Enhanced surface plasmon resonance detection of DNA hybridization based on ZnO nanorod arrays

We demonstrated an enhanced surface plasmon resonance detection incorporating ZnO nanorod arrays (NRAs) built on a thin gold film. ZnO NRAs were fabricated by wet chemical growth method and used for the detection of DNA hybridization. Experimental results exhibited that ZnO NRAs provided a notable sensitivity improvement by more than 3 times, which is attributed to an increase in the surface reaction area. The measured sensitivity enhancement matched well with the numerical analyses based on the effective medium theory. Our approach is intended to show the feasibility and extend the applicability of the ZnO-based SPR biosensor to diverse biomolecular binding events.     

Efficient representative pattern mining based on weight and maximality conditions

As a core area in data mining, frequent pattern (or itemset) mining has been studied for a long time. Weighted frequent pattern mining prunes unimportant patterns and maximal frequent pattern mining discovers compact frequent patterns. These approaches contribute to improving mining performance by reducing the search space. However, we need to consider both the downward closure property and patterns' subset checking process when integrating these different methods in order to prevent unintended pattern losses. Moreover, it is also essential to extract valid patterns with faster runtime and less memory consumption. For this reason, in this paper, we propose more efficient maximal weighted frequent pattern (MWFP) mining approaches based on tree and array structures. We describe how to handle these problems more efficiently, maintaining the correctness of our method. We develop two types of maximal weighted frequent mining algorithms based on weight ascending order and support descending order and compare these two algorithms to conclude which is more suitable for MWFP mining. In addition, comprehensive tests in this paper show that our algorithms are more efficient and scalable than state‐of‐the‐art algorithms, and they also have the correctness of the MWFP mining in terms of their pattern generation results.     

Controlled linear perturbation

We present an algorithmic solution to the robustness problem in computational geometry, called controlled linear perturbation, and demonstrate it on Minkowski sums of polyhedra. The robustness problem is how to implement real RAM algorithms accurately and efficiently using computer arithmetic. Approximate computation in floating point arithmetic is efficient but can assign incorrect signs to geometric predicates, which can cause combinatorial errors in the algorithm output. We make approximate computation accurate by performing small input perturbations, which we compute using differential calculus. This strategy supports fast, accurate Minkowski sum computation. The only prior robust implementation uses a less efficient algorithm, requires exact algebraic computation, and is far slower based on our extensive testing.     

Optimization of media processing workflows with adaptive operator behaviors

In this paper, we present the ARIA media processing workflow architecture that processes, filters, and fuses sensory inputs and actuates responses in real-time. The components of the architecture are programmable and adaptable; i.e. the delay, size, and quality/precision characteristics of the individual operators can be controlled via a number of parameters. Each data object processed by qStream components is subject to transformations based on the parameter values. For instance, the quality of an output data object and the corresponding processing delay and resource usage depend on the values assigned to parameters of the operators in the object flow path. In Candan, Peng, Ryu, Chatha, Mayer (Efficient stream routing in quality- and resource-adaptive flow architectures. In: Workshop on multimedia information systems, 2004), we introduced a class of flow optimization problems that promote creation and delivery of small delay or small resource-usage objects to the actuators in single-sensor, single-actuator workflows. In this paper, we extend our attention to multi-sensor media processing workflow scenarios. The algorithms we present take into account the implicit dependencies between various system parameters, such as resource consumption and object sizes. We experimentally show the effectiveness and efficiency of the algorithms.

The discovery of biomarkers for type 2 diabetic nephropathy by serum proteome analysis

Diabetic nephropathy (DN) is a serious kidney complication of diabetes, and constitutes the leading cause of end-stage renal disease. The earliest clinical evidence of DN is microalbuminuria, a term which refers to the appearance of small but abnormal amounts of albumin in the urine. However, screening methods for DN, such as biomarker assays, are yet to be developed for type 2 DN. In the present study, in an attempt to identify the biomarkers for initial diagnoses of type 2 DN, the protein profiles of human sera collected from 30 microalbuminuric type 2 diabetic patients were compared with those collected from 30 normoalbuminuric type 2 diabetic patients, via 2-DE. As a result, a total of 18 spots were determined to have different protein levels in the microalbuminuric patients. Twelve spots had lower protein levels of approximately 50%, and the other six had higher levels of approximately 100-300% as compared to the spots of normoalbuminuric patients. These spots were identified with ESI-Q-TOF (ESI-quadrupole-TOF) MS. Among the identified proteins, vitamin D-binding protein (DBP) and pigment epithelium-derived factor (PEDF) were verified by Western blotting. The results of this study indicate that the DBP may be employed as diagnostic and monitoring biomarkers of type 2 DN, contingent on further study into the matter.     

Preparation of bao-pbo-nd2o3-tio2 powders by hydrothermal synthesis

Homogeneous and nano-sized BPNT [(Ba_1-xPb_x)Nd₂Ti₅O₁₄] powders were prepared under various hydrothermal conditions. Crystallinity and homogeneity of the synthetic powders were investigated. The microwave dielectric properties of the filters prepared with hydrothermal powders were compared with those of the filters prepared with conventional powders. The microwave dielectric properties of the filter prepared with the hydrothermal powders were also better than those of the filter manufactured with the conventional powders. The dielectric constant, quality constant and temperature coefficient of resonance frequency of hydrothermally prepared filter under optimum condition and measured at 3.5 GHz around were about 93, 6067 and 0 ppm/°C, respectively.     

Removal of paraquat in aqueous suspension of TiO<Subscript>2</Subscript> in an immersed UV photoreactor

Experiments were performed to investigate the effect of operating parameters on the photodegradation efficiency of paraquat in a TiO₂-suspended photoreactor with immersed UV lamps. TiO₂ particles were prepared by a hydrothermal method. The removal rate of paraquat in the reactor was 0.54 mg/l/h with only air-sparging. The removal rate in 24 h with both the UV radiation and air-sparging was 50% higher than that with only the UV radiation. Variations of the paraquat concentration at the UV intensities of 4 and 8 W/m₂ decreased slowly with time, but that at 12 W/m₂ decreased more rapidly. The removal efficiency at the air-sparging flow rate of 1 //min increased as a UV light intensity increased. pH value in the reactor at the UV intensity of 12 W/m₂ decreased with time until 12 h and then increased with time over 12 h.     

Proactive thermal management in green datacenters

The increasing demand for faster computing and high storage capacity has resulted in an increase in energy consumption and heat generation in datacenters. Because of the increase in heat generation, cooling requirements have become a critical concern, both in terms of growing operating costs as well as their environmental and societal impacts. Presently, thermal management techniques make an effort to thermally profile and control datacenters’ cooling equipment to increase their efficiency. In conventional thermal management techniques, cooling systems are triggered by the temperature crossing predefined thresholds. Such reactive approaches result in delayed response as the temperature may already be too high, which can result in performance degradation of hardware.     

Tracking of moving interfaces in sedimentation processes using electrical impedance tomography

Sedimentation monitoring is widely used to control and optimize industrial processes. In this paper we propose a novel computational method for sedimentation monitoring using electrical impedance tomography (EIT). EIT measurements consist of electric current and voltage measurements that are made on the surface of the sedimentation tank and therefore they do not interfere with the sedimentation process. The proposed computational method is based on shape estimation and state estimation formulation of the EIT problem. The sedimentation is parameterized by the locations of the phase interfaces and conductivities of the phase layers. Three different evolution models for the state parameters are considered and the state estimates are computed using the extended Kalman filter algorithm. The performance of the method and the models are evaluated using simulated data from a six electrode EIT measurement configuration. From the results a promising performance of the method can be seen.     

Microstructures and tensile behavior of carbon nanotube reinforced Cu matrix nanocomposites

Carbon nanotubes (CNTs) have been considered as an ideal reinforcement to improve the mechanical performance of monolithic materials. However, the CNT/metal nanocomposites have shown lower strength than expected. In this study, the CNT reinforced Cu matrix nanocomposites were fabricated by spark plasma sintering (SPS) of high energy ball-milled nano-sized Cu powders with multi-wall CNTs, and followed by cold rolling process. The microstructure of CNT/Cu nanocomposites consists of two regions including CNT/Cu composite region, where most CNTs are distributed, and CNT free Cu matrix region. The stress–strain curves of CNT/Cu nanocomposites show a two-step yielding behavior, which is caused from the microstructural characteristics consisting of two regions and the load transfer between these regions. The CNT/Cu nanocomposites show a tensile strength of 281 MPa, which is approximately 1.6 times higher than that of monolithic Cu. It is confirmed that the key issue to enhance the strength of CNT/metal nanocomposite is homogeneous distribution of CNTs.