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Copper phthalocyanines are commercially important organic pigments for blue shades of colour. They are dispersed by mechanical means as tiny molecular crystals (of dimensions 0.02—0.5 μm) into a wide range of commercial media to form products such as printing inks, paints and coloured plastics. Many important technological properties of copper phthalocyanine pigments, including colour strength and dispersion performance, depend on the physical properties of their crystals, notably crystal lattice type, crystal size and crystal shape. The roles which these crystal properties play in determining a copper phthalocyanine pigment's technological performance are briefly reviewed. The reduction of crystal aggregation during the manufacture of a copper phthalocyanine pigment and the control of flocculation in an application medium are also highlighted.

In this paper, we develop four numerical methods for computing the singular value decomposition (SVD) of large sparse matrices on a shared-memory multiprocessor architecture. We particularly consider the SVD of unstructured sparse matrices in which the number of rows may be substantially larger or smaller than the number of columns. We emphasize Lanczos, block-Lanczos, subspace iteration and the trace minimization methods for determining a select number of smallest singular triplets (singular values and corresponding left- and right-singular vectors) for sparse matrices. The target architectures for implementations of such methods include the Alliant FX/80 and the Cray-2S/4–128. This algorithmic research is particularly motivated by recent information-retrieval techniques in which approximations to large sparse term-document matrices are needed, and by nonlinear inverse problems arising from seismic reflection tomography applications.

This paper presents a repair algorithm for the design of a Radial Basis Function (RBF) neural network. The proposed repair RBF (RRBF) algorithm starts from a single prototype randomly initialized in the feature space. The algorithm has two main phases: an architecture learning phase and a parameter adjustment phase. The architecture learning phase uses a repair strategy based on a sensitivity analysis (SA) of the network's output to judge when and where hidden nodes should be added to the network. New nodes are added to repair the architecture when the prototype does not meet the requirements. The parameter adjustment phase uses an adjustment strategy where the capabilities of the network are improved by modifying all the weights. The algorithm is applied to two application areas: approximating a non-linear function, and modeling the key parameter, chemical oxygen demand (COD) used in the waste water treatment process. The results of simulation show that the algorithm provides an efficient solution to both problems.

THz technology applications, sensors and sources are briefly reviewed. Emphasis is placed on the less familiar components, instruments or subsystems. Science drivers, some historic background and future trends are discussed.

China faces a critical economic structural transformation with increasing financial instability and uncertainty, necessitating a greater need for accurate measurement of systemic financial risk. In the paper, this work analyses the systemic financial risk in China between 2011 and 2020 based on financial development, fragility and risk indicators and the world economy to construct a comprehensive index of systemic financial risk (CISFR). The results show an upward trend in China’s financial risk in the past 10 years and a mid-to-high level fluctuation in the past five years, mainly driven by risks in the banking system, securities market and real estate market. In 2021–2022, China’s financial system is still in a high-risk stage, and high systemic risks are still an important economic issue. The study’s comprehensive index method can be extended to emerging economies. It reflects the main driving factors of financial risk by assigning weights to basic indicators from a multidimensional perspective, thus providing a reference for policymakers to prevent and control financial risk.

Quantum computing as emerging technology raises high expectations to accelerate complicated calculations, superseding capabilities of presently available supercomputers and to provide a solution to the ever-increasing challenge of processing big amount of data. Besides theoretical promises, quantum computers have successfully been realized in experimental settings during the past few years, and can now also be accessed commercially. Given this availability of quantum computers, their application potential can be scrutinized. Promised to lead to disruptive changes in addressing and solving problems from the domains of simulation, optimization and machine learning, quantum computers have been researched in context of many application scenarios in industrial and academic setting in the recent years. However, it turns out that currently available quantum computers are still to small in size and limited in quality to fulfill the high hopes set in them at the moment. This review reflects on the current state of the technology coming from the perspective of the application, and indicates the developments required on hardware, software and algorithmic side to eventually make quantum computing beneficial for applications.

Lasers emit light with a very high degree of monochromaticity, directionality and intensity. They can produce much higher intensities than incoherent light sources, such as incandescent lamps, fluorescent tubes and arcs. The first operating laser was realized in 1960, and much early research was funded by military agencies, but at the present time the commercial laser market is four times as large as the military market. Most applications of lasers are for peaceful purposes. Among the most important of these are fiber-optic communications and laser surgery. Other applications include laser printing, laser machining, construction alignment, and data storage on CD disks. Some military uses of lasers are also reviewed.

With the rapid development of embedded systems, users and services have been greatly facilitated while also experiencing security threats as a result of cyber-attacks and system vulnerabilities. Currently, the real-time embedded system (RTES) focus is to deal with these security issues. In this paper, we introduce a short review of security-aware techniques for RTES. We mainly discuss two common approaches to improve the security of RTESs. The first approach is achieved by exploring specific attacks. The second approach is realized by deploying security-guaranteed services. However, improving the security of embedded systems may cause excessive energy consumption at the same time. Therefore, we investigate the secure and energy-aware RTESs on a wide range of research. In addition, we study a number of common applications used in secure RETSs. This paper stands for providing awareness and better understanding of the current RTES research status as well as technical theory behind it. Hence, the RTES security issues are resolved.

Symbolic images represent a unified framework to apply several methods for the investigation of dynamical systems both discrete and continuous in time. By transforming the system flow into a graph, they allow it to formulate investigation methods as graph algorithms. Several kinds of stable and unstable return trajectories can be localized on this graph as well as attractors, their basins and connecting orbits. Extensions of the framework allow, e.g. the calculation of the Morse spectrum and verification of hyperbolicity. In this work, efficient algorithms and adequate data structures will be presented for the construction of symbolic images and some basic operations on them, like the localization of the chain recurrent set and periodic orbits. The performance of these algorithms will be analyzed and we show their application in practice. The focus is not only put on several standard systems, like Lorenz and Ikeda, but also on some less well-known ones. Additionally, some tuning techniques are presented for an efficient usage of the method.

In this paper, we present the layered agent architecture INTERRAP which has been developed to cope with the basic requirements for Cooperative Intelligent Systems (CIS): agents shall behave in a situated, efficient, and goal-directed manner, and they shall be able to interact (i.e. coordinate and collaborate) with other agents. Over the past few years, agent architectures combining reactive with deliberative facilities have become very trendy in DAI. However, most attempts end up at the local planning layer and fail to take into account important mechanisms for interaction and collaboration among agents. INTERRAP extends previous attempts to build layered architectures by a cooperation component which holds cooperation knowledge as well as a library of joint plant. The modules of the model and the flow of control among them are explained. The model is described and evaluated by the FORKS application, the simulation of an automated loading-dock.

This Review concerns the Algebraic Relational Theory of living systems as developed by Leguizamón and co-workers since 1973 and based on the categorical approach championed by Robert Rosen and his (ℳ, ℛ) systems. The Algebraic Relational Theory expanded, by using new mathematical developments such as lattice theory, the relational notions found in (ℳ, ℛ) systems with concepts such as material physical nature and extrinsic energy that reflect aspects of physical reality not captured by standard physical concepts like mass, energy or time. The Algebraic Relational Theory is another effort in the direction of developing a theory about the notion of biological organization.

The Review contains the foundations of the theory, the principal mathematical developments, and applications of the theoretical results to different biological problems. They are the substantial base from which new ideas could be developed. It also includes a synthesis of initial experiments connected with this area of research.

Carlos Leguizamón died in 1998. We had worked together for 20 years.

In this paper, we use the generalized fractional derivative in order to study the fractional differential equation associated with a fractional Gaussian model. Moreover, we propose new properties of generalized differential and integral operators. As a practical application, we estimate the order of the derivative of the fractional Gaussian models by solving an inverse problem involving real data on the dengue fever outbreak.

Borophene, a boron analogue of graphene, has been considered as an innovative two-dimensional (2D) material for the scientific and research community. First 2D boron sheet was reported in 2015 by growing it on Ag substrate. Attributable to its exceptional structural, electronic, and spin properties, it has earned enormous exploration interests in the multifaceted fields of material science, nanotechnology and computational physics. Borophene is the newest rising 2D material, which demonstrates various diversified configurations that can be marked by anisotropic and polymorphism. These configurations enabled enhanced tailoring properties of borophene for various applications. This review provides brief discussion on various experimentally synthesized borophene and borophene nanoribbon (BNR), their structural, electronic, and magnetic properties variations along with the width effect. Based upon the type of edges, BNRs are categorized as line edge-BNR (LE-BNR) and zigzag-BNR (ZZ-BNR). Electronic properties of LE-BNR with vacancy defect show semiconductor behavior and ZZ-BNR indicates metallic property. It covers all the structural allotropes, their synthesis, stability and other crucial intrinsic properties, characterization and tailoring of physical properties. Hence, this comprehensive review reported here incorporates the crucial recent experimental and theoretical advances on borophene and BNRs till date. This work also covers recent modifications reported in borophene and BNR to alter their properties as per the demands of various application areas such as nanoelectronic devices, interconnects, biosensors, metal detectors and gas sensors.

The Promise of Gene Therapy.

Novel Multiplex PCR Technologies.

Reducing the Spread of TB in China: New Technology Needed to Turn the Tide.

Application of Rapid and Accurate Two-Stage Genotyping Strategy in MRSA Nosocomial Infection in Japan.

Introduction to Luminex^®xMAP^® Technology and Applications for Biological Analysis in China.

Label-free Real-time Cell Based Assay System for Evaluating H1N1 Vaccination Success.

INDIA – Bioven starts BV-NSCLC-001 Phase III trial in NSCLC.

INDIA – Initiative in Chemical Biology and Therapeutics.

PHILLIPPINES – Asia–Pacific Analysis: The slow road to green energy.

SINGAPORE – Takeda progressing well in Asia with New Drug Applications.

SINGAPORE – NTU and University of Warwick boost brainpower in global neuroscience research.

THAILAND – Thai PhD. student awarded Monsanto's Beachell–Borlaug International Scholarship for rice improvement research.

EUROPE – Open access will change the world, if scientists want it to.

UNITED STATES & CANADA – Verisante places Aura Beta Units for safety, verification testing in B.C., Alberta and Ontario clinics.

UNITED STATES & CANADA – Life Technologies sets new worldwide standard for criminal forensic testing with introduction of GlobalFilerTM Express Kit.

UNITED STATES & CANADA – How immune cells can nudge nerves to regrow.

UNITED STATES & CANADA – Improved Genomic Target Selection Using IDT Oligos.

UNITED STATES & CANADA – US team uncover non-invasive method for diagnosing epilepsy.

NUS Researchers Create Palm-Size Device for Quick, Effective Treatment of Common Hearing Disorder.

World Asthma Day: Managing and Living with Asthma.

DARZALEX^® (daratumumab) Available in Singapore, Following Accelerated Approval by the Health Sciences Authority.

Managing Liver Cancer as a Global Health Problem.

Bayer and NUS Enterprise Announce Winners of Grants4Apps^® Singapore Open Innovation Challenge.

Exclusive Interviews with the Grants4Apps^® winners: I. EyeDEA, Singapore, II. GlycoLeap by Holmusk, Singapore and III. PillPocket, Thailand.

In this paper, we give a quantitative description of the Fucík spectrum of -Δ with several technical conditions and get some results which improve considerably [5, Theorems 2.6 and 3.3]. The isomorphism between C_*(J_{(a, b, f)}, ∞) and C_*(J_{(a, b)}, 0) are obtained provided (a,b) ∉ ∑, which is exploited as a tool to generalize a result given by [14] without assuming λ_l being simple. Two applications are discussed.

We describe a display system that automatically registers an array of casually positioned projectors and drives the display with a PC cluster. The display system uses a camera to compute the necessary transformations to geometrically align multiple overlapping projectors. Geometric alignment is realized through real-time corrective warping applied in the rendering pipeline. This combination of camera-aided display alignment with the PC-cluster rendering engine provides a display system that is easy to configure and reconfigure, accommodates casually tiled projectors and arbitrary display surfaces, and can be operational in a very short period of time.

In this paper, the author first gives a conjugacy-class version of Camina hypotheses and then applys the Camina group theory to discussing two classes of finite groups.