Strongly concealed adversarial attack against text classification models with limited queries.

In black-box scenarios, adversarial attacks against text classification models face challenges in ensuring highly available adversarial samples, especially a high number of invalid queries under long texts. The existing methods select distractors by comparing the confidence vector differences obtained before and after deleting words, and the query increases linearly with the length of the text, making it difficult to apply to attack scenarios with limited queries. Generating adversarial samples based on a thesaurus can lead to semantic inconsistencies and even grammatical errors, making it easy for the target model to recognize adversarial samples and resulting in a low success rate of attacks.

Enhancing source code classification effectiveness via prompt learning incorporating knowledge features.

Researchers have investigated the potential of leveraging pre-trained language models, such as CodeBERT, to enhance source code-related tasks. Previous methodologies have relied on CodeBERT's '[CLS]' token as the embedding representation of input sequences for task performance, necessitating additional neural network layers to enhance feature representation, which in turn increases computational expenses. These approaches have also failed to fully leverage the comprehensive knowledge inherent within the source code and its associated text, potentially limiting classification efficacy.

Dual Regulation Mechanism of Obesity: DNA Methylation and Intestinal Flora.

Obesity is a multifactorial chronic inflammatory metabolic disorder, with pathogenesis influenced by genetic and non-genetic factors such as environment and diet. Intestinal microbes and their metabolites play significant roles in the occurrence and development of obesity by regulating energy metabolism, inducing chronic inflammation, and impacting intestinal hormone secretion. Epigenetics, which involves the regulation of host gene expression without changing the nucleotide sequence, provides an exact direction for us to understand how the environment, lifestyle factors, and other risk factors contribute to obesity.

Stress transfer law in laboratory hydraulic fracturing experiments.

During the true triaxial hydraulic fracturing experiments, the compression stress applied to the specimen surface cannot be transferred to the interior immediately, resulting in inconsistency with in-situ stress conditions. To quantitatively analyze the stress transfer process from the surface to the interior of the specimen, an experimental method for monitoring the inside stress was proposed based on Fiber Bragg Grating (FBG) sensing technique, based on which the true triaxial stress loading experiments were conducted on a concrete-like specimen of 30 cm × 30 cm × 30 cm. The results show that the stresses inside the specimen require a certain loading time to reach the uniform state.

Role of NLRP3 inflammasome in central nervous system diseases.

The central nervous system (CNS) is the most delicate system in human body, with the most complex structure and function. It is vulnerable to trauma, infection, neurodegeneration and autoimmune diseases, and activates the immune system. An appropriate inflammatory response contributes to defence against invading microbes, whereas an excessive inflammatory response can aggravate tissue damage.

Microbial contribution to 14 biogenic amines accumulation in refrigerated raw and deep-fried hairtails (Trichiurus lepturus).

Biogenic amines (BAs) produced by microbial decarboxylation of amino acids are crucial toxic nitrogenous compounds in fish. An optimized ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method with simple pretreatment was established to detect 14 BAs in both raw (control check, CK) and deep-fried (DF) hairtails. This method exhibited a good linear relationship with average recoveries of 73.

Inpainting with Separable Mask Update Convolution Network.

Image inpainting is an active area of research in image processing that focuses on reconstructing damaged or missing parts of an image. The advent of deep learning has greatly advanced the field of image restoration in recent years. While there are many existing methods that can produce high-quality restoration results, they often struggle when dealing with images that have large missing areas, resulting in blurry and artifact-filled outcomes.

MSC-EVs transferring mitochondria and related components: A new hope for the treatment of kidney disease.

Kidney disease is a serious hazard to human health. Acute or chronic renal disease will have a significant negative impact on the body's metabolism. The involvement of mitochondria in renal illness has received a lot of interest as research on kidney disease has advanced.

Oral Realgar-Indigo Naturalis Formula Treatment for Acute Promyelocytic Leukemia in Children: A Randomized, Control Clinical Trial.

Objective: To analyze the efficacy, safety, and economy of RIF compared with intravenous arsenic trioxide (ATO) for the induction and consolidation therapy of pediatric APL.

Materials And Methods: In this randomized control clinical trial (NCT02200978), children with newly diagnosed APL from June 2013 to December 2017 were randomly divided into RIF and ATO groups. The groups were treated with RIF or ATO in combination with all-trans retinoic acid (ARTA) and conventional chemotherapeutic drugs during induction and consolidation therapy.

Rule extraction from biased random forest and fuzzy support vector machine for early diagnosis of diabetes.

Due to concealed initial symptoms, many diabetic patients are not diagnosed in time, which delays treatment. Machine learning methods have been applied to increase the diagnosis rate, but most of them are black boxes lacking interpretability. Rule extraction is usually used to turn on the black box.

The Role of B1 Cells in Systemic Lupus Erythematosus.

Systemic lupus erythematosus (SLE) is a systemic autoimmune disease characterized by multisystemic and multi-organ involvement, recurrent relapses and remissions, and the presence of large amounts of autoantibodies in the body as the main clinical features. The mechanisms involved in this disease are complex and remain poorly understood; however, they are generally believed to be related to genetic susceptibility factors, external stimulation of the body's immune dysfunction, and impaired immune regulation. The main immune disorders include the imbalance of T lymphocyte subsets, hyperfunction of B cells, production of large amounts of autoantibodies, and further deposition of immune complexes, which result in tissue damage.

Numerical simulation study on the crack propagation of conglomerate.

The conglomerate reservoir is rich in oil and gas reserves; however, the gravel's mechanical properties and laws are difficult to gain through laboratory experiments, which furthermore constrain the hydraulic fracturing design. To analyse the failure law of conglomerate, we simulated the uniaxial compression test based on discrete element software PFC2D and analysed the effect of different cementation strength, gravel content and gravel geometry on the rock deformation and failure characteristics. Results show that (i) as the cementation strength decreases, the compressive strength and elasticity modulus both reduce clearly, while the crack shapes get more complex and the critical value is 0.

Management and Clinical Outcome of Posterior Reversible Encephalopathy Syndrome in Pediatric Oncologic/Hematologic Diseases: A PRES Subgroup Analysis With a Large Sample Size.

This study investigated the management and clinical outcomes along with associated factors of posterior reversible encephalopathy syndrome (PRES) in childhood hematologic/oncologic diseases. We present data from children with hematologic/oncologic diseases who developed PRES after treatment of the primary disease with chemotherapy and hematopoietic stem cell transplantation (HSCT) at 3 medical centers in Changsha, China from 2015 to 2020, and review all previously reported cases with the aim of determining whether this neurologic manifestation affects the disease prognosis. In the clinical cohort of 58 PRES patients, hypertension [pooled odds ratio (OR) = 4.

Self-selective attention using correlation between instances for distant supervision relation extraction.

Distant supervision relation extraction methods are widely used to extract relational facts in text. The traditional selective attention model regards instances in the bag as independent of each other, which makes insufficient use of correlation information between instances and supervision information of all correctly labeled instances, affecting the performance of relation extractor. Aiming at this problem, a distant supervision relation extraction method with self-selective attention is proposed.

Immunoregulatory Effects of Mitochondria Transferred by Extracellular Vesicles.

Mitochondria participate in immune regulation through various mechanisms, such as changes in the mitochondrial dynamics, as metabolic mediators of the tricarboxylic acid cycle, by the production of reactive oxygen species, and mitochondrial DNA damage, among others. In recent years, studies have shown that extracellular vesicles are widely involved in intercellular communication and exert important effects on immune regulation. Recently, the immunoregulatory effects of mitochondria from extracellular vesicles have gained increasing attention.

Deep supervised learning with mixture of neural networks.

Deep Neural Network (DNN), as a deep architectures, has shown excellent performance in classification tasks. However, when the data has different distributions or contains some latent non-observed factors, it is difficult for DNN to train a single model to perform well on the classification tasks. In this paper, we propose mixture model based on DNNs (MoNNs), a supervised approach to perform classification tasks with a gating network and multiple local expert models.

Characteristics of decline in cognition and locomotion among the elderly in seven provinces of China.

Background: Decline in cognition and in locomotion is associated with aging. However, the relationship between them and the current occurrence of them in Chinese elderly people was weak.

Methods: To investigate the details of these two functions in Chinese elderly people and to try to find some early recognition and intervention clues, data of MMSE test and usual gait speed from 4487 elderly people from seven provinces in China were analysed.

[Effect of corticosterone on lissencephaly 1 expression in developing cerebral cortical neurons of fetal rats cultured in vitro].

Objective: To investigate the effect of corticosterone on the expression of the neuronal migration protein lissencephaly 1 (LIS1) in developing cerebral cortical neurons of fetal rats.

Methods: The primary cultured cerebral cortical neurons of fetal Wistar rats were divided into control group, low-dose group, and high-dose group. The neurons were exposed to the medium containing different concentrations of corticosterone (0 μmol/L for the control group, 0.

An Intelligible Risk Stratification Model Based on Pairwise and Size Constrained Kmeans.

Having a system to stratify individuals according to risk is key to clinical disease prevention. This allows individuals identified at different risk tiers to benefit from further investigation and intervention. But the same risk score estimated for two different persons does not mean they need the same further investigation or represent the similarity health condition between two persons.

Locally Embedding Autoencoders: A Semi-Supervised Manifold Learning Approach of Document Representation.

Topic models and neural networks can discover meaningful low-dimensional latent representations of text corpora; as such, they have become a key technology of document representation. However, such models presume all documents are non-discriminatory, resulting in latent representation dependent upon all other documents and an inability to provide discriminative document representation. To address this problem, we propose a semi-supervised manifold-inspired autoencoder to extract meaningful latent representations of documents, taking the local perspective that the latent representation of nearby documents should be correlative.