Miracle-dz/UniFAR-FTUs huggingface dataset:
Rock magnetic and geochemical evidence for authigenic magnetite formation via iron reduction in coal‐bearing sediments offshore Shimokita Peninsula, Japan (IODP Site C0020)

Sediments recovered at Integrated Ocean Drilling Program (IODP) Site C0020, in a fore‐arc basin offshore Shimokita Peninsula, Japan, include numerous coal beds (0.3–7 m thick) that are associated with a transition from a terrestrial to marine depositional environment. Within the primary coal‐bearing unit (∼2 km depth below seafloor) there are sharp increases in magnetic susceptibility in close proximity to the coal beds, superimposed on a background of consistently low magnetic susceptibility throughout the remainder of the recovered stratigraphic sequence. We investigate the source of the magnetic susceptibility variability and characterize the dominant magnetic assemblage throughout the entire cored record, using isothermal remanent magnetization (IRM), thermal demagnetization, anhysteretic remanent magnetization (ARM), iron speciation, and iron isotopes. Magnetic mineral assemblages in all samples are dominated by very low‐coercivity minerals with unblocking temperatures between 350 and 580°C that are interpreted to be magnetite. Samples with lower unblocking temperatures (300–400°C), higher ARM, higher‐frequency dependence, and isotopically heavy δ56Fe across a range of lithologies in the coal‐bearing unit (between 1925 and 1995 mbsf) indicate the presence of fine‐grained authigenic magnetite. We suggest that iron‐reducing bacteria facilitated the production of fine‐grained magnetite within the coal‐bearing unit during burial and interaction with pore waters. The coal/peat acted as a source of electron donors during burial, mediated by humic acids, to supply iron‐reducing bacteria in the surrounding siliciclastic sediments. These results indicate that coal‐bearing sediments may play an important role in iron cycling in subsiding peat environments and if buried deeply through time, within the subsequent deep biosphere.
Combining multigrid and wavelet ideas to construct more efficient multiscale algorithms for the solution of Poisson's equation

It is shown how various ideas that are well established for the solution of Poisson's equation using plane wave and multigrid methods can be combined with wavelet concepts. The combination of wavelet concepts and multigrid techniques turns out to be particularly fruitful. We propose a modified multigrid V cycle scheme that is not only much simpler, but also more efficient than the standard V cycle. Whereas in the traditional V cycle the residue is passed to the coarser grid levels, this new scheme does not require the calculation of a residue. Instead it works with copies of the charge density on the different grid levels that were obtained from the underlying charge density on the finest grid by wavelet transformations. This scheme is not limited to the pure wavelet setting, where it is faster than the preconditioned conjugate gradient method, but equally well applicable for finite difference discretizations.
CAMS-RS: Clustering Algorithm for Large-Scale Mass Spectrometry Data using Restricted Search Space and Intelligent Random Sampling.

High-throughput mass spectrometers can produce massive amounts of redundant data at an astonishing rate with many of them having poor signal-to-noise (S/N) ratio. These low S/N ratio spectra may not get interpreted using conventional spectra-to-database matching techniques. In this paper, we present an efficient algorithm, CAMS-RS (Clustering Algorithm for Mass Spectra using Restricted Space and Sampling) for clustering of raw mass spectrometry data. CAMS-RS utilizes a novel metric (called F-set) that exploits the temporal and spatial patterns to accurately assess similarity between two given spectra. The F-set similarity metric is independent of the retention time and allows clustering of mass spectrometry data from independent LC-MS/MS runs. A novel restricted search space strategy is devised to limit the comparisons of the number of spectra. An intelligent sampling method is executed on individual bins that allow merging of the results to make the final clusters. Our experiments, using experimentally generated datasets, show that the proposed algorithm is able to cluster spectra with high accuracy and is helpful in interpreting low S/N ratio spectra. The CAMS-RS algorithm is highly scalable with increasing number of spectra and our implementation allows clustering of up to a million spectra within minutes.
OMEGA Correct development of Real-time systems IST-2001-33522

The aim of this work is to provide a formal foundation for the unambiguous description of real-time, reactive, embedded systems in UML. For this application domain, we define the meaning of basic class diagrams where the behavior of objects is described by state machines. These reactive objects may communicate by means of asynchronous signals and synchronous operation calls. The notion of a thread of control is captured by a so-called activity group, i.e., a set of objects which contains exactly one active object and where at most one object may be executing. Explicit timing is realized via local clocks and an urgency predicate on transitions. We define a formal semantics for this kernel language, list a number of questions that arose, and discuss the decisions taken. The resulting semantics has been defined in the typed logic of the interactive theorem prover PVS, thus enabling formal verification based on this semantics.
Communications of the Association for Information Systems

This paper presents a research agenda for studying information systems using open source software A multi-level research model is developed at five discrete levels of analysis: (1) the artifact; (2) the individual; (3) the team, project, and community; (4) the organization; and (5) society. Each level is discussed in terms of key issues within the level. Examples are based on prior research. In a companion paper, [Niederman, et al 2006], we view the agenda through the lens of referent discipline theories.
Pemodelan Kawasan Panen Kelapa Sawit Malaysia Menggunakan Model Logistik

Palm oil and related products is Malaysia's second largest export. Palm oil state expenditures in 2010 are projected to reach approximately 64,282,738 tons within a year. However, these results still have not reached the stage of maximum when seen from an oil palm plantation areas in Peninsular Malaysia, Sabah and Sarawak covering an area of 4,691,160 hectares. Of the area, approximately 2,807 million hectares of oil palm plantations planted by the private sector (59.8%) while 20.2% is managed by the Government (FELDA 675.167 ha, 80.262 Risda and Felcra 160.832), 321.947 ha (7.1%) by the local government and the rest covering an area of 540.194 ha (12.9%) are currently working on. This study discusses the entire area of oil palm planted area compared to the harvest, the number of workers factors, yields and prices. The model used in this research is the method of logistics, with the probit model, logit model and complementary log-log function (complementary log-log) to 39 locations palm observations drawn from Jabatan Perangkaan Malaysia. Models are selected based on statistical test that involves the value of AIC (Akaike information criterion) of proc logistic method, the value of the method Genmod Proc devians as well as the value of p, the reference is taken to determine the best model in this study. After comparison of the statistical test is selected, indicating that the model Complement function logs is a better model than the models probit and logit models. Keywords: AIC, devians, genmod proc, logistic proc, palm oil
Method for Improving EEG Based Emotion Recognition by Combining It with Synchronized Biometric and Eye Tracking Technologies in a Non-invasive and Low Cost

Citation: López-Gil J-M, Virgili-Gomá J, Gil R and García R (2016) Method for Improving EEG Based Emotion Recognition by Combining It with Synchronized Biometric and Eye Tracking Technologies in a Non-invasive and Low Cost Way. Front. Comput. Neurosci. 10:85. doi: 10.3389/fncom.2016. 00085 Method for Improving EEG Based Emotion Recognition by Combining It with Synchronized Biometric and Eye Tracking Technologies in a Non-invasive and Low Cost Way
Learned Autoscaling for Cloud Microservices

As cloud applications shift from monoliths to loosely coupled microservices, application developers must decide how many compute resources (e.g., VMs) to give to each microservice within an application. This decision affects both (1) the dollar cost to the application developer and (2) the end-to-end latency perceived by the application user. Today, individual microservices are autoscaled by adding VMs whenever utilization metrics (e.g. CPU, RAM) cross a configurable threshold. Utilization-based autoscaling is simple to understand at the level of an individual microservice. However, an application user’s end-to-end latency consists of time spent on multiple microservices and each microservice might need a different threshold to achieve an overall end-to-end latency. Further, thresholds are application and workload dependent. We present COLA, an autoscaler for microservice-based applications. COLA learns autoscaling policies tailored to applications and their workloads and allocates VMs to an application’s microservices to meet end-to-end latency targets while minimizing dollar cost. Using 5 open-source applications, we compared COLA to several utilization and machine learning based autoscalers. COLA meets a desired median or tail latency target on 31 of 39 workloads where it provides an average cost reduction of 30.9% over the next cheapest autoscaler. COLA is the most cost effective autoscaling policy for 27 of these 31 workloads. The cost savings from managing a cluster with COLA result in COLA paying for its training cost in a few days.
Co-Training of Audio and Video Representations from Self-Supervised Temporal Synchronization

There is a natural correlation between the visual and auditive elements of a video. In this work we leverage this connection to learn general and effective features for both audio and video analysis from self-supervised temporal synchronization. We demonstrate that a calibrated curriculum learning scheme, a careful choice of negative examples, and the use of a contrastive loss are critical ingredients to obtain powerful multi-sensory representations from models optimized to discern temporal synchronization of audio-video pairs. Without further finetuning, the resulting audio features achieve performance superior or comparable to the state-of-the-art on established audio classification benchmarks (DCASE2014 and ESC-50). At the same time, our visual subnet provides a very effective initialization to improve the accuracy of video-based action recognition models: compared to learning from scratch, our self-supervised pretraining yields a remarkable gain of +16.7% in action recognition accuracy on UCF101 and a boost of +13.0% on HMDB51.
IT Shared Service Center and External Market Activities

In the last few years many corporate groups reorganized their IT-Services and established IT Shared Service Centers (IT SSC). These IT SSCs primarily delivered IT services internally; nevertheless some IT SSC provided IT services to external customers as well. These external market activities failed in most cases. In spite of the relevance to organizations, little research has been done investigating the reasons for such failures. In order to address this issue, we have conducted a qualitative study with eight IT SSC cases and five experts interviews. We have triangulated the results between the case studies and the expert interviews and we have identified two set of factors, one explaining IT SCC successes in internal markets and the other explaining IT SSC failures in external markets. The enabling factors for the successes of IT SSCs in internal markets include having the same corporate culture, knowledge of the parent organization and its processes, lower transactions cost, lower average cost, no dependence on external IT service providers, better data protection, improved IT opportunities and obligation to provide services. The factors explaining external market failures include the lack of experience with acquisition, no professional sales and marketing, lack of investment funds, weak unique features of IT services, reassessment of strategic group portfolio by the parent company, higher IT service costs, and inconsistent business models. These findings are relevant to managers of IT SSCs to make decisions on their corporate strategy, as well as to researchers to utilize these findings as a starting point for future research on IT SSCs.
Convection intrinseque et fluctuations de vitesse en sedimentation

Le mouvement individuel de particules spheriques au sein d'une suspension en sedimentation a bas nombre de reynolds a ete etudie. Au mouvement moyen de chute des particules s'ajoutent des fluctuations de vitesse importantes engendrees par les interactions hydrodynamiques a longue portee. Nous nous sommes interesses, tout d'abord, au mouvement moyen des particules dans une suspension composee de spheres monodisperses. Nous avons mis en evidence pour la premiere fois l'effet de convection globale de la suspension appele convection intrinseque. Nous avons mesure l'amplitude de cet effet en fonction de la fraction volumique de la suspension et nous avons montre que celle-ci est reliee a l'organisation des particules pres du bord du recipient. Dans une seconde partie, l'etude des fluctuations de vitesse des particules dans la suspension a ete menee. Dans un premier temps, l'analyse du mouvement individuel d'une sphere test unique evoluant dans une suspension monodisperse nous a permis d'obtenir ses fluctuations en fonction de ses caracteristiques (taille et densite) par rapport a celles de la suspension. Nous avons ensuite etudie les fluctuations de vitesse d'un melange de deux types de spheres de meme densite mais de diametres differents. La fraction volumique des plus petites est maintenue constante a 1% et celle des grosses particules varie de 0. 5% a 2% par sauts de 0. 5%. Deux zones particulieres de la suspension ont ete etudiees : la zone de melange des deux types de spheres et la zone en haut de la suspension ou ne se trouvent que les spheres dont la vitesse est la plus faible. Nous avons obtenu la variation des fluctuations des differentes particules en fonction de la concentration dans les deux zones. Nous avons analyse l'augmentation des fluctuations des deux types de particules lorsque la concentration augmente dans la zone de melange. Dans la zone de petites spheres seules, les fluctuations de vitesse baissent significativement par rapport a la valeur qu'elles avaient a la meme concentration mais sans le passage des grosses spheres. Il semble qu'un changement dans l'organisation des particules dans la suspension, provoque par le passage des grosses billes, conduise a cette observation.
Fixation Patterns During Process Model Creation: Initial Steps Toward Neuro-Adaptive Process Modeling Environments

Despite their wide adoption, industrial business process models often display a wide range of quality issues. While significant efforts have been undertaken to better understand factors impacting process model comprehension, only few studies focused on their creation. This paper presents a set of fixation patterns that have been derived from a modeling session with 120 participants during which the modelers' behavior was recorded in terms of eye movements as well as interactions with the modeling environment. The identified patterns can be used in the future as basis for automatic real-time detection of the activities a user is performing, an essential building block for the development of a neuro-adaptive environment for process modeling that is able to adapt to the task at hand and the user's individual processing capacities.
Urban networks in Europe.

This work contains revised versions of papers presented at an international colloquium on urbanization in Europe held in Saint-Cloud France October 21-22 1993. The 16 papers which are in English or French are organized into four sections examining the emerging structure of a European urban system new linkages among European cities the development of urban policies and improving comparability in research about cities in Europe. (ANNOTATION)
AIS Electronic Library (AISeL)

Due to the unique characteristics of small-and-medium sized enterprises (SMEs), critical success factors (CSFs) identified in the context of large enterprises may not be readily applicable to SMEs. This paper aims to enhance the current understanding of CSFs for ES implementation in SMEs. It synthesizes a set of CSFs that are likely to be significant for ES implementation in SMEs and then explores the perception of 30 SMEs regarding influential CSFs through an analysis of online customer success stories. The study highlights some differences in CSF identified in the literature and those perceived by SMEs. By identifying CSFs of high importance within the context of SMEs this study improves the prospects of successful ES implementation. It also identifies knowledge gaps that could be addressed in future studies to enhance the current understanding of CSFs for ES implementations in SMEs.
Biomonitoring polybrominated diphenyl ethers in lactating women

Breast milk is a valuable biological specimen for biomonitoring lipid-soluble polybrominated diphenyl ethers (PBDEs). The goal of this project was to determine the levels of PBDEs in breast milk of lactating women from the Seacoast region of New Hampshire and to examine potential relationships between PBDE levels in breast milk and stage of lactation, maternal characteristics, living environment and dietary intake. Forty women, ages 22 to 40, provided up to three breast milk samples at the end of their first, second and third month of breastfeeding for evaluation of day-to-day and month-to-month variation in PBDE levels. Participants were asked to complete four questionnaires, which provided maternal, living environment, and diet information. The sum of PBDE (SigmaPBDE) congeners found in breast milk was defined as: BDE-28/ 33, 47, 85, 99, 100, 153, 154, and 183. The SigmaPBDE concentrations in breast milk over the three-month collection period ranged from 6.5 to 166.7 ng/g lipid. The median for the three-month period was 29.7 ng/g. BDE-47 was the predominant congener; however, BDE-153 predominated in 20% of the participants' samples from each month. Day-to-day variation in SigmaPBDEs was negligible; there was no significant difference in mean PBDE levels from month-to-month. Regression analyses revealed relationships between logtransformed PBDE levels in breast milk and questionnaire data. Positive associations were seen between BDE-153 and age (r = 0.36 p = 0.02), saturated fat consumption (r = 0.31 p = 0.05), and the home model (r = 0.51 p = 0.004). There was a negative association between PBDE levels (Sigma and BDE-47) and fruit consumption (r = 0.36 p = 0.02, SigmaPBDE). Our results indicate that PBDE levels in breast milk from New Hampshire are within the range that has been reported in the U.S., and that levels are stable during the first three-months of lactation. Our findings revealed a higher predominance pattern with BDE-153 compared to other studies, and indicate that PBDE levels are influenced by age, diet, and the home environment.
Constructing Game Agents from Video of Human Behavior

Developing autonomous agents for computer games is often a lengthy and expensive undertaking that requires manual encoding of detailed and complex knowledge. In this paper we show how to acquire hierarchical skills for controlling a team of simulated football players by observing video of college football play. We then demonstrate the results in the Rush 2008 football simulator, showing that the learned skills have high fidelity with respect to the observed video and are robust to changes in the environment. Finally, we conclude with discussions of the broader impacts of this work and of possible improvements.
An Extreme Rainfall Event in Coastal South China During SCMREX‐2014: Formation and Roles of Rainband and Echo Trainings

In this study, an extreme rainfall event of 451 mm in 20 hr that occurred in coastal South China on 11 May 2014 during the Southern China Monsoon Rainfall Experiment is investigated using integrated observations from the dual‐Doppler radar pair, polarimetric radar, extensive mesonetwork, and enhanced upper‐air soundings. Results show the generation of the extreme rainfall by two consecutive mesoscale convective systems (MCSs) consisting of multiple meso‐β‐scale rainbands. The two MCSs are maintained by lifting southerly oceanic flows over a quasi‐stationary mesoscale outflow boundary (MOB) along the coastline that are enhanced by convectively generated weak cold pool. Northeastward “echo training” of convective cells, under the influence of environmental southwesterly flows, leads to the formation of the multiple rainbands in each MCS. Their subsequent propagations in a “rainband training” form, together with the echo training, along the coastline account for the production of extreme rainfall. The second MCS is characterized with a leading bowing rainband showing a process of rapid splitting and reestablishment (RSRE), which contributes to the formation of the rainband training. The occurrence of the RSRE process requires ample supply of unstable upstream oceanic air mass, the quasi‐stationary MOB, and a bowing rainband intersecting with the MOB. The second MCS produces more precipitation than the first one as a result of more rainbands, stronger convective intensity, and more moderate‐sized raindrops with larger maximal sizes. The above findings, especially the RSRE process and its associated storm internal circulation, appear to add new Insights into the formation and maintenance of training rainbands and their roles in heavy rainfall production.