bluuebunny/crossref_metadata_2025 huggingface dataset:
SMINT
Authors: Wu Huijun , Wang Chen , Nock Richard , Wang Wei , Yin Jie , Lu Kai , Zhu Liming
Published: May 2020

Sharing a pre-trained machine learning model, particularly a deep neural network via prediction APIs, is becoming a common practice on machine learning as a service (MLaaS) platforms nowadays. Although deep neural networks (DNN) have shown remarkable successes in many tasks, they are also criticized for the lack of interpretability and transparency. Interpreting a shared DNN model faces two additional challenges compared with interpreting a general model. (1) Limited training data can be disclosed to users. (2) The internal structure of the models may not be available. These two challenges impede the application of most existing interpretability approaches, such as saliency maps or influence functions, for DNN models. Case-based reasoning methods have been used for interpreting decisions; however, how to select and organize the data points under the constraints of shared DNN models is not discussed. Moreover, simply providing cases as explanations may not be sufficient for supporting instance level interpretability. Meanwhile, existing interpretation methods for DNN models generally lack the means to evaluate the reliability of the interpretation. In this article, we propose a framework named Shared Model INTerpreter (SMINT) to address the above limitations. We propose a new data structure called a boundary graph to organize training points to mimic the predictions of DNN models. We integrate local features, such as saliency maps and interpretable input masks, into the data structure to help users to infer the model decision boundaries. We show that the boundary graph is able to address the reliability issues in many local interpretation methods. We further design an algorithm named hidden-layer aware p-test to measure the reliability of the interpretations. Our experiments show that SMINT is able to achieve above 99% fidelity to corresponding DNN models on both MNIST and ImageNet by sharing only a tiny fraction of training data to make these models interpretable. The human pilot study demonstrates that SMINT provides better interpretability compared with existing methods. Moreover, we demonstrate that SMINT is able to assist model tuning for better performance on different user data.
Reviewing Speech Input with Audio
Authors: Hong Jonggi , Vaing Christine , Kacorri Hernisa , Findlater Leah
Published: May 2020

Speech input is a primary method of interaction for blind mobile device users, yet the process of dictating and reviewing recognized text through audio only (i.e., without access to visual feedback) has received little attention. A recent study found that sighted users could identify only about half of automatic speech recognition (ASR) errors when listening to text-to-speech output of the ASR results. Blind screen reader users, in contrast, may be better able to identify ASR errors through audio due to their greater use of speech interaction and increased ability to comprehend synthesized speech. To compare the experiences of blind and sighted users with speech input and ASR errors, as well as to compare their ability to identify ASR errors through audio-only interaction, we conducted a lab study with 12 blind and 12 sighted participants. The study included a semi-structured interview portion to qualitatively understand experiences with ASR, followed by a controlled speech input task to quantitatively compare participants’ ability to identify ASR errors in their dictated text. Findings revealed differences between blind and sighted participants in terms of how they use speech input and their level of concern for ASR errors (e.g., blind users were more highly concerned). In the speech input task, blind participants were able to identify only 40% of ASR errors, which, counter to our hypothesis, was not significantly different from sighted participants’ performance. In depth analysis of speech input, ASR errors, and strategy of identifying ASR errors scrutinized how participants entered a text with speech input and reviewed it. Our findings indicate the need for future work on how to support blind users in confidently using speech input to generate accurate, error-free text.
H-DrunkWalk
Authors: Chen Xinlei , Ruiz Carlos , Zeng Sihan , Gao Liyao , Purohit Aveek , Carpin Stefano , Zhang Pei
Published: May 2020

Large-scale micro-aerial vehicle (MAV) swarms provide promising solutions for situational awareness in applications such as environmental monitoring, urban surveillance, search and rescue, and so on. However, these scenarios do not provide localization infrastructure and limit cost and size of on-board capabilities of individual nodes, which makes it challenging for nodes to autonomously navigate to suitable preassigned locations. In this article, we present
H-DrunkWalk
, a collaborative and adaptive technique for heterogeneous MAV swarm navigation in environments not formerly preconditioned for operation. Working with heterogeneous MAV swarm, the
H-DrunkWalk
achieves high accuracy through collaboration but still maintains a low cost of the entire swarm. The heterogeneous MAV swarm consists of two types of nodes: (1) basic MAVs with limited sensing, communication, computing capabilities and (2) advanced MAVs with premium sensing, communication, computing capabilities. The key focus behind this networked MAV swarm research is to (1) rely on collaboration to overcome limitations of individual nodes and efficiently achieve system-wide sensing objectives and (2) fully take advantage of advanced MAVs to help basic MAVs improve their performance. The evaluations based on real MAV testbed experiments and large-scale physical-feature-based simulations show that compared to the traditional non-collaborative and non-adaptive method (dead reckoning with map bias), our system achieves up to 6× reductions in location estimation errors, and as much as 3× improvements in navigation success rate under the given time and accuracy constraints. In addition, by comprehensively considering the environment, heterogeneous structure, and quality of location estimation, our
H-DrunkWalk
brings 2× performance improvement (on average) as that of a hardware upgrade.
Security of Microfluidic Biochip
Authors: Chen Huili , Potluri Seetal , Koushanfar Farinaz
Published: May 2020

With the advancement of system miniaturization and automation, Lab-on-a-Chip (LoC) technology has revolutionized traditional experimental procedures. Microfluidic Biochip (MFB) is an emerging branch of LoC with wide medical applications such as DNA sequencing, drug delivery, and point of care diagnostics. Due to the critical usage of MFBs, their security is of great importance. In this article, we exploit the vulnerabilities of two types of MFBs: Flow-based Microfluidic Biochip (FMFB) and Digital Microfluidic Biochip (DMFB). We propose a systematic framework for applying Reverse Engineering (RE) attacks and Hardware Trojan (HT) attacks on MFBs as well as for practical countermeasures against the proposed attacks. We evaluate the attacks and defense on various benchmarks where experimental results prove the effectiveness of our methods. Security metrics are defined to quantify the vulnerability of MFBs. The overhead and performance of the proposed attacks as well as countermeasures are also discussed.
A Defect Estimator for Source Code
Authors: Kapur Ritu , Sodhi Balwinder
Published: May 2020

An important issue faced during software development is to identify defects and the properties of those defects, if found, in a given source file. Determiningdefectivenessof source code assumes significance due to its implications on software development and maintenance cost.

We present a novel system to estimate the presence of defects in source code and detect attributes of the possible defects, such as the severity of defects. The salient elements of our system are: (i) a dataset of newly introduced source code metrics, calledPROgrammingCONstruct (PROCON) metrics, and (ii) a novelMachine-Learning (ML)-based system, calledDefectEstimator forSourceCode (DESCo), that makes use of PROCON dataset for predicting defectiveness in a given scenario. The dataset was created by processing 30,400+ source files written in four popular programming languages, viz., C, C++, Java, and Python.

The results of our experiments show that DESCo system outperforms one of the state-of-the-art methods with an improvement of 44.9%. To verify the correctness of our system, we compared the performance of 12 different ML algorithms with 50+ different combinations of their key parameters. Our system achieves the best results with SVM technique with a mean accuracy measure of 80.8%.
Generating Difficult CNF Instances in Unexplored Constrainedness Regions
Authors: Escamocher Guillaume , O'Sullivan Barry , Prestwich Steven David
Published: May 2020

When creating benchmarks for satisfiability (SAT) solvers, we need Conjunctive Normal Form (CNF) instances that are easy to build but hard to solve. A recent development in the search for such methods has led to the Balanced SAT algorithm, which can create
k
-CNF instances with
m
clauses of high difficulty, for arbitrary
k
and
m
. In this article, we introduce the No-Triangle CNF algorithm, a CNF instance generator based on the cluster coefficient graph statistic. We empirically compare the two algorithms by fixing the arity and the number of variables, but varying the number of clauses. We find that the hardest instances produced by each method belong to different constrainedness regions. In the 3-CNF case, for example, hard No-Triangle CNF instances reside in the highly-constrained region (many clauses), while Balanced SAT instances obtained from the same parameters are easy to solve. This allows us to generate difficult instances where existing algorithms fail to do so.
Safe Exploration for Optimizing Contextual Bandits
Authors: Jagerman Rolf , Markov Ilya , Rijke Maarten De
Published: May 2020

Contextual bandit problems are a natural fit for many information retrieval tasks, such as learning to rank, text classification, recommendation, and so on. However, existing learning methods for contextual bandit problems have one of two drawbacks: They either do not explore the space of all possible document rankings (i.e., actions) and, thus, may miss the optimal ranking, or they present suboptimal rankings to a user and, thus, may harm the user experience. We introduce a new learning method for contextual bandit problems, Safe Exploration Algorithm (SEA), which overcomes the above drawbacks. SEA starts by using a baseline (or production) ranking system (i.e., policy), which does not harm the user experience and, thus, is safe to execute but has suboptimal performance and, thus, needs to be improved. Then SEA uses counterfactual learning to learn a new policy based on the behavior of the baseline policy. SEA also uses high-confidence off-policy evaluation to estimate the performance of the newly learned policy. Once the performance of the newly learned policy is at least as good as the performance of the baseline policy, SEA starts using the new policy to execute new actions, allowing it to actively explore favorable regions of the action space. This way, SEA never performs worse than the baseline policy and, thus, does not harm the user experience, while still exploring the action space and, thus, being able to find an optimal policy. Our experiments using text classification and document retrieval confirm the above by comparing SEA (and a boundless variant called BSEA) to online and offline learning methods for contextual bandit problems.
Passages
Authors: Groce Alex
Published: May 2020

John McPhee's Basin and Range, the first of his geology books usually read in a collection as the (sized rather like a large rock itself) Annals of the Former World is a funny choice for a Passages classic, at first glance. Maybe at second glance too, come to think of it.

Basin and Range is a travelogue, haphazard intro textbook on plate tectonics, and a meditation on the Earth, its age, and the rocks that give us some clue to almost utterly alien worlds that once occupied the space we now inhabit. Lava flows, trilobites, ancient seas, and primordial continents; the great extinctions that bookend geological periods of time, what does this all have to do with software engineering?
Risks to the Public
Authors: Neumann Peter G.
Published: May 2020

Boeing 737s can't land facing west (FAA via Clive D.W. Feather, R 31 56) The FAA received reports earlier this year of three incidents of display electronic unit (DEU) software errors on Model 737 NG airplanes ying into runway PABR in Barrow, Alaska. All six display units (DUs) blanked with a selected instru- ment approach to a runway with a 270-degree true heading, and all six DUs stayed blank until a di erent runway was selected. [...] The investigation revealed that the problem occurs when this combination of software is installed and a susceptible runway with a 270-degree true heading is selected for instrument approach. Not all runways with a 270-degree true heading are susceptible; only seven runways worldwide, as identi ed in this AD, have latitude and longitude values that cause the blanking behavior. (Note that this is all 6 dis- plays on each plane, not 2 displays on each of three planes.) (R 31 54). [More items later on polar coordinates, tangent of 90 and 270 being plus-minus in nity, etc. (R 31 56,57)
The Java Pathfinder Workshop 2019
Authors: Artho Cyrille , Phan Quoc-Sang , Aldous Peter , Almaawi Alyas , Bang Lucas , Berglund Lasse , Bultan Tevfik , Chen Zhenbang , Converse Hayes , Dong Wei , Eiers William , Gligoric Milos , Goldsmith Simon , Grunske Lars , Hooker Joshua , Kadron Ismet Burak , Kehrer Timo , Khurshid Sarfraz , Le Xuan-Bach D. , Lo David , Mercer Eric , Misailovic Sasa , Namakonov Egor , Lam Nguyen Hoang , Noller Yannic , Ogles Benjamin , Padhye Rohan , Parizek Pavel , Păsăreanu Corina S. , Powell S. Jacob , Saha Seemanta , Sen Koushik , Sherman Elena , Storey Kyle , Tang Minxing , Visser Willem , Wang Ji , Yu Hengbiao
Published: May 2020

Java Path nder (JPF) was originally developed as an explicit- state software model checker, and subsequently evolved into an extensible Java bytecode analysis framework that has been suc- cessfully used to implement techniques such as symbolic and con- colic execution, compositional veri cation, parallel execution, in- cremental program analysis, and many more.

To share recent research progress with JPF and related tools among the community, we have organized the annual JPF work- shop with the Automated Software Engineering Conference (ASE) 2019, held in San Diego, California, USA. We invited submissions about on-going and existing research, experience, and position papers on topics (1) related to JPF, its extensions and applica- tions in various domains; and (2) Java/Android program analysis in general. This paper gives an overview of all presentations and papers of the workshop, as well the results of the discussions.
Understanding Software Security from Design to Deployment
Authors: Mirakhorli Mehdi , Galster Matthias , Williams Laurie
Published: May 2020

Analyzing, implementing and maintaining security requirements of software-intensive systems and achieving truly secure software requires planning for security from ground up, and continuously assuring that security is maintained across the software's lifecycle and even after deployment when software evolves. Given the increasing complexity of software systems, new application domains, dynamic and often critical operating conditions, the distributed nature of many software systems, and fast moving markets which put pressure on software vendors, building secure systems from ground up becomes even more challenging. Security-related issues have previously been targeted in software engineering sub-communities and venues. In the second edition of the International Workshop on Security from Design to Deployment (SEAD) at the International Conference on Automated Software Engineering (ASE) 2020, we aimed to bring the research and practitioner communities of requirements engineers, security experts, architects, developers, and testers together to identify foundations, and challenges, and to formulate solutions related to automating the analysis, design, implementation, testing, and maintenance of secure software systems.
Pains and Gains of Peer- Reviewing in Software Engineering
Authors: Soldani Jacopo
Published: May 2020

Peer-reviewing constitutes the reference mechanism for assuring the quality of scientific contributions in software engineering. In the teaser of this column series (i.e., [1]) we provided an overview of the current trends for peer reviewing in software engineering, including experienced pains and gains.
Teaching CS humbly, and watching the AI revolution
Authors: Guzdial Mark , Zhang Jiajie
Published: May 2020

The
Communications
Web site, http://cacm.acm.org, features more than a dozen bloggers in the BLOG@CACM community. In each issue of
Communications
, we'll publish selected posts or excerpts.
twitter
Follow us on Twitter at http://twitter.com/blogCACM http://cacm.acm.org/blogs/blog-cacm Mark Guzdial on a book that changed his thinking about teaching computer science, and Jiajie Zhang on the AI Revolution.
Deceiving the masses on social media
Authors: Kirkpatrick Keith
Published: May 2020

The social media platforms like their freedom, but information gerrymandering may require legislation to fix.
Secure development tools and techniques need more research that will increase their impact and effectiveness in practice
Authors: Shostack Adam , Zurko Mary Ellen
Published: May 2020

Secure development is an important and pressing problem.
Optimal chimes
Authors: Shasha Dennis
Published: May 2020

The importance of the space between the notes.
31st ACM International Conference on Hypertext and Social Media
Authors: Salter Anastasia , Barber John , Gadiraju Ujwal
Published: May 2020

The ACM Hypertext conference is a premium venue for peer-reviewed research on hypertext theory, systems, and applications. It is concerned with all aspects of modern hypertext research including social media, semantic web, dynamic and computed hypertext and hypermedia as well as narrative systems and applications.

Hypertext 2020 was originally intended to be held in Orlando, Florida, USA, between July 13 and 15th at the University of Central Florida's downtown campus. However, due to the global pandemic, it will be moving to a virtual format. The conference will be "virtually" co-located with the Electronic Literature Organization Conference and Media Arts Festival, with engagement events targeted at creating transdisciplinary conversation. This year's theme is Hypertext for Social Good, a theme exemplified by the work of our plenary speakers Safiya Noble, Noah Wardrip-Fruin, and Stuart Moulthrop. We briefly describe the conference below, and hope to see many of you "online" at Hypertext 2020!

Conference Website: http://ht.acm.org/ht2020

Twitter: @ACMHT https://twitter.com/ACMHT

Hashtag: #ACMHT20 https://twitter.com/hashtag/ACMHT20
Graph embedding algorithms for attributed and temporal graphs
Authors: Goyal Palash
Published: May 2020

Palash Goyal is a Senior Research Scientist at Samsung Research America. In 2019, he got his doctoral degree in Computer Science from University of Southern California under the advisory of Dr. Emilio Ferrara. Over the course of his PhD, he worked with several government funded projects including IARPA and DARPA spanning domains of time series prediction, text analysis and understanding social behavior. He also applied his work on graph embedding in various industrial settings including developing automation systems in Siemens Corporate, identifying key steam injection candidate oil wells for Chevron and developing recommendation system for Target. His work on tracking temporal evolution of graphs using non-timestamped data was nominated for best paper award in ACM Hypertext.

In his thesis, supervised by Dr. Emilio Ferrara (USC Information Sciences Institute), he ex- tended the work of learning low-dimensional representations of nodes in a graph in several di- rections. Firstly, he published a survey of existing graph embedding approaches and shed light into the dependency between them drawing insights into the relations effectively captured by the methods. He further proposed a benchmark to evaluate any graph embedding approach and un- derstand its applicability. Secondly, he built models to capture temporal patterns in sequential graphs and efficiently update embeddings for streaming graphs. Finally, he developed multi-modal models for learning representations through graph data as well as other forms of data available for the nodes and edges including text.
How Do Committees Invent? and Ironies of Automation
Authors: Colyer Adrian
Published: May 2020

The Lindy effect tells us that if a paper has been highly relevant for a long time, it’s likely to continue being so for a long time to come as well. My first choice is "How Do Committees Invent?" Author Melvin E. Conway provides a lot of great material that led up to the formulation of the law that bears his name. My second choice is Lisanne Bainbridge’s "Ironies of Automation." It’s a classic treatise on the counterintuitive consequences of increasing levels of automation.
How spelling reform would promote better writing and speaking
Authors: Yaffe Philip
Published: May 2020

Each "Communication Corner" essay is self-contained; however, they build on each other. For best results, before reading this essay and doing the exercise, go to the first essay "How an Ugly Duckling Became a Swan," then read each succeeding essay.

Instead of mastering the chaos of learning to read and write in English, perhaps we should start spelling things the way they sound.
A
Authors: Martignano Maurizio
Published: May 2020

While in the past in the C/C++ world compilers and static analyzers took two separate paths and were two separate lines of tools, nowadays they are coming back together, especially the Clang compiler and its Clang/LLVM based static analyzers. The paper will show why and how this "reunion" is beneficial, especially when analyzing large codebases. In particular the paper first will present these relatively new analyzers, then it will show how these tools are currently integrated in code quality platforms - e.g. SonarQube; finally, the paper will describe the author's recent results in terms of improving the analyzers - code quality platforms integration and facilitating the adoption and execution of static analysis in software projects.
Verification of Ada Programs with AdaHorn
Authors: Beyene Tewodros A. , Herrera Christian , Nigam Vivek
Published: May 2020

We propose AdaHorn, a model checker for verification of Ada programs with respect to correctness properties given as assertions. AdaHorn translates an Ada program together with its assertion into a set of Constrained Horn Clauses, and feeds it to a Horn constraints solver. We evaluate the performance of AdaHorn on a set of Ada programs inspired by C programs from the software verification competition (SV-COMP). Our experimental results show that AdaHorn outputs correct results in more cases than GNATProve, which is a widely used Ada verification framework.
Co-engineering of Safety and Security Life Cycles for Engineering of Automotive Systems
Authors: Bramberger Robert , Martin Helmut , Gallina Barbara , Schmittner Christoph
Published: May 2020

Nowadays systems are becoming more and more connected. Consequently, the co-engineering of (cyber)security and safety life cycles becomes paramount. Currently, no standard provides a structured co-engineering process to facilitate the communication between safety and security engineers. In this paper, we propose a process for co-engineering safety and security by the explicit systematization and management of commonalities and variabilities, implicitly stated in the requirements of the different standards. Our process treats the safety and security life cycles as members of a security-informed safety-oriented process line and so it forces safety and security engineers to come together and brainstorm on what might be considered a commonality and what might be considered a variability. We illustrate the usage of our process by systematizing commonalities and variabilities at risk analysis phase in the context of ISO 26262 and SAE J3061. We then draw lessons learnt. Finally, we sketch some directions for future work.
SIGCSE organizational updates
Authors: Decker Adrienne
Published: May 2020

On behalf of the SIGCSE Board, I hope that everyone is adjusting to these unprecedented times. From emergency remote teaching, to isolating in our homes, to taking care of ourselves and families, and adjusting to this new existence, the current world situation has touched all of us in numerous ways. As a SIGCSE community, there has been much discussion of how these changes will impact our courses and students on the SIGCSE-members listserv. If you are not already a member of this wonderful community resource, feel free to see this page (https://sigcse.org/sigcse/membership/ mailing-lists.html) for information for how to join us in that discussion.
ACM data science task force calls for curricula feedback and example courses
Authors: Danyluk Andrea , Leidig Paul
Published: May 2020

At the August 2017 ACM Education Council meeting, a task force was formed to add to the broad, interdisciplinary conversation on data science, with an articulation of the role of computing discipline-specific contributions to this emerging field. As an inherently interdisciplinary area, data science both draws from and generates interest within many fields, including computer science.
ICER 2020 preview
Authors: Moskal Adon , Robins Anothony , McCauley Renee , Ko Amy J.
Published: May 2020

You are warmly invited to the sixteenth annual ACM International Computing Education Research (ICER) conference, which will be held … in your living room! The dates (North American) remain 10-12 August 2020, but a later end date is under consideration (please see the website for updates).
Report on the 3rd International Joint Conference on Rules and Reasoning (RuleML+RR 2019)
Authors: Calvanese Diego , Fodor Paul , Montali Marco
Published: May 2020

The annual International Joint Conference on Rules and Reasoning (RuleML+RR) is an international conference on research, applications, languages and standards for rule technologies, rule-based programming and rule-based systems including production rules systems, logic programming rule engines, as well as business-rule engines and management systems; Semantic Web rule languages and rule standards, including RuleML (e.g., Datalog+ RuleML, Reaction RuleML and LegalRuleML), SWRL, RIF, Common Logic, PRR, decision rules and Decision Model and Notation (DMN), as well as Semantics of Business Vocabulary and Business Rules (SBVR); rule-based Event Processing Languages (EPLs) and technologies; and foundational research on inference rules, transformation rules, decision rules, production rules, and Event-Condition-Action (ECA) rules. In 2017, RuleML+RR joined the efforts of two wellestablished conference series: the International Web Rule Symposia (RuleML) and the Web Reasoning and Rule Systems (RR) conferences, and it is now the leading conference to build bridges between academia and industry in the field of Web rules and its applications, especially as part of the Semantic Technology stack. RuleML+RR is commonly listed together with and related to other major high-impact Artificial Intelligence conferences worldwide, starting with IJCAI in 2011 and 2016, ECAI in 2012, AAAI in 2013, ECAI in 2014, the AI Summit London in 2017, and GCAI in 2018 and 2019. The RuleML symposia and RR conferences have been held since 2002 and 2007, respectively. The RR conferences have been a forum for discussion and dissemination of new results on Web reasoning and rule systems, with an emphasis on rule-based approaches and languages. The RuleML symposia have been devoted to disseminating research, applications, languages, and standards for rule technologies, with attention to both theoretical and practical developments, to challenging new ideas, and to industrial applications. Building on the tradition of both, RuleML and RR, the joint conference series RuleML+RR aims at bridging academia and industry in the field of rules, and at fostering the cross-fertilization between the different communities focused on the research, development, and applications of rule-based systems. RuleML+RR aims at being the leading conference series for all subjects concerning theoretical advances, novel technologies, and innovative applications about knowledge representation and reasoning with rules.
Optimal Monitoring Strategies for Critical Infrastructure Networks
Authors: Palani Kartik , Nicol David M.
Published: May 2020

Given a choice among multiple security monitoring solutions and multiple locations to deploy them,what strategy best protects the network? What metric is used to compare different securing strategies? What constraints make it harder/easier to secure critical infrastructure networks? This paper explores these questions and formalizes the network monitoring strategy problem for critical infrastructure networks. It also presents a deterministic polynomial time algorithm for discovering a near-optimal network monitoring strategy.
Cascading Failures in Interconnected Power-to-Water Networks
Authors: Pournaras Evangelos , Taormina Riccardo , Thapa Manish , Galelli Stefano , Palleti Venkata , Kooij Robert
Published: May 2020

The manageability and resilience of critical infrastructures, such as power and water networks, is challenged by their increasing interdependence and interconnectivity. Power networks often experience cascading failures, i.e. blackouts, that have unprecedented economic and social impact. Al- though knowledge exists about how to control such complex non-linear phenomena within a single power network, little is known about how such failures can spread and coevolve in the water network when failing power components energize the water distribution infrastructure, i.e. pumps and valves. This paper studies such a scenario and specifically the impact of power cascading failures on shortages of water supply. A realistic exemplary of an interconnected power-to-water network is experimentally evaluated using a modular simulation approach. Power and waterflow dynamics are simulated separately by taking into account different maximum powerlines capacities and water demand requirements. Results showcase the strong dependency of urban water sup- ply systems on the reliability of power networks, with severe shortages of water supply being caused by failures originating indistant power lines, especially for heavily loaded power networks.
Scheduling Post-disaster Repairs in Electricity Distribution Networks with Uncertain Repair Times
Authors: Tan Yushi , Das Arindam K. , Ahumada-Paras Mareldi , Arabshahi Payman , Kirschen Daniel S.
Published: May 2020

Natural disasters, such as hurricanes, large wind and ice storms, typically require the repair of a large number of com- ponents in electricity distribution networks. Since power cannot be restored before the completion of repairs, optimally scheduling the available crews to minimize the cu- mulative duration of the customer interruptions reduces the harm done to the affected community. We have previously proposed approximation algorithms to schedule post-disaster repairs in electricity distribution networks with complete damage information[1]. In this paper, we extend our pre- vious work to the case with incomplete damage information. We model this problem as scheduling a set of jobs with stochastic processing times on parallel identical machines in order to minimize the total weighted energization time. A linear programming (LP) based list scheduling pol- icy is proposed and then analyzed in terms of theoretical performance.
Helping learners as they construct knowledge: How can instructors leverage research findings
Authors: Viswanathan Viswa K.
Published: May 2020

The author presents research-based principles that can improve the recall of factual subject matter using existing features in LMS tools, apps, and other methods to meet targeted learning goals.
Ustilaginoidea virens: Insights into an Emerging Rice Pathogen
Authors: Sun Wenxian , Fan Jing , Fang Anfei , Li Yuejiao , Tariqjaveed Muhammad , Li Dayong , Hu Dongwei , Wang Wen-Ming
Published: May 2020

False smut of rice, caused by Ustilaginoidea virens, has become one of the most important diseases in rice-growing regions worldwide. The disease causes a significant yield loss and imposes health threats to humans and animals by producing mycotoxins. In this review, we update our understanding of the pathogen, including the disease cycle and infection strategies, the decoding of the U. virens genome, comparative/functional genomics, and effector biology. Whereas the decoding of the U. virens genome unveils specific adaptations of the pathogen in successfully occupying rice flowers, progresses in comparative/functional genomics and effector biology have begun to uncover the molecular mechanisms underlying U. virens virulence and pathogenicity. We highlight the identification and characterization of the produced mycotoxins and their biosynthetic pathways in U. virens.The management strategies for this disease are also discussed. The flower-specific infection strategy makes the pathogen a unique tool to unveil novel mechanisms for the interactions between nonobligate biotrophic pathogens and their hosts.
Field Equations and Lagrangian of the Kaluza Energy-Momentum Tensor
Authors: Williams L. L.
Published: May 2020

We provide an analysis and statement of the source term in the classical Kaluza field equations, by considering the 5-dimensional (5D) energy-momentum tensor corresponding to the 5D geodesic hypothesis that is typically presumed in the Kaluza theory. By providing the 5D matter Lagrangian, this work completes a Lagrangian analysis of the classical Kaluza theory that began by establishing the proper form of the unique Kaluza field Lagrangian. This work considers the transformation properties necessitated by general covariance of the Kaluza source terms, to establish the correct form for the source terms in the field equations, and to establish the 5D matter Lagrangian that corresponds to the 5D geodesic hypothesis. In addition to the effects of a scalar field expected from other scalar-tensor or scalar-electromagnetic theories, a peculiar Kaluza coupling coefficient arises for charged matter which acts to vary the source strengths in ways unknown to conventional physics. We briefly evaluate the implied modifications to source terms in the field equations. We find an ADM-like neutralization of gravity at high specific charge states and a saturation in field strength at high specific charge-to-mass ratios.
Mulberry Fruit Prevents Diabetes and Diabetic Dementia by Regulation of Blood Glucose through Upregulation of Antioxidative Activities and CREB/BDNF Pathway in Alloxan-Induced Diabetic Mice
Authors: Min A Young , Yoo Jae-Myung , Sok Dai-Eun , Kim Mee Ree
Published: May 2020

Although mulberry fruit has various beneficial effects, its effect on diabetes-related dementia remains unknown. We investigated whether the ethyl acetate fraction of ethanolic extract of mulberry fruit (MFE) could alleviate biochemical and behavioral deficits in alloxan-induced diabetic mice. In the diabetic mice, MFE considerably abolished multiple deficits, e.g., body weight reduction; water and food intake increase; and hyperglycemia, hyperlipidemia, hypoinsulinism, and hypertrophy of the liver, kidneys, spleen, and brain. A 200 mg/kg MFE dose reduced malondialdehyde levels and improved antioxidant enzyme activity in the liver, kidney, and brain tissues. MFE attenuated hyperglycemia-induced memory impairments and acetylcholine deprivation, protected neuronal cells in CA1 and CA3 regions via p-CREB/BDNF pathway activation, and reduced amyloid-β precursor protein and p-Tau expressions in the brain tissue. In conclusion, MFE exerts antidiabetic and neuroprotective effects by upregulating antioxidative activities and p-CREB/BDNF pathway in chronic diabetes. Therefore, MFE may be used as a therapeutic agent for diabetes and diabetic neurodegenerative diseases.
Advanced Ultrasound Screening for Temporomandibular Joint (TMJ) Internal Derangement
Authors: Friedman Saul N. , Grushka Miriam , Beituni Hussam K. , Rehman Madhu , Bressler Hart B. , Friedman Lawrence
Published: May 2020

Purpose. To present an advanced ultrasound (US) technique and propose its use as a screening diagnostic tool for temporomandibular joint (TMJ) internal derangement. Materials and Methods. The technique is based on maintaining the US probe parallel to the articular disc, rather than traditional axial and coronal views, with the position described relative to a clock face. Validation was achieved by direct comparison with magnetic resonance imaging (MRI). A total of 61 patients, with age ranging from 13 to 67 years, were prescreened for TMJ pain and internal derangement, underwent US imaging for screening, and MRI evaluation for final diagnosis. Results. 29 of the 61 patients had disc pathology on MRI. US screening produced no false positive results and only 6 false negative results, corresponding to a sensitivity of 79% and specificity of 100%. Half of the false negative cases involved disc pathology with a medial component to the disc displacement. Conclusion. US is both a sensitive and a specific screening tool for TMJ dysfunction when used by an appropriately trained operator, with the exception of medially displaced discs. If TMJ assessment is found to be abnormal, the patient should be referred for MRI, and any patient scheduled for surgery must have the diagnosis confirmed by MRI. If a component of medial disc displacement is suspected, MRI should be performed despite a normal screening US.
Research Advances on Biosynthesis, Regulation, and Biological Activities of Apocarotenoid Aroma in Horticultural Plants
Authors: Shi Jianan , Cao Chao , Xu Jiayu , Zhou Chunhua
Published: May 2020

Apocarotenoids, which play important roles in the growth and development of horticultural plants, are produced by the action of carotenoid cleavage oxygenase (CCO) family members or nonenzymatic cleavage actions. Apocarotenoids are commonly found in leaves, flowers, and fruits of many horticultural plants and participate in the formation of pigments, flavors, hormones, and signaling compounds. Some of them are recognized as important aroma components of fruit and flower with aromatic odor, such as βß-ionone, β-damascenone, and 6-methyl-5-hepten-2-one in tomato fruit, and have low odor thresholds with β-ionone having odor threshold of only 0.007 ppb. In this review, the main apocarotenoid aroma components in horticultural plants were listed, and factors influencing their production were discussed at first. Then, the biosynthetic pathway of apocarotenoid aromas was briefly introduced, and the CCDs gene family was highlighted, and the nonenzymatic production of apocarotenoid aromas was also mentioned. Next, chemical and molecular regulations of apocarotenoid aromas and their biological activities were summarized. Finally, further exploration aspects needed were suggested. We anticipate that this review can afford some crucial information for comprehensive application of apocarotenoid volatile compounds in horticultural plants.
An Eco-Inefficiency Dominance Probability Approach for Chinese Banking Operations Based on Data Envelopment Analysis
Authors: Li Feng , Wu Lunwen , Zhu Qingyuan , Yu Yanling , Kou Gang , Liao Yi
Published: May 2020

Data envelopment analysis (DEA) has proven to be a powerful technique for assessing the relative performance of a set of homogeneous decision-making units (DMUs). A critical feature of conventional DEA approaches is that only one or several sets of optimal virtual weights (or multipliers) are used to aggregate the ratio performance efficiencies, and thus, the efficiency scores might be too extreme or even unrealistic. Alternatively, this paper aims at developing a new performance dominance probability approach and applying it to analyze the banking operations in China. Towards that purpose, we first propose an extended eco-inefficiency model based on the DEA methodology to address banking activities and their possible relative performances. Since the eco-inefficiency will be obtained using a set of optimal weights, we further build a performance dominance structure by considering all sets of feasible weights from a data-driven perspective. Then, we develop two pairwise eco-inefficiency dominance concepts and propose the inefficiency dominance probability model. Finally, we illustrate the eco-inefficiency dominance probability approach with 32 Chinese listed banks from 2014 to 2018 to demonstrate the usefulness and efficacy of the proposed method.
From ACTH-Dependent to ACTH-Independent Cushing’s Syndrome from a Malignant Mixed Corticomedullary Adrenal Tumor: Potential Role of Embryonic Stem Cells
Authors: Ramírez-Rentería Claudia , Espinosa-De-Los-Monteros Ana Laura , Etual Espinosa-Cardenas , Marrero-Rodríguez Daniel , Castellanos Guillermo , Arreola-Rosales Rocio , Montoya-Martinez Guillermo , Taniguchi-Ponciano Keiko , Briseño-Díaz Paola , Padilla-Cristerna Mayte Lizeth , Figueroa-Corona María del Pilar , Moises Mercado
Published: May 2020

Context. Truly, mixed corticomedullary adrenal tumors (MCATs) may not come from colliding tumors but from a single stem cell. Objective. To report the immunohistochemical and molecular evaluation of a patient with ectopic ACTH syndrome (EAS) from a MCAT which has single cells with features of both 96 medullary and cortical differentiation. Case Description and Methods. A 16-year-old woman presented with severe EAS and a large right MCAT composed of ACTH-secreting cells resembling pheochromocytoma and another lineage similar to adrenal carcinoma. Immunohistochemistry (IHC) showed positivity for medullary (ACTH, chromogranin A, synaptophysin, and PS-100) and epithelial components (inhibin, melan-A, and calretinin). Embryonic stem cell markers were evaluated using RT/PCR and immunofluorescence. After initial surgery, the tumor recurred shifting to rapidly progressive ACTH-independent liver metastasis. Results. Histopathology and IHC revealed two distinct and intermingled cellular patterns, while some cells immunostained for both medullary and cortical markers. Demonstration of all stem cell biomarkers by RT/PCR and immunofluorescence was predominantly localized to the nucleus, whereas SOX2 immunoreactivity was evident in the cytoplasm as well. Conclusion. The expression of cancer stem cell biomarkers points towards the involvement of primitive embryonic cells as the origin of this neoplasm and maybe to the clinically aggressive and biochemically changing behavior.
How Different Government Subsidy Objects Impact on Green Supply Chain Decision considering Consumer Group Complexity
Authors: Meng Qingfeng , Li Mengwan , Li Zhen , Zhu Jing
Published: May 2020

This paper fully considers the complexity characteristics of the consumer group, such as the heterogeneity of consumer environmental preferences and consumption levels and constructs a two-stage price decision model of green supply chain composed of the manufacturer and retailers. Under the four different scenarios, no government subsidies, government subsidies are given to the manufacturer, government subsidies are given to the green product retailer, and government subsidies are given to green product consumers, the impact of government subsidies on green supply chain member price decisions is analyzed, and the validity of the model is verified by an example. The results show that compared with the no government subsidies, government subsidies to the manufacturer will reduce the wholesale and sales prices of green products, and subsidies to the green product retailer will lead to higher wholesale prices and lower sales prices of green products, and subsidies to green product consumers will increase the wholesale and sales prices of green products. No matter which object is subsidized by the government, the wholesale price of general products will not change and the sales price will decrease. Government subsidies will facilitate the sales of green products, thereby expanding the market share of green products.
Detection and Prognosis of Prostate Cancer Using Blood-Based Biomarkers
Authors: Jin Wei , Fei Xiang , Wang Xia , Song Yan , Chen Fangjie
Published: May 2020

Prostate cancer (PCa) is second only to lung cancer as a cause of death. Clinical assessment of patients and treatment efficiency therefore depend on the disease being diagnosed as early as possible. However, due to issues regarding the use of prostate-specific antigen (PSA) for screening purposes, PCa management is among the most contentious of healthcare matters. PSA screening is problematic primarily because of diagnosis difficulties and the high rate of false-positive biopsies. Novel PCa biomarkers, such as the Prostate Health Index (PHI) and the 4Kscore, have been proposed in recent times to improve PSA prediction accuracy and have shown higher performance by preventing redundant biopsies. The 4Kscore also shows high precision in determining the risk of developing high-grade PCa, whereas elevated PHI levels suggest that the tumor is aggressive. Some evidence also supports the effectiveness of miRNAs as biomarkers for distinguishing PCa from benign prostatic hyperplasia and for assessing the aggressiveness of the disease. A number of miRNAs that possibly act as tumor inhibitors or oncogenes are impaired in PCa. These new biomarkers are comprehensively reviewed in the present study in terms of their potential use in diagnosing and treating PCa.
A Mixed Discontinuous Galerkin Method for the Helmholtz Equation
Authors: Hu Qingjie , He Yinnian , Li Tingting , Wen Jing
Published: May 2020

In this paper, we introduce and analyze a mixed discontinuous Galerkin method for the Helmholtz equation. The mixed discontinuous Galerkin method is designed by using a discontinuous Pp+1−1−Pp−1 finite element pair for the flux variable and the scattered field with p≥0. We can get optimal order convergence for the flux variable in both Hdiv-like norm and L2 norm and the scattered field in L2 norm numerically. Moreover, we conduct the numerical experiments on the Helmholtz equation with perturbation and the rectangular waveguide, which also demonstrate the good performance of the mixed discontinuous Galerkin method.