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The purpose of this study is to explore the relationship between gender disparities in rural education attainments and agricultural landownership (ALO) in Sub-Sahara Africa with Sustainable Development Goal (SDG) perspective.

This study uses SDG indicators interactions and pairwise correlation analysis.

There is a significant negative association between gender disparities in rural education attainments and ALO in Sub-Sahara Africa. Such negative relationship is not influenced by national economic development and living standards.

The data is limited with 16 Sub-Sahara African countries, and as this is an early output of a number of follow-up studies in the author’s plan, the methodology is relatively simple.

Reducing gender disparity in rural Sub-Sahara Africa especially in ALO requires more integrated approaches which also address other aspects of sustainable development. This is particularly the situation because of the strong male-favored customary practices in rural Sub-Sahara Africa. The prioritization of different dimensions of sustainable development is also important in Sub-Sahara Africa.

Strong awareness of SDGs is important. Further efforts in collecting data for and use data of sustainable development, especially the SDGs, are essential. Emerging trend of studying the interactions across SDGs reflects the future direction of relevant fields.

This paper has high originality because it is an early-stage research in the SDG interactions in Sub-Sahara African countries with the perspective of gender, gender disparity, Sub-Sahara Africa, SDGs, ALO and rural education attainments. This paper has both academic and practical values because of its innovative research thoughts and policy-oriented implications.

This paper explores the linkage of digital infrastructure to the cost of debt.

This study uses the implementation of the “Broadband China” policy that improves digital infrastructure as an exogenous shock and exploits the difference-in-differences method (DID).

Empirical analyses show that digital infrastructure leads to increased firms’ borrowing costs, which is robust to several robustness checks. In addition, we find that this unfavourable effect can be attributed to intensified market competition led by digital infrastructure construction. Cross-sectional analysis shows that this effect is greater for non-SOEs and smaller firms. Finally, we offer additional evidence of the unfavourable effect by showing that digital infrastructure construction leads to decreased fundamentals.

Our paper unveils how digital infrastructure construction affects firms’ business strategy in using private debts and extends the determinants of firms’ borrowing costs.

The purpose of this paper is to review available technologies, analyse their features, propose a new approach of 3D sand mould printing based on line forming, introduce the manufacturing principle and show advantages of this approach, especially for larger parts with large Z steps in the build, such as 2 mm stepwise.

This paper introduces 3D sand mould printing, compares and analyses technological process and existing fabrication approaches among available technologies first. Then, a new approach of 3D sand mould printing is proposed to improve build speed. In addition, the proposed system will be analysed or benchmarked against existing systems.

A new approach based on line forming of sand mould printing is put forward by reviewing and analysing available technologies, to improve build speed from the aspect of basic moulding movement instead of optimization of moulding methods and process parameters. The theoretical calculation and analysis shows that build speed can be improved greatly, and it is more suitable for the manufacture of large-scale casting’s sand mould when considering dimensional accuracy and printing error, as well as uniformity of each layer.

The specific implement scheme of line forming and nozzle’s specific structure of this new approach need further study.

Much higher build speed of 3D sand mould printing with new approach brings evident implication for moulds companies and manufacturing industry, having a far-reaching influence on the development of national economy.

This paper reviews available technologies and presents a new approach of 3D sand mould printing for the first time. Analysis of the new approach shows that this new method of sand mould printing can boost build speed greatly. So, its application prospect is great.

In response to shortages in personal protective equipment (PPE) during the COVID-19 pandemic, makers, community groups and manufacturers around the world utilised 3D printing to fabricate items, including face shields and face masks for healthcare workers and the broader community. In reaction to both local and global needs, numerous designs emerged and were shared online. In this paper, 37 face shields and 31 face masks suitable for fused filament fabrication were analysed from a fabrication perspective, documenting factors such as filament use, time to print and geometric qualities. 3D print times for similar designs varied by several hours, meaning some designs could be produced in higher volumes. Overall, the results show that face shields were approximately twice as fast to 3D print compared to face masks and used approximately half as much filament. Additionally, a face shield typically required 1.5 parts to be 3D printed, whereas face masks required five 3D printed parts. However, by quantifying the print times, filament use, 3D printing costs, part dimensions, number of parts and total volume of each design, the wide variations within each product category could be tracked and evaluated. This data and objective analysis will help makers, manufacturers, regulatory bodies and researchers consolidate the 3D printing response to COVID-19 and optimise the ongoing strategy to combat supply chain shortages now and in future healthcare crises.

Artificial intelligence (AI) models are demonstrating day by day that they can find long-term solutions to improve wastewater treatment efficiency. Artificial neural networks (ANNs) are one of the most important of these models, and they are increasingly being used to forecast water resource variables. The goal of this study was to create an ANN model to estimate the removal efficiency of biological oxygen demand (BOD), total nitrogen (TN), total phosphorus (TP) and total suspended solids (TSS) at the effluent of various primary and secondary treatment methods in a wastewater treatment plant (WWTP).

The MATLAB App Designer model was used to generate the data set. Various combinations of wastewater quality data, such as temperature(T), TN, TP and hydraulic retention time (HRT) are used as inputs into the ANN to assess the degree of effect of each of these variables on BOD, TN, TP and TSS removal efficiency. Two of the models reflect two different types of primary treatment, while the other nine models represent different types of subsequent treatment. The ANN model’s findings are compared to the MATLAB App Designer model. For evaluating model performance, mean square error (MSE) and coefficient of determination statistics (R2) are utilized as comparative metrics.

For both training and testing, the R values for the ANN models were greater than 0.99. Based on the comparisons, it was discovered that the ANN model can be used to estimate the removal efficiency of BOD, TN, TP and TSS in WWTP and that the ANN model produces very similar and satisfying results to the APPDESIGNER model. The R-value (Correlation coefficient) of 0.9909 and the MSE of 5.962 indicate that the model is accurate. Because of the many benefits of the ANN models used in this study, it has a lot of potential as a general modeling tool for a range of other complicated process systems that are difficult to solve using conventional modeling techniques.

The objective of this study was to develop an ANN model that could be used to estimate the removal efficiency of pollutants such as BOD, TN, TP and TSS at the effluent of various primary and secondary treatment methods in a WWTP. In the future, the ANN could be used to design a new WWTP and forecast the removal efficiency of pollutants.