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Phase change memory (PCM) recently has emerged as a promising technology to meet the fast growing demand for large capacity memory in modern computer systems. In particular, multi-level cell (MLC) PCM that stores multiple bits in a single cell, offers high density with low per-byte fabrication cost. However, despite many advantages, such as good scalability and low leakage, PCM suffers from exceptionally slow write operations, which makes it challenging to be integrated in the memory hiearchy.In this paper, we propose architectural innovations to improve the access time of MLC PCM. Due to cell process variation, composition fluctuation and the relatively small differences among resistance levels, MLC PCM typically employs an iterative write scheme to achieve precise control, which suffers from large write access latency. To address this issue, we propose write truncation (WT) to reduce the number of write iterations with the assistance of an extra error correction code (ECC). We also propose form switch (FS) to reduce the storage overhead of the ECC. By storing highly compressible lines in SLC form, FS improves read latency as well. Our experimental results show that WT and FS improve the effective write/read latency by 57%/28% respectively, and achieve 26% performance improvement over the state of the art.

Most advanced humidity sensors are powered by batteries that need regular charging and replacement, causing environmental problems and complicated management issues. This paradigm has been overcome through the development of new technology based on the concept of simple, self-powered, rapid-response, flexible humidity sensors enabled by the properties of densely packed titanium dioxide (TiO 2 ) nanowire networks. These sensors eliminate the need for an external power source and produce an output voltage that can be readily related to ambient humidity level over a wide range of ambient conditions. They are characterized by rapid response and relaxation times (typically 4.5 and 2.8 s, respectively). These units are mechanically flexible and maintain a constant voltage output after 10 000 bending cycles. This new type of humidity sensor is easily attached to a human finger for use in the monitoring of ambient humidity level in the environment around human skin, near wet objects, or in the presence of moist materials. The unique properties of this new self-powered wearable humidity sensor technology open up a variety of new applications, including the development of electronic skin, personal healthcare products, and smart tracking in the future Internet-of-things.

BackgroundLymph node metastasis (LNM) has been shown to be related to the prognosis of early gastric cancer (EGC). The choice of optimal treatment depends on an accurate pre-operative assessment of LNM status in EGC patients. However, in China, where EGC cases account for only a small part of gastric cancer (GC) cases, there are not enough data to make an accurate assessment. Therefore, this study, which involved a relatively large number of EGC patients, aimed to explore the relationship between clinicopathological characteristics and LNM in EGC.MethodsClinicopathological data from 205 EGC patients who underwent surgical resection at Sun Yat-Sen University Cancer Center from January 2000 to December 2011 were retrospectively analyzed. Clinicopathological characteristics were assessed to identify effective predictive factors for LNM and overall survival.ResultsLNM occurred in 52 (25.37%) EGC cases; of these cases, 18 occurred in intra-mucosal cancers (13 N1, 4 N2 and 1 N3), and 34 occurred in sub-mucosal cancers (22 N1, 7 N2 and 5 N3). Logistic regression analysis demonstrated that tumor differentiation (P=0.002), depth of tumor infiltration (P=0.004), vessel invasion (P=0.012), tumor size (P=0.020) and gender (P=0.022) were risk factors associated with LNM in EGC, listed in order of priority. The overall survival rate was 90.2%. Kaplan-Meier survival analysis showed that overall survival of EGC patients was significantly correlated with LNM (P=0.001), N staging (P<0.001) and invasion of lymphatic or blood vessels (P=0.010), but it was not correlated with tumor size, depth of tumor infiltration or tumor cell differentiation. Moreover, a multiple Cox regression analysis demonstrated that only N staging (P=0.001) could serve as an independent prognostic predictor in EGC patients.ConclusionsBecause LNM independently predicts the prognosis of EGC, endoscopic mucosal resection (EMR) or endoscopic submucosal dissection (ESD) and laparoscopic partial gastrectomy should be cautiously used in high-risk EGC patients. A pre-operative assessment of LNM status based on clinicopathological factors may be useful for therapy planning.

Background2-Zinc-glycoprotein 1 (AZGP1) is a multidisciplinary protein that participates in many important functions in the human body, including fertilization, immunoregulation and lipid mobilization. Recently, it has been shown that AZGP1 is also involved in carcinogenesis and tumor differentiation. In this study, we investigated the expression levels and prognostic value of AZGP1 in primary gastric cancers.Methods and ResultsWe examined the expression of AZGP1 in 35 paired cancerous and matched adjacent noncancerous gastric mucosa tissues by real-time quantitative RT-PCR (qRT-PCR) and western blotting. Furthermore, we analyzed AZGP1 expression in 248 patients who underwent resection procedures between 2005 and 2007 using immunohistochemistry. The relationships between the AZGP1 expression levels, the clinicopathological factors, and patient survival were investigated. AZGP1 expression was significantly reduced at both the mRNA (P = 0.023) and protein levels (P = 0.019) in tumor tissue samples, compared with expression in matched adjacent non-tumor tissue samples. The immunohistochemical staining data showed that AZGP1 expression was significantly decreased in 52.8% (131/248) of gastric adenocarcinoma cases. Clinicopathological analysis showed that the reduced expression of AZGP1 was significantly correlated with tumor location (P = 0.011), histological grade (P = 0.005) and T stage (P = 0.008). Kaplan–Meier survival curves revealed that the reduced expression of AZGP1 was associated with a poor prognosis in gastric adenocarcinoma patients (P = 0.009). Multivariate Cox analysis identified AZGP1 expression was an independent prognostic factor for overall survival of gastric adenocarcinoma patients (HR = 1.681, 95% CI = 1.134–2.494, P = 0.011).ConclusionsOur study suggests that AZGP1 might serve as a candidate tumor suppressor and a potential prognostic biomarker in gastric carcinogenesis.

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