LA FRONTERA EN RUINAS: EL CUERPO ENFERMO Y LA BIOPOLÍTICA GLOBAL EN MAQUILAPOLIS Y SLEEP DEALER

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Manicomio y locura: revolución dentro de la Revolución Mexicana en Nadie me verá llorar de Cristina Rivera Garza / Asylum and Madness: Revolution within the Mexican Revolution in Cristina Rivera Garza’s Nadie me verá llorar

Interweaving history and fiction, Cristina Rivera Garza’s novel, Nadie me verá llorar (1999), traces the story of the asylum La Castañeda during the first decades of the twentieth century with the purpose of critically examining a new emerging discipline system in the process of construction of a “good citizen.” Yet, through the representation of a “demented” woman who does not conform to the nation’s modernization project, this novel also offers different angles to read the Mexican Revolution. Performative madness, as a strategy of resistance of so-called pathological subjects to domestication, can be interpreted as a revolutionary expression that has been silenced in the hegemonic history of the revolution. Thus, rather than it just being a site of confinement and control, the asylum becomes a battlefield of constant negotiation of power and language. Breaking with conventional ideas of history, Rivera Garza demonstrates that the defiance of disciplined civic life constitutes another form of revolution within the Mexican Revolution.           Keywords: asylum; Cristina Rivera Garza; Mexican Revolution; Mexican Literature; madness.  Como entretejido de discursos históricos y de ficción, Nadie me verá llorar de Cristina Rivera Garza (1999) rastrea la historia durante las primeras décadas del siglo XX de un manicomio concreto, La Castañeda, con el fin de examinar críticamente un nuevo sistema emergente de disciplina en el proceso de la construcción del “buen ciudadano”. Por medio del protagonismo de una “demente” que rechaza conformarse con el proyecto nacional de modernización, esta novela también ofrece diferentes ángulos para leer la Revolución Mexicana. La locura performativa, que apunta a la resistencia a la domesticación de los sujetos supuestamente patológicos, se puede interpretar como una manifestación revolucionaria pero silenciada en la historia hegemónica de la revolución. Así, el manicomio, más que simple sitio de encierro y de control, se convierte en un campo de constante negociación de poder y de lenguaje. Rompiendo con las ideas convencionales de la historia, Rivera Garza evidencia que el desafío a la disciplina de la vida ciudadana constituye otra forma de revolución dentro de la Revolución Mexicana. 

IMAGINAR SIN FRONTERA:VISIONES ERRANTES DE NACIÓN Y COSMOPOLITISMO DESDE LA PERIFERIA

This dissertation revisits the U.S.-Mexico borderlands to examine its neoliberal transformation intensified by globalization in order to address new aesthetic subjectivities that challenge this violent process from the peripheral experience and imagination. Despite increasing interest in the academic field, Border Studies have been trapped by hybridity theory -whose celebrative interpretations of the border phenomena frequently ignore social inequality and neutralize cultural conflicts- developed by Homi Bhabha and García Canclini, among others. Breaking with this postmodern frame, I explore the heterogeneous realities and marginal subjects particularly in relation to the crisis and the reformulation of two major and conflictive concepts: "cosmopolitanism" and "nation." I argue that for Border Studies to be effective, they have to respond to new scenarios of "peripheral" voices and experiences as they have been emerging along the U.S.-Mexico border and beyond. My dissertation thus focuses on narrative analysis of the topics that configure marginal languages and cultures: undocumented migratory labor and border crossing, the cholo community, popular border saints, narco-world and "bare life," feminicide in Ciudad Juárez and maquiladora workers. From Guillermo Gómez-Peña and Gloria Anzaldúa, the texts of embodied border identities I analyze attempt to dismantle binary models -the "borderless" and the "bordered"- of the idea of 'great community,' to demonstrate the representational crisis of a national or bi-national perspective that intensifies monolithic claims, and to offer different and even alternative ideas of community in a globalized context

Minority rights constraints on a state's power to regulate citizenship under international law.

In international law, there is no officially accepted definition of a minority. The traditional view on the definition of a minority requires that in order for persons belonging to ethnic, religious or linguistic groups to receive minority status and enjoy relevant minority rights, they must hold the citizenship of their State of residence. This thesis questions the traditional approach to the concepts of minority and minority rights with special reference to the case of the ethnic, linguistic Russians in Estonia and Latvia. It presents an analysis of the international legal and normative bases for justifying the effective protection of the ethnic, linguistic Russians in Estonia and Latvia as persons belonging to minorities with reference to their citizenship status. It is argued that at least three international legal and normative bases may be invoked for the effective protection of the ethnic, linguistic Russians in Estonia and Latvia. Such legal and normative bases can be found in minorities-specific standards with the focus on the protection of cultural identity for minorities, general human rights standards with an emphasis on substantive equality, and the right to internal self-determination. The linkage of these legal and normative bases to the protection of the ethnic, linguistic Russians in Estonia and Latvia as persons belonging to minorities with reference to citizenship in their States of residence strongly suggests that Estonian and Latvian citizenship laws are problematic from the perspective of minority protection. It also implies that Estonia and Latvia should protect the minority rights of the ethnic, linguistic Russians in an effective manner at the domestic legal level through the implementation of concrete protective measures to that effect, by taking into account their various needs and problems, including the matter of citizenship for the ethnic, linguistic Russian non-citizens and stateless persons. The discussion about the legal and normative bases for the protection of the ethnic, linguistic Russians in Estonia and Latvia with reference to their citizenship status also indicates that a State's power to regulate citizenship can be constrained 'to the extent' that it is obliged to protect minority rights in an effective manner at the domestic legal level under international law

Decentralized Deadlock-free Trajectory Planning for Quadrotor Swarm in Obstacle-rich Environments -- Extended version

This paper presents a decentralized multi-agent trajectory planning (MATP) algorithm that guarantees to generate a safe, deadlock-free trajectory in an obstacle-rich environment under a limited communication range. The proposed algorithm utilizes a grid-based multi-agent path planning (MAPP) algorithm for deadlock resolution, and we introduce the subgoal optimization method to make the agent converge to the waypoint generated from the MAPP without deadlock. In addition, the proposed algorithm ensures the feasibility of the optimization problem and collision avoidance by adopting a linear safe corridor (LSC). We verify that the proposed algorithm does not cause a deadlock in both random forests and dense mazes regardless of communication range, and it outperforms our previous work in flight time and distance. We validate the proposed algorithm through a hardware demonstration with ten quadrotors.Comment: 11 pages, extended version of conference versio

Temporal Dynamic Quantization for Diffusion Models

The diffusion model has gained popularity in vision applications due to its remarkable generative performance and versatility. However, high storage and computation demands, resulting from the model size and iterative generation, hinder its use on mobile devices. Existing quantization techniques struggle to maintain performance even in 8-bit precision due to the diffusion model's unique property of temporal variation in activation. We introduce a novel quantization method that dynamically adjusts the quantization interval based on time step information, significantly improving output quality. Unlike conventional dynamic quantization techniques, our approach has no computational overhead during inference and is compatible with both post-training quantization (PTQ) and quantization-aware training (QAT). Our extensive experiments demonstrate substantial improvements in output quality with the quantized diffusion model across various datasets

Isotropic Representation Can Improve Dense Retrieval

The recent advancement in language representation modeling has broadly affected the design of dense retrieval models. In particular, many of the high-performing dense retrieval models evaluate representations of query and document using BERT, and subsequently apply a cosine-similarity based scoring to determine the relevance. BERT representations, however, are known to follow an anisotropic distribution of a narrow cone shape and such an anisotropic distribution can be undesirable for the cosine-similarity based scoring. In this work, we first show that BERT-based DR also follows an anisotropic distribution. To cope with the problem, we introduce unsupervised post-processing methods of Normalizing Flow and whitening, and develop token-wise method in addition to the sequence-wise method for applying the post-processing methods to the representations of dense retrieval models. We show that the proposed methods can effectively enhance the representations to be isotropic, then we perform experiments with ColBERT and RepBERT to show that the performance (NDCG at 10) of document re-ranking can be improved by 5.17\%$\sim$8.09\% for ColBERT and 6.88\%$\sim$22.81\% for RepBERT. To examine the potential of isotropic representation for improving the robustness of DR models, we investigate out-of-distribution tasks where the test dataset differs from the training dataset. The results show that isotropic representation can achieve a generally improved performance. For instance, when training dataset is MS-MARCO and test dataset is Robust04, isotropy post-processing can improve the baseline performance by up to 24.98\%. Furthermore, we show that an isotropic model trained with an out-of-distribution dataset can even outperform a baseline model trained with the in-distribution dataset.Comment: 9 pages, 4 figure