127 research outputs found
Privacy-Preserving Polynomial Computing Over Distributed Data
In this letter, we delve into a scenario where a user aims to compute
polynomial functions using their own data as well as data obtained from
distributed sources. To accomplish this, the user enlists the assistance of
distributed workers, thereby defining a problem we refer to as
privacy-preserving polynomial computing over distributed data. To address this
challenge, we propose an approach founded upon Lagrange encoding. Our method
not only possesses the ability to withstand the presence of stragglers and
byzantine workers but also ensures the preservation of security. Specifically,
even if a coalition of workers collude, they are unable to acquire any
knowledge pertaining to the data originating from the distributed sources or
the user
Multiplexed Streaming Codes for Messages With Different Decoding Delays in Channel with Burst and Random Erasures
In a real-time transmission scenario, messages are transmitted through a
channel that is subject to packet loss. The destination must recover the
messages within the required deadline. In this paper, we consider a setup where
two different types of messages with distinct decoding deadlines are
transmitted through a channel that can introduce burst erasures of a length at
most , or random erasures. The message with a short decoding deadline
is referred to as an urgent message, while the other one with a decoding
deadline () is referred to as a less urgent message.
We propose a merging method to encode two message streams of different
urgency levels into a single flow. We consider the scenario where . We establish that any coding strategy based on this merging approach has a
closed-form upper limit on its achievable sum rate. Moreover, we present
explicit constructions within a finite field that scales quadratically with the
imposed delay, ensuring adherence to the upper bound. In a given parameter
configuration, we rigorously demonstrate that the sum rate of our proposed
streaming codes consistently surpasses that of separate encoding, which serves
as a baseline for comparison
Effects of phosphorus on chemical forms of Cd in plants of four spinach (Spinacia oleracea L.) cultivars differing in Cd accumulation
In order to clarify how cadmium (Cd) chemical forms in planta relate to the genotype difference in Cd accumulation of spinach (Spinacia oleracea L.), two low-Cd and two high-Cd cultivars were compared under a hydroponic experiment with two concentrations of Cd (8.98 or 44.71 μmol Cd L(-1)). The concentrations of phosphorus in the hydroponic system were also adjusted to two levels (0.5 and 1.0 mmol L(-1)) to investigate the influence of phosphorus on the forms and accumulation of Cd in the tested cultivars. Average Cd concentrations in shoots were 8.50-10.06 mg kg(-1) for high-Cd cultivars and 6.11-6.64 mg kg(-1) for low-Cd cultivars a under lower Cd treatment and were as high as 24.41-31.35 mg kg(-1) and 19.65-25.76 mg kg(-1), respectively, under a higher treatment. Phosphorus significantly decreased Cd accumulation in the tested cultivars, and the effect had superiority over the cultivar alternation under higher Cd stress. Cadmium in the NaCl-extractable fraction of the plant tissues showed the greatest relationship to genotype difference of Cd accumulation. The difference in the capacity to binding Cd into F HAc, F HCl, or F Residue was another important mechanism involving in the genotype difference in Cd accumulation of spinach. Among them, average proportion of Cd in F HAc in low-Cd cultivars was higher than that in high-Cd cultivars in association with the effect of phosphorus
Dual-Modal Attention-Enhanced Text-Video Retrieval with Triplet Partial Margin Contrastive Learning
In recent years, the explosion of web videos makes text-video retrieval
increasingly essential and popular for video filtering, recommendation, and
search. Text-video retrieval aims to rank relevant text/video higher than
irrelevant ones. The core of this task is to precisely measure the cross-modal
similarity between texts and videos. Recently, contrastive learning methods
have shown promising results for text-video retrieval, most of which focus on
the construction of positive and negative pairs to learn text and video
representations. Nevertheless, they do not pay enough attention to hard
negative pairs and lack the ability to model different levels of semantic
similarity. To address these two issues, this paper improves contrastive
learning using two novel techniques. First, to exploit hard examples for robust
discriminative power, we propose a novel Dual-Modal Attention-Enhanced Module
(DMAE) to mine hard negative pairs from textual and visual clues. By further
introducing a Negative-aware InfoNCE (NegNCE) loss, we are able to adaptively
identify all these hard negatives and explicitly highlight their impacts in the
training loss. Second, our work argues that triplet samples can better model
fine-grained semantic similarity compared to pairwise samples. We thereby
present a new Triplet Partial Margin Contrastive Learning (TPM-CL) module to
construct partial order triplet samples by automatically generating
fine-grained hard negatives for matched text-video pairs. The proposed TPM-CL
designs an adaptive token masking strategy with cross-modal interaction to
model subtle semantic differences. Extensive experiments demonstrate that the
proposed approach outperforms existing methods on four widely-used text-video
retrieval datasets, including MSR-VTT, MSVD, DiDeMo and ActivityNet.Comment: Accepted by ACM MM 202
PuCRZ1, an C2H2 transcription factor from Polyporus umbellatus, positively regulates mycelium response to osmotic stress
Polyporus umbellatus is an edible and medicinal mushroom with the capacity to produce sclerotia. However, the mechanism of P. umbellatus sclerotia formation is unclear. CRZ1 is a C2H2 family transcription factor involved in the Ca2+-calcineurin signaling pathway, which has the function of regulating sclerotia formation, maintaining ion homeostasis, and responding to stress. In this study, we identified 28 C2H2 transcription factors in P. umbellatus genome, 13 of which are differentially expressed between mycelium and sclerotia, including PuCRZ1. Combining DNA affinity purification and sequencing (DAP-seq) and quantitative real-time PCR (qRT-PCR), three genes (PuG10, PuG11, PuG12) were identified as putative PuCRZ1 target genes containing a putative binding motif (GTGGCG) within their promoter. Yeast single hybridization (Y1H) and EMSA further confirmed that PuCRZ1 can bind to the promoter region of PuG10, PuG11, and PuG12. PuCRZ1 gene could reduce the sensitivity of NaCl in yeast cells. Furthermore, overexpression of the PuCRZ1 target gene, especially the FVLY domain containing gene PuG11, could improve the mycelia growth rate and mannitol tolerance in P. umbellatus. These results demonstrate that PuCRZ1 in the Ca2+-calcineurin signaling pathway plays an important role in mycelia growth, as well as osmotic stress tolerance
Circulating Long Noncoding RNAs as Biomarkers for Predicting Head and Neck Squamous Cell Carcinoma
Background/Aims: The anatomical complexity of the head and neck region and the lack of sufficiently specific and sensitive biomarkers often lead to the diagnosis of head and neck squamous cell carcinoma (HNSCC) at advanced stages. To identify novel biomarkers for early diagnosis of primary HNSCC through a minimally invasive method, we investigated circulating long noncoding RNA (lncRNA) levels in plasma of HNSCC patients. Methods: The global lncRNA expression profiles of HNSCC patients were measured using microarray and next-generation RNA-sequencing (RNA-seq) data from both circulating and tissue samples. The diagnosis prediction model based on the lncRNA signatures and clinical features was evaluated by multi-stage validation and risk score analysis. Results: The data showed that 432 lncRNA transcripts were differentially expressed by fold changes of > 4 in circulating samples and 333 in tissues samples, respectively. Only 12 lncRNAs consistently emerged in these two kinds of samples. After the risk score analysis including a multistage validation, we identified three lncRNAs, namely, HOXA11-AS, LINC00964 and MALAT1, which were up-regulated in the plasma of HNSCC patients compared with those in healthy controls with merged areas under the curve (AUCs) in training and validation sets of 0.925 and 0.839, respectively. Conclusion: HOXA11-AS, LINC00964 and MALAT1 might be potential circulating biomarkers for the early detection of HNSCC in the future
Atypical radio pulsations from magnetar SGR 1935+2154
Magnetars are neutron stars with extremely strong magnetic fields, frequently
powering high-energy activity in X-rays. Pulsed radio emission following some
X-ray outbursts have been detected, albeit its physical origin is unclear. It
has long been speculated that the origin of magnetars' radio signals is
different from those from canonical pulsars, although convincing evidence is
still lacking. Five months after magnetar SGR 1935+2154's X-ray outburst and
its associated Fast Radio Burst (FRB) 20200428, a radio pulsar phase was
discovered. Here we report the discovery of X-ray spectral hardening associated
with the emergence of periodic radio pulsations from SGR 1935+2154 and a
detailed analysis of the properties of the radio pulses. The complex radio
pulse morphology, which contains both narrow-band emission and frequency
drifts, has not been seen before in other magnetars, but is similar to those of
repeating FRBs - even though the luminosities are many orders of magnitude
different. The observations suggest that radio emission originates from the
outer magnetosphere of the magnetar, and the surface heating due to the
bombardment of inward-going particles from the radio emission region is
responsible for the observed X-ray spectral hardening.Comment: 47 pages, 11 figure
Construction of a cross-species cell landscape at single-cell level.
Individual cells are basic units of life. Despite extensive efforts to characterize the cellular heterogeneity of different organisms, cross-species comparisons of landscape dynamics have not been achieved. Here, we applied single-cell RNA sequencing (scRNA-seq) to map organism-level cell landscapes at multiple life stages for mice, zebrafish and Drosophila. By integrating the comprehensive dataset of > 2.6 million single cells, we constructed a cross-species cell landscape and identified signatures and common pathways that changed throughout the life span. We identified structural inflammation and mitochondrial dysfunction as the most common hallmarks of organism aging, and found that pharmacological activation of mitochondrial metabolism alleviated aging phenotypes in mice. The cross-species cell landscape with other published datasets were stored in an integrated online portal-Cell Landscape. Our work provides a valuable resource for studying lineage development, maturation and aging
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