Spontaneous Symmetry Breaking through Mixing

We discuss a model, in which the negative mass square needed in the Higgs mechanism is generated by mixing with a heavy scalar. We have two scalar doublets in the standard model. Phenomenological properties of the heavy new scalar are discussed. The heavy scalar can be detected by the LHC.Comment: 4 page

On the Precision of a Length Measurement

We show that quantum mechanics and general relativity imply the existence of a minimal length. To be more precise, we show that no operational device subject to quantum mechanics, general relativity and causality could exclude the discreteness of spacetime on lengths shorter than the Planck length. We then consider the fundamental limit coming from quantum mechanics, general relativity and causality on the precision of the measurement of a length.Comment: 5 pages, to appear in the proceedings of the 2006 International School of Subnuclear Physics in Erice and in ''Young Scientists'' online-only supplement of the European Physical Journal C-Direct (Springer

Edge states in Open Antiferromagnetic Heisenberg Chains

In this letter we report our results in investigating edge effects of open antiferromagnetic Heisenberg spin chains with spin magnitudes $S=1/2, 1,3/2,2$ using the density-matrix renormalization group (DMRG) method initiated by White. For integer spin chains, we find that edge states with spin magnitude $S_{edge}=S/2$ exist, in agreement with Valence-Bond-Solid model picture. For half-integer spin chains, we find that no edge states exist for $S=1/2$ spin chain, but edge state exists in $S=3/2$ spin chain with $S_{edge}=1/2$, in agreement with previous conjecture by Ng. Strong finite size effects associated with spin dimmerization in half-integer spin chains will also be discussed.Comment: 4 pages, RevTeX 3.0, 5 figures in a separate uuencoded postscript file. Replaced once to enlarge the acknowlegement

Oreoglanis infulatus , a new species of glyptosternine catfish (Siluriformes: Sisoridae) from central Vietnam

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/72781/1/j.1095-8649.2001.tb00183.x.pd

Eastern medicine approaches to male infertility.

Male factor is a common cause of infertility and the male partner must be systematically evaluated in the workup of every infertile couple. Various Eastern medical strategies have been tried with variable success. This article describes the clinical effects of Eastern medicine approaches including acupuncture, Chinese herbal medicine, massage, yoga, tai chi, and qi gong, which could improve the sperm parameters and motility, genital inflammatory conditions, as well as immune system disorders, sexual dysfunction, and varicocele. Acupuncture reduces inflammation, increases sperm motility, improves semen parameters, modulates the immune system, and improves sexual and ejaculatory dysfunction in male infertility. The clinical effects may be mediated via activation of somatic afferent nerves innervating the skin and muscle. Chinese herbal medicines may also exert helpful effects in male infertility, and it is worth noting that some herbal drugs may result in male infertility. Massage also exerts positive effects in male infertility. Nevertheless, the mechanisms of clinical effects are unclear. Tai chi, qi gong, and yoga have not been investigated in male infertility, but it has been reported to regulate endocrine and central or autonomic nervous systems. In conclusion, Eastern medical approaches have beneficial on reproductive effects in male infertility. However, future well-designed, randomized, clinical control trials are needed to evaluate the safety, efficacy, and mechanisms of Eastern medical approaches for male infertility.postprin

Optimizing CNN-based segmentation with deeply customized convolutional and deconvolutional architectures on FPGA

Convolutional Neural Networks (CNNs) based algorithms have been successful in solving image recognition problems, showing very large accuracy improvement. In recent years, deconvolution layers are widely used as key components in the state-of-the-art CNNs for end-to-end training and models to support tasks such as image segmentation and super resolution. However, the deconvolution algorithms are computationally intensive which limits their applicability to real time applications. Particularly, there has been little research on the efficient implementations of deconvolution algorithms on FPGA platforms which have been widely used to accelerate CNN algorithms by practitioners and researchers due to their high performance and power efficiency. In this work, we propose and develop deconvolution architecture for efficient FPGA implementation. FPGA-based accelerators are proposed for both deconvolution and CNN algorithms. Besides, memory sharing between the computation modules is proposed for the FPGA-based CNN accelerator as well as for other optimization techniques. A non-linear optimization model based on the performance model is introduced to efficiently explore the design space in order to achieve optimal processing speed of the system and improve power efficiency. Furthermore, a hardware mapping framework is developed to automatically generate the low-latency hardware design for any given CNN model on the target device. Finally, we implement our designs on Xilinx Zynq ZC706 board and the deconvolution accelerator achieves a performance of 90.1 GOPS under 200MHz working frequency and a performance density of 0.10 GOPS/DSP using 32-bit quantization, which significantly outperforms previous designs on FPGAs. A real-time application of scene segmentation on Cityscapes Dataset is used to evaluate our CNN accelerator on Zynq ZC706 board, and the system achieves a performance of 107 GOPS and 0.12 GOPS/DSP using 16-bit quantization, and supports up to 17 frames per second for 512x512 image inputs with a power consumption of only 9.6W

Effect of berberine on insulin resistance in women with polycystic ovary syndrome: study protocol for a randomized multicenter controlled trial.

BACKGROUND: Insulin resistance and hyperinsulinemia play a key role in the pathogenesis of polycystic ovary syndrome (PCOS), which is characterized by hyperandrogenism, ovulatory dysfunction, and presence of polycystic ovaries on pelvic scanning. Insulin resistance is significantly associated with the long-term risks of metabolic syndrome and cardiovascular disease. Berberine has effects on insulin resistance but its use in women with PCOS has not been fully investigated. In this paper, we present a research design evaluating the effects of berberine on insulin resistance in women with PCOS. METHODS/DESIGN: This is a multicenter, randomized, placebo-controlled and double-blind trial. A total of 120 patients will be enrolled in this study and will be randomized into two groups. Berberine or placebo will be taken orally for 12 weeks. The primary outcome is the whole body insulin action assessed with the hyperinsulinemic-euglycemic clamp. DISCUSSION: We postulate that women with PCOS will have improved insulin resistance following berberine administration. TRIAL REGISTRATION: This study is registered at ClinicalTrials.gov, NCT01138930.published_or_final_versio

The predominant learning approaches of medical students

Background By identifying medical students’ learning approaches and the factors that influence students’ learning approaches, medical schools and health care institutions are better equipped to intervene and optimize their learning experience. The aims of our study is to determine the predominant learning approach amongst medical students on a clinical posting in a hospital in Singapore and to examine the demographic factors that affect their learning approach. Methods The Approaches and Study Skills Inventory for Students (ASSIST) questionnaire was administered to 250 medical students from various medical schools on clinical attachment to the Obstetrics and Gynaecology (O&G) department of KK Women’s and Children’s Hospital (KKH) Singapore between March 2013 and May 2015 to determine students’ predominant learning approaches. Multinomial logistic regression was used to examine the association between demographic factors (age, gender and highest education qualification) and predominant learning approach. A cut-off of p \u3c 0.05 was used for statistical significance. Results Amongst 238 students with one predominant learning approach, 96 (40.3%) and 121 students (50.8%) adopted the deep and strategic approach respectively, whilst only 21 (8.8%) adopted the surface approach. Male students appeared less likely to adopt the strategic learning approach than female students (p value = 0.06). Predominant learning approaches were not influenced by demographic characteristics such as age, gender and highest educational qualifications. Conclusions This study provided insight into the learning approaches of a heterogeneous group of medical students in Singapore. While it is encouraging that the majority of students predominantly utilised the deep and strategic learning approach, there was a significant proportion of students who utilised the surface approach. Interventions can be explored to promote deeper learning amongst these students

Biophysical Characteristics of Meridians and Acupoints: A Systematic Review

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