New metal chelate sorbent for albumin adsorption: Cibacron Blue F3GA-Zn(II) attached microporous poly(HEMA) membranes

Poly(2-hydroxyethyl methacrylate) [poly(HEMA)] membranes were prepared by UV-initiated photopolymerization of HEMA in the presence of an initiator (α-α′-azobis-isobutyronitrile, AIBN). The triazine dye Cibacron Blue F3GA was attached as an affinity ligand to poly(HEMA) membranes, covalently. These affinity membranes with a swelling ratio of 58% and containing 10.7 mmol Cibacron Blue F3GA/m² were used in the albumin adsorption studies. After dye-attachment, Zn(II) ions were chelated within the membranes via attached-dye molecules. Different amounts of Zn(II) ions [650–1440 mg Zn(II)/m²] were loaded on the membranes by changing the initial concentration of Zn(II) ions and pH. Bovine serum albumin (BSA) adsorption on these membranes from aqueous solutions containing different amounts of BSA at different pH was investigated in batch reactors. The nonspecific adsorption of BSA on the poly(HEMA) membranes was negligible. Cibacron Blue F3GA attachment significantly increased the BSA adsorption up to 92.1 mg BSA/m². Adsorption capacity was further increased when Zn(II) ions were attached (up to 144.8 mg BSA m²). More than 90% of the adsorbed BSA was desorbed in 1 h in the desorption medium containing 0.5M NaSCN at pH 8.0 and 0.025M EDTA at pH 4.9. © 1998 John Wiley & Sons, Inc. J Appl Polym Sci 68: 657–664, 1998     

Detection of COVID-19 and its pulmonary stage using Bayesian hyperparameter optimization and deep feature selection methods

Since the first case of COVID-19 was reported in December 2019, many studies have been carried out on artificial intelligence for the rapid diagnosis of the disease to support health services. Therefore, in this study, we present a powerful approach to detect COVID-19 and COVID-19 findings from computed tomography images using pre-trained models using two different datasets. COVID-19, influenza A (H1N1) pneumonia, bacterial pneumonia and healthy lung image classes were used in the first dataset. Consolidation, crazy-paving pattern, ground-glass opacity, ground-glass opacity and consolidation, ground-glass opacity and nodule classes were used in the second dataset. The study consists of four steps. In the first two steps, distinctive features were extracted from the final layers of the pre-trained ShuffleNet, GoogLeNet and MobileNetV2 models trained with the datasets. In the next steps, the most relevant features were selected from the models using the Sine–Cosine optimization algorithm. Then, the hyperparameters of the Support Vector Machines were optimized with the Bayesian optimization algorithm and used to reclassify the feature subset that achieved the highest accuracy in the third step. The overall accuracy obtained for the first and second datasets is 99.46% and 99.82%, respectively. Finally, the performance of the results visualized with Occlusion Sensitivity Maps was compared with Gradient-weighted class activation mapping. The approach proposed in this paper outperformed other methods in detecting COVID-19 from multiclass viral pneumonia. Moreover, detecting the stages of COVID-19 in the lungs was an innovative and successful approach.     

Towards an Unbiased Comparison of CC,BCC, and FCC Lattices in Terms of Prealiasing

In the literature on optimal regular volume sampling, the Body‐Centered Cubic (BCC) lattice has been proven to be optimal for sampling spherically band‐limited signals above the Nyquist limit. On the other hand, if the sampling frequency is below the Nyquist limit, the Face‐Centered Cubic (FCC) lattice was demonstrated to be optimal in reducing the prealiasing effect. In this paper, we confirm that the FCC lattice is indeed optimal in this sense in a certain interval of the sampling frequency. By theoretically estimating the prealiasing error in a realistic range of the sampling frequency, we show that in other frequency intervals, the BCC lattice and even the traditional Cartesian Cubic (CC) lattice are expected to minimize the prealiasing. The BCC lattice is superior over the FCC lattice if the sampling frequency is not significantly below the Nyquist limit. Interestingly, if the original signal is drastically undersampled, the CC lattice is expected to provide the lowest prealiasing error. Additionally, we give a comprehensible clarification that the sampling efficiency of the FCC lattice is lower than that of the BCC lattice. Although this is a well‐known fact, the exact percentage has been erroneously reported in the literature. Furthermore, for the sake of an unbiased comparison, we propose to rotate the Marschner‐Lobb test signal such that an undue advantage is not given to either lattice.     

LASER SHORT-PULSE HEATING: INFLUENCE OF LASER POWER INTENSITY ON TEMPERATURE FIELDS

High-power-intensity and short-pulse laser heating of metallic surfaces results in thermal separation of electron and lattice subsystems. In this case, energy transport between the subsystems is governed mainly by the collisional process. Moreover, electron and lattice subsystems respond differently for different pulse intensities, despite the fact that the laser pulses have the same energy content. Consequently, in the present study, laser step-input pulse heating of gold substrate is considered and the thermal response of electron and lattice subsystems to four different intensity pulses with the same energy content is examined. The electron kinetic theory approach is introduced to model the nonequilibrium energy transport in the substrate material. It is found that electron temperature rises rapidly in the heating cycle while lattice temperature rise is gradual, which is more pronounced for laser short pulse lengths. In the cooling cycle (time after the laser pulse diminishes), electron temperature decay rate differs from the rate of lattice site temperature rise due to the specific heat ratios of electron and lattice sites.     

Dual material gate junctionless tunnel field effect transistor

This paper proposes a junctionless tunnel field effect transistor (JLTFET) with dual material gate (DMG) structure and the performance was studied on the basis of energy band profile modulation. The two-dimensional simulation was carried out to show the effect of conduction band minima on the abruptness of transition between the ON and OFF states, which results in low subthreshold slope (SS). Appropriate selection of work function for source and drain side gate metal of a double metal gate JLTFET can also significantly reduce the subthreshold slope (SS), OFF state leakage and hence gives improved I _ON/I _OFF.     

Influence of principal component analysis acceleration factor on velocity measurement in 2D and 4D PC-MRI

Objective

The objective of the study was to determine how to optimize 2D and 4D phase-contrast magnetic resonance imaging (PC-MRI) acquisitions to acquire flow velocities in millimetric vessels. In particular, we search for the best compromise between acquisition time and accuracy and assess the influence of the principal component analysis (PCA).

Materials and methods

2D and 4D PC-MRI measurements are conducted within two in vitro vessel phantoms: a Y-bifurcation phantom, the branches of which range from 2 to 5 mm in diameter, and a physiological subject-specific phantom of the carotid bifurcation. The same sequences are applied in vivo in carotid vasculature.

Results

For a vessel oriented in the axial direction, both 2D and axial 4D PC-MRI provided accuracy measurements regardless of the k-t PCA factor, while the acquisition time is reduced by a factor 6 for k-t PCA maximum value. The in vivo measurements show that the proposed sequences are adequate to acquire 2D and 4D velocity fields in millimetric vessels and with clinically realistic time durations.

Conclusion

The study shows the feasibility of conducting fast, high-resolution PC-MRI flow measurements in millimetric vessels and that it is worth maximizing the k-t PCA factor to reduce the acquisition time in the case of 2D and 4D axial acquisitions.

     

Optimization of Polishing Conditions for Long Grain <Emphasis Type=Italic>Basmati</Emphasis> Rice in a Laboratory Abrasive Mill

Rice milling operation is a very energy-intensive process. The major qualities of the rice which are taken into consideration while milling are the degree of milling and head rice yield. A laboratory abrasion polisher, modified by attaching a humidifying and cooling unit, was used to polish long-grain Pusa Basmati rice in order to optimize the polishing conditions. Polishing experiments were carried out using central composite design for a factorial with a central point, at different initial grain temperatures (5–25 °C) and milling chamber temperatures (11–25 °C) at a constant humidity level of 95 ± 2% for different time intervals. Models capable of predicting the quality of milled rice were developed using response surface methodology and used to determine optimum processing conditions. Responses such as degree of milling (DOM), broken content, and specific energy consumption were used to assess product quality. Optimum milling conditions of a minimum of 10% DOM, a broken content of 8%, and a specific energy consumption of 11 kJ/DOM were obtained at a milling chamber temperature of 11 °C, an initial grain temperature of 15 °C, and a milling period of 180 s.     

Modeling and simulation of photon-coupled,fluorescent photoswitchable protein logic

Today's society has an ever-increasing demand for smaller-scale, lower-energy-consuming, cheaper, and faster computing and digital signal processing systems. Photon-coupled, fluorescent photoswitchable protein-based architectures are promising candidates for the fulfillment of these requirements. In order to properly design digital circuits based on the aforementioned building blocks, an efficient simulation procedure is needed. We present a simple, differential equation-based model, suitable for the design and simulation of such structures. It characterizes the radiation-induced switching, the form-dependent fluorescence, and the effect of photon coupling in a fast and efficient manner. The applicability of the model is demonstrated through simulations of the OR and NOR logic gates consisting of readily available, fluorescent photoswitchable proteins. It can be a potential design tool for future molecular logic circuitry based on such molecules.     

Experimental investigation of input–output characteristics of a travelling-wave ultrasonic motor

Speed, position and load characteristics of the ultrasonic motor is considerably influenced from the input characteristics such as driving frequency, magnitude and phase difference of phase voltages. Input and output characteristics of a traveling-wave ultrasonic motor have been investigated from the experimental point of view in the present study. For this aim, a half-bridge serial-resonance inverter based drive system has been designed and then implemented. The inverter is featured with pulse width modulation and pulse frequency modulation techniques. The frequency, amplitude and phase angle of two-phase sinusoidal output of the driver has been designed to be changed for the control purpose. Then the measuring circuits and tools have been set up to obtain required measurements. Input characteristics such as duty ratio of control signal-dc reference voltage, dc reference voltage-driving frequency and output characteristics such as driving frequency-rotor speed, driving frequency-feedback voltage, phase voltage-rotor speed are obtained from the experiments. Also load characteristics are studied with experiments. Afterwards these characteristics are discussed in details. This study gives a systematical experimental approach in order to demonstrate operating and control principles and characteristics of the travelling-wave ultrasonic motor.