Miracle-dz/UniFAR-FTUs huggingface dataset:
Cloud application logging for forensics

Logs are one of the most important pieces of analytical data in a cloud-based service infrastructure. At any point in time, service owners and operators need to understand the status of each infrastructure component for fault monitoring, to assess feature usage, and to monitor business processes. Application developers, as well as security personnel, need access to historic information for debugging and forensic investigations. This paper discusses a logging framework and guidelines that provide a proactive approach to logging to ensure that the data needed for forensic investigations has been generated and collected. The standardized framework eliminates the need for logging stakeholders to reinvent their own standards. These guidelines make sure that critical information associated with cloud infrastructure and software as a service (SaaS) use-cases are collected as part of a defense in depth strategy. In addition, they ensure that log consumers can effectively and easily analyze, process, and correlate the emitted log records. The theoretical foundations are emphasized in the second part of the paper that covers the implementation of the framework in an example SaaS offering running on a public cloud service. While the framework is targeted towards and requires the buy-in from application developers, the data collected is critical to enable comprehensive forensic investigations. In addition, it helps IT architects and technical evaluators of logging architectures build a business oriented logging framework.
Invasive lionfish : a guide to control and management

EXTENDED ABSTRACT The countries of the Wider Caribbean with their vibrant coral reefs are major tourist destinations bringing billions of dollars to the Caribbean annually. The importance of reef resources is invaluable to local economies and cultures. Invasive Alien Species (IAS) are considered one of the major threats to native species and habitats in the Caribbean. Recognizing the urgency of the lionfish invasion and the need to develop clear recommendations for local control, a special workshop was organized by an international team including the International Coral Reef Initiative, REEF, NOAA, and SPAW-RAC in August 2010 in Cancun, Mexico. With 47 participants representing over 25 organizations from 20 countries and territories of the Wider Caribbean, this workshop identified many of the best strategies for addressing the lionfish invasion. The results of this workshop have been published — Invasive Lionfish: A Guide to Control and Management — Gulf and Caribbean Fisheries Institute Special Publication Series Number 1 (English) and Number 2 (Spanish). The Guide includes:  Chapter One — The Lionfish Invasion: Past, Present, and Future — J. Morris  Chapter Two — Lionfish Research: Current Findings and Remaining Questions — J. Morris and S. Green  Chapter Three — Education and Outreach: Building Support and Expertise — J.L. Akins  Chapter Four — Control Strategies: Tools and Techniques for Local Control — J.L. Akins  Chapter Five — Monitoring: An Essential Action — S. Green  Chapter Six — Legal and Regulatory Considerations for Lionfish Management — D. St. A. Buddo  Chapter Seven — Resources, Partnerships, and Sustainable Funding — R. Gomez Lozano
Experimental Investigation of Nanoparticle Adsorption and Pore Blockage in Intermediate Wet Berea Sandstone

The global demand of energy is increasing with the growing population, and an increased consumption of available resources is therefore required. Even though there has been more focus on renewable energy over the last years, oil is still the main source of energy worldwide (IEA and OECD, 2016). Thus, continued oil extraction is necessary to satisfy the growing energy demand until it can be replaced by renewable alternatives. Since oil is non-renewable, the production must be maintained by either discovering new hydrocarbon reservoirs, or by improving the oil recovery in the reservoirs. Conventional production methods are seldom capable of producing more than 40 % of the reservoir oil (Schlumberger, 1998d), which means that there is a large potential for enhanced the oil recovery (EOR). The use of nanotechnology is beneficial in a range of fields, and its applications have also been suggested for the upstream sector of the petroleum industry (Lau et al., 2016). Silica (SiO2) nanoparticles have proved to be efficient for EOR in a range of laboratory core floods (Hendraningrat et al., 2012; Li et al., 2013; Ogolo et al., 2012; El-Diasty, 2015), and a combination of rock wettability alteration and reduction of interfacial tension (IFT) between oil and water are believed to be the main oil displacement mechanisms. Since silica nanoparticles consist of 99.8% SiO2 (Evonik, 2015), which is the main mineral in sandstone, they are are also considered environmentally friendly. This solves the legality issues related to field injection of EOR formulations in countries with a strong environmental policy. However, silica nanoparticles are easily destabilized when they are dispersed in saltwater and exposed to high temperature, which are regular sub-surface conditions. In this master’s thesis, I have looked at the EOR potential of nanofluids and the technical feasibility of field implementations. Laboratory experiments have been conducted to investigate the propagation of silica nanoparticles at various conditions, as this is important for the feasibility of field implementations. The nanoparticles were injected in intermediate wet Berea sandstone cores, since these were believed to represent many of the
Finding interesting correlations with conditional heavy hitters

The notion of heavy hitters-items that make up a large fraction of the population - has been successfully used in a variety of applications across sensor and RFID monitoring, network data analysis, event mining, and more. Yet this notion often fails to capture the semantics we desire when we observe data in the form of correlated pairs. Here, we are interested in items that are conditionally frequent: when a particular item is frequent within the context of its parent item. In this work, we introduce and formalize the notion of Conditional Heavy Hitters to identify such items, with applications in network monitoring, and Markov chain modeling. We introduce several streaming algorithms that allow us to find conditional heavy hitters efficiently, and provide analytical results. Different algorithms are successful for different input characteristics. We perform experimental evaluations to demonstrate the efficacy of our methods, and to study which algorithms are most suited for different types of data.
The Relation Among Gonadal Steroids, Immunocompetence, Body Mass, And Behavior in Young Black‐Headed Gulls (Larus Ridibundus)

We experimentally examined the effect of testosterone on the antibody response to a single immunization with sheep red blood cells in young black‐headed gulls. This species performs a number of testosterone‐mediated elaborate postural displays in social interactions and breeds in dense colonies in which there is a high likelihood of infectious diseases. In young chicks, only one‐third were capable of responding to immunization. In the responding chicks, testosterone enhanced antibody titers. Even when antibody responsiveness was measured >1 mo after the termination of hormonal treatment, antibody responses were enhanced in birds treated with androgen but not estrogen. At 9 mo of age, all birds responded to immunization, but there was no effect of testosterone on antibody titers. In these juveniles, frequency of display behavior was negatively related to changes in body mass, which suggests that displaying is energetically costly. Despite decreased body mass, antibody titers were highest in birds that displayed more frequently. This suggests that displaying signals immunocompetence. The results are discussed in relation to the immunocompetence handicap hypothesis and to what is known of the influence of the bursa of Fabricius and social stress on antibody production.
DNA barcodes reveal species-specific mercury levels in tuna sushi that pose a health risk to consumers

Excessive ingestion of mercury—a health hazard associated with consuming predatory fishes—damages neurological, sensory-motor and cardiovascular functioning. The mercury levels found in Bigeye Tuna (Thunnus obesus) and bluefin tuna species (Thunnus maccoyii, Thunnus orientalis, and Thunnus thynnus), exceed or approach levels permissible by Canada, the European Union, Japan, the US, and the World Health Organization. We used DNA barcodes to identify tuna sushi samples analysed for mercury and demonstrate that the ability to identify cryptic samples in the market place allows regulatory agencies to more accurately measure the risk faced by fish consumers and enact policies that better safeguard their health.
Study on novel control strategy in matrix converter motor system

In order to solve the problem of the industrial application of Matrix Converter (MC), the Matrix Converter Motor System (MCMS) is proposed. The control strategies of MCMS are studied based on the control of MC and the motor. The effects of voltage vector and direct torque control are analyzed. The new ameliorated control strategy is proposed.
A discrete firefly metaheuristic with local search for makespan minimization in permutation flow shop scheduling problems

Article history: Received 23 January 2010 Received in revised form 23 April 2010 Accepted 26 April 2010 Available online 26 April 2010 During the past two decades, there have been increasing interests on permutation flow shop with different types of objective functions such as minimizing the makespan, the weighted mean flow-time etc. The permutation flow shop is formulated as a mixed integer programming and it is classified as NP-Hard problem. Therefore, a direct solution is not available and metaheuristic approaches need to be used to find the near-optimal solutions. In this paper, we present a new discrete firefly meta-heuristic to minimize the makespan for the permutation flow shop scheduling problem. The results of implementation of the proposed method are compared with other existing ant colony optimization technique. The preliminary results indicate that the new proposed method performs better than the ant colony for some well known benchmark problems. © 2010 Growing Science Ltd. All rights reserved.
FAST VARIABILITY AND MILLIMETER/IR FLARES IN GRMHD MODELS OF Sgr A* FROM STRONG-FIELD GRAVITATIONAL LENSING

We explore the variability properties of long, high-cadence general relativistic magnetohydrodynamic (GRMHD) simulations across the electromagnetic spectrum using an efficient, GPU-based radiative transfer algorithm. We focus on both standard and normal evolution (SANE) and magnetically arrested disk (MAD) simulations with parameters that successfully reproduce the time-averaged spectral properties of Sgr A* and the size of its image at 1.3 mm. We find that the SANE models produce short-timescale variability with amplitudes and power spectra that closely resemble those inferred observationally. In contrast, MAD models generate only slow variability at lower flux levels. Neither set of models shows any X-ray flares, which most likely indicates that additional physics, such as particle acceleration mechanisms, need to be incorporated into the GRMHD simulations to account for them. The SANE models show strong, short-lived millimeter/infrared (IR) flares, with short (≲1 hr) time lags between the millimeter and IR wavelengths, that arise from the combination of short-lived magnetic flux tubes and strong-field gravitational lensing near the horizon. Such events provide a natural explanation for the observed IR flares with no X-ray counterparts.
Examination of a Remarkable Great Lake-Spawned Tornadic Supercell: The 2011 Goderich Ontario F3 Tornado Event

The Town of Goderich is located in southern Ontario, Canada, on the eastern shore of Lake Huron (Fig. 1a) and bills itself as ‘Canada’s prettiest town’. The terrain is relatively flat with the exception of a large 25 metre bluff along the lakeshore. Land use is primarily agricultural though Goderich (population approx. 8,000) does host a variety of industries including the world’s largest salt mining operation. Goderich was a planned town, beginning with a town square from which roadways radiated. This square became known for its numerous mature trees and historic buildings (Fig. 1b).
INSENS: Intrusion-Tolerant Routing in Wireless Sensor Networks

This paper describes an INtrusion-tolerant routing protocol for wireless SEnsor NetworkS (INSENS). INSENS constructs forwarding tables at each node to facilitate communication between sensor nodes and a base station. It minimizes computation, communication, storage, and bandwidth requirements at the sensor nodes at the expense of increased computation, communication, storage, and bandwidth requirements at the base station. INSENS does not rely on detecting intrusions, but rather tolerates intrusions by bypassing the malicious nodes. An important property of INSENS is that while a malicious node may be able to compromise a small number of nodes in its vicinity, it cannot cause widespread damage in the network. A prototype implementation in the ns2click simulator is presented to demonstrate and assess INSENS's tolerance to malicious attacks launched by intruder nodes in random and
Ordering Transactions with Prediction in Distributed Object Stores

In cloud-scale datacenters, it is common to shard (partition) data across large numbers of nodes. Atomic transactions are typically implemented by running transactions speculatively, and then certifying them, aborting ones that cause conflicts. However, in high contention scenarios, this approach has drawbacks: rather than achieving any substantial level of concurrency, it prevents concurrency by aborting all but one of the contending transactions. Our work explores a new option. We employ prediction, ordering transactions in advance based on the objects they are likely to access, providing ACID transactions in a Resilient Archive with Independent Nodes (ACID-RAIN). This preliminary ordering decreases abort rate, and eliminates aborts in error-free executions. To allow fast recovery from failures our scheme does not introduce any locks. The system consistency and durability rely on a single scalable tier of highly-available independent logs. Simulations using the Transactional-YCSB workloads show the scalability and benefits of ACID-
Combining wavelet and fractal coding for 3-D video coding

For low bit rates the visual quality of coded image sequences is more important than objective PSNR error measures. Especially at very low bit rates standard transform coding based methods like H.261 and MPEG suffer from annoying blocking artifacts. Wavelet-based coding schemes using overlapping basis functions avoid these blocking artifacts. At sharp edges however, ringing artifacts become visible. Well designed fractal coders are able to preserve sharp edges even at very low bit rates. But due to the block based algorithm of conventional fractal coders blocking artifacts cannot be avoided. In order to combine the advantages of wavelet and fractal coding, we propose a coding scheme that uses a hybrid approximation of "video cubes" in the 3-D wavelet domain. The combination of a 3-D fractal approximation and a direct encoding of the 3-D wavelet coefficients allows to exploit inter and intra redundancy of the video cubes. The use of smooth wavelet basis functions leads to sharper edges without blocking artifacts even at very low bit rates.
A low power 12-bit 40MS/s pipelined ADC with digital calibration

This paper presents a 12-bit 40 MS/s pipelined ADC fabricated in a 0.18 mum CMOS process. A simple open-loop residue amplifier is used in first stage to reduce power dissipation and increase circuit speed. The errors caused from open-loop amplifier are evaluated and calibrated by a statistics-based background calibration technology. A new circuit topology of open-loop amplifier is presented in this paper in order to achieve low-voltage and low-power requirements. Also, a proposed (1+1)-bit/stage structure for pipelined ADC is used to convert residue voltage that may exceed the convert range of the ADC. The active area of the ADC is 3.2times3. 7 mm2 and the power consumption equals 210 mW from a 1.8-V supply.
Biomarkers on patient T cells diagnose active tuberculosis and monitor treatment response.

BACKGROUND The identification and treatment of individuals with tuberculosis (TB) is a global public health priority. Accurate diagnosis of pulmonary active TB (ATB) disease remains challenging and relies on extensive medical evaluation and detection of Mycobacterium tuberculosis (Mtb) in the patient's sputum. Further, the response to treatment is monitored by sputum culture conversion, which takes several weeks for results. Here, we sought to identify blood-based host biomarkers associated with ATB and hypothesized that immune activation markers on Mtb-specific CD4+ T cells would be associated with Mtb load in vivo and could thus provide a gauge of Mtb infection. METHODS Using polychromatic flow cytometry, we evaluated the expression of immune activation markers on Mtb-specific CD4+ T cells from individuals with asymptomatic latent Mtb infection (LTBI) and ATB as well as from ATB patients undergoing anti-TB treatment. RESULTS Frequencies of Mtb-specific IFN-γ+CD4+ T cells that expressed immune activation markers CD38 and HLA-DR as well as intracellular proliferation marker Ki-67 were substantially higher in subjects with ATB compared with those with LTBI. These markers accurately classified ATB and LTBI status, with cutoff values of 18%, 60%, and 5% for CD38+IFN-γ+, HLA-DR+IFN-γ+, and Ki-67+IFN-γ+, respectively, with 100% specificity and greater than 96% sensitivity. These markers also distinguished individuals with untreated ATB from those who had successfully completed anti-TB treatment and correlated with decreasing mycobacterial loads during treatment. CONCLUSION We have identified host blood-based biomarkers on Mtb-specific CD4+ T cells that discriminate between ATB and LTBI and provide a set of tools for monitoring treatment response and cure. TRIAL REGISTRATION Registration is not required for observational studies. FUNDING This study was funded by Emory University, the NIH, and the Yerkes National Primate Center.
A Survey of Emergent Behavior and Its Impacts in Agent-based Systems

Increasingly, software agents are evolving from the roles of facilitators into decision-makers in managing complex, real-time systems such as logistics enterprise. Emergent behavior is that which is not attributed to any individual (agent), but is a global outcome of individual (agent) coordination. While agent's degree of autonomy and responsibility will continue to increase with time, the impact of emergent behavior in agent system on the performance and stability of these systems become an important issue. We found that emergent behavior is a major concern of potential users while we try to apply agent technology to such industry areas as transportation planning and logistics coordination. To really make agent technology work in industry convincingly, it is valuable to do a study of emergent behaviour and its impacts to the application of agent technology. This paper reviews the research on emergent behaviour, discuss its research challenge and application impact, and suggest research directions on agent emergent behaviour.
Defining an Ecologically Ideal Shallow Groundwater Depth for Regional Sustainable Management: Conceptual Development and Case Study on the Sanjiang Plain, Northeast China

The depth and fluctuation of shallow groundwater influence water supply to land surface vegetation. Knowledge of an ecologically ideal depth range of shallow groundwater for a vegetation ecosystem can be crucial for sustainability of regional water resource management and ecological conservation. In this study, we developed a conceptual model that identifies an upper and a lower boundary of shallow groundwater for sustaining present vegetation ecosystems, termed ecologically ideal shallow groundwater depth (EISGD). We then applied the conceptual model to the Sanjiang Plain (10.9 × 104 km2) in northeast China in order to gain insights into sustainable shallow groundwater usage in this intensively irrigated agricultural region. Using soil capillary rise, plant rooting depth, extinction depth, and the actual groundwater depth, we identified an upper boundary range of EISGD between 0.5 and 2.8 m and a lower boundary range of EISGD between 2.0 and 14.3 m for different vegetation covers in the Sanjiang Plain. Based on the ranges, we estimated allowable shallow groundwater withdrawal (i.e., without degrading the present vegetation ecosystem) for the region and identified an area of 2.54 × 1010 m2 with a total of 9.14 × 108 m3 water deficit. Currently, the entire Sanjiang Plain has a total volume of 45.30 × 108 m3 EISGD allowable shallow groundwater withdrawal, thus the plain’s northeast region can be considered as having a high allowable pumping capacity. This study demonstrates that application of an EISGD concept can be useful for developing regional management strategies and plans for ecological protection and sustainable groundwater utilization.
Design and fabrication of plasmonic nanostructures for spectroscopic applications

This work is focused on the design and fabrication of plasmonic nanostructures for spectroscopic applications. Our goal is to fabricate large-surface-area plasmonic nanostructures that provide local enhancement of electromagnetic fields for applications in fluorescence and Raman scattering spectroscopy. Periodic two-dimensional arrays of nanogrooves and nanopillars are obtained by holographic photolithography that makes use of surface relief gratings on azo-polymer films. Numerical calculations are performed to optimize the geometrical and material parameters of the structures in order to maximize the field enhancement factor.
UdS-Sant: English–German Hybrid Machine Translation System

This paper describes the UdS-Sant English‐German Hybrid Machine Translation (MT) system submitted to the Translation Task organized in the Workshop on Statistical Machine Translation (WMT) 2015. Our proposed hybrid system brings improvements over the baseline system by incorporating additional knowledge such as extracted bilingual named entities and bilingual phrase pairs induced from example-based methods. The reported final submission is the result of a hybrid system obtained from confusion network based system combination that combines the best performance of each individual system in a multi-engine pipeline.
Habitat Suitability and Distribution Models: With Applications in R

This book introduces the key stages of niche- based habitat suitability model building, evaluation and prediction required for understanding and predicting future patterns of species and biodiversity. Beginning with the main theory behind ecological niches and species distributions, the book proceeds through all major steps of model building, from conceptualization and model training to model evaluation and spatio- temporal predictions. Extensive examples using R support graduate students and researchers in quantifying ecological niches and predicting species distributions with their own data, and help to address key environmental and conservation problems. Reflecting this highly active field of research, the book incorporates the latest developments from informatics and statistics, as well as using data from remote sources such as satellite imagery. A website at www.unil. ch/ hsdm contains the codes and supporting material required to run the examples and teach courses. All three authors are recognized specialists of and have contributed substantially to the development of spatial prediction methods for species’ habitat suitability and distribution modeling. They published a large number of papers, overall cumulating tens of thousands of citations, and are ISI Highly Cited Researchers.