QCD corrections to the R-parity violating processes ppˉ/pp→eμ+Xp\bar{p}/pp \to e\mu+X at hadron colliders

We present the QCD corrections to the processes $p\bar{p}/pp \to e\mu+X$ at the Tevatron and the CERN large hadron collider(LHC). The numerical results show that variation of K factor is in the range between $1.28(1.32)$ and $1.79(1.58)$ at the Tevatron(LHC). We find that the QCD correction part from the one-loop gluon-gluon fusion subprocess is remarkable at the LHC and should be taken into account.Comment: 7 pages, 6 Postscript figures, to be appeared in Phy. Rev.

WH/ZHW_H/Z_H production associated with a T-odd (anti)quark at the LHC in NLO QCD

In the framework of the littlest Higgs model with T parity, we study the $W_H/Z_H$ production in association with a T-odd (anti)quark of the first two generations at the CERN Large Hadron Collider up to the QCD next-to-leading order. The kinematic distributions of final decay products and the theoretical dependence of the cross section on the factorization/renormalization scale are discussed. We apply three schemes in considering the QCD NLO contributions and find that the QCD NLO corrections by adopting the (II) and (III) subtraction schemes can keep the convergence of the perturbative QCD description and reduce the scale uncertainty of the leading order cross section. By using these two subtraction schemes, the QCD NLO corrections to the $W_H(Z_H) q_-$ production process enhance the leading order cross section with a K-factor in the range of $1.00 \sim 1.43$.Comment: 31 pages, 12 figures, accepted by Phys. Rev.

Comparative mitogenomics of the Decapoda reveals evolutionary heterogeneity in architecture and composition

The emergence of cost-effective and rapid sequencing approaches has resulted in an exponential rise in the number of mitogenomes on public databases in recent years, providing greater opportunity for undertaking large-scale comparative genomic and systematic research. Nonetheless, current datasets predominately come from small and disconnected studies on a limited number of related species, introducing sampling biases and impeding research of broad taxonomic relevance. This study contributes 21 crustacean mitogenomes from several under-represented decapod infraorders including Polychelida and Stenopodidea, which are used in combination with 225 mitogenomes available on NCBI to investigate decapod mitogenome diversity and phylogeny. An overview of mitochondrial gene orders (MGOs) reveals a high level of genomic variability within the Decapoda, with a large number of MGOs deviating from the ancestral arthropod ground pattern and unevenly distributed among infraorders. Despite the substantial morphological and ecological variation among decapods, there was limited evidence for correlations between gene rearrangement events and species ecology or lineage specific nucleotide substitution rates. Within a phylogenetic context, predicted scenarios of rearrangements show some MGOs to be informative synapomorphies for some taxonomic groups providing strong independent support for phylogenetic relationships. Additional comparisons for a range of mitogenomic features including nucleotide composition, strand asymmetry, unassigned regions and codon usage indicate several clade-specific trends that are of evolutionary and ecological interest

Microbial succession and the functional potential during the fermentation of Chinese soy sauce brine

The quality of traditional Chinese soy sauce is determined by microbial communities and their inter-related metabolic roles in the fermentation tank. In this study, traditional Chinese soy sauce brine samples were obtained periodically to monitor the transitions of the microbial population and functional properties during the 6 months of fermentation process. Whole genome shotgun method revealed that the fermentation brine was dominated by the bacterial genus Weissella and later dominated by the fungal genus Candida. Metabolic reconstruction of the metagenome sequences demonstrated a characteristic profile of heterotrophic fermentation of proteins and carbohydrates. This was supported by the detection of ethanol with stable decrease of pH values. To the best of our knowledge, this is the first study that explores the temporal changes in microbial successions over a period of 6 months, through metagenome shotgun sequencing in traditional Chinese soy sauce fermentation and the biological processes therein

Master integrals for mixed QCD-QED corrections to charged-current Drell-Yan production of a massive charged lepton

The master integrals for the mixed QCD-QED two-loop virtual corrections to the charged-current Drell-Yan process $q\bar{q}^{\prime} \rightarrow \ell \nu$ are computed analytically by using the differential equation method. A suitable choice of master integrals makes it successful to cast the differential equation system into the canonical form. We keep the dependence on charged lepton mass in the building of differential equations and then expand the system against the ratio of small charged lepton mass to large $W$-boson mass. In such a way the final results will contain large logarithms of the form $\log(m_{\ell}^2/m_W^2)$. Finally, all the canonical master integrals are given as Taylor series around $d = 4$ spacetime dimensions up to order four, with coefficients expressed in terms of Goncharov polylogarithms up to weight four.Comment: 34 pages, 6 figure

The complete mitochondrial genome of the snakeskin gourami, Trichopodus pectoralis (Regan 1910) (Teleostei: Osphronemidae)

We sequenced and assembled three whole mitogenome sequences of the commercially important snakeskin gourami Trichopodus pectoralis isolated from Malaysia (introduced), Viet Nam (native) and Thailand (native). The mitogenome length range from 16,397 to 16,420 bp. The final partitioned nucleotide alignment consists of 14,002 bp and supports the monophyly of the genus Trichopodus (95% ultrafast bootstrap support) with T. trichopterus forming a sister group with the members of T. pectoralis

On-Device Training Under 256KB Memory

On-device training enables the model to adapt to new data collected from the sensors by fine-tuning a pre-trained model. Users can benefit from customized AI models without having to transfer the data to the cloud, protecting the privacy. However, the training memory consumption is prohibitive for IoT devices that have tiny memory resources. We propose an algorithm-system co-design framework to make on-device training possible with only 256KB of memory. On-device training faces two unique challenges: (1) the quantized graphs of neural networks are hard to optimize due to low bit-precision and the lack of normalization; (2) the limited hardware resource does not allow full back-propagation. To cope with the optimization difficulty, we propose Quantization-Aware Scaling to calibrate the gradient scales and stabilize 8-bit quantized training. To reduce the memory footprint, we propose Sparse Update to skip the gradient computation of less important layers and sub-tensors. The algorithm innovation is implemented by a lightweight training system, Tiny Training Engine, which prunes the backward computation graph to support sparse updates and offload the runtime auto-differentiation to compile time. Our framework is the first solution to enable tiny on-device training of convolutional neural networks under 256KB SRAM and 1MB Flash without auxiliary memory, using less than 1/1000 of the memory of PyTorch and TensorFlow while matching the accuracy on tinyML application VWW. Our study enables IoT devices not only to perform inference but also to continuously adapt to new data for on-device lifelong learning. A video demo can be found here: https://youtu.be/0pUFZYdoMY8.Comment: NeurIPS 202