Exploring the Process of Fresh Produce Supply Within a Platform Ecosystem During City Lockdown Period

While the existing literature focusing on how organizations collaborate within ecosystems to overcome institutional logic conflicts and the information systems enabled inter-organizational cooperation, less is known on how information systems develop during crises and enable effective collaboration among stakeholders. Through an in-depth case study of Shenzhen Company H (pseudonym) platform ecosystem, we present an IT-enabled fresh produce supply process. Our findings reveal that this process unfolds across four dimensions - iterative IT tailoring, progressive system synergy, facilitative IT confluence, and user-attuned technological adaptation. Based on these dimensions, we propose an IT-enabled platform ecosystem orchestration mechanism in crisis situations. These mechanisms also offer practical implications not only for organizations\u27 strategies when facing crises but also for the enhancement of their daily operational competence

An Efficient Temporary Deepfake Location Approach Based Embeddings for Partially Spoofed Audio Detection

Partially spoofed audio detection is a challenging task, lying in the need to accurately locate the authenticity of audio at the frame level. To address this issue, we propose a fine-grained partially spoofed audio detection method, namely Temporal Deepfake Location (TDL), which can effectively capture information of both features and locations. Specifically, our approach involves two novel parts: embedding similarity module and temporal convolution operation. To enhance the identification between the real and fake features, the embedding similarity module is designed to generate an embedding space that can separate the real frames from fake frames. To effectively concentrate on the position information, temporal convolution operation is proposed to calculate the frame-specific similarities among neighboring frames, and dynamically select informative neighbors to convolution. Extensive experiments show that our method outperform baseline models in ASVspoof2019 Partial Spoof dataset and demonstrate superior performance even in the crossdataset scenario. The code is released online.Comment: Submitted to ICASSP 202

Exploring the active ingredients and potential mechanisms of action of sinomenium acutum in the treatment of rheumatoid arthritis based on systems biology and network pharmacology

Objective: To investigate and predict the targets and signaling pathways of sinomenium acutum (SA) in the treatment of rheumatoid arthritis (RA) through systems biology and network pharmacology, and to elucidate its possible mechanisms of action.Methods: We screened the active ingredients and corresponding target proteins of SA in Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), Traditional Chinese Medicines Integrated Database (TCMID) and Bioinformatics Analysis Tool for Molecular mechANism of Traditional Chinese Medicine (BATMAN); and obtained the targets of rheumatoid arthritis diseases in a database of gene-disease associations (DisGeNET), Online Mendelian Inheritance in Man (OMIM) database. The two targets were mapped by Venn diagram and the intersection was taken. The intersecting targets were used to construct protein-protein interaction (PPI) network maps in the String database, and Metascape was used for Gene Ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment. Finally, the molecular docking technique was applied to validate and further clarify the core target of SA for the treatment of rheumatoid arthritis.Results: A total of six active ingredients and 217 potential targets were obtained after screening; 2,752 rheumatoid arthritis-related targets and 66 targets common to RA and SA. GO function and KEGG pathway enrichment analysis yielded 751 GO function entries (652 GO biological processes, 59 GO molecular functions and 40 GO cellular components) and 77 KEGG signaling pathways. It mainly involves pathways related to neural activity ligand-receptor interaction pathways, cancer pathways, calcium signaling channels, Th17 cell differentiation and others, which are mainly classified into four categories, including regulation of immunity, anti-inflammation, regulation of cell growth and apoptosis, and signaling. The molecular docking results showed that the binding energy of PTGS2, CASP3, JUN and PPARG to the key components beta-sitosterol, 16-epi-Isositsirikine, Sinomenine and Stepholidine were ≤ −6.5 kcal/mol, suggesting the existence of molecular binding sites.Conclusion: SA acts on key targets such as PTGS2, CASP3, JUN, and PPARG to modulate signaling pathways such as neural activity ligand-receptor interaction, cancer, calcium ion, NF-κB, and Th17 cell differentiation to regulate immunity, anti-inflammation, modulation of cell cycle, bone metabolism, and signaling for the treatment of RA. It was also confirmed that the treatment of RA with SA has multi-component, multi-target, multi-pathway and multi-mechanism characteristics

A simultaneous search for prompt radio emission associated with the short GRB 170112A using the all-sky imaging capability of the OVRO-LWA

We have conducted the most sensitive low frequency (below 100 MHz) search to date for prompt, low-frequency radio emission associated with short-duration gamma-ray bursts (GRBs), using the Owens Valley Radio Observatory Long Wavelength Array (OVRO-LWA). The OVRO-LWA's nearly full-hemisphere field-of-view ($\sim20$,$000$ square degrees) allows us to search for low-frequency (sub-$100$ MHz) counterparts for a large sample of the subset of GRB events for which prompt radio emission has been predicted. Following the detection of short GRB 170112A by Swift, we used all-sky OVRO-LWA images spanning one hour prior to and two hours following the GRB event to search for a transient source coincident with the position of GRB 170112A. We detect no transient source, with our most constraining $1\sigma$ flux density limit of $650~\text{mJy}$ for frequencies spanning $27~\text{MHz}-84~\text{MHz}$. We place constraints on a number of models predicting prompt, low-frequency radio emission accompanying short GRBs and their potential binary neutron star merger progenitors, and place an upper limit of $L_\text{radio}/L_\gamma \lesssim 7\times10^{-16}$ on the fraction of energy released in the prompt radio emission. These observations serve as a pilot effort for a program targeting a wider sample of both short and long GRBs with the OVRO-LWA, including bursts with confirmed redshift measurements which are critical to placing the most constraining limits on prompt radio emission models, as well as a program for the follow-up of gravitational wave compact binary coalescence events detected by advanced LIGO and Virgo.Comment: 14 pages, 5 figures, ApJ submitte

β-hydroxybutyrate administration improves liver injury and metabolic abnormality in postnatal growth retardation piglets

Abnormal hepatic energy metabolism limits the growth and development of piglets. We hypothesized that β-hydroxybutyrate (BHB) might improve the growth performance of piglets by maintaining hepatic caloric homeostasis. A total of 30 litters of newborn piglets were tracked, and 30 postnatal growth retardation (PGR) piglets and 40 healthy piglets were selected to treat with normal saline with or without BHB (25 mg/kg/days) at 7-d-old. At the age of 42 days, 8 piglets in each group were sacrificed, and serum and liver were collected. Compared with the healthy-control group piglets, PGR piglets showed lower body weight (BW) and liver weight (p < 0.05), and exhibited liver injury and higher inflammatory response. The contents of serum and hepatic BHB were lower (p < 0.05), and gene expression related to hepatic ketone body production were down-regulated in PGR piglets (p < 0.05). While BHB treatment increased BW and serum BHB levels, but decreased hepatic BHB levels in PGR piglets (p < 0.05). BHB alleviated the liver injury by inhibiting the apoptosis and inflammation in liver of PGR piglets (p < 0.05). Compared with the healthy-control group piglets, liver glycogen content and serum triglyceride level of PGR piglets were increased (p < 0.05), liver gluconeogenesis gene and lipogenesis gene expression were increased (p < 0.05), and liver NAD+ level was decreased (p < 0.05). BHB supplementation increased the ATP levels in serum and liver (p < 0.05), whereas decreased the serum glucose, cholesterol, triglyceride and high-density lipoprotein cholesterol levels and glucose and lipid metabolism in liver of PGR piglets (p < 0.05). Therefore, BHB treatment might alleviate the liver injury and inflammation, and improve hepatic energy metabolism by regulating glucose and lipid metabolism, thereby improving the growth performance of PGR piglets

Microwave imaging of quasi-periodic pulsations at flare current sheet

Quasi-periodic pulsations (QPPs) are frequently detected in solar and stellar flares, but the underlying physical mechanisms are still to be ascertained. Here, we show microwave QPPs during a solar flare originating from quasi-periodic magnetic reconnection at the flare current sheet. They appear as two vertically detached but closely related sources with the brighter ones located at flare loops and the weaker ones along the stretched current sheet. Although the brightness temperatures of the two microwave sources differ greatly, they vary in phase with periods of about 10–20 s and 30–60 s. The gyrosynchrotron-dominated microwave spectra also present a quasi-periodic soft-hard-soft evolution. These results suggest that relevant high-energy electrons are accelerated by quasi-periodic reconnection, likely arising from the modulation of magnetic islands within the current sheet as validated by a 2.5-dimensional magnetohydrodynamic simulation

The Radio Sky at Meter Wavelengths: m-Mode Analysis Imaging with the Owens Valley Long Wavelength Array

A host of new low-frequency radio telescopes seek to measure the 21-cm transition of neutral hydrogen from the early universe. These telescopes have the potential to directly probe star and galaxy formation at redshifts $20 \gtrsim z \gtrsim 7$, but are limited by the dynamic range they can achieve against foreground sources of low-frequency radio emission. Consequently, there is a growing demand for modern, high-fidelity maps of the sky at frequencies below 200 MHz for use in foreground modeling and removal. We describe a new widefield imaging technique for drift-scanning interferometers, Tikhonov-regularized $m$-mode analysis imaging. This technique constructs images of the entire sky in a single synthesis imaging step with exact treatment of widefield effects. We describe how the CLEAN algorithm can be adapted to deconvolve maps generated by $m$-mode analysis imaging. We demonstrate Tikhonov-regularized $m$-mode analysis imaging using the Owens Valley Long Wavelength Array (OVRO-LWA) by generating 8 new maps of the sky north of $\delta=-30^\circ$ with 15 arcmin angular resolution, at frequencies evenly spaced between 36.528 MHz and 73.152 MHz, and $\sim$800 mJy/beam thermal noise. These maps are a 10-fold improvement in angular resolution over existing full-sky maps at comparable frequencies, which have angular resolutions $\ge 2^\circ$. Each map is constructed exclusively from interferometric observations and does not represent the globally averaged sky brightness. Future improvements will incorporate total power radiometry, improved thermal noise, and improved angular resolution -- due to the planned expansion of the OVRO-LWA to 2.6 km baselines. These maps serve as a first step on the path to the use of more sophisticated foreground filters in 21-cm cosmology incorporating the measured angular and frequency structure of all foreground contaminants.Comment: 27 pages, 18 figure

A Hybrid Wavelet de-noising and Rank-Set Pair Analysis approach for forecasting hydro-meteorological time series

Accurate, fast forecasting of hydro-meteorological time series is presently a major challenge in drought and flood mitigation. This paper proposes a hybrid approach, wavelet de-noising (WD) and Rank-Set Pair Analysis (RSPA), that takes full advantage of a combination of the two approaches to improve forecasts of hydro-meteorological time series. WD allows decomposition and reconstruction of a time series by the wavelet transform, and hence separation of the noise from the original series. RSPA, a more reliable and efficient version of Set Pair Analysis, is integrated with WD to form the hybrid WD-RSPA approach. Two types of hydro-meteorological data sets with different characteristics and different levels of human influences at some representative stations are used to illustrate the WD-RSPA approach. The approach is also compared to three other generic methods: the conventional Auto Regressive Integrated Moving Average (ARIMA) method, Artificial Neural Networks (ANNs) (BP-error Back Propagation, MLP-Multilayer Perceptron and RBF-Radial Basis Function), and RSPA alone. Nine error metrics are used to evaluate the model performance. Compared to three other generic methods, the results generated by WD-REPA model presented invariably smaller error measures which means the forecasting capability of the WD-REPA model is better than other models. The results show that WD-RSPA is accurate, feasible, and effective. In particular, WD-RSPA is found to be the best among the various generic methods compared in this paper, even when the extreme events are included within a time series