Study of J/Psi decays into eta Kstar Kstar-bar

We report the first observation of \mPJpsi \to \mPeta\mPKst\mAPKst decay in a \mPJpsi sample of 58 million events collected with the BESII detector. The branching fraction is determined to be $(1.15 \pm 0.13 \pm 0.22)\times 10^{-3}$. The selected signal event sample is further used to search for the \mPY resonance through \mPJpsi \to \mPeta \mPY, \mPY\to\mPKst\mAPKst. No evidence of a signal is seen. An upper limit of \mathrm{Br}(\mPJpsi \to \mPeta \mPY)\cdot\mathrm{Br}(\mPY\to\mPKst\mAPKst) < 2.52\times 10^{-4} is set at the 90% confidence level.Comment: 11 pages, 4 figure

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals &lt;1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

The Physics of the B Factories

This work is on the Physics of the B Factories. Part A of this book contains a brief description of the SLAC and KEK B Factories as well as their detectors, BaBar and Belle, and data taking related issues. Part B discusses tools and methods used by the experiments in order to obtain results. The results themselves can be found in Part C

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)1.

In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field

Forskjeller i lovteksten på norske og internasjonale regnskapsstandarder

Det har vert mye oppmerksomhet rundt de internasjonale regnskapsstandardene de siste årene, der det i 2005 ble det pliktige for børsnoterte selskap å føre regnskapet etter de internasjonale regnskapsstandardene. Det har også vert snakk om at andre bedrifter kan føre regnskap etter de internasjonale regnskapsstandarder. Ut i fra dette ønsket vi å finne ut hva som er forskjellen i de norske og de internasjonale regnskapsstandardene. Vi startet med å samle inn informasjon om rammeverk og oppbyggingen av de ulike standardene i en teoridel. Deretter har vi gjennomført en sammenligningsanalyse der vi har tatt for oss de ulike anleggsmidlene i balansen, og begrenset oss ned til avskrivning og nedskrivning (varige driftsmiddel), pensjonsmidler (finansielle anleggsmiddel) og de generelle immaterielle eiendelene og forskning og utvikling (immaterielle anleggsmiddel). Som en avsluttende del på analysen har vi tatt for oss notene i et årsregnskap ført etter de internasjonale regnskapsstandardene, Aker Kværner, og ett årsregnskap ført etter de norske regnskapsstandardene, Sunnhordland Kraftlag. Konklusjonen på denne analysen ble at de internasjonale regnskapsstandardene er langt mer omfattende enn de norske, og i noen tilfeller ikke egnet for norske bedrifter

Dual Learning-Based Siamese Framework for Change Detection Using Bi-Temporal VHR Optical Remote Sensing Images

As a fundamental and profound task in remote sensing, change detection from very-high-resolution (VHR) images plays a vital role in a wide range of applications and attracts considerable attention. Current methods generally focus on the research of simultaneously modeling and discriminating the changed and unchanged features. In practice, for bi-temporal VHR optical remote sensing images, the temporal spectral variability tends to exist in all bands throughout the entire paired images, making it difficult to distinguish none-changes and changes with a single model. In this paper, motivated by this observation, we propose a novel hybrid end-to-end framework named dual learning-based Siamese framework (DLSF) for change detection. The framework comprises two parallel streams which are dual learning-based domain transfer and Siamese-based change decision. The former stream is aimed at reducing the domain differences of two paired images and retaining the intrinsic information by translating them into each other&#8217;s domain. While the latter stream is aimed at learning a decision strategy to decide the changes in two domains, respectively. By training our proposed framework with certain change map references, this method learns a cross-domain translation in order to suppress the differences of unchanged regions and highlight the differences of changed regions in two domains, respectively, then focus on the detection of changed regions. To the best of our knowledge, the idea of incorporating dual learning framework and Siamese network for change detection is novel. The experimental results on two datasets and the comparison with other state-of-the-art methods verify the efficiency and superiority of our proposed DLSF

Progressive Domain Adaptation for Change Detection Using Season-Varying Remote Sensing Images

The development of artificial intelligence technology has prompted an immense amount of researches on improving the performance of change detection approaches. Existing deep learning-driven methods generally regard changes as a specific type of land cover, and try to identify them relying on the powerful expression capabilities of neural networks. However, in practice, different types of land cover changes are generally influenced by environmental factors at different degrees. Furthermore, seasonal variation-induced spectral differences seriously interfere with those of real changes in different land cover types. All these problems pose great challenges for season-varying change detection because the real and seasonal variation-induced changes are technically difficult to separate by a single end-to-end model. In this paper, by embedding a convolutional long short-term memory (ConvLSTM) network into a conditional generative adversarial network (cGAN), we develop a novel method, named progressive domain adaptation (PDA), for change detection using season-varying remote sensing images. In our idea, two cascaded modules, progressive translation and group discrimination, are introduced to progressively translate pre-event images from their own domain to the post-event one, where their seasonal features are consistent and their intrinsic land cover distribution features are retained. By training this hybrid multi-model framework with certain reference change maps, the seasonal variation-induced changes between paired images are effectively suppressed, and meanwhile the natural and human activity-caused changes are greatly emphasized. Extensive experiments on two types of season-varying change detection datasets and a comparison with other state-of-the-art methods verify the effectiveness and competitiveness of our proposed PDA