A Genome Wide Association Study Identifies Common Variants Associated with Lipid Levels in the Chinese Population

Plasma lipid levels are important risk factors for cardiovascular disease and are influenced by genetic and environmental factors. Recent genome wide association studies (GWAS) have identified several lipid-associated loci, but these loci have been identified primarily in European populations. In order to identify genetic markers for lipid levels in a Chinese population and analyze the heterogeneity between Europeans and Asians, especially Chinese, we performed a meta-analysis of two genome wide association studies on four common lipid traits including total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL) and high-density lipoprotein cholesterol (HDL) in a Han Chinese population totaling 3,451 healthy subjects. Replication was performed in an additional 8,830 subjects of Han Chinese ethnicity. We replicated eight loci associated with lipid levels previously reported in a European population. The loci genome wide significantly associated with TC were near DOCK7, HMGCR and ABO; those genome wide significantly associated with TG were near APOA1/C3/A4/A5 and LPL; those genome wide significantly associated with LDL were near HMGCR, ABO and TOMM40; and those genome wide significantly associated with HDL were near LPL, LIPC and CETP. In addition, an additive genotype score of eight SNPs representing the eight loci that were found to be associated with lipid levels was associated with higher TC, TG and LDL levels (P = 5.52×10-16, 1.38×10-6 and 5.59×10-9, respectively). These findings suggest the cumulative effects of multiple genetic loci on plasma lipid levels. Comparisons with previous GWAS of lipids highlight heterogeneity in allele frequency and in effect size for some loci between Chinese and European populations. The results from our GWAS provided comprehensive and convincing evidence of the genetic determinants of plasma lipid levels in a Chinese population

Parallel Algorithm for Wireless Data Compression and Encryption

As the wireless network has limited bandwidth and insecure shared media, the data compression and encryption are very useful for the broadcasting transportation of big data in IoT (Internet of Things). However, the traditional techniques of compression and encryption are neither competent nor efficient. In order to solve this problem, this paper presents a combined parallel algorithm named “CZ algorithm” which can compress and encrypt the big data efficiently. CZ algorithm uses a parallel pipeline, mixes the coding of compression and encryption, and supports the data window up to 1 TB (or larger). Moreover, CZ algorithm can encrypt the big data as a chaotic cryptosystem which will not decrease the compression speed. Meanwhile, a shareware named “ComZip” is developed based on CZ algorithm. The experiment results show that ComZip in 64 b system can get better compression ratio than WinRAR and 7-zip, and it can be faster than 7-zip in the big data compression. In addition, ComZip encrypts the big data without extra consumption of computing resources

Block-Split Array Coding Algorithm for Long-Stream Data Compression

With the advent of IR (Industrial Revolution) 4.0, the spread of sensors in IoT (Internet of Things) may generate massive data, which will challenge the limited sensor storage and network bandwidth. Hence, the study of big data compression is valuable in the field of sensors. A problem is how to compress the long-stream data efficiently with the finite memory of a sensor. To maintain the performance, traditional techniques of compression have to treat the data streams on a small and incompetent scale, which will reduce the compression ratio. To solve this problem, this paper proposes a block-split coding algorithm named “CZ-Array algorithm,” and implements it in the shareware named “ComZip.” CZ-Array can use a relatively small data window to cover a configurable large scale, which benefits the compression ratio. It is fast with the time complexity O(N) and fits the big data compression. The experiment results indicate that ComZip with CZ-Array can obtain a better compression ratio than gzip, lz4, bzip2, and p7zip in the multiple stream data compression, and it also has a competent speed among these general data compression software. Besides, CZ-Array is concise and fits the hardware parallel implementation of sensors

LDPC Decoding on GPU for Mobile Device

A flexible software LDPC decoder that exploits data parallelism for simultaneous multicode words decoding on the mobile device is proposed in this paper, supported by multithreading on OpenCL based graphics processing units. By dividing the check matrix into several parts to make full use of both the local memory and private memory on GPU and properly modify the code capacity each time, our implementation on a mobile phone shows throughputs above 100 Mbps and delay is less than 1.6 millisecond in decoding, which make high-speed communication like video calling possible. To realize efficient software LDPC decoding on the mobile device, the LDPC decoding feature on communication baseband chip should be replaced to save the cost and make it easier to upgrade decoder to be compatible with a variety of channel access schemes

Fast Algorithm of Truncated Burrows-Wheeler Transform Coding for Data Compression of Sensors

Lots of sensors in the IoT (Internet of things) may generate massive data, which will challenge the limited sensor storage and network bandwidth. So the study of big data compression is very useful in the field of sensors. In practice, BWT (Burrows-Wheeler transform) can gain good compression results for some kinds of data, but the traditional BWT algorithms are neither concise nor fast enough for the hardware of sensors, which will limit the BWT block size in a very small and incompetent scale. To solve this problem, this paper presents a fast algorithm of truncated BWT named “CZ-BWT algorithm” and implements it in the shareware named “ComZip.” CZ-BWT supports the BWT block up to 2 GB (or larger) and uses the bucket sort. It is very fast with the time complexity O(N) and fits the big data compression. The experiment results indicate that ComZip with the CZ-BWT filter is obviously faster than bzip2, and it can obtain better compression ratio than bzip2 and p7zip in some conditions. In addition, CZ-BWT is more concise than current BWT with SA (suffix array) sorts and fits the hardware BWT implementation of sensors

Study of Wireless Authentication Center with Mixed Encryption in WSN

WSN (wireless sensor network) has been used in a wide range of applications nowadays. Sensor networks may often relay critical data; thus, security must be a high priority. However, due to their limited computational, energy, and storage resources, sensor nodes are vulnerable to attack. So how to protect sensor nodes from attacks without raising computational capability and energy consumption is a worthwhile issue. A WAC (wireless authentication center) with mixed encryption named "MEWAC" is proposed. MEWAC is based on MCU (Microcontroller Unit) and WiFi (Wireless Fidelity) module and uses RSA, AES (Advanced Encryption Standard), and SHA-1 (Secure Hash Algorithm 1) to provide high performance authentication and data encryption services for sensor nodes. The experimental results show that MEWAC has the advantages of low cost, low power consumption, good performance, and stability; moreover, the authentication protocol improves the security of WSN and reduces the overhead in node authentication

Study of Wireless Authentication Center with Mixed Encryption in WSN

WSN (wireless sensor network) has been used in a wide range of applications nowadays. Sensor networks may often relay critical data; thus, security must be a high priority. However, due to their limited computational, energy, and storage resources, sensor nodes are vulnerable to attack. So how to protect sensor nodes from attacks without raising computational capability and energy consumption is a worthwhile issue. A WAC (wireless authentication center) with mixed encryption named “MEWAC” is proposed. MEWAC is based on MCU (Microcontroller Unit) and WiFi (Wireless Fidelity) module and uses RSA, AES (Advanced Encryption Standard), and SHA-1 (Secure Hash Algorithm 1) to provide high performance authentication and data encryption services for sensor nodes. The experimental results show that MEWAC has the advantages of low cost, low power consumption, good performance, and stability; moreover, the authentication protocol improves the security of WSN and reduces the overhead in node authentication