nils-herrmann/clean_scirepeval huggingface dataset:
Modification of Nafion membrane with biofunctional SiO2 nanofiber for proton exchange membrane fuel cells
Year: 2017

Proton currents are an integral part of the most important energy converting structures in biology. We prepared a new type of bioinspired Nafion (Bio Nafion) membrane composited of biofunctional SiO2 (Bio SiO2) nanofiber and Nafion matrix. SiO2 nanofibers were prepared by electrospinning silica sol prepared from tetraethyl orthosilicate. Meanwhile, Bio SiO2 nanofibers were synthesized by immobilizing amino acids (cysteine, serine, lysine, and glycine) on SiO2 nanofibers, which acted as efficient proton conducting pathways that involved numerous H+ transport sites. In our study, the SiO2 nanofibers biofunctionalized with cysteine were further oxidized, and the composite membranes were designated as Nafion Cys, Nafion Lys, Nafion Ser, and Nafion Gly, respectively. We then investigated the different polar groups SO3H, OH, and NH2) of the amino acids that contributed to membrane properties of thermal stability, water uptake (WU) dimensional stability, proton conductivity, and methanol permeability. Nafion Cys exhibited the highest proton conductivity of 0.2424 S/cm (80 degC) Nafion Gly showed the lowest proton conductivity and WU because glycine contains the least number of hydrophilic groups among the amino acids. Overall, the introduction of Bio SiO2 nanofiber to composite membranes significantly improved proton conductivity, dimensional stability, and methanol permeability.
Usefulness of Three Dimensional CT Scanning for Preoperative Diagnosis of Postoperative Paranasal Sinus Cysts
Year: 2006

The surgical strategy for postoperative paranasal sinus cysts (POSC) is often difficult, even with helical CT and MRI images. Not only the number and location, but also the hardness (bony or soft) of the POSC wall is an important factor to determine surgical approaches. The existing instruments may be unable to resolve the problems above mentioned.We have tried to decide on the best surgical strategy for POSC in such difficult cases, using the new three dimensional CT scan (3D Accuitomo(r) Morita, Inc. Kyoto) that provides high resolution sagittal, coronal and axial slice views of complex postoperative structures of the paranasal sinuses. 512 frames of X ray pictures are taken by 3D CT, and transmitted to a personal computer (PC) as digital data, where the data are stored as mass volume data. Without being time consuming, the mass volume data can easily be sliced in parallel in selected planes to obtain the best CT images of interest on the PC. And we can therefore choose appropriate surgical approaches, such as an endoscopic endonasal or transantral method.Between October 2004 and April 2005, 8 patients with POSC were operated on with the aid of the 3D CT scan. The CT was very helpful for preoperative diagnosis of the disease.
Ablation of glucokinase expressing tanycytes impacts energy balance and increases adiposity in mice
Venue: Molecular metabolism
Year: 2021

Glucokinase (GCK) is critical for glucosensing. In rats, GCK is expressed in hypothalamic tanycytes and appears to play an essential role in feeding behavior. In this study, we investigated the distribution of GCK expressing tanycytes in mice and their role in the regulation of energy balance.  In situ hybridization, reporter gene assay, and immunohistochemistry were used to assess GCK expression along the third ventricle in mice. To evaluate the impact of GCK expressing tanycytes on arcuate neuron function and mouse physiology, Gck deletion along the ventricle was achieved using loxP/Cre recombinase technology in adult mice.  GCK expression was low along the third ventricle, but detectable in tanycytes facing the ventromedial arcuate nucleus from bregma 1.5 to 2.2. Gck deletion induced the death of this tanycyte subgroup through the activation of the BAD signaling pathway. The ablation of GCK expressing tanycytes affected different aspects of energy balance, leading to an increase in adiposity in mice. This phenotype was systematically associated with a defect in NPY neuron function. In contrast, the regulation of glucose homeostasis was mostly preserved, except for glucoprivic responses.  This study describes the role of GCK in tanycyte biology and highlights the impact of tanycyte loss on the regulation of energy balance.
Finding Clues for Your Secrets: Semantics Driven, Learning Based Privacy Discovery in Mobile Apps
Venue: NDSS
Year: 2018

A long standing challenge in analyzing information leaks within mobile apps is to automatically identify the code operating on sensitive data. With all existing solutions relying on System APIs (e.g. IMEI, GPS location) or features of user interfaces (UI) the content from app servers, like user's Facebook profile, payment history, fall through the crack. Finding such content is important given the fact that most apps today are web applications, whose critical data are often on the server side. In the meantime, operations on the data within mobile apps are often hard to capture, since all server side information is delivered to the app in the same way, sensitive or not. A unique observation of our research is that in modern apps, a program is essentially a semantics rich documentation carrying meaningful program elements such as method names, variables and constants that reveal the sensitive data involved, even when the program is under moderate obfuscation. Leveraging this observation, we develop a novel semantics driven solution for automatic discovery of sensitive user data, including those from the server side. Our approach utilizes natural language processing (NLP) to automatically locate the program elements (variables, methods, etc. of interest, and then performs a learning based program structure analysis to accurately identify those indeed carrying sensitive content. Using this new technique, we analyzed 445,668 popular apps, an unprecedented scale for this type of research. Our work brings to light the pervasiveness of information leaks, and the channels through which the leaks happen, including unintentional over sharing across libraries and aggressive data acquisition behaviors. Further we found that many high profile apps and libraries are involved in such leaks. Our findings contribute to a better understanding of the privacy risk in mobile apps and also highlight the importance of data protection in today's software composition.
The production of prediction: What does machine learning want?
Year: 2015

Retail, media, finance, science, industry, security and government increasingly depend on predictions produced through techniques such as machine learning. How is it that machine learning can promise to predict with great specificity what differences matter or what people want in many different settings? We need, I suggest, an account of its generalization if we are to understand the contemporary production of prediction. This article maps the principal forms of material action, narrative and problematization that run across algorithmic modelling techniques such as logistic regression, decision trees and Naive Bayes classifiers. It highlights several interlinked modes of generalization that engender increasingly vast data infrastructures and platforms, and intensified mathematical and statistical treatments of differences. Such an account also points to some key sites of instability or problematization inherent to the process of generalization. If movement through data is becoming a principal intersection of power relations, economic value and valid knowledge, an account of the production of prediction might also help us begin to ask how its generalization potentially gives rise to new forms of agency, experience or individuations.
Omaha System Data: Methods for Research and Program Evaluation
Venue: Nursing Informatics
Year: 2009

Researchers are developing methods to evaluate health care quality and effectiveness using health informatics data sets. Standardized taxonomies such as the Omaha System are being used in computerized documentation systems to generate data on client assessments and health care services. Questions such as prevalence of client problems, care utilization, differential intervention effectiveness, and problem specific client outcomes can be investigated. Approaches for analyzing Omaha System data are emerging in the literature and in practice settings, and will be described in this poster.
Smart carpet using differential piezoresistive pressure sensors for elderly fall detection
Venue: 2015 IEEE 11th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob)
Year: 2015

Falls are events that affect almost every aging human being above the age of 65. These incidents can have major consequences on the physiological, psychological and socio economical levels. In this paper, a simple smart carpet design is developed to detect falls using a novel sensing technique. Conventional sensing methods use either inertial measurement sensors (accelerometers, gyroscopes) or environmental sensors (infrared, force, vibration, acoustic, etc. The proposed technique employs differential piezoresistive pressure sensors. The prototype of the system is implemented and tested using statistical methods. Experimental results show the sensitivity and the specificity of the system to be 88.8% and 94.9% respectively. The system could be deployed in home care environment as a final product. Our proposed sensing technique can be also integrated in beds to alert patients from falling during sleep.
Building an Argument for the Use of Science Fiction in HCI Education
Venue: IHSI
Year: 2019

Science fiction literature, comics, cartoons and, in particular, audio visual materials, such as science fiction movies and shows, can be a valuable addition in Human computer interaction (HCI) Education. In this paper, we present an overview of research relative to future directions in HCI Education, distinct crossings of science fiction in HCI and Computer Science teaching and the Framework for 21st Century Learning. Next, we provide examples where science fiction can add to the future of HCI Education. In particular, we argue herein first that science fiction, as tangible and intangible cultural artifact, can serve as a trigger for creativity and innovation and thus, support us in exploring the design space. Second, science fiction, as a means to analyze yet to come HCI technologies, can assist us in developing an open minded and reflective dialogue about technological futures, thus creating a singular base for critical thinking and problem solving. Provided that one is cognizant of its potential and limitations, we reason that science fiction can be a meaningful extension of selected aspects of HCI curricula and research.
Satisfacao e engajamento de visitantes a festivais: analise empirica de uma Oktoberfest
Year: 2020

To analyze the relationship between satisfaction and online engagement of visitors to the 34th Oktoberfest in Blumenau, Santa Catarina, Brazil, held in 2017.  An exploratory, documentary, and descriptive research was carried out, with a quantitative approach, through a survey with a questionnaire, applied during the month of October 2017 at Oktoberfest Blumenau, which resulted in 215 valid questionnaires.  The use of festivals as promoters of tourism in destinations has been massively used. However, with its growth, there was a need to find strategies to keep the visitors satisfied and engaged with its realization. Thus, seeking to maintain of its attractiveness and intention to revisit such an event. Oktoberfest is the main German cultural festival held across the country, and Blumenau has the largest edition in Brazil in number of audiences. Therefore, it is evident the need to assess how the visitor is perceiving the festival and how much she/he feels engaged with it, seeking to maintain the quality and appreciation of the typical German culture demonstrated through the Oktoberfest.  Among the main findings, it is highlighted that women were more satisfied with the Tangibility dimension, while men with the Empathy dimension. It was also possible to identify that visitor's satisfaction is not related to online engagement. Theoretical/methodological contributions: The study contributes to the academic literature by advancing research related to festivals and engagement, mainly through the use of Oktoberfest as an object of study. This festival has been used as a tourist product all over the world, however, researches that identify how it has been developing and whether it is in fact representing culture in a satisfactory way has not reached yet a significant space in the academic environment. Social/management contributions: The results presented here provide important results for the management and marketing not only of Blumenau's Oktoberfest, but also for other cultural events, where it shows that there are significant differences in relation to personal factors and their perception of engagement and satisfaction.
Consumer Cocreation in New Product Development
Year: 2010

The area of consumer cocreation is in its infancy and many aspects are not well understood. In this article, we outline and discuss a conceptual framework that focuses on the degree of consumer cocreation in new product development (NPD) The authors examine (a) the major stimulators and impediments to this process, (b) the impact of cocreation at each stage of the NPD process, and (c) the various firm related and consumer related outcomes. A number of areas for future research are suggested.
Sliding Mode Control of Wave Power Generation Plants
Venue: IEEE Transactions on Industry Applications
Year: 2012

The worldwide demand for energy requires alternatives to fossil fuels and nuclear fission, so renewable resources, particularly ocean energy, are called to play a relevant role in a near future. In particular, the oscillating water column (OWC) is one of the most promising devices to harness energy from the sea, as it is the case of the Nereida project plant, located in the Basque coast of Mutriku. This kind of devices consists of a particular type of turbine and a doubly fed induction generator. The turbogenerator module is usually controlled using a traditional proportional integral (PI) based vector control scheme, which requires an accurate knowledge of the system parameters and lacks of robustness, limiting, in some cases, the power extraction. To avoid these drawbacks, a novel sliding mode control based vector control scheme for the OWC plant is presented in this paper. This variable structure control is intrinsically robust under parameter uncertainties, which always appear in real systems, and presents a convenient disturbance rejection. The stability of the proposed controller is analyzed using the Lyapunov theory. The performance of the control scheme presented is proved by comparing it to the traditional PI based vector control scheme in a series of representative maximum power generation case studies. Both numerical simulations and experimental results show that the proposed solution provides high performance dynamic characteristics, improving the power extraction in spite of parameter uncertainties and system disturbances.
Situation evaluate on hierarchical network security based on D S evidence theory
Venue: Int. J. Commun. Networks Distributed Syst.
Year: 2014

With the development of network technology, the internet era is coming; the network security issues have become increasingly prominent. It is more important to conduct a comprehensive, accurate and quantitative evaluation for today's network security. Therefore, this paper proposed situation evaluation model for hierarchical network security based on D S evidence theory. The model uses the information collected from multi source sensors as source data, which was used for fusion and submitting to the upper layer based on D S evidence theory. We combined the existing vulnerability information and threats in service layer by scanning the log files and alarm events collected from sensors with analytical hierarchy process (AHP) to decide the relative weight of each factor. After evaluating the situational values of each node on host layer, we can finally evaluate network security situational values on the whole.
Bioleaching of rare earth elements from spent automobile catalyst as pretreatment method to improve Pt and Pd recovery: Process optimization and kinetic study
Year: 2021

In this study, the extraction of rare metals from the spent automobile catalyst using Aspergillus niger (A. niger) was investigated. The effect of different factors including initial glucose, initial pH, inoculum percentage, and Solid to Liquid (S/L) ratio on the A.niger growth was done. Then in the condition of initial glucose of 100 g/L, initial pH of 5, inoculum percentage of 2.5 S/L ratio of 1 (w/v) the extraction efficiency were 25.9 of cerium (Ce) 43.0 of aluminum (Al) for 240 h, and 23.9 of lanthanum (La) for 48 h. After the bioleaching section, the spent residue was applied for platinum (Pt) and palladium (Pd) recovery using aqua regia, which results in a 100 recovery of these metals. The shrinking core model results showed that both chemical reaction and diffusion on the surface controlled the overall reaction rate. Additionally, the characterization methods including SEM, FTIR, HPLC, and XRD before and after bioleaching were performed.
Impact of Loss and Gain Forecasting on the Behavior of Pricing Decision making
Year: 2020

Recent forecasting research has shown a paradigm shift from algorithm aversion to appreciation. Despite growing trust in technological decision support, business decisions are often made based on gut feeling and intuition, ignoring part or all of the available data and information. Creating effective decision support solutions necessitates the understanding of the impact of emerging artificial intelligence and machine learning technologies on business decision making processes. This study examines whether forecasting information delivery at a time when a business decision is made influences or changes the decision maker's mind, thereby leading to a different decision. The study employs a 2 x 2 between subject experimental setting where forecasted results (gain/loss) and automated advice (risk/certainty) were crossed examined. A sample of 137 participants was asked to make four different product price change decisions assisted by automated decision aid. The experiment involved two independent samples, one taken from Amazon Mechanical Turk workers and the other from the members of LinkedIn managerial groups. Results show that decision makers are more likely to rely on automated recommendation and change their initial decision when forecasted decision outcomes lead to gain, whereas they would discount algorithmic aid if a loss is forecasted. This research adds to the extant literature in the field of human technology interactions and contributes to the descriptive and prescriptive decision theories by illustrating that gain forecasting has a higher impact on the algorithm appreciation than loss forecasting.
A preliminary assessment of the impact of COVID 19 on environment A case study of China
Venue: Science of The Total Environment
Year: 2020

The coronavirus disease (COVID 19) is seriously threatening world public health security. Currently, >200 countries and regions have been affected by the epidemic, with the number of infections and deaths still increasing. As an extreme event, the outbreak of COVID 19 has greatly damaged the global economic growth and caused a certain impact on the environment. This paper takes China as a case study, comprehensively evaluating the dynamic impact of COVID 19 on the environment. The analysis results indicate that the outbreak of COVID 19 improves China's air quality in the short term and significantly contributes to global carbon emission reduction. However, in the long run, there is no evidence that this improvement will continue. When China completely lifts the lockdown and resumes large scale industrial production, its energy use and greenhouse gas (GHG) emissions are likely to exceed the level before the event. Moreover, COVID 19 significantly reduces the concentration of nitrogen dioxide (NO2) in the atmosphere. The decline initially occurred near Wuhan and eventually spread to the whole country. The above phenomenon shows that the decreasing economic activities and traffic restrictions directly lead to the changes of China's energy consumption and further prevent the environment from pollution. The results in this study support the fact that strict quarantine measures can not only protect the public from COVID 19, but also exert a positive impact on the environment. These findings can provide a reference for other countries to assess the influence of COVID 19 on the environment.
Fast and Furious: Podemos' Quest for Power in Multi level Spain
Year: 2016

After a stunning breakthrough in the 2014 European election, Podemos became the third largest parliamentary party in Spain in the 2016 general election and achieved representation in all regions. This article examines how Podemos has adapted to the opportunities and dilemmas posed by Spain's multi level setting in several ways: its formation in early 2014 and its evolution since; its ideological principles and policy menu; its organisation; and its political strategies and electoral alliances. The hypotheses test the effects of adaptation to multi level competition on the party electorate. The findings indicate the positive effect of support for more decentralisation on the likelihood of voting for Podemos, but also how this effect is territorially differentiated and could affect the party's cohesion and internal debate.
College Students' Digital Readiness for Academic Engagement (DRAE) Scale: Scale Development and Validation
Year: 2018

This study involves the development and validation of a survey that measures college students' digital readiness for academic engagement in terms of their perceived digital competencies for academic work. Both exploratory and confirmatory analyses were employed to assess the factorial structure of the Digital Readiness for Academic Engagement (DRAE) Scale. The participants in this study were undergraduate students enrolled in a Korean university. The data were randomly split into two groups. The results of the exploratory factor analysis indicated a five factor structure. In addition, confirmatory factor analysis found that the predicted model had an acceptable fit. The results are discussed, and implications for educational approaches in higher education are provided.
COVID 19: Protecting Healthcare Workers is a priority
Venue: Infection Control Hospital Epidemiology
Year: 2020

In Italy, more infections among healthcare personnel than in China were recorded. As of April 05, 2020 12,252 health workers in Italy have tested positive for COVID 19, making up 10% of Italy's COVID 19 cases; furthermore, 80 medical doctors and 25 nurses have died. Protecting healthcare workers is crucial in order not to amplify the COVID 19 epidemics. Moreover, relocating the public health emergency response from the hospitals to the territory, by integrating the hospital into an overall epidemic response, is a priority for contrasting further COVID 19 waves.