nils-herrmann/clean_scirepeval huggingface dataset:
ONOS: towards an open, distributed SDN OS
Venue: HotSDN
Year: 2014

We present our experiences to date building ONOS (Open Network Operating System) an experimental distributed SDN control platform motivated by the performance, scalability, and availability requirements of large operator networks. We describe and evaluate two ONOS prototypes. The first version implemented core features: a distributed, but logically centralized, global network view; scale out; and fault tolerance. The second version focused on improving performance. Based on experience with these prototypes, we identify additional steps that will be required for ONOS to support use cases such as core network traffic engineering and scheduling, and to become a usable open source, distributed network OS platform that the SDN community can build upon.
Overcoming late entry: the importance of entry position, inferences and market leadership
Year: 2015

There are two key unresolved questions that need to be addressed in order to understand the challenge of a late entry. Do late entrants that achieve market share leadership actually incur a market share penalty associated with their entry position? Is their specific entry position a contributing factor or irrelevant to their success? To address these questions, this article uses a consumer scanner data set containing 360 late entrants, 38 of which achieved market share leadership, to inform a regression analysis examining late entrant performance. As a result of our investigation exploring how late entrants can use marketing mix instruments to challenge incumbents, we propose that although late entry generally leads to a market share disadvantage, several opportunities remain for late entrants to excel.
Application Problems Vs Pure Mathematics Questions: Students' Perspectives
Year: 2017

The paper presents results of two case studies with undergraduate students majoring in applied mathematics and engineering. The first case study deals with students' preferences and difficulties with application problems and pure mathematics questions in their courses. The students were taking a second year course on ordinary differential equations (ODE) The students were asked about their preferences in dealing with application problems and pure mathematics questions and their difficulties with solving application problems not only in the ODE course but also in other courses. The second case study deals with students' preferences for application problems and pure mathematics questions in their first and second year engineering mathematics courses. The students were majoring in engineering. Students' responses are presented and discussed in the paper.
Research Advance in Swarm Robotics
Year: 2013

The research progress of swarm robotics is reviewed in details. The swarm robotics inspired from nature is a combination of swarm intelligence and robotics, which shows a great potential in several aspects. First of all, the cooperation of nature swarm and swarm intelligence are briefly introduced, and the special features of the swarm robotics are summarized compared to a single robot and other multi individual systems. Then the modeling methods for swarm robotics are described, followed by a list of several widely used swarm robotics entity projects and simulation platforms. Finally, as a main part of this paper, the current research on the swarm robotic algorithms are presented in detail, including cooperative control mechanisms in swarm robotics for flocking, navigating and searching applications.
A Stealth Cyber Attack Detection Strategy for DC Microgrids
Venue: IEEE Transactions on Power Electronics
Year: 2019

This paper proposes a cooperative mechanism for detecting potentially deceptive cyber attacks that attempt to disregard average voltage regulation and current sharing in cyber physical dc microgrids. Considering a set of conventional cyber attacks, the detection becomes fairly easy for distributed observer based techniques. However, a well planned set of balanced attacks, termed as the stealth attack, can bypass the conventional observer based detection theory as the control objectives are met without any physical error involved. In this paper, we discuss the formulation and associated scope of instability from stealth attacks to deceive distributed observers realizing the necessary and sufficient conditions to model such attacks. To address this issue, a novel cooperative vulnerability factor (CVF) framework for each agent is introduced, which accurately identifies the attacked agent(s) under various scenarios. To facilitate detection under worst cases, the CVFs from the secondary voltage control sublayer is strategically cross coupled to the current sublayer, which ultimately disorients the control objectives in the presence of stealth attacks and provides a clear norm for triggering defense mechanisms. Finally, the performance of the proposed detection strategy is simulated in MATLAB/SIMULINK environment and experimentally validated for false data injection and stealth attacks on sensors and communication links.
A Drosophila Model for EGFR Ras and PI3K Dependent Human Glioma
Venue: PLoS genetics
Year: 2009

Gliomas, the most common malignant tumors of the nervous system, frequently harbor mutations that activate the epidermal growth factor receptor (EGFR) and phosphatidylinositol 3 kinase (PI3K) signaling pathways. To investigate the genetic basis of this disease, we developed a glioma model in Drosophila. We found that constitutive coactivation of EGFR Ras and PI3K pathways in Drosophila glia and glial precursors gives rise to neoplastic, invasive glial cells that create transplantable tumor like growths, mimicking human glioma. Our model represents a robust organotypic and cell type specific Drosophila cancer model in which malignant cells are created by mutations in signature genes and pathways thought to be driving forces in a homologous human cancer. Genetic analyses demonstrated that EGFR and PI3K initiate malignant neoplastic transformation via a combinatorial genetic network composed primarily of other pathways commonly mutated or activated in human glioma, including the Tor, Myc, G1 Cyclins Cdks, and Rb E2F pathways. This network acts synergistically to coordinately stimulate cell cycle entry and progression, protein translation, and inappropriate cellular growth and migration. In particular, we found that the fly orthologs of CyclinE, Cdc25, and Myc are key rate limiting genes required for glial neoplasia. Moreover, orthologs of Sin1, Rictor, and Cdk4 are genes required only for abnormal neoplastic glial proliferation but not for glial development. These and other genes within this network may represent important therapeutic targets in human glioma.
CoP Doped MOF Based Electrocatalyst for pH Universal Hydrogen Evolution Reaction.
Venue: Angewandte Chemie
Year: 2019

Although electrocatalysts based on transition metal phosphides (TMPs) with cationic/anionic doping have been widely studied for hydrogen evolution reaction (HER) the origin of performance enhancement still remains elusive mainly due to the random dispersion of dopants. Herein, we report a controllable partial phosphorization strategy to generate CoP species within the Co based metal organic framework (Co MOF) Density functional theory calculations and experimental results reveal that the electron transfer from CoP to Co MOF through N P/N Co bonds could lead to the optimized adsorption energy of H2 O (DG H 2 O and hydrogen (DGH* which, together with the unique porous structure of Co MOF, contributes to the remarkable HER performance with an overpotential of 49 mV at a current density of 10 mA cm 2 in 1 m phosphate buffer solution (PBS, pH 7.0) The excellent catalytic performance exceeds almost all the documented TMP based and non noble metal based electrocatalysts. In addition, the CoP/Co MOF hybrid also displays Pt like performance in 0.5 m H2 SO4 and 1 m KOH, with the overpotentials of 27 and 34 mV, respectively, at a current density of 10 mA cm 2
A global local approach for hydraulic phase field fracture in poroelastic media
Venue: Comput. Math. Appl.
Year: 2021

In this work, phase field modeling of hydraulic fractures in porous media is extended towards a global local approach. Therein, the failure behavior is solely analyzed in a (small) local domain. In the surrounding medium, a simplified and linearized system of equations is solved. Both domains are coupled by Robin type interface conditions. The fracture(s) inside the local domain are allowed to propagate and consequently both subdomains change within time. Here, a predictor corrector strategy is adopted in which the local domain is dynamically adjusted to the current fracture pattern. The resulting framework is algorithmically described in detail and substantiated with some numerical tests.
School Climate, Academic Achievement and Educational Aspirations in Roma Minority and Bulgarian Majority Adolescents
Venue: Child youth care forum
Year: 2018

BackgroundSchool climate can promote students' academic achievement and high educational aspirations. School climate refers to the quality and character of school life, norms, values, social interactions and organizational processes within a school.ObjectiveWe examined for the present sample whether (a) school climate relates to academic achievement and educational aspirations and (b) such relations vary for Roma minority compared to their majority peers.MethodParticipants in this cross sectional study were 356 adolescents aged 11 19 years old (159 Roma, 197 Bulgarian majority) 332 mothers (149 Roma, 183 majority) 231 fathers (104 Roma, 127 majority) and 221 majority teachers who completed self report surveys to address the study goals. Adolescents provided data on educational aspirations and academic achievement, parents on their children's educational aspirations and teachers reported on school climate. We employed linear mixed models to explore associations of school climate, academic achievement and educational aspirations among Roma and Bulgarian majority youth.ResultsThere were negative associations between teacher reported school climate and students' academic achievement, as well as adolescent and parental educational aspirations for Roma adolescents only. Roma adolescents and parents reported lower academic achievement and educational aspirations than their majority counterparts.ConclusionsThis study supports the relevance of school climate in relation to academic achievement and aspirations of disadvantaged minority students. Interventions should pay close attention to perceptions and attitudes in a school to successfully promote positive outcomes among students.
Numerical Investigation of the Rotor Rotor Aerodynamic Interaction for eVTOL Aircraft Configurations
Year: 2020

The rotor rotor aerodynamic interaction is one of the key phenomena that characterise the flow and the performance of most of the new urban air mobility vehicles (eVTOLs) developed in the recent years. The present article describes a numerical activity that aimed to the systematic study of the rotor rotor aerodynamic interaction with application to the flight conditions typical of eVTOL aircraft. The activity considers the use of a novel mid fidelity aerodynamic solver based on vortex particle method. In particular, numerical simulations were performed when considering two propellers both in side by side and tandem configuration with different separation distances. The results of numerical simulations showed a slight reduction of the propellers performance in side by side configuration, while a remarkable loss of thrust in the order of 40% and a reduction of about 20% of the propulsive efficiency were found in tandem configuration, particularly when the propeller disks are completely overlapped. Moreover, the flow field analysis enabled providing a detailed insight regarding the flow physics involved in such aerodynamic interactions.
Investigation of Speaker Group Dependent Modelling for Recognition of Affective States from Speech
Venue: Cognitive Computation
Year: 2014

For successful human machine interaction (HCI) the pure textual information and the individual skills, preferences, and affective states of the user must be known. Therefore, as a starting point, the user's actual affective state has to be recognized. In this work we investigated how additional knowledge, for example age and gender of the user, can be used to improve recognition of affective state. Two methods from automatic speech recognition are used to incorporate age and gender differences in recognition of affective state: speaker group dependent (SGD) modelling and vocal tract length normalisation (VTLN) The investigations were performed on four corpora with acted and natural affected speech. Different features and two methods of classification (Gaussian mixture models (GMMs) and multi layer perceptrons (MLPs) were used. In addition, the effects of channel compensation and contextual characteristics were analysed. The results are compared with our own baseline results and with results reported in the literature. Two hypotheses were tested. First, incorporation of age information further improves speaker group dependent modelling. Second, acoustic normalization does not achieve the same improvement as achieved by speaker group dependent modelling, because the age and gender of a speaker affects the way emotions are expressed.
Deep Learning for Drug Design: an Artificial Intelligence Paradigm for Drug Discovery in the Big Data Era
Venue: The AAPS Journal
Year: 2018

Over the last decade, deep learning (DL) methods have been extremely successful and widely used to develop artificial intelligence (AI) in almost every domain, especially after it achieved its proud record on computational Go. Compared to traditional machine learning (ML) algorithms, DL methods still have a long way to go to achieve recognition in small molecular drug discovery and development. And there is still lots of work to do for the popularization and application of DL for research purpose, e.g. for small molecule drug research and development. In this review, we mainly discussed several most powerful and mainstream architectures, including the convolutional neural network (CNN) recurrent neural network (RNN) and deep auto encoder networks (DAENs) for supervised learning and nonsupervised learning; summarized most of the representative applications in small molecule drug design; and briefly introduced how DL methods were used in those applications. The discussion for the pros and cons of DL methods as well as the main challenges we need to tackle were also emphasized.
Review on the electromagnetic interference shielding properties of carbon based materials and their novel composites: Recent progress, challenges and prospects
Year: 2021

The rapid development of electronic devices have brought increased concern on electromagnetic radiation (EMR) problems. The radiated EM waves can not only affect the normal operation of devices, but also threat people's health. The most effective way to solve the EM pollution is to fabricate electromagnetic interference shielding materials (ESMs) and microwave absorption materials (MAMs) with lightweight, strong attenuation ability, and excellent mechanical stability. In this case, carbon materials and their nanocomposites attracted great attentions in the fields of electromagnetic interference (EMI) shielding due to the advantages of low density, natural abundance, easy preparation, excellent conductivity and flexibility. In this review, we firstly carried out a summary of recent achievements for carbon materials with different microstructures as ESMs/MAMs during the past five years. It is found that 3D carbon materials such as foams, sponges, and aerogels, as well as their composites are favorable for enhancing the EMI shielding efficiency. Then we introduced the latest progress of novel composites including MXene/carbon composites and metal organic frameworks (MOFs) derived porous carbon nanocomposites. In the end, current challenges and prospects were proposed toward the development of carbon based materials as ESMs/MAMs, which indicated the trend and key point for future research.
Candidate Genes for Aggression and Antisocial Behavior: A Meta analysis of Association Studies of the 5HTTLPR and MAOA uVNTR
Venue: Behavior genetics
Year: 2014

Variation in central serotonin levels due to genetic mutations or experimental modifications has been associated with the manifestation of aggression in humans and animals. Many studies have examined whether common variants in serotonergic genes are implicated in aggressive or antisocial behaviors (ASB) in human samples. The two most commonly studied polymorphisms have been the serotonin transporter linked polymorphic region of the serotonin transporter gene (5HTTLPR) and the 30 base pair variable number of tandem repeats of the monoamine oxidase A gene (MAOA uVNTR) Despite the aforementioned theoretical justification for these polymorphisms, findings across studies have been mixed and are thus difficult to interpret. A meta analysis of associations of the 5HTTLPR and MAOA uVNTR with ASB was conducted to determine: (1) the overall magnitude of effects for each polymorphism, (2) the extent of heterogeneity in effect sizes across studies and the likelihood of publication bias, and (3) whether sample level or study level characteristics could explain observed heterogeneity across studies. Both the 5HTTLPR and the MAOA uVNTR were significantly associated with ASB across studies. There was also significant and substantial heterogeneity in the effect sizes for both markers, but this heterogeneity was not explained by any sample level or study level characteristics examined. We did not find any evidence for publication bias across studies for the MAOA uVNTR, but there was evidence for an oversampling of statistically significant effect sizes for the 5HTTLPR. These findings provide support for the modest role of common serotonergic variants in ASB. Implications regarding the role of serotonin in antisocial behavior and the conceptualization of antisocial and aggressive phenotypes are discussed.
FPGA implementation of unsigned multiplier circuit based on quaternary signed digit number system
Venue: 2017 4th International Conference on Signal Processing, Computing and Control (ISPCC)
Year: 2017

Digital systems are mainly used in data processing, control systems and computation. They are having numberof advantages over analog system: one of advantage is fast arithmetic operation. There are different techniques for performing arithmetic operations such as Binary Signed Digit(BSD) Wallace, Booth multiplication etc. Using binary number system for arithmetic operation generates carry which creates delay and reduce the speed of operation. To overcome this problem we are using higher radix number system such as Quaternary Signed Digit (QSD) QSD number system is base 4 number system. QSD is represented by decimal numbers as 0, 1, 2 and 3. It is responsible for carry free arithmetic operations. In this paper we proposed a high speed, low power QSD multiplier which is capable of doing carry free operation. This circuit can multiply both signed and unsigned numbers without any extra delay. This circuit also increases the speed of operation and is less complex. The circuit is simulated on XilinxSPARTAN 3E 100or250 field programmable gate array (FPGA) board using Verilog HDL.
A new algorithm for probabilistic planning based on multi objective optimization
Venue: 2008 International Conference on Machine Learning and Cybernetics
Year: 2008

With the fast development of AI planning, planning technology has been widely applied to robotics and automated cybernetics. Many researchers pay more and more attention to the uncertainty in AI planning, probabilistic planning is a important branch of uncertainty planning. In realistic domains, probabilistic planning often involves multiple objectives, where it aims to generate optimal set of plans to satisfy all these objectives. To date, most of probabilistic plan algorithms have only focused on single objective formulations that bound one of the objectives by making some unnatural assumptions. In this paper, we focus on the probabilistic planning problem with multiple objectives, and we introduce the multi objective optimization method into probabilistic planning to define the multi objective value function, we extend the single objective probabilistic algorithm learning depth first search (LDFS) to its multi objective counterpart multi objective LDFS (MLDFS).We explain our implemented algorithm, the objective function we redefined, make conclusion and discuss our future work based on this framework.
Guidelines for Diagnosis and Treatment of Familial Hypercholesterolemia 2017
Venue: Journal of atherosclerosis and thrombosis
Year: 2018

Statement Familial hypercholesterolemia (FH) is an autosomal hereditary disease with the 3 major clinical features of hyper LDL cholesterolemia, premature coronary artery disease and tendon and skin xanthomas. As there is a considerably high risk of coronary artery disease (CAD) in addition to early diagnosis and intensive treatment, family screening (cascade screening) is required (Recommendation level A) For a diagnosis of FH, at least 2 of the following criteria should be satisfied: 1 LDL C 180 mg/dL, 2 Tendon/skin xanthomas, 3 History of FH or premature CAD within 2nd degree blood relatives (Recommendation level A) Intensive lipid lowering therapy is necessary for the treatment of FH. First line drug should be statins. (Recommendation level A, Evidence level 3) Screening for CAD as well as asymptomatic atherosclerosis should be conducted periodically in FH patients.
Synoptic analysis of dust storm over Arabian Peninsula: a case study on February 28, 2009
Venue: Natural Hazards
Year: 2018

Sand and dust storms are causing hazards and problems in aviation as well as the dangers and distresses they cause on living things. The low meteorological visibility, the presence of strong winds with gust, and the transport of dust and sand particles by the wind are dangerous on landing and departure of aircrafts, and even on planes that are parked. The main aim of the study is to examine the meteorological conditions causing the dust storm that took place in the Arabian Peninsula on February 28, 2009, and to determine the source of dust caused dust storm, sand storm, blown sand, and blown dust at the airports. Within the scope of the study, aviation routine weather report (METAR) and aviation selected special weather report (SPECI) reports have been assessed at many airports over Arabian Peninsula (AP) the northern part of the AP and North Africa. As model outputs; NCEP DOE Reanalysis 2 data, BSC DREAM8B, and HYSPLIT model were used. In the satellite images; METEOSAT MSG dust RGB images, MODIS, and Kalpana 1 data were used. According to obtained results, dust storms were detected in Bahrain, Kuwait, Saudi Arabia, and United Arab Emirates (UAE) At Al Ahsa Airport in Saudi Arabia, the lowest visibility measured on February 28, 2009, dropping to 200 m, which was dominated by blowing sand. The source region of the dust observed at Dubai Airport in UAE is the eastern regions of the Rub'al Khali Desert located between Saudi Arabia, Oman, and UAE.