Filipinas y su perpetua especialidad. La realidad de las Islas Filipinas y los filipinos durante el siglo XIX (1837-1898).

[ES]Las modificaciones constitucionales del siglo XIX tuvieron un profundo impacto sobre la organización de la colonia. En el presente trabajo se exponen los efectos jurídicos que dichos cambios tuvieron sobre Filipinas y los filipinos entre 1837 y 1898. Para ello, analizo el fenómeno de la especialidad y su repercusión tanto en los órganos de gobierno filipinos como en la sociedad de las Islas Filipinas. Prestando especial atención tanto a las causas como a las consecuencias del empleo del discurso de inferioridad así como el uso de diminutivos para referirse a los cargos ejercidos por nativos

Stereoscopic Omnidirectional Image Quality Assessment Based on Predictive Coding Theory

Objective quality assessment of stereoscopic omnidirectional images is a challenging problem since it is influenced by multiple aspects such as projection deformation, field of view (FoV) range, binocular vision, visual comfort, etc. Existing studies show that classic 2D or 3D image quality assessment (IQA) metrics are not able to perform well for stereoscopic omnidirectional images. However, very few research works have focused on evaluating the perceptual visual quality of omnidirectional images, especially for stereoscopic omnidirectional images. In this paper, based on the predictive coding theory of the human vision system (HVS), we propose a stereoscopic omnidirectional image quality evaluator (SOIQE) to cope with the characteristics of 3D 360-degree images. Two modules are involved in SOIQE: predictive coding theory based binocular rivalry module and multi-view fusion module. In the binocular rivalry module, we introduce predictive coding theory to simulate the competition between high-level patterns and calculate the similarity and rivalry dominance to obtain the quality scores of viewport images. Moreover, we develop the multi-view fusion module to aggregate the quality scores of viewport images with the help of both content weight and location weight. The proposed SOIQE is a parametric model without necessary of regression learning, which ensures its interpretability and generalization performance. Experimental results on our published stereoscopic omnidirectional image quality assessment database (SOLID) demonstrate that our proposed SOIQE method outperforms state-of-the-art metrics. Furthermore, we also verify the effectiveness of each proposed module on both public stereoscopic image datasets and panoramic image datasets

SymmNeRF: Learning to Explore Symmetry Prior for Single-View View Synthesis

We study the problem of novel view synthesis of objects from a single image. Existing methods have demonstrated the potential in single-view view synthesis. However, they still fail to recover the fine appearance details, especially in self-occluded areas. This is because a single view only provides limited information. We observe that manmade objects usually exhibit symmetric appearances, which introduce additional prior knowledge. Motivated by this, we investigate the potential performance gains of explicitly embedding symmetry into the scene representation. In this paper, we propose SymmNeRF, a neural radiance field (NeRF) based framework that combines local and global conditioning under the introduction of symmetry priors. In particular, SymmNeRF takes the pixel-aligned image features and the corresponding symmetric features as extra inputs to the NeRF, whose parameters are generated by a hypernetwork. As the parameters are conditioned on the image-encoded latent codes, SymmNeRF is thus scene-independent and can generalize to new scenes. Experiments on synthetic and real-world datasets show that SymmNeRF synthesizes novel views with more details regardless of the pose transformation, and demonstrates good generalization when applied to unseen objects. Code is available at: https://github.com/xingyi-li/SymmNeRF.Comment: Accepted by ACCV 202

PMC-VQA: Visual Instruction Tuning for Medical Visual Question Answering

In this paper, we focus on the problem of Medical Visual Question Answering (MedVQA), which is crucial in efficiently interpreting medical images with vital clinic-relevant information. Firstly, we reframe the problem of MedVQA as a generation task that naturally follows the human-machine interaction, we propose a generative-based model for medical visual understanding by aligning visual information from a pre-trained vision encoder with a large language model. Secondly, we establish a scalable pipeline to construct a large-scale medical visual question-answering dataset, named PMC-VQA, which contains 227k VQA pairs of 149k images that cover various modalities or diseases. Thirdly, we pre-train our proposed model on PMC-VQA and then fine-tune it on multiple public benchmarks, e.g., VQA-RAD and SLAKE, outperforming existing work by a large margin. Additionally, we propose a test set that has undergone manual verification, which is significantly more challenging, even the best models struggle to solve

Designs and Implementations in Neural Network-based Video Coding

The past decade has witnessed the huge success of deep learning in well-known artificial intelligence applications such as face recognition, autonomous driving, and large language model like ChatGPT. Recently, the application of deep learning has been extended to a much wider range, with neural network-based video coding being one of them. Neural network-based video coding can be performed at two different levels: embedding neural network-based (NN-based) coding tools into a classical video compression framework or building the entire compression framework upon neural networks. This paper elaborates some of the recent exploration efforts of JVET (Joint Video Experts Team of ITU-T SG 16 WP 3 and ISO/IEC JTC 1/SC29) in the name of neural network-based video coding (NNVC), falling in the former category. Specifically, this paper discusses two major NN-based video coding technologies, i.e. neural network-based intra prediction and neural network-based in-loop filtering, which have been investigated for several meeting cycles in JVET and finally adopted into the reference software of NNVC. Extensive experiments on top of the NNVC have been conducted to evaluate the effectiveness of the proposed techniques. Compared with VTM-11.0_nnvc, the proposed NN-based coding tools in NNVC-4.0 could achieve {11.94%, 21.86%, 22.59%}, {9.18%, 19.76%, 20.92%}, and {10.63%, 21.56%, 23.02%} BD-rate reductions on average for {Y, Cb, Cr} under random-access, low-delay, and all-intra configurations respectively

Subjective quality assessment of stereoscopic omnidirectional image

Stereoscopic omnidirectional images are eye-catching because they can provide realistic and immersive experience. Due to the extra depth perception provided by stereoscopic omnidirectional images, it is desirable and urgent to evaluate the overall quality of experience (QoE) of these images, including image quality, depth perception, and so on. However, most existing studies are based on 2D omnidirectional images and only image quality is taken into account. In this paper, we establish the very first Stereoscopic OmnidirectionaL Image quality assessment Database (SOLID). Three subjective evaluating factors are considered in our database, namely image quality, depth perception, and overall QoE. Additionally, the relationship among these three factors is investigated. Finally, several well-known image quality assessment (IQA) metrics are tested on our SOLID database. Experimental results demonstrate that the objective overall QoE assessment is more challenging compared to IQA in terms of stereoscopic omnidirectional images. We believe that our database and findings will provide useful insights in the development of the QoE assessment for stereoscopic omnidirectional images

Synthesis of Indolo[2,1‑<i>a</i>]isoquinolines by Nickel-Catalyzed Mizoroki–Heck/Amination Cascade Reaction

An efficient Mizoroki–Heck/amination cascade reaction of o-dihaloarenes with cyclic imines was realized by combining nickel and a sterically bulky N-heterocyclic carbene ligand. This protocol provides access to a variety of indole[2,1-a]isoquinolines from readily available starting materials. This cascade approach could be applied to produce straightforward synthesis of the natural product cryptowoline

Recovery of K by NH4HSO4 low-temperature roasting from brown corundum Fly Ash

Brown corundum dust ash(BCFA) is an industrial solid waste from the brown corundum production process. The alkali metal is a key factor limiting its comprehensive use. Currently, BCFA is mainly stockpiled and occupies a large amount of land. Its fine particles are easy to cause air pollution. The addition of NH _4 HSO _4 allows for the effective extraction of K from BCFA and the efficient use of BCFA. Under optimum conditions: NH _4 HSO _4 to BCFA mass ratio of 1.2:1, the roasting temperature of 240 °C, roasting time of 2 h, water leaching time of 90 min, water leaching temperature of 65 °C water leaching liquid to solid ratio of 3:1, the leaching rate of K from BCFA reached 97%. The leachate was crystallised by evaporation to obtain K, N compound fertiliser for agricultural use. The leaching residue is mainly Al and Si, which can be used for the preparation of refractory materials, aluminium and silicon molecular sieves, construction materials and other raw materials