bluuebunny/crossref_metadata_2025 huggingface dataset:
The Reinforcement Learning Competitions
Authors: Whiteson Shimon , Tanner Brian , White Adam
Published: July 2017

This article reports on the reinforcement learning competitions, which have been held annually since 2006. In these events, researchers from around the world developed reinforcement learning agents to compete in domains of various complexity and difficulty. We focus on the 2008 competition, which employed fundamentally redesigned evaluation frameworks that aimed systematically to encourage the submission of robust learning methods. We describe the unique challenges of empirical evaluation in reinforcement learning and briefly review the history of the previous competitions and the evaluation frameworks they employed. We describe the novel frameworks developed for the 2008 competition as well as the software infrastructure on which they rely. Furthermore, we describe the six competition domains, present selected competition results, and discuss the implications of these results. Finally, we summarize the 2009 competition, which used the same evaluation framework but different events, and outline ideas for the future of the competition.
An Analysis of Current Trends in CBR Research Using Multiview Clustering
Authors: Greene Derek , Freyne Jill , Smyth Barry , Cunningham Pádraig
Published: July 2017

The European Conference on Case‐Based Reasoning (CBR) in 2008 marked 15 years of international and European CBR conferences where almost seven hundred research papers were published. In this report we review the research themes covered in these papers and identify the topics that are active at the moment. The main mechanism for this analysis is a clustering of the research papers based on both cocitation links and text similarity. It is interesting to note that the core set of papers has attracted citations from almost three thousand papers outside the conference collection so it is clear that the CBR conferences are a subpart of a much larger whole. It is remarkable that the research themes revealed by this analysis do not map directly to the subtopics of CBR that might appear in a textbook. Instead they reflect the applications‐oriented focus of CBR research, and cover the promising application areas and research challenges that are faced.
Recommender Systems: An Overview
Authors: Burke Robin , Felfernig Alexander , Göker Mehmet H.
Published: July 2017

Recommender systems are tools for interacting with large and complex information spaces. They provide a personalized view of such spaces, prioritizing items likely to be of interest to the user. The field, christened in 1995, has grown enormously in the variety of problems addressed and techniques employed, as well as in its practical applications. Recommender systems research has incorporated a wide variety of artificial intelligence techniques including machine learning, data mining, user modeling, case‐based reasoning, and constraint satisfaction, among others. Personalized recommendations are an important part of many online e‐commerce applications such as Amazon.com, Netflix, and Pandora. This wealth of practical application experience has provided inspiration to researchers to extend the reach of recommender systems into new and challenging areas. The purpose of the articles in this special issue is to take stock of the current landscape of recommender systems research and identify directions the field is now taking. This article provides an overview of the current state of the field and introduces the various articles in the special issue.
Believable Robot Characters
Authors: Simmons Reid , Makatchev Maxim , Kirby Rachel , Lee Min Kyung , Fanaswala Imran , Browning Brett , Forlizzi Jodi , Sakr Majd
Published: July 2017

Believability of characters has been an objective in literature, theater, film, and animation. We argue that believable robot characters are important in human‐robot interaction, as well. In particular, we contend that believable characters evoke users' social responses that, for some tasks, lead to more natural interactions and are associated with improved task performance. In a dialogue‐capable robot, a key to such believability is the integration of a consistent story line, verbal and nonverbal behaviors, and sociocultural context. We describe our work in this area and present empirical results from three robot receptionist test beds that operate “in the wild.”
Mapping the Landscape of Human‐Level Artificial General Intelligence
Authors: Adams Sam S. , Arel Itamar , Bach Joscha , Coop Robert , Furlan Rod , Goertzel Ben , Hall J. Storrs , Samsonovich Alexei , Scheutz Matthias , Schlesinger Matthew , Shapiro Stuart C. , Sowa John F.
Published: July 2017

We present the broad outlines of a roadmap toward human‐level artificial general intelligence (henceforth, AGI). We begin by discussing AGI in general, adopting a pragmatic goal for its attainment and a necessary foundation of characteristics and requirements. An initial capability landscape will be presented, drawing on major themes from developmental psychology and illuminated by mathematical, physiological, and information‐processing perspectives. The challenge of identifying appropriate tasks and environments for measuring AGI will be addressed, and seven scenarios will be presented as milestones suggesting a roadmap across the AGI landscape along with directions for future research and collaboration.
A Survey of the Seventh International Planning Competition
Authors: Coles Amanda , Coles Andrew , Olaya Angel García , Jiménez Sergio , López Carlos Linares , Sanner Scott , Yoon Sungwook
Published: July 2017

In this article we review the 2011 International Planning Competition. We give an overview of the history of the competition, discussing how it has developed since its first edition in 1998. The 2011 competition was run in three main separate tracks: the deterministic (classical) track; the learning track; and the uncertainty track. Each track proposed its own distinct set of new challenges and the participants rose to these admirably, the results of each track showing promising progress in each area. The competition attracted a record number of participants this year, showing its continued and strong position as a major central pillar of the international planning research community.
Competitive Benchmarking: Lessons Learned from the Trading Agent Competition
Authors: Ketter Wolfgang , Symeonidis Andreas L.
Published: July 2017

Over the years, competitions have been important catalysts for progress in artificial intelligence. We describe the goal of the overall Trading Agent Competition (TAC) and highlight particular competitions. We discuss its significance in the context of today's global market economy as well as AI research, the ways in which it breaks away from limiting assumptions made in prior work, and some of the advances it has engendered over the past 10 years. Since its introduction in 2000, TAC has attracted more than 350 entries and brought together researchers from AI and beyond.
A Machine‐Learning Approach to the Detection of Fetal Hypoxia during Labor and Delivery
Authors: Warrick Philip A. , Hamilton Emily F. , Kearney Robert E. , Precup Doina
Published: July 2017

Labor monitoring is crucial in modern health care, as it can be used to detect (and help avoid) significant problems with the fetus. In this article we focus on detecting hypoxia (or oxygen deprivation), a very serious condition that can arise from different pathologies and can lead to lifelong disability and death. We present a novel approach to hypoxia detection based on recordings of the uterine pressure and fetal heart rate, which are obtained using standard labor monitoring devices. The key idea is to learn models of the fetal response to signals from its environment. Then, we use the parameters of these models as attributes in a binary classification problem. A running count of pathological classifications over several time periods is taken to provide the current label for the fetus. We use a unique database of real clinical recordings, both from normal and pathological cases. Our approach classifies correctly more than half the pathological cases, 1.5 hours before delivery. These are cases that were missed by clinicians; early detection of this type would have allowed the physician to perform a Cesarean section, possibly avoiding the negative outcome.
Agent‐Based Modeling and Simulation
Authors: Klügl Franziska , Bazzan Ana L. C.
Published: July 2017

This article gives an introduction to agent‐based modeling and simulation (ABMS). After a general discussion about modeling and simulation, we address the basic concept of ABMS, focusing on its generative and bottom‐up nature, its advantages as well as its pitfalls. The subsequent part of the article deals with application‐oriented aspects, including selected tools and well‐known applications. In order to illustrate the benefits of using ABMS, we focus on several aspects of a well‐known area related to simulation of complex systems, namely traffic. At the end, a brief look into future challenges is given.
Toward Adapting Cars to Their Drivers
Authors: Rosenfeld Avi , Bareket Zevi , Goldman Claudia V. , Kraus Sarit , LeBlanc David J. , Tsimhoni Omer
Published: July 2017

Traditionally, vehicles have been considered as machines that are controlled by humans for the purpose of transportation. A more modern view is to envision drivers and passengers as actively interacting with a complex automated system. Such interactive activity leads us to consider intelligent and advanced ways of interaction leading to cars that can adapt to their drivers.

In this article, we focus on the adaptive cruise control (ACC) technology that allows a vehicle to automatically adjust its speed to maintain a preset distance from the vehicle in front of it based on the driver's preferences. Although individual drivers have different driving styles and preferences, current systems do not distinguish among users. We introduce a method to combine machine‐learning algorithms with demographic information and expert advice into existing automated assistive systems. This method can reduce the interactions between drivers and automated systems by adjusting parameters relevant to the operation of these systems based on their specific drivers and context of drive. We also learn when users tend to engage and disengage the automated system. This method sheds light on the kinds of dynamics that users develop while interacting with automation and can teach us how to improve these systems for the benefit of their users. While generic packages such as Weka were successful in learning drivers' behavior, we found that improved learning models could be developed by adding information on drivers' demographics and a previously developed model about different driver types. We present the general methodology of our learning procedure and suggest applications of our approach to other domains as well.
Mechanix: A Sketch‐Based Tutoring and Grading System for Free‐Body Diagrams
Authors: Valentine Stephanie , Vides Francisco , Lucchese George , Turner David , Kim Hong‐hoe , Li Wenzhe , Linsey Julie , Hammond Tracy
Published: July 2017

Introductory engineering courses within large universities often have annual enrollments that can reach up to a thousand students. In this article, we introduce Mechanix, a sketch‐based deployed tutoring system for engineering students enrolled in statics courses. Our system not only allows students to enter planar truss and free‐ body diagrams into the system, just as they would with pencil and paper, but our system also checks the student's work against a hand‐drawn answer entered by the instructor, and then returns immediate and detailed feedback to the student. Students are allowed to correct any errors in their work and resubmit until the entire content is correct and thus all of the objectives are learned. Since Mechanix facilitates the grading and feedback processes, instructors are now able to assign more free‐ response questions, increasing teacher's knowledge of student comprehension. Furthermore, the iterative correction process allows students to learn during a test, rather than simply display memorized information.
Student Modeling: Supporting Personalized Instruction, from Problem Solving to Exploratory Open‐Ended Activities
Authors: Conati Cristina , Kardan Samad
Published: July 2017

The field of intelligent tutoring systems (ITSs) has successfully delivered techniques and applications to provide personalized coaching and feedback for problem solving in a variety of domains. The core of this personalized instruction is a student model: the ITS component in charge of assessing student traits and states relevant to tailor the tutorial interaction to specific student needs during problem solving. There are however, other educational activities that can help learners acquire the target skills and abilities at different stages of learning including, among others, exploring interactive simulations and playing educational games. This article describes research on creating student models that support personalization for these novel types of interactions, their unique challenges, and how AI and machine learning can help.
AI Grand Challenges for Education
Authors: Woolf Beverly Park , Lane H. Chad , Chaudhri Vinay K. , Kolodner Janet L.
Published: July 2017

This article focuses on contributions that AI can make to address long‐term educational goals. Challenges are described that support: (1) mentors for every learner; (2) learning 21st century skills; (3) interaction data for learning; (4) universal access to global classrooms; and (5) lifelong and lifewide learning. A vision and brief research agenda are described for each challenge along with goals that lead to development of global educational resources and the reuse and sharing of digital educational resources. Instructional systems with AI technology are described that currently support richer experiences for learners and supply researchers with new opportunities to analyze vast data sets of instructional behavior from big databases that record elements of learning, affect, motivation, and social interaction. Personalized learning is described that facilitates student and group experience, reflection, and assessment.
Any‐Angle Path Planning
Authors: Nash Alex , Koenig Sven
Published: July 2017

In robotics and video games, one often discretizes continuous terrain into a grid with blocked and unblocked grid cells and then uses a path‐planning algorithms to find a shortest path on the resulting grid graph. This path, however, is typically not a shortest path in the continuous terrain. In this overview article, we discuss a path‐planning methodology for quickly finding paths in continuous terrain that are typically shorter than shortest grid paths. Any‐angle path‐planning algorithms are variants of the heuristic path‐planning algorithm A* that find short paths by propagating information along grid edges (like A*, to be fast) without constraining the resulting paths to grid edges (unlike A*, to find short paths).
Integrating Digital Pens in Breast Imaging for Instant Knowledge Acquisition
Authors: Sonntag Daniel , Weber Markus , Cavallaro Alexander , Hammon Matthias
Published: July 2017

Future radiology practices assume that the radiology reports should be uniform, comprehensive, and easily managed. This means that reports must be readable to humans and machines alike. In order to improve reporting practices in breast imaging, we allow the radiologist to write structured reports with a special pen on paper with an invisible dot pattern. In this way, we provide a knowledge‐acquisition system for printed mammography patient forms for the combined work with printed and digital documents. In this domain, printed documents cannot be easily replaced by computer systems because they contain free‐form sketches and textual annotations, and the acceptance of traditional PC reporting tools is rather low among the doctors. This is due to the fact that current electronic reporting systems significantly add to the amount of time it takes to complete the reports. We describe our real‐time digital paper application and focus on the use case study of our deployed application. We think that our results motivate the design and implementation of intuitive pen‐based user interfaces for the medical reporting process and similar knowledge work domains. Our system imposes only minimal overhead on traditional form‐filling processes and provides for a direct, ontology‐based structuring of the user input for semantic search and retrieval applications, as well as other applied artificial intelligence scenarios, which involve manual form‐based data acquisition.
The Grid‐Based Path‐Planning Competition
Authors: Sturtevant Nathan R.
Published: July 2017

While there have been many papers published on path planning in grids, there has not been significant work on comparing existing approaches, and it is difficult to evaluate new work in comparison to existing work. After creating a public repository of grid‐based path‐planning problems I created the Grid‐Based Path‐Planning Competition (GPPC) to facilitate these comparisons. This article describes the motivation and design of the competition, as well as plans for the future of the competition.
Space Applications of Artificial Intelligence
Authors: Chien Steve , Morris Robert
Published: July 2017

We are pleased to introduce the space application issue articles in this issue of AI Magazine. The exploration of space is a testament to human curiosity and the desire to understand the universe that we inhabit. As many space agencies around the world design and deploy missions, it is apparent that there is a need for intelligent, exploring systems that can make decisions on their own in remote, potentially hostile environments. At the same time, the monetary cost of operating missions, combined with the growing complexity of the instruments and vehicles being deployed, make it apparent that substantial improvements can be made by the judicious use of automation in mission operations.
Using Semantics and Statistics to Turn Data into Knowledge
Authors: Pujara Jay , Miao Hui , Getoor Lise , Cohen William W.
Published: July 2017

Many information‐extraction and knowledge base construction systems are addressing the challenge of deriving knowledge from text. A key problem in constructing these knowledge bases from sources like the web is overcoming the erroneous and incomplete information found in millions of candidate extractions. To solve this problem, we turn to semantics — using ontological constraints between candidate facts to eliminate errors. In this article, we represent the desired knowledge base as a knowledge graph and introduce the problem of knowledge graph identification, collectively resolving the entities, labels, and relations present in the knowledge graph. Knowledge graph identification requires reasoning jointly over millions of extractions simultaneously, posing a scalability challenge to many approaches. We use probabilistic soft logic (PSL), a recently introduced statistical relational learning framework, to implement an efficient solution to knowledge graph identification and present state‐of‐the‐art results for knowledge graph construction while performing an order of magnitude faster than competing methods.
Plan Recognition for Exploratory Learning Environments Using Interleaved Temporal Search
Authors: Uzan Oriel , Dekel Reuth , Seri Or , Gal Ya'akov (Kobi)
Published: July 2017

This article presents new algorithms for inferring users' activities in a class of flexible and open‐ended educational software called exploratory learning environments (ELEs). Such settings provide a rich educational environment for students, but challenge teachers to keep track of students' progress and to assess their performance. This article presents techniques for recognizing students' activities in ELEs and visualizing these activities to students. It describes a new plan‐recognition algorithm that takes into account repetition and interleaving of activities. This algorithm was evaluated empirically using two ELEs for teaching chemistry and statistics used by thousands of students in several countries. It was able to outperform the state‐of‐the‐art plan‐recognition algorithms when compared to a gold standard that was obtained by a domain expert. We also show that visualizing students' plans improves their performance on new problems when compared to an alternative visualization that consists of a step‐by‐step list of actions.
DiversiNews: Surfacing Diversity in Online News
Authors: Trampuš Mitja , Fuart Flavio , Pighin Daniele , Štajner Tadej , Bercic Jan , Novak Blaž , Rusu Delia , Stopar Luka , Grobelnik Marko
Published: July 2017

For most events of at least moderate significance, there are likely tens, often hundreds or thousands of online articles reporting on it, each from a slightly different perspective. If we want to understand an event in depth, from multiple perspectives, we need to aggregate multiple sources and understand the relations between them. However, current news aggregators do not offer this kind of functionality. As a step toward a solution, we propose DiversiNews, a real‐time news aggregation and exploration platfom whose main feature is a novel set of controls that allow users to contrast reports of a selected event based on topical emphases, sentiment differences, and/or publisher geolocation. News events are presented in the form of a ranked list of articles pertaining to the event and an automatically generated summary. Both the ranking and the summary are interactive and respond in real time to user's change of controls. We validated the concept and the user interface through user tests with positive results.
Research Priorities for Robust and Beneficial Artificial Intelligence
Authors: Russell Stuart , Dewey Daniel , Tegmark Max
Published: July 2017

Success in the quest for artificial intelligence has the potential to bring unprecedented benefits to humanity, and it is therefore worthwhile to investigate how to maximize these benefits while avoiding potential pitfalls. This article gives numerous examples (which should by no means be construed as an exhaustive list) of such worthwhile research aimed at ensuring that AI remains robust and beneficial.
Beyond the Turing Test
Authors: Marcus Gary , Rossi Francesca , Veloso Manuela
Published: July 2017

The articles in this special issue of AI Magazine include those that propose specific tests and those that look at the challenges inherent in building robust, valid, and reliable tests for advancing the state of the art in AI.
The CADE ATP System Competition — CASC
Authors: Sutcliffe Geoff
Published: July 2017

The CADE ATP System Competition (CASC) is an annual evaluation of fully automatic automated theorem‐proving (ATP) systems for classical logic — the world championship for such systems. CASC provides a public evaluation of the relative capabilities of ATP systems, and aims to stimulate ATP research toward the development of more powerful ATP systems. Over the years CASC has been a catalyst for impressive improvements in ATP.
PSINET: Assisting HIV Prevention Among Homeless Youth by Planning Ahead
Authors: Yadav Amulya , Marcolino Leandro Soriano , Rice Eric , Petering Robin , Winetrobe Hailey , Rhoades Harmony , Tambe Milind , Carmichael Heather
Published: July 2017

Homeless youth are prone to human immunodeficiency virus (HIV) due to their engagement in high‐risk behavior such as unprotected sex, sex under influence of drugs, and so on. Many nonprofit agencies conduct interventions to educate and train a select group of homeless youth about HIV prevention and treatment practices and rely on word‐of‐mouth spread of information through their one single social network Previous work in strategic selection of intervention participants does not handle uncertainties in the social networks' structure and evolving network state, potentially causing significant shortcomings in spread of information. Thus, we developed PSINET, a decision‐support system to aid the agencies in this task. PSINET includes the following key novelties: (1) it handles uncertainties in network structure and evolving network state; (2) it addresses these uncertainties by using POMDPs in influence maximization; and (3) it provides algorithmic advances to allow high‐quality approximate solutions for such POMDPs. Simulations show that PSINET achieves around 60 percent more information spread over the current state of the art. PSINET was developed in collaboration with My Friend's Place (a drop‐in agency serving homeless youth in Los Angeles) and is currently being reviewed by its officials.
Symbiotic Cognitive Computing
Authors: Farrell Robert , Lenchner Jonathan , Kephart Jeffrey , Webb Alan , Muller Michael , Erickson Thomas , Melville David , Bellamy Rachel , Gruen Daniel , Connell Jonathan , Soroker Danny , Aaron Andy , Trewin Shari , Ashoori Maryam , Ellis Jason , Gaucher Brian , Gil Dario
Published: July 2017

IBM Research is engaged in a research program in symbiotic cognitive computing to investigate how to embed cognitive computing in physical spaces. This article proposes five key principles of symbiotic cognitive computing: context, connection, representation, modularity, and adaptation, along with the requirements that flow from these principles. We describe how these principles are applied in a particular symbiotic cognitive computing environment and in an illustrative application for strategic decision making. Our results suggest that these principles and the associated software architecture provide a solid foundation for building applications where people and intelligent agents work together in a shared physical and computational environment. We conclude with a list of challenges that lie ahead.
Applications of Answer Set Programming
Authors: Erdem Esra , Gelfond Michael , Leone Nicola
Published: July 2017

Answer set programming (ASP) has been applied fruitfully to a wide range of areas in AI and in other fields, both in academia and in industry, thanks to the expressive representation languages of ASP and the continuous improvement of ASP solvers. We present some of these ASP applications, in particular, in knowledge representation and reasoning, robotics, bioinformatics, and computational biology as well as some industrial applications. We discuss the challenges addressed by ASP in these applications and emphasize the strengths of ASP as a useful AI paradigm.
Challenges in Building Highly Interactive Dialogue Systems
Authors: Ward Nigel G. , DeVault David
Published: July 2017

Spoken dialogue researchers have recently demonstrated highly interactive systems in several domains. This paper considers how to build on these advances to make systems more robust, easier to develop, and more scientifically significant. We identify key challenges whose solution would lead to improvements in dialogue systems and beyond.
Twenty‐Five Years of Successful Application of Constraint Technologies at Siemens
Authors: Falkner Andreas , Friedrich Gerhard , Haselböck Alois , Schenner Gottfried , Schreiner Herwig
Published: July 2017

The development of problem solvers for configuration tasks is one of the most successful and mature application areas of artificial intelligence. The provision of tailored products, services, and systems requires efficient engineering and design processes where configurators play a crucial role. Because one of the core competencies of Siemens is to provide such highly engineered and customized systems, ranging from solutions for medium‐sized and small businesses up to huge industrial plants, the efficient implementation and maintenance of configurators are important goals for the success of many departments. For more than 25 years the application of constraint‐based methods has proven to be a key technology in order to realize configurators at Siemens. This article summarizes the main aspects and insights we have gained looking back over this period. In particular, we highlight the main technology factors regarding knowledge representation, reasoning, and integration that were important for our achievement. Finally we describe selected key application areas where the business success vitally depends on the high productivity of configuration processes.
Harold Cohen and AARON
Authors: Cohen Paul
Published: July 2017

Harold Cohen (1928–2016) was a computer art pioneer and the developer of AARON, one of the most creative AI programs in daily use. This memoriam, written by his son (and AI scientist) Paul, describes Harold Cohen's work and contributions to the AI and art communities. — ed.
Shakey: From Conception to History
Authors: Kuipers Benjamin , Feigenbaum Edward A. , Hart Peter E. , Nilsson Nils J.
Published: July 2017

Shakey the Robot, conceived 50 years ago, was a seminal contribution to AI. Shakey perceived its world, planned how to achieve a goal, and acted to carry out that plan. This was revolutionary. At the 29th AAAI Conference on Artificial Intelligence, attendees gathered to celebrate Shakey and to gain insights into how the AI revolution moves ahead. The celebration included a panel that was chaired by Benjamin Kuipers and featured AI pioneers Ed Feigenbaum, Peter Hart, and Nils Nilsson. This article includes written versions of the contributions of those panelists. —ed.
Using AI to Teach AI: Lessons from an Online AI Class
Authors: Goel Ashok K. , Joyner David A.
Published: July 2017

In fall 2014, we launched a foundational course in artificial intelligence (CS7637: Knowledge‐Based AI) as part of Georgia Institute of Technology's Online Master of Science in Computer Science program. We incorporated principles and practices from the cognitive and learning sciences into the development of the online AI course. We also integrated AI techniques into the instruction of the course, including embedding 100 highly focused intelligent tutoring agents in the video lessons. By now, more than 2000 students have taken the course. Evaluations have indicated that OMSCS students enjoy the course compared to traditional courses, and more importantly, that online students have matched residential students' performance on the same assessments. In this article, we present the design, delivery, and evaluation of the course, focusing on the use of AI for teaching AI. We also discuss lessons we learned for scaling the teaching and learning of AI.
Study ofthe flame resistance of low density polyethylene composites with oyster shells powder extracted from the Caspian Sea in Iran.
Authors: Mohammed Ahmed , Radhi Wisam , Ibrahim Ibrahim , Mohammed Faise
Published: July 2017

The flame resistance properties of oyster shells powder extracted from the

Caspian sea in Iran composites were studied. (0%, 2.5%, 5%, 10%, 15%

and 20%) (Wt. /wt) of added oyster shells powder with the particular size

(≤ 250 μm) where composite with low density polyethylene and several

factor were studied like average of average time of burning(ATB), rate of

burning(RB), average extent of burning(AEB) and percentage of the time

of burning(PTB). The obtained results showed that the average time of

burning initiates strongly impacts with (5%), increasing weight preparation

to(147Sec). And then begins to decline their behavior when increasing

proportions weighted. While, the composite shows exception behavior at

(20 %).
Direct In Vitro Regeneration of Fig (Ficus carica L. CV. Benaty) from Apical and Lateral Buds
Authors: Toma Rafail , Tamer Yousif
Published: July 2017

Benaty fig plant was successfully propagated by tissue culture technique and areproducible and reliable micropropagation protocol was developed through thisinvestigation. At initiation stage, healthy aseptic cultures from lateral and terminal budexplants of about 85% were achieved when the explants were treated with 0.15% HgCl 2for 7 minutes. A combined solution of ascorbic acid and citric acid (100 and 150 mgl -1 )was successfully used to overcome the problem of phenolic compounds exudation fromthe explants into the culture media. At shoot multiplication stage, the addition of 2.0 mgl -1 from both BA and kinetin gave the highest number of shoots per explant estimated at2.66 and 3.33 shoots/ explant respectively. As well as, activated charcoal promotedshoots multiplication in all multiplication parameters. The highest number of shoots perexplants (5 shoots/ explant) was obtained on MS medium containing 4.0 gl -1 AC. At rootformation stage, the interaction treatment of full MS salt strength with the use of 0.25mgl -1 NAA gave the highest rooting percentage reaching 87.5%. The highest number ofroots (18.5 roots/ explant) was recorded as well from the combined treatment of full MSsalt strength with the use of 0.25 mgl -1 NAA. While the longest roots (6.66 cm) wererecorded from the interaction treatment of half salt strength and 0.50 mgl -1 IBA. Theaddition of activated charcoal to the rooting culture medium decreased the rootingpercentage from 87.5% at control treatment to 50% and 62.5% when 2.0 and 4.0 gl -1 ACwere respectively added. The in vitro propagated fig plantlets were gradually moved in asuccessful way from lab to field conditions with 95% survival rate.
Impact of Some Pesticides on Total Counts of Soil Non-Symbiotic Nitrogen-Fixing Bacteria, Particularly Azotobacter sp
Authors: Khudhur Nashmeel , Sarmamy Abdul-Ghany
Published: July 2017

A pot experiment was conducted to evaluate the effect of glyphosate herbicide (n-phosphonomethyl glycine), mancozeb fungicide ([[1,2-ethanediylbis- [carbamodithioato]](2-)] manganese mixture with [[1,2-ethanediylbis- [carbamodithioato]]-(2- )] zinc) anddiazinon insecticide (O, O-diethyl O-[6- methyl-2- (1-methylethyl)- 4-pyrimidynyl]), threesoil orders and two soil moisture contents (50% and 100% of field capacity) and theircombinations on soil total non-symbiotic nitrogen-fixing bacteria particularlyAzotobacter sp. counts. This experiment last for two months from the 6 th of Jun until the8 th of August 2011 with five sampling periods at biweekly intervals. Factorial experiment(4×3×2) with Completely Randomized Design (CRD) and three replications was usedand the means were compared using Revised Least Significant Differences (R.LSD) atthe level of significant of 0.05. Significant results were obtained at the last two scheduledperiod’s sampling of 4 th and 5 th , and the results showed that: Mancozeb fungicidedecreased total Azotobacter sp.; Diazinon insecticide decreased both total non-symbioticnitrogen-fixing bacteria and total Azotobacter sp.; Agholan soil (order Entisols) showedthe greatest increase in soil total non-symbiotic nitrogen-fixing bacteria. 50% soilmoisture content revealed the greatest reduction total Azotobacter sp. while, 100% soilmoisture content showed the greatest increase in soil total Azotobacter sp. count. Thecombinations among: glyphosate, Agholan soil and 100% moisture combination showedthe greatest reduction in total non-symbiotic nitrogen-fixing bacteria and totalAzotobacter sp.
Analysis of organic functional groups and some trace heavy metals in the settleable dust particles (dustfall) of Sulaimani City/KURDISTAN REGION-IRAQ.
Authors: Majid Salih
Published: July 2017

Ambient settleable (dustfall) dust particles samples were collected during August 2009
to March 2010 from 18 locations in Sulaimani City/KRI for qualitative analyzing by
Fourier Transform Infrared (FTIR) spectroscopy instrument to characterize the common
functional groups that existed in the samples. Furthermore, the samples were
quantitatively analyzed for the heavy metals contents of; V, Co and As by Inductively
Coupled Plasma-Optical Emission Spectroscopy ICP-OES. The collected samples
involved samples of settleable dust particles from local source of the city (location 1 to
15) and settleable dust particles from dust storm event of 22 February, 2010 (location 16
to18). The FTIR analysis identified the following functional groups; Sulfinate ester;
Sulfoxide; Sulfate ion; P. Amine (bend.); Carbonyl; Thiol; Alkanes HC; P. Amine (str.);
Bonded and free hydroxyl group in all the samples of (1 to 15) for the local source of
dust particles except sample location number 6 which was free from sulfoxide, p. amine
(bend.), carbonyl and p. amine (str.) as compared to the samples of other locations and
it was also the only sampling location that had a silicate group. Moreover, sample
location number 13 was the only location that had an extra functional group of isocyanide
or alkynes HC functional group. For the dust storm samples of location numbers 16, 17
and 18 had also all the above mentioned 9 functional groups except the alkanes HC
functional group. On the other hand, the concentration ranges of the studied heavy metals
were (0.20 – 3.20), (2.02 – 5.45) and (2.89 – 45.50) mg dust kg-1 dust for As, Co and V
respectively in all the studied locations.
Diffusion Equations for Fluid Flow in Porous Rocks
Authors: Pant Pramod Kumar
Published: July 2017

The multiphase flow in porous media is a subject of great complexities with a long rich history in the field of fluid mechanics. This is a subject with important technical applications, most notably in oil recovery from petroleum reservoirs and so on. The single-phase fluid flow through a porous medium is well characterized by Darcy’s law. In the petroleum industry and in other technical applications, transport is modeled by postulating a multiphase generalization of the Darcy’s law. In this connection, distinct pressures are defined for each constituent phase with the difference known as capillary pressure, determined by the interfacial tension, micro pore geometry and surface chemistry of the solid medium. For flow rates, relative permeability is defined that relates the volume flow rate of each fluid to its pressure gradient. In the present paper, there is a derivation and analysis about the diffusion equation for the fluid flow in porous rocks and some important results have been founded. The permeability is a function of rock type that varies with stress, temperature etc., and does not depend on the fluid. The effect of the fluid on the flow rate is accounted for by the term of viscosity. The numerical value of permeability for a given rock depends on the size of the pores in the rock as well as on the degree of interconnectivity of the void space. The pressure pulses obey the diffusion equation not the wave equation. Then they travel at a speed which continually decreases with time rather than travelling at a constant speed. The results shown in this paper are much useful in earth sciences and petroleum industry.
Biomedical Waste Management of Mercury using Advanced Polymeric Materials: Application of MIP - Sieve Sensor
Authors: Srivastava Shrinkhala , Srivastava Saurabh
Published: July 2017

The most common routes of exposure to mercury in the healthcare facility include inhalation of inorganic mercury vapour after a spill or accidental skin contact with mercury. Accidental spills of liquid mercury can increase the levels of mercury in the air or wastewater of a HCFs. Establishing protocols for proper cleanup of spills involving mercury is an on flow challenge in Healthcare Sector where Bio safety and Bioethics are first law to be followed for human safety.
The surface ion-imprinted poly(ethylene terephthalate)- semicarbazide (PETSC) modified chelating fibre sieves (Hg-PET-SC) were prepared using Hg(II) as a template and formaldehyde as a cross-linker and showed higher adsorption capacity and selectivity for the Hg(II) ions compared with the nonimprinted fibres (NIP-PET-SC) without a template. The maximum limit of detection values for Hg-PET-SC and NIP-PET-SC were 60.05 g/l and 24.51 g/l, respectively using MIP-PET-SC-CNE and NIP-PET-SC-CNE sensors. The selectivity coefficient of Hg(II) ions and other metal ions on Hg-PET-SC indicated an overall preference for Hg(II) ions. Rebinding and crossselectivity studies were also carried out using various divalent ions as interferents.
Bioremediation of Heavy Metal Using Consortia Developed from Municipal Wastewater Isolates
Authors: Singh Kanhaiya Kumar , Vaishya R. C.
Published: July 2017

Nowadays heavy-metal pollution has become an environmental problem due to their toxic effects, and their invasion in to the food chain leads to serious environmental and health problems. Heavy Metal degradation through common physico-chemical techniques is very expensive and unsuitable in treating large contaminated area effectively. Bioremediation provides a promising means to reclaim such toxic substances in an economical and ecofriendly way. Bioremediation obtains microorganisms that capable to degrade toxic contaminants or have the ability to accumulate it in their cells. The present study was carried out to evaluate degradation capacity of consortia developed from municipal wastewater isolates. The activity of the isolates for hemolysis was studied on the Blood-Agar plates. The identification of isolates obtained through biochemical and morphological characteristics. Seven isolates and three defined consortia were tested for degradation of heavy metals (zinc, lead and chromium). Consortia 3 (R9 + S11 + T12) showed better degradation with 93.78% ability in reducing zinc when incubated for 72 hours and 86.16% when incubated for 24 hours. The lead reduction was found to be 84.33% by Consortia 1(A3 + B4) when incubated at 37°C for 72 hours incubation. The chromium was reduced by Consortia 2(C6 + D7) with 87.61% ability when incubated for 72 hours. The organisms had capacity to reduce the heavy metals depending on the factors like time and concentration of inoculum. As the time of incubation increases, more reduction was observed. This study gives us insight in to the inherent potential of the Consortia to bio remediate toxic heavy metals.
Levodopa in Parkinson’s Disease: A Review of Population Pharmacokinetics/Pharmacodynamics Analysis
Authors: Marsot Amélie , Guilhaumou Romain , Azulay Jean Philippe , Blin Olivier
Published: July 2017

Background: Parkinson’s disease is the second most common neurodegenerative disorder after Alzheimer’s disease. Although levodopa remains the single effective agent in the management of Parkinson’s disease, the accurate determination of this optimal dosage is complicated by marked between-subject and between-occasion variability in this population.  This review presents a synthesis of the population pharmacokinetic and pharmacodynamic models of levodopa described in Parkinson’s disease. Methods:A literature search was conducted from the PubMed database, from their inception through April 2016, using the following terms: levodopa, pharmacokinetic(s), pharmacodynamic(s) population, model(ling) and nonlinear mixed effect. Articles were excluded if they were not pertinent. References of all selected articles were also evaluated. Results: A total of 12 articles were finally retained. The following covariates were selected as interindividual variability factors: body weight, age, sex, creatinine clearance and levodopa dose. The clinical response versus effect site concentration relationship was described with different sigmoidal Emax models. Different pharmacodynamic effects were described: UPDRS, Tapping, Dyskinesia, CURSΣ and treatment response scale. Discussion: This review allows us to realize interpretation of a patient’s clinical picture and confirmed the appropriateness of the pharmacokinetic-pharmacodynamic modeling for levodopa. External evaluation of previous published models should be also continued to evaluate these previous studies. New pharmacokinetic and/or pharmacodynamic population modelling studies could be consider to improve future models and decrease variability, to better understand the evolution of patients with Parkinson’s disease treated by levodopa. This article is open to POST-PUBLICATION REVIEW. Registered readers (see “For Readers”) may comment by clicking on ABSTRACT on the issue’s contents page.
Effectiveness of Valganciclovir 900mg Versus 450mg for Cytomegalovirus Prophylaxis in Renal Transplantation: A Systematic Review and Meta-Analysis
Authors: Xin Wang , Hui Yang , Xiaodong Zhang , Xiangli Cui , Shihui Wang , Lihong Liu
Published: July 2017

Objectives: Valganciclovir 900 mg/day is approved for cytomegalovirus (CMV) prophylaxis, but 450 mg/day is seems also effective. We systematically reviewed the efficacy and safety of low-dose versus high-dose valganciclovir prophylaxis in renal transplantation recipients. Methods: An electronic search was conducted up to November 29, 2016. The primary outcomes were incidences of CMV, CMV disease, mortality and opportunistic infection. The second outcomes were acute rejection, allograft loss, adverse drug reaction (ADR). Results: 7 cohort studies, all with high quality involving (1431 patients) were included. There was no significant difference of the incidence of following CMV disease (1271 patients, odds ratio [OR] 0.74, 95% confidence interval [CI], 0.38-1.43, p=0.36), acute rejection (1343 patients, OR 0.77, 95%CI 0.53-1.14, p=0.19), allograft loss (1271 patients, OR 0.64, 95%CI 0.31-1.35, p=0.24), mortality (1271 patients, OR 0.55, 95%CI 0.20-1.47, p=0.23) and opportunistic infections (OI) (985 patients, OR 0.76, 95%CI 0.52-1.10, p=0.14) between the low-dose and the high-dose valganciclovir  prophylaxis. And no significant difference was observed for premature valganciclovir discontinuation (1010 patients, OR 0.81, 95%CI 0.52-1.25, p=0.33) and the incidence of leukopenia (1082 patients, OR 0.65, 95%CI 0.34-1.22, p=0.18) between the two regimens. Conclusion: 450 mg and 900 mg doses of valganciclovir are equipotent for CMV universal prophylaxis. CMV 450 mg prophylaxis should be used for renal transplant recipients. This article is open to POST-PUBLICATION REVIEW. Registered readers (see “For Readers”) may comment by clicking on ABSTRACT on the issue’s contents page.
Building Confidence
Authors: Budin Wendy C.
Published: July 2017

In this column, the editor of The Journal of Perinatal Education discusses the meaning of confidence and effective ways to build confidence for birth. The editor also describes the contents of this issue, which offer a broad range of resources, research, and inspiration for childbirth educators in their efforts to promote, support, and protect natural, safe, and healthy birth.
BAHASA DAN HABITUS KELAS DALAM BUKU AL-ARABIYAH BAYNA YADAIK JILID 2
Authors: Nida’uljanah Hanifah , Ridwan Muhammad
Published: July 2017

Penelitian ini membahas habitus kelas dominan dalam wacana buku Al-Arabiyah Bayna Yadaik jilid 2 dan habitus kelas terdominasi di dalamnya. Data utama yang diperlukan untuk penelitian ini adalah data kebahasaan berupa kalimat dalam wacana yang digunakan dalam buku tersebut. Data tersebut dikumpulkan dengan metode simak teknik sadap terhadap buku Al-Arabiyah Bayna Yadaik jilid 2. Teknik sadap dilakukan dengan cara sadap bebas libat cakap, yaitu peneliti memerhatikan dengan cermat tanpa ikut berpartisipasi dalam penggunaan bahasa dalam buku Al-Arabiyah Bayna Yadaik jilid 2. Penelitian dilakukan pendekatan analisis wacana kritis yang dilakukan dengan menemukan kalimat dari wacana buku tersebut yang menunjukkan dan mengisyaratkan suatu habitus kelas sosial tertentu. Hasil penelitian yaitu sosialisasi habitus kelas atas lebih banyak dilakukan dalam buku Al-Arabiyah Bayna Yadaik jilid 2 daripada habitus kelas bawah. Banyak kalimat ditemukan dalam bacaan yang mengindikasikan bahwa pelaku cerita berasal dari kelas atas. Habitus kelas atas ditunjukkan dengan berbagai mekanisme sosialisasi,  berupa kebiasaan, simbolisasi maupun karakter kelas atas, sedangkan habitus kelas bawah hanya ditampakkan dalam pencitraan profil saja.

 

Kata kunci: wacana, kelas sosial, analisis wacana kritis

 
KERAJINAN KACA GRAFIR SEBAGAI SOUVENIR INTERIOR DI SURAKARTA
Authors: Supriyatmono Supriyatmono
Published: July 2017

The traditional wealth of art in Indonesia which are several area include Surakarta region is still took care and everlasting. The are like various kinds of form of Industry to nuance/variation ethniqe which is home industry potential is the most important enough to effort in home small industry.

Grafir glass is the form of one system in the work of art instrument of glass painting can be done as work of art although industry, and so it is beside other techniques as like glass and lood, glass etsa, paint of glass and so on.