Hydrogen-related dynamic dielectric behavior of barium titanate single crystals

2005-2006 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Autonomous deployment for load balancing k-surface coverage in sensor networks

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LAACAD: Load bAlancing k-area coverage through autonomous deployment in wireless sensor networks

Session 6B: Coverage & LocalizationAlthough the problem of k-area coverage has been intensively investigated for dense wireless sensor networks (WSNs), how to arrive at a k-coverage sensor deployment that optimizes certain objectives in relatively sparse WSNs still faces both theoretical and practical difficulties. In this paper, we present a practical algorithm LAACAD (Load bAlancing k-Area Coverage through Autonomous Deployment) to move sensor nodes toward k-area coverage, aiming at minimizing the maximum sensing range required by the nodes. LAACAD enables purely autonomous node deployment as it only entails localized computations. We prove the convergence of the algorithm, as well as the (local) optimality of the output. We also show that our optimization objective is closely related to other frequently considered objectives. Therefore, our practical algorithm design also contributes to the theoretical understanding of the k-area coverage problem. Finally, we use extensive simulation results both to confirm our theoretical claims and to demonstrate the efficacy of LAACAD. © 2012 IEEE.postprin

Adopting RFID for body parts tagging: a Local Association Network approach

Adopting an innovative technology often requires extensive intelligence research. A major value indicator for RFID Technology adoption is how the potentials of RFID can translate into actions to improve business operational efficiency [1]. This paper presents a Local Association Network (LAN) approach to developing RFID enabled visibility systems for body tagging. On site testing validates the proposed approach. User feedback strengthens our belief that the proposed approach would help facilitate RFID technology adoption in body tagging. © 2010 IEEE.published_or_final_versio

Intensive expression of Bmi-1 is a new independent predictor of poor outcome in patients with ovarian carcinoma

Background: It has been suggested that the B-cell specific moloney leukemia virus insertion site 1 (Bmi-1) gene plays an oncogenic role in several types of human cancer, but the status of Bmi-1 amplification and expression in ovarian cancer and its clinical/prognostic significance are unclear.Methods: The methods of immunohistochemistry and fluorescence in situ hybridization were utilized to examine protein expression and amplification of Bmi-1 in 30 normal ovaries, 30 ovarian cystadenomas, 40 borderline ovarian tumors and 179 ovarian carcinomas.Results: Intensive expression of Bmi-1 was detected in none of the normal ovaries, 3% cystadenomas, 10% borderline tumors, and 37% ovarian carcinomas, respectively. Amplification of Bmi-1 was detected in 8% of ovarian carcinomas. In ovarian carcinomas, significant positive associations were found between intensive expression of Bmi-1 and the tumors ascending histological grade, later pT/pN/pM and FIGO stages (P < 0.05). In univariate survival analysis of the ovarian carcinoma cohorts, a significant association of intensive expression of Bmi-1 with shortened patient survival (mean 49.3 months versus 100.3 months, p < 0.001) was demonstrated. Importantly, Bmi-1 expression provided significant independent prognostic parameters in multivariate analysis (p = 0.005).Conclusions: These findings provide evidence that intensive expression of Bmi-1 might be important in the acquisition of an invasive and/or aggressive phenotype of ovarian carcinoma, and serve as a independent biomarker for shortened survival time of patients. © 2010 Yang et al; licensee BioMed Central Ltd.published_or_final_versio

A glimpse into Thurston's work

We present an overview of some significant results of Thurston and their impact on mathematics. The final version of this paper will appear as Chapter 1 of the book "In the tradition of Thurston: Geometry and topology", edited by K. Ohshika and A. Papadopoulos (Springer, 2020)

Lipidomics Reveals Early Metabolic Changes in Subjects with Schizophrenia: Effects of Atypical Antipsychotics

There is a critical need for mapping early metabolic changes in schizophrenia to capture failures in regulation of biochemical pathways and networks. This information could provide valuable insights about disease mechanisms, trajectory of disease progression, and diagnostic biomarkers. We used a lipidomics platform to measure individual lipid species in 20 drug-naïve patients with a first episode of schizophrenia (FE group), 20 patients with chronic schizophrenia that had not adhered to prescribed medications (RE group), and 29 race-matched control subjects without schizophrenia. Lipid metabolic profiles were evaluated and compared between study groups and within groups before and after treatment with atypical antipsychotics, risperidone and aripiprazole. Finally, we mapped lipid profiles to n3 and n6 fatty acid synthesis pathways to elucidate which enzymes might be affected by disease and treatment. Compared to controls, the FE group showed significant down-regulation of several n3 polyunsaturated fatty acids (PUFAs), including 20:5n3, 22:5n3, and 22:6n3 within the phosphatidylcholine and phosphatidylethanolamine lipid classes. Differences between FE and controls were only observed in the n3 class PUFAs; no differences where noted in n6 class PUFAs. The RE group was not significantly different from controls, although some compositional differences within PUFAs were noted. Drug treatment was able to correct the aberrant PUFA levels noted in FE patients, but changes in re patients were not corrective. Treatment caused increases in both n3 and n6 class lipids. These results supported the hypothesis that phospholipid n3 fatty acid deficits are present early in the course of schizophrenia and tend not to persist throughout its course. These changes in lipid metabolism could indicate a metabolic vulnerability in patients with schizophrenia that occurs early in development of the disease. © 2013 McEvoy et al

The T7-Primer Is a Source of Experimental Bias and Introduces Variability between Microarray Platforms

Eberwine(-like) amplification of mRNA adds distinct 6–10 bp nucleotide stretches to the 5′ end of amplified RNA transcripts. Analysis of over six thousand microarrays reveals that probes containing motifs complementary to these stretches are associated with aberrantly high signals up to a hundred fold the signal observed in unaffected probes. This is not observed when total RNA is used as target source. Different T7 primer sequences are used in different laboratories and platforms and consequently different T7 primer bias is observed in different datasets. This will hamper efforts to compare data sets across platforms