Miracle-dz/UniFAR-FTUs huggingface dataset:
Modeling the Formation of Topographic Asymmetry by Aspect‐Dependent Erosional Processes and Lateral Channel Migration

Some landscapes exhibit the intriguing characteristic that the steepness of hillslopes varies systematically with the direction they face, even where there is no bias introduced by bedrock structure. This topographic asymmetry has inspired numerous explanations. In the simplest scenario, insolation‐driven microclimatic differences lead to different erosion rates on opposing slopes and topographic asymmetry develops. Alternatively, lateral channel migration and the corresponding steepening of undercut slopes have also been suggested as a dominant cause of topographic asymmetry. To examine these proposed origins of asymmetric topography, we adapted a numerical landscape evolution model to include lateral channel migration as well as aspect‐induced variations in soil creep, regolith strength, and runoff. We compared the resulting topography and erosional response produced by each mechanism and found that the model with lateral channel migration produces unique signatures in erosion rates and the ridgetop Laplacian of elevation. To further investigate lateral channel migration, we developed a model of hillslope profile evolution in which sediment fluxes from opposing slopes control lateral channel migration rate and direction. We find that topographic asymmetry in this system can be self‐sustaining. All else being equal, we find that the aspect‐dependent models with variable regolith strength or runoff predict that less topographic asymmetry should develop as slope length decreases. These two models also predict that weaker asymmetry should develop as rock strength increases, whereas the lateral channel migration model predicts that greater rock strength should lead to weaker asymmetry only if lateral channel migration efficiency increases faster than fluvial incision efficiency.
A Detailed Description on Unsupervised Heterogeneous Anomaly Based Intrusion Detection Framework

Observing network traffic flow for anomalies is a common method in Intrusion Detection. More effort has been taken in utilizing the data mining and machine learning algorithms to construct anomaly based intrusion detection systems, but the dependency on the learned models that were built based on earlier network behaviour still exists, which restricts those methods in detecting new or unknown intrusions. Consequently, this investigation proposes a structure to identify an extensive variety of abnormalities by analysing heterogeneous logs, without utilizing either a prepared model of system transactions or the attributes of anomalies. To accomplish this, a current segment (clustering) has been used and a few new parts (filtering, aggregating and feature analysis) have been presented. Several logs from multiple sources are used as input and this data are processed by all the modules of the framework. As each segment is instrumented for a particular undertaking towards a definitive objective, the commitment of each segment towards abnormality recognition is estimated with various execution measurements. Ultimately, the framework is able to detect a broad range of intrusions exist in the logs without using either the attack knowledge or the traffic behavioural models. The result achieved shows the direction or pathway to design anomaly detectors that can utilize raw traffic logs collected from heterogeneous sources on the network monitored and correlate the events across the logs to detect intrusions.
Molecular hydrogen improves type 2 diabetes through inhibiting oxidative stress

The aim of the present study was to investigate the potential therapeutic effects of molecular hydrogen on type 2 diabetes mellitus (T2DM) in rats. Following maintenance on a high-fat diet for 4 weeks, a T2DM model was established using an injection of 30 mg/kg streptozotocin via the caudal vein into Sprague-Dawley rats. On day 0 and Day 80, the blood samples were obtained from each rat for the measurement of biochemical indicators including blood lipids, fasting blood glucose, hepatic glycogen, fasting serum insulin, insulin sensitivity index, insulin resistance index, serum superoxide dismutase (SOD) and serum malondialdehyde (MDA) using an automatic biochemical analyzer. The kidneys and pancreas tissues were harvested for HE staining and Western blot assay of toll-like receptor 4 (TLR4), myeloid differentiation primary response 88 (MyD88), phosphorylated (p)-p65, p65, p-IκB and IκB. The results showed that in rats with T2DM, molecular hydrogen treatment decreased fasting blood glucose levels, increased hepatic glycogen synthesis and improved insulin sensitivity. Treatment with molecular hydrogen also increased the production of SOD whilst decreasing the production of MDA. In addition, molecular hydrogen alleviated the pathological changes exhibited by pancreatic islets and kidney during T2DM. Mechanistically, molecular hydrogen decreased TLR4 and MyD88 expression levels whilst also decreasing p65 and NF-κB inhibitor phosphorylation. In conclusion, molecular hydrogen exerted therapeutic effects against T2DM by improving hyperglycemia and inhibiting oxidative stress through mechanisms that are associated with the TLR4/MyD88/NF-κB signaling pathway.
The Fashion Blogosphere: Success from the readers’ perspective

The role of blogs and bloggers as conduits of fashion information has strengthened through their growing popularity with fashion consumers. Convenience has been identified as a key reason why fashion consumers use the internet and social media, enabling them to quickly and easily find trend information, new products and retailer discounts. While research into blogs and blogging is growing little is given of how blog readers perceive and merit the success of fashion blogs. In this study we aim to promote a better understanding of the characteristics that fashion blog readers’ value as contributing factors of a successful fashion blog. This is achieved through an exploration of blog readers’ opinions and through the identification of key blogging trends focusing on female fashion bloggers and readers. The most significant measure of a blog’s success was found to be how relevant it is to its readers, the qualities of which are revealed in this article.
of regulatory motifs ISMARA : automated modeling of genomic signals as a democracy Material Supplemental

Material Supplemental http://genome.cshlp. org/content/suppl/2014/02/28/gr.169508. 113.DC2. html References http://genome.cshlp. org/content/24/5/869.full. html#ref-list-1 This article cites 108 articles, 38 of which can be accessed free at: Open Access Open Access option. Genome Research Freely available online through the License Commons Creative . http://creativecommons.org/licenses/by-nc/4.0/ License (Attribution-NonCommercial 4.0 International), as described at , is available under a Creative Commons Genome Research This article, published in
What Causes the Volatility of the Balancing Item

This paper analyzes the impacts of timing errors, capital flows and economic openness on the behavior of the balancing item. We choose Norway, Sweden, Philippines and South Africa as sample countries where the size of the balancing item is often excess the IMF's criterion of ‘smallness'. The empirical results show that the sources of the volatility of the balancing item are different among these four countries.
Dual-band antenna modification by using dual bad EBG structure for WLAN/WiMAX applications

In this paper, a U-slot antenna as represent of dual-band antenna is studied. This antenna covers the WLAN/WiMAX application with a moderate gain of 4.5 dBi. The antenna excites two modes of TM10 and TM20 and consequently with excitation of high order modes surface currents of antenna substrate increase. To overcome this drawback a dual-band electromagnetic bandgap (EBG) is offered and results of EBG unit cell is matched with the U-slot antenna operation bandwidth at two bands. Finally, arrange of unite cell array and antenna for two goals is investigated. As results prove, the combining antenna with EBG cells can solve the mutual coupling effect more than 20 dB and improve gain and bandwidth of antenna for about 3.5 dBi and 1% for each frequency band, respectively.
SURVEY AND SUMMARY RNA circularization strategies in vivo and in vitro

In the plenitude of naturally occurring RNAs, circular RNAs (circRNAs) and their biological role were underestimated for years. However, circRNAs are ubiquitous in all domains of life, including eukaryotes, archaea, bacteria and viruses, where they can fulfill diverse biological functions. Some of those functions, as for example playing a role in the life cycle of viral and viroid genomes or in the maturation of tRNA genes, have been elucidated; other putative functions still remain elusive. Due to the resistance to exonucleases, circRNAs are promising tools for in vivo application as aptamers, trans-cleaving ribozymes or siRNAs. How are circRNAs generated in vivo and what approaches do exist to produce ringshaped RNAs in vitro? In this review we illustrate the occurrence and mechanisms of RNA circularization in vivo, survey methods for the generation of circRNA in vitro and provide appropriate protocols.
Synthesis of 2H-furo[2,3-c]pyrazole ring systems through silver(I) ion-mediated ring-closure reaction

Fused pyrazole ring systems are common structural motifs of numerous pharmaceutically important compounds. Nevertheless, access to derivatives of the aromatic 2H-furo[2,3-c]pyrazole ring system is still quite limited, and their chemistry and functional properties remain largely underexplored. The current study investigates routes to construct this system from easily accessible starting materials using metal-catalyzed reactions. A simple and efficient procedure to access the 2H-furo[2,3-c]pyrazole ring system was developed by employing the silver(I) ion-mediated ring-closure reaction of 4-alkynyl-3-hydroxy-1-phenyl-1H-pyrazoles as a key step. The required intermediate hydroxyalkynyl substrates for this reaction were prepared by a Pd-catalyzed coupling of 4-iodo-1-phenyl-1H-pyrazol-3-ol with ethyne derivatives. The structures of the obtained target compounds were unequivocally confirmed by detailed 1H, 13C and 15N NMR spectroscopic experiments, HRMS and a single-crystal X-ray diffraction analyses. This silver(I)-mediated 5-endo-dig cyclization of readily available 4-alkynyl-3-hydroxy-1H-pyrazoles can be used as an efficient method to access many novel 2,5-disubstituted 2H-furo[2,3-c]pyrazoles.
CYP 1 B 1 mRNA inducibility due to benzo ( a ) pyrene is modified by the CYP 1 B 1 L 432 V gene polymorphism

Benzo(a)pyrene (BaP), a primary component of tobacco smoke, is activated by cytochrome P450 1B1 (CYP1B1). Smokers homozygous for the C-allele (*1/*1) at the CYP1B1 Leu432Val polymorphism have shown increased CYP1B1 expression, compared to smokers homozygous for the G-allele *3/*3. Since no difference has been shown in CYP1B1 expression between both genotypes in non-smokers, we assumed that the genetic impact is produced in combination with an exogenous induction (e.g. BaP). To confirm this theory and to quantify the effect, we induced human leucocytes with increasing BaP concentrations and determined CYP1B1 mRNA expression with real-time polymerase chain reaction (PCR). We incubated human leucocytes from 27 healthy donors with BaP concentrations ranging from 2.5 to 250 μM. We identified the CYP1B1 genotypes by melting curve analysis and assessed relative CYP1B1 mRNA expression using real-time PCR. Expression was related to β-2-microglobulin with the 2−ΔΔCT method. Inducibility of CYP1B1 mRNA by BaP was higher in leucocytes carrying the CYP1B1*1/*1 genotype than in leucocytes carrying the CYP1B1*3/*3 genotype (P = 0.012). We revealed significant differences, with BaP concentrations of 2.5 μM (P = 0.0094), 5 μM (P = 0.027), 10 μM (P = 0.0006), 25 μM (P = 0.0007) and 50 μM (P = 0.017). Homozygous carriers of the C-allele (*1/*1) at the CYP1B1 Leu432Val polymorphism show a higher response to environmental factors, such as carcinogenic BaP, than homozygous carriers of the G-allele *3/*3.
Title : Transcriptome response of high-and low-light adapted Prochlorococcus strains to changing iron availability Running title : Prochlorococcus response to iron stress 5 10 Contributors :

Prochlorococcus contributes significantly to ocean primary productivity. The link between primary productivity and iron in specific ocean regions is well established and iron-limitation of Prochlorococcus cell division rates in these regions has been demonstrated. However, the extent of ecotypic variation in iron metabolism among Prochlorococcus and the molecular basis for differences is not understood. Here, we examine the growth and transcriptional response of Prochlorococcus strains, MED4 and MIT9313, to changing iron concentrations. During steady-state, MIT9313 sustains growth at an order-of-magnitude lower iron concentration than MED4. To explore this difference, we measured the whole-genome transcriptional response of each strain to abrupt iron starvation and rescue. Only four of the 1159 orthologs of MED4 and MIT9313 were differentially-expressed in response to iron in both strains. However, in each strain, the expression of over a hundred additional genes changed, many of which are in labile genomic regions, suggesting a role for lateral gene transfer in establishing diversity of iron metabolism among Prochlorococcus. Furthermore, we found that MED4 lacks three genes near the iron-deficiency induced gene (idiA) that are present and induced by iron stress in MIT9313. These genes are interesting targets for studying the adaptation of natural Prochlorococcus assemblages to local iron conditions as they show more diversity than other genomic regions in environmental metagenomic databases. 25
Eurasian Cooling Linked to the Vertical Distribution of Arctic Warming

Observations show that deep Arctic winter warming, extending from surface to mid‐troposphere, has concurred with below‐average temperature over central Eurasia. Modeling studies focusing on the response to Arctic sea ice loss have shown Arctic surface warming but no consistent atmospheric changes at midlatitude. Using a large number of simulations from coupled and uncoupled climate models, we show that Eurasian below‐average temperatures are more frequent in winters with deep warming compared to shallow, near‐surface warming over the Barents‐Kara Seas. Dramatic weakening of the midlatitude jet stream and increase in Ural blocking frequency are more likely to occur in winters with deep Arctic warming. Deep warming is independent of sea ice forcing but follows increased poleward atmospheric energy and moisture advection from the North Atlantic to the Arctic, indicating that internal natural variability and not sea ice is the main driving forcing for deep Arctic warming‐cold Eurasia pattern in historical simulations.
Housing affordability: Is new local supply the key?

This paper seeks to predict the impact of future housing supply on the affordability of residential space in the United Kingdom, using quantitative model-based simulation methods. Our spatially disaggregated analysis focuses on the greater South East region, approximately within 1.5 hours commuting time from Central London. A dynamic spatial panel model is applied to account for observed temporal variations in property prices and housing affordability across districts. The dynamic structure of this model allows us to assess the scale and extent of knock-on effects of local supply shocks in one district on other districts in the region. These complex spatial effects have been largely ignored in local or regional housing market forecasting models to date. Applying this model, we are able to demonstrate that local house prices and affordability are not only determined by the underlying supply and demand conditions in the market in question, but also depend crucially on conditions in neighbouring housing markets whose properties can be considered close substitutes within a larger regional housing market. We also show that increasing housing supply in the most critical areas has little impact on (both local and regional) affordability, even if wages do not change in response to an increase in employment.
Minimum Architecture of SDN Tolerant to Failure of a Switch

Fault tolerance to a switch in SDN (Software Defined Network) requires implementation of redundancy. The article is devoted to research of some economical methods of entering of redundancy into SDN which allow to provide stability to failure of one switch. We will apply the method both to peer-to-peer networks, and to hierarchically organized peer-to-peer networks. It is proved that the constructed peer-to-peer SDN architecture concerning the number of switches is minimal. It is shown how to generalize results for a simple peer-to-peer network to a set of peer-to-peer networks.
Fully Convolutional Networks and Geographic Object-Based Image Analysis for the Classification of VHR Imagery

Land cover Classified maps obtained from deep learning methods such as Convolutional neural networks (CNNs) and fully convolutional networks (FCNs) usually have high classification accuracy but with the detailed structures of objects lost or smoothed. In this work, we develop a methodology based on fully convolutional networks (FCN) that is trained in an end-to-end fashion using aerial RGB images only as input. Skip connections are introduced into the FCN architecture to recover high spatial details from the lower convolutional layers. The experiments are conducted on the city of Goma in the Democratic Republic of Congo. We compare the results to a state-of-the art approach based on a semi-automatic Geographic object image-based analysis (GEOBIA) processing chain. State-of-the art classification accuracies are obtained by both methods whereby FCN and the best baseline method have an overall accuracy of 91.3% and 89.5% respectively. The maps have good visual quality and the use of an FCN skip architecture minimizes the rounded edges that is characteristic of FCN maps. Additional experiments are done to refine FCN classified maps using segments obtained from GEOBIA generated at different scale and minimum segment size. High OA of up to 91.5% is achieved accompanied with an improved edge delineation in the FCN maps, and future work will involve explicitly incorporating boundary information from the GEOBIA segmentation into the FCN pipeline in an end-to-end fashion. Finally, we observe that FCN has a lower computational cost than the standard patch-based CNN approach especially at inference.
Finite-dimensional predictor-based feedback stabilization of a 1D linear reaction-diffusion equation with boundary input delay

We consider a one-dimensional controlled reaction-diffusion equation, where the control acts on the boundary and is subject to a constant delay. Such a model is a paradigm for more general parabolic systems coupled with a transport equation. We prove that this is possible to stabilize (in H 1 norm) this process by means of an explicit predictor-based feedback control that is designed from a finite-dimensional subsystem. The implementation is very simple and efficient and is based on standard tools of pole-shifting. Our feedback acts on the system as a finite-dimensional predictor. We compare our approach with the backstepping method.
The effect of surge on riverine flood hazard and impact in deltas globally

Current global riverine flood risk studies assume a constant mean sea level boundary. In reality high sea levels can propagate up a river, impede high river discharge, thus leading to elevated water levels. Riverine flood risk in deltas may therefore be underestimated. This paper presents the first global scale assessment of the joint influence of riverine and coastal drivers of flooding in deltas. We show that if storm surge is ignored, flood depths are significantly underestimated for 9.3% of the expected annual population exposed to riverine flooding. The assessment is based on extreme water levels at 3433 river mouth locations as modeled by a state-of-the-art global river routing model, forced with a multi-model runoff ensemble and bounded by dynamic sea level conditions derived from a global tide and surge reanalysis. We first classified the drivers of riverine flooding at each location into four classes: surge-dominant, discharge-dominant, compound-dominant or insignificant. We then developed a model experiment to quantify the effect of surge on flood hazard and impacts. Drivers of riverine flooding are compound-dominant at 19.7% of the locations analyzed, discharge-dominant at 69.2%, and surge-dominant at 7.8%. Compared to locations with either surge- or discharge-dominant flood drivers, locations with compound-dominant flood drivers generally have larger surge extremes and are located in basins with faster discharge response and/or flat topography. Globally, surge exacerbates 1-in-10 years flood levels at 64.0% of the locations analyzed, with a mean increase of 11 cm. While this increase is generally larger at locations with compound- or surge-dominant flood drivers, flood levels also increase at locations with discharge-dominant flood drivers. This study underlines the importance of including dynamic downstream sea level boundaries in (global) riverine flood risk studies.
Audit Report Lag and Its Determinants

Audit report lag is an important issue because it can affect the timeliness of accounting information that is used by internal and external users for their decision making. This study aims to examine the influence of profitability, solvency, company size, and the reputation of public accounting firms on the audit report lag. We collected data from 40 Indonesian mining companies annual reports from 2013 to 2017. The hypotheses were tested by using multiple regression analysis. The results show that profitability and company size have significant negative impacts on audit report lag, but solvency and reputation public accounting firm have no effect. The results of this study can be taken into consideration for companies as well as possible so that they can submit financial reports in a timely manner. Keywords: profitability, solvency, company size, reputation public accounting firm, audit report lag
Economic Dispatch of Integrated Energy Systems With Robust Thermal Comfort Management

The heat and electricity integrated energy systems (HE-IESs) have a bright prospect in future energy systems owing to their excellent economic and environmental performance. Many uncertain factors in the HE-IESs, such as renewable energy sources, electrical load, and weather factors, threaten the secure and economical operation of systems as well as the thermal comfort of end-users. In this article, the uncertainties that affect the thermal comfort of end-users are modeled comprehensively, including building parameters, weather factors, and human behavior. Then, a two-stage adaptive robust economic dispatch (ARED) model with a robust thermal comfort management strategy is proposed for the operation of HE-IESs, where different policies are adopted to deal with multiple uncertainties based on their different properties. The ARED model is four-level programming with a static robust inner problem, making it computationally intractable. Hence, a sampling-based approximation method is proposed for the robust inner problem to convert the ARED model into a two-stage robust optimization with a linear recourse problem, and then the column-and-constraint generation method is used to solve it. Simulation results demonstrate the effectiveness of the proposed approach.