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Using a data sample of e+e− collision data corresponding to an integrated luminosity of 2.93 fb−1 collected with the BESIII detector at a center-of-mass energy of s=3.773GeV, we search for the singly Cabibbo-suppressed decays D0→π0π0π0, π0π0η, π0ηη and ηηη using the double tag method. The absolute branching fractions are measured to be B(D0→π0π0π0)=(2.0±0.4±0.3)×10−4, B(D0→π0π0η)=(3.8±1.1±0.7)×10−4 and B(D0→π0ηη)=(7.3±1.6±1.5)×10−4 with the statistical significances of 4.8σ, 3.8σ and 5.5σ, respectively, where the first uncertainties are statistical and the second ones systematic. No significant signal of D0→ηηη is found, and the upper limit on its decay branching fraction is set to be B(D0→ηηη)<1.3×10−4 at the 90% confidence level.
In this paper we will explore the similarities and differences between two feature logic-based approaches to the composition of semantic representations. The first approach is formulated for Lexicalized Tree Adjoining Grammar (LTAG, Joshi and Schabes 1997), the second is Lexical Ressource Semantics (LRS, Richter and Sailer 2004) and was first defined in Head-driven Phrase Structure Grammar. The two frameworks have several common characteristics that make them easy to compare: 1 They use languages of two sorted type theory for semantic representations. 2. They allow underspecification. LTAG uses scope constraints while LRS provides component-of contraints. 3 They use feature logics for computing semantic representations. 4. they are designed for computational applications. By comparing the two frameworks we will also point outsome characteristics and advantages of feature logic-based semantic computation in genereal.
This paper compares two approaches to computational semantics, namely semantic unification in Lexicalized Tree Adjoining Grammars (LTAG) and Lexical Resource Semantics (LRS) in HPSG. There are striking similarities between the frameworks that make them comparable in many respects. We will exemplify the differences and similarities by looking at several phenomena. We will show, first of all, that many intuitions about the mechanisms of semantic computations can be implemented in similar ways in both frameworks. Secondly, we will identify some aspects in which the frameworks intrinsically differ due to more general differences between the approaches to formal grammar adopted by LTAG and HPSG.
The frequency of intensional and non-first-order definable operators in natural languages constitutes a challenge for automated reasoning with the kind of logical translations that are deemed adequate by formal semanticists. Whereas linguists employ expressive higher-order logics in their theories of meaning, the most successful logical reasoning strategies with natural language to date rely on sophisticated first-order theorem provers and model builders. In order to bridge the fundamental mathematical gap between linguistic theory and computational practice, we present a general translation from a higher-order logic frequently employed in the linguistics literature, two-sorted Type Theory, to first-order logic under Henkin semantics. We investigate alternative formulations of the translation, discuss their properties, and evaluate the availability of linguistically relevant inferences with standard theorem provers in a test suite of inference problems stated in English. The results of the experiment indicate that translation from higher-order logic to first-order logic under Henkin semantics is a promising strategy for automated reasoning with natural languages.
The identification of inhibitors of eukaryotic protein biosynthesis, which are targeting single translation factors, is highly demanded. Here we report on a small molecule inhibitor, gephyronic acid, isolated from the myxobacterium Archangium gephyra that inhibits growth of transformed mammalian cell lines in the nM range. In direct comparison, primary human fibroblasts were shown to be less sensitive to toxic effects of gephyronic acid than cancer-derived cells. Gephyronic acid is targeting the protein translation system. Experiments with IRES dual luciferase reporter assays identified it as an inhibitor of the translation initiation. DARTs approaches, co-localization studies and pull-down assays indicate that the binding partner could be the eukaryotic initiation factor 2 subunit alpha (eIF2α). Gephyronic acid seems to have a different mode of action than the structurally related polyketides tedanolide, myriaporone, and pederin and is a valuable tool for investigating the eukaryotic translation system. Because cancer derived cells were found to be especially sensitive, gephyronic acid could potentially find use as a drug candidate.
Ice-nucleating particle concentrations of the past: insights from a 600-year-old Greenland ice core
(2020)
Ice-nucleating particles (INPs) affect the microphysics in cloud and precipitation processes. Hence, they modulate the radiative properties of clouds. However, atmospheric INP concentrations of the past are basically unknown. Here, we present INP measurements from an ice core in Greenland, which dates back to the year 1370. In total 135 samples were analyzed with the FRIDGE droplet freezing assay in the temperature range from −14 to −35 ∘C. The sampling frequency was set to 1 in 10 years from 1370 to 1960. From 1960 to 1990 the frequency was increased to one sample per year. Additionally, a few special events were probed, including volcanic episodes. The typical time coverage of a sample was on the order of a few months. Historical atmospheric INP concentrations were estimated with a conversion factor, which depends on the snow accumulation rate of the ice core, particle dry deposition velocity, and wet scavenging ratio. Typical atmospheric INP concentrations were on the order of 0.1 L−1 at −25 ∘C. The INP variability was found to be about 1–2 orders of magnitude. Yet, the short-term variability from samples over a seasonal cycle was considerably lower. INP concentrations were significantly correlated to some chemical tracers derived from continuous-flow analysis (CFA) and ion chromatography (IC) over a broad range of nucleation temperatures. The highest correlation coefficients were found for the particle concentration (spherical diameter dp > 1.2 µm). The correlation is higher for a time period of seasonal samples, where INP concentrations follow a clear annual pattern, highlighting the importance of the annual dust input in Greenland from East Asian deserts during spring. Scanning electron microscopy (SEM) analysis of selected samples found mineral dust to be the dominant particle fraction, verifying their significance as INPs. Overall, the concentrations compare reasonably well to present-day INP concentrations, albeit they are on the lower side. However, we found that the INP concentration at medium supercooled temperatures differed before and after 1960. Average INP concentrations at −23, −24, −25, −26, and −28 ∘C were significantly higher (and more variable) in the modern-day period, which could indicate a potential anthropogenic impact, e.g., from land-use change.
Ice nucleating particle concentrations of the past: insights from a
600 year old Greenland ice core
(2020)
Ice nucleating particles (INPs) affect the microphysics in cloud and precipitation processes. Hence, they modulate the radiative properties of clouds. However, atmospheric INP concentrations of the past are basically unknown. Here, we present INP measurements from an ice core in Greenland, which dates back to the year 1370. In total 135 samples were analyzed with the FRIDGE droplet freezing assay in the temperature range from −14 ◦C to −35 ◦C. The sampling frequency was set to 1 in 10 years from 1370 to 1960. From 1960 to 1990 the frequency was increased to 1 sample per year. Additionally, a number of special events were probed, including volcanic episodes. The typical time coverage of a sample was on the order of a few months. Historical atmospheric INP concentrations were estimated with a conversion factor, which depends on the snow accumulation rate of the ice core, particle dry deposition velocity and the wet scavenging ratio. Typical atmospheric INP concentrations were on the order of 0.1 L -1 at −25 ◦C. The INP variability was found to be about 1 – 2 orders of magnitude. Yet, the short-term variability from samples over a seasonal cycle was considerably lower. INP concentrations were significantly correlated to chemical tracers derived from continuous flow analysis (CFA) and ion chromatography (IC) over a broad range of nucleation temperatures. The highest correlation coefficients were found for the particle concentration (dp > 1.2 µm). The correlation is higher for the seasonal samples, where INP concentrations follow a clear annual pattern, highlighting the importance of the annual dust input in Greenland from East Asian deserts during spring. Scanning electron microscopy (SEM) of single particles retrieved from selected samples found particles of soil origin to be the dominant fraction, verifying the significance of mineral dust particles as INPs. Overall, the concentrations compare reasonably well to present day INP concentrations, albeit they are on the lower side. However, we found that the INP concentration at medium supercooled temperatures differed before and after 1960. Average INP concentrations at −23 ◦C, −24 ◦C, −25 ◦C, −26 ◦C and −28 ◦C were significantly higher (and more variable) in the modern day period, which could indicate a potential anthropogenic impact or some post-coring contamination of the topmost, very porous firn.
The project focuses on the efficiency of combined technologies to reduce the release of micropollutants and bacteria into surface waters via sewage treatment plants of different size and via stormwater overflow basins of different types. As a model river in a highly populated catchment area, the river Schussen and, as a control, the river Argen, two tributaries of Lake Constance, Southern Germany, are under investigation in this project. The efficiency of the different cleaning technologies is monitored by a wide range of exposure and effect analyses including chemical and microbiological techniques as well as effect studies ranging from molecules to communities.
As a surrogate of live cells, proteo-lipobeads are presented, encapsulating functional membrane proteins in a strict orientation into a lipid bilayer. Assays can be performed just as on live cells, for example using fluorescence measurements. As a proof of concept, we have demonstrated proton transport through cytochrome c oxidase.
CXCL12-CXCR4 signaling controls multiple physiological processes and its dysregulation is associated with cancers and inflammatory diseases. To discover as-yet-unknown endogenous ligands of CXCR4, we screened a blood-derived peptide library for inhibitors of CXCR4-tropic HIV-1 strains. This approach identified a 16 amino acid fragment of serum albumin as an effective and highly specific CXCR4 antagonist. The endogenous peptide, termed EPI-X4, is evolutionarily conserved and generated from the highly abundant albumin precursor by pH-regulated proteases. EPI-X4 forms an unusual lasso-like structure and antagonizes CXCL12-induced tumor cell migration, mobilizes stem cells, and suppresses inflammatory responses in mice. Furthermore, the peptide is abundant in the urine of patients with inflammatory kidney diseases and may serve as a biomarker. Our results identify EPI-X4 as a key regulator of CXCR4 signaling and introduce proteolysis of an abundant precursor protein as an alternative concept for chemokine receptor regulation.