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Developing covalent organic frameworks (COFs) with good electrical conductivity is essential to widen their range of practical applications. Thermal annealing is known to be a facile approach for enhancing conductivity. However, at higher temperatures, most COFs undergo amorphization and/or thermal degradation because of the lack of linker rigidity and physicochemical stability. Here, we report the synthesis of a conductive benzoxazole-linked COF/carbon hybrid material (BCOF-600C) by simple thermal annealing. The fused-aromatic benzoxazole and biphenyl building units endow the resulting COF with excellent physicochemical stability against high temperatures and strong acids/bases. This allows heat treatment to further enhance electrical conductivity with minimal structural alteration. The robust crystalline structure with periodically incorporated nitrogen atoms allowed platinum (Pt) atoms to be atomically integrated into the channel walls of BCOF-600C. The resulting electrocatalyst with well-defined active sites exhibited superior catalytic performance toward hydrogen evolution in acidic media.

SummaryDue to the enhanced labeling capability of maleimide-based fluorescent probes, lysine-cysteine-lysine (KCK) tags are frequently added to proteins for visualization. In this study, we employedin vitrosingle-molecule DNA flow-stretching assay as a sensitive way to assess the impact of the KCK-tag on the property of DNA-binding proteins. UsingBacillus subtilisParB as an example, we show that, although no noticeable changes were detected byin vivofluorescence imaging and chromatin immunoprecipitation (ChIP) assays, the KCK-tag substantially altered ParB’s DNA compaction rates, its response to nucleotide binding and to the presence of the specific sequence (parS) on the DNA. While it is typically assumed that short peptide tags minimally perturb protein function, our results urge researchers to carefully validate the use of tags for protein labeling. Our comprehensive analysis can be expanded and used as a guide to assess the impacts of other tags on DNA-binding proteins in single-molecule assays.MotivationSingle-molecule fluorescence microscopy has been extensively used in modern biology to define the molecular action of proteins. Appending short peptide tags is a common strategy to enhance fluorescence labeling. In this Resources article, we evaluate the impact of a commonly used tag, the lysine-cysteine-lysine (KCK) tag, on protein behavior in single-molecule DNA flow-stretching assay, which is a sensitive and versatile method to understand the action of DNA-binding proteins. Our motivation is to provide researchers with an experimental framework to validate the fluorescently labeled DNA-binding proteins in single-molecule methods.

Simulation-based reinforcement learning approaches are leading the next innovations in legged robot control. However, the resulting control policies are still not applicable on soft and deformable terrains, especially at high speed. The primary reason is that reinforcement learning approaches, in general, are not effective beyond the data distribution: The agent cannot perform well in environments that it has not experienced. To this end, we introduce a versatile and computationally efficient granular media model for reinforcement learning. Our model can be parameterized to represent diverse types of terrain from very soft beach sand to hard asphalt. In addition, we introduce an adaptive control architecture that can implicitly identify the terrain properties as the robot feels the terrain. The identified parameters are then used to boost the locomotion performance of the legged robot. We applied our techniques to the Raibo robot, a dynamic quadrupedal robot developed in-house. The trained networks demonstrated high-speed locomotion capabilities on deformable terrains: The robot was able to run on soft beach sand at 3.03 meters per second although the feet were completely buried in the sand during the stance phase. We also demonstrate its ability to generalize to different terrains by presenting running experiments on vinyl tile flooring, athletic track, grass, and a soft air mattress.

Multispectral pedestrian detection has been actively studied as a promising multi-modality solution to handle illumination and weather changes. Most multi-modality approaches carry the assumption that all inputs are fully-overlapped. However, these kinds of data pairs are not common in practical applications due to the complexity of the existing sensor configuration. In this letter, we tackle multispectral pedestrian detection, where all input data are not paired. To this end, we propose a novel single-stage detection framework that leverages multi-label learning to learn input state-aware features by assigning a separate label according to the given state of the input image pair. We also present a novel augmentation strategy by applying geometric transformations to synthesize the unpaired multispectral images. In extensive experiments, we demonstrate the efficacy of the proposed method under various real-world conditions, such as fully-overlapped images and partially-overlapped images, in stereo-vision. Code and a demonstration video are available at https://github.com/sejong-rcv/MLPD-Multi-Label-Pedestrian-Detection .

This study focuses on the applicability of single-atom Mo-doped graphitic carbon nitride (GCN) nanosheets which are specifically engineered with high surface area (exfoliated GCN), NH

Parkinson's disease (PD) is a progressive neurodegenerative disorder that affects movement. The nonreceptor tyrosine kinase c-Abl has shown a potential role in the progression of PD. As such, c-Abl inhibition is a promising candidate for neuroprotection in PD and α-synucleinopathies. Compound 5 is a newly synthesized blood-brain barrier penetrant c-Abl inhibitor with higher efficacy than existing inhibitors. The objective of the current study was to demonstrate the neuroprotective effects of compound 5 on the α-synuclein preformed fibril (α-syn PFF) mouse model of PD. Compound 5 significantly reduced neurotoxicity, activation of c-Abl, and Lewy body pathology caused by α-syn PFF in cortical neurons. Additionally, compound 5 markedly ameliorated the loss of dopaminergic neurons, c-Abl activation, Lewy body pathology, neuroinflammatory responses, and behavioral deficits induced by α-syn PFF injection in vivo. Taken together, these results suggest that compound 5 could be a pharmaceutical agent to prevent the progression of PD and α-synucleinopathies.

Ensuring interfacial stability of Si-containing anodes and Ni-rich cathodes is the key to achieving high-energy lithium-ion cells. Herein, we present 4-(allyloxy)phenyl fluorosulfate (APFS), a multi-functional electrolyte additive that forms a mechanical strain-adaptive solid electrolyte interphase (SEI) composed of LiF and polymeric species, and a thermally stable cathode–electrolyte interface containing S–O and S–F species. Radical copolymerization of vinylene carbonate (VC) with APFS via electrochemical initiation creates a spatially deformable polymeric SEI on the Si/C-graphite (SiG-C) anode with large volume changes during cycling. Here we show that APFS-promoted interfacial layers reduce Ni dissolution and deposition and that APFS deactivates Lewis acidic PF5, inhibiting the hydrolysis that produces unwanted HF. These results show that the combined use of VC and APFS allows capacity retention of 72.5% with a high capacity of 143.5 mAh g− 1 after 300 cycles at 45°C.

We examine whether corporate bankruptcy predictions can be improved by utilizing the recurrent neural network (RNN) and long short-term memory (LSTM) algorithms, which can process sequential data. Employing the RNN and LSTM methodologies improves bankruptcy prediction performance relative to using other classification techniques, such as logistic regression, support vector machine, and random forest methods. Because performance indicators, such as sensitivity and specificity, differ depending on the methodology, selecting a model that suits the purpose of the bankruptcy predictions is necessary. Our ensemble model, a synthesis of all methodologies, exhibits the best forecasting performance. In the test sample for the ensemble model, none of the observations with a default probability of less than 10% defaults within one year.

The patterning of poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS) hydrogels with excellent electrical property and spatial resolution is a challenge for bioelectronic applications. However, most PEDOT:PSS hydrogels are fabricated by conventional manufacturing processes such as photolithography, inkjet printing, and screen printing with complex fabrication steps or low spatial resolution. Moreover, the additives used for fabricating PEDOT:PSS hydrogels are mostly cytotoxic, thus requiring days of detoxification. Here, we developed a previously unexplored ultrafast and biocompatible digital patterning process for PEDOT:PSS hydrogel via phase separation induced by a laser. We enhanced the electrical properties and aqueous stability of PEDOT:PSS by selective laser scanning, which allowed the transformation of PEDOT:PSS into water-stable hydrogels. PEDOT:PSS hydrogels showed high electrical conductivity of 670 S/cm with 6-μm resolution in water. Furthermore, electrochemical properties were maintained even after 6 months in a physiological environment. We further demonstrated stable neural signal recording and stimulation with hydrogel electrodes fabricated by laser.

Due to the advantage that a thermal camera robustly works in various illumination conditions, it has become a crucial sensor in real-world applications, such as self-driving, advanced driver assistance as well as a surveillance system. However, unlike RGB images with color information, thermal images do not contain abundant information. This disadvantage makes it users difficult to recognize thermal scenes. In this paper, we aim to make pseudo-RGB that can be used at day and night by receiving thermal images as inputs and to show the necessity of pseudo-RGB research through colorization that synthesizes chromaticity of RGB in thermal images. Furthermore, we evaluate models to see whether the produced colorized image can be interpreted by perceptual models for tasks, such as pedestrian detection and depth estimation by feeding colorized images to the models that are trained with original RGB images. These experiments explicitly show the limitation and possibility of thermal colorization.

This study examines the time‐series momentum in China's commodity futures market. We find that a time‐series momentum strategy outperforms classical passive long and cross‐sectional momentum strategies in terms of the Sharpe ratio, risk‐adjusted excess returns, and cumulative returns. The time‐series momentum strategy with a 1‐month look‐back period and a 1‐month holding period exhibits the best performance. We observe clear time‐series momentum patterns and find that the time‐series momentum strategy is effective in the Chinese commodity futures market. However, the momentum lasts for less time in China than in the United States because China's futures market seems to have a greater number of speculative investors.

A construction surety bond helps a development project to proceed smoothly. This financial product has supported the rapid economic growth of several emerging markets, including the Republic of Korea. In this study, by using a unique and high-quality dataset, the authors analyze construction surety bonds to estimate their default probabilities. The results have several empirical implications. First, firm characteristics, such as firm size and leverage ratio, influence the surety bond default risk; the safety and liquidity measure are especially robust indicators. The result also confirms that account receivables can increase the default risk. Second, endogenous variables of the surety bond are also robust indicators of default. Because a construction surety bond itself has additional information about a company starting a new construction project, those variables can contribute to indicating default risk. Finally, default forecasting based on this model has much greater forecasting power than models based on the credit rating. TOPICS:Project finance, statistical methods, credit risk management, emerging markets

Despite their simple formulations, advection upstream splitting method (AUSM)-type flux schemes treat linear and nonlinear waves of complex flow fields in a robust and accurate manner. This paper presents the progress of AUSM-type fluxes augmented with pressure-based weight functions introduced by the authors and their colleagues. Starting from a flux designed for single-phase gas dynamics (AUSMPW+), its extensions to capture multi-phase flow physics with phase transition (AUSMPW+_N) have been carried out. The accuracy of the computed results by the AUSMPW+_N scheme for multi-phase flows is then further improved by introducing a simple phase interface-sharpening procedure, which scales the volume fraction in a mass-conserving manner. Various all-speed compressible tests ranging from interactions between a shock and phase interfaces, two- and three-dimensional interface-only problems, to a cryogenic three-component flow with phase change are computed to demonstrate the effectiveness of the proposed method.

Plant disease detection is essential for optimizing agricultural productivity and crop quality. With the recent advent of deep learning and large-scale plant disease datasets, many studies have shown high performance of supervised learning-based plant disease detectors. However, these studies still have limitations due to two aspects. First, labeling cost and class imbalance problems remain challenging in supervised learning-based methods. Second, plant disease datasets are either unstructured or weakly-unstructured and the shapes of leaves and diseased areas on them are variable, rendering plant disease detection even more challenging. To overcome these limitations, we propose an instance-aware unsupervised plant disease detector, which leverages normalizing flows, a visual saliency map and positional encodings. A novel way to explicitly combine these methods is the proposed model, in which the focus is on reducing background noise. In addition, to better fit the model to the plant disease detection domain and to enhance feature representation, a feature extractor is pre-trained in a self-supervised learning manner using only unlabeled data. In our extensive experiments, it is shown that the proposed approach achieves state-of-the-art performance on widely-used datasets, such as BRACOL (Weakly-unstructured) and PlantVillage (Unstructured), regardless of whether the dataset is weakly-structured or unstructured.

Following the Basel II convention, consumer credit default is commonly defined as delinquency beyond a period of 90 days. In this study, rather than considering default as a binary variable, we dissect delinquency states further to investigate default behavior in greater detail. As such, we define three states—no delinquency, delinquency and serious delinquency—and estimate the probabilities of the transitions between states using extensive panel data from Korea, covering a wide range of behavioral information. Our findings have several economic implications. First, the factors that affect delinquency risk can differ from those that affect the transition from delinquency to serious delinquency. Second, the recent increase in the number of seriously delinquent accounts can be attributed to changes in the borrower age distribution. Third, macroeconomic conditions, especially differences in gross domestic product and consumption growth, have led to the recent increase in delinquent accounts. Fourth, the debt-to-income (DTI) ratio has a profound effect on transitions between delinquency states and thus affects both recovery and delinquency. Furthermore, this result is robust to controls for demographic and macroeconomic factors.

Computations of all-speed multiphase real fluid flows for aerospace launch vehicles are known to be very demanding, owing to several issues that include robust capturing of two-phase shock/phase di...

This paper focuses on the limitations of single-phase computations which have been widely applied to the numerical simulations of flow fields around thermal vapor compressors (TVCs), and provides computational improvements through multi-phase flow modeling and analysis. In order to capture the multi-phase flow physics accurately and provide reliable results, several numerical methods and models, including the shock-stable multi-phase AUSMPW+ scheme, phase-changing models, cell-by-cell adaptive mesh refinement technique, and the IAPWS-97 equation of states, are combined into a numerical solver. We then simulate various TVC systems and compare the computed system performance and local flow physics between the single- and multi-phase computations. Based on the computational results and comparisons, we examine phase-changing process and its influence on two major local physical features, namely shock-train region and shear layer.

Understanding mortgage termination behavior is crucial for valuating mortgage-backed securities. Analyzing a unique loan-level dataset, this study examines the characteristics of mortgage prepayment and default behaviors in the Korean housing and housing finance markets. We also analyze mortgage termination behaviors across regions, loan purposes, and periods. The results suggest that the prepayment rate of fixed-rate mortgages (FRMs) and the ratio of adjustable-rate mortgages to FRMs can provide meaningful signals for the Korean household economy. Although the macro-prudential policies pertaining to the loan-to-value ratio (LTV) and debt-to-income ratio (DTI) are very effective, their effects can vary depending on the region or loan purpose. Furthermore, the DTI and credit score cannot always identify the default risks of mortgages not intended for housing purchases even though such mortgages are more vulnerable to macroeconomic changes. The observed changes in default behavior indicate that the government’s policies to promote fixed-rate loans have achieved a certain degree of success.

Nucleoid-associated proteins bind to DNA specifically and nonspecifically to perform various roles in chromosome organization and segregation. In this chapter, we describe how the interaction between nucleoid-associated proteins and flow-stretched DNAs can be visualized on the single-molecule level. We describe three different experimental schemes that allow one to directly observe how these proteins that make up bacterial chromatin, associate with and act on DNAs. First, we describe how to visualize the diffusion of fluorescently labeled proteins on flow stretched DNAs. Second, we describe how the binding of bacterial chromatin proteins can be correlated with DNA condensation. Lastly, we describe the DNA motion capture assay, which allows one to probe the mechanism of DNA condensation by tracking how different segments of a flow stretched DNA are compacted by bacterial chromatin proteins.

Nucleoid-associated proteins bind to DNA specifically and nonspecifically to perform various roles in chromosome organization and segregation. In this chapter, we describe how the interaction between nucleoid-associated proteins and flow-stretched DNAs can be visualized on the single-molecule level. We describe three different experimental schemes that allow one to directly observe how these proteins that make up bacterial chromatin, associate with and act on DNAs. First, we describe how to visualize the diffusion of fluorescently labeled proteins on flow stretched DNAs. Second, we describe how the binding of bacterial chromatin proteins can be correlated with DNA condensation. Lastly, we describe the DNA motion capture assay, which allows one to probe the mechanism of DNA condensation by tracking how different segments of a flow stretched DNA are compacted by bacterial chromatin proteins.

Summary Microrchidia (MORC) ATPases are critical for gene silencing and chromatin compaction in multiple eukaryotic systems, but the mechanisms by which MORC proteins act are poorly understood. Here, we apply a series of biochemical, single-molecule, and cell-based imaging approaches to better understand the function of the Caenorhabditis elegans MORC-1 protein. We find that MORC-1 binds to DNA in a length-dependent but sequence non-specific manner and compacts DNA by forming DNA loops. MORC-1 molecules diffuse along DNA but become static as they grow into foci that are topologically entrapped on DNA. Consistent with the observed MORC-1 multimeric assemblies, MORC-1 forms nuclear puncta in cells and can also form phase-separated droplets in vitro. We also demonstrate that MORC-1 compacts nucleosome templates. These results suggest that MORCs affect genome structure and gene silencing by forming multimeric assemblages to topologically entrap and progressively loop and compact chromatin.

Hematopoietic progenitor kinase 1 (HPK1, MAP4K1) is a serine/threonine kinase and a member of MAP4K. HPK1 is prominently expressed in subsets of hematopoietic cell lineages. HPK1 is a newly identified as a critical negative regulator in the activation of T lymphocytes and dendritic cells. It has been recently demonstrated that the important roles for kinase activity of HPK1 in anti-cancer immunity as a new intracellular checkpoint molecule as well as potential advantages of combination therapy with current checkpoint regimens. HPK1 inhibition is expected to have dual functions, 1. prolonged activation of T cells; 2. enhanced APC functions by dendritic cells. This dual targeting may synergistically work together for efficient immune responses in tumor microenvironment. We have developed a series of small molecule inhibitors of HPK1 with a lead compound of CMPD0431, which are orally available with good physicochemical and pharmacokinetic profiles. CMPD0431 and its series demonstrated good potency for HPK1 with kinase IC50 values of ~20 nM or under. Treatment of T cells with CMPD0431 successfully blocked serine 376 phosphorylation of SLP76, a critical biomarker substrate for HPK1 and also for downstream signaling in T cell activation, leading to sustained activation in human T cells. CMPD0431 was shown to increase the CD3/CD28-induced proliferation of human primary T cells with enhanced production of pro-inflammatory cytokines such as IFN-γ and IL-2. Furthermore, CMPD0431 enhanced the functional activity of antigen presentation with increased level of pro-inflammatory cytokine productions in mouse bone marrow-derived dendritic cells. All together, we have confirmed that HPK1 inhibition indeed play a dual function in T cells and dendritic cells to effectively promote cancer immunity. In the CT-26 syngeneic mouse model, we showed that CMPD0431 inhibited tumor growth with increased intratumoral infiltration of CD3+ lymphocytes and with increased pro-inflammatory cytokine production, demonstrating promoted cancer immunity with a potential for conversion of cold tumor into hot tumor. A subset of mice with high dose treatment of CMPD0431 showed a tumor regression with no further tumor regrowth for 20 days without compound treatment. The cured mouse group did not grow tumor even after re-challenging with CT-26 without compound treatment, demonstrating the effective immunological memory by CMPD0431. Those immune memory mouse group displayed increased secretion of IFN-γ by splenic T lymphocytes with enhanced response to the stimulation by CT-26 specific antigen, AH1 peptide. All together, these results support further development of CMPD0431 and its derivatives, first-in-class and advanced leads of HPK1 inhibitors with novel mechanism of action to be applied as a single-agent or combinational therapy with the current checkpoint inhibitors. Citation Format: Seungmook Lim, A Yeong Park, Misoon Kim, Gyooseung Jung, Suyeon Jo, Keonseung Lim, Gwibin Lee, Heekyoung Yang, Hyonam Kim, Hyeongjun Kim, Minwoo Lee, Jamie Jae Eun Kim, Jinhwa Lee. An HPK1 inhibitor CMPD0431 is a novel immuno-oncology agent that induces anti-tumor effects [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4150.

SMC (structural maintenance of chromosomes) family members play essential roles in chromosome condensation, sister chromatid cohesion, and DNA repair. Despite intensive efforts, it is still unclear how SMCs are loaded onto DNA and structure chromosomes. We employed single-molecule fluorescence microscopy to visualize how individual Bacillus subtilis SMC (BsSMC) dimers interact with flow-stretched DNAs. We find that BsSMC can vary its initial interaction with DNA, switching between static binding and sliding. Its diffusive properties are insensitive to the presence of ATP, suggesting that the initial loading of BsSMC onto DNA is ATP-independent. At higher concentrations, BsSMCs form distinct clusters that condense DNA by both wrapping and bridging distal DNA segments. SMC-mediated DNA compaction occurs in a weakly ATP-dependent manner. However, ATP increases the apparent cooperativity of DNA condensation, demonstrating that multiple BsSMCs can interact cooperatively through their ATPase head domains. Consistent with these results, BsSMC mutants that alter the ATPase cycle compact DNA more slowly than wild-type BsSMC in the presence of ATP, and an ATPase headless construct compacts DNA non-cooperatively with substantially lower compaction rate. Our results suggest that transiently static BsSMC can nucleate the formation of functionally active clusters that locally condense the chromosome while forming long-range DNA bridges.

SMC (structural maintenance of chromosomes) family members play essential roles in chromosome condensation, sister chromatid cohesion and DNA repair. It remains unclear how SMCs structure chromosomes and how their mechanochemical cycle regulates their interactions with DNA. Here we used single-molecule fluorescence microscopy to visualize how Bacillus subtilis SMC (BsSMC) interacts with flow-stretched DNAs. We report that BsSMC can slide on DNA, switching between static binding and diffusion. At higher concentrations, BsSMCs form clusters that condense DNA in a weakly ATP-dependent manner. ATP increases the apparent cooperativity of DNA condensation, demonstrating that BsSMC can interact cooperatively through their ATPase head domains. Consistent with these results, ATPase mutants compact DNA more slowly than wild-type BsSMC in the presence of ATP. Our results suggest that transiently static BsSMC molecules can nucleate the formation of clusters that act to locally condense the chromosome while forming long-range DNA bridges., The Structural Maintenance of Chromosomes (SMC) proteins are essential for chromosome condensation, cohesion and DNA repair. Here the authors use single molecule imaging to visualise how Bacillus subtilis SMC interacts with and condenses DNA.

The design of curved I-girders is complicated because of the many performance stages that must be evaluated, including erection, construction, and in service. Evaluation of girder stability during early stages of construction is particularly complicated because of the limited presence of bracing. In addition to stability issues during girder lifting, guidelines for the necessity of shore towers during erection are not available. The Texas Department of Transportation funded a research project to investigate girder stability during early stages of construction. Results from this project will be used to develop guidelines for evaluating girder stability during early construction stages as well as to proportion the girder cross sections for safe and economic construction. The research includes field monitoring, a parametric study using finite element analysis (FEA), and development of user-friendly finite element analytic software that will serve as a tool for designers. This paper summarizes the development of an analysis tool as part of the UT Bridge research project, which provides engineers with a three-dimensional FEA of plate girder bridges during erection and concrete deck placement. The software provides a user-friendly preprocessor to guide input and a three-dimensional visual postprocessor output. UT Bridge performs a linear elastic or eigenvalue buckling analysis for a curved or straight bridge's defined construction procedure and is available free from the website of the University of Texas at Austin Ferguson Structural Engineering Laboratory.

We simultaneously measure both the step size, via FIONA, and the 3-D orientation, via DOPI, of the light-chain domain of individual dimeric myosin VIs. This allows for the correlation of the change in orientation of the light chain domain to the stepping of the motor. Three different pairs of positions were tested using a rigid bifunctional rhodamine on the calmodulin of the IQ domain. The data for all three labeling positions support the model that the light chain domain undergoes a significant rotation of approximately 180°. Contrary to an earlier study [Sun, Y. et al. (2007) Mol Cell 28, 954–964], our data does not support a model of multiple angles of the lever arm of the lead head, nor “wiggly” walking on actin. Instead, we propose that for the two heads of myosin VI to coordinate their processive movement, the lever arm of the lead head must be uncoupled from the converter until the rear head detaches. More specifically, intramolecular strain causes the myosin VI lever arm of the lead head to uncouple from the motor domain, allowing the motor domain to go through its product-release (phosphate and ADP) steps at an unstrained rate. The lever arm of the lead head rebinds to the motor and attains a rigor conformation when the rear head detaches. By coupling the orientation and position information with previously described kinetics, this allows us to explain how myosin VI coordinates its heads processively while maintaining the ability to move under load with a (semi-) rigid lever arm.

Myosin VI challenges the prevailing theory of how myosin motors move on actin: the lever arm hypothesis. While the reverse directionality and large powerstroke of myosin VI can be attributed to unusual properties of a subdomain of the motor (converter with a unique insert), these adaptations cannot account for the large step size on actin. Either the lever arm hypothesis needs modification, or myosin VI has some unique form of extension of its lever arm. We determined the structure of the region immediately distal to the lever arm of the motor and show that it is a three-helix bundle. Based on C-terminal truncations that display the normal range of step sizes on actin, CD, fluorescence studies, and a partial deletion of the bundle, we demonstrate that this bundle unfolds upon dimerization of two myosin VI monomers. This unconventional mechanism generates an extension of the lever arm of myosin VI.

Digital magnetoresistance (MR) properties of the sheet and patterned NiFeCo/Cu/Co spin-valve trilayer films were characterized. As reported in our previous publication, NiFeCo/Cu/Co films showed strong in-plane uniaxial magnetic anisotropy on a special template, 4/spl deg/tilt-cut Si(111) wafer with a 50 /spl Aring/ of Cu underlayer, without any externally applied magnetic field during the deposition. In order to demonstrate the industrial applicability of NiFeCo/Cu/Co films on the specific templates for digital MR devices, dynamic and static MR measurements were performed along the easy axis of the films. For dynamic MR measurement, NiFeCo/Cu/Co films were optimized with respect to Cu spacer thickness and patterned into a stripe of high aspect ratio of 1: 200 (height: width) where the easy aids of the film was aligned along the height direction. After patterning, uniaxial magnetic anisotropy was maintained, and MR properties showed no appreciable degradation. Therefore, it was believed that the special template is effective for the uniaxial magnetic anisotropy of NiFeCo/Cu/Co films and useful in the industrial applications. MR properties of sheet and patterned trilayer films suggest that these NiFeCo/Cu/Co spin valves on the specific templates are good candidates for digital MR devices such as magnetoresistive random access memory (MRAM).