Towards a comprehensive methodology for KBS development

Abstract: The vitality of effective methods and processes for developing knowledge-based systems (KBS) is examined. The paper discusses what should be expected from a methodology. Have their advocates been getting it all wrong all the way? That is certainly a suggested view put forward. The criticism includes an articulation of the major schools of thought in developing KBS; their implicit assumptions and philosophies, especially the prototyping options, are presented in the light of this paper. After the criticism, the philosophical basis of a new comprehensive KBS development methodology is presented. This breeds the line model of development, which in turn creates what is suspected to be an essential concept of thought in the developer's mind.     

Heat transfer and fluid flow characteristics in flash desalination units

The present work investigates the effects of different operating and geometrical parameters on the flashing efficiency of water in a single stage flashing chamber. This chamber uses a submerged rectangular orifice as flow control area. Experiments were performed to investigate the effects of flow rate, liquid level in the flashing chamber, liquid inlet temperature and flashing range, on the flashing efficiency under various design conditions. These comprise flow with baffle placed in the flashing chamber, and wire meshes placed at the orifice to increase the turbulence level.It was found that the efficiency increased with the increase of the turbulence levels, flashing range and liquid inlet temperature; the efficiency deceased with the increase of the flow rate and liquid level in the flashing chamber. The application of numerical procedure to predict flow pattern and heat transfer in the flashing chamber is introduced as a powerful design tool.     

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.     

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.     

Effect of anti-scale agents on the solubility of CO2 in seawater at temperatures of 60 to 90ºC and pressures of 1–2 bar

The objective of this work is to present experimental data that would show the effect of temperature, salinity, pressure and the presence of anti-scale additives on CO₂ solubility in seawater. The paper examines the solubility of CO₂ in real seawater and real seawater dosed with two different anti-scale additives. The study has been performed at temperatures between 60ºC and 90ºC and at pressures of 1 and 2 bar. To assess the effect of each anti-scale additive on CO₂ gas solubility varying doses, 2–10 ppm of anti-scale additive have been used. For the purpose of the experimentation an experimental rig has been designed to ensure adequate contact between the gas phase and the aqueous phase. The continuous quantitative analysis of CO₂ concentration flowing from the experimental rig was measured using a CM-5011 Carbon Coulometer. A mass balance was carried out to calculate the amount of CO₂ absorbed into solution; Henry’s law constant was then calculated.     

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.     

Effect of solar UV‐B exclusion on the phytoplankton community in a sub‐tropical mountain reservoir: a mesocosm study

A mesocosm experiment was conducted over a 4 week period to investigate the response of a phytoplankton community in a mountain freshwater reservoir to solar UV‐B exclusion. The mesocosms were filled with water taken from the depth of 0.30 m in the reservoir, and exposed to near‐ambient solar UV‐B (+UV‐B) and solar UV‐B exclusion (?UV‐B). The resulting chlorophyll‐a (Chl‐a), carotenoids, soluble sugars, algal composition and algal abundance were analysed. The study results indicated that carotenoids, carbohydrates and species distribution were affected under the ?UV‐B treatment. The carotenoid concentration was generally higher under the +UV‐B treatment than under the ?UV‐B treatment. The sucrose and glucose concentrations were affected differently by the UV‐B treatments, although both sugars strongly decreased under the +UV‐B treatment by the end of the experiment. The sucrose and glucose concentrations exhibited similar distribution patterns to those of carotenoids for the +UV‐B treatment, suggesting that these sugars could be directly involved in secondary metabolism. In contrast, the fructose content did not exhibit significant differences between UV‐B treatments. The Chl‐a concentration exhibited a progressive decrease during the experiment for both UV‐B treatments. Although no significant impact of UV‐B exclusion on the Chl‐a concentration was observed in this study, a slightly higher concentration was observed for the ?UV‐B treatment. The total phytoplankton biovolume (BV) exhibited a pattern similar to that of the Chl‐a concentration. Analysis of the phytoplankton composition revealed 52 species. However, because some species and classes were extremely difficult to identify, only 46 species from seven classes (Cyanophyceae, Chlorophyceae, Bacillariophyceae, Euglenophyceae, Charophyceae, Dinophyceae, Xanthophyceae) were unambiguously identified and considered for the UV‐B treatments. Chlorophyceae, Bacillariophyceae and Cyanophyceae comprised about 78% of the identified species. Aulacoseira granulata and Cyclotella meneghiniana, followed by Ceratium hirundinella, were the most abundant species. Principal component analysis, using sampling periods and algal densities (PCA‐1), indicated a heterogeneous phytoplankton assemblage, whereas PCA‐2, with algal densities and biochemical variables (soluble carbohydrates, Chl‐a and carotenoids), indicated that biochemical parameters could provide qualitative information about La Angostura phytoplankton community responses to quality of the sunlight.     

Feasibility of using various photovoltaic systems for window-type air-conditioning units under hot-arid climates

This paper reports on the feasibility of using various Photovoltaic (PV) systems namely; Grid PV (GPV), Stand-Alone PV (SAPV), Grid PV Wind (GPVW) and PV Wind (PVW) for supplying the power requirements of a window-type air-conditioning system or other small loads. It was found that the GPVW system is the best system to meet the load requirement of a window-type air-conditioning system under the climatic conditions of Oman with values ranging from $39,500 to $56,500 for the capital cost and $9,000 to $33,000 for the total net capital cost depending on the wind speed. These values are attractive for remote off grid applications.