Miracle-dz/UniFAR-FTUs huggingface dataset:
Characterizing Speed and Scale of Cryptocurrency Discussion Spread on Reddit

Cryptocurrencies are a novel and disruptive technology that has prompted a new approach to how currencies work in the modern economy. As such, online discussions related to cryptocurrencies often go beyond posts about the technology and underlying architecture of the various coins, to subjective speculations of price fluctuations and predictions. Furthermore, online discussions, potentially driven by foreign adversaries, criminals or hackers, can have a significant impact on our economy and national security if spread at scale. This paper is the first to qualitatively measure and contrast discussion growth about three popular cryptocurrencies with key distinctions in motivation, usage, and implementation - Bitcoin, Ethereum, and Monero on Reddit. More specifically, we measure how discussions relevant to these coins spread in online social environments - how deep and how wide they go, how long they last, how many people they reach, etc. More importantly, we compare user behavior patterns between the focused community of the official coin subreddits and the general community across Reddit as a whole. Our Reddit sample covers three years of data between 2015 and 2018 and includes a time period of a record high Bitcoin price rise.1 Our results demonstrate that while the largest discussions on Reddit are focused on Bitcoin, posts about Monero (a cryptocurrency often used by criminals for illegal transactions on the Dark Web2) start discussions that are typically longer and wider. Bitcoin posts trigger subsequent discussion more immediately but Monero posts are more likely to trigger a longer lasting discussion. We find that moderately subjective posts across all three coins trigger larger, longer, and more viral discussion cascades within both focused and general communities on Reddit. Our analysis aims to bring the awareness to online discussion spread relevant to cryptocurrencies in addition to informing models for forecasting cryptocurrency price that rely on discussions in social media.
Detecting Areas of Potential High Prevalence of Chagas in Argentina

A map of potential prevalence of Chagas disease (ChD) with high spatial disaggregation is presented. It aims to detect areas outside the Gran Chaco ecoregion (hyperendemic for the ChD), characterized by high affinity with ChD and high health vulnerability. To quantify potential prevalence, we developed several indicators: an Affinity Index which quantifies the degree of linkage between endemic areas of ChD and the rest of the country. We also studied favorable habitability conditions for Triatoma infestans, looking for areas where the predominant materials of floors, roofs and internal ceilings favor the presence of the disease vector. We studied determinants of a more general nature that can be encompassed under the concept of Health Vulnerability Index. These determinants are associated with access to health providers and the socio-economic level of different segments of the population. Finally we constructed a Chagas Potential Prevalence Index (ChPPI) which combines the affinity index, the health vulnerability index, and the population density. We show and discuss the maps obtained. These maps are intended to assist public health specialists, decision makers of public health policies and public officials in the development of cost-effective strategies to improve access to diagnosis and treatment of ChD.
Nanoemulsion and Nanoliposome Based Strategies for Improving Anthocyanin Stability and Bioavailability

Background: Anthocyanins, a flavonoid class of water-soluble pigments, are reported to possess several biological activities, including antioxidant, anti-inflammatory, and anti-cancer. However, anthocyanins are highly susceptible to degradation in high pH, light, heat, and oxygen during processing and storage. Conventional microencapsulation techniques fail to provide stability to anthocyanins under physiological environments mainly because of their large particle size as well as low zeta potential and encapsulation efficiency. Methods: Nanotechnology provides novel strategies for preparing nanoformulations to enhance the physicochemical stability of anthocyanins. Nanoemulsion and nanoliposome are the two most commonly used nanosystems in pharmaceutical and food-related fields. In this review, an overview of various nanoemulsion and nanoliposome systems reported recently for enhancing stability, bioavailability, and bioactivity of anthocyanins is presented. Results: Anthocyanin nanoemulsions with different oil, water, surfactant, and cosurfactant ratios were prepared from extracts of mangosteen peel, purple sweet potato, cranberry, red cabbage, blueberry, jaboticaba peel, and acai berry and evaluated for their antioxidant activity, enhancement of physicochemical stability, topical skin application, and urinary tract infection. Likewise, unilamellar and multilamellar nanoliposomes were prepared using different types and levels of lecithin without or with cholesterol from anthocyanin standards and extracts of Hibiscus sabdariffa, mulberry, elderberry, black carrot, and pistachio green hull for the evaluation of physicochemical and oxidative stability, in vitro bioaccessibility, and melanogenic activity, as well as protective effects against diabetes mellitus and cataract. Conclusion: This review provides an insight into the current nanotechnology updates on enhancement of anthocyanin stability and biological activity.
Sliding Motions on SO(3), Sliding Subgroups

We propose a sliding surface for systems on the Lie group SO(3) ×ℝ3. The sliding surface is shown to be a Lie subgroup. The reduced-order dynamics along the sliding subgroup have an almost globally asymptotically stable equilibrium. The sliding surface is used to design a sliding-mode controller for the attitude control of rigid bodies. The closed-loop system is robust against matched disturbances and does not exhibit the undesired unwinding phenomenon.
No Warranty Express or Implied : Why do We Have so many Problems With the Computer Systems that Pervade our Lives ?

Computer systems, large and small, are everywhere. From the 100+ electronic control units in a modern car to mobile devices, to tablets and desktop computers, to petabyte databases that are mined for information, computers pervade our lives. When any factor in our lives becomes so pervasive, a range of problems will certainly follow ranging from basic frustration and inconvenience, to lost productivity, to losses due to using the devices apart from problems with the devices themselves, to loss of life. This article explores the unique role of computers in our lives from the perspective of their complexity, limits on our ability to ensure that systems are built without errors, tradeoffs inherent in the design of computer systems, and measures that can be taken to address these problems.
Efficient Hydrophobic Modification of Old Newspaper and Its Application in Paper Fiber Reinforced Composites

Paper fibers have gained broad attention in natural fiber reinforced composites in recent years. The specific problem in preparing paper fiber reinforced composites is that paper fibers easily become flocculent after pulverization, which increases difficulties during melt-compounding with polymer matrix and results in non-uniform dispersion of paper fibers in the matrix. In this study, old newspaper (ONP) was treated with a low dosage of gaseous methyltrichlorosilane (MTCS) to solve the flocculation. The modified ONP fibers were characterized by Scanning Electron Microscope (SEM), Fourier Transform Infrared Spectroscopy (FTIR), and Thermogravimetric Analysis (TG). Then the modified ONP fibers and high-density polyethylene (HDPE) were extruded and pelletized to prepare ONP/HDPE composites via injection molding. Maleic anhydride-grafted polyethylene (MAPE) was added to enhance the interfacial bonding performance with the ultimate purpose of improving the mechanical strength of the composites. The mechanical properties such as tensile, flexural, and impact strength and the water absorption properties of the composite were tested. The results showed that the formation of hydrogen bonding between ONP fibers was effectively prevented after MTCS treatment due to the reduction of exposed –OH groups at the fiber surface. Excessive dosage of MTCS led to severe fiber degradation and dramatically reduced the aspect ratio of ONP fibers. Composites prepared with ONP fibers modified with 4% (v/w) MTCS showed the best mechanical properties due to reduced polarity between the fibers and the matrix, and the relatively long aspect ratio of treated ONP fibers. The composite with or without MAPE showed satisfactory water resistance properties. MTCS was proven to be a cheap and efficient way to pretreat old newspaper for preparing paper fiber reinforced composites.
Atom Responding Machine for Dialog Generation

Recently, improving the relevance and diversity of dialogue system has attracted wide attention. For a post x, the corresponding response y is usually diverse in the real-world corpus, while the conventional encoder-decoder model tends to output the high-frequency (safe but trivial) responses and thus is difficult to handle the large number of responding styles. To address these issues, we propose the Atom Responding Machine (ARM), which is based on a proposed encoder-composer-decoder network trained by a teacher-student framework. To enrich the generated responses, ARM introduces a large number of molecule-mechanisms as various responding styles, which are conducted by taking different combinations from a few atom-mechanisms. In other words, even a little of atom-mechanisms can make a mickle of molecule-mechanisms. The experiments demonstrate diversity and quality of the responses generated by ARM. We also present generating process to show underlying interpretability for the result.
Towards Efficient Implementation of Realizability Checking for Reactive System Specifications

Realizability checking is used to detect flaws in reactive system specifications that are difficult for humans to find. However, these checks are computationally costly. To address this problem, researchers have studied efficient methods for implementing such checking procedures. In this paper, we propose a new implementation method of realizability checking. While symbolic approaches have been adopted in many previous methods, we take a partially symbolic approach, in which binary decision diagrams (BDDs) are used partially. We developed a prototype realizability checker based on our method, and experimentally compared it to tools based on other implementation methods. Our prototype was efficient in comparison to the other tools.
A Constellation of Horrors: Analysis and Visualization of the #Cuéntalo Movement

In this work, we analyze content and structure of the Twitter trending topic #cuentalo with the purpose of providing a visualization of the movement. A supervised learning methodology is used to train the classifying algorithms with hand-labeled observations. The methodology allows us to classify each tweet according to its role in the movement.
Endogenous carcinogenesis: molecular oncology into the twenty-first century--presidential address.

In this paper I will consider an aspect of carcinogenesis that needs further in-depth study because it could be a major cause of human cancers. I am referring to the Damoclean possibility that certain normal endogenous cellular processes are inher ently mutagenic and that this intrinsic mutagenesis is a signif icant factor in the etiology and pathogenesis of some human cancers. Moreover, I will prospectively consider the impact of molecular biology on cancer research. Our ability to determine the composition of genes at the molecular and atomic levels is likely to change radically many facets of cancer research. New techniques in molecular biology not only have highlighted critical deficiencies in our understanding of the differences between normal and cancer cells but also have lent us confidence that new and deeper, more fundamental insights will soon be within our grasp. I am pleased to report that our Association has taken new initiatives to incorporate recent advances in molecular biology into the purview of cancer researchers and thereby will be a leading facilitator of the transport of molecular oncology into the 21st century.
Self-Justification Processes Related to Bullying Among Brazilian Adolescents: A Mixed Methods Study

This study aims to investigate the associations between bullying and moral disengagement in a Brazilian sample, using a mixed method design. Two-thousand three hundred and thirty-four adolescents (11–19 years; 42.9% girls) answered self-report measures on bullying and moral disengagement in response to bullying situations. Fifty-five participants were randomly selected and interviewed on their experiences on bullying at school. Results allowed to identify specific mechanisms of moral disengagement associated with bullying behavior among Brazilian adolescents. Qualitative analysis highlighted how moral disengagement mechanisms were spontaneously used by the adolescents to explain both the bullying and the bystander behaviors. Findings support the relevance of moral disengagement mechanisms in explaining bullying behaviors. The value of addressing these mechanisms when designing anti-bullying interventions is discussed.
Mobile Health Applications for Pediatric Care: Review and Comparison

Background Despite the surge in mobile health (mHealth) applications (apps) about pediatric care in commercial app stores, to our knowledge, reviews of the quality of such apps are lacking. Consequently, it is a great challenge for health care professionals (HCPs) to identify appropriate and reliable mHealth apps for delivering health care services. Thus, we performed a structured review of the extant literature about mHealth apps in pediatric care and quality assessment of selected apps found in commercial app stores. Methods A review and comparison of mHealth apps in pediatric care found in Google’s Play Store (Android system) and Apple’s App Store (iOS system) were performed. For the structured review of the available literature, Google Scholar, PubMed, IEEE Xplore Digital Library, and Science Direct online databases were used for the literature search. The assessment criteria used for comparison included requirement for Internet connection, size of application, information on disease, diagnostic tools, medical calculator, information on disease treatments, dosage recommendations, and drug interaction checker. Results Fifty mHealth apps for general pediatric care and 8 mHealth apps for specific pediatric diseases were discussed in the literature. Of the 90 mHealth apps we reviewed, 27 that fulfilled the study criteria were selected for quality assessment. Medscape, Skyscape, and iGuideline scored the highest (score=7), while PediaBP scored the lowest (score=3). Conclusions Medscape, Skyscape, and iGuideline are the most comprehensive mHealth apps for HCPs as quick references for pediatric care. More studies about mHealth apps in pediatric care are warranted to ensure the quality and reliability of mHealth apps.
Carbohydrate Mouth Rinse Decreases Time to Complete a Simulated Cycling Time Trial

Rinsing carbohydrate solutions in the mouth can produce positive effects on the central nervous system via mouth/tongue receptors, ultimately increasing cycling performance. However, previous investigations on this topic have used complex carbohydrate solutions and time trials on a cyclergometer to complete a set amount of work. The purpose of the present study was to examine the effects of carbohydrate mouth rinsing on physical performance by using a commercially available drink during a cycling time trial with varying slopes. In a double-blind, placebo-controlled and randomized manner, 16 well-trained cyclists (37.6 ± 3.5 years; 76.9 ± 7.9 kg) performed two simulated cycling time trial (25.3 km) with their own bikes on a 3D virtual trainer. In one occasion, participants mouth-rinsed a 6.4% carbohydrate mixed solution for 5 s each 12.5% of total completion of the trial; in other occasion participants rinsed with a taste-matched placebo with 0.0% of carbohydrate. During the trials, participants were instructed to perform as fast as possible at a self-chosen pace while time, cycling power output and ratings of perceived exertion were obtained during the trials. When compared to the placebo, carbohydrate mouth rinse decreased the time employed to complete the distance (2,960 ± 412 vs. 2,888 ± 396 s; P = 0.04, respectively), while it increased overall cycling power (222 ± 51 vs. 231 ± 46 w, P = 0.04) and cycling power during the climbing sections (238 ± 46 vs. 248 ± 47 w, P = 0.03). Carbohydrate mouth rinse also increased the rating of perceived exertion at the end of the trial (18.3 ± 1.7 vs. 18.9 ± 1.1 arbitrary units, P = 0.04). In summary, mouth rinsing with a commercially available carbohydrate drink might be considered as an effective strategy to increase physical performance during cycling time trials. However, due to the performance downsides of breaking the aero-position or interrupting the breathing pattern for rising during a time trial, carbohydrate mouth rinse protocols might be more suitable for high-intensity training sessions, particularly those sessions intentionally performed with low carbohydrate intake.
Finding Diachronic Like‐Minded Users

User communities in social networks are usually identified by considering explicit structural social connections between users. While such communities can reveal important information about their members such as family or friendship ties and geographical proximity, just to name a few, they do not necessarily succeed at pulling like‐minded users that share the same interests together. Therefore, researchers have explored the topical similarity of social content to build like‐minded communities of users. In this article, following the topic‐based approaches, we are interested in identifying communities of users that share similar topical interests with similar temporal behavior. More specifically, we tackle the problem of identifying temporal (diachronic) topic‐based communities, i.e., communities of users who have a similar temporal inclination toward emerging topics. To do so, we utilize multivariate time series analysis to model the contributions of each user toward emerging topics. Further, our modeling is completely agnostic to the underlying topic detection method. We extract topics of interest by employing seminal topic detection methods; one graph‐based and two latent Dirichlet allocation‐based methods. Through our experiments on Twitter data, we demonstrate the effectiveness of our proposed temporal topic‐based community detection method in the context of news recommendation, user prediction, and document timestamp prediction applications, compared with the nontemporal as well as the state‐of‐the‐art temporal approaches.
Severe Fever With Thrombocytopenia Syndrome Virus-Induced Macrophage Differentiation Is Regulated by miR-146

Severe fever with thrombocytopenia syndrome (SFTS) is an emerging hemorrhagic fever with a high mortality rate in humans, which is caused by SFTS virus (SFTSV), a novel phlebovirus in the Bunyaviridae family, is tick borne and endemic in Eastern Asia. Previous study found that SFTSV can infect and replicate in macrophages in vivo and in vitro. However, the role of macrophages in virus replication and the potential pathogenic mechanisms of SFTSV in macrophage remain unclear. In this study, we provided evidence that the SFTSV infection drove macrophage differentiation skewed to M2 phenotype, facilitated virus shedding, and resulted in viral spread. We showed evidence that miR-146a and b were significantly upregulated in macrophages during the SFTSV infection, driving the differentiation of macrophages into M2 cells by targeting STAT1. Further analysis revealed that the elevated miR-146b but not miR-146a was responsible for IL-10 stimulation. We also found that SFTSV increased endogenous miR-146b-induced differentiation of macrophages into M2 cells mediated by viral non-structural protein (NSs). The M2 skewed differentiation of macrophages may have important implication to the pathogenesis of SFTS.
Microbial evaluation of selected fresh produce obtained at retail markets.

The microbial quality of five types of fresh produce obtained at the retail level was determined by standard quantitative techniques. These techniques included aerobic plate count (APC), total coliform counts, Escherichia coli counts, and yeast and mold counts. Three different methods were used to determine total coliform counts, which consisted of MacConkey agar plate counts, Colicomplete most probable number counts, and Petrifilm E. coli (EC) plate counts. The mean APCs for sprouts, lettuce, celery, cauliflower, and broccoli were 8.7, 8.6, 7.5, 7.4. and 6.3 log10 CFU/g, respectively. MacConkey agar counts indicated that 89 to 96% of the APCs consisted of gram-negative bacteria. Yeast and mold counts were in a range expected of fresh produce. Fresh produce was also analyzed for human pathogens. Samples were analyzed for Staphylococcus spp. , Bacillus spp. , Salmonella spp. , Listeria spp. , and Campylobacter spp. One isolate of Staphylococcus was found to be enterotoxigenic, and one species of Bacillus was also toxigenic. Neither Salmonella spp. nor Campylobacter spp. were detected in any of the produce samples. A variety of Listeria spp. , including Listeria monocytogenes, were found in fresh produce.
Sparse Signal Recovery via Improved Sparse Adaptive Matching Pursuit Algorithm

The accurate reconstruction of a signal within a reasonable period is the key process that enables the application of compressive sensing in large-scale image transmission. The sparsity adaptive matching pursuit (SAMP) algorithm does not need prior knowledge on signal sparsity and has high reconstruction accuracy but has low reconstruction efficiency. To overcome the low reconstruction efficiency, we propose the use of the fast segmentation sparsity adaptive matching pursuit (FSSAMP) algorithm, where the value of K estimated in each iteration increases in a nonlinear manner instead of undergoing linear growth. This form can reduce the number of iterations by accurate signal sparsity degree evaluation. In addition, we use signal segmentation strategies in the proposed algorithm to improve the algorithm accuracy. Experimental results demonstrated that the FSSAMP algorithm has more stable reconstruction performance and higher reconstruction accuracy than the SAMP algorithm.
Epitaph or Breaking News? Analyzing and Predicting the Stability of Knowledge Base Properties

Knowledge bases (KBs) contain huge amounts of facts about entities, their properties, and relations between them. They are thus the key asset in any intelligent system for tasks such as structured search and question answering. However, due to dynamics in the real world, properties and relations change over time, and stored knowledge may become outdated. While KB information evolves steadily, there is no information whether or not a KB property might be subject to change with high probability or whether it is likely to be stable. Systems exploiting KB information, however, could benefit a lot if they had access to this kind of information. In this paper, we analyze and predict the stability of KB entries, which allows to accompany entries with stability scores. Our predictive model exploits entity-based features and learns through historic data. A particular challenge to determine stability scores is that KB entries are not only added or modified due to real-world changes but also to reduce the incompleteness of KBs in general. Nevertheless, our evaluation of sample properties demonstrates the effectiveness of our method for predicting the one-year stability of KB properties.