Exploring the Benefits of Differentially Private Pre-training and Parameter-Efficient Fine-tuning for Table Transformers

For machine learning with tabular data, Table Transformer (TabTransformer) is a state-of-the-art neural network model, while Differential Privacy (DP) is an essential component to ensure data privacy. In this paper, we explore the benefits of combining these two aspects together in the scenario of transfer learning -- differentially private pre-training and fine-tuning of TabTransformers with a variety of parameter-efficient fine-tuning (PEFT) methods, including Adapter, LoRA, and Prompt Tuning. Our extensive experiments on the ACSIncome dataset show that these PEFT methods outperform traditional approaches in terms of the accuracy of the downstream task and the number of trainable parameters, thus achieving an improved trade-off among parameter efficiency, privacy, and accuracy. Our code is available at github.com/IBM/DP-TabTransformer.Comment: submitted to ICASSP 202

ICStega: Image Captioning-based Semantically Controllable Linguistic Steganography

Nowadays, social media has become the preferred communication platform for web users but brought security threats. Linguistic steganography hides secret data into text and sends it to the intended recipient to realize covert communication. Compared to edit-based linguistic steganography, generation-based approaches largely improve the payload capacity. However, existing methods can only generate stego text alone. Another common behavior in social media is sending semantically related image-text pairs. In this paper, we put forward a novel image captioning-based stegosystem, where the secret messages are embedded into the generated captions. Thus, the semantics of the stego text can be controlled and the secret data can be transmitted by sending semantically related image-text pairs. To balance the conflict between payload capacity and semantic preservation, we proposed a new sampling method called Two-Parameter Semantic Control Sampling to cutoff low-probability words. Experimental results have shown that our method can control diversity, payload capacity, security, and semantic accuracy at the same time.Comment: 5 pages, 5 tables, 3 figures. Accepted by ICASSP 202

Follow-up of patients with COVID-19 by the Delta variant after hospital discharge in Guangzhou, Guandong, China

The B.1.617.2 (Delta) variant of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has contributed to a new increment in cases across the globe. We conducted a prospective follow-up of COVID-19 cases to explore the recurrence and potential propagation risk of the Delta variant and discuss potential explanations for the infection recurrence. A prospective, non-interventional follow-up of discharged patients who had SARS-CoV-2 infections by the Delta variant in Guangdong, China, from May 2021 to June 2021 was conducted. The subjects were asked to complete a physical health examination and undergo nucleic acid testing and antibody detection for the laboratory diagnosis of COVID-19. In total, 20.33% (25/123) of patients exhibited recurrent positive results after discharge. All patients with infection recurrence were asymptomatic and showed no abnormalities in the pulmonary computed tomography. The time from discharge to the recurrent positive testing was usually between 1-33 days, with a mean time of 9.36 days. The cycle threshold from the real-time polymerase chain reaction assay that detected the recurrence of positivity ranged from 27.48 to 39.00, with an average of 35.30. The proportion of vaccination in the non-recurrent group was higher than that in the recurrently positive group (26% vs. 4%; χ2 = 7.902; P < 0.05). Two months after discharge, the most common symptom was hair loss and 59.6% of patients had no long-term symptoms at all. It is possible for the Delta variant SARS-CoV-2 patients after discharge to show recurrent positive results of nucleic acid detection; however, there is a low risk of continuous community transmission. Both, the physical and mental quality of life of discharged patients were significantly affected. Our results suggest that it makes sense to implement mass vaccination against the Delta variant of SARS-CoV-2

Evaluation of the new rural cooperative medical system in China: is it working or not?

<p>Abstract</p> <p>Background</p> <p>To prove the possibility of implementing the New Rural Cooperative Medical System (NRCMS) at different levels with a premium funding according to their economic level in developed and less developed areas in Guangdong province, and study the insurable inpatients in different types of regions, taking into account limitations of indemnities and loss ratios.</p> <p>Method</p> <p>All data samples were randomly collected from the NRCMS Department, Guangdong Province. Gross domestic product (GDP) at 10000 Yuan per capita was employed to divide Guangdong into two economic levels: (1) economically developed & (2) less economically developed regions. A descriptive analysis about tendency of raising premium and reimbursement ratios of common fund was performed with independent samples and t-test as well as implementing a model to evaluate the differences in premium contribution differences in co-payments, thresholds, and rebates. Also, a qualitative study measured several economic factors to evaluate farmers' financial and social potency in contributing to the NRCMS.</p> <p>Result</p> <p>A higher GDP per capita were found within economically developed regions (p < 0.05) than in less developed areas, with higher tendency for funding capacity and average funding capability in villages and towns within economically developed regions (p < 0.05) than in economically less developed. Maximum benefits between two regions in medical insurance coverage showed significant difference (p < 0.05); differences between basic medical insurance coverage between two regions was insignificant (p > 0.05); nevertheless, economically developed regions showed higher threshold and rebates with less co-payments in the economically developed than less developed.</p> <p>Conclusion</p> <p>Despite some loop holes in the NRCMS, the system is workable, but needs more strengthening by encouraging farmers' participation into NRCMS with a necessity to implement a new reimbursement payment system by health care providers. In addition it is proposed that for maximum benefits another premium funding should be secured.</p

Investigation on plasma enhanced decomposition of ammonium dinitramide (ADN) based propellant with optical diagnosis

Plasma-enhanced decomposition is a promising method to achieve reliable ignition and better thruster performance with an ADN-based propellant. High-speed imaging and optical emission spectroscopy are used to characterize the discharge plasma produced from ADN-based propellant vapor and argon carrier gas within parallel planes. Discharge regimes are independently controlled by varying working parameters. The transition from abnormal glow discharge (AGD) to filamentary discharge (FD) is identified from voltage-current characteristics and sudden changes in excitation electron temperature (Te-exc) and electron density (Ne) under a pressure of 0.2-10 kPa. Instabilities develop because there are more freedom degrees and higher collision probabilities after ADN-based propellant vapor is added. The product of Te-exc and Ne shows a higher energy transfer efficiency from input power to vapor in the FD regime. Water molecules increase the net dissociative attachment rate and effectively quench Ne. Although preheated vapor (as the discharge medium) has a much lower Ne, more radicals appear such as OH, NH, CH, CN, N2, N2+, and C2, which promote chemical interactions in an electric field and increase the probability of successful ignition. This can be attributed to thermalization due to an increase in the translational kinetic energy and rotational excitation, which has an important impact on chemical reaction kinetics. Therefore, preheating is verified as critical for improving the ignition and performance of a plasma-assisted ADN-based thruster

E-H mode transitions and high-energy electron characteristics of helical antenna coupled plasma

AbstractMetastable and high-energy electron characteristics obtained from optical emission spectroscopy are used to analyze the dependence of the H mode on the magnetic field strength and discharge pressure. The results show that the H-mode characteristics gradually appears as the magnetic field strength is increased, the reason being that electrons undergo multiple acceleration-collision cycles at high magnetic field strength, thereby the metastable ionization will be increased. This improves energy utilization and making the H mode appearing. The variation in the density of metastable states and the Langmuir probe data shows that the electron energy distribution function evolves from non-Maxwellian to Maxwellian. The radial constraint of the magnetic field to the electrons and thus reduces the electron heating efficiency. Moreover, the increase in electric field strength with magnetic field leads to an increase in energy obtained by the electrons per unit distance. The competition between the two makes the number of high-energy electrons decrease rapidly first, and then increase slowly with magnetic field strength increasing. The turning point increases with the increase of discharge pressure and radio-frequency (RF) power. And the higher the pressure the lower the high-energy electron. For fields between 105.5 G and 212.7 G. In the H-mode regime, and with increasing RF power, the number of high-energy electrons will be sudden rise after experiencing a steady increase. The sudden rise RF power increase with magnetic field and decrease with discharge pressure increase. However, at high magnetic fields (>265 G) and high power (>450 W), the high-energy electron density decreases with power increasing