Server connection versus marital disconnection: an investigation of the effect of internet addiction on couple burnout in Iran

The internet has become ubiquitous in many people's lives to an extent that necessitates the investigation of its impact on marital relationships. There has been a lack of such studies in the Iranian context and the present study investigated the relationship between internet addiction and couple burnout. A total of 377 married individuals participated in an online survey comprising demographic information, the Internet Addiction Test (IAT), and the Couple Burnout Measure (CBM). Partial least squares –structure equation modeling (PLS-SEM) was used to assess the relationships in the proposed research model. Structural equation modelling showed a significant effect of sub-components of internet addiction (lack of control; social withdrawal and emotional conflict; time management problems; and concealing problematic behavior) on emotional burnout. In addition, lack of control and time management problems showed significant and positive effect on somatic burnout. However, the relationships between internet addiction components and psychological burnout were not demonstrated as hypothesized. Given the explained relationships between factors comprising internet addiction and couple burnout, couple therapists need to be made more aware of the risks of internet overuse upon marital relationships and to encourage couples to optimize the internet use to prevent negative outcomes (in particular emotional burnout) among couples

Hybridised Artificial Neural Network model with Slime Mould Algorithm: A novel methodology for prediction urban stochastic water demand

Urban water demand prediction based on climate change is always challenging for water utilities because of the uncertainty which results from a sudden rise in water demand due to stochastic patterns of climatic factors. For this purpose, a novel combined methodology including, firstly, data pre-processing techniques were employed to decompose the time series of water and climatic factors by using Empirical Mode Decomposition and identifying the best model input via tolerance to avoid multi-collinearity. Second, the Artificial Neural Network (ANN) model was optimised by an up-to-date Slime Mould Algorithm (SMA-ANN) to predict the medium term of the stochastic signal of monthly urban water demand. Ten climatic factors over 16 years were used to simulate the stochastic signal of water demand. The results reveal that SMA outperforms Multi-Verse Optimiser and Backtracking Search Algorithm based on error scale. The performance of the hybrid model SMA-ANN is better than ANN (stand-alone) based on the range of statistical criteria. Generally, this methodology yields accurate results with a coefficient of determination of 0.9 and a mean absolute relative error of 0.001. This study can assist local water managers to efficiently manage the present water system and plan extensions to accommodate the increasing water demand

Efficacy of Electrocoagulation Treatment for the abatement of Heavy Metals: An Overview of Critical Processing Factors, Kinetic Models and Cost Analysis

The electrocoagulation (EC) process introduces coagulants by electrochemical means, and is widely adopted for removing heavy metals, besides other contaminants, such as organic pollutants, suspended and dissolved solids, colloidal materials, etc. However, its capability can vary significantly, depending on the operating conditions. Although most of the investigations so far are limited at the laboratory level with artificially prepared solutions or industrial effluent lacking full- and field-scale studies, the success of the process depends a lot on optimizing the process variable. It has been found that the current density (typically 1–20 mA/cm2), type of electrode (generally aluminum or iron) and minimum electrolysis time are the key process parameters that influence performance. Furthermore, key mechanisms involved in the EC process, including charge neutralization, reduction-oxidation and precipitation/co-precipitation, are crucial for pollutant abatement. This review presents a detailed study undertaking all significant parameters that play a crucial role in the EC process, its mechanism, and improving the efficiency of this process by optimization of these parameters, along with suitable kinetic models