Improved BER based on intensity noise alleviation using developed detection technique for incoherent SAC-OCDMA systems

The major drawback of incoherent spectral-amplitude coding optical code-division multiple-access (SAC-OCDMA) systems is their inherent intensity noise originating due to the incoherency of the broadband light sources. In this paper, we propose a developed detection technique named the modified-AND subtraction detection for incoherent SAC-OCDMA systems. This detection technique is based upon decreasing the received signal strength during the decoding process by dividing the spectrum of the utilized code sequence. The proposed technique is capable of mitigating the intensity noise effect, as well as suppressing the multiple-access interference impact. Based on modified quadratic congruence (MQC) code, the analytical results reveal that the modified-AND detection offer best bit-error rate (BER) performance and enables MQC code to support higher transmission rate up to 1.25?Gb/s compared to conventional AND detection. Furthermore, we ascertained that the proposed technique enhances the system performance using a simulation experiment.     

Differences observed in properties of ternary NiCoFe films electrodeposited at low and high pH

Ternary NiCoFe films were potentiostatically electrodeposited from the electrolytes with low (3.0) and high (3.6) pH levels, and differences in their compositional, structural, magnetic and magnetoresistance properties were studied. The compositional analysis demonstrated that the Ni content in the films decreased, and Co and Fe content increased while electrolyte pH was changed from low to high level. The structural analysis of the films was carried out using the X-ray diffraction (XRD) and scanning electron microscopy (SEM) techniques. The XRD data revealed that the films have a strong (111) texture of the face-centred cubic (fcc) structure at low pH, while for the films at high pH a mixture of dominantly fcc and hexagonal closed packed structure was observed. The SEM studies showed that films grown at low pH level had comparatively larger grains than those at high pH. The magnetic characteristics studied by a vibrating sample magnetometer and magnetotransport properties were seen to be changed by the electrolyte pH. However, all films have in-plane magnetic anisotropy. The differences observed in the magnetic and magnetotransport properties were attributed to the microstructural changes caused by the electrolyte pH.     

Characterization of synthetic and activated sludge and conditioning with cationic polyelectrolytes

This study investigates the effect of cationic polyelectrolytes on the final properties of synthetic and activated sludge. Synthetic sludge was prepared according to established procedures. Activated sludge was produced in a labscale, continuous-flow reactor which was fed with live activated sludge from a waste-water treatment plant. Capillary suction time (CST) was used to evaluate the sludge dewatering behaviour. The results from experiments indicated that the cationic polyelectrolytes had a critical effect on sludge dewatering, and made an improvement in the final properties of sludge. The two types of sludge have very similar dewatering characteristics after cationic polymer conditioning. The development of synthetic sludge is suggested also to be a possible surrogate for studying the final properties of activated sludge.     

Effects of heavy metals and polyelectrolytes in humic substance coagulation under saline conditions

Charge neutralisation plays a major role in heavy metal and humic substance removal in water treatment. Humic substances have no readily identifiable structure and they consist of anionic macromolecules of low to moderate molecular weight. Humic substances are easily coagulated using cationic metals and polyelectrolytes. Different concentrations of humic substances have been coagulated with different concentrations of heavy metals and/or polyelectrolytes. The charge neutralisation was determined using U.V. spectrophotometer. Humic substance removal increased with increasing salinity level until reaching a point where HS destabilization is considered complete and salinity no longer play a role in HS removal. Humic substance removal increased with increasing heavy metals concentration and precipitation was experienced at high concentrations of heavy metals (15–20 mg/L) and low concentration of humic substances (10 mg/L). In addition, HS removal also increased with increasing polyelectrolyte concentration. Diallydimethylammonium chloride (PDADMAC) polyelectrolyte was more effective in humic substance coagulation compared to copolymer of dimethyl aminoethyl acrylate (CoAA). The addition of heavy metals in polyelectrolyte coagulation increased humic substance removal due to the combined charge neutralization of the metals and polyelectrolytes.     

Measurement of intrinsic properties of amyloid fibrils by the peak force QNM method

We report the investigation of the mechanical properties of different types of amyloid fibrils by the peak force quantitative nanomechanical (PF-QNM) technique. We demonstrate that this technique correctly measures the Young's modulus independent of the polymorphic state and the cross-sectional structural details of the fibrils, and we show that values for amyloid fibrils assembled from heptapeptides, α-synuclein, Aβ(1-42), insulin, β-lactoglobulin, lysozyme, ovalbumin, Tau protein and bovine serum albumin all fall in the range of 2-4 GPa.     

Evaluation of the effects of different remineralizing agents on Streptococcus mutans biofilm adhesion

The aim of the study was to compare the effects of different remineralization methods that are well established in clinical and daily use on S. mutans biofilm adhesion. In this study 72 human third molars were used. From each tooth two pieces of 4?mm x 7?mm enamel blocks were acquired. The samples were divided into 6 groups in which include 10 samples per time period (24h and 48?h) and for each remineralization method; control, flouride, ozone, CPP-ACP, arginine, novamin. After remineralization procedures, enamel surfaces were covered with saliva. 10⁵ CFU/mL of active S. mutans culture were inoculated onto the samples. S. mutans colonies were counted with Plate Count Agar (PCA) decimal dilution method. Micromorphologic effects of different remineralization methods were observed by Scanning Electron Microscopy (SEM). The most S. mutans biofilm formation for both time periods was observed in the control group whereas the less biofilm adhesion was showed in the arginine group. There were no statistically significant differences among remineralization agents (p?>?0.05). In the control group there was statistical difference between 24?h and 48?h (p?<?0.005) but in the other study groups there were no significant difference between the time periods (p?>?0.05). Remineralization agents did not significant differ on S. mutans biofilm adhesion.     

Physical elution in phage display selection of inorganic-binding peptides

Phage display is a commonly utilized in vivo approach in selecting peptides specific to solid inorganic materials. In this process, traditionally, high affinity peptides are recovered by a chemical elution method, which involves contacting the phage library with the desired inorganic, washing the weak binders, and eluting the tight binders under harsh buffer conditions. This process may result in incomplete removal of all strong binders, separation of the phage from the display protein, or may modify the material surface. To overcome these potential limitations, we developed a physical elution technique based on ultrasonication. Here, we report two optimized ultrasonication protocols by which we selected peptides specific to natural mineral mica. We first performed a 30-s physical elution after the chemical elution step and increased the efficiency of screening strong binders by about 100%. Encouraged by the results, we applied physical elution-only protocol where we obtained 45% of the selected sequences as strong binders. The approach has a far shorter total elution time, i.e., seconds compared to hours in traditional chemical elution. The novel physical elution approach using ultrasonication reported herein can be a highly efficient alternate step in the screening of solid material specific peptides.     

CSatDTA: Prediction of Drug–Target Binding Affinity Using Convolution Model with Self-Attention

Drug discovery, which aids to identify potential novel treatments, entails a broad range of fields of science, including chemistry, pharmacology, and biology. In the early stages of drug development, predicting drug–target affinity is crucial. The proposed model, the prediction of drug–target affinity using a convolution model with self-attention (CSatDTA), applies convolution-based self-attention mechanisms to the molecular drug and target sequences to predict drug–target affinity (DTA) effectively, unlike previous convolution methods, which exhibit significant limitations related to this aspect. The convolutional neural network (CNN) only works on a particular region of information, excluding comprehensive details. Self-attention, on the other hand, is a relatively recent technique for capturing long-range interactions that has been used primarily in sequence modeling tasks. The results of comparative experiments show that CSatDTA surpasses previous sequence-based or other approaches and has outstanding retention abilities.     

ENet-6mA: Identification of 6mA Modification Sites in Plant Genomes Using ElasticNet and Neural Networks

N6-methyladenine (6mA) has been recognized as a key epigenetic alteration that affects a variety of biological activities. Precise prediction of 6mA modification sites is essential for understanding the logical consistency of biological activity. There are various experimental methods for identifying 6mA modification sites, but in silico prediction has emerged as a potential option due to the very high cost and labor-intensive nature of experimental procedures. Taking this into consideration, developing an efficient and accurate model for identifying N6-methyladenine is one of the top objectives in the field of bioinformatics. Therefore, we have created an in silico model for the classification of 6mA modifications in plant genomes. ENet-6mA uses three encoding methods, including one-hot, nucleotide chemical properties (NCP), and electron–ion interaction potential (EIIP), which are concatenated and fed as input to ElasticNet for feature reduction, and then the optimized features are given directly to the neural network to get classified. We used a benchmark dataset of rice for five-fold cross-validation testing and three other datasets from plant genomes for cross-species testing purposes. The results show that the model can predict the N6-methyladenine sites very well, even cross-species. Additionally, we separated the datasets into different ratios and calculated the performance using the area under the precision–recall curve (AUPRC), achieving 0.81, 0.79, and 0.50 with 1:10 (positive:negative) samples for F. vesca, R. chinensis, and A. thaliana, respectively.