Miracle-dz/UniFAR-FTUs huggingface dataset:
Scheduling the Spark Framework under the Mesos Resource Manager

Using clusters of servers and datacenters to process large numbers of data- and computation-intensive jobs is becoming mainstream. The need for large clusters is driven by the fact that many workloads are growing at a faster rate than the advances in single computer performance. To manage processing in a cluster of multiple computers, several frameworks have appeared over the years. These frameworks supply the user with convenient computation constructs and abstract from the low-level implementations to relieve the burden of inter-process communication and task placement in a cluster. However, these frameworks often assume total control over a static partition of the cluster, leading to under-utilization in times when one framework is over-committed with work, whereas another framework is idling. To overcome this under-utilization, and multiplex frameworks in clusters, cluster schedulers have been proposed, which sit on top of the hardware resources and schedule hardware resource leases to frameworks. It is not well described how these systems differ from each other. Furthermore, how to achieve \emph{performance balance} between frameworks, such that multiple frameworks achieve similar performance metrics when running time-varying workloads is relatively unexplored. We define a taxonomy which describes the combination of cluster schedulers and frameworks, called Two-Level schedulers in general. We characterize the multiple state-of-the-art cluster schedulers that are described in the literature or are used in practice. We distinguish multiple aspects which define the cluster schedulers. These aspects can dictate how frameworks interface with the cluster scheduler and can also influence framework performance. We aim to achieve performance balance for multiple \gls{spark} frameworks running under the \gls{mesos} cluster scheduler. First, we evaluate the performance of a single framework running single interactive data analytics queries. We find multiple configuration parameters which influence the performance for interactive queries. However, we conclude that using \gls{sparkmesos} for interactive queries results in either inefficient use of resources, or does not allow us to multiplex resources over multiple frameworks. We continue with achieving performance balance for multiple frameworks for non-interactive queries. We first establish a baseline performance balance, which we attain by using knowledge of the possibly different workload intensities run by the frameworks in a real cluster. Afterwards, we achieve similar performance balance, compared to the baseline, for up to three frameworks without knowing the workload intensity a priori. This is achieved by using a feedback loop controller, which updates resource share sizes allocated to frameworks dynamically, based on the online performance metrics of the frameworks.
Population Dynamics of Benthic-Epiphytic Dinoflagellates on Two Macroalgae From Coral Reef Systems of the Northern Mexican Caribbean

"In the present study the abundance of epiphytic dinoflagellates was evaluated at two coral reef sites of the natural protected areas, Arrecife de Puerto Morelos and Isla Contoy, located in the northern Mesoamerican Reef System of the Mexican Caribbean. Abundances were monitored from April to December, 2015 on two genera of macroalga belonging to different functional groups: Dictyota and Amphiroa. In general, the tota abundance of dinoflagellates was higher in Puerto Morelos on both macroalgae. Ostreopsis cf. marina and O. heptagona were the dominant species. Relative abundance of these species varied from 8 to 99% of total epiphytic dinoflagellates. Maximum abundances at Puerto Morelos were registered in April, with 33,801 cells·g−1 on Dictyota and 6,264 cells·g−1 on Amphiroa. In Isla Contoy the maximum abundance was 16,006 cells·g−1 and it was detected on Dictyota during December. Other dinoflagellate genera were more abundant during the warmer period (May–September) in both locations. Prorocentrum was the second most abundant genus and was represented by six species (P. hoffmannianum, P. lima, P. belizeanum, P. elegans, P. emarginatum, and P. rathymum). The maximum pooled abundance of Prorocentrum species was 4,144 cells·g−1 on Dictyota in August. Coolia spp. did not reach abundances higher than 1,000 cells·g−1 and Gambierdiscus spp. only exceeded 100 cells·g−1 during August. Mean water temperature in Isla Contoy was significantly lower than that of Puerto Morelos during the entire study period. There was a negative correlation between the water temperature and the abundance of O. cf. marina. The dominance of Ostreopsis in the Caribbean is significant because of its capability to produce palytoxin analogs and its potential role in ciguatera fish poisoning outbreaks in the region. This is the first study that reports blooms of Ostreopsis in Mexican Caribbean coral reefs, a fact that emphasizes the significance of this genus at global scale. "
Bispecific Designed Ankyrin Repeat Proteins (DARPins) Targeting Epidermal Growth Factor Receptor Inhibit A431 Cell Proliferation and Receptor Recycling*

Background: The EGF receptor (EGFR) is an important therapeutic target. Results: Bispecific anti-EGFR designed ankyrin repeat proteins (DARPins), alternative targeting molecules efficiently produced in bacteria, were shown to inhibit A431 cell proliferation and receptor recycling. Conclusion: One bispecific construct containing four DARPins showed a biological activity superior to that of the registered antibody cetuximab. Significance: Bispecific DARPins may form building blocks for tomorrow's cancer therapeutics. The EGF receptor (EGFR) has been implicated in the development and progression of many tumors. Although monoclonal antibodies directed against EGFR have been approved for the treatment of cancer in combination with chemotherapy, there are limitations in their clinical efficacy, necessitating the search for robust targeting molecules that can be equipped with new effector functions or show a new mechanism of action. Designed ankyrin repeat proteins (DARPins) may provide the targeting component for such novel reagents. Previously, four DARPins were selected against EGFR with (sub)nanomolar affinity. As any targeting module should preferably be able to inhibit EGFR-mediated signaling, their effect on A431 cells overexpressing EGFR was examined: three of them were shown to inhibit proliferation by inducing G1 arrest, as seen for the Food and Drug Administration-approved antibody cetuximab. To understand this inhibitory mechanism, we mapped the epitopes of the DARPins using yeast surface display. The epitopes for the biologically active DARPins overlapped with the EGF-binding site, whereas the fourth DARPin bound to a different domain, explaining the lack of a biological effect. To optimize the biological activity of the DARPins, we combined two DARPins binding to different epitopes with a flexible linker or with a leucine zipper, leading to a homodimer. The latter DARPin was able to reduce surface EGFR by inhibiting receptor recycling, leading to a dramatic decrease in cell viability. These results indicate that multispecific EGFR-specific DARPins are superior to cetuximab and may form the basis of new opportunities in tumor targeting and tumor therapy.
Cross-Platform Identification of Anonymous Identical Users in Multiple Social Media Networks

The last few years have witnessed the emergence and evolution of a vibrant research stream on a large variety of online social media network (SMN) platforms. Recognizing anonymous, yet identical users among multiple SMNs is still an intractable problem. Clearly, cross-platform exploration may help solve many problems in social computing in both theory and applications. Since public profiles can be duplicated and easily impersonated by users with different purposes, most current user identification resolutions, which mainly focus on text mining of users’ public profiles, are fragile. Some studies have attempted to match users based on the location and timing of user content as well as writing style. However, the locations are sparse in the majority of SMNs, and writing style is difficult to discern from the short sentences of leading SMNs such as Sina Microblog and Twitter. Moreover, since online SMNs are quite symmetric, existing user identification schemes based on network structure are not effective. The real-world friend cycle is highly individual and virtually no two users share a congruent friend cycle. Therefore, it is more accurate to use a friendship structure to analyze cross-platform SMNs. Since identical users tend to set up partial similar friendship structures in different SMNs, we proposed the Friend Relationship-Based User Identification (FRUI) algorithm. FRUI calculates a match degree for all candidate User Matched Pairs (UMPs), and only UMPs with top ranks are considered as identical users. We also developed two propositions to improve the efficiency of the algorithm. Results of extensive experiments demonstrate that FRUI performs much better than current network structure-based algorithms.
Extensive Variations in Diurnal Growth Patterns and Metabolism Among Ulva spp. Strains1[OPEN]

Sea lettuce (Ulva spp.) strains show extensive variation in growth and metabolism, demonstrating a large potential for strain selection in boosting biomass and metabolite yields in aquaculture. Green macroalgae of the genus Ulva play a key role in coastal ecosystems and are of increasing commercial importance. However, physiological differences between strains and species have yet to be described in detail. Furthermore, the strains of Ulva used in aquaculture usually originate from opportunistic collection in the wild without prior selection of best performing strains. Hence, efforts are required to detect the potential variability in growth and metabolic accumulation between Ulva strains and ultimately select the best performing strains under given environmental conditions. Here, the growth, physiological, and metabolic characteristics of 49 laminar Ulva spp. strains were investigated using a custom-made high-throughput phenotyping platform, enzymatic assays, and gas chromatography-mass spectrometry. We found large natural variation for a wide range of growth and metabolic characteristics, with growth rates varying from 0.09 to 0.37 mg.mg−1.d−1 among strains. Ulva spp. possess a unique diurnal growth pattern and primary metabolism compared with land plants, with higher growth rates during the night than during the light period. Starch and sucrose only contributed on average 35% of the carbon required to sustain Ulva’s night growth. Nitrates accumulated during the night in Ulva tissues, and nitrate accumulation and consumption was positively correlated with growth. In addition, we identified six amino acids as possible biomarkers for high growth in Ulva. The large variability in growth and metabolite accumulation recorded among morphologically similar Ulva strains justifies future efforts in strain selection for increasing biomass, metabolite yields, and nutrient removal in the growing aquaculture industry.
Developing a Decision Support Testing Algorithm to Detect Severity Level of Dengue

Dengue is a vector borne disease that has become a global threat. In order to reduce the mortality rate early detection of dengue severity level is crucial. This study is an extension of the decision models developed individually for inflammatory mediators and immune parameters. The objective of this study is to improve the individual models by considering their combined effect and to improve the decision making at 96 hours from onset of illness. In order to combine these, three approaches are attempted including, combining together the individual full models on inflammatory mediators and immune parameters, combining the immune parameters based model with decision tree informed cytokines and implementing a decision tree informed model with immune parameters and inflammatory mediators. The decision tree algorithm that is used in model development is Improved ID3 algorithm. The decision tree based model is a two-step decision system with the initial decision being made using the parameters TNF-? , IL-10, dengue NS1 antigen and dengue IgG antibody and, the operator values above 0.4413, are then subjected to the second test including platelet and Platelet Activating Factor. The decision tree based model performed well with an accuracy of 76.19% and 82.3% of DHF patients were correctly classified. Sensitivity analysis indicated the model to be robust.
Is This Time Different? Do Bank CEOs Learn From Crises?

This paper studies the impact of Bank Holding Company (BHC) CEO’s early-life exposure to the 1980s savings and loans(S&Ls) crisis on the survival, systemic risks and policies of her BHC that she is in charge of in the future. First, I characterize the features of banks managed by CEOs who witnessed more intensely the S&L crisis (seasoned CEOs) measured by the state-level bank failure rate. I find that BHCs with seasoned CEOs are less likely to fail, and they decouple from the rest of the banking industry by taking lower systemic risks. One unit of the crisis intensity measure is associated with 0.5% lower failure rate and 0.39% lower systemic risk, measured by marginal expected shortfall. Second, I attempt to pin down the potential policy channels exploited by CEOs to account for these results. Seasoned CEOs shape their bank business models to be less reliant on interest rates. As such, these CEOs exhibit more effective control over credit risk and have higher holdings of liquid assets on their balance sheet. However, their asset growth and diversification strategies are not significantly different from those of less experienced CEOs. Finally, using exogenous turnovers, I show that the findings are not driven by bank-CEO matching. ”We know we have crises every five or ten years. ” Jamie Dimon, J.P. Morgan’s chairman and chief executive, said in January 2010. ∗gloria.yu@insead.edu
HST/COS Observations of Quasar Outflows in the 500–1050 Å Rest Frame. I. The Most Energetic Outflows in the Universe and Other Discoveries

The Hubble Space Telescope/Cosmic Origins Spectrograph (COS) has opened a new discovery space for studying quasar absorption outflows and their contribution to active galactic nucleus (AGN) feedback. Specifically, COS provides high-quality far-ultraviolet (FUV) spectra covering the diagnostic-rich 500–1050 Å rest frame (hereafter, EUV500) of medium redshift objects. The quality and quantity of EUV500 diagnostic troughs allow us to probe the very high-ionization phase, which carries 90% or more of the outflowing material, as well as to determine the distance of most outflows from the central source (R). The first objective is impossible to achieve with ground-based spectra, and R can be measured in only ∼1% of them. Here, we summarize the main results of the first dedicated survey of such outflows, including the following. 1. Measurements of the three most energetic outflows to date, which can be the main agents for AGN feedback processes in the environments of the host galaxies. 2. All the outflows have a very high-ionization component, similar to the one found in warm absorbers, which carries most of the outflow’s kinetic luminosity. This finding suggests that all the high-ionization outflows observed from the ground also have a similar undetected very high-ionization component. 3. Of the 13 studied EUV500 outflows, 9 have 100 < R < 2000 parsecs, 2 have 5 < R < 20 parsecs, 1 has 0.05 < R < 50 parsecs, and in 1 case, R cannot be determined. 4. One of the outflows has the largest velocity shift (1550 km s−1) and acceleration (1.5 cm s−2) measured to date. This outflow is physically similar to the fast X-ray outflow detected in quasar PG 1211+143.
Slicing: A sustainable approach to structuring samples for analysis in long‐term studies

The longitudinal study of populations is a core tool for understanding ecological and evolutionary processes. Long‐term studies typically collect samples repeatedly over individual lifetimes and across generations. These samples are then analysed in batches (e.g. qPCR plates) and clusters (i.e. group of batches) over time in the laboratory. However, these analyses are constrained by cross‐classified data structures introduced biologically or through experimental design. The separation of biological variation from the confounding among‐batch and among‐cluster variation is crucial, yet often ignored. The commonly used approaches to structuring samples for analysis, sequential and randomization, generate bias due to the non‐independence between time of collection and the batch and cluster they are analysed in. We propose a new sample structuring strategy, called slicing, designed to separate confounding among‐batch and among‐cluster variation from biological variation. Through simulations, we tested the statistical power and precision to detect within‐individual, between‐individual, year and cohort effects of this novel approach. Our slicing approach, whereby recently and previously collected samples are sequentially analysed in clusters together, enables the statistical separation of collection time and cluster effects by bridging clusters together, for which we provide a case study. Our simulations show, with reasonable slicing width and angle, similar precision and similar or greater statistical power to detect year, cohort, within‐ and between‐individual effects when samples are sliced across batches, compared with strategies that aggregate longitudinal samples or use randomized allocation. While the best approach to analysing long‐term datasets depends on the structure of the data and questions of interest, it is vital to account for confounding among‐cluster and batch variation. Our slicing approach is simple to apply and creates the necessary statistical independence of batch and cluster from environmental or biological variables of interest. Crucially, it allows sequential analysis of samples and flexible inclusion of current data in later analyses without completely confounding the analysis. Our approach maximizes the scientific value of every sample, as each will optimally contribute to unbiased statistical inference from the data. Slicing thereby maximizes the power of growing biobanks to address important ecological, epidemiological and evolutionary questions.
PENGARUH MEDIA SOSIAL TERHADAP KEPUTUSAN PEMBELIAN MELALUI MOTIVASI KONSUMEN PADA PRODUK FAST FASHION

Perkembangan motivasi belanja konsumen ter­ha­dap produk fashion di­dukung oleh perkembangan media so­sial. Di sisi lain pengambilan keputusan pe­m­­­­­­­­­belian dalam fashion sangat dipengaruhi oleh in­for­masi dan sumber yang tersedia di masyarakat. Penelitian ini bertujuan un­tuk me­nge­tahui pe­­ngaruh dari media sosial terhadap ke­pu­tusan pembelian melalui motivasi kon­sumen pa­da produk fast fashion . Penelitian ini menggu­nakan metode kuantitatif. Sebanyak 100 res­pon­den ditentukan dengan menggunakan purposive sam­­pling . Da­ta di­kum­pul­kan meng­gu­nakan ang­ket serta diolah meng­gu­­nakan partial least square . Ha­sil penelitian menunjukkan bah­wa media sos­i­al berpengaruh pada keputusan pembelian, dan motivasi konsumen ber­pe­nga­ruh signifikan ter­­­hadap ke­pu­tusan pembelian produk fast fas­hion
Diversity patterns of the terrestrial snail fauna of Nyungwe Forest National Park (Rwanda), a Pleistocene refugium in the heart of Africa

We investigated the land snail fauna of Nyungwe Forest National Park in south-western Rwanda. Fifty plots at altitudes between 1718 and 2573 m were studied. In total, 3461 specimens were collected and were assigned to 102 land snail species. With respect to land snail species, Nyungwe Forest is the richest forest known in Africa. A comparison with other forests in the northern Albertine Rift indicates that land snail species richness in this region is significantly correlated with distance from Pleistocene forest refugia. The high beta diversity in Nyungwe is the result of a high species turnover between sites, which has biogeographical and ecological origins. Nyungwe Forest is situated on the Congo–Nile divide where species of different geographical origin may meet. Moreover, Nyungwe Forest offers a high diversity of habitats because it extends across a wide range of altitudinal zones. Species richness decreased with increasing altitude. It was also correlated with the presence of bare rocks that offer additional microhabitats and shelter. Although the occurrences of different land snail species in Nyungwe Forest were significantly clustered, only a minority of the species could be assigned to a group of species with similar occurrences. The majority of the species respond individualistically to environmental variables. The significant nestedness of the occurrences of the land snail species in Nyungwe was mainly correlated with altitude. © 2015 The Linnean Society of London, Biological Journal of the Linnean Society, 2015, 114, 363–375.
The efficacy of botanical protectants in the storage of cocoyam (Colocasia esculenta (L) Schott).

Aqueous extracts made from Ocimum basilium L. , Vernonia amygdalina Del. , Azadirachta indica L. and Carica papaya L. at different concentrations (150g/l and 300g/l) were used to study their effects on corm fresh weight loss, rotting and sprouting of two cocoyam varieties (Colocasia esculenta var. “Ede Ofe” and var. Ugwuta”). All the aqueous extracts at both 150g/I and 300g/I reduced fresh weight loss and rotting of corms in both varieties better than in water control. O. basilium L. at both 150g/I and 300g/I significantly reduced fresh weight loss and rotting of corms in both varieties compared to all other extracts and also promoted higher sprouting in both varieties at 300g/l. C. esculenta var. “Ede ofe” had less weight loss, rotting of corms (i. e. were more storable) and less sprouting than C. esculenta var. “Ugwuta”. Agro-Science Vol. 7 (2) 2008: pp. 93-98