Miracle-dz/UniFAR-FTUs huggingface dataset:
Structural and Physiological Analyses of the Alkanesulphonate-Binding Protein (SsuA) of the Citrus Pathogen Xanthomonas citri

Background The uptake of sulphur-containing compounds plays a pivotal role in the physiology of bacteria that live in aerobic soils where organosulfur compounds such as sulphonates and sulphate esters represent more than 95% of the available sulphur. Until now, no information has been available on the uptake of sulphonates by bacterial plant pathogens, particularly those of the Xanthomonas genus, which encompasses several pathogenic species. In the present study, we characterised the alkanesulphonate uptake system (Ssu) of Xanthomonas axonopodis pv. citri 306 strain (X. citri), the etiological agent of citrus canker. Methodology/Principal Findings A single operon-like gene cluster (ssuEDACB) that encodes both the sulphur uptake system and enzymes involved in desulphurisation was detected in the genomes of X. citri and of the closely related species. We characterised X. citri SsuA protein, a periplasmic alkanesulphonate-binding protein that, together with SsuC and SsuB, defines the alkanesulphonate uptake system. The crystal structure of SsuA bound to MOPS, MES and HEPES, which is herein described for the first time, provides evidence for the importance of a conserved dipole in sulphate group coordination, identifies specific amino acids interacting with the sulphate group and shows the presence of a rather large binding pocket that explains the rather wide range of molecules recognised by the protein. Isolation of an isogenic ssuA-knockout derivative of the X. citri 306 strain showed that disruption of alkanesulphonate uptake affects both xanthan gum production and generation of canker lesions in sweet orange leaves. Conclusions/Significance The present study unravels unique structural and functional features of the X. citri SsuA protein and provides the first experimental evidence that an ABC uptake system affects the virulence of this phytopathogen.
RMBase: a resource for decoding the landscape of RNA modifications from high-throughput sequencing data

Although more than 100 different types of RNA modifications have been characterized across all living organisms, surprisingly little is known about the modified positions and their functions. Recently, various high-throughput modification sequencing methods have been developed to identify diverse post-transcriptional modifications of RNA molecules. In this study, we developed a novel resource, RMBase (RNA Modification Base, http://mirlab.sysu.edu.cn/rmbase/), to decode the genome-wide landscape of RNA modifications identified from high-throughput modification data generated by 18 independent studies. The current release of RMBase includes ∼9500 pseudouridine (Ψ) modifications generated from Pseudo-seq and CeU-seq sequencing data, ∼1000 5-methylcytosines (m5C) predicted from Aza-IP data, ∼124 200 N6-Methyladenosine (m6A) modifications discovered from m6A-seq and ∼1210 2′-O-methylations (2′-O-Me) identified from RiboMeth-seq data and public resources. Moreover, RMBase provides a comprehensive listing of other experimentally supported types of RNA modifications by integrating various resources. It provides web interfaces to show thousands of relationships between RNA modification sites and microRNA target sites. It can also be used to illustrate the disease-related SNPs residing in the modification sites/regions. RMBase provides a genome browser and a web-based modTool to query, annotate and visualize various RNA modifications. This database will help expand our understanding of potential functions of RNA modifications.
Reliability modeling of large fault-tolerant systems

A cluster-based ultrareliable architecture is presented, offering synchronization and system functionality comparable to that of fully connected systems, with reduced system overhead. A reliability model considering the distribution of concurrent faults across the system clusters is shown to increase the accuracy of reliability and system fault-tolerance estimates. The hybrid fault model, which classifies faults based on their behavior, further improves reliability estimates and enhances the fault handling capability of each cluster. Linear growth in cluster reliability with respect to cluster size is possible, as are refinements in the convergence and consistency algorithms for synchronization. <<ETX>>
A relativistic model of the radio jets in NGC 315

We apply our intrinsically symmetrical, decelerating relativistic jet model to deep VLA imaging of the inner ±70arcsec of the giant low-luminosity radio galaxy NGC315. An optimized model accurately fits the data in both total intensity and linear polarization. We infer that the velocity, emissivity and field structure in NGC315 are very similar to those of the other low-luminosity sources we have modelled, but that all of the physical scales are larger by a factor of about 5. We derive an inclination to the line of sight of 38 ◦ ± 2 ◦ for the jets. Where they first brighten, their on-axis velocity is β = v/c � 0.9. They decelerate to β � 0.4 between 8 and 18kpc from the nucleus and the velocity thereafter remains constant. The speed at the edge of the jet is �0.6 of the on-axis value where it is best constrained, but the transverse velocity profile may deviate systematically from the Gaussian form we assume. The proper emissivity profile is split into three power-law regions separated by shorter transition zones. In the first of these, at �3kpc (the flaring point) the jets expand rapidly at constant emissivity, leading to a large increase in the observed brightness on the approaching side. At �10kpc, the emissivity drops abruptly by a factor of 2. Where the jets are well resolved their rest-frame emission is centre-brightened. The magnetic field is modelled as random on small scales but anisotropic and we rule out a globally ordered helical configuration. To a first approximation, the field evolves from a mixture of longitudinal and toroidal components to predominantly toroidal, but it also shows variations in structure along and across the jets, with a significant radial component in places. Simple adiabatic models fail to fit the emissivity variations.
Vehicle localization with low cost radar sensors

Autonomous vehicles rely on GPS aided by motion sensors to localize globally within the road network. However, not all driving surfaces have satellite visibility. Therefore, it is important to augment these systems with localization based on environmental sensing such as cameras, lidar and radar in order to increase reliability and robustness. In this work we look at using radar for localization. Radar sensors are available in compact format devices well suited to automotive applications. Past work on localization using radar in automotive applications has been based on careful sensor modeling and Sequential Monte Carlo, (Particle) filtering. In this work we investigate the use of the Iterative Closest Point, ICP, algorithm together with an Extended Kalman filter, EKF, for localizing a vehicle equipped with automotive grade radars. Experiments using data acquired on public roads shows that this computationally simpler approach yields sufficiently accurate results on par with more complex methods.
Social Ties and Adolescent Sleep Disruption

Teens tend go to bed later, get less sleep, and report more daytime sleepiness. Medical research emphasizes biological determinants of teens’ disrupted sleep (i.e., the timing of puberty and resultant drops in melatonin), rarely or inadequately considering youths’ social ties as a determinant of sleep behaviors. Sociologists recognize how social ties affect health behaviors but have generally neglected sleep, especially among teens. Drawing on a sample of 974 teens from the Study of Early Child Care and Youth Development, this study controls for developmental and social relational factors to predict changes in youths’ sleep patterns between 12 and 15 years of age. In general, social relational factors outperform developmental factors in determining youths’ sleep patterns, particularly pointing to the importance of parental, peer, and school ties in promoting healthy sleep behaviors. The implications of these findings for further research are briefly discussed.
Crime warning system using image and sound processing

This paper presents a surveillance system which alerts when controversy or an intruder is detected by using CCTV. The system takes advantage of sound signal processing to identify fighting and image processing to detect an intruder, then will notify and sent a signal to the system administer when an event occurs. The result shows that the energy of sound signal during fighting is higher than when in normal situation and the change pixel is increased when there is an intruder. According to the result, this concept is applied to CCTV system in order to avoid human fatigue leading to the error to work quality after working with the monitor for long hours.
Création de Vocabulaires Visuels Efficaces pour la Catégorisation d'Images

Nous proposons dans cet article une methode de construction automatique de vocabulaires visuels. Le vocabulaire visuel est obtenu par quantification de descripteurs locaux des images. Les vocabulaires visuels produits sont utilises pour construire automatiquement des representations discriminantes des objets presents dans les images. Nous decrivons une application de ces techniques a la categorisation d'images par sacs de primitives (bags of features) et montrons que les resultats obtenus sont tres superieurs a ceux obtenus par les methodes concurrentes.
Identification of conserved secondary structures and expansion segments in enod40 RNAs reveals new enod40 homologues in plants

enod40 is a plant gene that participates in the regulation of symbiotic interaction between leguminous plants and bacteria or fungi. Furthermore, it has been suggested to play a general role in non-symbiotic plant development. Although enod40 seems to have multiple functions, being present in many land plants, the molecular mechanisms of its activity are unclear; they may be determined though, by short peptides and/or RNA structures encoded in the enod40 genes. We utilized conserved RNA structures in enod40 sequences to search nucleotide sequence databases and identified a number of new enod40 homologues in plant species that belong to known, but also, to yet unknown enod40-containing plant families. RNA secondary structure predictions and comparative sequence analysis of enod40 RNAs allowed us to determine the most conserved structural features, present in all known enod40 genes. Remarkably, the topology and evolution of one of the conserved structural domains are similar to those of the expansion segments found in structural RNAs such as rRNAs, RNase P and SRP RNAs. Surprisingly, the enod40 RNA structural elements are much more stronger conserved than the encoded peptides. This finding suggests that some general functions of enod40 gene could be determined by the encoded RNA structure, whereas short peptides may be responsible for more diverse functions found only in certain plant families.
Information Embedding with Distortion Side Information

We use the distortion side information (DSI) framework to study the gains in information embedding when the encoder exploits sensitivity of the source samples. Our study for the Gaussian source model extends the dirty paper coding result by Costa to the case of a weighted power constraint with the weights only known to the transmitter. A coding scheme based on fixed codebook variable-partition codes is presented for this problem. We also present another coding scheme that exploits the knowledge of DSI and is robust against intentional attacks. Finally, we study a related problem of Wyner-Ziv coding with reliability side information (RSI) at the decoder. This latter setup illustrates that fixed codebook variable-partition codes could also be fundamental in systems that rely on conventional distortion measures
Wine microbiology is driven by vineyard and winery anthropogenic factors

The effects of different anthropic activities (vineyard: phytosanitary protection; winery: pressing and sulfiting) on the fungal populations of grape berries were studied. The global diversity of fungal populations (moulds and yeasts) was performed by pyrosequencing. The anthropic activities studied modified fungal diversity. Thus, a decrease in biodiversity was measured for three successive vintages for the grapes of the plot cultivated with Organic protection compared to plots treated with Conventional and Ecophyto protections. The fungal populations were then considerably modified by the pressing‐clarification step. The addition of sulfur dioxide also modified population dynamics and favoured the domination of the species Saccharomyces cerevisiae during fermentation. The non‐targeted chemical analysis of musts and wines by FT‐ICR‐MS showed that the wines could be discriminated at the end of alcoholic fermentation as a function of adding SO2 or not, but also and above all as a function of phytosanitary protection, regardless of whether these fermentations took place in the presence of SO2 or not. Thus, the existence of signatures in wines of chemical diversity and microbiology linked to vineyard protection has been highlighted.
Reducing FPGA Router Run-Time through Algorithm and Architecture

We propose a new FPGA routing approach that, when combined with a low-cost architecture change, results in a 34% reduction in router run-time, at the cost of a 3% area overhead, with no increase in critical path delay. Our approach begins with traditional PathFinder-style routing, which we run on a coarsened representation of the routing architecture. This leads to fast generation of a partial routing solution where ignals are assigned to groups of wire segments rather than individual wire segments. A boolean satisfiability (SAT)-based stage follows, generating a legal routing solution from the partial solution. Our approach points to a new research direction: reducing FPGA CAD run-time by exploring FPGA architectures and algorithms together.
ARENA: An Approach for the Automated Generation of Release Notes

Release notes document corrections, enhancements, and, in general, changes that were implemented in a new release of a software project. They are usually created manually and may include hundreds of different items, such as descriptions of new features, bug fixes, structural changes, new or deprecated APIs, and changes to software licenses. Thus, producing them can be a time-consuming and daunting task. This paper describes ARENA (Automatic RElease Notes generAtor), an approach for the automatic generation of release notes. ARENA extracts changes from the source code, summarizes them, and integrates them with information from versioning systems and issue trackers. ARENA was designed based on the manual analysis of 990 existing release notes. In order to evaluate the quality of the release notes automatically generated by ARENA, we performed four empirical studies involving a total of 56 participants (48 professional developers and eight students). The obtained results indicate that the generated release notes are very good approximations of the ones manually produced by developers and often include important information that is missing in the manually created release notes.
Managing operational business intelligence workloads

We explore how to manage database workloads that contain a mixture of OLTP-like queries that run for milliseconds as well as business intelligence queries and maintenance tasks that last for hours. As data warehouses grow in size to petabytes and complex analytic queries play a greater role in day-to-day business operations, factors such as inaccurate cardinality estimates, data skew, and resource contention all make it notoriously difficult to predict how such queries will behave before they start executing. However, traditional workload management assumes that accurate expectations for the resource requirements and performance characteristics of a workload are available at compile-time, and relies on such information in order to make critical workload management decisions. In this paper, we describe our approach to dealing with inaccurate predictions. First, we evaluate the ability of workload management algorithms to handle workloads that include unexpectedly long-running queries. Second, we describe a new and more accurate method for predicting the resource usage of queries before runtime. We have carried out an extensive set of experiments, and report on a few of our results.
Matrix Factorization Based Models Considering Item Categories and User Neighbors

Matrix factorization is a popular collaborative filtering method for recommendation techniques with predictive accuracy and good scalability. In this paper, we propose two models on the basis of basic matrix factorization, namely CW-MF, NICW-MF. CW-MF considers user's preference on item categories and NICW-MF takes into account the impact of user's neighbors to minimize the preference between user and his neighbors. We conduct empirical experiments on MovieLens dataset, and results show that our two models perform well.
Antiproliferative Scalarane-Based Metabolites from the Red Sea Sponge Hyrtios erectus

Two new sesterterpenes analogs, namely, 12-acetoxy,16-epi-hyrtiolide (1) and 12β-acetoxy,16β-methoxy,20α-hydroxy-17-scalaren-19,20-olide (2), containing a scalarane-based framework along with seven previously reported scalarane-type sesterterpenes (3–9) have been isolated from the sponge Hyrtios erectus (order Dictyoceratida) collected from the Red Sea, Egypt. The structures of the isolated compounds were elucidated on the basis of their spectroscopic data and comparison with reported NMR data. Compounds 1–9 exhibited considerable antiproliferative activity against breast adenocarcinoma (MCF-7), colorectal carcinoma (HCT-116) and hepatocellular carcinoma cells (HepG2). Compounds 3, 5 and 9 were selected for subsequent investigations regarding their mechanism of cell death induction (differential apoptosis/necrosis assessment) and their influence on cell cycle distribution.
INTEGRATING GIS DATA INTO A CHOICE EXPERIMENT OF PREFERENCES OVER RESOURCE USE ALTERNATIVE: A BRITISH COLUMBIA EXAMPLE

—A valley in the Selkirk mountains of British Columbia was used as the setting for a choice experiment to determine resource values and individual preferences over management alternatives. GIS and management models of wildlife, recreation and timber already existed from previous research and lent themselves readily to application within a choice modeling framework for valuation and utility analysis. Choice models are a subset of stated preference modeling which have historically been applied to consumer problems. They are now emerging as an alternative to the more conventional valuation approaches such as contingent valuation. This study applies these techniques directly to a specific resource setting and using the spatially referenced detail available through GIS, communicates a great deal of resource information to survey respondents for their evaluation in a choice experiment format. The results of the survey allow inferences on preferences, valuation, trade offs and opportunity costs to be drawn. These are all extremely useful results for resource managers and policymakers alike. This study can serve as an example for larger scale research of this type.
Multipredicate Join Algorithms for Accelerating Relational Graph Processing on GPUs

Recent work has demonstrated that the use of programmable GPUs can be advantageous during relational query processing on analytical workloads. In this paper, we take a closer look at graph problems such as finding all triangles and all four-cliques of a graph. In particular, we present two different join algorithms for the GPU. The first is an implementation of Leapfrog-Triejoin (LFTJ), a recently presented worst-case optimal multi-predicate join algorithm. The second is a novel approach, inspired by the former but more suitable for GPU architectures. Our preliminary performance benchmarks show that for both approaches using GPUs is cost-effective. (the GPU implementation outperforms respective CPU variants). While the second algorithm is faster overall, it comes with increased implementation complexity and storage requirements for intermediary results. Furthermore, both our algorithms are competitive with the hand-written C++ implementation for finding triangles and four-cliques in the graph-processing system GraphLab executing on a multi-core CPU.
Validating Adequacy and Suitability of Business-IT Alignment Criteria in an Inter-Enterprise Maturity Model 202

Aligning requirements of a business with its information technology is currently a major issue in enterprise computing. Existing literature indicates important criteria to judge the level of alignment between business and IT within a single enterprise. However, identifying such criteria in an inter-enterprise setting - or re-thinking the existing ones - is hardly addressed at all. Business-IT alignment in such settings poses new challenges, as in inter-enterprise collaborations, alignment is driven by economic processes instead of centralized decision-making processes. In our research, we develop a maturity model for business-IT alignment in inter-enterprise settings that takes this difference into account. In this paper, we report on a multi-method approach we devised to confront the validation of the business-IT alignment criteria that we included in the maturity model. As independent feedback is critical for our validation, we used a focus group session and a case study as instruments to take the first step in validating the business-IT alignment criteria. We present how we applied our approach, what we learnt, and what the implications were for our model.
Integrating Public Health and Computer Science Theoretical Perspectives for Developing Tailored Health Messages

In this paper, we review current approaches employed by both public health and computer science to develop tailored persuasive messages to foster health-related behavior change. It is based on this review that we propose an integrated framework for merging public health and computer science approaches. We believe that such a framework can lead to new methods to extend current tailoring research. Our method for analyzing persuasive health messages, influenced by this integrated framework, is presented as an example.
Relay-aided Interference Alignment for the quasi-static interference channel

In this paper, we first investigate the Degrees Of Freedom (DOF) for the M-user Interference Channel (IC) in static environments with the help of a MIMO relay. The relay stores the received signal during the first time-slot and sends a linearly-transformed version over the next time-slot. Using this scheme, it is shown that Interference Alignment can be done with much less complexity. Having very loose constraints on the channel structure, the proposed method calculates a proper choice for the relay gains such that the M-user IC is able to achieve a DOF of M over 2. It is also proved that if the relay's output power scales as P over (log P)t where P is the power of the transmitters, there is no loss in the achieved DOF. This result is true for all positive and negative ranges of t. In other words, in an M-user IC with quasi-static channel gains, it is possible to achieve M over 2 DOF through the use of a MIMO relay whose power grows at a rate slower than that of the transmitters. Similarly, a network of low-power users can benefit from our proposed method if the relay power scales faster than the power of the main transmitters. The results of this paper are valuable when being applied to a practical system. While it is very difficult to use Interference Alignment in M-user IC setup, adding a relay can make alignment more affordable by simplifying the transmitter/receiver structure.