Preserving roads involves regularly evaluating government policy through advanced assessments using vehicles with specialized capabilities and high-resolution scanning technology. However, the cost is often not affordable due to a limited budget. Road surface surveys are highly expected to use low-cost tools and methods capable of being carried out comprehensively. This research aims to create a road damage detection application system by identifying and qualifying precisely the type of damage that occurs using a single CNN to detect objects in real time. Especially for the type of pothole, further analysis is to measure the volume or dimensions of the hole with a LiDAR smartphone. The study area is 38 province’s representative area in Indonesia. This research resulted in the iRodd (intelligent-road damage detection) for detection and classification per type of road damage in real-time object detection. Especially for the type of pothole damage, further analysis is carried out to obtain a damage volume calculation model and 3D visualization. The resulting iRodd model contributes in terms of completion (analyzing the parameters needed to be related to the road damage detection process), accuracy (precision), reliability (the level of reliability has high precision and is still within the limits of cost-effective), correct prediction (four-fifths of all positive objects that should be identified), efficient (object detection models strike a good balance between being able to recognize objects with high precision and being able to capture most objects that would otherwise be detected-high sensitivity), meanwhile, in the calculation of pothole volume, where the precision level is established according to the volume error value, comparing the derived data to the reference data with an average error of 5.35% with an RMSE value of 6.47 mm. The advanced iRodd model with LiDAR smartphone devices can present visualization and precision in efficiently calculating the volume of asphalt damage (potholes).

Proposed herein is an environment-friendly method to realize oil/water separation. Nylon mesh is exposed to atmospheric pressure plasma for surface modification, by which micro/nano structures and oxygen-containing groups are created on nylon fibers. Consequently, the functionalized mesh possesses superhydrophilicity in air and thus superoleophobicity underwater. The water pre-wetted mesh is then used to separate oil/water mixtures with the separation efficiency above 97.5% for various oil/water mixtures. Results also demonstrate that the functionalized nylon mesh has excellent recyclability and durability in terms of oil/water separation. Additionally, polyurethane sponge slice and polyester fabric are also functionalized and employed to separate oil/water mixtures efficiently, demonstrating the wide suitability of this method. This simple, green and highly efficient method overcomes a nontrivial hurdle for environmentally-safe separation of oil/water mixtures, and offers insights into the design of advanced materials for practical oil/water separation.

In the current context of China’s vigorous development of its high-speed rail (HSR) network to accelerate the realization of connectivity, which is the aim of the “Belt and Road” initiative, it is crucial to study how the specific opening of HSR enhances enterprise human capital investment efficiency. Using a multiple-time-point difference-in-differences (DID) regression model, we empirically study data from listed Chinese companies. An HSR opening can promote the efficiency of an enterprise’s human capital investment. We further explore the relationship between HSR and a company’s human capital investment, by considering the moderating effects of firm property rights and foreign shareholding. Our findings indicate that these factors can enhance the impact of HSR on the efficiency of firms’ investments in human capital. Finally, to ensure the reliability of our experimental findings, we employed a combination of propensity score matching and the DID methodology. The findings of this study offer empirical evidence that can inform enterprise management strategies and provide valuable insights for policymakers seeking to promote economic growth.

This paper examines the effect of governance in Sub-Saharan African (SSA) countries. Specifically, this study investigates (i) the interacting impact of government efficiency, regulatory quality, and the rule of law alongside other socioeconomic variables to determine foreign capital inflow (FCI) based on each economic SSA bloc; and (ii) the characteristic drivers of FCI, impacting economic growth in the SSA countries. Descriptive statistics, static models, least square dummy variables (LSDVs) and the dynamic system general method of moment (GMM) were employed as the study’s estimating techniques. Based on the result of the LSDV, food security and the rule of law significantly impact FCI in the sub-economic blocs in the region. Only six countries across the four economic blocs responded to food security and the rule of law in the model. The dynamic system-GMM provided evidence of five socioeconomic variables and three governance variables contributing to FCI. The findings revealed (i) regulatory quality and the rule of law are governance variables that significantly impacted FCI; and (ii) food security failed to significantly impact FCI in the SSA region. However, inflation, life expectancy, the human capital index, exchange rate and gross domestic product (GDP) growth impacted FCI significantly. In the aggregate, inflation, regulatory quality, exchange rate and the human capital index exhibited positive relationships, while other variables such as life expectancy, government effectiveness and the rule of law appeared significant but inversely impacted FCI in the SSA region. The key policy implication recommendation from this study is that a good legal framework could moderate the flow of foreign capital in favour of growth as it creates a strong foundation for sustainable economic development in the region.

The goal of this research is to focus on the impact of HR agility on Jordanian pharmaceutical manufacturing companies’ innovative performance. The study population of the study consists of managers at different levels of pharmaceutical companies listed on the Amman Stock Exchange. Convenience sample consists of 450 questionnaires was sent. PLS-SEM was employed in this work to assess the measurement model and to verify the study theories. The findings revealed that human resource agility has a positive impact on innovative performance. The implications of the research as this analysis have shown, a variety of factors influence the agility of human resources, allowing organizations to create and implement strategies that lead to better adaptability in a rapidly changing environment. Significant ramifications could arise from this review for organizations that prioritize fostering employee confidence, refining strategies to gain a competitive edge, enhancing employee skills, and adapting to both internal and external shifts in the work environment.