How Private Are Commonly-Used Voting Rules?

Differential privacy has been widely applied to provide privacy guarantees by adding random noise to the function output. However, it inevitably fails in many high-stakes voting scenarios, where voting rules are required to be deterministic. In this work, we present the first framework for answering the question: "How private are commonly-used voting rules?" Our answers are two-fold. First, we show that deterministic voting rules provide sufficient privacy in the sense of distributional differential privacy (DDP). We show that assuming the adversarial observer has uncertainty about individual votes, even publishing the histogram of votes achieves good DDP. Second, we introduce the notion of exact privacy to compare the privacy preserved in various commonly-studied voting rules, and obtain dichotomy theorems of exact DDP within a large subset of voting rules called generalized scoring rules

On the Stochastic Gradient Descent and Inverse Variance-flatness Relation in Artificial Neural Networks

Stochastic gradient descent (SGD), a widely used algorithm in deep-learning neural networks has attracted continuing studies for the theoretical principles behind its success. A recent work uncovered a generic inverse variance-flatness (IVF) relation between the variance of neural weights and the landscape flatness of loss function near solutions under SGD [Feng & Tu, PNAS 118,0027 (2021)]. To investigate this seemly violation of statistical principle, we deploy a stochastic decomposition to analyze the dynamical properties of SGD. The method constructs the true "energy" function which can be used by Boltzmann distribution. The new energy differs from the usual cost function and explains the IVF relation under SGD. We further verify the scaling relation identified in Feng's work. Our approach may bridge the gap between the classical statistical mechanics and the emerging discipline of artificial intelligence, with potential for better algorithm to the latter

A perspective on algal biogas

Algae are suggested as a biomass source with significant growth rates, which may be cultivated in the ocean (seaweed) or on marginal land (microalgae). Biogas is suggested as a beneficial route to sustainable energy; however the scientific literature on algal biogas is relatively sparse. This report comprises a review of the literature and provides a state of the art in algal biogas and is aimed at an audience of academics and energy policy makers. It was produced by IEA Bioenergy Task 37 which addresses the challenges related to the economic and environmental sustainability of biogas production and utilisation.JRC.F.8-Sustainable Transpor

Differential Privacy for Eye-Tracking Data

As large eye-tracking datasets are created, data privacy is a pressing concern for the eye-tracking community. De-identifying data does not guarantee privacy because multiple datasets can be linked for inferences. A common belief is that aggregating individuals' data into composite representations such as heatmaps protects the individual. However, we analytically examine the privacy of (noise-free) heatmaps and show that they do not guarantee privacy. We further propose two noise mechanisms that guarantee privacy and analyze their privacy-utility tradeoff. Analysis reveals that our Gaussian noise mechanism is an elegant solution to preserve privacy for heatmaps. Our results have implications for interdisciplinary research to create differentially private mechanisms for eye tracking

5-Sulfanyl­idene-2H,5H-1,3-dithiolo[4,5-d][1,3]dithiol-2-one

The title mol­ecule, C4OS5, is essentially planar, with an r.m.s. deviation of 0.032 (3) Å. All the C—S single bonds are shorter than the standard Csp 3—S single-bond length, showing the π-conjugated nature of the molecule. In the crystal, molecules lie parallel to one another and pack in columns along the a axis. Short inter­molecular S⋯S contacts [3.314 (3), 3.482 (2) and 3.501 (2) Å] are observed between the columns. The angle between the two mol­ecular dipole moments in the unit cell is 39.3 (1)° and the macro-polarization vector is along the [1 0 − 1.41] direction. As a result of the high polarization and π-conjugation of the structure, the crystalline powder exhibits a second harmonic generating intensity, which is as strong as that of the urea standard powder crystals, when irradiated by a 1053 nm laser beam. The diffraction space of the crystal showed a nonmerohedral twinning

Microscopic Investigation of a Copper Molten Mark by Optical Microscopy (OM) and Atomic Force Microscopy (AFM)

AbstractA wide variety of physical and chemical detecting methods have been proposed for discriminating between and electric arc bead that caused a fire, versus one that was caused by the fire itself. The simplest proposed method claims that examination of the molten marks in a bead under a microscope will suffice to make the distinction. Generally, copper molten marks of the bead are examined by using optical (OM) and scanning electron microscopy (SEM). In this paper, OM and AFM were employed to investigate a molten mark formed in laboratory. AFM observation reveals that AFM could be an auxiliary method to investigate the copper molten mark formed in the fire in order to confirm the reasons of the fire

Comparison of pre-treatments to reduce salinity and enhance biomethane yields of Laminaria digitata harvested in different seasons

Pre-treatment can enhance anaerobic digestion of seaweed; however, seasonal variation in the biochemical composition of seaweed has a significant impact on the pre-treatment effect. In this study, various pre-treatments were employed for the brown seaweed Laminaria digitata harvested in March (with high ash content and low carbon to nitrogen (C:N) ratio) and September (with low ash content and high C:N ratio). Washing of L. digitata harvested in March with hot water (defined as 40 °C) removed 54% of the ash and improved the volatile solids (VS) content by 31% leading to an improved biomethane yield of 282 L CH4 kg VS−1. This pre-treatment affected a 16% increase in biodegradability, reduced salt accumulation in the digestate by 54%, and increased specific methane yield per wet weight by 25%. This level of effect was not noted for seaweed harvested in September, when the biodegradability is higher

Assessment of continuous fermentative hydrogen and methane co-production using macro- and micro-algae with increasing organic loading rate

A two-stage continuous fermentative hydrogen and methane co-production using macro-algae (Laminaria digitata) and micro-algae (Arthrospira platensis) at a C/N ratio of 20 was established. The hydraulic retention time (HRT) of first-stage H2 reactor was 4 days. The highest specific hydrogen yield of 55.3 mL/g volatile solids (VS) was obtained at an organic loading rate (OLR) of 6.0 gVS/L/d. In the second-stage CH4 reactor at a short HRT of 12 days, a specific methane yield of 245.0 mL/gVS was achieved at a corresponding OLR of 2.0 gVS/L/d. At these loading rates, the two-stage continuous system offered process stability and effected an energy yield of 9.4 kJ/gVS, equivalent to 77.7% of that in an idealised batch system. However, further increases in OLR led to reduced hydrogen and methane yields in both reactors. The process was compared to a one-stage anaerobic co-digestion of algal mixtures at an HRT of 16 days. A remarkably high salinity level of 13.3 g/kg was recorded and volatile fatty acid accumulations were encountered in the one-stage CH4 reactor. The two-stage system offered better performances in both energy return and process stability. The gross energy potential of the advanced gaseous biofuels from this algal mixture may reach 213 GJ/ha/yr