Experimental studies on the shape and path of small air bubbles rising in clean water

This Letter reports experiments on the shape and path of air bubbles (diameter range 0.1–0.2 cm) rising in clean water. We find that bubbles in this diameter range have two steady shapes, a sphere and an ellipsoid, depending on the size of the capillary tube from which they detach. The spherical bubbles move significantly slower than the ellipsoidal ones of equivalent volume. Bubbles with diameter less than about 0.15 cm rise rectilinearly. The larger spherical bubbles follow zigzag paths while the larger ellipsoidal bubbles follow spiral paths

Cascaded Code Distributed Computing With Low Complexity and Improved Flexibility

Coded distributed computing (CDC), proposed by Li et al., offers significant potential for reducing the communication load in MapReduce computing systems. In the setting of the cascaded CDC that consisting of $K$ nodes, $N$ input files, and $Q$ output functions, the objective is to compute each output function through $s\geq 1$ nodes with a computation load $r\geq 1$, enabling the application of coding techniques during the Shuffle phase to achieve minimum communication load. However, a significant limitation in most existing cascaded CDC schemes is their demand for splitting the original data into an exponentially growing number of input files and requiring an exponentially large number of output functions, which imposes stringent requirements for implementation. In this paper, we focus on the cascaded case of $K/s\in\mathbb{N}$, deliberately designing the strategy of data placement and output functions assignment based on a grouping method, such that a low-complexity Shuffle strategy is achievable. The main advantages of the proposed scheme include: 1) the multicast gains equal to $(r+s-1)(1-1/s)$ and $r+s-1$ which is approximate to $r+s-1$ when $s$ is relatively large, and the communication load is quite approximate to or surprisingly better than the optimal state-of-the-art scheme proposed by Li et al.; 2) the proposed scheme requires significantly less number of input files and output functions; 3) all the operations are implemented over the minimum binary field $\mathbb{F}_2$ in the one-shot fashion. Finally, we derive a new converse bound for the cascaded CDC framework, under the given strategies of data placement and output functions assignment. We demonstrate that the communication load of the proposed scheme is order optimal within a factor of $2$; and is also approximately optimal when $K$ is sufficiently large for a given $r$

Recent Advances in Graph-based Machine Learning for Applications in Smart Urban Transportation Systems

The Intelligent Transportation System (ITS) is an important part of modern transportation infrastructure, employing a combination of communication technology, information processing and control systems to manage transportation networks. This integration of various components such as roads, vehicles, and communication systems, is expected to improve efficiency and safety by providing better information, services, and coordination of transportation modes. In recent years, graph-based machine learning has become an increasingly important research focus in the field of ITS aiming at the development of complex, data-driven solutions to address various ITS-related challenges. This chapter presents background information on the key technical challenges for ITS design, along with a review of research methods ranging from classic statistical approaches to modern machine learning and deep learning-based approaches. Specifically, we provide an in-depth review of graph-based machine learning methods, including basic concepts of graphs, graph data representation, graph neural network architectures and their relation to ITS applications. Additionally, two case studies of graph-based ITS applications proposed in our recent work are presented in detail to demonstrate the potential of graph-based machine learning in the ITS domain

Coded Caching Schemes for Two-dimensional Caching-aided Ultra-Dense Networks

Coded caching technique is an efficient approach to reduce the transmission load in networks and has been studied in heterogeneous network settings in recent years. In this paper, we consider a new widespread caching system called $(K_1,K_2,U,r,M,N)$ two-dimensional (2D) caching-aided ultra-dense network (UDN) with a server containing $N$ files, $K_1K_2$ cache nodes arranged neatly on a grid with $K_1$ rows and $K_2$ columns, and $U$ cache-less users randomly distributed around cache nodes. Each cache node can cache at most $M\leq N$ files and has a certain service region by Euclidean distance. The server connects to users through an error-free shared link and the users in the service region of a cache node can freely retrieve all cached contents of this cache node. We aim to design a coded caching scheme for 2D caching-aided UDN systems to reduce the transmission load in the worst case while meeting all possible users' demands. First, we divide all possible users into four classes according to their geographical locations. Then our first order optimal scheme is proposed based on the Maddah-Ali and Niesen scheme. Furthermore, by compressing the transmitted signals of our first scheme based on Maximum Distance Separable (MDS) code, we obtain an improved order optimal scheme with a smaller transmission load.Comment: 44 page

Derivatives Usage, Operational Hedge and Exchange Rate Regime: Evidence from Chinese Firms

In 2005, China liberalized its foreign exchange regime, and allows its currency Renminbi (RMB) to fluctuate within a managed band width. This important economic event exposes Chinese firms to considerable foreign exchange risk. The aim of this study is to analyze the relationship between the new exchange rate regime and firm’s risk management strategy. The study uses a sample of 30 Chinese firms listed in Hong Kong Stock Exchange. The use of foreign currency derivatives and operational hedging are investigated simultaneously. The information on the derivatives usage and currency composition of debt and assets and revenues are extracted from the footnotes of firms’ annual reports from 2004 to 2007. The study observes that neither more Chinese firms use foreign currency derivatives, nor a matching took place after the introduction of a managed floating exchange rate regime. Further investigation has been made by comparing the differences of firm-level characteristics between hedgers and non-hedgers. The evidence shows firms with smaller size and higher foreign revenue tend to hedge. The findings are inconsistent with the hypothesis that large firms tend to hedge and firms with higher foreign revenue are likely to leave foreign currency liabilities un-hedged. The finding supports the hypothesis that hedging positively linked with the level of foreign debt. Five sets of explanation are proposed. First, the rigidity of RMB exchange rate may hinder the exchange-rate hedging. Second, it may be the issue of the depth of market that precludes firms from using foreign currency derivatives extensively. Third, the phenomenon of one-way-bet that strong expectation to RMB appreciation may fuel firms in engaging the game of mismatch. Forth, it can be the ownership of firms, i.e. state- owned enterprises (SOEs) in the study impacts the finding. Finally, it can be attribute to institutional problem, such as unfamiliarity to the currency derivatives, or lacking institutional service. The research ends with a short discussion on limitations of the current study and highlights insight shall be further explored in this field

Learn to Generate Time Series Conditioned Graphs with Generative Adversarial Nets

Deep learning based approaches have been utilized to model and generate graphs subjected to different distributions recently. However, they are typically unsupervised learning based and unconditioned generative models or simply conditioned on the graph-level contexts, which are not associated with rich semantic node-level contexts. Differently, in this paper, we are interested in a novel problem named Time Series Conditioned Graph Generation: given an input multivariate time series, we aim to infer a target relation graph modeling the underlying interrelationships between time series with each node corresponding to each time series. For example, we can study the interrelationships between genes in a gene regulatory network of a certain disease conditioned on their gene expression data recorded as time series. To achieve this, we propose a novel Time Series conditioned Graph Generation-Generative Adversarial Networks (TSGG-GAN) to handle challenges of rich node-level context structures conditioning and measuring similarities directly between graphs and time series. Extensive experiments on synthetic and real-word gene regulatory networks datasets demonstrate the effectiveness and generalizability of the proposed TSGG-GAN

Investigation and Research on Physical Education and Health Curriculum of K-12 School in Guizhou Province

The purpose of this study is to investigate the current situation of physical education and health curriculum in primary and secondary schools in Guizhou Province, and to provide reference for promoting the better implementation of physical education and health curriculum in Guizhou Province. In the form of questionnaires, 1549 parents\u27 questionnaires and 254 teachers\u27 questionnaires were collected and statistically analyzed in Guizhou Province, China. Use Excel to summarize and analyze the collected questionnaires. The results found the teaching content could basically meet the needs of students. The satisfaction of primary school students, junior high school students and senior high school students with physical education and health curriculum evaluation was 71.6%, 68.4% and 63.6%, respectively. Students\u27 satisfaction with the content of physical education and health curriculum in senior high school decreased; both students and teachers believed that all students had the opportunity to participate in sports activities in physical education and health classes, but the time for skill learning and physical training in PE classes in primary and secondary schools was less than 20 minutes. The intensity of classroom exercise in 60% of primary and secondary schools was less than 75%. 94.1% of teachers control exercise load according to experience, and only 3.9% of schools use intelligent monitoring devices to monitor. 50.9% of primary and junior high school physical education classes did not meet the required number of class hours. 69.6% of the students were satisfied with the elective items in the physical education courses offered, but their satisfaction with the senior high school dropped to 61.6%. Primary and secondary schools in Guizhou Province should continue to increase the construction and investment of physical education and health curriculum venues, equipment and facilities, and optimize the use and development of existing physical education curriculum resources. Physical education teachers should constantly update teaching concepts, improve teaching methods and improve course teaching ability. Schools and teachers should carry out physical education and health courses according to the requirements of physical Education and Health Curriculum Standards, and actively promote the Chinese Health physical Education Curriculum Model put forward by JI Liu professor to ensure a certain exercise load and exercise density

Design of Reconfigurable Intelligent Surface-Aided Cross-Media Communications

A novel reconfigurable intelligent surface (RIS)-aided hybrid reflection/transmitter design is proposed for achieving information exchange in cross-media communications. In pursuit of the balance between energy efficiency and low-cost implementations, the cloud-management transmission protocol is adopted in the integrated multi-media system. Specifically, the messages of devices using heterogeneous propagation media, are firstly transmitted to the medium-matched AP, with the aid of the RIS-based dual-hop transmission. After the operation of intermediate frequency conversion, the access point (AP) uploads the received signals to the cloud for further demodulating and decoding process. Based on time division multiple access (TDMA), the cloud is able to distinguish the downlink data transmitted to different devices and transforms them into the input of the RIS controller via the dedicated control channel. Thereby, the RIS can passively reflect the incident carrier back into the original receiver with the exchanged information during the preallocated slots, following the idea of an index modulation-based transmitter. Moreover, the iterative optimization algorithm is utilized for optimizing the RIS phase, transmit rate and time allocation jointly in the delay-constrained cross-media communication model. Our simulation results demonstrate that the proposed RIS-based scheme can improve the end-to-end throughput than that of the AP-based transmission, the equal time allocation, the random and the discrete phase adjustment benchmarks

First Steps towards Parameter Optimization of Bioelectrochemical Systems using a Microsystems Engineering Approach

There is a growing interest in exploiting bioelectrochemical systems (BESs), such as microbial fuel cells, as an alternative energy source for sustainable living. Certain species of microorganisms, such as Pseudomonas aeruginosa 14 (PA14) wild type, produce electron carriers, Phenazines, which transfers electrons to the anode in the system and produce digital output signal. The electric current generation of BESs is influenced by many biophysical and biochemical parameters in the system, such as glucose level, cell culture community, cell density, PH, and oxygen level. The existing MFCs are at macroscale, and not suitable for parameter optimization; and as a result they are not yet cost effective. Here, we present our first effort in parameter optimization of BESs using a microfluidic device. Microfluidic device affords us an ability to quickly define a physical and chemical environment for PA14, and its compatibility with microscope allows us a real time observation of the responses. We will present experimental results on the roles of carbon sources in PA14 motility and promising results of Phenazines being a chemoattractant to PA14. We will discuss the relation between PA14 motility and biofilm formation, and subsequently electric current generation