158 research outputs found

    The status quo of short videos as a source of health information regarding bowel preparation before colonoscopy

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    BackgroundFor high-quality colonoscopies, adequate bowel preparation is a prerequisite, closely associated with the diagnostic accuracy and therapeutic safety of colonoscopy. Although popular-science short videos can help people quickly access health information, the overall quality of such short videos as a source of health information regarding bowel preparation before colonoscopy is unclear. Therefore, we intend to conduct a cross-sectional study to investigate the quality of bowel preparation information before colonoscopy through short videos taken on TikTok and Bilibili.MethodsThe Chinese phrases “colonoscopy” and “bowel preparation” were used as keywords to search for and screen the top 100 videos in the comprehensive rankings on TikTok and Bilibili. The Global Quality Score (GQS) and the modified DISCERN score were used to assess the quality of the information provided in these short videos.ResultsA total of 186 short videos were included in this study; 56.5% of them were posted by health professionals, whereas 43.5% of them were posted by nonhealth professionals. The overall quality of these videos was unsatisfactory, with a median DISCERN score of 3 (2–4) and a median GQS of 3 (3–4). The radar maps showed that videos posted by gastroenterologists had higher completeness scores regarding outcomes, management, and risk factors, while nongastroenterologists had higher completeness scores concerning adverse effects, symptoms, and definitions of bowel preparation. Additionally, the median DISCERN score and GQS of the videos posted by gastroenterologists were 3 (3–4) and 3 (3–4), respectively, whereas the quality of the videos posted by patients was the worst, with a median DISCERN score of 2 (1–2) and a median GQS of 2 (1.25–3).ConclusionIn conclusion, the overall quality of health information-related videos on bowel preparation before colonoscopy posted on specified short video platforms was not satisfactory. Gastroenterologists provide more information on the outcomes, management, and risk factors for bowel preparation before colonoscopy, while nongastroenterologists focus on adverse effects, symptoms, and definitions of bowel preparation

    Decision Fusion for Large-Scale Sensor Networks with Nonideal Channels

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    Since there has been an increasing interest in the areas of Internet of Things (IoT) and artificial intelligence that often deals with a large number of sensors, this chapter investigates the decision fusion problem for large-scale sensor networks. Due to unavoidable transmission channel interference, we consider sensor networks with nonideal channels that are prone to errors. When the fusion rule is fixed, we present the necessary condition for the optimal sensor rules that minimize the Monte Carlo cost function. For the K-out-of-L fusion rule chosen very often in practice, we analytically derive the optimal sensor rules. For general fusion rules, a Monte Carlo Gauss-Seidel optimization algorithm is developed to search for the optimal sensor rules. The complexity of the new algorithm is of the order of OLN compared with OLNL of the previous algorithm that was based on Riemann sum approximation, where L is the number of sensors and N is the number of samples. Thus, the proposed method allows us to design the decision fusion rule for large-scale sensor networks. Moreover, the algorithm is generalized to simultaneously search for the optimal sensor rules and the optimal fusion rule. Finally, numerical examples show the effectiveness of the new algorithms for large-scale sensor networks with nonideal channels

    A case report of neuralgic amyotrophy

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    Neuralgic muscular atrophy is not uncommon in clinical practice. Due to the different branches of brachial plexus involved in the lesion, the clinical symptoms are different, and there is a lack of clear imaging diagnostic criteria, so the diagnosis of this disease brings great challenges to clinicians. We have certain experience in the diagnosis and treatment of this disease, and hereby select a representative case of neuralgic muscular atrophy to share its diagnosis and treatment process, focusing on analyzing the characteristic symptoms of this disease, valuable imaging data and targeted treatment, so as to enable clinicians to better understand this disease

    Conceptual design and progress of transmitting \sim MV DC HV into 4 K LHe detectors

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    A dual-phase TPC (Time Projection Chamber) is more advanced in characterizing an event than a single-phase one because it can, in principle, reconstruct the 3D (X-Y-Z) image of the event, while a single-phase detector can only show a 2D (X-Y) picture. As a result, more enriched physics is expected for a dual-phase detector than a single-phase one. However, to build such a detector, DC HV (High Voltage) must be delivered into the chamber (to have a static electric field), which is a challenging task, especially for an LHe detector due to the extremely low temperature, \sim 4 K, and the very high voltage, \sim MV (Million Volts). This article introduces a convincing design for transmitting \sim MV DC into a 4 K LHe detector. We also report the progress of manufacturing a 100 kV DC feedthrough capable of working at 4 K. Surprisingly, we realized that the technology we developed here might be a valuable reference to the scientists and engineers aiming to build residential bases on the Moon or Mars

    Searching for ER and/or NR-like dark matter signals with the especially low background liquid helium TPCs

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    In the Dark Matter (DM) direct detection community, the absence of convincing signals has become a ``new normal'' for decades. Among other possibilities, the ``new normal'' might indicate that DM-matter interactions could generate not only the hypothetical NR (Nuclear Recoil) events but also the ER (Electron Recoil) ones, which have often been tagged as backgrounds historically. Further, we argue that ER and NR-like DM signals could co-exist in a DM detector's same dataset. So in total, there would be three scenarios we can search for DM signals: (i) ER excess only, (ii) NR excess only, and (iii) ER and NR excesses combined. To effectively identify any possible DM signal under the three scenarios, a DM detector should (a) have the minimum ER and NR backgrounds and (b) be capable of discriminating ER events from NR ones. Accordingly, we introduce the newly established project, ALETHEIA, which implements liquid helium-filled TPCs (Time Projection Chamber) in hunting for DM. Thanks to the nearly single-digit number of ER and NR backgrounds on 1 ton*yr exposure, presumably, the ALETHEIA detectors should be able to identify any form of DM-induced excess in its ROI (Research Of Interest). As far as we know, ALETHEIA is the first DM direct detection experiment claiming such an inclusive search; conventional detectors search DM mainly on the ``ER excess only'' and/or the ``NR excess only'' channel, not the ``ER and NR excesses combined'' channel. In addition, we introduce a preliminary scheme to one of the most challenging R\&D tasks, transmitting 500+ kV into a 4 K LHe detector
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