Background/Objectives: Machine learning applied to MALDI-TOF mass spectra can flag antimicrobial resistance days before conventional susceptibility testing, but models rarely retain accuracy in a new laboratory. We asked whether this failure can be r...
Important scientific areas, such as cellular biology, medicine, pharmacy, and environmental sciences, are dependent on very sensitive analytical techniques to track and detect biomolecules. In this work, we develop a simple, low-cost and effective sy...
Optical network monitoring and soft failure identification such as optical filter shifting and filter tightening are increasingly significant for the complex and dynamic optical networks of the future. Center frequency shift of optical filtering devi...
BODIPY dyes are photostable neutral derivatives of 4,4-difluoro-4-bora-3a,4a-diaza-s-indacene. These are widely used as chemosensors, laser materials, and molecular probes. At the same time, BODIPY dyes have small or moderate Stokes shifts like most...
Urban inundation forecasting in high-density cities is complicated by sparse incident labels, nonstationary rainfall, and changing sensing systems. Using Taipei as a case study, we develop a building-scale GeoAI decision-support prototype that integr...
We evaluate rolling-window XGBoost retraining (Adaptive XGBoost, AXGB) for leak detection on the simulated BattLeDIM benchmark, with an edge prototype and network simulation. Hourly supervised retraining on 6 h label windows (AXGB-S) reaches F1 = 0.9...
Haze can cause a significant reduction in the contrast and brightness of images. CNN-based methods have achieved benign performance on synthetic data. However, they show weak generalization performance on real data because they are only trained on fu...
High-resolution land cover mapping is crucial in various disciplines but is often hindered by the lack of accurately matched labels. Our study introduces an innovative deep learning methodology for effective land cover mapping, independent of matched...
Herein, we present the synthesis and application of a fluorogenic, large Stokes-shift (>100 nm), bioorthogonally conjugatable, membrane-permeable tetrazine probe, which can be excited at common laser line 488 nm and detected at around 600 nm. The...
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To identify severe missing events in low-voltage distribution network (LVDN) measurements under coexisting errors and asynchrony, a label-free severe missing event detection method based on the mean shift test is proposed. First, mathematical models...
Fine-grained vehicle orientation estimation is widely reported with strong in-domain accuracy, yet performance degrades substantially when models are applied across datasets; the relative contributions of visual domain shift and annotation label inco...
Background: Asthma significantly impacts global health, necessitating effective management strategies. A combination of inhaled corticosteroids (ICSs) and long-acting β2-agonists (LABA) is recommended for patients with inadequately controlled as...
As the most abundant protein with a variety of physiological functions, human serum albumin (HSA) has been used extensively for the delivery and improvement of therapeutic molecules. Thiolactone chemistry provides a powerful tool to prepare albumin-b...
Fluorogens are an attractive type of dye for imaging applications, eliminating time-consuming washout steps from staining protocols. With just a handful of reported fluorogen-protein pairs, mostly in the green region of spectra, there is a need for t...
As global pork consumption rises, livestock farms increasingly adopt deep learning-based automated monitoring systems for efficient pigsty management. Typically, a system applies a pre-trained model on a source domain to a target domain. However, rea...
This paper presents OpS-EWMA-LLM (Operational State Shifts Detection using Exponential Weighted Moving Average and Labeling using Large Language Model), a hybrid framework that combines fleet-normalized statistical shift detection with LLM-assisted d...
Organic anion transporting polypeptides (OATPs) were found to readily deliver membrane impermeable, tetrazine bearing fluorescent probes into cells. This feature was explored in OATP3A1 conditioned bio-orthogonal labeling schemes of various intracell...
Cross-view image geolocalization aims to achieve accurate localization of geo-tagged images without geo-tagging by matching ground-view images with satellite images. However, there are huge imaging differences between ground and satellite viewpoints,...
19F-NMR has proved to be a valuable tool in fragment-based drug discovery. Its applications include screening libraries of fluorinated fragments, assessing competition among elaborated fragments and identifying the binding poses of promising hits. By...
Here, we present a protocol for the one-step synthesis of the title compound in quantitative yield using adapted Vilsmeier conditions. The product was characterized by 1H-,2H-,13C-NMR-, as well as IR and Raman spectroscopy. Spectral data are given in...
Road safety authorities each hold accident records that, when combined, could train stronger severity prediction models, yet these records can be neither centralized, for privacy and governance reasons, nor naively merged, because jurisdictions encod...
Transformer-based fake news classifiers often perform well within their training domain but show substantial performance degradation when applied to a different domain. This degradation is commonly attributed to changes in learned representations, wh...
High-impedance fault detectors are commonly trained in simulation, yet their transfer to physical arcing remains poorly quantified. Using a report-calibrated source generator and 983 physical vegetation-conduction tests from the Vegetation High-Imped...
We present a numerical investigation on the detection of superparamagnetic labels using a giant magnetoresistance (GMR) vortex structure. For this purpose, the Landau–Lifshitz–Gilbert equation was solved numerically applying an external z...
Partial domain adaptation (PDA) is a framework for mitigating the covariate shift problem when target labels are contained in source labels. For this task, adversarial neural network (ANN) methods proposed in the literature have been proven to be fle...
Top-performing computer vision models are powered by convolutional neural networks (CNNs). Training an accurate CNN highly depends on both the raw sensor data and their associated ground truth (GT). Collecting such GT is usually done through human la...
This article examines how “Blue Shirts” [藍衣社] was made and remade as a political label through press circulation in Republican China. Rather than assuming that each occurrence referred to a stable organisation, it ana...
Research on wine perception shows that extrinsic information can alter reported sensory perceptions. This study adopts a repeated measures design to quantify how label information affects perceived quality relative to blind tasting. Forty-five adult...
Hydrophilic interaction liquid chromatography (HILIC) is widely used for the analysis of glycans and oligosaccharides, yet the molecular basis of retention remains incompletely understood. In this study, we investigated dextran ladders labelled with...
The automated detection of deep-sea polymetallic nodules is critical for processing large volumes of benthic imagery. However, its scalability faces challenges from cross-expedition covariate shifts, such as changes in lighting, altitude, and camera...
Discrete transforms of Weyl orbit functions on finite fragments of shifted dual root lattices are established. The congruence classes of the dual weight lattices intersected with the fundamental domains of the affine Weyl groups constitute the point...
Mean-shift tracking has gained more interests, nowadays, aided by its feasibility of real-time and reliable tracker implementation. In order to reduce background clutter interference to mean-shift object tracking, this paper proposes a novel indicato...
12 October 2023
The inherent dependency of deep learning models on labeled data is a well-known problem and one of the barriers that slows down the integration of such methods into different fields of applied sciences and engineering, in which experimental and numer...
This paper proposes a novel approach for semi-supervised domain adaptation for holistic regression tasks, where a DNN predicts a continuous value
In real-world machine learning scenarios, training data are frequently weakly annotated and distributionally misaligned with deployment environments. Specifically, label ambiguity may arise when each instance is associated with a set of candidate lab...
Despite the significant advances noted in semantic segmentation of aerial imagery, a considerable limitation is blocking its adoption in real cases. If we test a segmentation model on a new area that is not included in its initial training set, accur...
Deep learning has attracted extensive attention in the field of hyperspectral images (HSIs) classification. However, supervised deep learning methods heavily rely on a large amount of label information. To address this problem, in this paper, we prop...
Multi-label image classification (MLIC) is vulnerable to contextual bias, where models may exploit spurious label–context associations rather than object evidence, leading to degraded generalization under distribution shifts. To address this is...
We present packet switching applications based on extended spectral-amplitude-coding (SAC) labels in generalized multi-protocol label switching (GMPLS) networks. The proposed approach combines the advantages of wavelength-division multiplexing (WDM)...
To minimize dependency on the availability of data labels, some WiFi-CSI based-gesture recognition solutions utilize an unsupervised representation learning phase prior to fine-tuning downstream task classifiers. In this case, however, the overall pe...
Fluorescent labels, commonly used in highly sensitive analytical techniques for detecting and tracking biomolecules in critical fields like cellular biology, medicine, medicinal chemistry, and environmental science, are currently too expensive for ro...
Current object detection methods deployed in closed-circuit television (CCTV) systems experience substantial performance degradation due to domain gaps between training datasets and real-world environments. At the same time, increasing privacy concer...
The global increase of cardiovascular diseases is linked to the shift towards unbalanced diets with increasing salt and fat intake. This has led to a growing consumers’ interest in more balanced food products, which explains the growing number of hea...
Protein dynamics play important roles in biological functions, which accompany allosteric structure changes. Diffracted X-ray blinking (DXB) uses monochromatic X-rays and nanocrystal probes. The intramolecular motion of target proteins is analyzed fr...
In unsupervised cross-domain remote sensing road extraction, severe data distribution shifts and heterogeneous background interference significantly constrain model performance. In addition to appearance shift, source and target images acquired by di...
Background: Gait event detection from inertial sensors offers scalable insights into locomotor health, with applications in clinical monitoring and mobile health. However, supervised methods are limited by scarce annotations, device variability, and...
Fluorescent labels are key tools in a wide range of modern scientific applications, such as fluorescence microscopy, flow cytometry, histochemistry, direct and indirect immunochemistry, and fluorescence in situ hybridization (FISH). Small fluorescent...
Deep neural network-based fault diagnosis is gaining significant attention within the Industry 4.0 framework, yet practical deployment is still hindered by domain shift, partial label mismatch, and class imbalance. In this regard, this paper proposes...
30 September 2013
The identification of metabolites in drug discovery is important. At present, radioisotopes and mass spectrometry are both widely used. However, rapid and comprehensive identification is still laborious and difficult. In this study, we developed ne...
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