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This paper aims to evaluate the undergraduate and graduate accounting students’ perceptions of sustainable (or green) information technology (IT) and information system (IS) practices and their contribution to its implementation.

A five-point Likert scale questionnaire was applied to 361 undergraduate and graduate accounting students in Rio de Janeiro (Brazil) in eight higher education institutions (HEIs). Data are analyzed with SPSS.

There is a high perception of importance regarding IT/IS sustainability practices among the accounting students tested, although respondents are not comfortable with predominantly technical IT/IS topics. However, students are divided on the significance of the accountant’s contribution to these practices, confirming that reflection on their future role is still a challenge for them and their HEIs. The female sub-sample attaches significantly greater importance than the male sample to the accountant role in the implementation of green IT practices.

The authors have proposed a novel integrative framework of IT/IS theories related to sustainability and accounting, and how accounting professionals could participate in the “neutral arena” of the education for sustainable development (SD).

Findings could be useful for educators and coordinators of sustainability of IT/IS in accounting courses, stimulating brainstorming on the accountant’s role in assisting organizations in green IT/IS strategies, best practice and implementation.

This study makes an original contribution to the research base of SD in HEIs. The lack of awareness identified in the study could be elaborated to stimulate discussion about the central role of the accountant in SD processes within organizations.

The purpose of this paper is to apply the Steady State Kalman Filter for temperature measurements of tissues via magnetic resonance thermometry. Instead of using classical direct inversion, a methodology is proposed that couples the magnetic resonance thermometry with the bioheat transfer problem and the local temperatures can be identified through the solution of a state estimation problem.

Heat transfer in the tissues is given by Pennes’ bioheat transfer model, while the Proton Resonance Frequency (PRF)-Shift technique is used for the magnetic resonance thermometry. The problem of measuring the transient temperature field of tissues is recast as a state estimation problem and is solved through the Steady-State Kalman filter. Noisy synthetic measurements are used for testing the proposed methodology.

The proposed approach is more accurate for recovering the local transient temperatures from the noisy PRF-Shift measurements than the direct data inversion. The methodology used here can be applied in real time due to the reduced computational cost. Idealized test cases are examined that include the actual geometry of a forearm.

The solution of the state estimation problem recovers the temperature variations in the region more accurately than the direct inversion. Besides that, the estimation of the temperature field in the region was possible with the solution of the state estimation problem via the Steady-State Kalman filter, but not with the direct inversion.

The recursive equations of the Steady-State Kalman filter can be calculated in computational times smaller than the supposed physical times, thus demonstrating that the present approach can be used for real-time applications, such as in control of the heating source in the hyperthermia treatment of cancer.

The original and novel contributions of the manuscript include: formulation of the PRF-Shift thermometry as a state estimation problem, which results in reduced uncertainties of the temperature variation as compared to the classical direct inversion; estimation of the actual temperature in the region with the solution of the state estimation problem, which is not possible with the direct inversion that is limited to the identification of the temperature variation; solution of the state estimation problem with the Steady-State Kalman filter, which allows for fast computations and real-time calculations.