Exploring the Public Perception in Social Big Data: An Investigation in Mars Recall Scandal

Social media has become a popular platform of interpersonal communication in which users can search for news and convey real-time information. Researching into social big data, such as Twitter, can be an effective way to identify public opinions and feelings in risk emergence, as it provides rich sources of data for opinion mining and sentiment analysis. This study aims to investigate and analyse the public perception towards the Mars and Snickers product recall scandal. The study proposes a comprehensive data analysis framework, and utilises the dataset formed of 10,930 Twitter messages over the span of 10-day following the product recall announcement made by Mars Inc., to gauge public attitudes and opinions. The study finds that the overall attitude of Twitter users towards the scandal was negative, and Snickers were the most mentioned product in the 10-day periods after the announcement of the recall. The data analysis highlights that the Tweet diffusion (retweeting) has positive associations with the number of followers and the use of hashtags, hence companies should pay more attention to users who have a large number of followers, as their tweets will be read by a great number of other Twitter users. The findings suggest effective methods for practitioners in crisis management (e.g., how to use social media to disseminate information). The study also presents a progressive tweet-mining framework that can serve as a tool in crisis management to classify the tweet topics, identify and analyse the sentiment and comprehend the changes of the public attitudes

Linear Depth QFT over IBM Heavy-hex Architecture

Compiling a given quantum algorithm into a target hardware architecture is a challenging optimization problem. The compiler must take into consideration the coupling graph of physical qubits and the gate operation dependencies. The existing noise in hardware architectures requires the compilation to use as few running cycles as possible. Existing approaches include using SAT solver or heuristics to complete the mapping but these may cause the issue of either long compilation time (e.g., timeout after hours) or suboptimal compilation results in terms of running cycles (e.g., exponentially increasing number of total cycles). In this paper, we propose an efficient mapping approach for Quantum Fourier Transformation (QFT) circuits over the existing IBM heavy-hex architecture. Such proposal first of all turns the architecture into a structure consisting of a straight line with dangling qubits, and then do the mapping over this generated structure recursively. The calculation shows that there is a linear depth upper bound for the time complexity of these structures and for a special case where there is 1 dangling qubit in every 5 qubits, the time complexity is 5N+O(1). All these results are better than state of the art methods

Fatty acid transport protein 4 (FATP4) prevents light-induced degeneration of cone and rod photoreceptors by inhibiting RPE65 isomerase

Although rhodopsin is essential for sensing light for vision, it also mediates light-induced apoptosis of photoreceptors in mouse. RPE65, which catalyzes isomerization of all-trans retinyl fatty acid esters to 11-cis-retinol (11cROL) in the visual cycle, controls the rhodopsin regeneration rate and photoreceptor susceptibility to light-induced degeneration. Mutations in RPE65 have been linked to blindness in affected children. Despite such importance, the mechanism that regulates RPE65 function remains unclear. Through unbiased expression screening of a bovine retinal pigment epithelium (RPE) cDNA library, we have identified elongation of very long-chain fatty acids-like 1 (ELOVL1) and fatty acid transport protein 4 (FATP4), which each have very long-chain fatty acid acyl-CoA synthetase (VLCFA-ACS) activity, as negative regulators of RPE65. We found that the VLCFA derivative lignoceroyl (C24:0)-CoA inhibited synthesis of 11cROL, whereas palmitoyl (C16:0)-CoA promoted synthesis of 11cROL. We further found that competition of FATP4 with RPE65 for the substrate of RPE65 was also involved in the mechanisms by which FATP4 inhibits synthesis of 11cROL. FATP4 was predominantly expressed in RPE, and the FATP4-deficient RPE showed significantly higher isomerase activity. Consistent with these results, the regeneration rate of 11-cis-retinaldehyde and the recovery rate for rod light sensitivity were faster in FATP4-deficient mice than wild-type mice. Moreover, FATP4-deficient mice displayed increased accumulation of the cytotoxic all-trans retinaldehyde and hypersusceptibility to light-induced photoreceptor degeneration. Our findings demonstrate that ELOVL1, FATP4, and their products comprise the regulatory elements of RPE65 and play important roles in protecting photoreceptors from degeneration induced by light damage

The next widespread bamboo flowering poses a massive risk to the giant panda

The IUCN Red List has downgraded several species from “endangered” to “vulnerable” that still have largely unknown extinction risks. We consider one of those downgraded species, the giant panda, a bamboo specialist. Massive bamboo flowering could be a natural disaster for giant pandas. Using scenario analysis, we explored possible impacts of the next bamboo flowering in the Qinling and Minshan Mountains that are home to most giant pandas. Our results showed that the Qinling Mountains could experience large-scale bamboo flowering leading to a high risk of widespread food shortages for the giant pandas by 2020. The Minshan Mountains could similarly experience a large-scale bamboo flowering with a high risk for giant pandas between 2020 and 2030 without suitable alternative habitat in the surrounding areas. These scenarios highlight thus-far unforeseen dangers of conserving giant pandas in a fragmented habitat. We recommend advance measures to protect giant panda from severe population crashes when flowering happens. This study also suggests the need to anticipate and manage long-term risks to other downgraded species

Data Poisoning Attacks and Defenses to Crowdsourcing Systems

A key challenge of big data analytics is how to collect a large volume of (labeled) data. Crowdsourcing aims to address this challenge via aggregating and estimating high-quality data (e.g., sentiment label for text) from pervasive clients/users. Existing studies on crowdsourcing focus on designing new methods to improve the aggregated data quality from unreliable/noisy clients. However, the security aspects of such crowdsourcing systems remain under-explored to date. We aim to bridge this gap in this work. Specifically, we show that crowdsourcing is vulnerable to data poisoning attacks, in which malicious clients provide carefully crafted data to corrupt the aggregated data. We formulate our proposed data poisoning attacks as an optimization problem that maximizes the error of the aggregated data. Our evaluation results on one synthetic and two real-world benchmark datasets demonstrate that the proposed attacks can substantially increase the estimation errors of the aggregated data. We also propose two defenses to reduce the impact of malicious clients. Our empirical results show that the proposed defenses can substantially reduce the estimation errors of the data poisoning attacks.This proceeding is published as Minghong Fang, Minghao Sun, Qi Li, Neil Zhenqiang Gong, Jin Tian, and Jia Liu. 2021. Data Poisoning Attacks and Defenses to Crowdsourcing Systems. In Proceedings of the Web Conference 2021 (WWW '21). Association for Computing Machinery, New York, NY, USA, 969–980. https://doi.org/10.1145/3442381.3450066. © 2021 IW3C2 (International World Wide Web Conference Committee), under Creative Commons CC-BY 4.0 License

Ang II (Angiotensin II) Conversion to Angiotensin-(1-7) in the Circulation Is POP (Prolyloligopeptidase)-Dependent and ACE2 (Angiotensin-Converting Enzyme 2)-Independent

The Ang II (Angiotensin II)-Angiotensin-(1-7) axis of the Renin Angiotensin System encompasses 3 enzymes that form Angiotensin-(1-7) [Ang-(1-7)] directly from Ang II: ACE2 (angiotensin-converting enzyme 2), PRCP (prolylcarboxypeptidase), and POP (prolyloligopeptidase). We investigated their relative contribution to Ang-(1-7) formation in vivo and also ex vivo in serum, lungs, and kidneys using models of genetic ablation coupled with pharmacological inhibitors. In wild-type (WT) mice, infusion of Ang II resulted in a rapid increase of plasma Ang-(1-7). In ACE2−/−/PRCP−/− mice, Ang II infusion resulted in a similar increase in Ang-(1-7) as in WT (563±48 versus 537±70 fmol/mL, respectively), showing that the bulk of Ang-(1-7) formation in circulation is essentially independent of ACE2 and PRCP. By contrast, a POP inhibitor, Z-Pro-Prolinal reduced the rise in plasma Ang-(1-7) after infusing Ang II to control WT mice. In POP−/− mice, the increase in Ang-(1-7) was also blunted as compared with WT mice (309±46 and 472±28 fmol/mL, respectively P=0.01), and moreover, the rate of recovery from acute Ang II-induced hypertension was delayed (P=0.016). In ex vivo studies, POP inhibition with ZZP reduced Ang-(1-7) formation from Ang II markedly in serum and in lung lysates. By contrast, in kidney lysates, the absence of ACE2, but not POP, obliterated Ang-(1-7) formation from added Ang II. We conclude that POP is the main enzyme responsible for Ang II conversion to Ang-(1-7) in the circulation and in the lungs, whereas Ang-(1-7) formation in the kidney is mainly ACE2-dependent.Peer reviewe

The First Data Release of the Beijing-Arizona Sky Survey

The Beijing-Arizona Sky Survey (BASS) is a new wide-field legacy imaging survey in the northern Galactic cap using the 2.3m Bok telescope. The survey will cover about 5400 deg$^2$ in the $g$ and $r$ bands, and the expected 5$\sigma$ depths (corrected for the Galactic extinction) in the two bands are 24.0 and 23.4 mag, respectively. BASS started observations in January 2015, and has completed about 41% of the whole area as of July 2016. The first data release contains both calibrated images and photometric catalogs obtained in 2015 and 2016. The depths of single-epoch images in the two bands are 23.4 and 22.9 mag, and the full depths of three epochs are about 24.1 and 23.5 mag, respectively.Comment: 16 pages, published by A

Secrets of RLHF in Large Language Models Part I: PPO

Large language models (LLMs) have formulated a blueprint for the advancement of artificial general intelligence. Its primary objective is to function as a human-centric (helpful, honest, and harmless) assistant. Alignment with humans assumes paramount significance, and reinforcement learning with human feedback (RLHF) emerges as the pivotal technological paradigm underpinning this pursuit. Current technical routes usually include \textbf{reward models} to measure human preferences, \textbf{Proximal Policy Optimization} (PPO) to optimize policy model outputs, and \textbf{process supervision} to improve step-by-step reasoning capabilities. However, due to the challenges of reward design, environment interaction, and agent training, coupled with huge trial and error cost of large language models, there is a significant barrier for AI researchers to motivate the development of technical alignment and safe landing of LLMs. The stable training of RLHF has still been a puzzle. In the first report, we dissect the framework of RLHF, re-evaluate the inner workings of PPO, and explore how the parts comprising PPO algorithms impact policy agent training. We identify policy constraints being the key factor for the effective implementation of the PPO algorithm. Therefore, we explore the PPO-max, an advanced version of PPO algorithm, to efficiently improve the training stability of the policy model. Based on our main results, we perform a comprehensive analysis of RLHF abilities compared with SFT models and ChatGPT. The absence of open-source implementations has posed significant challenges to the investigation of LLMs alignment. Therefore, we are eager to release technical reports, reward models and PPO code

Evolution of Immune and Stromal Cell States and Ecotypes During Gastric Adenocarcinoma Progression

Understanding tumor microenvironment (TME) reprogramming in gastric adenocarcinoma (GAC) progression may uncover novel therapeutic targets. Here, we performed single-cell profiling of precancerous lesions, localized and metastatic GACs, identifying alterations in TME cell states and compositions as GAC progresses. Abundant IgA+ plasma cells exist in the premalignant microenvironment, whereas immunosuppressive myeloid and stromal subsets dominate late-stage GACs. We identified six TME ecotypes (EC1–6). EC1 is exclusive to blood, while EC4, EC5, and EC2 are highly enriched in uninvolved tissues, premalignant lesions, and metastases, respectively. EC3 and EC6, two distinct ecotypes in primary GACs, associate with histopathological and genomic characteristics, and prognosis. Extensive stromal remodeling occurs in GAC progression. High SDC2 expression in cancer-associated fibroblasts (CAFs) is linked to aggressive phenotypes and poor survival, and SDC2 overexpression in CAFs contributes to tumor growth. Our study provides a high-resolution GAC TME atlas and underscores potential targets for further investigation