Japan Advanced Institute of Science and Technology

Covalent organic frameworks (COFs) are a class of crystalline porous organic polymers with permanent porosity and highly ordered structures. Unlike other polymers, a significant feature of COFs is that they are structurally predesignable, synthetically controllable, and functionally manageable. In principle, the topological design diagram offers geometric guidance for the structural tiling of extended porous polygons, and the polycondensation reactions provide synthetic ways to construct the predesigned primary and high-order structures. Progress over the past decade in the chemistry of these two aspects undoubtedly established the base of the COF field. By virtue of the availability of organic units and the diversity of topologies and linkages, COFs have emerged as a new field of organic materials that offer a powerful molecular platform for complex structural design and tailor-made functional development. Here we target a comprehensive review of the COF field, provide a historic overview of the chemistry of the COF field, survey the advances in the topology design and synthetic reactions, illustrate the structural features and diversities, scrutinize the development and potential of various functions through elucidating structure-function correlations based on interactions with photons, electrons, holes, spins, ions, and molecules, discuss the key fundamental and challenging issues that need to be addressed, and predict the future directions from chemistry, physics, and materials perspectives.

The discovery of the enhancement of Raman scattering by molecules adsorbed on nanostructured metal surfaces is a landmark in the history of spectroscopic and analytical techniques. Significant experimental and theoretical effort has been directed toward understanding the surface-enhanced Raman scattering (SERS) effect and demonstrating its potential in various types of ultrasensitive sensing applications in a wide variety of fields. In the 45 years since its discovery, SERS has blossomed into a rich area of research and technology, but additional efforts are still needed before it can be routinely used analytically and in commercial products. In this Review, prominent authors from around the world joined together to summarize the state of the art in understanding and using SERS and to predict what can be expected in the near future in terms of research, applications, and technological development. This Review is dedicated to SERS pioneer and our coauthor, the late Prof. Richard Van Duyne, whom we lost during the preparation of this article.

As the Si counterpart of graphene, silicene may be defined as an at least partially sp2-hybridized, atom-thick honeycomb layer of Si that possesses π-electronic bands. Here we show that two-dimensional, epitaxial silicene forms through surface segregation on zirconium diboride thin films grown on Si wafers. A particular buckling of silicene induced by the epitaxial relationship with the diboride surface leads to a direct π-electronic band gap at the Γ point. These results demonstrate that the buckling and thus the electronic properties of silicene are modified by epitaxial strain.

Using the first-principles calculations, we explore the electronic structures of 2H-$M{X}_{2}$ ($M$ $=$ Mo, W; $X$ $=$ S, Se, Te). When the number of layers reduces to a single layer, the indirect gap of bulk becomes a direct gap with larger gap and the band curvatures are found to lead to the drastic changes of effective masses. On the other hand, when the strain is applied on the single layer, the direct gap becomes an indirect gap and the effective masses vary. Especially, the tensile strain reduces the gap energy and effective masses while the compressive strain enhances them. Furthermore, the much larger tensile stress leads to become metallic.

Conjugated covalent networks Although graphene and related materials are two-dimensional (2D) fully conjugated networks, similar covalent organic frameworks (COFs) could offer tailored electronic and magnetic properties. Jin et al. synthesized a fully π-conjugated COF through condensation reactions of tetrakis(4-formylphenyl)pyrene and 1,4-phenylenediacetonitrile. The reactions were reversible, which provides the self-healing needed to form a crystalline material of stacked, π-bonded 2D sheets. Chemical oxidation of this semiconductor with iodine greatly enhanced its conductivity, and the radicals formed on the pyrene centers imparted a high spin density and paramagnetism. Science , this issue p. 673

This paper is a part of our attempt to build a new knowledge-based theory of the firm and organization to explain the dynamic process of knowledge creation and utilization. For this, we revisit the theory of knowledge creation through the SECI process and ba, and try to advance them further by incorporating the dialectic thinking. In this paper, knowledge creation is conceptualized as a dialectical process, in which various contradictions are synthesized through dynamic interactions among individuals, the organization, and the environment. With the view of a firm as a dialectic being, and strategy and organization should be re-examined as the synthesizing and self-transcending process instead of a logical analysis of structure or action. An organization is not an information-processing machine that is composed of small tasks to carry out a given task, but an organic configuration of ba. Ba, which is conceptualized as a shared context in motion, can transcend time, space, and organization boundaries to create knowledge.

The knowledge-based view of the firm views a firm as a knowledge-creating entity, and argues that knowledge and the capability to create and utilize such knowledge are the most important source of a firm's sustainable competitive advantage. Knowledge and skills give a firm a competitive advantage because it is through this set of knowledge and skills that a firm is able to innovate new products/processes/services, or improve existing ones more efficiently and/or effectively. The raison d'être of a firm is to continuously create knowledge.

BACKGROUND: As more and more researchers are turning to big data for new opportunities of biomedical discoveries, machine learning models, as the backbone of big data analysis, are mentioned more often in biomedical journals. However, owing to the inherent complexity of machine learning methods, they are prone to misuse. Because of the flexibility in specifying machine learning models, the results are often insufficiently reported in research articles, hindering reliable assessment of model validity and consistent interpretation of model outputs. OBJECTIVE: To attain a set of guidelines on the use of machine learning predictive models within clinical settings to make sure the models are correctly applied and sufficiently reported so that true discoveries can be distinguished from random coincidence. METHODS: A multidisciplinary panel of machine learning experts, clinicians, and traditional statisticians were interviewed, using an iterative process in accordance with the Delphi method. RESULTS: The process produced a set of guidelines that consists of (1) a list of reporting items to be included in a research article and (2) a set of practical sequential steps for developing predictive models. CONCLUSIONS: A set of guidelines was generated to enable correct application of machine learning models and consistent reporting of model specifications and results in biomedical research. We believe that such guidelines will accelerate the adoption of big data analysis, particularly with machine learning methods, in the biomedical research community.

This paper is a part of our attempt to build a new knowledge-based theory of the firm and organization to explain the dynamic process of knowledge creation and utilization. For this, we revisit the theory of knowledge creation through the SECI process and ba, and try to advance them further by incorporating the dialectic thinking. In this paper, knowledge creation is conceptualized as a dialectical process, in which various contradictions are synthesized through dynamic interactions among individuals, the organization, and the environment. With the view of a firm as a dialectic being, and strategy and organization should be re-examined as the synthesizing and self-transcending process instead of a logical analysis of structure or action. An organization is not an information-processing machine that is composed of small tasks to carry out a given task, but an organic configuration of ba. Ba, which is conceptualized as a shared context in motion, can transcend time, space, and organization boundaries to create knowledge.

Remarkable room-temperature ferromagnetism was observed in undoped $\mathrm{Ti}{\mathrm{O}}_{2}$, $\mathrm{Hf}{\mathrm{O}}_{2}$, and ${\mathrm{In}}_{2}{\mathrm{O}}_{3}$ thin films. The magnetic moment is rather modest in the case of ${\mathrm{In}}_{2}{\mathrm{O}}_{3}$ films on MgO substrates (while on ${\mathrm{Al}}_{2}{\mathrm{O}}_{3}$ substrates, it is negative showing diamagnetism) when the magnetic field was applied parallel to the film plane. In contrast, it is very large in the other two cases (about 20 and $30\phantom{\rule{0.3em}{0ex}}\mathrm{emu}∕{\mathrm{cm}}^{3}$ for $200\text{\ensuremath{-}}\mathrm{nm}$-thick $\mathrm{Ti}{\mathrm{O}}_{2}$ and $\mathrm{Hf}{\mathrm{O}}_{2}$ films, respectively). Since bulk $\mathrm{Ti}{\mathrm{O}}_{2}$, $\mathrm{Hf}{\mathrm{O}}_{2}$, and ${\mathrm{In}}_{2}{\mathrm{O}}_{3}$ are clearly diamagnetic, and moreover, there are no contaminations in any substrate, we must assume that the thin film form, which might create necessary defects or oxygen vacancies, would be the reason for undoped semiconducting or insulating oxides to become ferromagnetic at room temperature.

The mean diameter of monodispersed Pd nanoparticles could be controlled from 17 to 30 Å in a one-step reaction by changing the amount of protective polymer, poly(N-vinyl-2-pyrrolidone) (PVP) and the kind and/or the concentration of alcohol in the solvent. Although increasing the amount of protective polymer made the size of Pd nanoparticles smaller, the particle size appeared to have a lower limit determined by the kind of alcohol. On the other hand, monodispersed Pd nanoparticles of smaller diameter were obtained in the order methanol > ethanol > 1-propanol, indicating that a faster reduction rate of [PdCl4]2- ions is an important factor to produce the smaller particles. The particle diameter showed a minimum at around 40 vol % of alcohol in solvent. Once the monodispersed Pd nanoparticles were obtained, the larger particles with a narrow size distribution could be easily synthesized by using the stepwise growth reaction. The Pd nanoparticles obtained here had fcc structures like that of bulk Pd, although the lattice constant increased with a decrease in the particle size.

The earliest and the most critical stage in VLSI layout design is the placement. The background is the rectangle packing problem: given a set of rectangular modules of arbitrary sizes, place them without overlap on a plane within a rectangle of minimum area. Since the variety of the packing is uncountably infinite, the key issue for successful optimization is the introduction of a finite solution space which includes an optimal solution. This paper proposes such a solution space where each packing is represented by a pair of module name sequences, called a sequence-pair. Searching this space by simulated annealing, hundreds of modules have been packed efficiently as demonstrated. For applications to VLSI layout, we attack the biggest MCNC benchmark ami49 with a conventional wiring area estimation method, and obtain a highly promising placement.

This paper presents a general framework for building classifiers that deal with short and sparse text & segments by making the most of hidden topics discovered from large-scale data collections. The main motivation of this work is that many classification tasks working with short segments of text & Web, such as search snippets, forum & chat messages, blog & news feeds, product reviews, and book & movie summaries, fail to achieve high accuracy due to the data sparseness. We, therefore, come up with an idea of gaining external knowledge to make the data more related as well as expand the coverage of classifiers to handle future data better. The underlying idea of the framework is that for each classification task, we collect a large-scale external data collection called universal dataset, and then build a classifier on both a (small) set of labeled training data and a rich set of hidden topics discovered from that data collection. The framework is general enough to be applied to different data domains and genres ranging from search results to medical text. We did a careful evaluation on several hundred megabytes of Wikipedia (30M words) and MEDLINE (18M words) with two tasks: Web search domain disambiguation and disease categorization for medical text, and achieved significant quality enhancement.

The pre-designable porous structures found in covalent organic frameworks (COFs) render them attractive as a molecular platform for addressing environmental issues such as removal of toxic heavy metal ions from water. However, a rational structural design of COFs in this aspect has not been explored. Here we report the rational design of stable COFs for Hg(II) removal through elaborate structural design and control over skeleton, pore size, and pore walls. The resulting framework is stable under strong acid and base conditions, possesses high surface area, has large mesopores, and contains dense sulfide functional termini on the pore walls. These structural features work together in removing Hg(II) from water and achieve a benchmark system that combines capacity, efficiency, effectivity, applicability, selectivity, and reusability. These results suggest that COFs offer a powerful platform for tailor-made structural design to cope with various types of pollution.

We describe a simple method to control the size of Pt nanoparticles with the use of an alcohol reduction. They then are assembled on the electrode by an electrophoretic deposition. The mean diameter of monodispersed Pt nanoparticles can be controlled from 19 to 33 Å in one-step reaction by changing the kind and/or the concentration of alcohol in water and the amount of protective polymer, poly(N-vinyl-2-pyrrolidone) (PVP). The monodispersed Pt nanoparticles of smaller diameter are obtained in the order of methanol > ethanol > 1-propanol, indicating that a faster reduction rate of [PtCl6]2- ions is an important factor to produce the smaller particles. The particle diameter decreases linearly with concentration of alcohol in water. Furthermore, increasing the amount of PVP makes the size of Pt nanoparticles smaller, the size distribution remaining quite narrow. By the combination of the one-step reaction with the stepwise growth reaction, Pt nanoparticles of arbitrary diameter in the range 19−50 Å can be obtained. The Pt nanoparticles obtained here have fcc structures such as bulk Pt. By using an electrophoretic deposition, more Pt nanoparticles move toward the anode with the increase of both the applied voltage and the electrophoretic time to form the Pt nanoparticle monolayer. Using the high concentration of Pt dispersion is effective to form the Pt nanoparticle monolayer.

We have fabricated label-free protein biosensors based on aptamer-modified carbon nanotube field-effect transistors (CNT-FETs) for the detection of immunoglobulin E (IgE). After the covalent immobilization of 5'-amino-modified 45-mer aptamers on the CNT channels, the electrical properties of the CNT-FETs were monitored in real time. The introduction of target IgE at various concentrations caused a sharp decrease in the source-drain current, and a gradual saturation was observed at lower concentrations. The amount of the net source-drain current before and after IgE introduction on the aptamer-modified CNT-FETs increased as a function of IgE concentration. The detection limit for IgE was determined as 250 pM. We have also prepared CNT-FET biosensors using a monoclonal antibody against IgE (IgE-mAb). The electrical properties of the aptamer- and antibody-modified CNT-FETs were compared. The performance of aptamer-modified CNT-FETs provided better results than the ones obtained using IgE-mAb-modified CNT-FETs under similar conditions. Thus, we suggest that the aptamer-modified CNT-FETs are promising candidates for the development of label-free protein biosensors.

Highly luminescent covalent organic frameworks (COFs) are rarely achieved because of the aggregation-caused quenching (ACQ) of π-π stacked layers. Here, we report a general strategy to design highly emissive COFs by introducing an aggregation-induced emission (AIE) mechanism. The integration of AIE-active units into the polygon vertices yields crystalline porous COFs with periodic π-stacked columnar AIE arrays. These columnar AIE π-arrays dominate the luminescence of the COFs, achieve exceptional quantum yield via a synergistic structural locking effect of intralayer covalent bonding and interlayer noncovalent π-π interactions and serve as a highly sensitive sensor to report ammonia down to sub ppm level. Our strategy breaks through the ACQ-based mechanistic limitations of COFs and opens a way to explore highly emissive COF materials.

In this paper, we propose a method for analyzing word-word dependencies using deterministic bottom-up manner using Support Vector machines. We experimented with dependency trees converted from Penn treebank data, and achieved over 90 % accuracy of word-word dependency. Though the result is little worse than the most up-to-date phrase structure based parsers, it looks satisfactorily accurate considering that our parser uses no information from phrase structures. 1

In this paper a new type of digital proxy signature is proposed. The proxy signature allows a designated person, called a proxy signer, to sign on behalf of an original signer. Classification of the proxy signatures is shown from the point of view of the degree of delegation, and conditions of a proposed proxy signature for partial delegation are clarified. The proposed proxy signature scheme is based on the discrete logarithm problem. Compared to the consecutive execution of the ordinary digital signature schemes, it has a direct form, and a verifier does not need a public key of a user other than the original signer in the verification stage. Moreover, it requires less amount of computational work than the consecutive execution of the signature schemes. Due to this efficiency together with the delegation property, an organization, e.g. a software company, can very efficiently create many signatures of its own by delegating its signing operations to multiple employees. Another attractive feature of the proposed schemes is their highapplicability to other ordinary signature schemes based on the discrete logarithm problem. For instance, designated confirmer proxy signatures can be constructed. Furthermore, using a proposed on-line proxy updating protocol, the original signer can revoke proxies of dishonest proxy signers.

Total order broadcast and multicast (also called atomic broadcast/multicast) present an important problem in distributed systems, especially with respect to fault-tolerance. In short, the primitive ensures that messages sent to a set of processes are, in turn, delivered by all those processes in the same total order.