nils-herrmann/clean_scirepeval huggingface dataset:
A Task Allocation Approach for Human Robot Collaboration in Product Defects Inspection Scenarios
Venue: 2020 29th IEEE International Conference on Robot and Human Interactive Communication (RO MAN)
Year: 2020

The presence and coexistence of human operators and collaborative robots in shop floor environments raises the need for assigning tasks to either operators or robots, or both. Depending on task characteristics, operator capabilities and the involved robot functionalities, it is of the utmost importance to design strategies allowing for the concurrent and/or sequential allocation of tasks related to object manipulation and assembly. In this paper, we extend the FLEXHRC framework presented in  to allow a human operator to interact with multiple, heterogeneous robots at the same time in order to jointly carry out a given task. The extended FLEXHRC framework leverages a concurrent and sequential task representation framework to allocate tasks to either operators or robots as part of a dynamic collaboration process. In particular, we focus on a use case related to the inspection of product defects, which involves a human operator, a dual arm Baxter manipulator from Rethink Robotics and a Kuka youBot mobile manipulator.
CAR T Cell Therapy in Acute Lymphoblastic Leukemia and Potential for Chronic Lymphocytic Leukemia
Venue: Current Treatment Options in Oncology
Year: 2016

transfer of autologous T cells engineered to express a chimeric antigen receptor (CAR) represents a powerful targeted immunotherapy that has shown great promise in some of the most refractory leukemias. CAR modified T cells directed against CD19 have led the way, setting a high standard with remission rates as high as 90 in clinical trials for relapsed/refractory acute lymphoblastic leukemia (ALL) Yet, the first demonstration of efficacy was in another disease, chronic lymphocytic leukemia (CLL) in which CD19 targeted CAR T cells eradicated bulky, highly refractory disease. Despite early encouraging results, clinical trials in CLL have yielded lower response rates, revealing disease specific differences in response in this form of immunotherapy. Ongoing research focused on identifying and overcoming these limitations, promises to improve response rates. Beyond the induction of remission, the transformative impact of engineered T cell therapy lies in its potential for long term disease control. With longer follow up and durable T cell persistence now reported, we are closer to answering the question of whether sustained remissions are possible with CAR T cell monotherapy. As might be expected with a highly effective therapy using a single mechanism of action, escape pathways have emerged. Combinatorial approaches are needed to anticipate and prevent this mode of relapse. Lastly, toxicity management is vital to ensure the safety of this exciting cancer immunotherapy.
The Crisis Close at Hand: How COVID 19 Challenges Long Term Care Planning for Adults with Intellectual Disability
Venue: Health equity
Year: 2020

Whether cared for in the community or in a facility, adults with intellectual disability are among the most vulnerable individuals in the United States. Families caring for these individuals face financial, social, and emotional stress as they navigate long term care choices for their loved ones. COVID 19 has stressed an already overwhelmed and disparate system.
Optimal Stackelberg Strategies for Closed Loop Supply Chain with Third Party Reverse Logistics
Venue: Asia Pac. J. Oper. Res.
Year: 2012

Closed loop supply chain (CLSC) especially the reverse logistics system with the third party reverse logistics providers (3PRLP) is very important for materials return, remanufacturing, repair, recovery, recycling, and reusing. In this paper, based on a one leader and multi follower Stackelberg game with the manufacturer being the leader, we model a multi echelon CLSC with 3PRLP under the consideration of impacts of environmental legislation on scrap recycling. Furthermore, in order to encourage the 3PRLP to exert him to return activities we design a target rebate punish contract between the manufacturer and the 3PRLP under both stochastic price dependent demands and stochastic effort dependent returns. We analyze the closed form analytic expressions for both united optimization strategies in centralized closed loop system and the Stackelberg strategies in decentralized system, and conclude that the wholesale price contract may not coordinate the forward supply chain and the target rebate punish may coordinate the reverse chain under certain conditions. Finally, according to the practice of Chinese steel enterprises we carry out some simulation experiments to validate our theoretical analyses and gain some insights into the impacts of reverse logistics activities on the practitioners operations and decisions.
Harmonic Distortion Feature of AC Transformers Caused by DC Bias
Venue: 2012 Asia Pacific Power and Energy Engineering Conference
Year: 2012

With regard to the first 660kV HVDC transmission line from Yinchuan to Qingdao, quantitative harmonic analysis of the main transformer in Yi Ming substation, about 65km away from the Qingdao converter station, is carried out based on an established nonlinear magnetic model by PSCAD/EMTDC. The results indicate that, both the odd and even harmonic components are getting much higher under DC bias than that without DC bias, which thereby makes the power transformers to severe harmonic sources. The relationship between the injected neural DC currents and the even harmonic ratio is established which presents further potential for developing inverse current injection based DC bias suppression scheme.
Walkthrough and History of the Virtual Fields Method
Year: 2020

This paper presents the history of the Virtual Fields Method, an identification method developed 30 years ago in order to identify constitutive parameters from full field measurements. This method was initially proposed in the case of bending plate problems, but it has progressively been adapted to many other testing configurations. In this paper we look back at the first developments of the method and highlight the main problems that were progressively tackled, especially in terms of increasing complexity of the constitutive equations that were considered, and improvement of the identification technique itself to make it more efficient.
College students' use and acceptance of emergency online learning due to COVID 19
Venue: International Journal of Educational Research Open
Year: 2020

Due to COVID 19, higher education institutions transitioned to online learning. This study explored college students' perceptions of their adoption, use, and acceptance of emergency online learning. The factors analyzed were attitude, affect, and motivation; perceived behavioral control (ease of use of technology, self efficacy, and accessibility) and cognitive engagement. Quantitative and qualitative data were collected from 270 students. The findings present how motivation, self efficacy, and use of technology play a significant role in the cognitive engagement and academic performance of students. Also, participants preferred face to face learning. This study presents suggestions on how to improve the acceptance of emergency online learning.
Sliding Mode Temperature Control for Hybrid Solar/Electricity Oven
Year: 2019

his work presents sliding mode temperature control for hybrid solar/electricity oven. The system is primarily power by solar thermal air collector and solar photo voltaic and supplemented by electricity utility on periods of little or no insolation. Solar thermal storage method is also shown. Sliding mode control (SMC) method is compared to PID control method on paint curing oven model using MATLAB/Simulink. The simulation results show that SMC has better performance due to its fast rise time of less than two minutes as against 195 minutes with PID controller. A flat plate collector and paint curing oven has been built. From experimental results, the collector supplied 43.27% of the heat energy required to operate the oven at a temperature of 120degC. The SMC controller implementation is based on micro controller programed in C+ The controller can automatically maintain different temperature levels for specified durations because it accepts multiple reference inputs. Return on investment calculation shows that the system has payback period of sixteen month.
Domestic Sources of Twenty first century Geopolitics: Domestic Politics and Sovereign Wealth Funds in GCC Economies
Year: 2019

The present article brings domestic politics into an analysis on sovereign wealth funds (SWFs) that are relevant for the study of contemporary geopolitics. What are the domestic drivers behind SWF creation, and how does a country's domestic political environment affect the creation of these funds? Using a comparative historical case study on sovereign funds in Gulf Cooperation Countries, this article investigates the effects of domestic state society structures on decisions about SWF creation and their evolving structure. Thereby, this article adds to an emerging stream of literature that looks at the drivers and implications of SWFs. One of the key findings of this analysis is that there are systematic links between the sovereign fund types and domestic structures; these structures include and exclude socio economic actors that influence policy making decisions.
FAKTOR YANG MEMPENGARUHI HARGA SAHAM PERUSAHAAN KELAPA SAWIT YANG TERDAFTAR DI INDEKS SAHAM SYARIAH INDONESIA PERIODE 2013 2017SKRIPSI
Year: 2019

Tinggi rendahnya harga saham suatu perusahaan dapat dipengaruhi oleh berbagai faktor diantaranya faktor Market Value Added dan rasio keuangan. Penelitian ini bertujuan untuk menganalisis pengaruh variabel Market Value Added dan rasio keuangan perusahaan kelapa sawit yang terdaftar di Indeks saham syariah Indonesia terhadap harga saham. Rasio rasio keuangan yang diteliti yaitu Total Asset Turn Over, Debt to Asset Ratio, Return on Asset. Penelitian ini menggunakan metode penelitian kuantitatif. Jumlah sampel yang digunakan dalam penelitian ini adalah 7 perusahaan kelapa sawit yang terdaftar pada Indeks Saham Syariah Indonesia (ISSI) periode 2013 2017. Metode pengambilan sampel yang digunakan adalah purposive sampling dimana pengambilan sampel dilakukan berdasarkan kriteria tertentu. Analisis yang digunakan adalah analisis data panel dan model yang terpilih adalah Random effect model dan uji hipotesis dengan uji t statistik, Koefisien Determinasi dan uji F dengan signifikansi sebesar 0,05 atau 5% Dari hasil analisis yang dilakukan diperoleh hasil secara parsial (uji t Test) variabel Maket Value Added dengan tingkat signifikansi sebesar 0,0036, Total asset Turn Over dengan tingkat signifikansi 0,0026 dan Debt to Asset Ratio dengan tingkat signifikansi sebesar 0,0487 berpengaruh terhadap harga saham, sedangkan variabel Return on Asset secara parsial tidak berpengaruh terhadap harga saham. Hasil uji secara simultan (uji F) menunjukkan bahwa secara simultan semua variabel berpengaruh signfikan terhadap harga saham.  Added, Total asset Turn Over, Debt to Asset Ratio, Return on Asset serta harga Saham
Technological Intercropping with the Cloud, IoT, and Big Data in Indian Organic Agriculture
Year: 2020

The Himalayan challenges encompassing Indian agriculture at present is the deterioration of soi1l quality, the decrease in quantity and quality of farm produce, the indiscriminate use of agrochemicals and synthetic fertilizers, unattractive price remuneration for producers, exiguous water availability for irrigation, poor post harvest practices, and unpredictable weather conditions. Corollaries to these appalling situations include growers who are further prone to distress sales, inaccessibility to formal credit, insufficient market intelligence, detachment from mainstream commercial supply chains, bleak information networks, counterfeit agri inputs, and mediocre crop management practices. When it comes to organic agriculture, there are many hard challenges, as the protocols are much more stringent and unforgiving. Today, organic agriculture should undergo a paradigm shift from being only traditional to being organic smart agriculture (OSA) in which the technological intercropping (TI) is present with various information and communication technologies (ICTs) and digital technologies, like IoT, cloud computing and big data analytics. This would play a key role in maneuvering desirable information and tools, leading to better decision making and risk management. Making the organic agriculture smart would involve using the latest high yielding agricultural technologies coupled up with the value based technological interventions for improving agricultural productivity and sustainability, all the while remaining globally competitive and environment friendly. However, given the technological complexities and asymmetry in information networks, small and marginal farmers may not be able to comprehend or come on this platform single handedly; therefore, the role of farmer based organizations like farmer producer organizations (FPOs) farmer clubs, NGOs operating in rural areas, SHGs, rural formal credit institutions (RFCI) including micro finance institutions (MFIs) crop insurance service providers, panchayat bodies, post offices, certification bodies, etc. will be absolutely critical to strategize and execute the entire game plan. The author envisions a CONSORTIUM DRIVEN MULTIPLE STAKEHOLDER MODEL (CDMSM) for providing these analytics services to the rural diaspora in a customized manner. The idea is to utilize the existing infrastructure available in rural/rural town areas by technologically upgrading them for reaching out to the organic small and marginal farmers. Hence, this would be a cost effective and faster means to educate and coach the organic grower community. Further, the rural unemployed youths can be trained to act as infopreneurs, and they can be employed with the above mentioned stakeholder bodies for installation of sensors and proper dissemination of information. Again, the possibility of carbon credit can be worked out, as well as once the technological intercropping takes a concrete shape as the data and information collected integrated with the upgraded infrastructure can be used to do the carbon audit, credit/debit, and trade.
Effective Approches and Challenges Focused in IRIS Image Recognition A Survey
Year: 2016

One of the most well known biometric identification iris recognition system is viewed as the most accurate and reliable biometric identification system. Over the past few years, although the False Rejection Rate and Equal Error Rate of iris images are increasing and False acceptance Rate of iris images are decreasing, the iris images causes few effects due to feature extraction approach. As a result feature extraction from the actual image has to be made to provide better authentication, which is a difficult task. Various techniques have been present in the literature on iris feature extraction which has its own limitations and advantages. The purpose of this article is to present a survey of the published literature which deals with the iris feature extraction, focusing on the relative merits and demerits of a variety of Iris recognition algorithms.
The Chemical Constituents of Aspidopterys Obcordata Hemsl by Comprehensive Preliminary Test
Year: 2014

To study the chemical constituents of Aspidopterys obcordata Hemsl by comprehensive preliminary test.Components of water extraction,95% EtOH extraction and petroleum extraction from Aspidopterys obcordata Hemsl were studied by using tube reaction,paper reaction and TLC methods.The active components of Aspidopterys obcordata Hemsl were preliminary investigated according to precipitation reaction and chromogenic reaction of several indicator and chro mogenic agent.Terpenoids,polyphenols and tannins may be existed in Aspidopterys obcordata Hemsl.The active components of Aspidopterys obcordata Hemsl were preliminary determined.The results provided experimental data for further study.
Mobile assisted language learning: A Duolingo case study
Venue: ReCALL
Year: 2019

The growing availability of mobile technologies has contributed to an increase in mobile assisted language learning in which learners can autonomously study a second language (L2) anytime or anywhere (e.g. Kukulska Hulme, Lee Norris, 2017; Reinders Benson, 2017) Research investigating the effectiveness of such study for L2 learning, however, has been limited, especially regarding large scale commercial L2 learning apps, such as Duolingo. Although one commissioned research study found favorable language learning outcomes (Vesselinov Grego, 2012) limited independent research has reported issues related to learner persistence, motivation, and program efficacy (Lord, 2015; Nielson, 2011) The current study investigates the semester long learning experiences and results of nine participants learning Turkish on Duolingo. The participants showed improvement on L2 measures at the end of the study, and results indicate a positive, moderate correlation between the amount of time spent on Duolingo and learning gains. In terms of perceptions of their experiences, the participants generally viewed Duolingo's flexibility and gamification aspects positively; however, variability in motivation to study and frustration with instructional materials were also expressed.
Minimum error state discrimination and quantitative wave particle duality
Year: 2020

We establish the link between minimum error discrimination of two pure states and wave particle duality in two path interferometers. In particular, the upper bound of the probability of success discrimination is derived directly from the corresponding duality relation. It is already known that quantum state discrimination can produce wave particle duality relations, here we show the converse is also true: Wave particle duality can be used to obtain information about state discrimination.
High Concentrations of Very Long Chain Leaf Wax Alkanes of Thrips Susceptible Pepper Accessions (Capsicum spp)
Venue: Journal of chemical ecology
Year: 2020

The cuticular wax layer can be important for plant resistance to insects. Thrips (Frankliniella occidentalis) damage was assessed on 11 pepper accessions of Capsicum annuum and C. chinense in leaf disc and whole plant assays. Thrips damage differed among the accessions. We analyzed the composition of leaf cuticular waxes of these accessions by GC MS. The leaf wax composition was different between the two Capsicum species. In C. annuum, 1 octacosanol (C28 alcohol) was the most abundant component, whereas in C. chinense 1 triacotanol (C30 alcohol) was the prominent. Thrips susceptible accessions had significantly higher concentrations of C25 C29 n alkanes and iso alkanes compared to relatively resistant pepper accessions. The triterpenoids a and ss amyrin tended to be more abundant in resistant accessions. Our study suggests a role for very long chain wax alkanes in thrips susceptibility of pepper. Electronic supplementary material The online version of this article (10.1007/s10886 020 01226 x) contains supplementary material, which is available to authorized users.
Hydrodynamic Analysis Based Modeling and Experimental Verification of a New Water Jet Thruster for an Amphibious Spherical Robot
Venue: Sensors
Year: 2019

Thrusters are the bottom actuators of the amphibious spherical robot, and play an important role in the motion control of these robots. To realize accurate motion control, a thrust model for a new water jet thruster based on hydrodynamic analyses is proposed in this paper. First, the hydrodynamic characteristics of the new thruster were numerically analyzed using computational fluid dynamics (CFD) commercial software CFX. The moving reference frame (MRF) technique was utilized to simulate propeller rotation. In particular, the hydrodynamics of the thruster were studied not only in the axial flow but also in oblique flow. Then, the basic framework of the thrust model was built according to hydromechanics theory. Parameters in the basic framework were identified through the results of the hydrodynamic simulation. Finally, a series of relevant experiments were conducted to verify the accuracy of the thrust model. These proved that the thrust model based simulation results agreed well with the experimental results. The maximum error between the experimental results and simulation results was only 7% which indicates that the thrust model is precise enough to be utilized in the motion control of amphibious spherical robots.
"Selfie" harm: Effects on mood and body image in young women.
Venue: Body image
Year: 2018

"Selfies" (self taken photos) are a common self presentation strategy on social media. This study experimentally tested whether taking and posting selfies, with and without photo retouching, elicits changes to mood and body image among young women. Female undergraduate students (N 110) were randomly assigned to one of three experimental conditions: taking and uploading either an untouched selfie, taking and posting a preferred and retouched selfie to social media, or a control group. State mood and body image were measured pre and post manipulation. As predicted, there was a main effect of experimental condition on changes to mood and feelings of physical attractiveness. Women who took and posted selfies to social media reported feeling more anxious, less confident, and less physically attractive afterwards compared to those in the control group. Harmful effects of selfies were found even when participants could retake and retouch their selfies. This is the first experimental study showing that taking and posting selfies on social media causes adverse psychological effects for women.
DQ GAT: Towards Safe and Efficient Autonomous Driving with Deep Q Learning and Graph Attention Networks
Venue: ArXiv
Year: 2021

Autonomous driving in multi agent and dynamic traffic scenarios is challenging, where the behaviors of other road agents are uncertain and hard to model explicitly, and the egovehicle should apply complicated negotiation skills with them to achieve both safe and efficient driving in various settings, such as giving way, merging and taking turns. Traditional planning methods are largely rule based and scale poorly in these complex dynamic scenarios, often leading to reactive or even overly conservative behaviors. Therefore, they require tedious human efforts to maintain workability. Recently, deep learning based methods have shown promising results with better generalization capability but less hand engineering effort. However, they are either implemented with supervised imitation learning (IL) that suffers from the dataset bias and distribution mismatch problems, or trained with deep reinforcement learning (DRL) but focus on one specific traffic scenario. In this work, we propose DQ GAT to achieve scalable and proactive autonomous driving, where graph attention based networks are used to implicitly model interactions, and asynchronous deep Q learning is employed to train the network end to end in an unsupervised manner. Extensive experiments through a high fidelity driving simulation show that our method can better trade off safety and efficiency in both seen and unseen scenarios, achieving higher goal success rates than the baselines (at most 4.7x) with comparable task completion time. Demonstration videos are available at https: /caipeide.github.io/dq gat/