Throughput Analysis of CSMA Wireless Networks with Finite Offered-load

This paper proposes an approximate method, equivalent access intensity (EAI), for the throughput analysis of CSMA wireless networks in which links have finite offered-load and their MAC-layer transmit buffers may be empty from time to time. Different from prior works that mainly considered the saturated network, we take into account in our analysis the impacts of empty transmit buffers on the interactions and dependencies among links in the network that is more common in practice. It is known that the empty transmit buffer incurs extra waiting time for a link to compete for the channel airtime usage, since when it has no packet waiting for transmission, the link will not perform channel competition. The basic idea behind EAI is that this extra waiting time can be mapped to an equivalent "longer" backoff countdown time for the unsaturated link, yielding a lower link access intensity that is defined as the mean packet transmission time divided by the mean backoff countdown time. That is, we can compute the "equivalent access intensity" of an unsaturated link to incorporate the effects of the empty transmit buffer on its behavior of channel competition. Then, prior saturated ideal CSMA network (ICN) model can be adopted for link throughput computation. Specifically, we propose an iterative algorithm, "Compute-and-Compare", to identify which links are unsaturated under current offered-load and protocol settings, compute their "equivalent access intensities" and calculate link throughputs. Simulation shows that our algorithm has high accuracy under various offered-load and protocol settings. We believe the ability to identify unsaturated links and compute links throughputs as established in this paper will serve an important first step toward the design and optimization of general CSMA wireless networks with offered-load control.Comment: 6 pages. arXiv admin note: text overlap with arXiv:1007.5255 by other author

G2C: A Generator-to-Classifier Framework Integrating Multi-Stained Visual Cues for Pathological Glomerulus Classification

Pathological glomerulus classification plays a key role in the diagnosis of nephropathy. As the difference between different subcategories is subtle, doctors often refer to slides from different staining methods to make decisions. However, creating correspondence across various stains is labor-intensive, bringing major difficulties in collecting data and training a vision-based algorithm to assist nephropathy diagnosis. This paper provides an alternative solution for integrating multi-stained visual cues for glomerulus classification. Our approach, named generator-to-classifier (G2C), is a two-stage framework. Given an input image from a specified stain, several generators are first applied to estimate its appearances in other staining methods, and a classifier follows to combine visual cues from different stains for prediction (whether it is pathological, or which type of pathology it has). We optimize these two stages in a joint manner. To provide a reasonable initialization, we pre-train the generators in an unlabeled reference set under an unpaired image-to-image translation task, and then fine-tune them together with the classifier. We conduct experiments on a glomerulus type classification dataset collected by ourselves (there are no publicly available datasets for this purpose). Although joint optimization slightly harms the authenticity of the generated patches, it boosts classification performance, suggesting more effective visual cues are extracted in an automatic way. We also transfer our model to a public dataset for breast cancer classification, and outperform the state-of-the-arts significantly.Comment: Accepted by AAAI 201

Implications of C1q/TNF-related protein superfamily in patients with coronary artery disease.

The C1q complement/TNF-related protein superfamily (CTRPs) displays differential effects on the regulation of metabolic homeostasis, governing cardiovascular function. However, whether and how they may serve as predictor/pro-diagnosis factors for assessing the risks of coronary artery disease (CAD) remains controversial. Therefore, we performed a clinical study to elaborate on the implication of CTRPs (CTRP1, CTRP5, CTRP7, and CTRP15) in CAD. CTRP1 were significantly increased, whereas CTRP7 and CTRP15 levels were decreased in CAD patients compared to the non-CAD group. Significant differences in CTRP1 levels were discovered between the single- and triple-vascular-vessel lesion groups. ROC analysis revealed that CTRP7 and CTRP15 may serve as CAD markers, while CTRP1 may serve as a marker for the single-vessel lesion of CAD. CTRP1 and CTRP5 can serve as markers for the triple-vessel lesion. CTRP1 may serve as an independent risk predictor for triple-vessel lesion, whereas CTRP15 alteration may serve for a single-vessel lesion of CAD. CTRP1 may serve as a novel superior biomarker for diagnosis of severity of vessel-lesion of CAD patients. CTRP7, CTRP15 may serve as more suitable biomarker for the diagnosis of CAD patients, whereas CTRP5 may serve as an independent predictor for CAD. These findings suggest CTRPs may be the superior predictive factors for the vascular lesion of CAD and represent novel therapeutic targets against CAD

A study of a clothing image segmentation method in complex conditions using a features fusion model

According to a priori knowledge in complex conditions, this paper proposes an unsupervised image segmentation algorithm to be used for clothing images that combines colour and texture features. First, block truncation encoding is used to divide the traditional three-dimensional colour space into a six-dimensional colour space so that more fine colour features can be obtained. Then, a texture feature based on the improved local binary pattern (LBP) algorithm is designed and used to describe the clothing image with the colour features. After that, according to the statistical appearance law of the object region and background information in the clothing image, a bisection method is proposed for the segmentation operation. Since the image is divided into several subimage blocks, bisection image segmentation will be accomplished more efficiently. The experimental results show that the proposed algorithm can quickly and effectively extract effective clothing regions from complex circumstances without any artificial parameters. The proposed clothing image segmentation method will play an important role in computer vision, machine learning applications, pattern recognition and intelligent systems

Valence band offset of InN/BaTiO3 heterojunction measured by X-ray photoelectron spectroscopy

X-ray photoelectron spectroscopy has been used to measure the valence band offset of the InN/BaTiO(3 )heterojunction. It is found that a type-I band alignment forms at the interface. The valence band offset (VBO) and conduction band offset (CBO) are determined to be 2.25 ± 0.09 and 0.15 ± 0.09 eV, respectively. The experimental VBO data is well consistent with the value that comes from transitivity rule. The accurate determination of VBO and CBO is important for use of semiconductor/ferrroelectric heterojunction multifunctional devices

Regulation of interferon pathway in 2-methoxyestradiol-treated osteosarcoma cells

BACKGROUND: Osteosarcoma is a bone tumor that often affects children and young adults. Although a combination of surgery and chemotherapy has improved the survival rate in the past decades, local recurrence and metastases still develop in 40% of patients. A definite therapy is yet to be determined for osteosarcoma. Anti- tumor compound and a metabolite of estrogen, 2-methoxyestradiol (2-ME) induces cell death in osteosarcoma cells. In this report, we have investigated whether interferon (IFN) pathway is involved in 2-ME-induced anti-tumor effects in osteosarcoma cells. METHODS: 2-ME effects on IFN mRNA levels were determined by Real time PCR analysis. Transient transfections followed by reporter assays were used for investigating 2-ME effects on IFN-pathway. Western blot analyses were used to measure protein and phosphorylation levels of IFN-regulated eukaryotic initiation factor-2 alpha (eIF-2α). RESULTS: 2-ME regulates IFN and IFN-mediated effects in osteosarcoma cells. 2 -ME induces IFN gene activity and expression in osteosarcoma cells. 2-ME treatment induced IFN-stimulated response element (ISRE) sequence-dependent transcription and gamma-activated sequence (GAS)-dependent transcription in several osteosarcoma cells. Whereas, 2-ME did not affect IFN gene and IFN pathways in normal primary human osteoblasts (HOB). 2-ME treatment increased the phosphorylation of eIF-2α in osteosarcoma cells. Furthermore, analysis of osteosarcoma tissues shows that the levels of phosphorylated form of eIF-2α are decreased in tumor compared to normal controls. CONCLUSIONS: 2-ME treatment triggers the induction and activity of IFN and IFN pathway genes in 2-ME-sensitive osteosarcoma tumor cells but not in 2-ME-resistant normal osteoblasts. In addition, IFN-signaling is inhibited in osteosarcoma patients. Thus, IFN pathways play a role in osteosarcoma and in 2-ME-mediated anti-proliferative effects, and therefore targeted induction of IFN signaling could lead to effective treatment strategies in the control of osteosarcoma

Low Loss and Magnetic Field-tuned Superconducting THz Metamaterial

Superconducting terahertz (THz) metamaterial (MM) made from superconducting Nb film has been investigated using a continuous-wave THz spectroscopy with a superconducting split-coil magnet. The obtained quality factors of the resonant modes at 132 GHz and 450 GHz are about three times as large as those calculated for a metal THz MM operating at 1 K, which indicates that superconducting THz MM is a very nice candidate to achieve low loss performance. In addition, the magnetic field-tuning on superconducting THz MM is also demonstrated, which offer an alternative tuning method apart from the existed electric, optical and thermal tuning on THz MM