Instance-Specific Loss-Weighted Decoding for Decomposition-Based Multiclass Classification.

Multiclass classification problems are often addressed by decomposing them into a set of binary classification tasks. A critical step in this approach is the effective aggregation of predictions from each decomposed binary classifier to yield the final multiclass prediction, a process known as decoding. Existing studies have ignored the varying generalization ability of each binary classifier across different samples during decoding, potentially leading to suboptimal performance.

Variational Label Enhancement for Instance-Dependent Partial Label Learning.

Partial label learning (PLL) is a form of weakly supervised learning, where each training example is linked to a set of candidate labels, among which only one label is correct. Most existing PLL approaches assume that the incorrect labels in each training example are randomly picked as the candidate labels. However, in practice, this assumption may not hold true, as the candidate labels are often instance-dependent.

Label-Specific Time-Frequency Energy-Based Neural Network for Instrument Recognition.

Predominant instrument recognition plays a vital role in music information retrieval. This task involves identifying and categorizing the dominant instruments present in a piece of music based on their distinctive time-frequency characteristics and harmonic distribution. Existing predominant instrument recognition approaches mainly focus on learning implicit mappings (such as deep neural networks) from time-domain or frequency-domain representations of music audio to instrument labels.

The Efficacy of Entomopathogenic Nematodes Plus an Adjuvant against and in Aboveground Applications.

In the southern United States, corn earworm, (Boddie), and soybean looper, (Walker) are economically important crop pests. Although Bt crops initially provided effective control of target pests such as , many insect pests have developed resistance to these Bt crops. Alternative approaches are needed, including biological control agents such as entomopathogenic nematodes (EPNs).

Student Loss: Towards the Probability Assumption in Inaccurate Supervision.

Noisy labels are often encountered in datasets, but learning with them is challenging. Although natural discrepancies between clean and mislabeled samples in a noisy category exist, most techniques in this field still gather them indiscriminately, which leads to their performances being partially robust. In this paper, we reveal both empirically and theoretically that the learning robustness can be improved by assuming deep features with the same labels follow a student distribution, resulting in a more intuitive method called student loss.

Towards Enabling Binary Decomposition for Partial Multi-Label Learning.

Partial multi-label learning (PML) is an emerging weakly supervised learning framework, where each training example is associated with multiple candidate labels which are only partially valid. To learn the multi-label predictive model from PML training examples, most existing approaches work by identifying valid labels within candidate label set via label confidence estimation. In this paper, a novel strategy towards partial multi-label learning is proposed by enabling binary decomposition for handling PML training examples.

The mechanisms of metabolic resistance to pyrethroids and neonicotinoids fade away without selection pressure in the tarnished plant bug Lygus lineolaris.

Background: Heavy selection pressure prompted the development of resistance in a serious cotton pest tarnished plant bug (TPB), Lygus Lineolaris in the mid-southern United States. Conversely, a laboratory resistant TPB strain lost its resistance to five pyrethroids and two neonicotinoids after 36 generations without exposure to any insecticide. It is worthwhile to examine why the resistance diminished in this population and determine whether the resistance fade away has practical value for insecticide resistance management in TPB populations.

GluN1 antibody causes behavioral deficits in prepulse inhibition and memory through CaMKIIβ signaling.

Accumulating evidence suggests that some patients with schizophrenia have high production of autoantibodies against the N-methyl-d-aspartate receptor (NMDAR) subunit GluN1 and that these antibodies lead to cognitive impairment. However, the molecular mechanisms of the deficits seen in these patients are largely unknown. In the present study, we found that passive infusion of GluN1 antibody into the hippocampus of mice for 7 days led to decreased expression of GluN1, phosphor-Ser897-GluN1, and EphrinB2 receptor (EphB2R); deficits in long-term potentiation (LTP) and synaptic transmission in the hippocampal CA1 area; impairment in prepulse inhibition (PPI); and deterioration of recognition memory in novel object recognition test.

Lethal Concentration and Sporulation by Contact and Direct Spray of the Entomopathogenic Fungus on Different Stages of (Heteroptera: Pentatomidae).

The southern green stink bug, (L.) (Heteroptera: Pentatomidae) is the most significant pest of soybean worldwide. The present study was conducted to compare the effectiveness of a Delta native strain NI8 of by contact and direct spray on nymphs (2nd to 5th instar) and adults of .

Variational Label Enhancement.

Multi-label learning focuses on the ambiguity at the label side, i.e., one instance is associated with multiple class labels, where the logical labels are always adopted to partition class labels into relevant labels and irrelevant labels rigidly.

Collaborative Learning of Label Semantics and Deep Label-Specific Features for Multi-Label Classification.

In multi-label classification, the strategy of label-specific features has been shown to be effective to learn from multi-label examples by accounting for the distinct discriminative properties of each class label. However, most existing approaches exploit the semantic relations among labels as immutable prior knowledge, which may not be appropriate to constrain the learning process of label-specific features. In this paper, we propose to learn label semantics and label-specific features in a collaborative way.

Adaptive Graph Guided Disambiguation for Partial Label Learning.

In partial label learning, a multi-class classifier is learned from the ambiguous supervision where each training example is associated with a set of candidate labels among which only one is valid. An intuitive way to deal with this problem is label disambiguation, i.e.

Maximum Margin Multi-Dimensional Classification.

Multi-dimensional classification (MDC) assumes heterogeneous class spaces for each example, where class variables from different class spaces characterize semantics of the example along different dimensions. The heterogeneity of class spaces leads to incomparability of the modeling outputs from different class spaces, which is the major difficulty in designing MDC approaches. In this article, we make a first attempt toward adapting maximum margin techniques for MDC problem and a novel approach named M3MDC is proposed.

Multi-Label Classification With Label-Specific Feature Generation: A Wrapped Approach.

Label-specific features serve as an effective strategy to learn from multi-label data, where a set of features encoding specific characteristics of each label are generated to help induce multi-label classification model. Existing approaches work by taking the two-stage strategy, where the procedure of label-specific feature generation is independent of the follow-up procedure of classification model induction. Intuitively, the performance of resulting classification model may be suboptimal due to the decoupling nature of the two-stage strategy.

Association Analysis of Neuronal Nitric Oxide Synthase 1 Gene Polymorphism With Psychopathological Symptoms in Chronic Ketamine Users.

We previously found that chronic ketamine usages were associated with various psychotic and cognitive symptoms mimicking schizophrenia. The blockade of the NMDA receptor and subsequent nitric oxide synthase 1 (NOS1) dysfunction were found to be closely correlated with schizophrenia including NOS1 gene polymorphisms. We examined the allelic variants of the gene coding neuronal nitric oxide synthase 1 () in chronic ketamine users in the Chinese population and analyzed the association between gene polymorphism and psychopathological symptoms in chronic ketamine users.

Towards Class-Imbalance Aware Multi-Label Learning.

Multi-label learning deals with training examples each represented by a single instance while associated with multiple class labels. Due to the exponential number of possible label sets to be considered by the predictive model, it is commonly assumed that label correlations should be well exploited to design an effective multi-label learning approach. On the other hand, class-imbalance stands as an intrinsic property of multi-label data which significantly affects the generalization performance of the multi-label predictive model.

Mating Type Idiomorphs, Heterothallism, and High Genetic Diversity in , Cause of Peach Scab.

Scab (caused by ) is a major disease affecting peach in the eastern United States. The aims of the study were to characterize the mating-type loci in , determine whether they are in equilibrium, and assess the population genetic diversity and structure of the pathogen. The mating-type gene was identified in isolate JP3-5 in an available genome sequence, and the gene was PCR amplified from isolate PS1-1, thus indicating a heterothallic structure.

Chronic administration of ketamine induces cognitive deterioration by restraining synaptic signaling.

The discovery of the rapid antidepressant effects of ketamine has arguably been the most important advance in depression treatment. Recently, it was reported that repeated long-term ketamine administration is effective in preventing relapse of depression, which may broaden the clinical use of ketamine. However, long-term treatment with ketamine produces cognitive impairments, and the underlying molecular mechanisms for these impairments are largely unknown.

First description of the sexual stage of , causal agent of pecan scab.

Pecan scab, caused by , is the most prevalent disease of pecan in the southeastern United States. Recent characterization of the mating type () distribution of revealed that the idiomorphs are in equilibrium at various spatial scales, indicative of regular sexual recombination. However, the occurrence of the sexual stage of has never been observed, and the pathogen was previously considered to rely entirely on asexual reproduction.

Preliminary comparative analysis of kynurenine pathway metabolites in chronic ketamine users, schizophrenic patients, and healthy controls.

Objective: The serum kynurenine pathway metabolites kynurenic acid (KYNA), kynurenine (KYN), and tryptophan (TRP) were examined in chronic ketamine users and in schizophrenic patients. The correlations of the metabolites with sociodemographic data, clinical characteristics, and drug use status were analyzed.

Methods: Seventy-nine healthy controls, 78 ketamine users, and 80 schizophrenic patients were recruited.

Partial Multi-Label Learning via Credible Label Elicitation.

Partial multi-label learning (PML) deals with the problem where each training example is associated with an overcomplete set of candidate labels, among which only some candidate labels are valid. The task of PML naturally arises in learning scenarios with inaccurate supervision, and the goal is to induce a multi-label predictor which can assign a set of proper labels for unseen instance. The PML training procedure is prone to be misled by false positive labels concealed in the candidate label set, which serves as the major modeling difficulty for partial multi-label learning.

GRIN2B Gene Polymorphism in Chronic Ketamine Users.

Background And Objectives: We examined the allelic variants of N-methyl- d-aspartate receptor 2B (GRIN2B) and analyzed the associations between GRIN2B gene polymorphism with ketamine use conditions and psychopathological symptoms in chronic ketamine users.

Methods: A total of 231 subjects were recruited. Four single nucleotide polymorphisms of GRIN2B, rs1805502, rs7301328, rs890, and rs1806201 were examined in 151 male chronic ketamine users and 80 controls.

Interactivity in a Decision Aid: Findings From a Decision Aid to Technologically Enhance Shared Decision Making RCT.

Introduction: Colorectal cancer screening (CRCS) remains underutilized. Decision aids (DAs) can increase patient knowledge, intent, and CRCS rates compared with "usual care," but whether interactivity further increases CRCS rate remains unknown.

Study Design: A two-armed RCT compared the effect of a web-based DA that interactively assessed patient CRC risk and clarified patient preference for specific CRCS test to a web-based DA with the same content but without the interactive tools.

Liuwei Dihuang Decoction for primary osteoporosis: A protocol for a systematic review and meta-analysis.

Background: Primary osteoporosis (POP) is one kind of global disease, as a serious threat to human health. Liuwei Dihuang Decoction (LWDHD) has been recommended to treat osteoporosis alone or combined with medicine in China; however, its efficacy is unclear. The object of this systematic review and meta-analysis is to evaluate the efficacy and safety of LWDHD in the management of POP.