bluuebunny/crossref_metadata_2025 huggingface dataset:
Geostatistical and Statistical Classification of Sea-Ice Properties and Provinces from SAR Data
Authors: Herzfeld Ute , Williams Scott , Heinrichs John , Maslanik James , Sucht Steven
Published: July 2016

Recent drastic reductions in the Arctic sea-ice cover have raised an interest in understanding the role of sea ice in the global system as well as pointed out a need to understand the physical processes that lead to such changes. Satellite remote-sensing data provide important information about remote ice areas, and Synthetic Aperture Radar (SAR) data have the advantages of penetration of the omnipresent cloud cover and of high spatial resolution. A challenge addressed in this paper is how to extract information on sea-ice types and sea-ice processes from SAR data. We introduce, validate and apply geostatistical and statistical approaches to automated classification of sea ice from SAR data, to be used as individual tools for mapping sea-ice properties and provinces or in combination. A key concept of the geostatistical classification method is the analysis of spatial surface structures and their anisotropies, more generally, of spatial surface roughness, at variable, intermediate-sized scales. The geostatistical approach utilizes vario parameters extracted from directional vario functions, the parameters can be mapped or combined into feature vectors for classification. The method is flexible with respect to window sizes and parameter types and detects anisotropies. In two applications to RADARSAT and ERS-2 SAR data from the area near Point Barrow, Alaska, it is demonstrated that vario-parameter maps may be utilized to distinguish regions of different sea-ice characteristics in the Beaufort Sea, the Chukchi Sea and in Elson Lagoon. In a third and a fourth case study the analysis is taken further by utilizing multi-parameter feature vectors as inputs for unsupervised and supervised statistical classification. Field measurements and high-resolution aerial observations serve as basis for validation of the geostatistical-statistical classification methods. A combination of supervised classification and vario-parameter mapping yields best results, correctly identifying several sea-ice provinces in the shore-fast ice and the pack ice. Notably, sea ice does not have to be static to be classifiable with respect to spatial structures. In consequence, the geostatistical-statistical classification may be applied to detect changes in ice dynamics, kinematics or environmental changes, such as increased melt ponding, increased snowfall or changes in the equilibrium line.
Starobinsky-Like Inflation and Running Vacuum in the Context of Supergravity
Authors: Basilakos Spyros , Mavromatos Nick , Solà Joan
Published: July 2016

We describe the primeval inflationary phase of the early Universe within a quantum field theoretical (QFT) framework that can be viewed as the effective action of vacuum decay in the early times. Interestingly enough, the model accounts for the “graceful exit” of the inflationary phase into the standard radiation regime. The underlying QFT framework considered here is supergravity (SUGRA), more specifically an existing formulation in which the Starobinsky-type inflation (de Sitter background) emerges from the quantum corrections to the effective action after integrating out the gravitino fields in their (dynamically induced) massive phase. We also demonstrate that the structure of the effective action in this model is consistent with the generic idea of re-normalization group (RG) running of the cosmological parameters; specifically, it follows from the corresponding RG equation for the vacuum energy density as a function of the Hubble rate, ρ Λ ( H ) . Overall, our combined approach amounts to a concrete-model realization of inflation triggered by vacuum decay in a fundamental physics context, which, as it turns out, can also be extended for the remaining epochs of the cosmological evolution until the current dark energy era.
Leptin-Induced JAK/STAT Signaling and Cancer Growth
Authors: Mullen McKay , Gonzalez-Perez Ruben
Published: July 2016

Growth factor and cytokine signaling can influence the development of several cancer types. One of the key players in the development of cancer is the Janus kinas (JAK) signal transducer of activators of transcription (STAT) signaling pathway. The majority of growth factors and cytokine interactions with their membrane-bound receptors trigger JAK-STAT activation. The influential relationship between obesity and cancer is a fact. However, there is a complex sequence of events contributing to the regulation of this mechanism to promote tumor growth, yet to be fully elucidated. The JAK-STAT pathway is influenced by obesity-associated changes that have been shown to impact cancer growth and progression. This intricate process is highly regulated by a vast array of adipokines and cytokines that exert their pleiotropic effects on cancer cells to enhance metastasis to distant target sites. Leptin is a cytokine, or more precise, an adipokine secreted mainly by adipose tissue that requires JAK-STAT activation to exert its biological functions. Leptin is the central regulator of energy balance and appetite. Leptin binding to its receptor OB-R in turn activates JAK-STAT, which induces proliferation, angiogenesis, and anti-apoptotic events in normal cells and malignant cells expressing the receptor. Leptin also induces crosstalk with Notch and IL-1 (NILCO), which involves other angiogenic factors promoting tumor growth. Therefore, the existence of multiple novel classes of therapeutics that target the JAK/STAT pathway has significant clinical implications. Then, the identification of the signaling networks and factors that regulate the obesity-cancer link to which potential pharmacologic interventions can be implemented to inhibit tumor growth and metastasis. In this review, we will discuss the specific relationship between leptin-JAK-STAT signaling and cancer.
Catalytic Chan–Lam coupling using a ‘tube-in-tube’ reactor to deliver molecular oxygen as an oxidant
Authors: Mallia Carl J , Burton Paul M , Smith Alexander M R , Walter Gary C , Baxendale Ian R
Published: July 2016

A flow system to perform Chan–Lam coupling reactions of various amines and arylboronic acids has been realised employing molecular oxygen as an oxidant for the re-oxidation of the copper catalyst enabling a catalytic process. A tube-in-tube gas reactor has been used to simplify the delivery of the oxygen accelerating the optimisation phase and allowing easy access to elevated pressures. A small exemplification library of heteroaromatic products has been prepared and the process has been shown to be robust over extended reaction times.
FOUR DUAL AGN CANDIDATES OBSERVED WITH THE VLBA
Authors: Gabányi K. É. , An T. , Frey S. , Komossa S. , Paragi Z. , Hong X.-Y. , Shen Z.-Q.
Published: July 2016

According to hierarchical structure formation models, merging galaxies are expected to be seen in different stages of coalescence. However, there are currently no straightforward observational methods to either select or to confirm a large number of dual active galactic nucleus (AGN) candidates. Most attempts involve obtaining a better understanding of double-peaked narrow emission line sources, in order to distinguish the objects for which the emission lines originate from narrow-line kinematics or jet-driven outflows, from those which might harbor dual AGNs. We observed four such candidate sources with the Very Long Baseline Array (VLBA), at 1.5 GHz with a ∼10 mas angular resolution, for which the spectral profiles of AGN optical emission suggested the existence of dual AGNs. In SDSS J210449.13–000919.1 and SDSS J23044.82–093345.3 the radio structures are aligned with the optical emission features, thus the double-peaked emission lines might be the results of jet-driven outflows. In the third detected source SDSS J115523.74+150756.9, the radio structure is less extended and is oriented nearly perpendicular to the position angle derived from optical spectroscopy. The fourth source remained undetected with the VLBA, but it was imaged with the Very Large Array at arcsec resolution a few months before our observations, suggesting the existence of an extended radio structure. We did not detect two radio-emitting cores in any of the four sources, a convincing signature of duality.
THE SPECTACULAR RADIO-NEAR-IR-X-RAY JET OF 3C 111: THE X-RAY EMISSION MECHANISM AND JET KINEMATICS
Authors: Clautice Devon , Perlman Eric S. , Georganopoulos Markos , Lister Matthew L. , Tombesi Francesco , Cara Mihai , Marshall Herman L. , Hogan Brandon , Kazanas Demos
Published: July 2016

Relativistic jets are the most energetic manifestation of the active galactic nucleus (AGN) phenomenon. AGN jets are observed from the radio through gamma-rays and carry copious amounts of matter and energy from the sub-parsec central regions out to the kiloparsec and often megaparsec scale galaxy and cluster environs. While most spatially resolved jets are seen in the radio, an increasing number have been discovered to emit in the optical/near-IR and/or X-ray bands. Here we discuss a spectacular example of this class, the 3C 111 jet, housed in one of the nearest, double-lobed FR II radio galaxies known. We discuss new, deep Chandra and Hubble Space Telescope (HST) observations that reveal both near-IR and X-ray emission from several components of the 3C 111 jet, as well as both the northern and southern hotspots. Important differences are seen between the morphologies in the radio, X-ray, and near-IR bands. The long (over 100 kpc on each side), straight nature of this jet makes it an excellent prototype for future, deep observations, as it is one of the longest such features seen in the radio, near-IR/optical, and X-ray bands. Several independent lines of evidence, including the X-ray and broadband spectral shape as well as the implied velocity of the approaching hotspot, lead us to strongly disfavor the EC/CMB model and instead favor a two-component synchrotron model to explain the observed X-ray emission for several jet components. Future observations with NuSTAR, HST, and Chandra will allow us to further constrain the emission mechanisms.
UNVEILING THE GAMMA-RAY SOURCE COUNT DISTRIBUTION BELOW THE FERMI DETECTION LIMIT WITH PHOTON STATISTICS
Authors: Zechlin Hannes-S. , Cuoco Alessandro , Donato Fiorenza , Fornengo Nicolao , Vittino Andrea
Published: July 2016

The source-count distribution as a function of their flux,

, is one of the main quantities characterizing gamma-ray source populations. We employ statistical properties of the Fermi Large Area Telescope (LAT) photon counts map to measure the composition of the extragalactic gamma-ray sky at high latitudes (

°) between 1 and 10 GeV. We present a new method, generalizing the use of standard pixel-count statistics, to decompose the total observed gamma-ray emission into (a) point-source contributions, (b) the Galactic foreground contribution, and (c) a truly diffuse isotropic background contribution. Using the 6 yr Fermi-LAT data set (P7REP), we show that the

distribution in the regime of so far undetected point sources can be consistently described with a power law with an index between 1.9 and 2.0. We measure

down to an integral flux of

improving beyond the 3FGL catalog detection limit by about one order of magnitude. The overall

distribution is consistent with a broken power law, with a break at

The power-law index

for bright sources above the break hardens to

for fainter sources below the break. A possible second break of the

distribution is constrained to be at fluxes below

at 95% confidence level. The high-latitude gamma-ray sky between 1 and 10 GeV is shown to be composed of ∼25% point sources, ∼69.3% diffuse Galactic foreground emission, and ∼6% isotropic diffuse background.
Une diplomatie charitable ? Léon XIII, la France et les soldats italiens prisonniers en Éthiopie (1896)
Authors: Cavagnini Giovanni
Published: July 2016

Cet article se focalise sur la démarche pontificale entreprise au lendemain de la bataille d’Adoua (1896) pour libérer les presque 2 000 soldats italiens capturés par les Éthiopiens. Avec le soutien de la France, Léon XIII chargea Mgr Cyrille Macaire, vicaire patriarcal des coptes d’Alexandrie, d’aller à Addis Abeba et de convaincre le Négus Ménélik, ce qui devait avoir un immense écho, aidant à détendre les relations entre le Royaume d’Italie et le Saint-Siège. Les problèmes logistiques et l’hostilité de l’Italie causèrent l’échec de la mission pontificale, qui mit pourtant en lumière la volonté de Léon XIII de retrouver le prestige perdu après la fin de son pouvoir temporel, en jouant le rôle de médiateur « charitable » entre les Puissances.
Effect of processing, packaging and storage-temperature based hurdles on the shelf stability of sautéed ready-to-eat Ruspolia nitidula
Authors: Ssepuuya G. , Aringo R.O. , Mukisa I.M. , Nakimbugwe D.
Published: July 2016

Ruspolia nitidula (an edible grasshopper) is a seasonal delicacy in Uganda and its neighbouring countries, with a postharvest shelf stability of 1-2 days. Our previous processing research increased the shelf stability of ready-to-eat R. nitidula to 12 weeks at ambient temperature. However, there is need to double the shelf-life to cover the 20-24 weeks between swarming seasons and, increase the efficiency and cost effectiveness of the processing and packaging techniques developed. This research investigated the effectiveness of 9 preservation hurdles on the microbial (total plate count), sensorial (overall acceptability) and chemical (acid value, peroxide value and thio-barbituric acid value) stability of ready-to-eat R. nitidula. Chilled storage and ambient temperature storage of the vacuum packed product increased the shelf stability of R. nitidula from 12 to 22 weeks. After 22 weeks of storage, the products had an overall acceptability of 6-7 on a 9-point hedonic scale, a total plate count of <4 log cfu/g, an acid value of approximately <1 mg KOH/g, a peroxide value of <21.50 meq O2/kg and a thio-barbituric value of <0.079. Either chilled storage or vacuum packaging are suitable means of preserving dried ready-to-eat edible grass hoppers and can be used depending on availability. Further research into increasing the shelf stability of R. nitidula at room temperature will be very beneficial to its commercialisation.
Hip Pain After a Femoral Fracture: It Is Not Always Related to the Implant
Authors: White Brian J. , Hawkes Tara K. , Herzog Mackenzie M.
Published: July 2016

The source of continued hip pain following fixation of traumatic femoral shaft fracture is not always clear. Intra-articular hip pathology is often overlooked when evaluating the etiology of residual pain. The purpose of this study was to describe cases of intra-articular hip pathology following traumatic femoral shaft fracture. This was a retrospective case series of patients presenting to a private practice orthopedic clinic from 2012 to 2015. Three patients presented with symptomatic intra-articular hip pathology following traumatic ipsilateral femoral shaft fracture. Patients who underwent hip arthroscopy with allograft labral reconstruction were identified retrospectively. Validated, subjective outcome scores administered included the Modified Harris Hip Score (MHHS), Lower Extremity Functional Scale (LEFS), visual analog scale (VAS) for pain, and VAS scale for patient satisfaction. Three patients were identified with residual, disabling groin pain after femoral shaft fracture fixation following a traumatic motor vehicle accident. All 3 patients were found to have a symptomatic ipsilateral labral tear. In 2 of the patients, an indentation on the lateral femoral head was appreciated, which was hypothesized to be caused by a subluxation event. All 3 patients were treated with arthroscopic hip surgery. At final follow-up, all 3 patients showed significant improvement in MHHS, VAS pain scores, level of satisfaction, and LEFS. Residual pain following ipsilateral femoral shaft fracture is not always related to implant. Intra-articular hip pathology should be considered in patients with lingering hip pain. [
Orthopedics.
2016; 39(6):e1080–e1084.]
Strategies to Enhance Success Among Dual-Specialty Students in Advanced Practice Nursing Programs
Authors: Wilbeck Jennifer , Collins Michelle , Reeves Geri , Downes Elizabeth
Published: July 2016

Background:

In attempts to simultaneously address the 2008 Consensus model and meet the growing need for advanced practice nurses with a robust scope of practice, some schools of nursing offer dual advanced practice nursing (APN) programs.

Method:

Built on the successes of multiple dual programs at two universities, this article provides specific practice strategies to enhance academic success among students and faculty in dual-specialty APN programs.

Results:

Faculty- and student-led strategies are outlined, addressing the academic and professional aspects of the dual APN role. With implementation of these strategies, graduation and subsequent dual certification rates in these programs remains extremely high.

Conclusion:

Adaptation of these strategies to support student and faculty efforts can potentiate additional opportunities for successful dual APN programs. [
J Nurs Educ
. 2016;55(8):463–466.
Design of Head Movement Controller System (HEMOCS) for Control Mobile Application through Head Pose Movement Detection
Authors: Tolle Herman , Arai Kohei
Published: July 2016

Head movement has been found to be a natural way of interaction. It can be used as an alternative control method and provides accessibility for users when used in human computer interface solutions. The combination of Head-mounted displays (HMDs) with mobile devices, provide an innovation of new low cost of human-computer interaction. Such devices are hands-free systems. In this paper, we introduce a new method for recognizing head movement as the controller of mobile application and proposed a new control system using head movement only. The proposed method can determine specific head pose movement and respond it as a controller. The implementation of a music player application on an iOS devices shows that the proposed method is appropriate for a new experience of real-time human-computer interaction with head movement control only.
Usage of Smartphone Applications: A Descriptive Study of Top 100 U.S. Retailers
Authors: Koo Wanmo
Published: July 2016

The study investigated how top 100 U.S. retailers use their smartphone applications. Based on the literature, the study found five major functions of smartphone applications: content delivery, transaction, promotion, location service, and entertainment. Descriptive and frequency analyses revealed actual usage of the five functions among the top 100 U.S. retailers. Detailed implications for marketers were discussed based on the findings.
Image Representation, Filtering, and Natural Computing in a Multivalued Quantum System
Authors: Chakraborty Sanjay , Dey Lopamudra
Published: July 2016

Image processing on quantum platform is a hot topic for researchers now a day. Inspired from the idea of quantum physics, researchers are trying to shift their focus from classical image processing towards quantum image processing. Storing and representation of images in a binary and ternary quantum system is always one of the major issues in quantum image processing. This chapter mainly deals with several issues regarding various types of image representation and storage techniques in a binary as well as ternary quantum system. How image pixels can be organized and retrieved based on their positions and intensity values in 2-states and 3-states quantum systems is explained here in detail. Beside that it also deals with the topic that focuses on the clear filteration of images in quantum system to remove unwanted noises. This chapter also deals with those important applications (like Quantum image compression, Quantum edge detection, Quantum Histogram etc.) where quantum image processing associated with some of the natural computing techniques (like AI, ANN, ACO, etc.).
Evolutionary Computing to Examine Variation in Proteins with Evolution
Authors: Ray Sujay
Published: July 2016

Amino-acid sequences play a pivotal role for the structure of proteins. Alterations in a single amino-acid may vary the protein functioning. Alignment of sequences recognizes evolutionary and structurally related residues in a group of amino-acid sequences. It also aids to perceive the regions that are conserved throughout and are also functionally important. Although protein alignment issue has been studied in the past decades, but computational approaches serves as more accurate to investigate the entire process in a comparably lesser time. Evolutionary algorithms, more specifically, genetic algorithms are very beneficial. It leads to the global optimization of the protein after observance of “the fittest” among the rest. On global optimization, the protein tends to be more stable, thereby, helping the process of interactions among other stable proteins and provides a residue level study. Thus, this state-of-art can be implemented for alignment of macro-molecules, which serves as an essential criterion for further molecular level analyses.
Derivation and Simulation of an Efficient QoS Scheme in MANET through Optimised Messaging Based on ABCO Using QualNet
Authors: Das Abhijit , Chaudhuri Atal
Published: July 2016

Mobile Ad hoc Network or MANET is a collection of heterogeneous mobile nodes and is infrastructure-less by choice or by default. MANET is prone to confront a lot of challenges in designing a proper Quality of Service (QoS) model where transmission reliability has an important contrtibution. This chapter proposes an optimised message transmission scheme inspired by Artificial Bee Colony Optimisation (ABCO) technique. In this proposed scheme, QoS parameters that have been taken into consideration are throughput, delay, packet loss, and bandwidth utilisation. Here, three agents, namely message selection agent, message forwarding agent, and QoS factor calculating agent, have been introduced to govern and optimise the whole message transmission scheme. Through this method, a significant improvement in QoS factor can be achieved in comparison with the existing schemes. QualNet simulator has been used to evaluate the proposed concept.
Innovative Hierarchical Fuzzy Logic for Modelling Using Evolutionary Algorithms
Authors: Mohammadian M. , Stonier R. J.
Published: July 2016

This paper considers issues in the design and construction of a fuzzy logic system to model complex (nonlinear) systems. Several important applications are considered and methods for the decomposition of complex systems into hierarchical and multi-layered fuzzy logic sub-systems are proposed. The learning of fuzzy rules and internal parameters is performed using evolutionary computing. The proposed method using decomposition and conversion of systems into hierarchical and multi-layered fuzzy logic sub-systems reduces greatly the number of fuzzy rules to be defined and improves the learning speed for such systems. However such decomposition is not unique and may give rise to variables with no physical significance. This can raise then major difficulties in obtaining a complete class of rules from experts even when the number of variables is small. Application areas considered are: the prediction of interest rate, hierarchical control of the inverted pendulum, robot control, feedback boundary control for a distributed optimal control system and image processing.
Quantum Computing Based Technique for Cancer Disease Detection System
Authors: Chaturvedi Setu Kumar , Jain Milan
Published: July 2016

Barring any cancer prevention breakthroughs, the expansion of the aged population will likely increase number of older individuals diagnosed for cancer in the coming decades. Dimensions of the cancer burden and its devastating manner of challenge ahead are inferred in the context of with aging populations to underscore the possible increase that demographic factors may have on the magnitude of the cancer problem for older persons in the future years. Presently the detection procedure is very time consuming and not accurate, in this respect there is a need of more accurate, fast and efficient method through computing technologies. The present research work incorporates quantum computing with clustering algorithm i.e. Shor's algorithm of quantum computing with hierarchical clustering technique. Here adaptation of Shor's algorithm helps to increase accuracy, and hierarchical clustering technique helps to detect the stages of cancer.
Ultra High Frequency Sigmoid and Trigonometric Higher Order Neural Networks for Data Pattern Recognition
Authors: Zhang Ming
Published: July 2016

This chapter develops a new nonlinear model, Ultra high frequency siGmoid and Trigonometric Higher Order Neural Networks (UGT-HONN), for data pattern recognition. UGT-HONN includes Ultra high frequency siGmoid and Sine function Higher Order Neural Networks (UGS-HONN) and Ultra high frequency siGmoid and Cosine functions Higher Order Neural Networks (UGC-HONN). UGS-HONN and UGC-HONN models are used to recognition data patterns. Results show that UGS-HONN and UGC-HONN models are better than other Polynomial Higher Order Neural Network (PHONN) and Trigonometric Higher Order Neural Network (THONN) models, since UGS-HONN and UGC-HONN models to recognize data pattern with error approaching 0.0000%.
Higher Order Neural Network for Financial Modeling and Simulation
Authors: Mishra Partha Sarathi , Dehuri Satchidananda
Published: July 2016

Financial market creates a complex and ever changing environment in which population of investors are competing for profit. Predicting the future for financial gain is a difficult and challenging task, however at the same time it is a profitable activity. Hence, the ability to obtain the highly efficient financial model has become increasingly important in the competitive world. To cope with this, we consider functional link artificial neural networks (FLANNs) trained by particle swarm optimization (PSO) for stock index prediction (PSO-FLANN). Our strong experimental conviction confirms that the performance of PSO tuned FLANN model for the case of lower number of ahead prediction task is promising. In most cases LMS updated algorithm based FLANN model proved to be as good as or better than the RLS updated algorithm based FLANN but at the same time RLS updated FLANN model for the prediction of stock index system cannot be ignored.
Particle Swarm Optimization Algorithm as a Tool for Profiling from Predictive Data Mining Models
Authors: Klepac Goran
Published: July 2016

This chapter introduces the methodology of particle swarm optimization algorithm usage as a tool for finding customer profiles based on a previously developed predictive model that predicts events like selection of some products or services with some probabilities. Particle swarm optimization algorithm is used as a tool that finds optimal values of input variables within developed predictive models as referent values for maximization value of probability that customers select/buy a product or service. Recognized results are used as a base for finding similar profiles between customers. The presented methodology has practical value for decision support in business, where information about customer profiles are valuable information for campaign planning and customer portfolio management.
Application of Genetic Algorithms in Inventory Control
Authors: Mishra Vinod Kumar
Published: July 2016

The genetic algorithm (GA) is an adaptive heuristic search procedures based on the mechanics of natural selection and natural genetics. Inventory control is widely used in the area of mathematical sciences, management sciences; system science, industrial engineering, production engineering etc. but they have wide differences in mathematical and computation maturity. This chapter enables the reader to understand the basic theory of genetic algorithm and how to apply the genetic algorithms for optimizing the parameters in inventory control The current and future trend of the research with the definition of key terms of genetic algorithm has also incorporated in this chapter.
Utilizing Feature Selection on Higher Order Neural Networks
Authors: Zhao Zongyuan , Xu Shuxiang , Kang Byeong Ho , Kabir Mir Md Jahangir , Liu Yunling , Wasinger Rainer
Published: July 2016

Artificial Neural Network has shown its impressive ability on many real world problems such as pattern recognition, classification and function approximation. An extension of ANN, higher order neural network (HONN), improves ANN's computational and learning capabilities. However, the large number of higher order attributes leads to long learning time and complex network structure. Some irrelevant higher order attributes can also hinder the performance of HONN. In this chapter, feature selection algorithms will be used to simplify HONN architecture. Comparisons of fully connected HONN with feature selected HONN demonstrate that proper feature selection can be effective on decreasing number of inputs, reducing computational time, and improving prediction accuracy of HONN.
On the Accelerated Convergence of Genetic Algorithm Using GPU Parallel Operations
Authors: Li Cheng-Chieh , Liu Jung-Chun , Lin Chu-Hsing , Lo Winston
Published: July 2016

The genetic algorithm plays a very important role in many areas of applications. In this research, the authors propose to accelerate the evolution speed of the genetic algorithm by parallel computing, and optimize parallel genetic algorithms by methods such as the island model. The authors find that when the amount of population increases, the genetic algorithm tends to converge more rapidly into the global optimal solution; however, it also consumes greater amount of computation resources. To solve this problem, the authors take advantage of the many cores of GPUs to enhance computation efficiency and develop a parallel genetic algorithm for GPUs. Different from the usual genetic algorithm that uses one thread for computation of each chromosome, the parallel genetic algorithm using GPUs evokes large amount of threads simultaneously and allows the population to scale greatly. The large amount of the next generation population of chromosomes can be divided by a block method; and after independently operating in each block for a few generation, selection and crossover operations of chromosomes can be performed among blocks to greatly accelerate the speed to find the global optimal solution. Also, the travelling salesman problem (TSP) is used as the benchmark for performance comparison of the GPU and CPU; however, the authors did not perform algebraic optimization for TSP.
AI-Based Cyber Defense for More Secure Cyberspace
Authors: Bogatinov Dimitar Stevo , Bogdanoski Mitko , Angelevski Slavko
Published: July 2016

The growing network attacks and intrusions have put the government organizations at a great risk. In cyberspace, humans have great limitations in data analyze and cyber defense because of the amount of data they have to process and the limited response time. Considering these parameters one of the best solutions is when the cyber defense mechanisms are AI (Artificial intelligence)-based because they can easily determine and respond to the attacks that are underway. The responses can be easily managed using man in the loop or fully atomized techniques. This chapter gives brief review of the usage of artificial intelligence in support of cyber defense, explains some useful applications that already exist, emphasizing the neural nets, expert systems and intelligent agents in cyber defense. Furthermore the chapter will propose a technical AI-based cyber defense model which can support the governmental and non-governmental efforts against cyber threats and can improve the success against malicious attack in the cyberspace.
Green Computing and Its Impact
Authors: Singh Shailendra , Gond Sunita
Published: July 2016

The mission “Saving Earth” has become need of all of us to sustain life on the earth. There are many holistic approaches for Green Computing which impact on stack holders of the computing system including hardware, software and people. There are many reasons to develop green computing like environmental friendly, saving powers, long term profit, reduce pollution, power management and increasing performance etc. Approach to develop green computing can be broadly divided into four parts: hardware device manufacturing, software techniques, people awareness and standard policies.
Green and Energy-Efficient Computing Architecture for E-Learning
Authors: Palanivel K. , Kuppuswami S.
Published: July 2016

Information and Communication Technology (ICT) is one of the fast growing industries that facilitate many latest services to the users and therefore, the number of users is increasing rapidly. The usage of ICT and its life cycle produce hazardous substances that need to be addressed in efficient and green ways. The adoption of green computing involves many improvements and provide energy-efficiency services for data centers, power management and cloud computing. Cloud computing is a highly scalable and cost-effective infrastructure for running Web applications. However, the growing demand of Cloud infrastructure has drastically increased the energy consumption of data centers, which has become a critical issue. Hence, energy-efficient solutions are required to minimize the impact of Cloud environment. E-learning methodology is an example of Green computing. Thus, it is proposed a Green Cloud Computing Architecture for e-Learning Applications that can lower expenses and reduce energy consumption.
Adoption of Virtualization in Cloud Computing
Authors: Khan Nusratullah , Shah Asadulah , Nusratullah Kajal
Published: July 2016

There has been rapid expansion of the information technology due to contribution to emission of carbon dioxide. The cloud computing technology has been perceived to present solution to various studies that try to investigate on the most appropriate ways of reducing the carbon dioxide gas emissions. The current study aimed at investigating the adoption of virtualization in cloud computing as a means through which the green computing can be achieved. According to the paper virtualization among its many process helps in curtailing equipment required through cloud computing resources to facilitate adequate use of resources to make use of energy and assets.
New Genetic Operator (Jump Crossover) for the Traveling Salesman Problem
Authors: El Hassani Hicham , Benkachcha Said , Benhra Jamal
Published: July 2016

Inspired by nature, genetic algorithms (GA) are among the greatest meta-heuristics optimization methods that have proved their effectiveness to conventional NP-hard problems, especially the traveling salesman problem (TSP) which is one of the most studied supply chain management problems. This paper proposes a new crossover operator called Jump Crossover (JMPX) for solving the travelling salesmen problem using a genetic algorithm (GA) for near-optimal solutions, to conclude on its efficiency compared to solutions quality given by other conventional operators to the same problem, namely, Partially matched crossover (PMX), Edge recombination Crossover (ERX) and r-opt heuristic with consideration of computational overload. The authors adopt a low mutation rate to isolate the search space exploration ability of each crossover. The experimental results show that in most cases JMPX can remarkably improve the solution quality of the GA compared to the two existing classic crossover approaches and the r-opt heuristic.
Fine needle aspiration cytology of cervical lymph node involvement by ovarian serous borderline tumor
Authors: Chen Longwen , Butler Kristina A. , Bell Debra A.
Published: July 2016

Serous borderline tumor (SBT) involving a cervical lymph node is extremely rare. In addition, fine needle aspiration (FNA) cytology of the involved cervical lymph node shares tremendous morphologic similarity with other low-grade papillary carcinomas. Thus, it can be easily misdiagnosed as metastatic carcinoma. A 42-year-old female had a history of bilateral SBT and postbilateral salpingo-oophorectomy. She presented with left cervical lymphadenopathy 6 months later. FNA cytology showed a low-grade papillary neoplasm with psammoma bodies. Needle core biopsy along with immunostains was diagnostic of cervical lymph node involvement (LNI) of SBT. although extremely rare, cervical LNI can be found in patients with SBTs. FNA cytology, sometimes, is indistinguishable from metastatic papillary adenocarcinoma. Cell block or needle core biopsy is essential to make the correct diagnosis.
Asylum seekers and refugees in Indonesia: Problems and potentials
Authors: Briskman Linda Ruth , Fiske Lucy Imogen
Published: July 2016

Asylum seekers and refugees in Indonesia increasingly experience protracted waiting times for permanent settlement in other countries. They have few, if any, legal rights, coupled with extremely limited financial resources and no access to government provided services. In response to the prospect of living for many years in this difficult and liminal space, a small community of refugees in the West Java town of Cisarua has built relationships, skills and confidence among themselves and with host Indonesians to respond to identified needs. This paper outlines the main political and policy frameworks affecting the lives of refugees in Indonesia and then draws on research interviews and participant observation to illustrate the resilience and agency utilised by the community to mitigate uncertain futures. The major focus is on education for asylum seeker/refugee children.
Improved Methodologies for Continuous Flow Analysis of Stable
Water Isotopes in Ice Cores
Authors: Jones Tyler R. , White James W. C. , Steig Eric J. , Vaughn Bruce H. , Morris Valerie , Gkinis Vasileios , Markle Bradley R. , Schoenemann Spruce W.
Published: July 2016

Abstract. Water isotopes in ice cores are used as a climate proxy for local temperature and regional atmospheric circulation as well as evaporative conditions in moisture source regions. Traditional measurements of water isotopes have been achieved using magnetic sector isotope ratio mass spectrometry (IRMS). However, a number of recent studies have shown that laser absorption spectrometers (LAS) perform as well or better than IRMS. The new LAS technology has been combined with continuous flow analysis (CFA) to improve data density and sample throughput in numerous prior ice coring projects. Here, we present a comparable semi-automated LAS-CFA system for measuring high-resolution water isotopes of ice cores. We outline new methods for partitioning both system uncertainty and system mixing length into liquid and vapor components – useful measures for defining and improving the overall performance of the system. Critically, our methods take into account the uncertainty of depth registration that is not present in IRMS nor fully accounted for in other CFA studies. We also explain a method for introducing consecutive sections of isotopically distinct ice at the melt head to define the system-wide mixing length. These analyses are achieved using samples from a South Pole firn core, a Greenland ice core, and the WAIS Divide ice core. The measurement system utilizes a 16-position carousel contained in a freezer to consecutively deliver ~ 1 m × 1.3 cm2 ice sticks to a temperature controlled melt head, where the ice is converted to a continuous liquid stream, and eventually vaporized using a concentric nebulizer for isotopic analysis. An integrated delivery system for water isotope standards is used for calibration to the VSMOW-SLAP scale and depth registration is achieved using a precise overhead laser distance device with an uncertainty of ±0.2 mm. As an added check on our system, we perform inter-lab LAS comparisons using WAIS Divide ice samples, a corroboratory step not taken in prior CFA studies. The overall results are important for substantiating data obtained from LAS-CFA systems, including optimizing liquid and vapor mixing lengths, determining melt rates for ice cores with different accumulation and thinning histories, and removing system-wide mixing effects that are convolved with the natural diffusional signal that results primarily from water molecule diffusion in the firn column.
Optimization of Saturn paraboloid magnetospheric field model parameters
using Cassini equatorial magnetic field data
Authors: Belenkaya Elena S. , Kalegaev Vladimir V. , Cowley Stanley W. H. , Provan Gabrielle , Blokhina Marina S. , Barinov Oleg G. , Kirillov Alexander A. , Grigoryan Maria S.
Published: July 2016

Abstract. The paraboloid model of Saturn's magnetosphere describes the magnetic field as being due to the sum of contributions from the internal field of the planet, the ring current, and the tail current, all contained by surface currents inside a magnetopause boundary which is taken to be a paraboloid of revolution about the planet-Sun line. The parameters of the model have previously been determined by comparison with data from a few passes through Saturn's magnetosphere in compressed and expanded states, depending on the prevailing dynamic pressure of the solar wind. Here we significantly expand such comparisons through examination of Cassini magnetic field data from 18 near-equatorial passes that span wide ranges of local time, focusing on modelling the co-latitudinal field component that defines the magnetic flux passing through the equatorial plane. For 12 of these passes, spanning pre-dawn, via noon, to post-midnight, the spacecraft crossed the magnetopause during the pass, thus allowing an estimate of the concurrent subsolar radial distance of the magnetopause R1 to be made, considered to be the primary parameter defining the scale size of the system. The best-fit model parameters from these passes are then employed to determine how the parameters vary with R1, using least-squares linear fits, thus providing predictive model parameters for any value of R1 within the range. We show that the fits obtained using the linear approximation parameters are of the same order as those for the individually selected parameters. We also show that the magnetic flux mapping to the tail lobes in these models is generally in good accord with observations of the location of the open-closed field line boundary in Saturn's ionosphere, and the related position of the auroral oval. We then investigate the field data on six passes through the nightside magnetosphere, for which the spacecraft did not cross the magnetopause, such that in this case we compare the observations with three linear approximation models representative of compressed, intermediate, and expanded states. Reasonable agreement is found in these cases for models representing intermediate or expanded states.
Long-term drainage reduces CO2 uptake and increases CO2 emission
on a Siberian floodplain due to shifts in vegetation community and soil
thermal characteristics
Authors: Kwon Min Jung , Heimann Martin , Kolle Olaf , Luus Kristina A. , Schuur Edward A. G. , Zimov Nikita , Zimov Sergey A. , Göckede Mathias
Published: July 2016

Abstract. With increasing air temperatures and changing precipitation patterns forecast for the Arctic over the coming decades, the thawing of ice-rich permafrost is expected to increasingly alter hydrological conditions by creating mosaics of wetter and drier areas. The objective of this study is to investigate how 10 years of lowered water table depths of wet floodplain ecosystems would affect CO2 fluxes measured using a closed chamber system, focusing on the role of long-term changes in soil thermal characteristics and vegetation community structure. Drainage diminishes the heat capacity and thermal conductivity of organic soil, leading to warmer soil temperatures in shallow layers during the daytime and colder soil temperatures in deeper layers, resulting in a reduction in thaw depths. These soil temperature changes can intensify growing-season heterotrophic respiration by up to 95 %. With decreased autotrophic respiration due to reduced gross primary production under these dry conditions, the differences in ecosystem respiration rates in the present study were 25 %. We also found that a decade-long drainage installation significantly increased shrub abundance, while decreasing Eriophorum angustifolium abundance resulted in Carex sp. dominance. These two changes had opposing influences on gross primary production during the growing season: while the increased abundance of shrubs slightly increased gross primary production, the replacement of E. angustifolium by Carex sp.  significantly decreased it. With the effects of ecosystem respiration and gross primary production combined, net CO2 uptake rates varied between the two years, which can be attributed to Carex-dominated plots' sensitivity to climate. However, underlying processes showed consistent patterns: 10 years of drainage increased soil temperatures in shallow layers and replaced E. angustifolium by Carex sp., which increased CO2 emission and reduced CO2 uptake rates. During the non-growing season, drainage resulted in 4 times more CO2 emissions, with high sporadic fluxes; these fluxes were induced by soil temperatures, E. angustifolium abundance, and air pressure.
CH4 exchange at the forest floor of a forestry-drained fen: low flux rates but high temporal variation
Authors: Korkiakoski Mika , Koskinen Markku , Minkkinen Kari , Ojanen Paavo , Penttilä Timo , Rainne Juuso , Laurila Tuomas , Lohila Annalea
Published: July 2016

Abstract. We measured methane (CH4) exchange rates with automatic chambers at the forest floor of a nutrient-rich drained peatland in 2011–2013. The fen, located in southern Finland, was drained for forestry in the 1970s and the tree stand is now a mixture of Scots pine, Norway spruce and pubescent birch. Our measurement system consisted of six transparent polycarbonate chambers and stainless steel frames, positioned on a number of different field and moss layer types. Flux rates were calculated with both linear and exponential regression. The use of linear regression systematically underestimated CH4 flux rates by 20–50 % when compared to exponential regression. However, the use of exponential regression with small fluxes (
Leaf-scale experiments reveal important omission in the
Penman-Monteith equation
Authors: Schymanski Stanislaus J. , Or Dani
Published: July 2016

Abstract. The Penman-Monteith (PM) equation is commonly considered the most advanced physically based approach to computing transpiration rates from plants considering stomatal conductance and atmospheric drivers. It has been widely evaluated at the canopy scale, where aerodynamic and canopy resistance to water vapour are difficult to estimate directly, leading to various empirical corrections when scaling from leaf to canopy. Here we evaluated the PM equation directly at the leaf scale, using a detailed leaf energy balance model and direct measurements in a controlled, insulated wind tunnel using artificial leaves with fixed and pre-defined "stomatal" conductance. Experimental results were consistent with a detailed leaf energy balance model; however, the results revealed systematic deviations from PM-predicted fluxes, which pointed to fundamental problems with the PM equation. Detailed analysis of the derivation by Monteith (1965) and later amendments revealed two errors in considering the effect of stomata and the two-sided exchange of sensible heat. A corrected set of analytical solutions for leaf temperature as well as latent and sensible heat flux is presented and comparison with the original PM equation indicates a major improvement in reproducing experimental results at the leaf scale. The errors in the original PM equation and its failure to reproduce experimental results at the leaf scale (for which it was originally derived) propagate into inaccurate sensitivities of transpiration and sensible heat fluxes to changes in atmospheric conditions, such as those associated with climate change (even with reasonable present day performance after calibration). The new formulation presented here rectifies some of the shortcomings of the PM equation and could provide a more robust starting point for canopy representation and climate change studies.