Crystalline silicon (c-Si) has low optical absorption due to its high surface reflection of incident light. Nanotexturing of c-Si which produces black silicon (b-Si) offers a promising solution. In this work, effect of H₂O₂ concentrations towards surface morphological and optical properties of b-Si fabricated by two-step silver-assisted wet chemical etching (Ag-based two-step MACE) for potential photovoltaic (PV) applications is presented. The method involves a 30 s deposition of silver nanoparticles (Ag NPs) in an aqueous solution of AgNO₃:HF (5:6) and an optimized etching in HF:H₂O₂:DI H₂O solution under 0.62 M, 1.85 M, 2.47 M, and 3.7 M concentrations of H₂O<

Objective: To evaluate and compare the effect of mechanical surface treatment (groove, aluminum oxide particles)
with 45 degree bevel type of joint on tensile bond strength of acrylic specimens repaired by two curing methods
(microwave and water both).
Methodology: Eighty specimens (80) were prepared from pink heat cure acrylic resin. They were divided into two
main groups (40 specimen repaired by microwave energy and 40 specimens repaired by water bath method).Each
group can be divided into four subgroups of ten according to the surface treatment. The control group A was left
intact, group B received no surface treatment, group C and D received surface treatment by (groove, 50 m aluminum
oxide particles). Specimens

The purpose of this study is to investigate the histopathological response of dentinopulpal
response of human teeth to the Er: YAG laser cavity preparation in comparison with the conventional
class I cavity preparation. Thirty five sound human upper and lower first premolar teeth which were
needed to be extracted for orthodontic purposes were used in the study. Regarding to the method of
cavity preparation, the teeth were grouped into three groups; Group1; Control group which consists of
seven sound teeth without cavity preparation, Group2; Conventional cavity preparation group and group
3; Er: YAG laser cavity preparation group. Each of Group2 and3 consists of fourteen teeth that is
subdivided into: A. 7teeth that e

Removing hazardous organic pollutants, such as 4-nitrophenol (4-NP) and Congo red (CR) dyes from aqueous media and CO2 from the atmospheric medium remains a significant challenge. Herein, we report a facile in-situ synthetic approach for fabricating CuO-ZnO heterostructure photocatalysts through the surfactant-assisted co-precipitation method. The catalytic results demonstrate that the Cu1O-ZnO photocatalyst exhibits excellent activity under direct sunlight irradiation, owing to the heterostructure formation between the CuO and ZnO. The Cu1O-ZnO photocatalyst showed higher reaction rate constant (k) values of 0.20 min−1 for 4-NP and 0.09 min−1 for CR compared to previous reports. Additionally, efficient CO2 reduction was also achiev

The present study considers to confirming the applicability of flow with double-sided square lid driven cavity flow by using the lattice Boltzmann equation with moment-based boundary conditions for no slip boundaries.  The boundary conditions are applied over the hydrodynamic moments of the lattice Boltzmann equations locally at each node. The investigation is carried out numerically for both single and multiple relaxation time models. To simulate two-sided lid driven-cavity flow, the top and bottom walls are moving with constant velocity while other walls are stationary. Various Reynolds numbers are used in a range of 100 and up to 5000. The present method shows the effect of the moving boundaries on the two symmetrical cavities t

Optical burst switching (OBS) network is a new generation optical communication technology. In an OBS network, an edge node first sends a control packet, called burst header packet (BHP) which reserves the necessary resources for the upcoming data burst (DB). Once the reservation is complete, the DB starts travelling to its destination through the reserved path. A notable attack on OBS network is BHP flooding attack where an edge node sends BHPs to reserve resources, but never actually sends the associated DB. As a result the reserved resources are wasted and when this happen in sufficiently large scale, a denial of service (DoS) may take place. In this study, we propose a semi-supervised machine learning approach using k-means algorithm

6. coli K12 and B. subtilis 168 were investigated for their cadmium and mercury tolerance abilities. They were developed by UV mutagenesis technique to increase their tolerances either to cadmium or mercury, and their names then were designated depend on the name and concentration of metals. E. coli K12 Cd3^R exhibited bioremediation amount of 6.5 mg Cd/g dry biomass cell. At the same time, its wild-type (E. coli K12 Cd3) was able to remove 5.2 mg Cd/g dry biomass cell in treatment of 17 mg Cd /L within 72 hours of incubation at 37 °C (pH=7) in vitro assays. The results show that E.coli K12 Hg 20 was able to remove 0.050 µg Hg/g dry biomass cell

In this research the results of applying Artificial Neural Networks with modified activation function to
perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance
Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of
identification strategy consists of a feed-forward neural network with a modified activation function that
operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have
been trained online and offline have been used, without requiring any previous knowledge about the
system to be identified. The activation function that is used in the hidden layer in FFNN is a modified
version of the wavelet func

In this research the results of applying Artificial Neural Networks with modified activation function to perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of identification strategy consists of a feed-forward neural network with a modified activation function that operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have been trained online and offline have been used, without requiring any previous knowledge about the system to be identified. The activation function that is used in the hidden layer in FFNN is a modified version of the wavelet function. This approach ha

Modeling forward kinematics with neural networks allows for efficient handling of nonlinear relationships and realistic error correction in time-critical applications by relying on accurate training data. This paper presents a Multi-Layer Feed-Forward Neural Network (MLFFNN) to solve the forward kinematics of a 3-DOF robot. The proposed MLFFNN consists of 50 hidden neurons and was trained using 628319 samples to find only the position (x, y, z) of the end-effector. Data were generated by MATLAB, assuming an incremental motion of joints. The joint variables ( , , and ) are the inputs of the NN, which outputs the positions of the end effector (x, y, z) calculated using the Denavit-Hartenberg (DH) method. The results demonstrate that t