This paper provides a comparative perspective on infrastructure provision in developing Asia's three largest countries: China, India, and Indonesia. It discusses their achievements and shortfalls in providing network infrastructure (energy, transport, water, and telecommunications) over the past two decades. It documents how three quite distinct development paths—and very different levels of national saving and investment—were manifested in different trajectories of infrastructure provision. The paper then describes the institutional, economic, and policy factors that enabled or hindered progress in providing infrastructure. Here, contrasting levels of centralization of planning played a key role, as did countries’ differing abilities to mobilize infrastructure-related revenue streams such as user charges and land value capture. The paper then assesses future challenges for the three countries in providing infrastructure in a more integrated and sustainable way, and links these challenges with the global development agenda to which the three countries have committed. The concluding recommendations hope to provide a platform for further policy and research dialogue.

The presence of a crisis has consistently been an inherent aspect of the Supply Chain, mostly as a result of the substantial number of stakeholders involved and the intricate dynamics of their relationships. The objective of this study is to assess the potential of Big Data as a tool for planning risk management in Supply Chain crises. Specifically, it focuses on using computational analysis and modeling to quantitatively analyze financial risks. The “Web of Science—Elsevier” database was employed to fulfill the aims of this work by identifying relevant papers for the investigation. The data were inputted into VOS viewer, a software application used to construct and visualize bibliometric networks for subsequent research. Data processing indicates a significant rise in the quantity of publications and citations related to the topic over the past five years. Moreover, the study encompasses a wide variety of crisis types, with the COVID-19 pandemic being the most significant. Nevertheless, the cooperation among institutions is evidently limited. This has limited the theoretical progress of the field and may have contributed to the ambiguity in understanding the research issue.

Gout is an arthritis characterized by the deposition of sodium monoacid crystals in the synovial membrane, articular cartilage, and periarticular tissues that leads to an inflamatory process. In most cases, the diagnosis is established by clinical criteria and analysis of the synovial fluid for MSU crystals. However, gout may manifest in atypical ways and make diagnosis difficult. In these situations, imaging studies play a fundamental role in helping to confirm the diagnosis or even exclude other differential diagnoses. Conventional radiography is still the most commonly used method in the follow-up of these patients, but it is a very insensitive test, because it only detects late changes. In recent years, advances in imaging methods have emerged in relation to gout. Ultrasound has proven to be a highly accurate test in the diagnosis of gout, identifying MSU deposits in articular cartilage and periarticular tissues, and detecting and characterizing tophi, tendinopathies, and tophi enthesopathies. Computed tomography is an excellent exam for the detection of bone erosions and evaluation of spinal involvement. Dual-energy computed tomography, a new method that provides information on the chemical composition of tissues, allows identification of MSU deposits with high accuracy. MRI can be useful in the evaluation of deep tissues not accessible by ultrasound. In addition to diagnosis, with the emergence of drugs that aim to reduce the tophaceous burden, imaging examinations become a useful tool in the follow-up treatment of gout patients.

This study focuses on the use of the Soil and Water Assessment Tool (SWAT) model for water budgeting and resource planning in Oued Cherraa basin. The combination of hydrological models such as SWAT with reliable meteorological data makes it possible to simulate water availability and manage water resources. In this study, the SWAT model was employed to estimate hydrological parameters in the Oued Cherra basin, utilizing meteorological data (2012–2020) sourced from the Moulouya Hydraulic Basin Agency (ABHM). The hydrology of the basin is therefore represented by point data from the Tazarhine hydrological station for the 2009–2020 period. In order to optimize the accuracy of a specific model, namely SWAT-CUP, a calibration and validation process was carried out on the aforementioned model using observed flow data. The SUFI-2 algorithm was utilized in this process, with the aim of enhancing its precision. The performance of the model was then evaluated using statistical parameters, with particular attention being given to Nash-Sutcliffe efficiency (NSE) and coefficient of determination (R²). The NSE values for the study were 0.58 for calibration and 0.60 for validation, while the corresponding R² values were 0.66 and 0.63. The study examined 16 hydrological parameters for Oued Cherra, determining that evapotranspiration accounted for 89% of the annual rainfall, while surface runoff constituted only 6%. It also showed that groundwater recharge was pretty much negligible. This emphasized how important it is to manage water resources effectively. The calibrated SWAT model replicated flow patterns pretty well, which gave us some valuable insights into the water balance and availability. The study’s primary conclusions were that surface water is limited and that shallow aquifers are a really important source of water storage, especially for irrigation during droughts.