486 research outputs found

    Prognosis of Nasopharyngeal Carcinoma in the Elderly is Worse than in Younger Individuals–Experience of a Medical Institute

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    SummaryPurposeWe aimed to evaluate outcomes of the elderly (>65 years) by comparing with younger (<40 years) patients after treatments for nasopharyngeal carcinoma (NPC).Materials and methodsWe retrospectively obtained clinical data from charts for 23 older and 21 younger patients in whom NPC was diagnosed and who underwent curative managements during 2007 and 2011. Occurrence of local recurrence, distant metastasis, and death from any cause were recorded as endpoints. Cox proportional hazards regression was applied to determine age effects on survival risks after adjusting for the potential confounders.ResultsOlder patients more commonly received a diagnosis of chronic diseases than the younger patients (56.5% versus 23.8%, p = 0.036), whereas they were less likely to have received intensive treatments for NPC. After adjusting for medical history and neoadjuvant chemotherapy, older age was the only significant predictor in the study cohort for overall survival and progression-free survival. The adjusted hazard ratio (HR) for death from all causes in older patients was 6.3 (95% confidence interval [CI] = 1.3–30.2), and the adjusted HR for disease progression in older patients was 10.9 (95% CI = 2.3–50.6).ConclusionAging was the only independent prognostic risk factor in this study cohort. Medical history and treatment variations could not fully explain the difference in prognosis. Our results strengthen the need to ameliorate toxicities and improve supportive care for older patients with a diagnosis of NPC

    Multimodal Transformer Distillation for Audio-Visual Synchronization

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    Audio-visual synchronization aims to determine whether the mouth movements and speech in the video are synchronized. VocaLiST reaches state-of-the-art performance by incorporating multimodal Transformers to model audio-visual interact information. However, it requires high computing resources, making it impractical for real-world applications. This paper proposed an MTDVocaLiST model, which is trained by our proposed multimodal Transformer distillation (MTD) loss. MTD loss enables MTDVocaLiST model to deeply mimic the cross-attention distribution and value-relation in the Transformer of VocaLiST. Our proposed method is effective in two aspects: From the distillation method perspective, MTD loss outperforms other strong distillation baselines. From the distilled model's performance perspective: 1) MTDVocaLiST outperforms similar-size SOTA models, SyncNet, and PM models by 15.69% and 3.39%; 2) MTDVocaLiST reduces the model size of VocaLiST by 83.52%, yet still maintaining similar performance.Comment: Submitted to ICASSP 202

    Constant Delivery Delay Protocol Sequences for the Collision Channel Without Feedback

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    International audienceWe consider a collision channel model without feedback based on a time-slotted communication channel shared by K users. In this model, packets transmitted in the same time slot collide with each other and are unrecoverable. Each user accesses the channel according to an internal periodical pattern called protocol sequence. Due to the lack of feedback, users cannot synchronize their protocol sequences, leading to unavoidable collisions and varying throughput. Protocol sequences that provide constant throughput regardless of delay offsets between users are called shift-invariant (SI), they have been studied and characterized in previous work. We propose a new class of SI sequences: Constant Individual Delivery Delay (CIDD) sequences which ensure that the delay between two successfully delivered packets is constant for each user. We present a characterization of CIDD sequences. We also prove that CIDD sequences can achieve the lower bound of SI sequences period but not the optimal throughput

    PEFT for Speech: Unveiling Optimal Placement, Merging Strategies, and Ensemble Techniques

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    Parameter-Efficient Fine-Tuning (PEFT) is increasingly recognized as an effective method in speech processing. However, the optimal approach and the placement of PEFT methods remain inconclusive. Our study conducts extensive experiments to compare different PEFT methods and their layer-wise placement adapting Differentiable Architecture Search (DARTS). We also explore the use of ensemble learning to leverage diverse PEFT strategies. The results reveal that DARTS does not outperform the baseline approach, which involves inserting the same PEFT method into all layers of a Self-Supervised Learning (SSL) model. In contrast, an ensemble learning approach, particularly one employing majority voting, demonstrates superior performance. Our statistical evidence indicates that different PEFT methods learn in varied ways. This variation might explain why the synergistic integration of various PEFT methods through ensemble learning can harness their unique learning capabilities more effectively compared to individual layer-wise optimization.Comment: Accepted to ICASSP 2024 Self-supervision in Audio, Speech and Beyond (SASB) worksho

    Sonomyographic responses during voluntary isometric ramp contraction of the human rectus femoris muscle

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    This paper aims to investigate the relationship between torque and muscle morphological change, which is derived from ultrasound image sequence and termed as sonomyography (SMG), during isometric ramp contraction of the rectus femoris (RF) muscle, and to further compare SMG with the electromyography (EMG) and mechanomyography (MMG), which represent the electrical and mechanical activities of the muscle. Nine subjects performed isometric ramp contraction of knee up to 90% of the maximal voluntary contraction (MVC) at speeds of 45, 22.5 and 15% MVC/s, and EMG, MMG and ultrasonography were simultaneously recorded from the RF muscle. Cross-sectional area, which was referred to as SMG, was automatically extracted from continuously captured ultrasound images using a newly developed image tracking algorithm. Polynomial regression analyses were applied to fit the EMG/MMG/SMG-to-torque relationships, and the regression coefficients of EMG, MMG, and SMG were compared. Moreover, the effect of contraction speed on SMG/EMG/MMG-to-torque relationships was tested by pair-wise comparisons of the mean relationship curves at different speeds for EMG, MMG and SMG. The results show that continuous SMG could provide important morphological parameters of continuous muscle contraction. Compared with EMG and MMG, SMG exhibits different changing patterns with the increase of torque during voluntary isometric ramp contraction, and it is less influenced by the contraction speed

    Body Massage Performance Investigation by Brain Activity Analysis

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    Massage has been widely applied to improve health and reduce stress. However, the performance difference between hands-on treatment and treatment by mechanical devices has been little mentioned. Therefore, the main aim of this paper is to investigate a subject's EEG performance under massage treatment applied by hand and treatment applied by mechanical devices. Massage was applied to four acupoints for three minutes each. The massage acupoint sequence was from left Jian-wai-yu, right Jian-wai-yu, left Zuo-fei-yu, and finally right Zuo-fei-yu. An EEG system of 32 channels was used. Twenty-four volunteers, mainly college students, were enrolled. EEG rhythm powers of each massage sessions were derived. Two-way ANOVA revealed that there were also significant interactions between the massage stage and the massage type on delta (P < 0.01), theta (P < 0.05), and beta rhythms (P < 0.01), and there were significant differences at different stages for the mechanical massage group (F = 5.557, P < 0.01). The mechanical massage group had more significant differences than the hands-on group for stage coherence of around coherence on alpha rhythm. Further rhythm power scalp topography between two massage methods is also investigated
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