Pyramid: Enhancing Selectivity in Big Data Protection with Count Featurization

Protecting vast quantities of data poses a daunting challenge for the growing number of organizations that collect, stockpile, and monetize it. The ability to distinguish data that is actually needed from data collected "just in case" would help these organizations to limit the latter's exposure to attack. A natural approach might be to monitor data use and retain only the working-set of in-use data in accessible storage; unused data can be evicted to a highly protected store. However, many of today's big data applications rely on machine learning (ML) workloads that are periodically retrained by accessing, and thus exposing to attack, the entire data store. Training set minimization methods, such as count featurization, are often used to limit the data needed to train ML workloads to improve performance or scalability. We present Pyramid, a limited-exposure data management system that builds upon count featurization to enhance data protection. As such, Pyramid uniquely introduces both the idea and proof-of-concept for leveraging training set minimization methods to instill rigor and selectivity into big data management. We integrated Pyramid into Spark Velox, a framework for ML-based targeting and personalization. We evaluate it on three applications and show that Pyramid approaches state-of-the-art models while training on less than 1% of the raw data

Investigating Thermal Comfort and User Behaviors in Outdoor Spaces: A Seasonal and Spatial Perspective

Numerous studies have examined the correlation between the number of attendants in a given outdoor environment and thermal indices to understand how the environmental planning has an impact on the users. However, extensive observations should be conducted to examine the detailed static and dynamic behavior patterns of users. We conducted dynamic observations at a stepped plaza to perform on-site measurements of the physical environment and observations of users behaviors, including their resting positions, movements, and stay durations. The results indicated that more people rested on the steps during the cool season than hot season. Compared to neutral temperatures, people demonstrated higher heat tolerance to the hot season. The results indicated that more than 75% of users preferred to remain in shaded areas and stayed longer than in the sunlight. The people tended to engage in static activities in environments that exhibit sufficient shading. The shaded areas were conducive to static activities as the summer grew hotter. The results verified that the people of Taiwan would avoid sunlight and desire shaded spaces based on their previous climate experiences and expectations, which can serve as a reference for outdoor space design to improve the usability and quality of open urban spaces

Simulation analysis of manipulating light propagation through turbid Media

We model light propagation through turbid media by employing the pseudospectral time-domain (PSTD) simulation technique. With specific amplitude and phase, light can be manipulated to propagate through turbid media via multiple scattering. By exploiting the flexibility of the PSTD simulation, we analyze factors that contribute to enhancing light penetration. Specific research findings suggest that it is possible to propagate light with specific amplitude/phase. The reported simulation analysis enables quantitative analyses of directing light through turbid media. Please click Additional Files below to see the full abstract

Use of Fomepizole in Pediatric Methanol Exposure: The First Case Report in Taiwan and a Literature Review

Methanol poisoning is rare in the pediatric population, but a delay in diagnosis and intervention may cause severe morbidity and mortality. The current therapy for methanol poisoning is ethanol or fomepizole, which acts as a competitive inhibitor of hepatic alcohol dehydrogenase to inhibit the production of toxic metabolites derived from the oxidation of methanol. However, clinical experience in pediatric methanol poisoning is limited, and the safety profiles of the antidotes have not been established in children, especially in Asian populations. This is the first case to describe the use of fomepizole in a child with methanol exposure in Taiwan

DEXON: A Highly Scalable, Decentralized DAG-Based Consensus Algorithm

A blockchain system is a replicated state machine that must be fault tolerant. When designing a blockchain system, there is usually a trade-off between decentralization, scalability, and security. In this paper, we propose a novel blockchain system, DEXON, which achieves high scalability while remaining decentralized and robust in the real-world environment. We have two main contributions. First, we present a highly scalable sharding framework for blockchain. This framework takes an arbitrary number of single chains and transforms them into the \textit{blocklattice} data structure, enabling \textit{high scalability} and \textit{low transaction confirmation latency} with asymptotically optimal communication overhead. Second, we propose a single-chain protocol based on our novel verifiable random function and a new Byzantine agreement that achieves high decentralization and low latency

Determination of Nucleopolyhedrovirus’ Taxonomic Position

To date , over 78 genomes of nucleopolyhedroviruses (NPVs) have been sequenced and deposited in NCBI. How to define a new virus from the infected larvae in the field is usually the first question. Two NPV strains, which were isolated from casuarina moth (L. xylina) and golden birdwing larvae (Troides aeacus), respectively, displayed the same question. Due to the identity of polyhedrin (polh) sequences of these two isolates to that of Lymantria dispar MNPV and Bombyx mori NPV, they are named LdMNPV-like virus and TraeNPV, provisionally. To further clarify the relationships of LdMNPV-like virus and TraeNPV to closely related NPVs, Kimura 2-parameter (K-2-P) analysis was performed. Apparently, the results of K-2-P analysis that showed LdMNPV-like virus is an LdMNPV isolate, while TraeNPV had an ambiguous relationship to BmNPV. Otherwise, MaviNPV, which is a mini-AcMNPV, also exhibited a different story by K-2-P analysis. Since K-2-P analysis could not cover all species determination issues, therefore, TraeNPV needs to be sequenced for defining its taxonomic position. For this purpose, different genomic sequencing technologies and bioinformatic analysis approaches will be discussed. We anticipated that these applications will help to exam nucleotide information of unknown species and give an insight and facilitate to this issue