In this work, we conducted an SNN simulation by adding a device model with a non-linear weight update to test the impact on SNN performance. We found that SNN has a strong tolerance for the device non-linearity and the network can keep the accuracy high if a device meets one of the two conditions: 1. symmetric LTP and LTD curves and 2. positive non-linearity factors for both LTP and LTD. The reason was analyzed in terms of the balance between network parameters as well as the variability of weight. The results are considered to be a piece of useful prior information for the future implementation of emerging device-based neuromorphic hardware.

Anthocyanins are generally accumulated within a few layers, including the epidermal cells of leaves and stems in plants. Solanum tuberosum cv. ‘Jayoung’ (hereafter, JY) is known to accumulate anthocyanin both in inner tissues and skins. We discovered that anthocyanin accumulation in the inner tissues of JY was almost diminished (more than 95% was decreased) in tuber induction condition. To investigate the transcriptomic mechanism of anthocyanin accumulation in JY flesh, which can be modulated by growth condition, we performed mRNA sequencing with white-colored flesh tissue of Solanum tuberosum cv. ‘Atlantic’ (hereafter, ‘Daeseo’, DS) grown under canonical growth conditions, a JY flesh sample grown under canonical growth conditions, and a JY flesh sample grown under tuber induction conditions. We could identify 36 common DEGs (differentially expressed genes) in JY flesh from canonical growth conditions that showed JY-specifically increased or decreased expression level. These genes were enriched with flavonoid biosynthetic process terms in GO analysis, as well as gene set enrichment analysis (GSEA) analysis. Further in silico analysis on expression levels of anthocyanin biosynthetic genes including rate-limiting genes such as StCHS and StCHI followed by RT-PCR and qRT-PCR analysis showed a strong positive correlation with the observed phenotypes. Finally, we identified StWRKY44 from 36 common DEGs as a possible regulator of anthocyanin accumulation, which was further supported by network analysis. In conclusion, we identified StWRKY44 as a putative regulator of tuber-induction-dependent anthocyanin accumulation.

The development of curative therapy for bladder dysfunction is usually hampered owing to the lack of reliable ex vivo human models that can mimic the complexity of the human bladder. To overcome this issue, 3D in vitro model systems offering unique opportunities to engineer realistic human tissues/organs have been developed. However, existing in vitro models still cannot entirely reflect the key structural and physiological characteristics of the native human bladder. In this study, we propose an in vitro model of the urinary bladder that can create 3D biomimetic tissue structures and dynamic microenvironments to replicate the smooth muscle functions of an actual human urinary bladder. In other words, the proposed biomimetic model system, developed using a 3D bioprinting approach, can recreate the physiological motion of the urinary bladder by incorporating decellularized extracellular matrix from the bladder tissue and introducing cyclic mechanical stimuli. The results showed that the developed bladder tissue models exhibited high cell viability and proliferation rate and promoted myogenic differentiation potential given dynamic mechanical cues. We envision the developed in vitro bladder mimicry model can serve as a research platform for fundamental studies on human disease modeling and pharmaceutical testing.

Charge-lattice coupling plays a central role in the exotic behaviors of multiferroic complex oxides, such as manganites, however, obtaining a microscopic picture is challenging. Here, Savitzky et al. map periodic lattice displacement fields at the picometer scale to study local order-disorder competition.

Abstract The toxicity of atmospheric-pressure pulsed plasma on plant leaf tissues is studied. A nanosecond-pulsed plasma jet is applied to Arabidopsis thaliana leaves. In case of cotyledon, cell death is induced by treatment of only a few seconds. Cell death is also induced in the adult leaf by only 5 seconds of plasma treatment. Plasma induced reactive oxygen species (ROS) accumulation across the tissues within plasma-treated area. Plasma also induced direct physical damage to epidermis tissue of treated area but merely no damage to mesophyll. Thus, we propose direct physical damage in epidermis and ROS accumulation across the treated area induced cell death by plasma treatment. Plasma treatment with same duration in different organ also induced ROS accumulation but not plant death, suggests damage on photosynthetic organ by oxidative stress might be direct reason to induce cell death. We could also observe similar plasma induced death in Solanum esculentum, Petunia axillaris, and Nicotiana benthamiana but death is induced only in treated area. Thus, we propose atmospheric plasma induce oxidative stress in photosynthetic organ to induce cell death in plants.

A synaptic device that contains weight information between two neurons is one of the essential components in a neuromorphic system, which needs highly linear and symmetric characteristics of weight update. In this study, a charge trap flash (CTF) memory device with a multilayered high-κ barrier oxide structure on the MoS2 channel is proposed. The fabricated device was oxide-engineered on the barrier oxide layers to achieve improved synaptic functions. A comparison study between two fabricated devices with different barrier oxide materials (Al2O3 and SiO2) suggests that a high-κ barrier oxide structure improves the synaptic operations by demonstrating the increased on/off ratio and symmetry of synaptic weight updates due to a better coupling ratio. Lastly, the fabricated device has demonstrated reliable potentiation and depression behaviors and spike-timing-dependent plasticity (STDP) for use in a spiking neural network (SNN) neuromorphic system.

Ca2+-triggered SNARE-mediated membrane fusion is essential for neuronal communication. The speed of this process is of particular importance because it sets a time limit to cognitive and physical activities. In this work, we expand the proteoliposome-to-supported bilayer (SBL) fusion assay by successfully incorporating synaptotagmin 1 (Syt1), a major Ca2+ sensor. We report that Syt1 and Ca2+ together can elicit more than a 50-fold increase in the number of membrane fusion events when compared with membrane fusion mediated by SNAREs only. What is remarkable is that ~55% of all vesicle fusion events occurs within 20 ms upon vesicle docking. Furthermore, pre-binding of Syt1 to SNAREs prior to Ca2+ inhibits spontaneous fusion, but intriguingly, this leads to a complete loss of the Ca2+ responsiveness. Thus, our results suggest that there is a productive and a non-productive pathway for Syt1, depending on whether there is a premature interaction between Syt1 and SNAREs. Our results show that Ca2+ binding to Syt1 prior to Syt1's binding to SNAREs may be a prerequisite for the productive pathway. The successful reconstitution of Syt1 activities in the physiological time scale provides new opportunities to test the current mechanistic models for Ca2+-triggered exocytosis.

Alzheimer’s disease (AD) is closely associated with synaptic dysfunction, and thus current treatments often aim to stimulate neurotransmission to improve cognitive impairment. Whereas the formation of the soluble N-ethylmaleimide-sensitive factor attachment protein receptor (SNARE) complex is essential for synaptic transmission, the correlation between SNAREs and AD neuropathology is unknown. Here, we report that intracellular amyloid-β (Aβ) oligomers directly inhibit SNARE-mediated exocytosis by impairing SNARE complex formation. We observe abnormal reduction of SNARE complex levels in the brains of APP/PS1 transgenic (TG) mice compared to age-matched wild-types. We demonstrate that Aβ oligomers block SNARE complex assembly through the direct interaction with a target membrane (t)-SNARE syntaxin 1a in vitro. Furthermore, the results of the in vitro single-vesicle content-mixing assay reveal that Aβ oligomers inhibit SNARE-mediated fusion pores. Thus, our study identifies a potential molecular mechanism by which intracellular Aβ oligomers hamper SNARE-mediated exocytosis, likely leading to AD-associated synaptic dysfunctions.

We report the coexistence of ferroelectricity and a spin liquid state in hexagonal TbInO_{3} with quasi-two-dimensional triangular spin lattice. Geometrical ferroelectricity associated with In trimerization accompanies topological ferroelectric structural defects. Magnetic susceptibility data show in-plane magnetic anisotropy of Tb spins without any long-range order above 1.8 K, and we also confirm no trace of any phase transition down to 0.15 K from a specific heat measurement, which indicates that this system is highly frustrated and may host a spin liquid ground state. By analyzing the Schottky anomaly in the specific heat results, we propose a model where crystal-field levels are different in each Tb sites, and only one of them has a magnetic ground state and forms a unique honeycomb spin lattice. These observations put forward an interesting possibility where spin liquid and ferroelectric behaviors coexist, and the atomically sharp ferroelectric domain walls may host new magnetic edge states or local spin excitations.