Characterisation of optically driven microstructures for manipulating single DNA molecules under a fluorescence microscope

Optical tweezers are powerful tools for manipulating single DNA molecules using fluorescence microscopy, particularly in nanotechnology‐based DNA analysis. We previously proposed a manipulation technique using microstructures driven by optical tweezers that allows the handling of single giant DNA molecules of millimetre length that cannot be manipulated by conventional techniques. To further develop this technique, the authors characterised the microstructures quantitatively from the view point of fabrication and efficiency of DNA manipulation under a fluorescence microscope. The success rate and precision of the fabrications were evaluated. The results indicate that the microstructures are obtained in an aqueous solution with a precision ∼50 nm at concentrations in the order of 10⁶ particles/ml. The visibility of these microstructures under a fluorescence microscope was also characterised, along with the elucidation of the fabrication parameters needed to fine tune visibility. Manipulating yeast chromosomal DNA molecules with the microstructures illustrated the relationship between the efficiency of manipulation and the geometrical shape of the microstructure. This report provides the guidelines for designing microstructures used in single DNA molecule analysis based on on‐site DNA manipulation, and is expected to broaden the applications of this technique in the future.Inspec keywords: DNA, molecular biophysics, fluorescence, optical microscopy, radiation pressure, biological techniquesOther keywords: optically driven microstructures, single DNA molecule analysis, fluorescence microscopy, optical tweezers, nanotechnology‐based DNA analysis, manipulation technique, aqueous solution, fine tune visibility, yeast chromosomal DNA molecules, geometrical shape, on‐site DNA manipulation     

Radiation-induced degradation of galactomannan polysaccharides

In this study, guar gum, tara gum and locust bean gum were irradiated in a gamma cell in the solid state. The change in their molecular weights were determined by size exclusion chromatography analysis and the change in their viscosity values with change of temperature and irradiation dose were determined. Chain scission yield, G(s), and degradation rate values were calculated. The calculated G(s) values is 1.09 ± 0.16, 1.07 ± 0.06, 0.85 ± 0.10 for GG, TG and LBG, respectively. The effect of mannose-galactose ratio and initial molecular weight of these gums on the degradation behavior were discussed.     

Subsurface radar signal deconvolution

We present two methods of signal deconvolution for systems whose impulse response (wavelet function) can be explicitly determined, and where the goal is to locate short impulses in the presence of strong, reverberation-like interferences.The first method, which we call algebraic deconvolution, differs from other known techniques in two ways: first of all, explicit use of the wavelet function provides more powerful a priori knowledge than the autocorrelation or the power spectrum. Secondly, this method permits to flexibly trade off noise versus resolution.In the second method presented here, we use an analytical model (synthetic wavelet) of the system impulse response to determine an inverse filter.These methods have been developed for video pulse radar signals, and encouraging early results have been obtained.     

Improved gait recognition by multiple-projections normalization

Recognizing people by gait promises to be useful for identifying individuals from a distance; in this regard, improved techniques are under development. In this paper, an improved method for gait recognition is proposed. Binarized silhouette of a motion object is first represented by four 1-D signals that are the basic image features called the distance vectors. The distance vectors are differences between the bounding box and silhouette, and extracted using four projections to silhouette. Fourier Transform is employed as a preprocessing step to achieve translation invariant for the gait patterns accumulated from silhouette sequences that are extracted from the subjects’ walk in different speed and/or different time. Then, eigenspace transformation is applied to reduce the dimensionality of the input feature space. Support vector machine (SVM)-based pattern classification technique is then performed in the lower-dimensional eigenspace for recognition. The input feature space is alternatively constructed by using two different approaches. The four projections (1-D signals) are independently classified in the first approach. A fusion task is then applied to produce the final decision. In the second approach, the four projections are concatenated to have one vector and then pattern classification with one vector is performed in the lower-dimensional eigenspace for recognition. The experiments are carried out on the most well-known public gait databases: the CMU, the USF, SOTON, and NLPR human gait databases. To effectively understand the performance of the algorithm, the experiments are executed and presented as increasing amounts of the gait cycles of each person available during the training procedure. Finally, the performance of the proposed algorithm is comparatively illustrated to take into consideration the published gait recognition approaches.     

International river basin organizations: variation,options and insights

Permanent international river basin organizations (IRBOs) come in many shapes and sizes, ranging from those which are mainly facilitative in nature to those empowered to act on their own. Although differences in IRBO types may have important impacts on transboundary water resources management, systematic analysis of variation in their structure and responsibilities is scant. This paper synthesizes and applies a typology to determine the structural composition, abundance, spatial distribution, scale and in-basin configurations of the different forms of IRBOs. The results provide a set of options for future IRBOs, and serve to ground-truth and nuance theoretical divisions between different types of organizations in transboundary basins.     

Wavelet domain association rules for efficient texture classification

The wavelet domain association rules method is proposed for efficient texture characterization. The concept of association rules to capture the frequently occurring local intensity variation in textures. The frequency of occurrence of these local patterns within a region is used as texture features. Since texture is basically a multi-scale phenomenon, multi-resolution approaches such as wavelets, are expected to perform efficiently for texture analysis. Thus, this study proposes a new algorithm which uses the wavelet domain association rules for texture classification. Essentially, this work is an extension version of an early work of the Rushing et al. [10], [11], where the generation of intensity domain association rules generation was proposed for efficient texture characterization. The wavelet domain and the intensity domain (gray scale) association rules were generated for performance comparison purposes. As a result, Rushing et al. [10], [11] demonstrated that intensity domain association rules performs much more accurate results than those of the methods which were compared in the Rushing et al. work. Moreover, the performed experimental studies showed the effectiveness of the wavelet domain association rules than the intensity domain association rules for texture classification problem. The overall success rate is about 97%.     

Synthesis of nano B2O3/TiO2 composite material as a new solid phase extractor and its application to preconcentration and separation of cadmium

A new solid phase extractor, nano-scale diboron trioxide/titanium dioxide composite material, was synthesized and used for separation and/or preconcentration of trace cadmium ion from various samples. The characterization of the synthesized material was performed by scanning electron microscope (SEM), transmission electron microscope (TEM) and X-ray diffractometer methods (XRD). The specific surface area of the material was also determined and found as 3.4 m²/g. Analytical parameters including pH of sample solution, sample volume, flow rate of sample solution, volume and concentration of eluent for the column solid phase extraction (SPE) procedure were examined. The effect of common matrix ions on the recovery of the cadmium has also been investigated and found that they did not interfere on cadmium preconcentration. Under the optimum experimental conditions, preconcentration factor and analytical detection limit were determined as 50 and 1.44 μg/L, respectively. The reusability (stabile up to 100 run) and adsorption capacity (49 mg/g) of the sorbent were excellent. The accuracy of the method was confirmed by analyzing certified reference materials (Tea leaves GBW-07605). The results demonstrated good agreement with the certified values (relative error <10%). The precision of the method was also satisfactory. The recovery of cadmium under the optimum conditions was found to be 96 ± 3% at 95% confidence level. The method was applied for the determination of cadmium in tap water and tea leaves.     

Effectiveness of phase I applications for identifying randomly scattered out‐of‐control observations and estimating control chart parameters

Estimation of unknown process parameters with fixed‐size samples are studied in the following. The standard textbook approach for phase I control chart implementation with a Shewhart control chart is evaluated for the case of normally distributed independent observations with random sampling. The charts are simultaneously implemented by generating observations that have a given percentage of randomly scattered out‐of‐control observations. Simulating the phase I steps, where out‐of‐control samples are detected iteratively by determining trial control limits, identifying samples exceeding these limits, and revising the control limits, the standard practice is evaluated in terms of both detection performance and quality of parameter estimates. It is shown that standard phase I control chart implementations with 3‐σ‐limits may perform very poorly in identifying true out‐of‐control observations and providing a reference set of in‐control observations for estimation in some practical settings. A chart design with 2‐σ‐limits is recommended for a successful phase I analysis.     

A grey wolf optimizer approach for optimal weight design problem of the spur gear

The weight of gears is an important issue for high performance of the machine elements. Thus, the design of the gear pairs with respect to the minimum weight is an important and attractive subject to study. Various analytical and heuristic approaches were utilized to optimize the weight of gears in previous studies. In this study, the problem of gear optimization as per the minimum weight was solved with Grey Wolf Optimizer (GWO). GWO is a meta-heuristic optimization method that stands out with its successful performance in engineering applications. In this study, the performance of GWO was investigated in the case of constituting a spur gear with respect to minimum weight for the first time. Compared with the previous studies, the results obtained in the study show that it is possible to design a lighter gear with GWO.     

Electrochemical corrosion properties of metal alloys used in orthopaedic implants

This study concerns an investigation of the corrosion behavior of 316 stainless steel, CoCrMo and Ti6Al4V alloys in simulated body conditions (ringer lactate) at 37 °C by the use of Tafel plots, mixed potential and electrochemical impedance spectroscopy (EIS). Ti6Al4V alloy has the highest corrosion resistance followed by CoCr alloy. Ti6Al4V–CoCrMO was the best couple for galvanic corrosion with the minimum galvanic potential and current values according to mixed potential theory and Tafel method. It was concluded that Ti6Al4V was the most suitable material for implant applications in the human body.