Experimental Observation of Classical Sub-Wavelength Interference with Thermal-Like Light

We show the experimental observation of the classical sub-wavelength double-slit interference with a pseudo-thermal light source. The experimental results are in agreement with the recent theoretical prediction shown in quant-ph/0404078 (to be appeared in Phys. Rev. A).Comment: 4 pages, 6 figure

Split Learning over Wireless Networks: Parallel Design and Resource Management

Split learning (SL) is a collaborative learning framework, which can train an artificial intelligence (AI) model between a device and an edge server by splitting the AI model into a device-side model and a server-side model at a cut layer. The existing SL approach conducts the training process sequentially across devices, which incurs significant training latency especially when the number of devices is large. In this paper, we design a novel SL scheme to reduce the training latency, named Cluster-based Parallel SL (CPSL) which conducts model training in a "first-parallel-then-sequential" manner. Specifically, the CPSL is to partition devices into several clusters, parallelly train device-side models in each cluster and aggregate them, and then sequentially train the whole AI model across clusters, thereby parallelizing the training process and reducing training latency. Furthermore, we propose a resource management algorithm to minimize the training latency of CPSL considering device heterogeneity and network dynamics in wireless networks. This is achieved by stochastically optimizing the cut layer selection, real-time device clustering, and radio spectrum allocation. The proposed two-timescale algorithm can jointly make the cut layer selection decision in a large timescale and device clustering and radio spectrum allocation decisions in a small timescale. Extensive simulation results on non-independent and identically distributed data demonstrate that the proposed solutions can greatly reduce the training latency as compared with the existing SL benchmarks, while adapting to network dynamics.Comment: The paper has been submitted to IEEE Journal on Selected Areas in Communication

Data Driven Chiller Plant Energy Optimization with Domain Knowledge

Refrigeration and chiller optimization is an important and well studied topic in mechanical engineering, mostly taking advantage of physical models, designed on top of over-simplified assumptions, over the equipments. Conventional optimization techniques using physical models make decisions of online parameter tuning, based on very limited information of hardware specifications and external conditions, e.g., outdoor weather. In recent years, new generation of sensors is becoming essential part of new chiller plants, for the first time allowing the system administrators to continuously monitor the running status of all equipments in a timely and accurate way. The explosive growth of data flowing to databases, driven by the increasing analytical power by machine learning and data mining, unveils new possibilities of data-driven approaches for real-time chiller plant optimization. This paper presents our research and industrial experience on the adoption of data models and optimizations on chiller plant and discusses the lessons learnt from our practice on real world plants. Instead of employing complex machine learning models, we emphasize the incorporation of appropriate domain knowledge into data analysis tools, which turns out to be the key performance improver over state-of-the-art deep learning techniques by a significant margin. Our empirical evaluation on a real world chiller plant achieves savings by more than 7% on daily power consumption.Comment: CIKM2017. Proceedings of the 26th ACM International Conference on Information and Knowledge Management. 201

Artificial intelligence planning and 3D printing augmented modules in the treatment of a complicated hip joint revision: a case report

Total hip revision with osseous defects can be very difficult. Artificial intelligence offers preoperative planning, real-time measurement, and intraoperative judgment, which can guide prothesis placement more accurately. Three-dimensional printed metel augment modules which are made according to the individualized osseous anatomy, can fit the osseous defects well and provide mechanical support. In this case, we used AI to plan the size and position of the acetabular cup and 3D-printed augmented modules in a complicated hip revision with an acetabular bone defects, which achieved stable fixation and relieved hip pain postoperatively

Label-Free Spectral Imaging Unveils Biochemical Mechanisms of Low-Level Laser Therapy on Spinal Cord Injury

Background/Aims: Low-level laser therapy (LLLT) leads to complex photochemical responses during the healing process of spinal cord injury (SCI). Confocal Raman Microspectral Imaging (in combination with multivariate analysis) was adopted to illustrate the underlying biochemical mechanisms of LLLT treatment on a SCI rat model. Methods: Using transversal tissue sections, the Raman spectra can identify areas neighboring the injury site, glial scar, cavity, and unharmed white matter, as well as their correlated cellular alterations, such as demyelination and up-regulation of chondroitin sulfate proteoglycans (CSPGs). Multivariate data analysis methods are used to depict the underlying therapeutic effects by highlighting the detailed content and distribution variations of the biochemical constituents. Results: It is confirmed that photon-tissue interactions might lead to a decay of the inhibitory response to remyelination by suppressing CSPG expression, as also morphologically demonstrated by reduced glial scar and cavity areas. An inter-group comparison semi-quantitatively confirms changes in lipids, phosphatidic acid, CSPGs, and cholesterol during SCI and its LLLT treatment, paving the way for in vitro and in vivo understanding of the biochemical changes accompanying pathobiological SCI events. Conclusion: The achieved results in this work not only have once again proved the well-known cellular mechanisms of SCI, but further illustrate the underlying biochemical variability during LLLT treatment, which provide a sound basis for developing real-time Raman methodologies to monitor the efficacy of the SCI LLLT treatment

Efficacy of early prone or lateral positioning in patients with severe COVID-19: a single-center prospective cohort

Abstract Background Position intervention has been shown to improve oxygenation, but its role in non-invasively ventilated patients with severe COVID-19 has not been assessed. The objective of this study was to investigate the efficacy of early position intervention on non-invasively ventilated patients with severe COVID-19. Methods This was a single-center, prospective observational study in consecutive patients with severe COVID-19 managed in a provisional ICU at Renmin Hospital of Wuhan University from 31 January to 15 February 2020. Patients with chest CT showing exudation or consolidation in bilateral peripheral and posterior parts of the lungs were included. Early position intervention (prone or lateral) was commenced for &amp;gt; 4 hours daily for 10 days in these patients, while others received standard care. Results The baseline parameters were comparable between the position intervention group (n = 17) and the standard care group (n = 35). Position intervention was well-tolerated and increased cumulative adjusted mean difference of SpO2/FiO2 (409, 95% CI 86 to 733) and ROX index (26, 95% CI 9 to 43) with decreased Borg scale (−9, 95% CI −15 to −3) during the first 7 days. It also facilitated absorption of lung lesions and reduced the proportion of patients with high National Early Warning Score 2 (≥ 7) on days 7 and 14, with a trend toward faster clinical improvement. Virus shedding and length of hospital stay were comparable between the two groups. Conclusions This study provides the first evidence for improved oxygenation and lung lesion absorption using early position intervention in non-invasively ventilated patients with severe COVID-19, and warrants further randomized trials. </jats:sec