nils-herrmann/clean_scirepeval huggingface dataset:
Predicting Zika Prevention Techniques Discussed on Twitter: An Exploratory Study
Venue: CHIIR
Year: 2018

Social media platforms are widely seen as a valuable medium to spread a wide range of information including charitable causes and health awareness. But given the flexibility provided by the social media platforms, it is important to ensure that the right kind of information is delivered to the right audience when needed. The pilot study presented in this paper considered a sample of Zika related tweets that were classified into different prevention techniques. The classification categories were drawn from the guidelines by CDC. Training a logistic regression model on the annotated data we found the accuracy to be 72% The findings are significant in studying the effectiveness of social media platforms in spreading the right kind of information in time. This in turn can be useful in informing health care officials to take necessary steps with the help of real time communication for such unfortunate events in future.
Higher vs lower positive end expiratory pressure in patients with acute lung injury and acute respiratory distress syndrome: systematic review and meta analysis.
Venue: JAMA
Year: 2010

Trials comparing higher vs lower levels of positive end expiratory pressure (PEEP) in adults with acute lung injury or acute respiratory distress syndrome (ARDS) have been underpowered to detect small but potentially important effects on mortality or to explore subgroup differences.  To evaluate the association of higher vs lower PEEP with patient important outcomes in adults with acute lung injury or ARDS who are receiving ventilation with low tidal volumes and to investigate whether these associations differ across prespecified subgroups.  Search of MEDLINE, EMBASE, and Cochrane Central Register of Controlled Trials (1996 January 2010) plus a hand search of conference proceedings (2004 January 2010)  Two reviewers independently screened articles to identify studies randomly assigning adults with acute lung injury or ARDS to treatment with higher vs lower PEEP (with low tidal volume ventilation) and also reporting mortality.  Data from 2299 individual patients in 3 trials were analyzed using uniform outcome definitions. Prespecified effect modifiers were tested using multivariable hierarchical regression, adjusting for important prognostic factors and clustering effects.  There were 374 hospital deaths in 1136 patients (32.9% assigned to treatment with higher PEEP and 409 hospital deaths in 1163 patients (35.2% assigned to lower PEEP (adjusted relative risk [RR] 0.94; 95% confidence interval [CI] 0.86 1.04; P .25) Treatment effects varied with the presence or absence of ARDS, defined by a value of 200 mm Hg or less for the ratio of partial pressure of oxygen to fraction of inspired oxygen concentration (P .02 for interaction) In patients with ARDS (n 1892) there were 324 hospital deaths (34.1% in the higher PEEP group and 368 (39.1% in the lower PEEP group (adjusted RR, 0.90; 95% CI, 0.81 1.00; P .049) in patients without ARDS (n 404) there were 50 hospital deaths (27.2% in the higher PEEP group and 44 (19.4% in the lower PEEP group (adjusted RR, 1.37; 95% CI, 0.98 1.92; P .07) Rates of pneumothorax and vasopressor use were similar.  Treatment with higher vs lower levels of PEEP was not associated with improved hospital survival. However, higher levels were associated with improved survival among the subgroup of patients with ARDS.
QUEIJO MINAS FRESCAL COM TEOR REDUZIDO DE LACTOSE E ADICIONADO DE BACTERIAS PROBIOTICAS DO GENERO KEFIR
Year: 2018

O queijo e o principal, e mais consumido, produto derivado do leite.Entre esses, o queijo minas frescal e um dos mais comsumidos no Brasil, porem grande parte da populacao mundial adulta apresenta alergia ou intolerancia a lactose. Assim sendo, o presente trabalho teve por objetivo elaborar um queijo minas frescal com teor reduzido de lactose com adicao de probioticos do genero kefir, analisando suas caracteristicas fisico quimicas e sensoriais. A adicao de bacterias probioticas teve por objetivo oferecer um bom estado nutricional ao queijo por meio da incorporacao de graos de kefir. Foram desenvolvidas tres formulacoes de queijo, T1, T2 e T3, com o leite tratado com a enzima lactase nas concentracoes de 0,3,  A lactose foi diminuida em 50% em queijos adicionados de enzima lactase, chegando a atingir 78,10% no tratamento com maior quantidade da enzima. Os valores de proteina (de 14,64+0,16 a 11,67+0,07% cinzas (2,47+0,01% a 2,62+0,04% e gordura (de 11,70+0,03% a 13,38+0,08% e pH (6,61 a 5,23) apresentaram se dentro do esperado. Sendo assim, a avaliacao fisico quimica demonstrou que todos os queijos desenvolvidos estavam de acordo com a legislacao vigente. Na analise sensorial, evidenciou se que o tratamento T1 foi o mais aceito pelos provadores. Com base nisso, pode se concluir que a adicao de lactase e probioticos teve um resultado eficaz nos queijos desenvolvidos, mostrando se uma opcao positiva para o mercado de laticinios.
Personality Perception of Robot Avatar Teleoperators in Solo and Dyadic Tasks
Venue: Front. Robot. AI
Year: 2017

Humanoid robot avatars are a potential new tele communication tool whereby a user is remotely represented by a robot that replicates their arm and head movements. They have been shown to have a number of benefits over more traditional media such as phones or video calls. However using a tele operated humanoid as a communication medium inherently changes the appearance of the operator, and appearance based stereotypes are used in interpersonal judgements (whether consciously or unconsciously) One such judgement that plays a key role in how people interact is personality. Hence, we have been motivated to investigate if and how using a robot avatar alters the perceived personality of tele operators. To do so we carried out two studies where participants performed 3 communication tasks, solo in study one and dyadic in study 2, and were recorded on video both with and without robot mediation. Judges recruited using online crowdsourcing services then made personality judgements of those in the video clips. We observed that judges were able to make internally consistent trait judgements in both communication conditions. However, judge agreement was affected by robot mediation, although which traits were affected was highly task dependent. Our most important finding was that in dyadic tasks personality trait perception was shifted to incorporate cues relating to the robot's appearance when it was used to communicate. Our findings have important implications for tele presence robot design and personality expression in autonomous robots.
Differential triggering of spontaneous glutamate release by P/Q N and R type Ca2+ channels
Venue: Nature Neuroscience
Year: 2013

The role of voltage gated Ca2+ channels (VGCCs) in spontaneous miniature neurotransmitter release is incompletely understood. We found that stochastic opening of P/Q N and R type VGCCs accounts for ~50% of all spontaneous glutamate release at rat cultured hippocampal synapses, and that R type channels have a far greater role in spontaneous than in action potential evoked exocytosis. VGCC dependent miniature neurotransmitter release (minis) showed similar sensitivity to presynaptic Ca2+ chelation as evoked release, arguing for direct triggering of spontaneous release by transient spatially localized Ca2+ domains. Experimentally constrained three dimensional diffusion modeling of Ca2+ influx exocytosis coupling was consistent with clustered distribution of VGCCs in the active zone of small hippocampal synapses and revealed that spontaneous VGCCs openings can account for the experimentally observed VGCC dependent minis, although single channel openings triggered release with low probability. Uncorrelated stochastic VGCC opening is therefore a major trigger for spontaneous glutamate release, with differential roles for distinct channel subtypes.
Dimension expansion of high capacity optical data storage
Year: 2019

Human beings are entering a Big Data era, which has significantly boosted the current digital economy and society. But in reality, all current data storage technologies and mediums can only store less than half of what we generate, which means most of the data will be forcibly lost if without breakthrough in high capacity storage technologies. However, Ernst Abbe set a fundamental barrier that limits the smallest feature size of a recording voxel to approximately half of the wavelength. Alternatively, this limitation could be overcome by implementing multiplex technology. In this review, techniques employed various multiplex dimensions such as 3D space, polarization and wavelength are briefly introduced. Especially, we highlight the development history, current state of the art and urgent challenges of five dimensional optical data storage based on laser induced nanogratings.
TUTORIAL ON AGENT BASED MODELING AND SIMULATION: ABM DESIGN FOR THE ZOMBIE APOCALYPSE
Venue: 2018 Winter Simulation Conference (WSC)
Year: 2018

Agent based modeling (ABM) and simulation is an approach to modeling systems comprised of autonomous, interacting agents. Computational advances are making it possible to develop agent based models in a variety of application areas, including areas where simulation has not been extensively applied. ABM applications range from supply chains, consumer goods markets, and financial markets, to predicting the spread of epidemics and understanding the factors responsible for the fall of ancient civilizations. Progress suggests that ABM could have far reaching effects on the way that businesses use computer models to support decision making and how researchers use models as electronic laboratories to identify promising research directions. Some contend that ABM "is a third way of doing science" and could augment traditional discovery methods for creating new knowledge. This brief tutorial introduces agent based modeling by describing key concepts of ABM and addressing toolkits and methods for developing agent based models.
Sequential Recommendation with Relation Aware Kernelized Self Attention
Venue: AAAI
Year: 2020

Recent studies identified that sequential Recommendation is improved by the attention mechanism. By following this development, we propose Relation Aware Kernelized Self Attention (RKSA) adopting a self attention mechanism of the Transformer with augmentation of a probabilistic model. The original self attention of Transformer is a deterministic measure without relation awareness. Therefore, we introduce a latent space to the self attention, and the latent space models the recommendation context from relation as a multivariate skew normal distribution with a kernelized covariance matrix from co occurrences, item characteristics, and user information. This work merges the self attention of the Transformer and the sequential recommendation by adding a probabilistic model of the recommendation task specifics. We experimented RKSA over the benchmark datasets, and RKSA shows significant improvements compared to the recent baseline models. Also, RKSA were able to produce a latent space model that answers the reasons for recommendation.
PENDIDIKAN KARAKTER DALAM EKSTRAKURIKULER PRAMUKA DI SMP NEGERI 1 YOGYAKARTA
Year: 2016

Penelitian ini bertujuan untuk mendeskripsikan proses dan implementasi pendidikan karakter dalam ekstrakurikuler Pramuka di SMP Negeri 1 Yogyakarta, mengkaji secara mendalam mengenai faktor pendukung dan penghambat, serta strategi yang digunakan dalam mengatasi hambatan yang muncul dalam implementasi kebijakan tersebut. Penelitian ini menggunakan pendekatan kualitatif dengan metode deskriptif. Subjek dalam penelitian ini adalah kepala sekolah, guru, pembina Pramuka, dan siswa sebagai dewan penggalang. Metode pengumpulan data yang digunakan berupa observasi, wawancara, dan dokumentasi. Analisis data menggunakan teknik deskriptif kualitatif melalui reduksi data, penyajian data, dan penarikan kesimpulan. Uji keabsahan data menggunakan triangulasi teknik dan sumber. Hasil penelitian ini menunjukkan bahwa: 1) Proses dan implementasi pendidikan karakter dalam ekstrakurikuler Pramuka di SMP Negeri 1 Yogyakarta menggunakan beberapa metode yaitu; a) metode belajar interaktif progresif, b) sistem among, c) kiasan dasar. 2) Faktor pendukung yaitu UU No. 12 Tahun 2010 tentang Gerakan Pramuka serta hasil dari Keputusan Musyawarah Nasional Gerakan Pramuka nomor: 11/Munas/2013 tentang AD/ART Gerakan Pramuka, fasilitas dan prasarana yang lengkap, antusiasme peserta didik, pembina Pramuka yang profesional, kurikulum sekolah yang mewajibkan ekstrakurikuler Pramuka, serta pengelolaan kegiatan ekstrakurikuler Pramuka yang sudah baik. Faktor penghambat yaitu terbatasnya anggaran dana sekolah, masih ada beberapa siswa yang menganggap Pramuka hanya sebatas melaksanakan kegiatan sekolah saja, ditambah lagi dengan minimnya pengetahuan orang tua tentang kegiatan ekstrakurikuler Pramuka. 3) Strategi sekolah dengan cara mendapatkan dana dari pentas seni, persewaan gedung olahraga (GOR) Dana BOS dan bantuan dari Dinas Pendidikan. Serta diadakannya pertemuan rutin maupun insidental dengan orang tua atau wali murid.  Pendidikan Karakter, Ekstrakurikuler Pramuka
A Vendor Buyer Supply Chain Model for Deteriorating Item with Quadratic Time Varying Demand and Pro rata Warranty Policy
Year: 2018

The article considers a single vendor a single buyer supply chain in which the buyer sells a seasonal deteriorating product to customers over a single period of time. At the buyer's end, the demand is assumed to be quadratic in time. The vendor follows a lot for lot policy for replenishment made to the buyer and (s)he agrees to refund the customer's purchase price on a pro rata basis, if any item fails during the warranty period offered by the buyer. We derive and optimize the average expected total cost of the supply chain in order to obtain the optimal decisions of the integrated system. An algorithm is developed for finding the optimal solution of the model numerically. A numerical example is taken to demonstrate the coordination policy between the vendor and the buyer. Sensitivity analysis is carried out to investigate the effects of key parameters on the optimal decisions.
Anatomy, Shoulder and Upper Limb, Brachial Artery
Year: 2019

The brachial artery is the extension of the axillary artery starting at the lower margin of the teres major muscle and is the major artery of the upper extremity. The brachial artery courses along the ventral surface of the arm and gives rise to multiple smaller branching arteries before reaching the cubital fossa.[1] These branching arteries include the deep brachial artery, the superior ulnar collateral artery, and the inferior ulnar collateral artery. Once the brachial artery reaches the cubital fossa, it divides into its terminal branches: the radial and ulnar arteries of the forearm. The brachial artery and its branches supply the biceps brachii muscle, triceps brachii muscle, and coracobrachialis muscle. The median nerve, a division of the brachial plexus, initially lies lateral to the brachial artery at its proximal segment. At its distal segment, the median nerve crosses the medial side of the brachial artery and lies in the ventral cubital fossa.
Sexual assault history and self destructive behaviors in women college students: Testing the perniciousness of perfectionism in predicting non suicidal self injury and suicidal behaviors
Venue: Personality and Individual Differences
Year: 2019

The present study examined presence of sexual assault history and perfectionism (viz. positive strivings evaluative concerns) as predictors of self destructive behaviors (viz. NSSI suicidal behaviors) in a sample of 287 women college students. Results obtained from conducting a series of hierarchical regression analyses indicated several notable patterns. Sexual assault history was a consistent predictor of both NSSI and suicidal behaviors. Moreover, the inclusion of perfectionism was also found to consistently predict additional unique variance in NSSI and suicidal behaviors, even after accounting for sexual assault history. These patterns remained largely unchanged even after accounting for shared variance between NSSI and suicidal behaviors. Within the perfectionism set, evaluative concerns emerged as the most consistent unique predictor of both indices of self destructive behavior. Finally, we did not find evidence for a significant Positive Strivings x Evaluative Concerns interaction effect in our analyses. Overall, our findings indicate that beyond the presence of sexual assault history, perfectionism remains an important predictor of self destructive behaviors in women college students.
Assessing the Relationship Between Job Demands, Job Resources, Burnout, Work Engagement, and Work Life Balance Among Teachers in a Secondary Public School
Year: 2020

Using the Job Demands Resources (JD R) Model as a framework, this study aimed to determine the association between job resources, job demands, burnout, work engagement, and work life balance among teachers in a secondary public school. The researcher employed a quantitative research design through a self administered survey among teachers in a secondary public school (School X) in Paranaque City, National Capital Region, Philippines using convenience sampling in selecting the participants from School X. Cronbach's Alpha tested the reliability of the data. Bivariate relationships were then explored using Pearson Correlation to determine how significant and to what degree are the relationships among the investigated variables. The results confirmed the following relationships based from the hypothesized JD R Model: (1) there is a positive association between job demands and burnout; (2) there is a positive association between job resources and work engagement; and (3) there is a negative association between burnout and work life balance. However, the data from this study revealed that there is no significant association between work engagement and work life balance. Finally, in predicting work life balance using burnout and work engagement, only burnout remains the significant regressor. This study contributed to the limited Philippine based literature explaining how job demands and resources are associated with burnout and work engagement, respectively, and how these mechanisms are integral to the work life balance of public school teachers. The study found that work life balance among public school teachers may improve by primarily managing and reducing the demands of their jobs. https:/doi.org/10.26803/ijhss.12.4.3
FDC Cache: Semantics driven Federated Caching and Querying for Big Data
Venue: 2020 IEEE International Conference on Big Data (Big Data)
Year: 2020

To deliver business value, most data driven enterprises and applications require data to be extracted and merged from otherwise siloed data storage platforms. FDC Cache has been designed and developed to enable the fusion and caching of data drawn from multiple small and/or Big Data stores. This capability executes a sequence of queries, wherein the results from one query may be used to constrain subsequent queries. The results of each query are linked with results from previous queries, incrementally building a cache of semantically linked data that can be used to support multiple independent data requests. FDC Cache uses Semantic Web technologies, and knowledge graphs in particular, to describe the relevant data and relationships in a computable model. This enables applications to reason over the graph, for example to dynamically retrieve targeted subsets of data comprised of previously disparate information. We have successfully applied FDC Cache to two distinct industrial use cases: (i) merging data across multiple sources to assemble information about current parts in a gas turbine, and (ii) dynamically aligning siloed data from electric grid transmission and distribution networks to an industry standard common model, in which the cache creation time has been shown to scale sub linearly with the number of data elements. FDC Cache has been open sourced as part of the GE developed open source Semantics Toolkit.
Assessing the Relationship between Rewards and Employee's Motivation in Some Selected Non Profit Organizations in Abuja, Nigeria
Year: 2018

This study examines the relationship between rewards and employee's motivation in four selected non profit organizations in Abuja, Nigeria. The employees of the four organizations (Action Aid Nigeria, African Development Foundation (ADF) African Youth Growth Foundation (AYGF) and Think Nigeria First Initiative) were taken as sample of the study. The objectives of this study were to find out the relationship between rewards and employees' performance in the non profit organization in Abuja, Nigeria and also to ascertain the extent to which both intrinsic and extrinsic rewards impact on employees' performance. Self designed questionnaire was used for data collection.180questionnaires were distributed and 154 were returned, hence the response rate was 83.2% The data was analyzed using the techniques of rank correlation coefficient and multiple regression analysis. All the findings were tested at 0.01 and 0.05 level of significance. The result concludes that there is a direct relationship between extrinsic rewards and the employee's motivation. However, intrinsic rewards found an insignificant impact on employee motivation.  Rewards, Employee motivation, Non Profit Organization (NGO) intrinsic, extrinsic
Visual Question Generation from Radiology Images
Venue: ALVR
Year: 2020

Visual Question Generation (VQG) the task of generating a question based on image contents, is an increasingly important area that combines natural language processing and computer vision. Although there are some recent works that have attempted to generate questions from images in the open domain, the task of VQG in the medical domain has not been explored so far. In this paper, we introduce an approach to generation of visual questions about radiology images called VQGR, i.e. an algorithm that is able to ask a question when shown an image. VQGR first generates new training data from the existing examples, based on contextual word embeddings and image augmentation techniques. It then uses the variational auto encoders model to encode images into a latent space and decode natural language questions. Experimental automatic evaluations performed on the VQA RAD dataset of clinical visual questions show that VQGR achieves good performances compared with the baseline system. The source code is available at https:/github.com/sarrouti/vqgr.