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Corruption has gained attention around the world as a prominent issue. This is because corruption has greatly affected several countries. Following the exploration of various definitions and types of corruption, this thesis focuses on two efforts to rein in “grand corruption”, also known as executive corruption. The thesis is informed by existing theories of corruption as well as anti-corruption agencies and then situates Peru’s experience with corruption in its theoretical context and its broader Latin American context. This work conducts a comparative analysis and follows a process-tracing approach to examine and evaluate Peru’s recent anti-corruption agencies and their effectiveness in holding politically powerful people to account. An analysis is made regarding the efforts of two presidents who claimed to be committed to battling corruption; however, each had different motivations and operated under different circumstances. These differences are showcased in the following influential pillars: institutional design, funding, and oversight within the National Anti-Corruption Commission (CNA) and the Superior Court of Justice Specialized in Organized Crime and Corruption (CSJ).

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Whenever data is stored or transmitted, it inevitably encounters noise that can lead to harmful corruption. The communication technologies rely on decoding the data using Error Correcting Codes (ECC) that enable the rectification of noise to retrieve the original message. Maximum Likelihood (ML) decoding has proven to be optimally accurate, but it has not been adopted due to the lack of a feasible implementation arising from its computational complexity. It has been established that ML decoding of arbitrary linear codes is a Nondeterministic Polynomial-time (NP) hard problem. As a result, many code-specific decoders have been developed as an approximation of an ML decoder. This code-centric decoding approach leads to a hardware implementation that tightly couples with a specific code structure. Recently proposed Guessing Random Additive Noise Decoding (GRAND) offers a solution by establishing a noise-centric decoding approach, thereby making it a universal ML decoder. Both the soft-detection and hard-detection variants of GRAND have shown to be capacity achieving for any moderate redundancy arbitrary code. This thesis claims that GRAND can be efficiently implemented in hardware with low complexity while offering significantly higher energy efficiency than state-of-the-art code-centric decoders. In addition to being hardware-friendly, GRAND offers high parallelizability that can be chosen according to the throughput requirement making it flexible for a wide range of applications. To support this claim, this thesis presents custom-designed energy-efficient integrated circuits and hardware architectures for the family of GRAND algorithms. The universality of the algorithm is demonstrated through measurements across various codebooks for different channel conditions. Furthermore, we employ the noise recycling technique in both hard-detection and soft-detection scenarios to improve the decoding by exploiting the temporal noise correlations. Using the fabricated chips, we demonstrate that employing noise recycling with GRAND significantly reduces energy and latency, while providing additional gains in decoding performance. Efficient integrated architectures of GRAND will significantly reduce the hardware complexity while future-proofing a device so that it can decode any forthcoming code. The noise-centric decoding approach overcomes the need for code standardization making it adaptable for a wide range of applications. A single GRAND chip can replace all existing decoders, offering competitive decoding performance while also providing significantly higher energy and area efficiency. / 2026-05-23T00:00:00Z

This paper deals with a study of the ranch lands in Cooke, Wise, Denton, and Montague Counties, which are located in the North Grand Prairie of Texas.

Un des supports théoriques de la biologie évolutive est la théorie de la radiation adaptative, qui stipule que la diversification des espèces est le fruit de l'action de la sélection naturelle divergente sur les populations, laquelle émerge des caractéristiques biotiques et abiotiques de l'environnement. Il existe plusieurs exemples de cas de radiation adaptative dans la littérature. Or, la majorité des études se penchent sur la variation phénotypique morphologique et sur l'histoire de vie. Ainsi y a-t-il relativement peu de données sur la variation physiologique, tant au niveau de l'organisme qu'au niveau moléculaire. De plus, la caractérisation des bases génétiques de traits phénotypiques complexes s'avère peu aisée et demeure élusive. Dans cette étude, nous avons tiré profit des nouvelles technologies de la génomique pour caractériser les bases génétiques de la variation phénotypique observée chez deux populations divergentes du grand corégone (Coregonus clupeqformis), l'écotype limnétique (nain) ainsi que l'écotype benthique (normal). À l'aide d'une biopuce à ADNc spécifique au Salmonidés, nous avons comparé les profils d'expression génétique des corégones nains et normaux issus de leur milieu naturel ainsi que d'un environnement contrôlé. Le parallélisme observé dans les patrons de transcription génétique entre deux lacs et le milieu contrôlé indique que la sélection naturelle a modulé la régulation de gènes candidats associés à des adaptations phénotypiques distinguant les deux écotypes du corégone. De plus, le compromis observé entre différents traits d'histoire de vie chez les corégones nains et normaux se reflète à travers le profil de transcription pour ces gènes candidats. Enfin, l'analyse de regroupements (cluster analysis) entre les patrons de transcription des gènes candidats suggère que les principales fonctions physiologiques impliquées dans la divergence adaptative des corégones nains et normaux sont sous le contrôle d'un seul ou de quelques gènes de régulation. / One important theoretical framework in evolutionary biology is the adaptive radiation theory, which states that species diversification is the outcome of diverging natural selection, a selective force stemming from biotic and abiotic characteristics of the environment and acting on populations. Many cases of adaptive radiation have been observed and documented in the literature, focusing mainly on morphological adaptations and on life-history traits. Thus relatively few data are available on the physiological processes of adaptation, both at the organismal and molecular levels. Moreover, characterizing the genetics of phenotypic variation for complex traits is not an easy task and remains elusive in most cases. In this study, we took advantage of technologies of the post-genomic era in order to characterize the genetic bases of adaptive phenotypic variation observed in two diverging populations of the lake whitefish (Coregonus clupeaformis), the limnetic (dwarf) and the benthic (normal) ecotypes. Using a salmonids-specific cDNA microarray, we compared the gene expression profiles of dwarf and normal whitefish individuals sampled from two natural populations and from a controlled environment. Parallelism in regulation patterns observed between two lakes and the control environment indicates that natural selection played a role in modulating the regulation for these candidate genes, in association with phenotypic adaptations distinguishing the two whitefish ecotypes. Also, the observed trade-off between life-history traits in dwarf and normal whitefish is reflected in the expression profiles for these candidate genes. Lastly, cluster analysis performed on transcription profiles for these genes suggests that the major physiological processes involved in the adaptive divergence of the dwarf and normal whitefish are under the control of one or few regulation genes