nils-herrmann/clean_scirepeval huggingface dataset:
Measuring the Effects of Gender on Online Social Conformity
Venue: Proc. ACM Hum. Comput. Interact.
Year: 2019

Social conformity occurs when an individual changes their behaviour in line with the majority's expectations. Although social conformity has been investigated in small group settings, the effect of gender of both the individual and the majority/minority is not well understood in online settings. Here we systematically investigate the impact of groups' gender composition on social conformity in online settings. We use an online quiz in which participants submit their answers and confidence scores, both prior to and following the presentation of peer answers that are dynamically fabricated. Our results show an overall conformity rate of 39% and a significant effect of gender that manifests in a number of ways: gender composition of the majority, the perceived nature of the question, participant gender, visual cues of the system, and final answer correctness. We conclude with a discussion on the implications of our findings in designing online group settings, accounting for the effects of gender on conformity.
ALDH2 contributes to melatonin induced protection against APP/PS1 mutation prompted cardiac anomalies through cGAS STING TBK1 mediated regulation of mitophagy
Venue: Signal Transduction and Targeted Therapy
Year: 2020

Ample clinical evidence suggests a high incidence of cardiovascular events in Alzheimer's disease (AD) although neither precise etiology nor effective treatment is available. This study was designed to evaluate cardiac function in AD patients and APP/PS1 mutant mice, along with circulating levels of melatonin, mitochondrial aldehyde dehydrogenase (ALDH2) and autophagy. AD patients and APP/PS1 mice displayed cognitive and myocardial deficits, low levels of circulating melatonin, ALDH2 activity, and autophagy, ultrastructural, geometric (cardiac atrophy and interstitial fibrosis) and functional (reduced fractional shortening and cardiomyocyte contraction) anomalies, mitochondrial injury, cytosolic mtDNA buildup, apoptosis, and suppressed autophagy and mitophagy. APP/PS1 mutation downregulated cyclic GMP AMP synthase (cGAS) and stimulator of interferon genes (STING) levels and TBK1 phosphorylation, while promoting Ab accumulation. Treatment with melatonin overtly ameliorated unfavorable APP/PS1 induced changes in cardiac geometry and function, apoptosis, mitochondrial integrity, cytosolic mtDNA accumulation (using both immunocytochemistry and qPCR) mitophagy, and cGAS STING TBK1 signaling, although these benefits were absent in APP/PS1/ALDH2 mice. In vitro evidence indicated that melatonin attenuated APP/PS1 induced suppression of mitophagy and cardiomyocyte function, and the effect was negated by the nonselective melatonin receptor blocker luzindole, inhibitors or RNA interference of cGAS, STING, TBK1, and autophagy. Our data collectively established a correlation among cardiac dysfunction, low levels of melatonin, ALDH2 activity, and autophagy in AD patients, with compelling support in APP/PS1 mice, in which melatonin rescued myopathic changes by promoting cGAS STING TBK1 signaling and mitophagy via an ALDH2 dependent mechanism.
Neurointervention for emergent large vessel occlusion during the COVID 19 pandemic
Venue: Journal of NeuroInterventional Surgery
Year: 2020

Introduced into the human population in December 2019, the zoonotic novel b coronavirus spread rapidly. Labeled Coronavirus Disease 2019 (COVID 19) by the World Health Organization (WHO) the infection reached pandemic proportions by March 11, 2020. At the time of writing this commentary, globally our way of life is transforming. Hospitals are no exception, with mobilization into an emergency mode including halting all non urgent elective procedures and clinic visits. The Centers for Disease Control and Prevention (CDC) and the WHO are currently recommending aggressive measures to prevent viral transmission. For healthcare workers, aside from standard precautions like using personal protective equipment (PPE) and handwashing, these bodies are strongly encouraging the practice of 'social distancing' (SD) and 'self quarantine' (SQ) for those with suspected or proven infections. In essence, SD means avoiding crowds, closing schools, canceling all social events and meetings, and maintaining a 6 foot distance between individuals. SQ refers to isolating oneself for 2 weeks without any social contact to avoid transmission. These efforts will be critical to mitigating covid 19 spread, as they may 'flatten the curve' of new and serious cases and prevent the healthcare system from being overwhelmed. Healthcare workers are on the front line, and doctors, nurses, and hospital staff are at highest risk of contracting the virus. As cases become ubiquitous throughout the healthcare system, many staff will become secondarily infected and will require medical treatment and SQ. As the volume of infected personnel increases, many services will need to operate on a skeleton crew. If infection breaches a critical threshold, some emergency services may cease to be possible. The greatest potential impact will be on mechanical thrombectomy (MT) in acute ischemic stroke. MT for emergent large vessel occlusion (ELVO) represents one of the most impactful and effective emergent interventions in medicine,1 markedly reducing morbidity and mortality. MT is
The effect of a fibre supplement compared to a healthy diet on body composition, lipids, glucose, insulin and other metabolic syndrome risk factors in overweight and obese individuals
Venue: British Journal of Nutrition
Year: 2010

Optimum levels and types of dietary fibre that provide the greatest beneficial effects on metabolic syndrome risk factors in overweight and obese individuals have yet to be determined in clinical trials. The present parallel design study compared the effects of fibre intake from a healthy diet v. a fibre supplement (psyllium) or a healthy diet plus fibre supplement on fasting lipids, glucose, insulin and body composition. Overweight/obese adults were randomised to either control (with placebo) fibre supplement (FIB) healthy eating plus placebo (HLT) or healthy eating plus fibre supplement (HLT FIB) There was a significant increase in fibre intake in HLT FIB, HLT and FIB groups up to 59, 31 and 55 g, respectively, at 12 weeks when compared to control (20 g) Weight, BMI and total body fat were significantly reduced in FIB and HLT FIB groups, with weight and BMI significantly reduced in the HLT group compared with control at 12 weeks. HLT FIB and HLT groups had significant reductions in TAG and insulin compared with control at 6 and 12 weeks, and in insulin compared with the FIB group at 12 weeks. The HLT FIB, HLT and FIB groups all had significant reductions in total cholesterol and LDL cholesterol compared with control after 6 and 12 weeks. The present study demonstrated that simply adding psyllium fibre supplementation to a normal diet was sufficient to obtain beneficial effects in risk factors. However, a high fibre diet consisting of a psyllium supplement plus fibre from a healthy diet provided the greatest improvements in metabolic syndrome risk factors.
The prioritization and categorization method (PCM) process evaluation at Ericsson: a case study
Venue: Bus. Process. Manag. J.
Year: 2017

The purpose of this paper is to demonstrate and evaluate the prioritization and categorization method (PCM) which facilitates the active participation of process stakeholders (managers, owners, customers) in process assessments. Stakeholders evaluate processes in terms of effectiveness, efficiency and relevance against certain contextual business and industry factors. This collective evaluation serves as a foundation for the management decision making process regarding process improvement and redesign.  The PCM is examined based on a case study at Ericsson. In total, 55 stakeholders, representing different organizational levels and functions, assessed eight core processes. Follow up interviews and feedback after the evaluation sessions were collected for triangulation purpose.  The PCM helps Ericsson evaluate its processes within business context and industry environments. The results show that, to realize seamless end to end processes in the eight assessed processes, Ericsson has to make a greater effort to improve its process structures, governance and culture for fulfilling the needs of future business. Ericsson Steering Group is satisfied with the insights provided and has decided to train more stakeholders to use PCM.  This research is based on a single case within a specific organizational setting. The results may not be necessary generalizable to other business and industry settings. Organizations need to configure PCM in consideration of their own processes and business contingencies to explore and fulfil their process improvement purposes.  This paper presents a new context aware, easy to use and holistic method for business process management (BPM) the PCM. The method requires the active engagement of stakeholders, it focusses on developing dynamic BPM capabilities and fully embeds organizational contingencies and contextual factors in the decision making regarding BPM. This paper contributes a novel method to explorative BPM.
An undergraduate course on model based system engineering for embedded systems
Venue: Comput. Appl. Eng. Educ.
Year: 2020

Model based system engineering (MBSE) is becoming an industrial standard to design embedded systems. Therefore, its integration in electrical and computer engineering education is critical. This article presents an undergraduate course on MBSE for embedded systems through the formulation of course learning outcomes, identification of the course contents, and the construction of a holistic view for the contents. The holistic view of the course binds the contents by providing the modeling methodology, the transformation engine, and the simulation environment of an end to end framework. Furthermore, students obtain integrated design experience, through problem based learning, using three case studies. Assessment through quantitative evaluation and students' feedback show the viability of the presented course.
On the descriptive ineffability of expressive meaning
Year: 2011

On the descriptive ineffability of expressive meaning This paper addresses the question of whether there can be a unitary account of expressive meaning by considering the descriptive ineffability of expressives such as damn or bastard, on the one hand, and certain kinds of repetition, on the other. Drawing on Blakemore's (2002) work on the semantics of discourse markers and Wharton's (2009) work on the pragmatics of non verbal communication, I show first, that Blakemore's notion of procedural meaning can provide an explanation for the descriptive ineffability of expressives such as damn; and, second, that why linguistic expressives are similar to non linguistic expressive behaviour such as gesture and tone of voice. Finally, I show that the descriptive ineffability of expressive meanings conveyed by repetition must be given a different sort of explanation: it follows from the hearer's assumption that the processing effort entailed by the repetition can be offset by weakly communicated cognitive effects effects which the speaker trusts the hearer to derive for himself on the basis of his memory and imagination. The paper concludes by speculating on why these two different sorts of expressive meaning are not distinguished in work on free indirect style (cf Banfield 1982, Fludernik 1993)  Descriptive ineffability Expressive Expletive Free indirect style Interjection Non verbal communication Procedural meaning Relevance Repetition Weak communication
The Power of Political Image: Justin Trudeau, Instagram, and Celebrity Politics
Year: 2019

This article explores dynamics of online image management and its impact on leadership in a context of digital permanent campaigning and celebrity politics in Canada. Recent studies have shown that images can play a critical role when members of the public are evaluating politicians. Specifically, voters are looking for specific qualities in political leaders, including honesty, intelligence, friendliness, sincerity, and trustworthiness, when making electoral decisions. Image management techniques can help create the impression that politicians possess these qualities. Heads of governments using social media to capture attention through impactful images or videos on an almost daily basis seems like a new norm. Specifically, this article takes interest in Justin Trudeau's use of Instagram during the first year immediately following his election on October 19, 2015. Through a hybrid quantitative and qualitative approach, we examine how Trudeau and his party convey a specific image to voters in a context of permanent and increasingly personalized campaigning. We do so through an analysis of his Instagram feed focusing on different elements, including how he frames his governing style visually, how his personal life is used on his Instagram to support the Liberal Party of Canada's values and ideas, and how celebrity culture codes are mobilized to discuss policy issues such as environment, youth, and technology. This analysis sheds light on the effects and implications of image management in Canada. More generally, it offers a much needed look at image based e politicking and contributes to the academic literature on social media, permanent campaigning, as well as celebrity and politics in Canada.
InMoDeGAN: Interpretable Motion Decomposition Generative Adversarial Network for Video Generation
Venue: ArXiv
Year: 2021

In this work, we introduce an unconditional video generative model, InMoDeGAN, targeted to (a) generate high quality videos, as well as to (b) allow for interpretation of the latent space. For the latter, we place emphasis on interpreting and manipulating motion. Towards this, we decompose motion into semantic sub spaces, which allow for control of generated samples. We design the architecture of InMoDeGAN generator in accordance to proposed Linear Motion Decomposition, which carries the assumption that motion can be represented by a dictionary, with related vectors forming an orthogonal basis in the latent space. Each vector in the basis represents a semantic sub space. In addition, a Temporal Pyramid Discriminator analyzes videos at different temporal resolutions. Extensive quantitative and qualitative analysis shows that our model systematically and significantly outperforms state of the art methods on the VoxCeleb2 mini and BAIR robot datasets w.r.t. video quality related to (a) Towards (b) we present experimental results, confirming that decomposed sub spaces are interpretable and moreover, generated motion is controllable.
A dual vibration reduction structure based self powered active suspension system with PMSM ball screw actuator via an improved H2/H control
Year: 2020

PMSM ball screw actuator used in active suspensions has a promise of high energy efficiency, large transmission ratio, and compact structure; however, the nonlinear damping and the overlarge equivalent inertial mass of the actuator have impeded development of the active suspension. In this study, a dual vibration reduction structure according to the stiffness and the damping enhancement is proposed to configure a self powered featured active suspension. First, mechanics and energy regeneration of the proposed actuator are tested based on the varying charge voltage method. Subsequently, the dual vibration reduction structure is developed by adding the extra spring and damper between the unsprung mass and the conventional vibration reduction device. To regulate the proposed active suspension system, an improved H2/H is developed based on a new soft constraint involved objective function to generate the applicable ideal active force via feedforward and feedback linearization modeling. Moreover, the dual vibration reduction structure is optimized through genetic algorithms according to the novel fitness function. Finally, the comparisons are carried out by evaluating the proposed active suspension, the ideal active suspension and the passive suspension. The results demonstrate that the proposed active suspension regulated by the improved H2/H control is self powered to achieve a near ideal performance.
Anti obesity effects of tea from Mangifera indica L. leaves of the Uba variety in high fat diet induced obese rats.
Venue: Biomedicine pharmacotherapy Biomedecine pharmacotherapie
Year: 2017

Due to the high content of bioactive compounds, herbal teas are being investigated as adjuvant in chronic disease management. Studies have shown that mango leaf tea contain mangiferin, total phenolics and antioxidants, compounds with many functional properties. Therefore, this study aims to evaluate the anti obesity effects of tea from Mangifera indica L. leaves, Uba variety (TML) in obese rats fed a high fat diet (HFD) For this, adult male Wistar rats were divided into three groups (n=8) the control group (fed AIN 93 diet) obese group (fed a HFD) and treated group (fed a HFD and supplemented with TML for 8 weeks) We analysed biometric measures and serum biochemical parameters of metabolic control, inflammation and oxidative stress biomarkers, histomorphometry of visceral adipose tissue and mRNA expression of peroxisome proliferator activated receptor gamma co activator 1 alpha (PPAR g) lipoprotein lipase (LPL) and fatty acid synthase (FAS) The consumption of TML (24.7+ 2.1mL/day) exerted antioxidant and anti inflammatory effects, increasing total antioxidant capacity and interleukin 10 serum concentrations, reduced abdominal fat accumulation, upregulated PPAR g and LPL and downregulated FAS expression. Our data suggest that TML has therapeutic potential in treating obesity and related diseases through regulating the expression of transcriptional factors and enzymes associated with adipogenesis.
PFS: A Personalized Flight Recommendation Service via Cross Domain Triadic Factorization
Venue: 2018 IEEE International Conference on Web Services (ICWS)
Year: 2018

When a passenger is going to book an airline flight, after he inputs his query conditions, he has to search from a long flight list to find the one that best matchs his preferences. Therefore, a friendly personalized flight recommender system is a necessary tool for online travel service companies. However, the majority of current approaches do not work well since in most cases, there is no enough historical order information on the route the customers may plan to take. In this paper, we propose an approach for building a Personalize Flight recommendation Service (PFS) In PFS, the attributes' information of flight orders is organized into several domains, and a tensor factorization method is used to recommend flights to users. Specifically, PFS applies a history based weighting strategy to better model users' biases. PFS is also implemented in a distributed and parallel way to increase its execution speed when dealing with a huge amount of flight data. Extensive experiments on both a real flight order dataset and a synthetic large scale dataset show the superiority of our model against other comparative ones.
Construction and teaching practice of provincial top quality online open course of fresh electronic commerce and cold chain logistics
Year: 2019

Through designing teaching situation, organizing fragmented teaching content and resources, and supplementing and expanding traditional classroom, excellent online open course has played a great role in promoting classroom reform and innovation in higher education. Fresh e commerce and cold chain logistics are the core courses of logistics management, e commerce and other specialties. They are characterized by many knowledge points, strong practicality and rapid content updating. Fresh E commerce and Cold Chain Logistics of Henan College of Animal Husbandry Economy is an online open course of provincial high quality resources. It has been running for two semesters, with a total number of 1374 students. This paper expounds the course construction from the aspects of construction foundation, content design, application sharing, construction measures and characteristics, and probes into the existing problems in the course of course operation. "Sheng Xian Dian Shang Yu Leng Lian Wu Liu "Sheng Ji Jing Pin Zai Xian Kai Fang Ke Cheng De Jian She Yu Jiao Xue  Han Bing He Nan Mu Ye Jing Ji Xue Yuan Wu Liu Yu Dian Shang Xue Yuan ,He Nan Zheng Zhou 450044 Dong Bei Cai Jing Da Xue Guan Li Ke Xue Yu Gong Cheng Xue Yuan ,Liao Zhu ,Da Lian 116023 renjiajia85@qq.com, 45027523@qq.com, 19805264@qq.com, 307331232@qq.com *Ren Jia Jia Guan Jian Ci Sheng Xian Dian Shang Leng Lian Wu Liu Zai Xian Kai Fang Ke Cheng Hun He Shi Jiao Xue Zhong Wen Zhai Yao Jing Pin Zai Xian Kai Fang Ke Cheng Tong Guo She Ji Jiao Xue Qing Jing ,Zu Zhi Sui Pian Hua Jiao Xue Nei Rong He Zi Yuan ,Shi Chuan Tong Ke Tang De Bu Chong Yu Kuo Zhan ,Dui Cu Jin Gao Deng Jiao Yu Ke Tang Gai Ge Yu Chuang Xin Fa Hui Liao Ju Da Zuo Yong Sheng Xian Dian Shang Yu Leng Lian Wu Liu Shi Wu Liu Guan Li Dian Zi Shang Wu Deng Zhuan Ye De He Xin Ke Cheng ,Ju You Zhi Shi Dian Duo Shi Jian Xing Qiang Nei Rong Geng Xin Xun Su De Te Dian He Nan Mu Ye Jing Ji Xue Yuan De <Sheng Xian Dian Shang Yu Leng Lian Wu Liu Shi Sheng Ji Jing Pin Zi Yuan Zai Xian Kai Fang Ke Cheng ,Xian Yi Yun Xing 2Xue Qi Xuan Ke Zong Ren Shu Da 1374Ren Ben Wen Cong Jian She Ji Chu Nei Rong She Ji Ying Yong Gong Xiang Jian She Cuo Shi Te Se Deng Fang Mian Chan Shu Liao Ke Cheng De Jian She Qing Kuang ,Bing Dui Ke Cheng Zai Yun Xing Guo Cheng Zhong De Xian Cun Wen Ti Jin Xing Liao Tan Tao 2nd International Conference on Humanities Education and Social Sciences (ICHESS 2019)
Learning Heterogeneous Spatial Temporal Representation for Bike Sharing Demand Prediction
Venue: AAAI
Year: 2019

Bike sharing systems, aiming at meeting the public's need for "last mile" transportation, are becoming popular in recent years. With an accurate demand prediction model, shared bikes, though with a limited amount, can be effectively utilized whenever and wherever there are travel demands. Despite that some deep learning methods, especially long shortterm memory neural networks (LSTMs) can improve the performance of traditional demand prediction methods only based on temporal representation, such improvement is limited due to a lack of mining complex spatial temporal relations. To address this issue, we proposed a novel model named STG2Vec to learn the representation from heterogeneous spatial temporal graph. Specifically, we developed an event flow serializing method to encode the evolution of dynamic heterogeneous graph into a special language pattern such as word sequence in a corpus. Furthermore, a dynamic attention based graph embedding model is introduced to obtain an importance awareness vectorized representation of the event flow. Additionally, together with other multi source information such as geographical position, historical transition patterns and weather, e.g. the representation learned by STG2Vec can be fed into the LSTMs for temporal modeling. Experimental results from Citi Bike electronic usage records dataset in New York City have illustrated that the proposed model can achieve competitive prediction performance compared with its variants and other baseline models.