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Argues in this wideranging paper that the legitimacy of international law depends on the principle that pacts should be respected, reviewing the issues of self‐preservation, proportionality and human rights in relation to this. Focuses on the economic war against terrorism by the USA preeminently, as expressed in the PATRIOT Act and the International Emergency Economic Powers Act and the Anti‐Terrorism and Effective Death Penalty Act. Concludes that the Patriot Act and the Homeland Security Act give the Executive branch of government extraordinary and warlike powers: but wars have an end whereas terrorism does not. Looks at the role of the US Federal courts in the context of national security, proportionality and human rights concerns, and finds them deficient; reports specific cases concerning Iranian resistance movements and their status as regards terrorism, and the Bajkajian, Austin and Alexander cases as regards proportionality.

Begins with the Staff Report to the National Commission on Terrorist Attack on the United States, which indicates the methods used to trace, seize and freeze terrorist assets, and the informal methods used by al‐Qaeda to transfer money. Questions the amount of progress made since September 11 to freeze funds. Focuses on encryption technology and how it allows illegal use of the Internet in the form of cyber laundering and e‐cash, and on the move by terrorists into narcotics production and trafficking ‐ which is defined as nacre‐terrorism. Describes efforts to proscribe cyber crime, including cyber laundering and cyber terrorism, including controls on privacy and encryption. Shows how business corporations can become involved with terrorism, including a case study on tanzanite.

Damage detection of frame structures is important for guaranteeing the safety of people’s lives and property. Sensitivity analysis is an effective method for damage identification. The purpose of this paper is to conduct a sensitivity analysis of beam–column joint rotation angles for frame structures with limited flexural stiffness beams.

First, based on the D-value method and the assumption of inflection points, statically indeterminate frames were transformed to statically determinate structures, and the expressions of beam–column joint rotation angles were derived. Next, the sensitivity coefficients of beam–column joint rotation angles were obtained by taking the derivative of the expressions of beam–column joint rotation angles with respect to the linear stiffness of column. Finally, the expressions of the sensitivity coefficients were verified by a numerical example.

The analytical solutions of the sensitivity coefficients are in good agreement with finite element results. The results show that the beam–column joint rotation angles of damaged column decrease and those of intact columns within the same story increase when damage occurs.

In this study, the sensitivity coefficients of beam–column joint rotation angles with respect to the linear stiffnesses of columns were derived for frame structures. Based on the result of the sensitivity analysis, the relationship between the changes of beam–column joint rotation angles and damaged columns is revealed. The findings provide an important base to further detect damage of frame structures.

Accurate prediction of port cargo throughput within Free Trade Zones (FTZs) can optimize resource allocation, reduce environmental pollution, enhance economic benefits and promote sustainable transportation development.

This paper introduces a novel self-adaptive grey multivariate prediction modeling framework (FARDCGM(1,N)) to forecast port cargo throughput in China, addressing the challenges posed by mutations and time lag characteristics of time series data. The model explores policy-driven mechanisms and autoregressive time lag terms, incorporating policy dummy variables to capture deviations in system development trends. The inclusion of autoregressive time lag terms enhances the model’s ability to describe the evolving system complexity. Additionally, the fractional-order accumulative generation operation effectively captures data features, while the Grey Wolf Optimization algorithm determines optimal nonlinear parameters, enhancing the model’s robustness.

Verification using port cargo throughput forecasts for FTZs in Shanghai, Guangdong and Zhejiang provinces demonstrates the FARDCGM(1,N) model’s remarkable accuracy and stability. This innovative model proves to be an excellent forecasting tool for systematically analyzing port cargo throughput under external interventions and time lag effects.

A novel self-adaptive grey multivariate modeling framework, FARDCGM(1,N), is introduced for accurately predicting port cargo throughput, considering policy-driven impacts and autoregressive time-lag effects. The model incorporates the GWO algorithm for optimal parameter selection, enhancing adaptability to sudden changes. It explores the dual role of policy variables in influencing system trends and the impact of time lag on dynamic response rates, improving the model’s complexity handling.