CORE: Augmenting Regenerating-Coding-Based Recovery for Single and Concurrent Failures in Distributed Storage Systems

Data availability is critical in distributed storage systems, especially when node failures are prevalent in real life. A key requirement is to minimize the amount of data transferred among nodes when recovering the lost or unavailable data of failed nodes. This paper explores recovery solutions based on regenerating codes, which are shown to provide fault-tolerant storage and minimum recovery bandwidth. Existing optimal regenerating codes are designed for single node failures. We build a system called CORE, which augments existing optimal regenerating codes to support a general number of failures including single and concurrent failures. We theoretically show that CORE achieves the minimum possible recovery bandwidth for most cases. We implement CORE and evaluate our prototype atop a Hadoop HDFS cluster testbed with up to 20 storage nodes. We demonstrate that our CORE prototype conforms to our theoretical findings and achieves recovery bandwidth saving when compared to the conventional recovery approach based on erasure codes.Comment: 25 page

GrowCLIP: Data-aware Automatic Model Growing for Large-scale Contrastive Language-Image Pre-training

Cross-modal pre-training has shown impressive performance on a wide range of downstream tasks, benefiting from massive image-text pairs collected from the Internet. In practice, online data are growing constantly, highlighting the importance of the ability of pre-trained model to learn from data that is continuously growing. Existing works on cross-modal pre-training mainly focus on training a network with fixed architecture. However, it is impractical to limit the model capacity when considering the continuously growing nature of pre-training data in real-world applications. On the other hand, it is important to utilize the knowledge in the current model to obtain efficient training and better performance. To address the above issues, in this paper, we propose GrowCLIP, a data-driven automatic model growing algorithm for contrastive language-image pre-training with continuous image-text pairs as input. Specially, we adopt a dynamic growth space and seek out the optimal architecture at each growth step to adapt to online learning scenarios. And the shared encoder is proposed in our growth space to enhance the degree of cross-modal fusion. Besides, we explore the effect of growth in different dimensions, which could provide future references for the design of cross-modal model architecture. Finally, we employ parameter inheriting with momentum (PIM) to maintain the previous knowledge and address the issue of the local minimum dilemma. Compared with the existing methods, GrowCLIP improves 2.3% average top-1 accuracy on zero-shot image classification of 9 downstream tasks. As for zero-shot image retrieval, GrowCLIP can improve 1.2% for top-1 image-to-text recall on Flickr30K dataset.Comment: Accepted by ICCV202

The impact of family function on post-traumatic reactions of Chinese adolescents infected with COVID-19: a latent profile study

BackgroundSince the end of 2019, Corona Virus Disease 2019, also known as COVID-19, has broken out in various countries. However, the change of China's COVID-19 prevention and control policy and the sharp increase in the number of infected people are making the teenagers have post-traumatic reactions. Negative post-traumatic reactions include: post-traumatic stress disorder (PTSD), depression, anxiety. Positive post-traumatic reaction mainly refers to post-traumatic growth (PTG). The purpose of this study is to explore the post-traumatic reaction, which refers to PTSD, depression, anxiety and the co-occurrence pattern of growth after trauma and to further explore the influence of family function on different categories of Post-traumatic Reactions.MethodsLatent profile analysis (LPA) was used to explore the co-occurrence of PTSD, depression, anxiety, and PTG. Multiple logistics regression was used to analyze the influence of family function on different categories of post-traumatic response.ResultsThere were three categories of post-traumatic reactions in adolescents infected with COVID-19 adolescents infected with COVID-19, namely: growth class, struggling class, and pain class. Multivariate Logistic regression showed that the growth class and struggling class were affected by problem solving and behavior control in family function, while the growth class and pain class were affected by problem solving, roles, behavior control, and general functioning. Multiple logistic regression showed that the growth class and struggling class were affected by problem solving and roles.ConclusionsThe findings of this study provide evidence for the identification of high-risk individuals and the provision of effective interventions in clinical practice, as well as the influence of family functioning on the different categories of PTSD among adolescents infected with COVID-19

A transcription factor of the NAC family regulates nitrate-induced legume nodule senescence

17 Pags.- 7 Figs. © 2023 The AuthorsLegumes establish symbioses with rhizobia by forming nitrogen-fixing nodules. Nitrate is amajor environmental factor that affects symbiotic functioning. However, the molecularmechanism of nitrate-induced nodule senescence is poorly understood. Comparative transcriptomic analysis reveals an NAC-type transcription factor inLotus japo-nicus, LjNAC094, that acts as a positive regulator in nitrate-induced nodule senescence.Stable overexpression and mutant lines ofNAC094were constructed and used for phenotypiccharacterization. DNA-affinity purification sequencing was performed to identify NAC094targeting genes and results were confirmed by electrophoretic mobility shift and transactiva-tion assays. Overexpression ofNAC094induces premature nodule senescence. Knocking outNAC094partially relieves nitrate-induced degradation of leghemoglobins and abolishes nodule expres-sion of senescence-associated genes (SAGs) that contain a conserved binding motif forNAC094. Nitrate-triggered metabolic changes in wild-type nodules are largely affected innac094mutant nodules. Induction ofNAC094and its targetingSAGswas almost blocked inthe nitrate-insensitivenlp1,nlp4, andnlp1 nlp4mutants. We conclude that NAC094 functions downstream of NLP1 and NLP4 by regulating nitrate-induced expression ofSAGs. Our study fills in a key gap between nitrate and the execution ofnodule senescence, and provides a potential strategy to improve nitrogen fixation and stresstolerance of legumes.This work was supported by the National Natural Science Foundation of China (32000192, 31870220), the Foundation of Hubei Hongshan Laboratory (2022hszd014), Fundamental Research Funds for the Central Universities (2662020SKPY007), and MCIN/AEI/10.13039/501100011033 (grant PID2020-113985GB-I00). We also thank the BaiChuan fellowship of College of Life Science and Technology, Huazhong Agricultural University, for funding support.Peer reviewe

Single cell-type transcriptome profiling reveals genes that promote nitrogen fixation in the infected and uninfected cells of legume nodules

2 Pags.- 1 Fig. © 2022 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License, which permits use,distribution and reproduction in any medium, provided the original work is properly cited.Excessive application of nitrogen fertilizers has inevitably resultedin environmental problems. The symbiotic nitrogen fixation (SNF) that occurs in the root nodules of leguminous plants provides asustainable source of reduced nitrogen in agricultural ecosystems. More than 200 genes have been reported to regulate SNF, including rhizobial infection, nodule organogenesis and senescence (Royet al., 2020). Mature nodules consist mainly of twocell types: infected cells (IC) that contain nitrogen-fixing bac-teroids and uninfected cells (UC) that mediate active metabolismand nutrient transport. Although it is well known that SNFrequires functional specialization, the specific genes responsiblefor transcriptional regulation and carbon/nitrogen metabolismand transport in IC and UC remain largely unexplored.Single-cell transcriptomics has emerged as a powerful tech-nique for investigating spatiotemporal patterns of gene expression.This work was supported by the National Natural Science Foundation of China (31870220, 32000192), the China Post-doctoral Science Foundation (2020M680103), Fundamental Research Funds for the Central Universities 2662020SKPY007 and MCIN/AEI/10.13039/501100011033 (grant PID2020-113985GB-I00)Peer reviewe

Effectiveness of intravenous r-tPA versus UK for acute ischaemic stroke: a nationwide prospective Chinese registry study

BACKGROUND Intravenous recombinant tissue plasminogen activator (r-tPA) and urokinase (UK) are both recommended for the treatment of acute ischaemic stroke (AIS) in China, but with few comparative outcome data being available. We aimed to compare the outcomes of these two thrombolytic agents for the treatment of patients within 4.5 hours of onset of AIS in routine clinical practice in China. METHODS A pre-planned, prospective, nationwide, multicentre, real-world registry of consecutive patients with AIS (age ≥18 years) who received r-tPA or UK within 4.5 hours of symptom onset according to local decision-making and guideline recommendations during 2017-2019. The primary effectiveness outcome was the proportion of patients with an excellent functional outcome (defined by modified Rankin scale scores 0 to 1) at 90 days. The key safety endpoint was symptomatic intracranial haemorrhage according to standard definitions. Multivariable logistic regression was used for comparative analysis, with adjustment according to propensity scores to ensure balance in baseline characteristics. RESULTS Overall, 4130 patients with AIS were registered but 320 had incomplete or missing data, leaving 3810 with available data for analysis of whom 2666 received r-tPA (median dose 0.88 (IQR 0.78-0.90) mg/kg) and 1144 received UK (1.71 (1.43-2.00)×10 international unit per kilogram). There were several significant intergroup differences in patient characteristics: r-tPA patients were more educated, had less history of stroke, lower systolic blood pressure, greater neurological impairment and shorter treatment times from symptom onset than UK patients. However, in adjusted analysis, the frequency of excellent outcome (OR 1.18, 95% CI 1.00 to 1.40, p=0.052) and symptomatic intracranial haemorrhage (OR 0.70, 95% CI 0.33 to 1.47, p=0.344) were similar between groups. CONCLUSIONS UK may be as effective and carry a similar safety profile as r-tPA in treating mild to moderate AIS within guidelines in China. REGISTRATION: http://www.clinicaltrials.gov. unique identifier: NCT02854592

Making MapReduce Scheduling Effective in Erasure-Coded Storage Clusters

Abstract-With the explosive growth of data, enterprises increasingly adopt erasure coding on storage clusters to save storage space. On the other hand, erasure coding incurs higher performance overhead, especially during recovery. This motivates us to study the feasibility of alleviating performance overhead of erasure coding, while maintaining its storage efficiency advantage. In this paper, we study the performance issue of MapReduce when it runs on erasure-coded storage. We first review our previously proposed degraded-first scheduling, which avoids network bandwidth competition among degraded map tasks in failure mode, and hence improves the MapReduce performance over the default locality-first scheduling in MapReduce. We then show that the basic degraded-first scheduling may not work effectively when there are multiple running MapReduce jobs, and hence we propose heuristics to enhance the degraded-first scheduling design. Simulations demonstrate the performance gain of our enhanced degraded-first scheduling in a multi-job scenario. Our work makes a case that a new design of MapReduce scheduling is critical when we move to erasure-coded storage