213 research outputs found

    Meta-Transformer: A Meta-Learning Framework for Scalable Automatic Modulation Classification

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    Recent advances in deep learning (DL) have led many contemporary automatic modulation classification (AMC) techniques to use deep networks in classifying the modulation type of incoming signals at the receiver. However, current DL-based methods face scalability challenges, particularly when encountering unseen modulations or input signals from environments not present during model training, making them less suitable for real-world applications like software-defined radio devices. In this paper, we introduce a scalable AMC scheme that provides flexibility for new modulations and adaptability to input signals with diverse configurations. We propose the Meta-Transformer, a meta-learning framework based on few-shot learning (FSL) to acquire general knowledge and a learning method for AMC tasks. This approach empowers the model to identify new unseen modulations using only a very small number of samples, eliminating the need for complete model retraining. Furthermore, we enhance the scalability of the classifier by leveraging main-sub transformer-based encoders, enabling efficient processing of input signals with diverse setups. Extensive evaluations demonstrate that the proposed AMC method outperforms existing techniques across all signal-to-noise ratios (SNRs) on RadioML2018.01A. The source code and pre-trained models are released at https://github.com/cheeseBG/meta-transformer-amc

    EUNNet: Efficient UN-Normalized Convolution Layer for Stable Training of Deep Residual Networks Without Batch Normalization Layer

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    Batch Normalization (BN) is an essential component of the Deep Neural Networks (DNNs) architectures. It helps improve stability, convergence, and generalization. However, studies are showing that BN might introduce several concerns. Although there are methods for training DNNs without BN using proper weight initialization, they require several learnable scalars or accurate fine-tuning to the training hyperparameters. As a result, in this study, we aim to stabilize the training process of un-normalized networks without using proper weight initialization and to minimize the hyperparameters fine-tuning step. We propose EUNConv, an Efficient UN-normalized Convolutional layer, which helps train un-normalized Deep Residual Networks (ResNets) by using hyperparameters of the normalized networks. Furthermore, we introduce Efficient UN-normalized Neural Network (EUNNet), which replaces all of the conventional convolutional layers of ResNets with our proposed EUNConv. Experimental results show that the proposed EUNNet achieves the same or even better performance than previous methods in various tasks: image recognition, object detection, and segmentation. In particular, EUNNet requires less fine-tuning and less sensitivity to hyperparameters than previous methods

    Antinociceptive effect of intermittent fasting via the orexin pathway on formalin-induced acute pain in mice

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    Abstract It has been suggested that stress responses induced by fasting have analgesic effects on nociception by elevating the levels of stress-related hormones, while there is limited understanding of pain control mechanisms. Here, we investigated whether acute or intermittent fasting alleviates formalin-induced pain in mice and whether spinal orexin A (OXA) plays a role in this process. 6, 12, or 24 h acute fasting (AF) and 12 or 24 h intermittent fasting (IF) decreased the second phase of pain after intraplantar formalin administration. There was no difference in walking time in the rota-rod test and distance traveld in the open field test in all groups. Plasma corticosterone level and immobility time in the forced swim test were increased after 12 h AF, but not after 12 h IF. 12 h AF and IF increased not only the activation of OXA neurons in the lateral hypothalamus but also the expression of OXA in the lateral hypothalamus and spinal cord. Blockade of spinal orexin 1 receptor with SB334867 restored formalin-induced pain and spinal c-Fos immunoreactivity that were decreased after 12 h IF. These results suggest that 12 h IF produces antinociceptive effects on formalin-induced pain not by corticosterone elevation but by OXA-mediated pathway

    Retrospective analysis of sepsis in cutaneous T-cell lymphoma reveals significantly greater risk in Black patients.

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    BACKGROUND: Sepsis is a leading cause of morbidity, mortality, and resource utilization among patients with cutaneous T-cell lymphoma (CTCL). OBJECTIVE: To characterize the demographic, clinical, and microbial attributes distinguishing patients with CTCL sepsis from other patients with non-Hodgkin lymphoma (NHL) sepsis and patients with CTCL in general. METHODS: Two-part retrospective cohort study at an academic medical center from 2001-2019 involving patients with CTCL (n = 97) and non-CTCL NHL (n = 88) admitted with sepsis, and a same-institution CTCL patient database (n = 1094). Overall survival was estimated by Kaplan-Meier analyses. RESULTS: Patients with CTCL sepsis were more likely to be older, Black, experience more sepsis episodes, die or be readmitted within 30 days of an inpatient sepsis episode, and develop Gram-positive bacteremia than patients with non-CTCL NHL sepsis. Staphylococcus aureus and Escherichia coli were the most frequently speciated organisms in CTCL (26%) and non-CTCL NHL (14%), respectively. No between-group differences were identified regarding sex, presence of central line, chemotherapy use, or disease stage. Compared with general patients with CTCL, patients with sepsis were Black and exhibited advanced-stage disease, higher body surface area involvement, and higher lactate dehydrogenase levels. LIMITATIONS: Single institution, retrospective nature may limit generalizability. CONCLUSION: Awareness of CTCL-specific risk factors is crucial for guiding sepsis prevention and improving patient outcomes

    Context Dependent Memory in the Wilds

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    Memory retrieval is influenced by both prior and current experiences. The various factors (e.g., frequency, recency, or similarity) may interfere during retrieval due to prior experiences, while the context-dependent memory effect may enhance based on present experiences. Most memory research has been limited to controlled laboratory settings, but this study aims to examine memory retrieval in a more natural setting by using a GPS application (e.g., Traccar Client) to track participants’ daily GPS locations every 60 seconds for 5 weeks. Participants were then asked to recall their locations at a specific time, choosing from all locations visited in the previous 4 weeks. Results demonstrated the existence of the context-dependent memory effect in real-world settings, with more frequent or recent visits leading to increased correct responses. This study is the first to use the current methodology to study the context-dependent memory effect and to measure an individual’s genuine memories in a more ecologically valid way

    Information extraction and artwork pricing

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    Traditional art pricing models often lack fine measurements of painting content. This paper proposes a new content measurement: the Shannon information quantity measured by the singular value decomposition (SVD) entropy of the painting image. Using a large sample of artworks' auction records and images, we show that the SVD entropy positively affects the sales price at 1% significance level. Compared to the other commonly adopted content variables, the SVD entropy has advantages in variable significance, sample robustness as well as model fit. Considering the convenient availability of digital painting images and the straightforward calculation algorithm of this measurement, we expect its wide application in future research

    Safety, tolerability, pharmacokinetics and pharmacodynamics of multiple ascending doses of the novel long-acting glucagon analogue HM15136 in overweight and obese patients with co-morbidities

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    Aim To evaluate the safety, tolerability, pharmacokinetics and pharmacodynamics of multiple ascending doses of the novel long-acting glucagon analogue HM15136 in overweight/obese patients with co-morbidities, with and without type 2 diabetes (T2D).Materials and Methods This was a phase 1, double-blind, randomized, placebo-controlled, two-part trial with a 12-week treatment period of once-weekly subcutaneous HM15136 (0.02/0.04/0.06 mg/kg). Part 1 included patients with dyslipidaemia and/or hypertension and no T2D. Part 2 included patients with dyslipidaemia and/or hypertension plus T2D.Results In part 1, 23/27 (85.2%) patients receiving HM15136 and all patients receiving placebo (9/9 [100%]) experienced a treatment-emergent adverse event (TEAE). Five of 27 (18.5%) patients receiving HM15136 developed anti-HM15136 antibodies. Dose-dependent increases in mean HM15136 serum concentration and fasting plasma glucose (FPG) were observed, as were dose-dependent weight reductions of 0.5%/2.3%/2.6% at doses of 0.02/0.04/0.06 mg/kg, respectively. In part 2, 8/12 (66.7%) patients receiving HM15136 and all patients receiving placebo (4/4 [100.0%]) reported a TEAE. Two (16.7%) patients developed anti-HM15136 antibodies. Dose-dependent increases in mean HM15136 serum concentration were observed. FPG of more than 200 mg/dL was reported in 4/9 (44.4%) and 2/3 (66.7%) patients receiving 0.02 and 0.06 mg/kg, respectively. The 0.06 mg/kg dose was not tolerated in part 2 because of hyperglycaemia. Patients receiving 0.02 mg/kg showed a 0.9% weight reduction. No serious TEAEs leading to discontinuation were reported in either study part.Conclusions This study of HM15136 provides a preliminary safety and tolerability profile with initial insights into its efficacy profile

    Narrowband ultraviolet B response in cutaneous T-cell lymphoma is characterized by increased bacterial diversity and reduced Staphylococcus aureus and Staphylococcus lugdunensis

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    Skin microbiota have been linked to disease activity in cutaneous T-cell lymphoma (CTCL). As the skin microbiome has been shown to change after exposure to narrowband ultraviolet B (nbUVB) phototherapy, a common treatment modality used for CTCL, we performed a longitudinal analysis of the skin microbiome in CTCL patients treated with nbUVB. 16S V4 rRNA gene amplicon sequencing for genus-level taxonomic resolution, tuf2 amplicon next generation sequencing for staphylococcal speciation, and bioinformatics were performed on DNA extracted from skin swabs taken from lesional and non-lesional skin of 25 CTCL patients receiving nbUVB and 15 CTCL patients not receiving nbUVB from the same geographical region. Disease responsiveness to nbUVB was determined using the modified Severity Weighted Assessment Tool: 14 (56%) patients responded to nbUVB while 11 (44%) patients had progressive disease. Microbial α-diversity increased in nbUVB-responders after phototherapy. The relative abundance of Staphylococcus, Corynebacterium, Acinetobacter, Streptococcus, and Anaerococcus differentiated nbUVB responders and non-responders after treatment (q\u3c0.05). Microbial signatures of nbUVB-treated patients demonstrated significant post-exposure depletion of S. aureus (q=0.024) and S. lugdunensis (q=0.004) relative abundances. Before nbUVB, responder lesional skin harboured higher levels of S. capitis (q=0.028) and S. warneri (q=0.026) than non-responder lesional skin. S. capitis relative abundance increased in the lesional skin of responders (q=0.05) after phototherapy; a similar upward trend was observed in non-responders (q=0.09). Post-treatment skin of responders exhibited significantly reduced S. aureus (q=0.008) and significantly increased S. hominis (q=0.006), S. pettenkoferi (q=0.021), and S. warneri (q=0.029) relative abundances compared to that of no-nbUVB patients. Staphylococcus species abundance was more similar between non-responders and no-nbUVB patients than between responders and no-nbUVB patients. In sum, the skin microbiome of CTCL patients who respond to nbUVB is different from that of non-responders and untreated patients, and is characterized by shifts in S. aureus and S. lugdunensis. Non-responsiveness to phototherapy may reflect more aggressive disease at baseline
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