nils-herrmann/clean_scirepeval huggingface dataset:
DESIGN AND FABRICATION OF ELECTRIC CYCLE
Year: 2019

As the worldwide population is growing day by day and there is an increasing demand for the product from the manufacturing industry a simple, reliable, eco friendly, safety, and less costly product. One of them is electric vehicles. One type of such an electric vehicle is the electric cycle (e cycle) E cycle typically incorporates a battery, which can be charged at an ordinary domestic power socket, linked to an electric motor in the bicycle transmission system. Increase in fuel price of Petrol bike along with the consideration of the environmental factors uses a bicycle over a motor vehicle for short distance traveling. The rider has the power to controls the output power from motor i.e. speed using a handlebar mounted throttle and controller. The term 'e bike' is generic and includes a combination of different electrically powered two wheelers some of which function by simply turning a throttle. In this paper, a comparative and in depth study of supporting component of the electric cycle is carried out. This project is based on a combination of the standard geared bicycle with an electric power motor The system is modified in such a way that the rider can make choice of which mode he prefers i.e. he can either choose the bicycle to be driven completely with the electric motor or he can choose it to be driven manually by himself.
The effect of encapsulated traditional Chinese medicine external application combined with hyperbaric oxygen therapy on nerve conduction velocity and the quality of life of patients with nerve root cervical spondylosis
Year: 2017

Mu De Tan Jiu Zhong Yao Feng Bao Wai Fu Lian He Gao Ya Yang Liao Fa Dui Shen Jing Gen Xing Jing Zhui Bing (NRCS)Huan Zhe Shen Jing Chuan Dao Su Du Ji Sheng Huo Zhi Liang De Ying Xiang Fang Fa Xuan Ze Ben Yuan 84Li NRCSHuan Zhe ,Sui Ji Shu Zi Biao Fa Fen Wei Dui Zhao Zu Ji Guan Cha Zu ,Ge 42Li Dui Zhao Zu Cai Qu Gao Ya Yang Liao Fa Zhi Liao ,Guan Cha Zu Yu Yi Gao Ya Yang Liao Fa +Zhong Yao Feng Bao Wai Fu Zhi Liao ,Liang Zu Jun Zhi Liao 3Zhou Jian Ce Liang Zu Zhi Liao Qian Hou Nao Shen Jing Chi Shen Jing Zheng Zhong Shen Jing FBo Chuan Dao Su Du Teng Tong Ping Fen (VAS) Sheng Huo Zhi Liang Ping Fen (SF 36)Bi Jiao ,Bing Tong Ji Liang Zu Lin Chuang Liao Xiao Jie Guo Guan Cha Zu Zhi Liao Hou Nao Shen Jing Chi Shen Jing Zheng Zhong Shen Jing FBo Chuan Dao Su Du Fen Bie Wei (57.63+ 7.41)m/s, (59.28+ 9.47)m/s, (55.28+ 7.48)m/s,Gao Yu Dui Zhao Zu De (49.83+ 6.25)m/s, (50.13+ 8.25)m/s, (48.56+ 6.42)m/s,Chai Yi You Tong Ji Xue Yi Yi (t1=5.216, t2=4.721, t3=4.418,P<0.05);Guan Cha Zu Zhi Liao Hou Zong You Xiao Lu 90.48%Gao Yu Dui Zhao Zu 71.43%,Chai Yi You Tong Ji Xue Yi Yi (kh2=4.941,P<0.05);Jing Zhi Liao ,Guan Cha Zu VASPing Fen Wei (1.52+ 0.61)Fen ,Di Yu Dui Zhao Zu (3.45+ 1.02)Fen ,SF 36Ping Fen Wei (77.54+ 8.43)Fen ,Gao Yu Dui Zhao Zu (65.08+ 8.39)Fen ,Chai Yi You Tong Ji Xue Yi Yi (t1=10.524, t2=6.789,P<0.05) Jie Lun Lian He Cai Yong Zhong Yao Feng Bao Wai Fu Yu Gao Ya Yang Liao Fa Zhi Liao Shen Jing Gen Xing Jing Zhui Bing Huan Zhe Liao Xiao Xian Zhu ,Ke Ti Gao Qi Shen Jing Chuan Dao Su Du ,Jian Qing Qi Teng Tong Gan ,Ti Gao Qi Sheng Huo Zhi Liang
A patient specific lumped parameter model of coronary circulation
Venue: Scientific Reports
Year: 2018

A new lumped parameter model for coronary hemodynamics is developed. This model is developed for the whole coronary network based on CT scans of a patient specific geometry including the right coronary tree, which is absent in many previous mathematical models. The model adopts the structured tree model boundary conditions similar to the work of Olufsen et al. thus avoiding the necessity of invasive perfusion measurements. In addition, we also incorporated the effects of the head loss at the two inlets of the large coronary arteries for the first time. The head loss could explain the phenomenon of a sudden increase of the resistance at the inlet of coronary vessel. The estimated blood pressure and flow rate results from the model agree well with the clinical measurements. The computed impedances also match the experimental perfusion measurement. The effects of coronary arterial stenosis are considered and the fractional flow reserve and relative flow in the coronary vessels for a stenotic vessel computed in this model show good agreement with published experimental data. It is believed that the approach could be readily translated to clinical practice to facilitate real time clinical diagnosis.
Relationship with peers of young school aged children with type 1 diabetes
Year: 2018

Functioning in a peer group plays an important role in child development. Building self esteem of children depends on many factors such as physical health, self evaluation of their physical performance, academic achievement, social support, family relationships, as well as relationships with peers and teachers. Importance of contacts with peers increases during school age. At this time children are not able to reject the opinion of other people and subject their behaviour completely to the expectations of their peers. When the need for emotional contact is not satisfied, the complex of being different appears. Isolation within group causes a sense of inferiority, the child becomes passive and resigned. Children, who are chronically ill, rejected or isolated often follow negative emotions in their actions, they become aggressive towards other children or do not want to continue learning. Often the decision about an individual teaching plan results in further isolation of the child. The child's position in the peer group affects the developing personality, self confidence and self esteem. aim of the study: The aim of the study was to determine the interpersonal relationships of young school aged children with type 1 diabetes in their peer groups.  The study was conducted on children with type 1 diabetes and their parents, who are supervised by Clinic of Diabetes, Regional Medical Center in Opole. The research tool used in both groups was a questionnaire consisting of open and closed questions elaborated by the authors of this study.  73% (41) of evaluated children declared that diabetes does not hinder their performance at school. 93% (55) children claimed that they do not hide their condition from their peers. In addition, 61% (34) talk about their illness with their peers and 69% (38) of them can count on their peers' help in self control of diabetes. 71.9% (46) of parents of children with type 1 diabetes allow their children to participate in school trips and 68.8% (44) to participate in school competitions.  In most children, diabetes does not affect children's performance at school. They participate in classes, are accepted and liked in their peer group. Chronically ill children should be able to participate in all types of activities as much as their healthy peers. It seems necessary to continue studies on performance of young school aged children with type 1 diabetes in their peer group.
Anomaly Detection Techniques using Deep Learning in IoT: A Survey
Venue: 2019 International Conference on Computational Intelligence and Knowledge Economy (ICCIKE)
Year: 2019

IoT technologies is improving life quality by enhancing several real life smart applications. IoT includes large number of devices generating huge amount of data which needs large computation. Anomaly detection and security is the major concern in the IoT domain. This survey paper provides an overview of anomaly detection using machine learning and deep learning methods in IoT applications. Machine learning and deep learning are powerful tools for analyzing normal and abnormal behavior of IoT components and devices. In this paper we outline key issues in research and challenges using deep anomaly detection techniques for resource constrained devices in real world problems of IoT. Fog computing move the computation at the device or the edge to solve some of the issues of network security and delay in computation.
Constitutive but no Triops induced differences in bet hedging strategies for hatching in Daphnia
Venue: Hydrobiologia
Year: 2012

Since cladocerans from the genus Daphnia are known to have evolved several inducible defenses (morphological and life history shifts) against the notostracan predator Triops, we investigated whether hatching was also altered in response to Triops. We tested whether dormant eggs of Daphnia magna are able to detect Triops cancriformis kairomones in the water as a signal of predation pressure and alter their hatching response accordingly to avoid predation. We predicted that, in the presence of Triops kairomones, hatching fractions might be reduced (postponing hatching to a next growing season) and/or that hatching might peak earlier (increasing chances to reproduce before Triops becomes predatory) We also tested whether this response depended on the origin of the population. Ephippia from three D. magna populations, originating from one permanent lake and two temporary pond systems, were exposed to Triops kairomone and control treatments. We observed significant population differences in hatching patterns, both in terms of the fraction of eggs that hatch as well as the timing of hatching, with evidence for within season bet hedging through delayed hatching in the populations inhabiting temporary habitats. However, no indication was found that the populations also adjust their hatching pattern to the presence of Triops kairomones.
Understanding Factors influencing Consumers Online Purchase intention Via Mobile App: Perceived Ease of use, Perceived Usefulness, System Quality, information Quality, and Service Quality
Venue: Marketing of Scientific and Research Organizations
Year: 2019

The development of technology has been significantly given the implication towards consumer's behaviour in having the online purchase intention via mobile app that has been developed by the e commerce company to serve better and deliver a better service to the consumers; especially when internet has connected people through their smartphones. The insignificant growth in doing the online purchase via mobile app which does not go along with the growth of internet mobile users in Indonesia and Singapore will deliver this study in order to evaluate and validate the implication of ease of use, usefulness, system quality, information quality, and service quality towards consumer's behaviour in having the online purchase intention via mobile app. Data was gathered with survey by spreading 100 questionnaires randomly to the respondents who had the experience in doing the online purchase via mobile app in the last 6 months in Indonesia and Singapore. The methodology in doing this study is the quantitative approach by considering the connection amongst the independent variables and the dependent variables. This research found that usefulness and information quality significantly affect the online purchase intention through mobile app in Indonesia while in Singapore ease of use, usefulness, and service quality significantly affect the online purchase intention through mobile app.
Modulation of Coordinated Activity across Cortical Layers by Plasticity of Inhibitory Synapses
Venue: Cell reports
Year: 2020

In the neocortex, synaptic inhibition shapes all forms of spontaneous and sensory evoked activity. Importantly, inhibitory transmission is highly plastic, but the functional role of inhibitory synaptic plasticity is unknown. In the mouse barrel cortex, activation of layer (L) 2/3 pyramidal neurons (PNs) elicits strong feedforward inhibition (FFI) onto L5 PNs. We find that FFI involving parvalbumin (PV) expressing cells is strongly potentiated by postsynaptic PN burst firing. FFI plasticity modifies the PN excitation to inhibition (E/I) ratio, strongly modulates PN gain, and alters information transfer across cortical layers. Moreover, our LTPi inducing protocol modifies firing of L5 PNs and alters the temporal association of PN spikes to g oscillations both in vitro and in vivo. All of these effects are captured by unbalancing the E/I ratio in a feedforward inhibition circuit model. Altogether, our results indicate that activity dependent modulation of perisomatic inhibitory strength effectively influences the participation of single principal cortical neurons to cognition relevant network activity.
Paulo Freire's Critical Pedagogy in the Classroom: Promotion of Critica Thinking in South African English First Additional Language (FAL) Students
Year: 2016

This study investigated the use of Paulo Freire's critical pedagogy in an English (FAL)classroom andits implications in order to promote students' critical thinking skills and to improve English (FAL) lecturers'teaching practice. A qualitative approach with open ended questionnaires and unstructured interviews were used tocollect data. The research population of this study included eight first year English (FAL) students and eight finalyearstudent teachers whose home language is Xhosa, Zulu or Sesotho, with English as their medium of instruction, as well as four lecturers with the home languages of Xhosa, Zulu or Sesotho, majored in English at teacher training.Results indicate that cooperative learning, students' questions, and problem posing methods as instructional cuesplay a significant role in stimulating students' participation in the discussion of the topic and problems related tothe content. This study recommends that lecturers should ensure that teaching and learning objectives manifestcollaborative activities inclined to a social constructivist approach.
Self adversarial Variational Autoencoder with Gaussian Anomaly Prior Distribution for Anomaly Detection
Venue: Knowl. Based Syst.
Year: 2020

Recently, deep generative models have become increasingly popular in unsupervised anomaly detection. However, deep generative models aim at recovering the data distribution rather than detecting anomalies. Besides, deep generative models have the risk of overfitting training samples, which has disastrous effects on anomaly detection performance. To solve the above two problems, we propose a Self adversarial Variational Autoencoder with a Gaussian anomaly prior assumption. We assume that both the anomalous and the normal prior distribution are Gaussian and have overlaps in the latent space. Therefore, a Gaussian transformer net T is trained to synthesize anomalous but near normal latent variables. Keeping the original training objective of Variational Autoencoder, besides, the generator G tries to distinguish between the normal latent variables and the anomalous ones synthesized by T, and the encoder E is trained to discriminate whether the output of G is real. These new objectives we added not only give both G and E the ability to discriminate but also introduce additional regularization to prevent overfitting. Compared with the SOTA baselines, the proposed model achieves significant improvements in extensive experiments. Datasets and our model are available at a Github repository.
A novel recurrent neural network and its finite time solution to time varying complex matrix inversion
Venue: Neurocomputing
Year: 2019

A complex valued nonlinear recurrent neural network is designed and researched for time varying matrix inversion solving in complex field. Unlike the design methods of the conventional gradient neural network (CGNN) and the previous Zhang neural network (ZNN) the proposed complex valued nonlinear recurrent neural network (CVNRNN) model is established on basis of a nonlinear evolution formula and possesses a better finite time convergence Besides, the detailed theoretical analysis provides a guarantee for the finite time convergence achievement of the CVNRNN model. In addition, the theoretical analysis is also verified by numerical simulations, which comparatively show that the proposed CVNRNN model is faster and more accurate than the ZNN model and the CGNN model in solving time varying complex matrix inversion.
Carbohydrate Conjugates in Vaccine Developments
Venue: Frontiers in Chemistry
Year: 2020

Vaccines are powerful tools that can activate the immune system for protection against various diseases. As carbohydrates can play important roles in immune recognition, they have been widely applied in vaccine development. Carbohydrate antigens have been investigated in vaccines against various pathogenic microbes and cancer. Polysaccharides such as dextran and b glucan can serve as smart vaccine carriers for efficient antigen delivery to immune cells. Some glycolipids, such as galactosylceramide and monophosphoryl lipid A, are strong immune stimulators, which have been studied as vaccine adjuvants. In this review, we focus on the current advances in applying carbohydrates as vaccine delivery carriers and adjuvants. We will discuss the examples that involve chemical modifications of the carbohydrates for effective antigen delivery, as well as covalent antigen carbohydrate conjugates for enhanced immune responses.
Superconductivity in the vicinity of antiferromagnetic order in CrAs.
Venue: Nature communications
Year: 2014

One of the common features of unconventional superconducting systems such as the heavy fermion, high transition temperature cuprate and iron pnictide superconductors is that the superconductivity emerges in the vicinity of long range antiferromagnetically ordered state. In addition to doping charge carriers, the application of external pressure is an effective and clean approach to induce unconventional superconductivity near a magnetic quantum critical point. Here we report on the discovery of superconductivity on the verge of antiferromagnetic order in CrAs via the application of external pressure. Bulk superconductivity with Tc2 K emerges at the critical pressure Pc8 kbar, where the first order antiferromagnetic transition at T(N)265 K under ambient pressure is completely suppressed. The close proximity of superconductivity to an antiferromagnetic order suggests an unconventional pairing mechanism for CrAs. The present finding opens a new avenue for searching novel superconductors in the Cr and other transition metal based systems.
Experimental statistical signature of many body quantum interference
Year: 2018

Multi particle interference is an essential ingredient for fundamental quantum mechanics phenomena and for quantum information processing to provide a computational advantage, as recently emphasized by boson sampling experiments. Hence, developing a reliable and efficient technique to witness its presence is pivotal in achieving the practical implementation of quantum technologies. Here, we experimentally identify genuine many body quantum interference via a recent efficient protocol, which exploits statistical signatures at the output of a multimode quantum device. We successfully apply the test to validate three photon experiments in an integrated photonic circuit, providing an extensive analysis on the resources required to perform it. Moreover, drawing upon established techniques of machine learning, we show how such tools help to identify the a priori unknown optimal features to witness these signatures. Our results provide evidence on the efficacy and feasibility of the method, paving the way for its adoption in large scale implementations.An experimental protocol to discern true multi particle interference is demonstrated in a boson sampling device without dynamic reconfiguration. Statistical features of three photon interference were evaluated in a seven mode integrated interferometer.
Modulation of tonotopic ventral medial geniculate body is behaviorally relevant for speech recognition
Venue: eLife
Year: 2019

Sensory thalami are central sensory pathway stations for information processing. Their role for human cognition and perception, however, remains unclear. Recent evidence suggests an involvement of the sensory thalami in speech recognition. In particular, the auditory thalamus (medial geniculate body, MGB) response is modulated by speech recognition tasks and the amount of this task dependent modulation is associated with speech recognition abilities. Here, we tested the specific hypothesis that this behaviorally relevant modulation is present in the MGB subsection that corresponds to the primary auditory pathway (i.e. the ventral MGB [vMGB] We used ultra high field 7T fMRI to identify the vMGB, and found a significant positive correlation between the amount of task dependent modulation and the speech recognition performance across participants within left vMGB, but not within the other MGB subsections. These results imply that modulation of thalamic driving input to the auditory cortex facilitates speech recognition.
Relativistic AGN jets III. Synthesis of synchrotron emission from double double radio galaxies
Year: 2020

The class of Double Double Radio Galaxies (DDRGs) relates to episodic jet outbursts. How various regions and components add to the total intensity in radio images is less well known. In this paper we synthesize synchrotron images for DDRGs based on special relativistic hydrodynamic simulations, making advanced approximations for the magnetic fields. We study the synchrotron images for: Three different radial jet profiles; Ordered, entangled or mixed magnetic fields; Spectral ageing from synchrotron cooling; The contribution from different jet components; The viewing angle and Doppler (de )boosting; The various epochs of the evolution of the DDRG. To link our results to observational data, we adopt to J1835+6204 as a reference source. In all cases the synthesized synchrotron images show two clear pairs of hotspots, in the inner and outer lobes. The best resemblance is obtained for the piecewise isochoric jet model, for a viewing angle of approximately \vartheta \sim 71^\circ} i.e. inclined with the lower jet towards the observer, with predominantly entangled \gtrsim 70$ per cent of the magnetic pressure) in turbulent, rather than ordered fields. The effects of spectral ageing become significant when the ratio of observation frequencies and cut off frequency \nu_{\rm obs}\nu_{\infty,0} \gtrsim 10^ 3} corresponding to \sim 3 \cdot 10^2$ MHz. For viewing angles \vartheta \lesssim 30^\circ} a DDRG morphology can no longer be recognized. The second jets must be injected within \lesssim$ 4 per cent of the lifetime of the first jets for a DDRG structure to emerge, which is relevant for Active Galactic Nuclei feedback constraints.
Predicting Project Performance by Analyzing Key Success Factors on Project Fiancing(PF) Development
Year: 2014

Financing (PF) development project is the type which influences national economy and building industry largely because it is exerted by using borrowed money from many kinds of investors and huge amount of financial raising. Many domestic PF projects are focused mainly on the profit maximization lacking in a sufficient feasibility study. Nowadays many projects are suspending due to the global finance debacle and stagnation of real estate industry. Therefore, in this paper, risk factors of PF project are deducted and Key Success Factors (KSFs) are derived through Factor Analysis and qualified using Fuzzy AHP method. And through the evaluation of the derived success factors in real projects, a strong correlationship has been identified between the score of each PF success factor and the level of success and/or expected rate of return (ROR) So, the result of this paper can help decision makers of the PF projects make a better decision and give a meaningful guidance in achieving successful PF projects.