Miracle-dz/UniFAR-FTUs huggingface dataset:
Self-organization, the cascade model, and natural hazards

We consider the frequency-size statistics of two natural hazards, forest fires and landslides. Both appear to satisfy power-law (fractal) distributions to a good approximation under a wide variety of conditions. Two simple cellular-automata models have been proposed as analogs for this observed behavior, the forest fire model for forest fires and the sand pile model for landslides. The behavior of these models can be understood in terms of a self-similar inverse cascade. For the forest fire model the cascade consists of the coalescence of clusters of trees; for the sand pile model the cascade consists of the coalescence of metastable regions.
Type Directives and Type Graphs in Elm

We introduce type graphs into Elm in order to improve type error messages for infinite types, and integrate type qualifiers (for type classes a la Haskell) and Elm's row polymorphism into type graphs. We also discuss how specialized type rules and siblings can be used to achieve domain-specific type error diagnosis in the context of Elm.
Indication of active overthrust faulting along the Holocene‐Wisconsin transition in the marginal zone of Jakobshavn Isbræ

[1] A zone of highly irregular ice motion has been detected within the ice sheet adjacent to Jakobshavn Isbrae, a fast moving ice stream in West Greenland. Two tilt sensors in different boreholes and frozen into the ice show angle variations of up to 0.1° and 0.3° within a 1200 s interval. The amplitude of these flutter oscillations increases toward the transition from Holocene to Wisconsin ice at 682 m depth, 150 m above bedrock. All other tilt sensors above and below show low background noise. A numerical model confirms that the stress configuration is exceptional in the neighborhood of the ice stream. Stress transfer from the ice stream to the margins causes an extra forcing of the basal ice at the drill site. Several possible explanations for the observed flutter oscillations are given, the most likely being dynamic rupture events or stick-slip motion along the Holocene-Wisconsin transition. If true, this would correspond to an active overthrust fault with very high loading rates.
A structural gap in Dpo4 supports mutagenic bypass of a major benzo[a]pyrene dG adduct in DNA through template misalignment

Erroneous replication of lesions in DNA by DNA polymerases leads to elevated mutagenesis. To understand the molecular basis of DNA damage-induced mutagenesis, we have determined the x-ray structures of the Y-family polymerase, Dpo4, in complex with a DNA substrate containing a bulky DNA lesion and incoming nucleotides. The DNA lesion is derived from an environmentally widespread carcinogenic polycyclic aromatic hydrocarbon, benzo[a]pyrene (BP). The potent carcinogen BP is metabolized to diol epoxides that form covalent adducts with cellular DNA. In the present study, the major BP diol epoxide adduct in DNA, BP-N2-deoxyguanosine (BP–dG), was placed at a template–primer junction. Three ternary complexes reveal replication blockage, extension past a mismatched lesion, and a −1 frameshift mutation. In the productive structures, the bulky adduct is flipped/looped out of the DNA helix into a structural gap between the little finger and core domains. Sequestering of the hydrophobic BP adduct in this new substrate-binding site permits the DNA to exhibit normal geometry for primer extension. Extrusion of the lesion by template misalignment allows the base 5′ to the adduct to serve as the template, resulting in a −1 frameshift. Subsequent strand realignment produces a mismatched base opposite the lesion. These structural observations, in combination with replication and mutagenesis data, suggest a model in which the additional substrate-binding site stabilizes the extrahelical nucleotide for lesion bypass and generation of base substitutions and −1 frameshift mutations.
NSL-KDD: Cyberattack Detection in IoT Utilizing Machine Learning Approaches

The Internet of Things (IoT) is a new technology that makes it easy and advantageous to share information with other gadgets across wirelessly or web networks. Yet, due to changes and advancements in the IoT environment, IoT systems are more vulnerable to cyberattacks, which may result in nefarious incursions. The effects of these incursions may result in harm to the physical and the business. It becomes more difficult for the conventional system to effectively deal with these attacks as the number of network attacks that are feasible rises. A number of machine learning (ML) approaches, including Logistic Regression (LR), Decision Tree (DT), K-nearest Neighbor (KNN), Random Forest(RF), and the Support Vector Machine(SVM), have been employed to predict and visualize attack threats in order to address the aforementioned security problems. Employing the NSL-KDD dataset, the mentioned ML approaches have been compared with regard to evaluation measures, including accuracy, precision, F1-score, and recall. The results show that the RF model has the highest accuracy rate of 99.7%, while the accuracy rates for the other models, including LR, DT, KNN, and SVM, are 88.5%, 95%, 99.3%, and 97.9% respectively.
Local B cells and IgE production in the oesophageal mucosa in eosinophilic oesophagitis

Background: Eosinophilic oesophagitis (EO) is an emerging yet increasingly prevalent disorder characterised by a dense and selective eosinophilic infiltration of the oesophageal wall. While EO is considered an atopic disease primarily triggered by food antigens, disparities between standard allergen testing and clinical responses to exclusion diets suggest the participation of distinct antigen-specific immunoglobulin E (IgE) in the pathophysiology of EO. Aim: To find evidence for a local IgE response. Methods: Endoscopic biopsies of the distal oesophagus of atopic and non-atopic EO and control individuals (CTL) were processed for immunohistochemistry and immunofluorescence to assess the presence of B cells, mast cells, and IgE-bearing cells. Oesophageal RNA was analysed for the expression of genes involved in B cell activation, class switch recombination to IgE and IgE production, including germline transcripts (GLTs), activation-induced cytidine deaminase (AID), IgE heavy chain (Cε) and mature IgE mRNA using polymerase chain reaction and microarray analysis. Results: Regardless of atopy, EO showed increased density of B cells (p<0.05) and of IgE-bounded mast cells compared to CTL. Both EO and CTL expressed μGLT, εGLT, γ4GLT, AID, Cε and IgE mRNA. However, the frequency of expression of total GLTs (p = 0.002), εGLT (p = 0.024), and Cε (p = 0.0003) was significantly higher in EO than in CTL, independent of the atopic status. Conclusion: These results support the heretofore unproven occurrence of both local immunoglobulin class switching to IgE and IgE production in the oesophageal mucosa of EO patients. Sensitisation and activation of mast cells involving local IgE may therefore critically contribute to disease pathogenesis.
A Linux Implementation Validation of Track-Aligned Extents and Track-Aligned RAIDs

Through clean-slate implementation of two storage optimizations--track-aligned extents and track-aligned RAIDs--this paper shows the values of independent validations. The experience revealed many unanticipated disk and storage data path behaviors as potential roadblocks for wide deployment of these optimizations, and also identified implementation issues to retrofit these concepts to legacy data paths.
Using Properties of the Amazon Graph to Better Understand Reviews

According to a 2010 paper published by PowerReviews, a e-tailing consulting company, 63% of shoppers consistently read reviews prior to making a purchase decision while 33% of that total spend at least half an hour reading reviews for a product; thus online reviews of a product have now become a strong factor in determining the sales of a particular product. Perhaps no retailer is more influenced by online ratings than Amazon.com, the world‘s largest online retailer, and one of the pioneering companies of online feedback scores. Amazon.com also has the world‘s largest collection of online reviews [1], which further emphasizes the importance of product reviews for the online retailer. However, there has been significant controversy surrounding the accuracy and origins of many of these reviews. A 2011 article by Daily Mail, for instance, reports that that many manufacturers have started hiring companies to post fake reviews on Amazon.com in an attempt to increase the manufacturer‘s credibility while at the same time, defaming competition [6]. Trevor Pinch, a professor of sociology at Cornell, along with Web entrepreneur Filip Kesler published a paper further strengthening the assumption that there is personal bias involved in many of the reviews, by uncovering the fact that around 85% of Amazon‘s top 1000 reviewers receive free products from publishers, agents, authors, and manufacturers [2]. The helpfulness rating of the reviews themselves have also been found to be bias. [3] demonstrates that user helpfulness ratings oftentimes do not directly reflect the content quality of the review itself. [4] elaborates on this notion by illustrating the fact that users rate the helpfulness of a review based upon their own personal preference towards the item. This project aims to accomplish two tasks: to be able to predict future Amazon ratings given current rating data, and to adjust the current star rating scheme to better reflect the true quality of the item. Predicting the future rating of a product is valuable because it gives both manufacturers and customers the opportunity to know the consensus perception of the product at an earlier time. Being able to establish when the future rating can be predicted with a high degree of confidence is also desired since many customers will not purchase a product until they are confident that the consensus view of the product is a favorable one. In fact, [1] found that 72% of consumers find user product reviews to be a “very/extremely” important factor when it comes to selecting and purchasing a product. Because a vast majority of users rely upon Amazon.com reviews to determine the quality of a product, attempting to produce more accurate ratings by accounting for the biases mentioned above is also an important task. The star rating likely represents the first opportunity most users have to pass judgement on an item they find when browsing Amazon, and the star rating also factors into other components which can influence the sale of a product, such as when that product appears in the search results.
Large Scale Network Analysis with Interactive Visualisation

This paper proposes a new interactive visualization for analyzing large hierarchical structures and networks. The technique combines of different graph layout methods with a layout refinement process, an interactive navigation mechanism and clustering algorithms. The integration of these components makes it flexible in dealing with a variety of graph and hierarchical structures. Interactive exploration is enabled with chain-context view. We aim to provide user with an effective mechanism for understanding of the nature of various networks. This could lead to the discovering and revealing of the hidden structures and relationships among elements as well as relationships associated with the elements.
TOPIC-BASED WEB SITE SUMMARIZATION

Purpose Summarization of an entire Web site with diverse content may lead to a summary heavily biased towards the site’s dominant topics. This paper presents a novel topic-based framework to address this problem. Design/methodology/approach A two-stage framework is proposed. The first stage identifies the main topics covered in a Web site via clustering and the second stage summarizes each topic separately. The proposed system is evaluated by a user study, and compared with the single-topic summarization approach. Findings The user study demonstrates that the clustering-summarization approach statistically significantly outperforms the plain summarization approach in the multi-topic Web site summarization task. Text-based clustering based on selecting features with high variance over Web pages is reliable, Outgoing links are useful if a rich set of cross links is available. Research limitations/implications More sophisticated clustering methods than those used in this study are worth investigating. The proposed method should be tested on web content that is less structured than organizational web sites, for example blogs. Practical implications The proposed summarization framework can be applied to the effective organization of search engine results and faceted or topical browsing of large Web sites. Originality/value Several key components are integrated for web site summarization for the first time, including feature selection and link analysis, key phrase and key sentence extraction. Insight into the contributions of links and content to topic-based summarization was gained. A classification approach is used to minimize the number of parameters. Article Type: Research paper
Analyses of HAdV-4 vac and HAdV-7 vac , Two Human Adenovirus ( HAdV ) Strains That Constituted Original Prophylaxis against HAdV-Related Acute Respiratory Disease , a Reemerging Epidemic Disease

Bioinformatics and Computational Biology Program, School of Computational Sciences, George Mason University, 10900 University Boulevard, MSN 5B3, Manassas, Virginia 20110; HQ USAF Surgeon General Office, Directorate of Modernization (SGR), and Epidemic Outbreak Surveillance (EOS) Consortium, 5201 Leesburg Pike, Suite 1401, Falls Church, Virginia 22041; Division of Microbiology, Department of Infectious and Parasitic Diseases Pathology, Armed Forces Institute of Pathology, 5300 Georgia Avenue, N.W. , Washington D.C. 20306; and Department of Defense Center for Deployment Health Research, Naval Health Research Center, San Diego, California 92186
Crystal structure of the oligomerization domain of NSP4 from rotavirus reveals a core metal-binding site.

During the maturation of rotaviral particles, non-structural protein 4 (NSP4) plays a critical role in the translocation of the immature capsid into the lumen of the endoplasmic reticulum. Full-length NSP4 and a 22 amino acid peptide (NSP4(114-135)) derived from this protein have been shown to induce diarrhea in young mice in an age-dependent manner, and may therefore be the agent responsible for rotavirally-induced symptoms. We have determined the crystal structure of the oligomerization domain of NSP4 which spans residues 95 to 137 (NSP4(95-137)). NSP4(95-137) self-associates into a parallel, tetrameric coiled-coil, with the hydrophobic core interrupted by three polar layers occupying a and d-heptad positions. Side-chains from two consecutive polar layers, consisting of four Gln123 and two of the four Glu120 residues, coordinate a divalent cation. Two independent structures built from MAD-phased data indicated the presence of a strontium and calcium ion bound at this site, respectively. This metal-binding site appears to play an important role in stabilizing the homo-tetramer, which has implications for the engagement of NSP4 as an enterotoxin.
Utility Optimal Scheduling in Degree-Limited Satellite Networks

In this paper, we consider the problem of flow control together with power allocation to antennas on satellite with arbitrary link states, so as to maximize the utility function while stabilizing the network. Inspired by Lyapunov optimization method, a Degree-Limited Scheduling Algorithm (DLSA) is proposed with a control parameter V, which requires no stochastic knowledge of link state. Discussion about implementation is carried out about the complexity of DLSA and several approximation methods to reduce complexity. Analyze shows DLSA stabilizes the network and the gap between utility function under DLSA and the optimal value is arbitrarily close to zero on the order of O(1/V). Simulation results verify DLSA on a simple network.
Müllerian inhibiting substance regulates its receptor/SMAD signaling and causes mesenchymal transition of the coelomic epithelial cells early in Müllerian duct regression

Examination of Müllerian inhibiting substance (MIS) signaling in the rat in vivo and in vitro revealed novel developmental stage- and tissue-specific events that contributed to a window of MIS responsiveness in Müllerian duct regression. The MIS type II receptor (MISRII)-expressing cells are initially present in the coelomic epithelium of both male and female urogenital ridges, and then migrate into the mesenchyme surrounding the male Müllerian duct under the influence of MIS. Expression of the genes encoding MIS type I receptors, Alk2 and Alk3, is also spatiotemporally controlled; Alk2 expression appears earlier and increases predominantly in the coelomic epithelium, whereas Alk3 expression appears later and is restricted to the mesenchyme, suggesting sequential roles in Müllerian duct regression. MIS induces expression of Alk2, Alk3 and Smad8, but downregulates Smad5 in the urogenital ridge. Alk2-specific small interfering RNA (siRNA) blocks both the transition of MISRII expression from the coelomic epithelium to the mesenchyme and Müllerian duct regression in organ culture. Müllerian duct regression can also be inhibited or accelerated by siRNA targeting Smad8 and Smad5, respectively. Thus, the early action of MIS is to initiate an epithelial-to-mesenchymal transition of MISRII-expressing cells and to specify the components of the receptor/SMAD signaling pathway by differentially regulating their expression.
Towards Energy-Aware Resource Scheduling to Maximize Reliability in Cloud Computing Systems

Cloud computing has become increasingly popular due to deployment of cloud solutions that will enable enterprises to cost reduction and more operational flexibility. Reliability is a key metric for assessing performance in such systems. Fault tolerance methods are extensively used to enhance reliability in Cloud Computing Systems (CCS). However, these methods impose extra hardware and/or software cost. Proper resource allocation is an alternative approach which can significantly improve system reliability without any extra overhead. On the other hand, contemplating reliability irrespective of energy consumption and Quality of Service (QoS) requirements is not desirable in CCSs. In this paper, an analytical model to analyze system reliability besides energy consumption and QoS requirements is introduced. Based on the proposed model, a new online resource allocation algorithm to find the right compromise between system reliability and energy consumption while satisfying QoS requirements is suggested. The algorithm is a new swarm intelligence technique based on imperialist competition which elaborately combines the strengths of some well-known meta-heuristic algorithms with an effective fast local search. A wide range of simulation results, based on real data, clearly demonstrate high efficiency of the proposed algorithm.
Integrating high dimensional bi-directional parsing models for gene mention tagging

Motivation: Tagging gene and gene product mentions in scientific text is an important initial step of literature mining. In this article, we describe in detail our gene mention tagger participated in BioCreative 2 challenge and analyze what contributes to its good performance. Our tagger is based on the conditional random fields model (CRF), the most prevailing method for the gene mention tagging task in BioCreative 2. Our tagger is interesting because it accomplished the highest F-scores among CRF-based methods and second over all. Moreover, we obtained our results by mostly applying open source packages, making it easy to duplicate our results. Results: We first describe in detail how we developed our CRF-based tagger. We designed a very high dimensional feature set that includes most of information that may be relevant. We trained bi-directional CRF models with the same set of features, one applies forward parsing and the other backward, and integrated two models based on the output scores and dictionary filtering. One of the most prominent factors that contributes to the good performance of our tagger is the integration of an additional backward parsing model. However, from the definition of CRF, it appears that a CRF model is symmetric and bi-directional parsing models will produce the same results. We show that due to different feature settings, a CRF model can be asymmetric and the feature setting for our tagger in BioCreative 2 not only produces different results but also gives backward parsing models slight but constant advantage over forward parsing model. To fully explore the potential of integrating bi-directional parsing models, we applied different asymmetric feature settings to generate many bi-directional parsing models and integrate them based on the output scores. Experimental results show that this integrated model can achieve even higher F-score solely based on the training corpus for gene mention tagging. Availability: Data sets, programs and an on-line service of our gene mention tagger can be accessed at http://aiia.iis.sinica.edu.tw/biocreative2.htm Contact: chunnan@iis.sinica.edu.tw
GENERAL ASPECTS OF INTERDISCIPLINARY RESEARCH IN EXPERIMENTAL HUMAN BIOLOGY.

General Aspects of Interdisciplinary Research in ExC. KERESzTESY and DR. JACKSON W. FosTER. The perimental Human Biology: DR. JOSEF BROZEK and Effect of Atropine Sulfate on the Course of InfluPROFESSOR ANCEL KEYs . 507 enza Virus Infection: DR. A. H. WHEELER and DR. W. J. NUNGESTER. Growth of Corallorhiza MacuObituary: lata: DR. D. T. MACDOUGAL and PRoFEssOR H. S. I. Huang: DR. ARNOLD GESELL. Recent Deaths 512 REzIn. Guanidino Arsenicals: PROFESSOR MARSTON Scientific Events: T. BOGERT and PROFESSOR WILLIAM C. STRICKLER 522 The Proposed British Aeronautical College; The Scientifc Aparatus and Laboratory Methods: Junior Academy of Science of Wisconsi&n; FellowA P . ships of the Textile Research Institute of PrinceA Standard Penicillnase Preparation: DR. A. J. ton University; The Foundation for the Study of LIEBMANN, E. B. MCQUARRIE and DR. D. PERLCyles; Awards of the Aunmericon Society of MeSTEIN. Penicillin Treatment of Crown Gall: PROChncale Engineoers 513 FESSOR J. G. BROWN and ALICE M. BOYLE . 527 chanical ngineer . Scientific Notes and News.55 0. 515 Science N w s 1
Classification of wheat cultivar by digital image analysis

Digital image analysis was used to develop a pattern recognition algorithm to classify individual kernels of seven Chinese spring wheat cultivars grown at 4 locations. Totally, 20 morphological parameters and 12 color parameters were extracted. Three hundred kernels per sample were used as the training data set to develop identification model, and another 200 kernels were used as the test set. For the test set, the classification accuracy of wheat cultivars was 100% in each growing location. Except for Xinkehan 9 with 98.3%, the correct discrimination of the training set of collective samples is 100% for wheat cultivar. For the test set, the correct discrimination of Longmai 26 and Qingchun 566 were 97.5% and 95.0%, the others is 100%. For the origin of wheat grains, the classification of Gansu, Ningxia, Xinjiang and Heilongjiang were 88.6%, 92.9%, 72.9% and 95.7%, respectively. The results show that it is feasible to identify and classify wheat cultivar (grains) using digital image analysis.