Path-loss propagation models are useful in radio communications for the prediction of signal's coverage area, link's design and power budget. They are equally used for radio channel characterization to accurately predict television coverage, interference analysis and ensure coexistence between the primary service providers and secondary users (through frequency re-use). One of the challenges with the application of a predictive path loss model for any environment other than the one it was developed for is the issue of high prediction errors. This is due to their high dependence on environmental complexity and terrain. In this paper, we investigated the error bounds of eight empirical path loss models to evaluate their reliability of predicting path losses on the UHF band in Ekiti State, South West Nigeria. Measurement of the signal strength for the UHF channel 41 (631.25MHz), Television Broadcasting Station at Ado-Ekiti, was carried out via major routes spanning through the Urban and Suburban areas of the State, using the station as reference. The signal strength values were converted to path losses and compared with predictions of eight selected models. The prediction error, relative error, root mean square error (RMSE), spread corrected mean square error (SC-RMSE), skewness and the normalized error probability density function metrics was calculated to determine the error bound which was used to validate the best predictive model for the routes under consideration. The results of this investigation show that no single model gives an accurate prediction consistently based on the evaluating metrics. However, the Electronic Communication Committee (ECC) 33 model provides better values for the overall metrics considered with RMSE values of 8.48 dB and 9.62 dB (between it and measured values) for Ekiti Suburban and Urban routes respectively. Therefore, optimizing ECC 33 model will bring the RMSE values to the standard acceptable range for both sub -urban and urban routes. The significance of this finding is that ECC 33 model has the least prediction error compared to other selected models and by extension the closest value to the measured values. This validates it to be suitable for the prediction of path losses on the UHF band over the study area.

Three‐dimensional (3D) printing has promising application potentials in improving food product manufacturing, increasingly helping in simplifying the supply chain, as well as expanding the utilization of food materials. To further understand the current situation of 3D food printing in providing food engineering solutions with customized design, the authors checked recently conducted reviews and considered the extrusion‐based type to deserve additional literature synthesis. In this perspective review, therefore, we scoped the potentials of 3D extrusion‐based printing in resolving food processing challenges. The evolving trends of 3D food printing technologies, fundamentals of extrusion processes, food printer, and printing enhancement, (extrusion) food systems, algorithm development, and associated food rheological properties were discussed. The (extrusion) mechanism in 3D food printing involving some essentials for material flow and configuration, its uniqueness, suitability, and printability to food materials, (food material) types in the extrusion‐based (3D food printing), together with essential food properties and their dynamics were also discussed. Additionally, some bottlenecks/concerns still applicable to extrusion‐based 3D food printing were brainstormed. Developing enhanced calibrating techniques for 3D printing materials, and designing better methods of integrating data will help improve the algorithmic representations of printed foods. Rheological complexities associated with the extrusion‐based 3D food printing require both industry and researchers to work together so as to tackle the (rheological) shifts that make (food) materials unsuitable. Practical Applications As a processing technology with digital additive manufacturing methodology, 3D food printing over the decades has evolved greatly with the extrusion‐based type increasingly studied. This perspective review scoped the potentials of 3D extrusion‐based printing in resolving food processing challenges. In this work, we demonstrated how this extrusion‐based technique increasingly contributes to situate the 3D food printing as among innovative technologies with an upscale dimension. To fully embrace the extrusion‐based 3D printing, the food industry needs to primarily understand the potentials this technology would provide in enhancing food material properties/types.

In this study, soil resistivity measurements and water quality analysis were carried out as a means of assessing the impact of Ile-Oluji dumpsite on the environment. Resistivity measurements were made on radially established traverses adopting 2D dipole-dipole profiling and Schlumberger depth sounding techniques. Physicochemical and microbial analyses for parameters including color, turbidity, temperature, pH, total dissolved solids (TDS), conductivity, hardness, major ions, total coliform, and E.coli were performed on surface and groundwater samples. The underlying geologic layers were topsoil, laterite, weathered layer, partly weathered/fractured basement, and fresh bedrock. Indication of subsoil contamination and by extension the groundwater was observed from contrasting geoelectric characteristics of the area within and outside the waste dump. Relatively low resistivities (< 78 Ωm) defined the leachate contaminated zone to depth extent of > 25 m and a distance > 50 m beyond the waste boundary, including a nearby stream. Leachate migration was aided by the surface topographic dip and groundwater flow in the north and northeastern directions and through basement fractures/faults. The concentrations of major pollution indicators like conductivity, TDS, hardness, chloride, magnesium, calcium, potassium, E.coli exceeded standard thresholds for potable water quality and were at least 10 times more within the contaminated zone than in samples at control locations. All the water samples were fecal contaminated having E.coli of 6–95 CFU/100 ml counts. The results showed that the environment around the dumpsite had been significantly polluted and the level of pollution raised an intermediate to high public health safety risk that requires high action priority.

Exposure level of radiation and heavy metal concentration were examined in Agricultural research farm, Federal Polytechnic Ile-Oluji and environs using a gamma scout survey meter and Atomic Absorption Spectroscopy respectively. The exposure level was determined by placing a survey meter 1 m above the soil level in each sampling point. The mean value of exposure level was 0.5113 µSv hr-1which was higher than the recommended limit of 0.11µSv hr-1 [1]. For the heavy metal values, there is a general increase in the concentration from Zn metal to Pb in the order Zn>Fe>Cu>Cr>Cd>As>Pb. The highest concentration of heavy metals was recorded for Zn while Pb metal has the lowest heavy metal concentration for the soil samples. In the plant samples however, the trend of heavy metals is as Cu>Zn>Fe>Cr>Cd>As>Pb. The highest concentration of the metals is recorded for Cu metal while Pb has the lowest value.Concentrations of Cd, Cr, Zn and Fe were all above permissible levels in plant materials while only Pb and As have lower values than the safety limit.The transfer factor from soil to plant is greater than 0.5 in some of the areas indicating a high risk through the food chain to man. Similarly, most of the metals have transfer factors greater than 0.2 which is also an indication of contamination of the Cassava plant in the study area.