Interaction Analysis of Repeated Measure Data

Extensive penalized variable selection methods have been developed in the past two decades for analyzing high dimensional omics data, such as gene expressions, single nucleotide polymorphisms (SNPs), copy number variations (CNVs) and others. However, lipidomics data have been rarely investigated by using high dimensional variable selection methods. This package incorporates our recently developed penalization procedures to conduct interaction analysis for high dimensional lipidomics data with repeated measurements. The core module of this package is developed in C++. The development of this software package and the associated statistical methods have been partially supported by an Innovative Research Award from Johnson Cancer Research Center, Kansas State University

The hint protocol: Using a broadcast method to enable ID-free data transmission for dense IoT devices

IoT (Internet of Things) has attracted a lot of attention recently. IoT devices need to report their data or status to base stations at various frequencies. The IoT communications observed by a base station normally exhibit the following characteristics: (1) massively connected, (2) lightly loaded per packet, and (3) periodical or at least mostly predictable. The current design principals of communication networks, when applied to IoT scenarios, however, do not fit well to these requirements. For example, an IPv6 address is 128 bits, which is much longer than a 16-bit temperature report. Also, contending to send a small packet is not cost-effective. In this work, we propose a novel framework, which is slot-based, schedule-oriented, and identity-free for uploading IoT devices' data. We show that it fits very well for IoT applications. We propose two schemes, from an ideal one to a more practical one. The main idea is to bundle time slots with certain hashing functions of device IDs, thus significantly reducing transmission overheads, including device IDs and contention overheads

A survey on composition and microbiota of fresh and fermented yak milk at different Tibetan altitudes

Yak milk is a type of milk that people are less familiar with due to its remote geographical location, the particular geographical environment and climatic conditions in Tibet, which may have significant effects on composition, microbiota and fermentation outcome. To investigate the chemical composition and microbiota of fresh and fermented yak milk, and to isolate and characterize the predominant microorganisms in the fermented milk, yak milk (24 fresh and 30 fermented milk samples) was collected from four areas of different altitudes in Tibet, and their microbiological profile and chemical composition were investigated. Yak milk had a higher fat, crude protein, lactose and dry matter content than cow milk. The fermented yak milk showed a great diversity in fat and dry matter levels due to the different ways of processing in different localities, and lower pH and higher lactic acid content compared with commercial cow milk yogurt. Fermented yak milk had a better sanitary quality than fresh yak milk. Three species of lactobacilli (Lactobacillus fermentum, Lactobacillus helveticus and Lactobacillus curvatus) and five species of yeast (Saccharomyces cerevisiae, Candida kefyr, Candida lambica, Candida famat and Candida holmii) were identified phenotypically and encountered as predominant fermentation microbiota. The predominant lactic species in fermented milk was L. fermentu

Give me a hint: An ID-free small data transmission protocol for dense IoT devices

IoT (Internet of Things) has attracted a lot of attention recently. IoT devices need to report their data or status to base stations at various frequencies. The IoT communications observed by a base station normally exhibit the following characteristics: (1) massively connected, (2) lightly loaded per packet, and (3) periodical or at least mostly predictable. The current design principals of communication networks, when applied to IoT scenarios, however, do not fit well to these requirements. For example, an IPv6 address is 128 bits, which is much longer than a 16-bit temperature report. Also, contending to send a small packet is not cost-effective. In this work, we propose a novel framework, which is slot-based, schedule-oriented, and identity-free for uploading IoT devices' data. We show that it fits very well for IoT applications. The main idea is to bundle time slots with certain hashing functions of device IDs, thus significantly reducing transmission overheads, including device IDs and contention overheads. The framework is applicable from small-scale body-area (wearable) networks to large-scale massively connected IoT networks. Our simulation results verify that this framework is very effective for IoT small data uploading