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Improving the competitiveness of East Africa's rice industries necessitates increased and viable production of rice of the quality desired by consumers. This paper aims to understand consumer preferences for rice quality attributes in Uganda and Kenya to inform the countries' rice breeding programs and value chain development interventions.

Rice samples are obtained from retail markets in various districts/counties across the two countries. The samples are analyzed in a grain quality laboratory for the rice's physicochemical characteristics and the resulting data are used to non-parametrically estimate hedonic price functions. District/county dummies are included to account for potential heterogeneity in consumer preferences.

Ugandan consumers are willing to pay a price premium for rice with a relatively high proportion of intact grains, but the consumers discount chalkiness. Kenyan consumers discount high amylose content and impurities. There is evidence of heterogeneity in consumer preferences for rice in Mbale, Butaleja and Arua districts of Uganda and in Kericho and Busia counties of Kenya.

The study makes a novel contribution to the literature on consumer preferences for rice in East Africa by applying a hedonic pricing model to the data generated from a laboratory analysis of the physicochemical characteristics of rice samples obtained from the market. Rather than base our analysis on consumers' subjective sensory assessment of the quality characteristics of rice, standard laboratory methods are used to generate the data, which enables a more objective assessment of the relationship between market prices and the quantities of attributes present in the rice samples.

This paper aims to study the influence of microparticles on the surface cavitation behavior of 2Cr3WMoV steel; microparticle suspensions of different concentration, particle size, material and shape were prepared based on ultrasonic vibration cavitation experimental device.

2Cr3WMoV steel was taken as the research object for ultrasonic cavitation experiment. The morphology, quantity and distribution of cavitation pits were observed and analyzed by metallographic microscope and scanning electron microscope.

The study findings showed that the surface cavitation process produced pinhole cavitation pits on the surface of 2Cr3WMoV steel. High temperature in the process led to oxidation and carbon precipitation on the material surface, resulting in the “rainbow ring” cavitation morphology. Both the concentration and size of microparticles affected the number of pits on the material surface. When the concentration of microparticles was 1 g/L, the number of pits reached the maximum, and when the size of microparticles was 20 µm, the number of pits reached the minimum. The microparticles of Fe3O4, Al2O3, SiC and SiO2 all increased the number of pits on the surface of 2Cr3WMoV steel. In addition, the distribution of pits of spherical microparticles was more concentrated than that of irregularly shaped microparticles in turbidity.

Most of the current studies have not systematically focused on the effect of each factor of microparticles on the cavitation behavior when they act separately, and the results of the studies are more scattered and varied. At the same time, it has not been found to carry out the study of microparticle cavitation with 2Cr3WMoV steel as the research material, and there is a lack of relevant cavitation morphology and experimental data.

The aim of this study is to report the effect of different content of calcium oxide on the process of electromelting magnesia.

The process of molten magnesia was analyzed by finite element simulation and proved by scanning electron microscope.

The results show that with the increase of CaO content, the maximum temperature appreciation increases from 3,616°C To 3,729°C, showing an approximate nonlinear evolution. Low thermal conductivity and low specific heat of CaO result in higher temperature. With the increase of CaO content and temperature, the maximum flow velocity of MgO slag increases from 0.043 to 1.34 mm/s. Under different initial CaO contents, the distribution trend of CaO volume fraction is basically the same, and the CaO volume fraction is evenly distributed between 50 and 225 mm in the furnace.

The influence of different contents of impurity calcium oxide on the process of electromelting magnesia was analyzed and a theoretical system was established.

The purpose of this study to investigate the organized porous network zinc (OPNZ) scaffolds. Their mechanical characteristics, surface roughness and fracture mechanism were assessed in relation to their structural properties. The prospects of fused deposition modeling (FDM) for printing metal scaffolds via rapid tooling have also been studied.

Zn scaffolds with different pore and strut sizes were manufactured via the rapid tooling method. This method is a multistep process that begins with the 3D printing of a polymer template. Later, a paraffin template was obtained from the prepared polymer template. Finally, this paraffin template was used to fabricate the Zn scaffold using microwave sintering. The characterization of prepared Zn samples involved structural characterization, microstructural study, surface roughness testing and compression testing. Moreover, based on the Gibson–Ashby model analysis, the model equations’ constant values were evaluated, which can help in predicting the mechanical properties of Zn scaffolds.

The scanning electron microscopy study confirmed that the fabricated sample pores were open and interconnected. The X-ray diffraction analysis revealed that the Zn scaffold contained hexagonal closed-packed Zn peaks related to the a-Zn phase, validating that scaffolds were free from contamination and impurity. The range for ultimate compressive strength, compressive modulus and plateau stresses for Zn samples were found to be 6.75–39 MPa, 0.14–3.51 GPa and 1.85–12.6 MPa by adjusting their porosity, which are comparable with the cancellous bones. The average roughness value for the Zn scaffolds was found to be 1.86 µm.

This research work can widen the scope for extrusion-based FDM printers for fabricating biocompatible and biodegradable metal Zn scaffolds. This study also revealed the effects of scaffold structural properties like porosity, pore and strut size effect on their mechanical characteristics in view of tissue engineering applications.

This paper aims to better control the mechanical properties and functional properties of NiTi alloy.

NiTi alloy samples with equal atomic ratio were formed by selective laser melting (SLM). X-ray diffraction (XRD), differential scanning calorimetry (DSC), scanning electron microscopy and tensile testing methods were used to study the effects of different laser power and scanning speed on the densification behavior, phase transformation characteristics and mechanical properties of NiTi alloy.

Compared with the laser power, the variation of the keyhole effect caused by the change of scanning speed is more intense, which has a greater effect on the densification behavior of SLM NiTi alloy. The effect of the laser power on the phase transition temperature is small. The increase of scanning speed weakens the burning degree of Ni element, so phase transition temperature decreases. The results of DSC test and tensile test show that the scanning velocity can significantly change the phase transition temperature, martensite twins reorientation and stress–strain behavior of SLM NiTi alloy.

This study provides a potential method to regulate the mechanical properties and functional properties of NiTi shape memory alloy in the future and NiTi alloys formed by SLM with good elongation were obtained because the Supercellular crystal structure formed during the nonequilibrium solidification of SLM and the superfine precipitates dispersed in the alloy prevented the dislocation formation.

The purpose of this paper is to identify the root cause of low yield problems in the semiconductor manufacturing process using sensor data continuously collected from manufacturing equipment and describe the process environment in the equipment.

This paper proposes a sensor data mining process based on the sequential modeling of random forests for low yield diagnosis. The process consists of sequential steps: problem definition, data preparation, excursion time and critical sensor identification, data visualization and root cause identification.

A case study is conducted using real-world data collected from a semiconductor manufacturer in South Korea to demonstrate the effectiveness of the diagnosis process. The proposed model successfully identified the excursion time and critical sensors previously identified by domain engineers using costly manual examination.

The proposed procedure helps domain engineers narrow down the excursion time and critical sensors from the massive sensor data. The procedure's outcome is highly interpretable, informative and easy to visualize.

Completing Right-of-Way (ROW) acquisition process on schedule is critical to avoid delays and cost overruns on transportation projects. However, transportation agencies face challenges in accurately forecasting ROW acquisition timelines in the early stage of projects due to complex nature of acquisition process and limited design information. There is a need of improving accuracy of estimating ROW acquisition duration during the early phase of project development and quantitatively identifying risk factors affecting the duration.

The quantitative research methodology used to develop the forecasting model includes an ensemble algorithm based on decision tree and adaptive boosting techniques. A dataset of Georgia Department of Transportation projects held from 2010 to 2019 is utilized to demonstrate building the forecasting model. Furthermore, sensitivity analysis is performed to identify critical drivers of ROW acquisition durations.

The forecasting model developed in this research achieves a high accuracy to predict ROW durations by explaining 74% of the variance in ROW acquisition durations using project features, which is outperforming single regression tree, multiple linear regression and support vector machine. Moreover, number of parcels, average cost estimation per parcel, length of projects, number of condemnations, number of relocations and type of work are found to be influential factors as drivers of ROW acquisition duration.

This research contributes to the state of knowledge in estimating ROW acquisition timeline through (1) developing a novel machine learning model to accurately estimate ROW acquisition timelines, and (2) identifying drivers (i.e. risk factors) of ROW acquisition durations. The findings of this research will provide transportation agencies with insights on how to improve practices in scheduling ROW acquisition process.

Numerous metals can be processed using the additive manufacturing process laser-based powder bed fusion of metals (PBF-LB/M, ISO/ASTM 52900). The main advantages of additive manufacturing technologies are the high degree of design freedom and the cost-effective implementation of lightweight structures. This could be profitable for gears with increased power density, combining reduced mass with considerable material strength. Current research on additively manufactured gears is focused on developing lightweight structures but is seldom accompanied by simulations and even less by mechanical testing. There has been very little research into the mechanical and material properties of additively manufactured gears. The purpose of this study is to investigate the behavior of lightweight structures in additively manufactured gears under static loads.

This research identifies the static load-carrying capacity of helical gears with different lightweight structures produced by PBF-LB/M with the case hardening steel 16MnCr5. A static gear loading test rig with a maximum torque at the pinion of T₁ = 1200 Nm is used. Further focus is set on analyzing material properties such as the relative density, microstructure, hardness depth profile and chemical composition.

All additively manufactured gear variants show no failure or plastic deformation at the maximum test load. The shaft hub connection, the lightweight hub designs and the gearing itself are stable and intact regarding their form and function. The identified material characteristics are comparable to conventionally manufactured gears (wrought and machined), but also some particularities were observed.

This research demonstrates the mechanical strength of lightweight structures in gears. Future research needs to consider the dynamic load-carrying capacity of additively manufactured gears.

The high specific strength makes magnesium alloys have a wide range of applications in aerospace, military, automotive, marine and construction industries. However, its poor corrosion resistance and weldability have limited its development and application. Friction stir welding (FSW) can effectively avoid the defects of fusion welding. However, the microstructure, mechanical properties and corrosion behavior of FSW joints in magnesium alloys vary among different regions. The purpose of this paper is to review the corrosion of magnesium alloy FSW joints, and to summarize the protection technology of welded joints.

The corrosion of magnesium alloy FSW joints includes electrochemical corrosion and stress corrosion. This paper summarizes corrosion protection techniques for magnesium alloys FSW joints, focusing on composition, microstructure changes and surface treatment methods.

Currently, this research is mainly focused on enhancing the corrosion resistance of magnesium alloy FSW joints by changing compositions, structural modifications and surface coating technologies. Refinement of the grains can be achieved by adjusting welding process parameters, which in turn minimizes the effects of the second phase on the alloy’s corrosion resistance.

This paper presents a comprehensive review on the corrosion and protection of magnesium alloys FSW joints, covering the latest research advancements and practical applications. It aims to equip researchers with a better insight into the field and inspire new studies on this topic.

The purpose of this study is to explore how a time-varying electromagnetic stirring (EMS) affects the fluid flow and solidification behavior in a slab caster continuous casting mold. Further, the study of inclusion movements in the mold is carried out under the effect of a time-varying electromagnetic field.

A three-dimensional coupled numerical model of solidification and magnetohydrodynamics has been developed for slab caster mold to investigate the inclusions transport by discrete phase model with the use of user-defined functions. Enthalpy porosity and the Lagrangian approach are applied to analyze the behavior of solidification and inclusion.

The study shows that the magnetic field density distribution has a radial symmetry in relation to the stirrer’s center. As the EMS current intensity increases, the strength of the lower recirculation zone gradually decreases and nearly disappears at higher intensities. Additionally, the area of localized remelting zone expands in the solidification front with rising current intensity. The morphology of inclusions and EMS current intensity have a significant impact on the behavior and movement of inclusions within the molten steel.

By using the model, one can optimize the EMS parameter to enhance the quality of steel casting through the elimination of impurities and by improving the microstructure of cast that mainly depend on solidification and flow patterns of molten steel.

Until now, the use of time-varying EMS in the slab caster mold to study solidification and inclusion behavior has not been explored.