Dimethyl 3,5-diethyl-1H-pyrrole-2,4-dicarboxyl­ate

The title pyrrole derivative, C12H17NO4, consists of a pyrrole ring with two diagonally attached meth­oxy­carbonyl groups and two diagonally attached ethyl groups. The two carbonyl groups are approximately in the same plane as the pyrrole ring, making dihedral angles of 3.50 (19) and 6.70 (19)°. In the crystal, adjacent mol­ecules are assembled into dimers in a head-to-head mode by pairs of inter­molecular N—H⋯O hydrogen bonds

Analysis of the oxidized low density lipoprotein receptor 1 gene as a potential marker for carcass quality traits in Qinchuan cattle

Objective The oxidized low density lipoprotein receptor 1 (OLR1) gene plays an important role in the degradation of oxidized low-density lipoprotein and adipocyte proliferation in mammals. For this reason, we aimed at investigating the association of OLR1 gene polymorphisms with carcass quality traits in Chinese Qinchuan cattle. Methods The single nucleotide polymorphism (SNP) was identified in the 3′ untranslated region of bovine OLR1 gene by DNA sequencing. In addition, the haplotype frequency and linkage disequilibrium estimates of three SNPs were evaluated in 520 individuals. Results Results indicated that the studied three SNPs were within the range of moderate genetic diversity (0.25< polymorphism information content<0.5). Haplotype analysis of three SNPs showed that ten different haplotypes were identified, but only five haplotypes were listed as those with a frequency of <0.05 were excluded. The Hap3 (-G1T2C3-) had the highest haplotype frequency (42.10%). Linkage disequilibrium analysis showed that the three SNPs had a low linkage (r2<0.001). The T10588C and C10647T were significantly associated with backfat thickness and intramuscular fat content in Qinchuan cattle. Conclusion Based on our results, we believe that the OLR1 gene could be a strong candidate gene for influencing carcass quality traits in Qinchuan cattle

Novel insights into bacterial dimethylsulfoniopropionate catabolism in the East China Sea

The compatible solute Dimethylsulfoniopropionate (DMSP), made by many marine organisms, is one of Earth’s most abundant organosulfur molecules. Many marine bacteria import DMSP and can degrade it as a source of carbon and/or sulfur via DMSP cleavage or DMSP demethylation pathways, which can generate the climate active gases dimethyl sulfide (DMS) or methanthiol (MeSH), respectively. Here we used culture-dependent and -independent methods to study bacteria catabolising DMSP in East China Sea (ECS). Of bacterial isolates, 42.11% showed DMSP-dependent DMS (Ddd+) activity, and 12.28% produced detectable levels of MeSH. Interestingly, although most Ddd+ isolates were Alphaproteobacteria (mainly Roseobacters), many gram-positive Actinobacteria were also shown to cleave DMSP producing DMS. The mechanism by which these Actinobacteria cleave DMSP is unknown, since no known functional ddd genes have been identified in genome sequences of Ddd+ Microbacterium and Agrococcus isolates or in any other sequenced Actinobacteria genomes. Gene probes to the DMSP demethylation gene dmdA and the DMSP lyase gene dddP demonstrated that these DMSP-degrading genes are abundant and widely distributed in ECS seawaters. dmdA was present in relatively high proportions in both surface (19.53% ± 6.70%) and bottom seawater bacteria (16.00% ± 8.73%). In contrast, dddP abundance positively correlated with chlorophyll a, and gradually decreased with the distance from land, which implies that the bacterial DMSP lyase gene dddP might be from bacterial groups that closely associate with phytoplankton. Bacterial community analysis showed positive correlations between Rhodobacteraceae abundance and concentrations of DMS and DMSP, further confirming the link between this abundant bacterial class and the environmental DMSP cycling

Time machine : generative real-time model for failure (and lead time) prediction in HPC systems

High Performance Computing (HPC) systems generate a large amount of unstructured/alphanumeric log messages that capture the health state of their components. Due to their design complexity, HPC systems often undergo failures that halt applications (e.g., weather prediction, aerodynamics simulation) execution. However, existing failure prediction methods, which typically seek to extract some information theoretic features, fail to scale both in terms of accuracy and prediction speed, limiting their adoption in real-time production systems. In this paper, differently from existing work and inspired by current transformer-based neural networks which have revolutionized the sequential learning in the NLP tasks, we propose a novel scalable log-based, self-supervised model (i.e., no need for manual labels), called Time Machine1 , that predicts (i) forthcoming log events (ii) the upcoming failure and its location and (iii) the expected lead time to failure. Time Machine is designed by combining two stacks of transformer-decoders, each employing the selfattention mechanism. The first stack addresses the failure location by predicting the sequence of log events and then identifying if a failure event is part of that sequence. The lead time to predicted failure is addressed by the second stack. We evaluate Time machine on four real-world HPC log datasets and compare it against three state-of-the-art failure prediction approaches. Results show that Time Machine significantly outperforms the related works on Bleu, Rouge, MCC, and F1-score in predicting forthcoming events, failure location, failure lead-time, with higher prediction speed

Association between Single Nucleotide Polymorphisms in SIRT1 and SIRT2 Loci and Growth in Tibetan Sheep

Silent information regulator 1 and 2 (SIRT1, 2) were NAD+-dependent histone or non-histone deacetylase, which emerged as key metabolic sensors in several tissues of mammals. In the present study, the search for polymorphisms within the ovine SIRT1 and SIRT2 loci as well as association analyses between SNPs and growth-related traits were performed in Tibetan sheep. To determine the expression pattern of SIRT1 and SIRT2 genes in Tibetan sheep, the quantitative real-time polymerase chain reaction (qPCR) analysis revealed that those two genes were widely expressed in diverse tissues. Expression of SIRT1 was less in abomasum of lamb, whereas it was greater in duodenum within adult stage. In the case of SIRT2, the greatest expression was observed in reticulum (lamb) and in muscle (adult), whereas the least expression was in liver for lamb and in kidney for adult animals. The association analysis demonstrated that g.3148 C \u3e T polymorphism of SIRT1 affected heart girth (p = 0.002). The g.8074 T \u3e A SNP of SIRT2 had a significant correlation with body weight (p = 0.011) and body length (p = 0.008). These findings suggested that the SIRT1 and SIRT2 polymorphism was involved in growth-related traits in Tibetan sheep, which may be considered to be genetic markers for improving the growth traits of Tibetan sheep

An Assessment Method for Debris Flow Dam Formation in Taiwan

Debris flows in tributaries rush into and block the main branches of rivers and often result in serious hazards. Dam failures cause large floods in the downstream area and can lead to fatalities and property damage. This study proposes an assessment method to evaluate the formation of a debris flow dam, which includes two conditions: (1) the sediment transported by the debris flow must reach across the river; and (2) the thickness of the deposit by the debris flow must be higher than the in situ water depth. This methodology was used to study the case of a debris flow dam caused by debris flow across the Er River in Taiwan, which blocked the Chishan River and led to the formation of the Namasha debris flow dam. This methodology can also be applied to identify the formation of debris flow dams.El flujo de detritos que cae en los tributarios de los ríos puede bloquear los ramales principales y eventualmente convertirse en un riesgo. El rompimiento de uno de estos represamientos de agua puede causar inundaciones en las zonas de la corriente, además de víctimas y daños a propiedades. Este estudio propone un método para evaluar la formación de represamientos de agua por flujo de detritos bajo dos condiciones: (1) los sedimentos transportados por el flujo de detritos deben alcanzar el lecho del río; (2) el grosor de los depósitos por el flujo de detritos debe ser mayor que la profundidad de agua in situ. Esta metodología se utilizó para estudiar el caso de represamiento por el flujo de detritos en el río Er de Taiwán, el cual bloqueó el río Chishan y que condujo a la formación de la presa Namasha. Esta metodología también puede aplicarse para identificar la formación de represamientos por flujo de detritos

EMMNet: Sensor Networking for Electricity Meter Monitoring

Smart sensors are emerging as a promising technology for a large number of application domains. This paper presents a collection of requirements and guidelines that serve as a basis for a general smart sensor architecture to monitor electricity meters. It also presents an electricity meter monitoring network, named EMMNet, comprised of data collectors, data concentrators, hand-held devices, a centralized server, and clients. EMMNet provides long-distance communication capabilities, which make it suitable suitable for complex urban environments. In addition, the operational cost of EMMNet is low, compared with other existing remote meter monitoring systems based on GPRS. A new dynamic tree protocol based on the application requirements which can significantly improve the reliability of the network is also proposed. We are currently conducting tests on five networks and investigating network problems for further improvements. Evaluation results indicate that EMMNet enhances the efficiency and accuracy in the reading, recording, and calibration of electricity meters