Algorithmically Effective Differentially Private Synthetic Data

We present a highly effective algorithmic approach for generating $\varepsilon$-differentially private synthetic data in a bounded metric space with near-optimal utility guarantees under the 1-Wasserstein distance. In particular, for a dataset $X$ in the hypercube $[0,1]^d$, our algorithm generates synthetic dataset $Y$ such that the expected 1-Wasserstein distance between the empirical measure of $X$ and $Y$ is $O((\varepsilon n)^{-1/d})$ for $d\geq 2$, and is $O(\log^2(\varepsilon n)(\varepsilon n)^{-1})$ for $d=1$. The accuracy guarantee is optimal up to a constant factor for $d\geq 2$, and up to a logarithmic factor for $d=1$. Our algorithm has a fast running time of $O(\varepsilon n)$ for all $d\geq 1$ and demonstrates improved accuracy compared to the method in (Boedihardjo et al., 2022) for $d\geq 2$.Comment: 23 page

Differentially private low-dimensional representation of high-dimensional data

Differentially private synthetic data provide a powerful mechanism to enable data analysis while protecting sensitive information about individuals. However, when the data lie in a high-dimensional space, the accuracy of the synthetic data suffers from the curse of dimensionality. In this paper, we propose a differentially private algorithm to generate low-dimensional synthetic data efficiently from a high-dimensional dataset with a utility guarantee with respect to the Wasserstein distance. A key step of our algorithm is a private principal component analysis (PCA) procedure with a near-optimal accuracy bound that circumvents the curse of dimensionality. Different from the standard perturbation analysis using the Davis-Kahan theorem, our analysis of private PCA works without assuming the spectral gap for the sample covariance matrix.Comment: 21 page

Divide-or-Conquer? Which Part Should You Distill Your LLM?

Recent methods have demonstrated that Large Language Models (LLMs) can solve reasoning tasks better when they are encouraged to solve subtasks of the main task first. In this paper we devise a similar strategy that breaks down reasoning tasks into a problem decomposition phase and a problem solving phase and show that the strategy is able to outperform a single stage solution. Further, we hypothesize that the decomposition should be easier to distill into a smaller model compared to the problem solving because the latter requires large amounts of domain knowledge while the former only requires learning general problem solving strategies. We propose methods to distill these two capabilities and evaluate their impact on reasoning outcomes and inference cost. We find that we can distill the problem decomposition phase and at the same time achieve good generalization across tasks, datasets, and models. However, it is harder to distill the problem solving capability without losing performance and the resulting distilled model struggles with generalization. These results indicate that by using smaller, distilled problem decomposition models in combination with problem solving LLMs we can achieve reasoning with cost-efficient inference and local adaptation

Research progress on extraction, purification, structure and biological activity of Dendrobium officinale polysaccharides

Dendrobium officinale Kimura et Migo (D. officinale) is a traditional medicinal and food homologous plant that has been used for thousands of years in folk medicine and nutritious food. Recent studies have shown that polysaccharide is one of the main biologically active components in D. officinale. D. officinale polysaccharides possess several biological activities, such as anti-oxidant, heptatoprotective, immunomodulatory, gastrointestinal protection, hypoglycemic, and anti-tumor activities. In the past decade, polysaccharides have been isolated from D. officinale by physical and enzymatic methods and have been subjected to structural characterization and activity studies. Progress in extraction, purification, structural characterization, bioactivity, structure-activity relationship, and possible bioactivity mechanism of polysaccharides D. officinale were reviewed. In order to provide reference for the in-depth study of D. officinale polysaccharides and the application in functional food and biomedical research

The instantly blocking-based fluorescent immunochromatographic assay for the detection of SARS-CoV-2 neutralizing antibody

IntroductionAt present, there is an urgent need for the rapid and accurate detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) neutralizing antibodies (NAbs) to evaluate the ability of the human body to resist coronavirus disease 2019 (COVID-19) after infection or vaccination. The current gold standard for neutralizing antibody detection is the conventional virus neutralization test (cVNT), which requires live pathogens and biosafety level-3 (BSL-3) laboratories, making it difficult for this method to meet the requirements of large-scale routine detection. Therefore, this study established a time-resolved fluorescence-blocking lateral flow immunochromatographic assay (TRF-BLFIA) that enables accurate, rapid quantification of NAbs in subjects.MethodsThis assay utilizes the characteristic that SARS-CoV-2 neutralizing antibody can specifically block the binding of the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein and angiotensin-converting enzyme 2 (ACE2) to rapidly detect the content of neutralizing antibody in COVID-19-infected patients and vaccine recipients.ResultsWhen 356 samples of vaccine recipients were measured, the coincidence rate between this method and cVNT was 88.76%, which was higher than the coincidence rate of 76.97% between cVNT and a conventional chemiluminescence immunoassay detecting overall binding anti-Spike-IgG. More importantly, this assay does not need to be carried out in BSL-2 or 3 laboratories.DiscussionTherefore, this product can detect NAbs in COVID-19 patients and provide a reference for the prognosis and outcome of patients. Simultaneously, it can also be applied to large-scale detection to better meet the needs of neutralizing antibody detection after vaccination, making it an effective tool to evaluate the immunoprotective effect of COVID-19 vaccines

Ferromagnetism in two-dimensional CrTe2epitaxial films down to a few atomic layers

Two-dimensional (2D) van der Waals ferromagnetic materials have attracted intense attention due to their potential impact on both fundamental and applied research studies. Recently, a new 2D ferromagnet CrTe2, prepared by mechanical exfoliation or chemical vapor deposition, has gained interest due to its novel magnetic properties. In this work, high quality CrTe2 epitaxial thin films were prepared on GaAs (111)B substrates using solid source molecular beam epitaxy, with the thickness varying from 35 to 4 monolayers (MLs). The magnetic easy axis of all the films is oriented along the c-axis. A Curie temperature of 205 K is found in the 35 ML CrTe2 film, measured by the temperature-dependent anomalous Hall resistance (RAHE). Importantly, even when the film thickness decreases to 4 MLs, a robust out-of-plane ferromagnetism with a Curie temperature of 191 K has been demonstrated. This finding could pave the way for investigating the fundamental studies in 2D ferromagnetism and has great significance in device applications

Derivation of a Triple Mosaic Adenovirus for Cancer Gene Therapy

A safe and efficacious cancer medicine is necessary due to the increasing population of cancer patients whose particular diseases cannot be cured by the currently available treatment. Adenoviral (Ad) vectors represent a promising therapeutic medicine for human cancer therapy. However, several improvements are needed in order for Ad vectors to be effective cancer therapeutics, which include, but are not limited to, improvement of cellular uptake, enhanced cancer cell killing activity, and the capability of vector visualization and tracking once injected into the patients. To this end, we attempted to develop an Ad as a multifunctional platform incorporating targeting, imaging, and therapeutic motifs. In this study, we explored the utility of this proposed platform by generating an Ad vector containing the poly-lysine (pK), the herpes simplex virus type 1 (HSV-1) thymidine kinase (TK), and the monomeric red fluorescent protein (mRFP1) as targeting, tumor cell killing, and imaging motifs, respectively. Our study herein demonstrates the generation of the triple mosaic Ad vector with pK, HSV-1 TK, and mRFP1 at the carboxyl termini of Ad minor capsid protein IX (pIX). In addition, the functionalities of pK, HSV-1 TK, and mRFP1 proteins on the Ad vector were retained as confirmed by corresponding functional assays, indicating the potential multifunctional application of this new Ad vector for cancer gene therapy. The validation of the triple mosaic Ad vectors also argues for the ability of pIX modification as a base for the development of multifunctional Ad vectors

Thermal induced spin-polarized current protected by spin-momentum locking in nanowires

Spin-momentum locking arising from strong spin-orbit coupling is one of the key natures of topological materials. Since charge can induce a spin polarization due to spin-momentum locking, the search for materials that exhibit this feature has become one of the top priorities in the field of spintronics. In this paper, we report the electrical detection of the spin-transport properties of nanowires, using a nonlocal geometry measurement. A clear hysteresis voltage signal, which depends on the relative orientations between the magnetization of the ferromagnetic electrodes and the carrier spin polarization, has been observed. The hysteresis voltage states can be reversed by altering the electron movement direction, providing direct evidence of the spin-momentum locking feature of nanowires and revealing its topological nature. Furthermore, the current-dependent measurement suggests that the charge (spin) current is induced by thermal effect, which utilizes the thermoelectric properties of . Using the thermal effect to control the spin-polarized current protected by spin-momentum locking offers possibilities for small-sized devices based on the topological materials