DTC: A Dynamic Transaction Chopping Technique for Geo-Replicated Storage Services

Replicating data across geo-distributed datacenters is usually necessary for large scale cloud services to achieve high locality, durability and availability. One of the major challenges in such geo-replicated data services lies in consistency maintenance, which usually suffers from long latency due to costly coordination across datacenters. Among others, transaction chopping is an effective and efficient approach to address this challenge. However, existing chopping is conducted statically during programming, which is stubborn and complex for developers. In this article, we propose Dynamic Transaction Chopping (DTC), a novel technique that does transaction chopping and determines piecewise execution in a dynamic and automatic way. DTC mainly consists of two parts: a dynamic chopper to dynamically divide transactions into pieces according to the data partition scheme, and a conflict detection algorithm to check the safety of the dynamic chopping. Compared with existing techniques, DTC has several advantages: transparency to programmers, flexibility in conflict analysis, high degree of piecewise execution, and adaptability to data partition schemes. A prototype of DTC is implemented to verify the correctness of DTC and evaluate its performance. The experiment results show that our DTC technique can achieve much better performance than similar work

Text or Image? What is More Important in Cross-Domain Generalization Capabilities of Hate Meme Detection Models?

This paper delves into the formidable challenge of cross-domain generalization in multimodal hate meme detection, presenting compelling findings. We provide enough pieces of evidence supporting the hypothesis that only the textual component of hateful memes enables the existing multimodal classifier to generalize across different domains, while the image component proves highly sensitive to a specific training dataset. The evidence includes demonstrations showing that hate-text classifiers perform similarly to hate-meme classifiers in a zero-shot setting. Simultaneously, the introduction of captions generated from images of memes to the hate-meme classifier worsens performance by an average F1 of 0.02. Through blackbox explanations, we identify a substantial contribution of the text modality (average of 83%), which diminishes with the introduction of meme's image captions (52%). Additionally, our evaluation on a newly created confounder dataset reveals higher performance on text confounders as compared to image confounders with an average $\Delta$F1 of 0.18.Comment: Accepted at EACL'2024 Finding

Bias-Conflict Sample Synthesis and Adversarial Removal Debias Strategy for Temporal Sentence Grounding in Video

Temporal Sentence Grounding in Video (TSGV) is troubled by dataset bias issue, which is caused by the uneven temporal distribution of the target moments for samples with similar semantic components in input videos or query texts. Existing methods resort to utilizing prior knowledge about bias to artificially break this uneven distribution, which only removes a limited amount of significant language biases. In this work, we propose the bias-conflict sample synthesis and adversarial removal debias strategy (BSSARD), which dynamically generates bias-conflict samples by explicitly leveraging potentially spurious correlations between single-modality features and the temporal position of the target moments. Through adversarial training, its bias generators continuously introduce biases and generate bias-conflict samples to deceive its grounding model. Meanwhile, the grounding model continuously eliminates the introduced biases, which requires it to model multi-modality alignment information. BSSARD will cover most kinds of coupling relationships and disrupt language and visual biases simultaneously. Extensive experiments on Charades-CD and ActivityNet-CD demonstrate the promising debiasing capability of BSSARD. Source codes are available at https://github.com/qzhb/BSSARD.Comment: accepted by AAAI 202

A Fluorogenic, Small Molecule Reporter for Mammalian Phospholipase C Isozymes

Phospholipase C isozymes (PLCs) catalyze the conversion of the membrane lipid phosphatidylinositol 4,5-bisphosphate (PIP2) into two second messengers, inositol 1,4,5-trisphosphate and diacylglycerol. This family of enzymes are key signaling proteins that regulate the physiological responses of many extracellular stimuli such as hormones, neurotransmitters, and growth factors. Aberrant regulation of PLCs has been implicated in various diseases including cancer and Alzheimer’s disease. How, when, and where PLCs are activated under different cellular contexts are still largely unknown. We have developed a fluorogenic PLC reporter, WH-15, that can be cleaved in a cascade reaction to generate fluorescent 6-aminoquinoline. When applied in enzymatic assays with either pure PLCs or cell lysates, this reporter displays more than a 20-fold fluorescence enhancement in response to PLC activity. Under assay conditions, WH-15 has comparable Km and Vmax with the endogenous PIP2. This novel reporter will likely find broad applications that vary from imaging PLC activity in live cells to high throughput screening of PLC inhibitors

Fluorous enzymatic synthesis of phosphatidylinositides

Fluorous enzymatic synthesis is used to synthesize multiple phosphatidylinositides, which are directly immobilized on a microarray to probe protein–lipid interactions

Charge Shielding of PIP2 by Cations Regulates Enzyme Activity of Phospholipase C

Hydrolysis of phosphatidylinositol 4,5-bisphosphate (PIP2) of the plasma membrane by phospholipase C (PLC) generates two critical second messengers, inositol-1,4,5-trisphosphate and diacylglycerol. For the enzymatic reaction, PIP2 binds to positively charged amino acids in the pleckstrin homology domain of PLC. Here we tested the hypothesis that positively charged divalent and multivalent cations accumulate around the negatively charged PIP2, a process called electrostatic charge shielding, and therefore inhibit electrostatic PIP2-PLC interaction. This charge shielding of PIP2 was measured quantitatively with an in vitro enzyme assay using WH-15, a PIP2 analog, and various recombinant PLC proteins (β1, γ1, and δ1). Reduction of PLC activity by divalent cations, polyamines, and neomycin was well described by a theoretical model considering accumulation of cations around PIP2 via their electrostatic interaction and chemical binding. Finally, the charge shielding of PIP2 was also observed in live cells. Perfusion of the cations into cells via patch clamp pipette reduced PIP2 hydrolysis by PLC as triggered by M1 muscarinic receptors with a potency order of Mg2+ < spermine4+ < neomycin6+. Accumulation of divalent cations into cells through divalent-permeable TRPM7 channel had the same effect. Altogether our results suggest that Mg2+ and polyamines modulate the activity of PLCs by controlling the amount of free PIP2 available for the enzymes and that highly charged biomolecules can be inactivated by counterions electrostatically

Charge Shielding of PIP2 by Cations Regulates Enzyme Activity of Phospholipase C

Hydrolysis of phosphatidylinositol 4,5-bisphosphate (PIP2) of the plasma membrane by phospholipase C (PLC) generates two critical second messengers, inositol-1,4,5-trisphosphate and diacylglycerol. For the enzymatic reaction, PIP2 binds to positively charged amino acids in the pleckstrin homology domain of PLC. Here we tested the hypothesis that positively charged divalent and multivalent cations accumulate around the negatively charged PIP2, a process called electrostatic charge shielding, and therefore inhibit electrostatic PIP2-PLC interaction. This charge shielding of PIP2 was measured quantitatively with an in vitro enzyme assay using WH-15, a PIP2 analog, and various recombinant PLC proteins (β1, γ1, and δ1). Reduction of PLC activity by divalent cations, polyamines, and neomycin was well described by a theoretical model considering accumulation of cations around PIP2 via their electrostatic interaction and chemical binding. Finally, the charge shielding of PIP2 was also observed in live cells. Perfusion of the cations into cells via patch clamp pipette reduced PIP2 hydrolysis by PLC as triggered by M1 muscarinic receptors with a potency order of Mg2+ < spermine4+ < neomycin6+. Accumulation of divalent cations into cells through divalent-permeable TRPM7 channel had the same effect. Altogether our results suggest that Mg2+ and polyamines modulate the activity of PLCs by controlling the amount of free PIP2 available for the enzymes and that highly charged biomolecules can be inactivated by counterions electrostatically