nils-herrmann/clean_scirepeval huggingface dataset:
Recognition of Drivers' Activity Based on 1D Convolutional Neural Network
Year: 2020

Driving a car is a complex activity which involves movements of the whole body. Many studies on drivers' behavior are conducted to improve road traffic safety. Such studies involve the registration and processing of multiple signals, such as electroencephalography (EEG) electrooculography (EOG) and the images of the driver's face. In our research, we attempt to develop a classifier of scenarios related to learning to drive based on the data obtained in real road traffic conditions via smart glasses. In our approach, we try to minimize the number of signals which can be used to recognize the activities performed while driving a car.  We attempt to evaluate the drivers' activities using both electrooculography (EOG) and a deep learning approach. To acquire data we used JINS MEME smart glasses furnished with 3 point EOG electrodes, 3 axial accelerometer and 3 axial gyroscope. Sensor data were acquired on 20 drivers (ten experienced and ten learner drivers) on the same 28.7 km route under real road conditions in southern Poland. The drivers performed several tasks while wearing the smart glasses and the tasks were linked to the signal during the drive. For the recognition of four activities (parking, driving through a roundabout, city traffic and driving through an intersection) we used one dimensional convolutional neural network (1D CNN)  The maximum accuracy was 95.6% on validation set and 99.8% on training set. The results prove that the model based on 1D CNN can classify the actions performed by drivers accurately.  We have proved the feasibility of recognizing drivers' activity based solely on EOG data, regardless of the driving experience and style. Our findings may be useful in the objective assessment of driving skills and thus, improving driving safety.
Overcoming Channel Uncertainties in Molecular Communication Inspired Direct Drug Targeting
Venue: 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Year: 2019

Recent progress in the development of new methods for cancer treatment has shown advantages of multiple therapies over mono therapy. In particular, direct drug targeting (DDT) combined with mixed immunotherapy and chemotherapy has the potential to mitigate the undesired side effects allied with conventional therapies, where nanorobots in DDT carry therapeutic agents through the blood vessel channel in order to localize and target diseased tissue with a safe drug interaction. This process can be modeled by a "touchable" (i.e. externally controllable and trackable) molecular communication (MC) system. However, in such a complex process overcoming unavoidable vascular channel uncertainties remains a great challenge. In this paper a multiple model predictive controller (MMPC) is proposed, which is robust against random channel uncertainties. The efficacy of the proposed method is illustrated through identification of globally optimized drug administration schedules. Furthermore, we introduce upper and lower bounds on the inputs and outputs which lead to clinically realistic constraints on the system. Simulation results demonstrate the promising performance of proposed MMPC to control tumor growth in presence of vascular channel uncertainties in MC inspired DDT for cancer treatment.
Response to Comments on Evaluation of Estrogenic Activities of Aquatic Herbicides and Surfactants Using a
Year: 2008

Comments on 'Evaluation of Estrogenic Activities of Aquatic Herbicides and Surfactants Using a Rainbow Trout Vitellogenin Assay' We have read the comments of Kramer et al. (unpublished data) on our paper, 'Evaluation of estrogenic activities of aquatic herbicides and surfactants using a rainbow trout vitellogenin assay' (Xie et al. 2005a) We appreciate their comments and would like to respond to them.
The Role of Institutional Investors in Seasoned Equity Offerings
Year: 2008

Do institutional investors possess private information about seasoned equity offerings (SEOs) If so, do they use this private information to trade in a direction opposite to this information (a manipulative trading role) or in the same direction (an information production role) We use a large sample of transaction level institutional trading data to distinguish between these two roles of institutional investors. We explicitly identify institutional SEO allocations for the first time in the literature. We analyze the consequences of the private information possessed by institutional investors for SEO share allocation, institutional trading before and after the SEO and realized trading profitability, and the SEO discount. We find that institutions are able to identify and obtain more allocations in SEOs with better long run stock returns, they trade in the same direction as their private information, and their post SEO trading significantly outperforms a naive buy and hold trading strategy. Further, more pre offer institutional net buying and larger institutional SEO allocations are associated with a smaller SEO discount. Overall, our results are consistent with institutions possessing private information about SEOs and with an information production instead of a manipulative trading role for institutional investors in SEOs.
China's Search for Assured Retaliation: The Evolution of Chinese Nuclear Strategy and Force Structure
Venue: International Security
Year: 2010

After exploding its first nuclear device in 1964, China did not develop sufficient forces or doctrine to overcome its vulnerability to a first strike by the United States or the Soviet Union for more than three decades. Two factors explain this puzzling willingness to live with nuclear vulnerability: (1) the views and beliefs of senior leaders about the utility of nuclear weapons and the requirements of deterrence, and (2) internal organizational and political constraints on doctrinal innovation. Even as China's technical expertise grew and financial resources for modernization became available after the early 1980s, leadership beliefs have continued to shape China's approach to nuclear strategy, reflecting the idea of assured retaliation (i.e. using the fewest number of weapons to threaten an opponent with a credible second strike) The enduring effect of these leadership ideas has important implications for the trajectory of China's current efforts to modernize its nuclear force.
A Graph Theory Based Method for Regional Integrated Energy Network Planning: A Case Study of a China U.S. Low Carbon Demonstration City
Year: 2019

With the significant attention on global climate change, regional integrated energy systems (RIES) in low carbon city planning has become one of the most important ways for global cities to achieve the goal of energy conservation and emission reduction. However, the planning strategy used in the primary stage of RIES establishment will greatly affect the system economy and environment. In view of the lack of planning guidance mechanisms for the large scale RIES in China, a method for RIES preliminary overall planning, focused on energy types and use, is proposed in this paper. A graph theory based mathematical optimal model was established with the lifetime costs of the whole system as the economic goal, and an improved Prim algorithm was put forward to solve the costs of the transmission and distribution network with the dynamic weight set of pipeline flow. The model was solved by an algorithm based on the idea of a dynamic minimum spanning tree and optimal path planning. The model and method were applied in a China U.S. low carbon demonstration city to verify feasibility and validity. The results could help us to comprehensively integrate regional energy and accurately plan future cities.
Proteomic analysis of human follicular fluid from fertile women
Venue: Clinical Proteomics
Year: 2015

BackgroundFollicular fluid is a unique biological fluid in which the critical events of oocyte and follicular maturation and somatic cell germ cell communication occur. Because of the intimate proximity of follicular fluid to the maturing oocyte, this fluid provides a unique window into the processes occurring during follicular maturation. A thorough identification of the specific components within follicular fluid may provide a better understanding of intrafollicular signaling, as well as reveal potential biomarkers of oocyte health for women undergoing assisted reproductive treatment. In this study, we used high and low pH HPLC peptide separations followed by mass spectrometry to perform a comprehensive proteomic analysis of human follicular fluid from healthy ovum donors. Next, using samples from a second set of patients, an isobaric mass tagging strategy for quantitative analysis was used to identify proteins with altered abundances after hCG treatment. total of 742 follicular fluid proteins were identified in healthy ovum donors, including 413 that have not been previously reported. The proteins belong to diverse functional groups including insulin growth factor and insulin growth factor binding protein families, growth factor and related proteins, receptor signaling, defense/immunity, anti apoptotic proteins, matrix metalloprotease related proteins, and complement activity. In a quantitative analysis, follicular fluid samples from age matched women undergoing in vitro fertilization oocyte retrieval were compared and 17 follicular fluid proteins were found at significantly altered levels (p 0.05) between pre hCG and post hCG samples. These proteins belong to a variety of functional processes, including protease inhibition, inflammation, and cell adhesion.ConclusionsThis database of FF proteins significantly extends the known protein components present during the peri ovulatory period and provides a useful basis for future studies comparing follicular fluid proteomes in various fertility, disease, and environmental exposure conditions. We identified 17 differentially expressed proteins after hCG treatment and together these data showed the feasibility for defining biomarkers that illuminate how the ovarian follicle microenvironment is altered in various infertility related conditions.
Citation Skew in Plastic Surgery Journals: Does the Journal Impact Factor Predict Individual Article Citation Rate?
Venue: Aesthetic surgery journal
Year: 2019

Citation skew refers to the unequal distribution of citations to articles published in a particular journal.  We aimed to assess for the existence of citation skew within plastic surgery journals and to determine whether the journal impact factor (JIF) is an accurate indicator of the citation rates of individual articles.  We identified all journals within the field of plastic and reconstructive surgery using the Journal Citation Report (JCR) The number of citations in 2018 for all individual articles published in 2016 and 2017 was abstracted.  A total of 33 plastic surgery journals were identified comprising 9,823 articles. The citation distribution showed right skew with the majority of articles having either 0 or 1 citation (40% and 25% respectively) A total of 3,374 (34% articles achieved citation rates similar to or higher than their journal's IF while 66% of articles failed to achieve a citation rate equal to the JIF. Review articles achieved higher citation rates (median, 2) when compared to original articles (median,1) p<0.0001. Overall, 50% of articles contributed to 93.7% of citations and 12.6% of articles contributed to 50% of citations. A weak positive correlation was found between the number of citations and the JIF (r=0.327, p<0.0001) CONCLUSIONS Citation skew exists within plastic surgery journals similar to other fields of biomedical science. Most articles did not achieve citation rates equal the JIF with a small percentage of articles having a disproportionate influence on citations and the JIF. Therefore, the JIF should not be used to assess the quality and impact of individual scientific work.
Desires and Intentions for Fatherhood: A Comparison of Childless Gay and Heterosexual Men in Germany
Venue: Journal of family psychology JFP journal of the Division of Family Psychology of the American Psychological Association
Year: 2018

The present study explores the motivation for fatherhood in a sample of childless German gay and heterosexual men aged 18 to 40 years (N 628 638) Referring to the theory of planned behavior (TPB) three potential predictors were considered: the individual's attitude toward having children, perceived attitudes of significant others toward fatherhood, and anticipated parental self efficacy. Regarding fathering motivation, the general desire to become a father was differentiated from the more concrete fathering intention. Level and structure oriented analyses were combined in an innovative way. Consistent with previous research, gay participants reported weaker fathering desires and intentions than their heterosexual counterparts; however, there was no wider desire intention gap among gay than among heterosexual participants (level oriented analysis) As expected, associations between TPB predictors and fathering motivation were independent of sexual orientation (structure oriented analysis) Participants' appreciation of children and their self attribution of parental self efficacy were strongly associated with fathering intentions; these associations were substantially mediated by fathering desires. However, the association between significant others' attitudes toward fatherhood and participants' fathering motivation was comparably weak. Demographics were controlled for in each analysis. Results are discussed from both an individual and a societal perspective.
Obstacle and Dirichlet problems on arbitrary nonopen sets in metric spaces, and fine topology
Year: 2015

We study the double obstacle problem for p harmonic functions on arbitrary bounded nonopen sets E in quite general metric spaces. The Dirichlet and single obstacle problems are included as special cases. We obtain the Adams criterion for the solubility of the single obstacle problem and establish connections with fine potential theory. We also study when the minimal p weak upper gradient of a function remains minimal when restricted to a nonopen subset. Many of the results are new even for open E (apart from those which are trivial in this case) and also on Rn.
Spatially incoherent Fourier digital holography
Venue: Commercial Scientific Sensing and Imaging
Year: 2017

The possibility of incoherent digital holography has been widely studied because it is free from coherent light sources. Here spatially incoherent Fourier digital holography is described. The incoherent hologram is obtained by a rotational shearing interferometer. The hologram obtained by the interferometer is a cosine transform of a spatially incoherent object. After describing the principle of a rotational shearing interferometer, methods to obtain Fourier transform of an object presented.
Hybrid Flow Shop Multi Objective Scheduling with Sequence Dependent Setup Times and Machine Availability Constraints
Year: 2019

The hybrid flow shop environment is one of the most common species of flow shop used in many industries including automotive, chemical industries, textile, etc. In this research we contemporaneously investigate scheduling of this environment and the Preventive Maintenance together. As in the real world the utilities and interests of customer and producers are different and even opposite in many cases, the necessity of production scheduling with multi objectives will become more obvious. In this paper we try to investigate the Hybrid flow shop scheduling with the assumption of setup times related to sequence and limited availability of machines, in order to minimize the completion time and total tardiness times of jobs. The studied problem is a combinatorial optimization problem which its complicated nature makes it impossible to be solved in the natural time. Therefore, we try to find a suitable meta heuristic algorithm, for solving the problem. In this research we suggest two algorithms named MO VNS and MO GA VNS that both of them are multi objective methods based on Pareto Archive. Numerical examples are used to evaluate presented algorithms. We perform some experiments for evaluating the suggested methods. Due to these experiments some sample problems are designed and generated. The results show that MO GAVNS algorithm is much better comparing the other algorithms.
The Curse of Class Imbalance and Conflicting Metrics with Machine Learning for Side channel Evaluations
Venue: IACR Cryptol. ePrint Arch.
Year: 2018

We concentrate on machine learning techniques used for profiled side channel analysis in the presence of imbalanced data. Such scenarios are realistic and often occurring, for instance in the Hamming weight or Hamming distance leakage models. In order to deal with the imbalanced data, we use various balancing techniques and we show that most of them help in mounting successful attacks when the data is highly imbalanced. Especially, the results with the SMOTE technique are encouraging, since we observe some scenarios where it reduces the number of necessary measurements more than 8 times. Next, we provide extensive results on comparison of machine learning and side channel metrics, where we show that machine learning metrics (and especially accuracy as the most often used one) can be extremely deceptive. This finding opens a need to revisit the previous works and their results in order to properly assess the performance of machine learning in side channel analysis.
SysML model driven approach to verify blocks compatibility
Year: 2019

In the component paradigm, the system is seen as an assembly of heterogeneous components, where the system reliability depends on these components compatibility. In our approach, we focus on verifying compatibility of components modelled with SysML diagrams. Thus, we model component interactions with sequence diagrams (SDs) and components with SysML blocks. The SDs constitutes a good start point for compatibility verification. However, this verification is still inapplicable directly on SDs, because they are expressed in informal language. Thus, to apply a verification method, it is necessary to translate the SDs into formal models, and then verify the wanted properties. In this paper, we propose a high level model driven approach which consists of an ATL grammar that automates the transformation of SDs into interface automata. Also, to allow an easy use of Ptolemy tool to verify properties on automata, we have proposed some Acceleo templates, which generate the Ptolemy entry specification.
NWPU Crowd: A Large Scale Benchmark for Crowd Counting and Localization
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence
Year: 2021

In the last decade, crowd counting and localization attract much attention of researchers due to its wide spread applications, including crowd monitoring, public safety, space design, etc. Many convolutional neural networks (CNN) are designed for tackling this task. However, currently released datasets are so small scale that they can not meet the needs of the supervised CNN based algorithms. To remedy this problem, we construct a large scale congested crowd counting and localization dataset, NWPU Crowd, consisting of 5,109 images, in a total of 2,133,375 annotated heads with points and boxes. Compared with other real world datasets, it contains various illumination scenes and has the largest density range <inline formula><tex math notation="LaTeX"$0\\sim !20,033$/tex math><alternatives><mml:math><mml:mrow><mml:mn>0</mml:mn><mml:mspace width=" mspace width=" math><inline graphic xlink:href="wang ieq1 3013269.gif"/alternatives>/inline formula> Besides, a benchmark website is developed for impartially evaluating the different methods, which allows researchers to submit the results of the test set. Based on the proposed dataset, we further describe the data characteristics, evaluate the performance of some mainstream state of the art (SOTA) methods, and analyze the new problems that arise on the new data. What's more, the benchmark is deployed at <uri>https:/www.crowdbenchmark.com//uri> and the dataset/code/models/results are available at <uri>https:/gjy3035.github.io/NWPU Crowd Sample Code//uri>
Supporting mental model accuracy in trigger action programming
Venue: UbiComp
Year: 2015

Trigger action programming is a simple programming model that enables users to create rules that automate behavior of smart homes, devices, and online services. Existing trigger action programming systems, such as if this then that (IFTTT) already have millions of users worldwide; however, their oversimplification limits the expressivity of the programs that can be created. While extensions of IFTTT to allow more complex programs have been proposed, previous work neglects a key distinction between different trigger types (states and events) and action types (instantaneous, extended, and sustained actions) In this paper, we systematically study the impact of these differences through two user studies that reveal: (i) inconsistencies in interpreting the behavior of trigger action programs and (ii) errors made in creating programs with a desired behavior. Based on a characterization of these issues, we offer recommendations for improving the IFTTT interface so as to mitigate issues that arise from mental model inaccuracies.
Aging causes decreased resistance to multiple stresses and a failure to activate specific stress response pathways
Venue: Aging
Year: 2016

In this work, we examine the relationship between stress resistance and aging. We find that resistance to multiple types of stress peaks during early adulthood and then declines with age. To dissect the underlying mechanisms, we use C. elegans transcriptional reporter strains that measure the activation of different stress responses including: the heat shock response, mitochondrial unfolded protein response, endoplasmic reticulum unfolded protein response, hypoxia response, SKN 1 mediated oxidative stress response, and the DAF 16 mediated stress response. We find that the decline in stress resistance with age is at least partially due to a decreased ability to activate protective mechanisms in response to stress. In contrast, we find that any baseline increase in stress caused by the advancing age is too mild to detectably upregulate any of the stress response pathways. Further exploration of how worms respond to stress with increasing age revealed that the ability to mount a hormetic response to heat stress is also lost with increasing age. Overall, this work demonstrates that resistance to all types of stress declines with age. Based on our data, we speculate that the decrease in stress resistance with advancing age results from a genetically programmed inactivation of stress response pathways, not accumulation of damage.