Private Semi-supervised Knowledge Transfer for Deep Learning from Noisy Labels

Deep learning models trained on large-scale data have achieved encouraging performance in many real-world tasks. Meanwhile, publishing those models trained on sensitive datasets, such as medical records, could pose serious privacy concerns. To counter these issues, one of the current state-of-the-art approaches is the Private Aggregation of Teacher Ensembles, or PATE, which achieved promising results in preserving the utility of the model while providing a strong privacy guarantee. PATE combines an ensemble of "teacher models" trained on sensitive data and transfers the knowledge to a "student" model through the noisy aggregation of teachers' votes for labeling unlabeled public data which the student model will be trained on. However, the knowledge or voted labels learned by the student are noisy due to private aggregation. Learning directly from noisy labels can significantly impact the accuracy of the student model. In this paper, we propose the PATE++ mechanism, which combines the current advanced noisy label training mechanisms with the original PATE framework to enhance its accuracy. A novel structure of Generative Adversarial Nets (GANs) is developed in order to integrate them effectively. In addition, we develop a novel noisy label detection mechanism for semi-supervised model training to further improve student model performance when training with noisy labels. We evaluate our method on Fashion-MNIST and SVHN to show the improvements on the original PATE on all measures

A 3D Non-Stationary MIMO Channel Model for Reconfigurable Intelligent Surface Auxiliary UAV-To-Ground MmWave Communications

Unmanned aerial vehicle (UAV) communications exploiting millimeter wave (mmWave) can satisfy the increasing data rate demands for future wireless networks owing to the line-of-sight (LoS) dominated transmission and flexibility. In reality, the LoS link can be easily and severely blocked due to poor propagation environments such as tall buildings or trees. To this end, we introduce a reconfigurable intelligent surface (RIS), which passively reflects signals with programmable reflection coefficients, between the transceivers to enhance the communication quality. Specifically, in this paper we generalize a three-dimensional (3D) non-stationary wideband end-to-end channel model for RIS auxiliary UAV-to-ground mmWave multiple-input multiple-output (MIMO) communication systems. By modeling the RIS as a virtual cluster, we study the power delivering capability of RIS as well as the fading characteristic of the proposed channel model. Important channel statistical properties are derived and thoroughly investigated, and the impact of RIS reflection phase configurations on these statistical properties is studied, which provides guidelines for the practical system design. The agreement between theoretical and simulated as well as measurement results validate the effectiveness of the proposed channel model

Polysaccharides from the Medicinal Mushroom Cordyceps taii Show Antioxidant and Immunoenhancing Activities in a D-Galactose-Induced Aging Mouse Model

Cordyceps taii, an edible medicinal mushroom native to south China, is recognized as an unparalleled resource of healthy foods and drug discovery. In the present study, the antioxidant pharmacological properties of C. taii were systematically investigated. In vitro assays revealed the scavenging activities of the aqueous extract and polysaccharides of C. taii against various free radicals, that is, 1,1-diphenyl-2-picrylhydrazyl radical, hydroxyl radical, and superoxide anion radical. The EC50 values for superoxide anion-free radical ranged from 2.04 mg/mL to 2.49 mg/mL, which was at least 2.6-fold stronger than that of antioxidant thiourea. The polysaccharides also significantly enhanced the antioxidant enzyme activities (superoxide dismutase, catalase, and glutathione peroxidase) and markedly decreased the malondialdehyde production of lipid peroxidation in a D-galactose-induced aging mouse model. Interestingly, the immune function of the administration group was significantly boosted compared with the D-galactose-induced aging model group. Therefore, the C. taii polysaccharides possessed potent antioxidant activity closely associated with immune function enhancement and free radical scavenging. These findings suggest that the polysaccharides are a promising source of natural antioxidants and antiaging drugs. Consequently, a preliminary chemical investigation was performed using gas chromatography-mass spectroscopy and revealed that the polysaccharides studied were mainly composed of glucose, mannose, and galactose. Fourier-transform infrared spectra also showed characteristic polysaccharide absorption bands

Privacy-Preserving Tensor Factorization for Collaborative Health Data Analysis

Tensor factorization has been demonstrated as an efficient approach for computational phenotyping, where massive electronic health records (EHRs) are converted to concise and meaningful clinical concepts. While distributing the tensor factorization tasks to local sites can avoid direct data sharing, it still requires the exchange of intermediary results which could reveal sensitive patient information. Therefore, the challenge is how to jointly decompose the tensor under rigorous and principled privacy constraints, while still support the model's interpretability. We propose DPFact, a privacy-preserving collaborative tensor factorization method for computational phenotyping using EHR. It embeds advanced privacy-preserving mechanisms with collaborative learning. Hospitals can keep their EHR database private but also collaboratively learn meaningful clinical concepts by sharing differentially private intermediary results. Moreover, DPFact solves the heterogeneous patient population using a structured sparsity term. In our framework, each hospital decomposes its local tensors, and sends the updated intermediary results with output perturbation every several iterations to a semi-trusted server which generates the phenotypes. The evaluation on both real-world and synthetic datasets demonstrated that under strict privacy constraints, our method is more accurate and communication-efficient than state-of-the-art baseline methods

Two variants on T2DM susceptible gene HHEX are associated with CRC risk in a Chinese population

Increasing amounts of evidence has demonstrated that T2DM (Type 2 Diabetes Mellitus) patients have increased susceptibility to CRC (colorectal cancer). As HHEX is a recognized susceptibility gene in T2DM, this work was focused on two SNPs in HHEX, rs1111875 and rs7923837, to study their association with CRC. T2DM patients without CRC (T2DM-only, n=300), T2DM with CRC (T2DM/CRC, n=135), cancer-free controls (Control, n=570), and CRC without T2DM (CRC-only, n=642) cases were enrolled. DNA samples were extracted from the peripheral blood leukocytes of the patients and sequenced by direct sequencing. The χ(2) test was used to compare categorical data. We found that in T2DM patients, rs1111875 but not the rs7923837 in HHEX gene was associated with the occurrence of CRC (p= 0.006). for rs1111875, TC/CC patients had an increased risk of CRC (p=0.019, OR=1.592, 95%CI=1.046-2.423). Moreover, our results also indicated that the two variants of HEEX gene could be risk factors for CRC in general population, independent on T2DM (p< 0.001 for rs1111875, p=0.001 for rs7923837). For rs1111875, increased risk of CRC was observed in TC or TC/CC than CC individuals (p<0.001, OR= 1.780, 95%CI= 1.385-2.287; p<0.001, OR= 1.695, 95%CI= 1.335-2.152). For rs7923837, increased CRC risk was observed in AG, GG, and AG/GG than AA individuals (p< 0.001, OR= 1.520, 95%CI= 1.200-1.924; p=0.036, OR= 1.739, 95%CI= 0.989-3.058; p< 0.001, OR= 1.540, 95%CI= 1.225-1.936). This finding highlights the potentially functional alteration with HHEX rs1111875 and rs7923837 polymorphisms may increase CRC susceptibility. Risk effects and the functional impact of these polymorphisms need further validation

A Statistical MIMO Channel Model for Reconfigurable Intelligent Surface Assisted Wireless Communications

Reconfigurable intelligent surface (RIS) consisting of a large number of programmable near-passive units has been a hot topic in wireless communications due to its capability in providing smart radio environments to enhance the communication performance. However, the existing research are mainly based on simplistic channel models, which will, in principle, lead to inaccurate analysis of the system performance. In this paper, we propose a general three-dimensional (3D) wideband non-stationary end-to-end channel model for RIS assisted multiple-input multiple-output (MIMO) communications, which takes into account the physical properties of RIS, such as unit numbers, unit sizes, array orientations and array configurations. By modeling the RIS by a virtual cluster, we describe the end-to-end channel by a superposition of virtual line-of-sight (V-LoS), single-bounced non-LoS (SB-NLoS), and double-bounced NLoS (DB-NLoS) components. We also derive an equivalent cascaded channel model and show the equivalence between end-to-end and cascaded modeling of RIS channels. Then, a sub-optimal solution with low complexity is used to derive the RIS reflection phases. The impact of physical properties of RIS, such as unit numbers, unit sizes, array orientations, array configurations and array relative locations, on channel statistical characteristics has been investigated and analyzed, the results demonstrate that the proposed model is helpful for characterizing the RIS-assisted communication channels

Synthesis, Characterization, and In Vitro Photodynamic Activity of Novel Amphiphilic Zinc(II) Phthalocyanines Bearing Oxyethylene-Rich Substituents

Three novel zinc(II) phthalocyanines substituted with one or two 3,4,5-tris(3,6,9-trioxadecoxy)benzoxy group(s) have been prepared and spectroscopically characterized. These compounds are highly soluble and remain nonaggregated in N,N-dimethylformamide. Upon excitation, they exhibit a relatively weak fluorescence emission and high efficiency to generate singlet oxygen compared with the unsubstituted zinc(II) phthalocyanine. These amphiphilic photosensitizers formulated with Cremophor EL are highly photocytotoxic against HT29 human colon adenocarcinoma and HepG2 human hepatocarcinoma cells. The mono-α-substituted analogue 4 is particularly potent with IC50 values as low as 0.02 μM. The higher photodynamic activity of this compound can be attributed to its lower aggregation tendency in the culture media as shown by absorption spectroscopy and higher cellular uptake as suggested by the stronger intracellular fluorescence, resulting in a higher efficiency to generate reactive oxygen species inside the cells

Come Rain and Shine? Exploring the Effects of Mobile Weather Applications on Users’ Movements

All Weather conditions affect human behaviors and the growing number of Mobile Weather Applications (MWAs) has amplified this effect. Yet, little is known about how human seek to actively control their behavior by appropriating mobile technology to anticipate changing weather conditions. Guided by Anticipatory Behavioral Control Theory (ABCT), this study endeavors to bride the abovementioned knowledge gap by investigating how the interface design and usage of MWAs would impact the relationship between abnormal weather conditions and users’ movement patterns. From analyzing panel data collected on the hourly movement trajectories of over 1.95 million anonymous mobile phone users over a 2-month period, we strive to shed light on the moderating influence of content representation and usage intensity of MWAs on the relationship between weather conditions and human behaviors