472 research outputs found

    Exp. Penal N° 410-2000 Violación De La Libertad Sexual

    Get PDF
    El presente expediente, tiene como tema el desalojo de un inmueble. Se determinará la calidad de las sentencias en todas las instancias. Cuando el bien es adquirido por la demandante, ésta observa que el bien está siendo ocupado por una inquilina a quien la define como ocupante precaria. Se presenta una demanda contra la ocupante del inmueble. Sin embargo, en Primera Instancia se declara infundada la demanda. Porque, la ocupante no tiene la condición de precaria y se demuestra que es arrendataria. Con recurso de apelación, por parte de la demandante, en Segunda Instancia, la Cuarta Sala Civil de la Corte Superior de Justicia favorece a la demandante declarando fundada la demanda de desalojo por ocupante precaria, pero con votos en discordia. Como último Recurso, la demandada solicita el Recurso de Casación, fundamentando que se ha aplicado de manera errónea el artículo 1708, inciso 2 del Código Civil. Es así que, la Sala Civil de la Corte Suprema de Justicia declara fundando el recurso de casación. Pronunciándose que, la demandada no tiene la calidad de ocupante precaria porque, sustenta con título su condición de arrendataria la cual no es permanente. Declarando nula la sentencia de segunda instancia y revocando la sentencia de primera instancia; reformándola declararon improcedente la demanda de desalojo por ocupante precaria. Es así que, la Sala Suprema se pronuncia que la demandante debe de proceder demandando a la arrendataria, por la conclusión del contrato de arrendamiento que, tiene la demandada con su anterior propietario.The present file has as its theme the eviction of a property. The quality of the sentences will be determined in all instances. When the property is acquired by the applicant, it observes that the property is being occupied by a tenant who defines it as a precarious occupant. A lawsuit is filed against the occupant of the property. However, in the First Instance the claim is declared unfounded. Because, the occupant does not have precarious status and it is proven that she is a tenant. With appeal by the plaintiff, in Second Instance, the Fourth Civil Chamber of the Superior Court of Justice favors the plaintiff by declaring the demand for eviction founded by a precarious occupant, but with votes in discord. As a last Appeal, the defendant requests the Appeal, on the grounds that Article 1708, subsection 2 of the Civil Code has been applied erroneously. Thus, the Civil Chamber of the Supreme Court of Justice declares founding the appeal. Pronouncing that the defendant does not have the status of precarious occupant because, she sustains with title her tenant status which is not permanent. Declaring the second instance ruling null and repealing the first instance ruling; reforming it declared inadmissible the demand for eviction by precarious occupant. Thus, the Supreme Court pronounces that the plaintiff must proceed to sue the lessee, for the conclusion of the lease contract that the defendant has with its previous owner.Trabajo de suficiencia profesiona

    Vision as a compensatory mechanism for disturbance rejection in upwind flight

    Get PDF
    Recent experimental results demonstrate that flies possess a robust tendency to orient towards the frontally-centered focus of the visual motion field that typically occurs during upwind flight. We present a closed loop flight model, with a control algorithm based on feedback of the location of the visual focus of contraction, which is affected by changes in wind direction. The feasibility of visually guided upwind orientation is demonstrated with a model derived from current understanding of the biomechanics and sensorimotor computation of insects. The matched filter approach used to model the visual system computations compares extremely well with open-loop experimental data

    Live-virus exposure of vaccine-protected macaques alters the anti-HIV-1 antibody repertoire in the absence of viremia

    Get PDF
    Background: We addressed the question whether live-virus challenges could alter vaccine-induced antibody (Ab) responses in vaccinated rhesus macaques (RMs) that completely resisted repeated exposures to R5-tropic simian-human immunodeficiency viruses encoding heterologous HIV clade C envelopes (SHIV-Cs). Results: We examined the Ab responses in aviremic RMs that had been immunized with a multi-component protein vaccine (multimeric HIV-1 gp160, HIV-1 Tat and SIV Gag-Pol particles) and compared anti-Env plasma Ab titers before and after repeated live-virus exposures. Although no viremia was ever detected in these animals, they showed significant increases in anti-gp140 Ab titers after they had encountered live SHIVs. When we investigated the dynamics of anti-Env Ab titers during the immunization and challenge phases further, we detected the expected, vaccine-induced increases of Ab responses about two weeks after the last protein immunization. Remarkably, these titers kept rising during the repeated virus challenges, although no viremia resulted. In contrast, in vaccinated RMs that were not exposed to virus, anti-gp140 Ab titers declined after the peak seen two weeks after the last immunization. These data suggest boosting of pre-existing, vaccine-induced Ab responses as a consequence of repeated live-virus exposures. Next, we screened polyclonal plasma samples from two of the completely protected vaccinees by peptide phage display and designed a strategy that selects for recombinant phages recognized only by Abs present after – but not before – any SHIV challenge. With this “subtractive biopanning” approach, we isolated V3 mimotopes that were only recognized after the animals had been exposed to live virus. By detailed epitope mapping of such anti-V3 Ab responses, we showed that the challenges not only boosted pre-existing binding and neutralizing Ab titers, but also induced Abs targeting neo-antigens presented by the heterologous challenge virus. Conclusions: Anti-Env Ab responses induced by recombinant protein vaccination were altered by the multiple, live SHIV challenges in vaccinees that had no detectable viral loads. These data may have implications for the interpretation of “vaccine only” responses in clinical vaccine trials

    Tagvisor: A Privacy Advisor for Sharing Hashtags

    Get PDF
    Hashtag has emerged as a widely used concept of popular culture and campaigns, but its implications on people's privacy have not been investigated so far. In this paper, we present the first systematic analysis of privacy issues induced by hashtags. We concentrate in particular on location, which is recognized as one of the key privacy concerns in the Internet era. By relying on a random forest model, we show that we can infer a user's precise location from hashtags with accuracy of 70% to 76%, depending on the city. To remedy this situation, we introduce a system called Tagvisor that systematically suggests alternative hashtags if the user-selected ones constitute a threat to location privacy. Tagvisor realizes this by means of three conceptually different obfuscation techniques and a semantics-based metric for measuring the consequent utility loss. Our findings show that obfuscating as little as two hashtags already provides a near-optimal trade-off between privacy and utility in our dataset. This in particular renders Tagvisor highly time-efficient, and thus, practical in real-world settings

    Quantifying Privacy Risks of Prompts in Visual Prompt Learning

    Full text link
    Large-scale pre-trained models are increasingly adapted to downstream tasks through a new paradigm called prompt learning. In contrast to fine-tuning, prompt learning does not update the pre-trained model's parameters. Instead, it only learns an input perturbation, namely prompt, to be added to the downstream task data for predictions. Given the fast development of prompt learning, a well-generalized prompt inevitably becomes a valuable asset as significant effort and proprietary data are used to create it. This naturally raises the question of whether a prompt may leak the proprietary information of its training data. In this paper, we perform the first comprehensive privacy assessment of prompts learned by visual prompt learning through the lens of property inference and membership inference attacks. Our empirical evaluation shows that the prompts are vulnerable to both attacks. We also demonstrate that the adversary can mount a successful property inference attack with limited cost. Moreover, we show that membership inference attacks against prompts can be successful with relaxed adversarial assumptions. We further make some initial investigations on the defenses and observe that our method can mitigate the membership inference attacks with a decent utility-defense trade-off but fails to defend against property inference attacks. We hope our results can shed light on the privacy risks of the popular prompt learning paradigm. To facilitate the research in this direction, we will share our code and models with the community.Comment: To appear in the 33rd USENIX Security Symposium, August 14-16, 202

    Data Poisoning Attacks Against Multimodal Encoders

    Full text link
    Traditional machine learning (ML) models usually rely on large-scale labeled datasets to achieve strong performance. However, such labeled datasets are often challenging and expensive to obtain. Also, the predefined categories limit the model's ability to generalize to other visual concepts as additional labeled data is required. On the contrary, the newly emerged multimodal model, which contains both visual and linguistic modalities, learns the concept of images from the raw text. It is a promising way to solve the above problems as it can use easy-to-collect image-text pairs to construct the training dataset and the raw texts contain almost unlimited categories according to their semantics. However, learning from a large-scale unlabeled dataset also exposes the model to the risk of potential poisoning attacks, whereby the adversary aims to perturb the model's training dataset to trigger malicious behaviors in it. Previous work mainly focuses on the visual modality. In this paper, we instead focus on answering two questions: (1) Is the linguistic modality also vulnerable to poisoning attacks? and (2) Which modality is most vulnerable? To answer the two questions, we conduct three types of poisoning attacks against CLIP, the most representative multimodal contrastive learning framework. Extensive evaluations on different datasets and model architectures show that all three attacks can perform well on the linguistic modality with only a relatively low poisoning rate and limited epochs. Also, we observe that the poisoning effect differs between different modalities, i.e., with lower MinRank in the visual modality and with higher Hit@K when K is small in the linguistic modality. To mitigate the attacks, we propose both pre-training and post-training defenses. We empirically show that both defenses can significantly reduce the attack performance while preserving the model's utility

    A Control-Oriented Analysis of Bio-inspired Visuomotor Convergence

    Get PDF
    Insects exhibit incredibly robust closed loop fight dynamics in the face of uncertainties. A fundamental principle contributing to this unparalleled behavior is rapid processing and convergence of visual sensory information to fight motor commands via spatial wide-field integration, accomplished by retinal motion pattern sensitive interneurons (LPTCs) in the lobula plate portion of the visual ganglia. With in a control- theoretic frame work, models for spatially continuous retinal image flow and wide-field integration processing are developed, establishing the connection between image flow kernels (retinal motion pattern sensitivities) and the feedback terms they represent. It is shown that these out puts are sufficient to stabilize speed regulation and terrain following tasks. Hence, extraction of global retinal motion cues through computationally efficient wide-field integration processing provides a novel and promising methodology for utilizing visual sensory information in autonomous robotic navigation and fight control applications
    corecore