Boosting Distributed Machine Learning Training Through Loss-tolerant Transmission Protocol

Distributed Machine Learning (DML) systems are utilized to enhance the speed of model training in data centers (DCs) and edge nodes. The Parameter Server (PS) communication architecture is commonly employed, but it faces severe long-tail latency caused by many-to-one "incast" traffic patterns, negatively impacting training throughput. To address this challenge, we design the \textbf{L}oss-tolerant \textbf{T}ransmission \textbf{P}rotocol (LTP), which permits partial loss of gradients during synchronization to avoid unneeded retransmission and contributes to faster synchronization per iteration. LTP implements loss-tolerant transmission through \textit{out-of-order transmission} and \textit{out-of-order Acknowledges (ACKs)}. LTP employs \textit{Early Close} to adjust the loss-tolerant threshold based on network conditions and \textit{Bubble Filling} for data correction to maintain training accuracy. LTP is implemented by C++ and integrated into PyTorch. Evaluations on a testbed of 8 worker nodes and one PS node demonstrate that LTP can significantly improve DML training task throughput by up to 30x compared to traditional TCP congestion controls, with no sacrifice to final accuracy.Comment: This paper will be published on IWQoS 2023. Preview version onl

Screening of traditional Chinese medicines with therapeutic potential on chronic obstructive pulmonary disease through inhibiting oxidative stress and inflammatory response

NADP(H): quinone oxidoreductase (QR) inducing effects of 38 bioactive TCM extracts in hepa 1c1c7 cells. The QR inducing effect was determined after 24h treatment of the hepa 1c1c7 cells in the presence or absence of tested TCMs. The data of the untreated control group was normalized as 1, and then the QR inducing activity of tested extracts was represented by the maximum folds of QR inducing activity (MQI) compared with the untreated control group. Sulforaphane (SF, 2.0 μM) was used as a positive control. The data are reported the means ± SD from three independent experiments. Figure S2. Inhibitory effects on NO production of 55 bioactive TCM extracts in RAW 264.7 cells. The NO concentration in the RAW 264.7 cell culture media was determined through the Griess reaction 24 h after treated in the presence or absence of tested TCMs and lipopolysaccharides (LPS, 1.0 μg/mL). Didox (100 μM) was adopted as a positive control. The data are reported the means ± SD from three independent experiments. The maximum inhibition rates (MIRs) of NO production under the untoxic tested concentration were calculated by comparing the decreased NO concentration in TCM-treated group with that in LPS-stimulated group. Table S1. TCM extracts with QR inducing activity and/or NO inhibitory effect. (DOCX 4312 kb

The foundations of statistical mechanics from entanglement: Individual states vs. averages

We consider an alternative approach to the foundations of statistical mechanics, in which subjective randomness, ensemble-averaging or time-averaging are not required. Instead, the universe (i.e. the system together with a sufficiently large environment) is in a quantum pure state subject to a global constraint, and thermalisation results from entanglement between system and environment. We formulate and prove a "General Canonical Principle", which states that the system will be thermalised for almost all pure states of the universe, and provide rigorous quantitative bounds using Levy's Lemma.Comment: 12 pages, v3 title changed, v2 minor change

Gravitational collapse with tachyon field and barotropic fluid

A particular class of space-time, with a tachyon field, \phi, and a barotropic fluid constituting the matter content, is considered herein as a model for gravitational collapse. For simplicity, the tachyon potential is assumed to be of inverse square form i.e., V(\phi) \sim \phi^{-2}. Our purpose, by making use of the specific kinematical features of the tachyon, which are rather different from a standard scalar field, is to establish the several types of asymptotic behavior that our matter content induces. Employing a dynamical system analysis, complemented by a thorough numerical study, we find classical solutions corresponding to a naked singularity or a black hole formation. In particular, there is a subset where the fluid and tachyon participate in an interesting tracking behaviour, depending sensitively on the initial conditions for the energy densities of the tachyon field and barotropic fluid. Two other classes of solutions are present, corresponding respectively, to either a tachyon or a barotropic fluid regime. Which of these emerges as dominant, will depend on the choice of the barotropic parameter, \gamma. Furthermore, these collapsing scenarios both have as final state the formation of a black hole.Comment: 18 pages, 7 figures. v3: minor changes. Final version to appear in GR

Predicting the catalytic sites of isopenicillin N synthase (IPNS) related non-haem iron-dependent oxygenases and oxidases (NHIDOX) through a structural superimposition and molecular docking approach

Isopenicillin N synthase (IPNS) related Non-haem iron-dependent oxygenases and oxidases (NHIDOX) demonstrated a striking structural conservativeness, even with low protein sequence homology. It is evident that these enzymes have an architecturally similar catalytic centre with active ligands lining the reactive pocket. Deacetoxycephalosporin C synthase (DAOCS), isopenicillin N synthase (IPNS), deacetylcephalosporin C synthase (DACS), clavaminate synthase 1 and 2 (CAS1 and 2) are important bacterial enzymes that catalyze the formation of β-lactam antibiotics belonging to this enzyme family. Most plant enzyme members within this subfamily namely flavonol synthase (FLS), leucoanthocyanidin dioxygenase (LDOX), anthocyanidin synthase (ANS), 1-aminocyclopropane-1-carboxylic acid oxidase (ACCO), gibberellin 20-oxidase (G20O), desacetoxyvindoline-4-hydroxylase (D4H), flavanone 3β-hydroxylase (F3H), and hyoscyamine 6β-hydroxylase (H6H) are involved in catalyzing the biosyntheses of plant secondary metabolites. With the advancement of protein structural analysis software, it is possible to predict the catalytic sites of protein that shared a structural resemblance. By exploiting the superimposition model of DAOCS-IPNS, DAOCS-IPNS-CAS, G20O-LDOX, FLS-LDOX, ACCO-LDOX, D4H-LDOX, F3H-LDOX and H6H-LDOX model; a computational protocol for predicting the catalytic sites of proteins is now made available. This study shows that without the crystallized or nuclear magnetic resonance (NMR) structures of most NHIDOX enzyme, the plausible catalytic sites of protein can be forecasted using this structural bioinformatics approach.Keywords: Enzyme, catalytic sites, isopenicillin N synthase, ligand

Chloroplast Genomes in Populus (Salicaceae): Comparisons From an Intensively Sampled Genus Reveal Dynamic Patterns of Evolution

The chloroplast is one of two organelles containing a separate genome that codes for essential and distinct cellular functions such as photosynthesis. Given the importance of chloroplasts in plant metabolism, the genomic architecture and gene content have been strongly conserved through long periods of time and as such are useful molecular tools for evolutionary inferences. At present, complete chloroplast genomes from over 4000 species have been deposited into publicly accessible databases. Despite the large number of complete chloroplast genomes, comprehensive analyses regarding genome architecture and gene content have not been conducted for many lineages with complete species sampling. In this study, we employed the genus Populus to assess how more comprehensively sampled chloroplast genome analyses can be used in understanding chloroplast evolution in a broadly studied lineage of angiosperms. We conducted comparative analyses across Populus in order to elucidate variation in key genome features such as genome size, gene number, gene content, repeat type and number, SSR (Simple Sequence Repeat) abundance, and boundary positioning between the four main units of the genome. We found that some genome annotations were variable across the genus owing in part from errors in assembly or data checking and from this provided corrected annotations. We also employed complete chloroplast genomes for phylogenetic analyses including the dating of divergence times throughout the genus. Lastly, we utilized re-sequencing data to describe the variations of pan-chloroplast genomes at the population level for P. euphratica. The analyses used in this paper provide a blueprint for the types of analyses that can be conducted with publicly available chloroplast genomes as well as methods for building upon existing datasets to improve evolutionary inference

Electro-Optical Detection of ZnO-Based Unbalanced Fabry-Perot Resonators

Zinc oxide films prepared by magnetron sputtering are introduced to the electro-optical detection to improve the voltage sensitivity. With the help of large piezoelectric effect, ZnO films make up for the deficiency of the low electro-optical coefficient. In this paper, we illustrated the mechanism of piezo-induced enhancements, and measured the electric signals on the line of coplanar waveguides. This method breaks through the limit of material species for optoelectronically responsive sensing, and shows promising applications in optical detection.

Factorization Properties of Soft Graviton Amplitudes

We apply recently developed path integral resummation methods to perturbative quantum gravity. In particular, we provide supporting evidence that eikonal graviton amplitudes factorize into hard and soft parts, and confirm a recent hypothesis that soft gravitons are modelled by vacuum expectation values of products of certain Wilson line operators, which differ for massless and massive particles. We also investigate terms which break this factorization, and find that they are subleading with respect to the eikonal amplitude. The results may help in understanding the connections between gravity and gauge theories in more detail, as well as in studying gravitational radiation beyond the eikonal approximation.Comment: 35 pages, 5 figure

Type 1 diabetes, COVID-19 vaccines and short-term safety: Subgroup analysis from the global COVAD study

AIMS/INTRODUCTION Coronavirus disease 2019 (COVID-19) vaccinations have been proven to be generally safe in healthy populations. However, the data on vaccine safety in patients with type 1 diabetes are scarce. This study aimed to evaluate the frequency and severity of short-term (<7-day) adverse vaccination events (AEs) and their risk factors among type 1 diabetes patients. MATERIALS AND METHODS This study analyzed data from the COVID-19 vaccination in Autoimmune Diseases (COVAD) survey database (May to December 2021; 110 collaborators, 94 countries), comparing <7-day COVID-19 vaccine AE among type 1 diabetes patients and healthy controls (HCs). Descriptive statistics; propensity score matching (1:4) using the variables age, sex and ethnicity; and multivariate analyses were carried out. RESULTS This study analyzed 5,480 completed survey responses. Of all responses, 5,408 were HCs, 72 were type 1 diabetes patients (43 females, 48.0% white European ancestry) and Pfizer was the most administered vaccine (39%). A total of 4,052 (73.9%) respondents had received two vaccine doses. Patients with type 1 diabetes had a comparable risk of injection site pain, minor and major vaccine AEs, as well as associated hospitalizations to HCs. However, type 1 diabetes patients had a higher risk of severe rashes (3% vs 0.4%, OR 8.0, 95% confidence interval 1.7-36), P = 0.007), although reassuringly, these were rare (n = 2 among type 1 diabetes patients). CONCLUSIONS COVID-19 vaccination was safe and well tolerated in patients with type 1 diabetes with similar AE profiles compared with HCs, although severe rashes were more common in type 1 diabetes patients