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A fast calculation method was used to obtain the spectral optical properties of human normal and pathological (chromophobe renal cell carcinoma) kidney tissues. Using total transmittance, total reflectance and collimated transmittance spectra acquired from ex vivo kidney samples, the spectral optical properties of both tissues, namely the absorption, the scattering and the reduced scattering coefficients, as well as the scattering anisotropy, dispersion and light penetration depth, were calculated between 200 and 1000 nm. Analysis of the mean absorption coefficient spectra of the kidney tissues showed that both contain melanin and lipofuscin, and that 83 % of the melanin in the normal kidney converts into lipofuscin in the pathological kidney.

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To forestall future financial crises, risk governance has been embraced as a line of defense. Therefore, this paper seeks to synthesize the risk governance literature, identifying gaps, and suggesting direction for future research, through a systematic literature review (SLR). Analyzing 151 papers from the Scopus and Web of Science databases, this paper finds a steady increase in academic work on risk governance. Using the theory, context, characteristics, and methodology (TCCM) framework, the study emphasizes the importance of chief risk officers, geographical context coverage, and effectiveness and regulation of risk governance. Methodologically, endogeneity issues are a major concern for researchers, agency theory (AT) being the most popular theory used. Finally, moderating and mediating variables that affect risk governance are identified as important but under-explored. While providing practitioners and policymakers with a framework, empirical testing is encouraged. The study contributes to SDG Goal 8, Target 10 of strengthening financial institutions and promoting a resilient financial system.

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Multiple Sclerosis is one of the most common diseases of the central nervous system that affects millions of people worldwide. The prediction of this disease is considered a challenge since the symptoms are highly variable as the disease worsens and, as such, it has emerged as a topic that artificial intelligence scientists have tried to challenge. With the goal of providing a brief review that may serve as a starting point for future researchers on such a deep field, this paper puts forward a summary of artificial intelligence applications for Multiple Sclerosis evaluation and diagnosis. It includes a detailed recap of what Multiple Sclerosis is, the connections between artificial intelligence and the human brain, and a description of the main proposals in this field. It also concludes what the most reliable methods are at the present time, discussing approaches that achieve accuracy values up to 98.8%. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.