nils-herrmann/clean_scirepeval huggingface dataset:
Tweet Irony Detection Using Ensembles of Word Level Attentive Long Short term Memory and Convolutional Neural Network
Venue: 2018 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC FSKD)
Year: 2018

Irony detection is a key subtask of many natural language processing tasks. For example, irony can flip the polarity of "apparently positive" sentences and have a negative impact on polarity detection performance in sentiment analysis. Up to now, most of the irony detection methods are simple to deal with the task as text classification. However, irony expresses semantics in a very subtle way, so it requires a deeper understanding of natural language, which is beyond the grasp of standard text categorization techniques. In this paper, we design and ensemble two independent models, based on Bidirectional Long Short term Memory(BiLSTM) strengthened with self attention mechanism and a pre trained Convolutional Neural Network(CNN) to capture both the semantic and sentiment information in tweets. In the test set of irony detection, our model is superior to the traditional approach in terms of F1 score. More importantly, the model training takes less time because we don't need to manually find the rules and prepare a lot of time consuming and labor intensive other language knowledge, so our model is more developable.
Factors Predicting the Effectiveness of Celebrity Endorsement Advertising: HND Marketing Students Perspective
Year: 2020

Large amount of money is spent in contracting celebrity endorser to promote firms' brands. The purpose of this study was to reveal factors predicting the effectiveness of celebrity endorsement advertising from HND marketing student's perspective. The study utilized quantitative research design, Correlational and descriptive analysis via SPSS. The study collected both primary data via questionnaire and secondary data via literature review. Convenient sampling techniques were used. Questionnaire was employed by using five point Likert scale. The study found the important role of choosing a celebrity that possesses trust, expertise, attractive and overall credibility. The study concludes that the celebrity endorsement is an effective tool for advertising. The researchers suggest providing training to celebrity endorsers by firms before using them for such purposes.
ANALISA TAHAPAN INOVASI PADA PRODUK MINUMAN SARI KEDELAI SOY FUSION
Year: 2015

Abstrak Penelitian ini dilakukan untuk menganalisa tahapan inovasi produk pada minuman susu kedelai Soy yaitu lahirnya gagasan, penyaringan ide, pengembangan dan pengujian konsep, pengembangan strategi pemasaran, analisis bisnis, pengembangan produk, pengujian pasar, dan komersialisasi. Metode penelitian menggunakan metode penelitian deskriptif kualitatif. Pengumpulan data menggunakan wawancara semi terstruktur dan pengamatan. Pengujian keabsahan data menggunakan triangulasi sumber dengan membandingkan hasil wawancara dengan data dan pengamatan yang terkait. Hasil Penelitian ini menunjukkan bahwa gagasan dilahirkan dari internal dan eksternal perusahaan. Terdapat empat produk minuman susu kedelai dengan kombinasi sayur bayam, wortel dan buah naga serta cookies es krim. Target potensial ibu rumah tangga dan anak muda yang gemar mencoba hal baru dan peduli akan kesehatan. Dalam penetapan strategi pemasaran digunakan strategi bauran pemasaran. Untuk pengujian pasar dilakukan uji gelombang penjualan. Komersialisasi produk dilakukan di Toko Mitra Sidoarjo dan via delivery service untuk wilayah Surabaya.  Inovasi Produk, Bauran pemasaran, Susu Kedelai, Soy Fusion.
Pemodelan Dan Peramalan Indeks Harga Konsumen (IHK) Kota Sampit Dengan Seasonal Arima (Sarima)
Year: 2020

Sampit is one of 82 cities in Indonesia which calculate inflation. Inflation is an increase of prices on goods and services in a region. Government's control is very important because inflation relates to the real income, the exchange rate, import exports, and so on. Inflation is based on the Consumer Price Index (CPI) Because of CPI is a monthly data prices, it is highly influenced by seasonal factors. Therefore, CPI data modelling is needed because it helps the government to make appropriate policies. Method that can be used for time series data with seasonal influences is Seasonal Autoregressive Integrated Moving Average (SARIMA) The results of the study show that the right model for Sampit's CPI is SARIMA with the order p 1, d 1, P 1, D 1, Q 1, s 12. It is the best model that can built and be used for forecasting because with 95 percent of confidence, the model explains 87.23 percent of data. Forecasting in this research use interval analysis and found that January 2020 may be the highest increase of CPI (inflation) in 2020.  CPI, Inflation, SARIMA
Novel Polymerase Spiral Reaction (PSR) for rapid visual detection of Bovine Herpesvirus 1 genomic DNA from aborted bovine fetus and semen.
Venue: Gene
Year: 2018

Bovine herpesvirus 1 (BHV 1) is a major viral pathogen affecting bovines leading to various clinical manifestations and causes significant economic impediment in modern livestock production system. Rapid, accurate and sensitive detection of BHV 1 infection at frozen semen stations or at dairy herds remains a priority for control of BHV 1 spread to susceptible population. Polymerase Spiral Reaction (PSR) a novel addition in the gamut of isothermal techniques, has been successfully implemented in initial optimization for detection of BHV 1 genomic DNA and further validated in clinical samples. The developed PSR assay has been validated for detection of BHV 1 from bovine semen (n=99) a major source of transmission of BHV 1 from breeding bulls to susceptible dams in artificial insemination programs. The technique has also been used for screening of BHV 1 DNA from suspected aborted fetal tissues (n=25) The developed PSR technique is 100 fold more sensitive than conventional PCR and comparable to real time PCR. The PSR technique has been successful in detecting 13 samples positive for BHV 1 DNA in bovine semen, 4 samples more than conventional PCR. The aborted fetal tissues were negative for presence of BHV 1 DNA. The presence of BHV 1 in bovine semen samples raises a pertinent concern for extensively screening of semen from breeding bulls before been used for artificial insemination process. PSR has all the attributes for becoming a method of choice for rapid, accurate and sensitive detection of BHV 1 DNA at frozen semen stations or at dairy herds in resource constrained settings.
The plant immune system in heterogeneous environments.
Venue: Current opinion in plant biology
Year: 2019

The plant immune system inhibits pathogen growth and contributes to shaping a healthy microbial community in the plant body. Plants must appropriately respond to both microbial signals and abiotic factors that are diverse in time and space, and thus, proper integration of these inputs at local and systemic levels is of crucial importance for optimal plant responses and fitness in nature. Here, we review our current knowledge of three properties of the plant immune system, resilience, tunability, and balance, which enable plants to deal with complex cocktails of environmental factors. We also discuss future challenges on the path towards a comprehensive understanding of the interactions between plant immunity and pathogenic, non pathogenic, and beneficial microbes.
Moral disengagement and ethical decision making: The moderating role of trait guilt and shame.
Year: 2016

Process focused models of ethical decision making (EDM) have focused on individual and situational constraints influencing EDM processes and outcomes. Trait affect and propensity to morally disengage are two individual factors that influence EDM. The current study examines the moderating role of dispositional guilt and shame on the relationship between moral disengagement and EDM. Results indicate that moderate and high levels of dispositional guilt attenuate the negative relationship between moral disengagement and EDM, while low guilt does not. Dispositional shame does not moderate the relationship between moral disengagement and EDM. Implications for personnel selection are discussed.
Big data vs accurate data in health research: Large scale physical activity monitoring, smartphones, wearable devices and risk of unconscious bias.
Venue: Medical hypotheses
Year: 2018

Fundamental to the advancement of scientific knowledge is unbiased, accurate and validated measurement techniques. Recent United Nations and landmark Nature publications highlight the global uptake of mobile technology and the staggering potential for big data to encourage people to be physically active and to influence health policy. However, concerns exist about inconsistencies in smartphone health apps. Big data has many benefits, but noisy data may lead to wrong conclusions. In reaction to the increasing availability of low quality data; we call for a rigorous debate into the validity of substituting big data for accurate data in health research. We evaluated the step counting accuracy of a smartphone app previously used by 717,527 people from 111 countries. Our new data (from 48 participants; aged 21 59 years; body mass index 17.7 33.5 kg/m2) revealed significant (15 66% undercounting by Apple phones. In contrast to the generally positive performances of wearable devices for stereotypical treadmill like walking, we observed extraordinarily large (0 200% of steps taken) error ranges for both Android and Apple phones. Unconscious bias (developers' perceptions of usual behaviour) may be embedded into many unvalidated smartphone apps. Consumer grade wearable devices appear unsuitable to detect steps in people with slow, short or non stereotypical gait patterns. Specifically, there is a risk of systematically undercounting the steps by obese people, females or people from different ethnic groups resulting in biases when reporting associations between physical inactivity and obesity. More research is required to develop smartphone apps suitable for all people of the heterogeneous global population.
Borderline personality disorder in youth: The prospective impact of child abuse on non suicidal self injury and suicidality.
Venue: Comprehensive psychiatry
Year: 2016

Borderline personality disorder (BPD) is characterized by greater engagement in non suicidal self injury (NSSI) and suicidality. The aim of the study is to test whether the occurrence of child abuse contributes to these high risk behaviors in BPD youth.  BPD female youth aged 13 21years with (n=29) and without (n=29) a history of child abuse were administered clinical interviews assessing diagnostic history, child abuse, NSSI and suicidality (i.e. ideation, plans, and attempts) NSSI and suicidality were subsequently reevaluated at the 1 and 2 month follow up assessments.  Several findings emerged. First, relative to BPD youth without abuse, the abuse group reported greater past NSSI; however, no significant differences emerged in the follow up period. Second, the occurrence of child abuse was associated with a 5 fold increase in the rate of lifetime suicide attempts relative to the no abuse group and additionally, prospectively predicted suicide ideation (but not attempts) Last, exploratory analyses indicated that the co occurrence of physical and sexual abuse was associated with greater past NSSI and suicidality as compared to the no abuse and sexual abuse only participants.  As a whole, child abuse particularly co occurring physical and sexual abuse increases risk for NSSI and suicidality among BPD youth, which may have important treatment implications in this high risk population.
Kraken: ultrafast metagenomic sequence classification using exact alignments
Venue: Genome Biology
Year: 2013

Kraken is an ultrafast and highly accurate program for assigning taxonomic labels to metagenomic DNA sequences. Previous programs designed for this task have been relatively slow and computationally expensive, forcing researchers to use faster abundance estimation programs, which only classify small subsets of metagenomic data. Using exact alignment of k mers, Kraken achieves classification accuracy comparable to the fastest BLAST program. In its fastest mode, Kraken classifies 100 base pair reads at a rate of over 4.1 million reads per minute, 909 times faster than Megablast and 11 times faster than the abundance estimation program MetaPhlAn. Kraken is available at http:/ccb.jhu.edu/software/kraken/
Impact of policy incentives on the promotion of integrated PV and battery storage systems: a techno economic assessment
Venue: IET Renewable Power Generation
Year: 2020

During the last two decades, the use of residential photovoltaic (PV) systems has been widely promoted by governments through various support mechanisms such as feed in tariffs, net metering, net billing, etc. These support schemes have developed a secure investment environment, increasing the penetration level of PVs in low voltage distribution grids. Nonetheless, increased PV integration may introduce several technical problems regarding the secure operation of distribution grids. Battery energy storage (BES) systems can mitigate such challenges, but the high capital cost is one of the most important limiting factors towards the widespread use of these systems. In fact, the financial viability of integrated PV and BES systems under different support schemes remains an open issue. In this study, the profitability of PV and BES systems is evaluated through an advanced techno economic model, that provides the optimal size of PV BES system in terms of net present value, based on the electricity production and consumption profile of the installation, PV and BES systems costs, and electricity charges. The proposed model may be a useful tool for prosumers, grid operators and policymakers, to assess the impact of various incentive policy schemes and different BES operation strategies on the economic viability of PV BES systems.
Boosting Signal to Noise in Complex Biology: Prior Knowledge Is Power
Venue: Cell
Year: 2011

A major difficulty in the analysis of complex biological systems is dealing with the low signal to noise inherent to nearly all large biological datasets. We discuss powerful bioinformatic concepts for boosting signal to noise through external knowledge incorporated in processing units we call filters and integrators. These concepts are illustrated in four landmark studies that have provided model implementations of filters, integrators, or both.
Socio emotional school climate in relation to adjustment among sighted and visually impaired students
Year: 2011

School climate has long been recognized as having an important effect on student learning and achievement. The schools are the major social environment in which student shares beliefs, fears, value norms and where in turn student's cognitive and affective functioning is shaped by the characteristics of their schools and schooling. The climate of a school is one of the most important ingredients' of a successful instructional program and without a climate that creates a harmonious and well functioning school, a high degree of academic achievement is difficult.
LDM based dynamic network discovery and selection for IPv6 mobility management optimization in C ITS environments
Venue: 2015 International Conference on Models and Technologies for Intelligent Transportation Systems (MT ITS)
Year: 2015

ITS comprises any information and communication technologies applied to transport infrastructures for improving the performance of traffic management and warning systems, productivity and efficiency of ITS services. Benefits of ITS can be further enhanced if ITS entities continuously communicate with each other and exchange relevant information using Cooperative ITS (C ITS) techniques. C ITS gives scope for V2X communication technologies like Vehicle to Vehicle (V2V) Vehicle to Roadside (V2R) and Vehicle to Infrastructure (V2I) schemes. The current C ITS protocol stack relies on heterogeneous wireless access networks, the communication diversity covers Wi Fi, DSRC, CALM, 3G, 4G/LTE/LTE A, and Satellite among others. This fact demands the design and implementation of context aware, resource efficient, scalable, and optimized Layer 3 mobility management mechanisms integrated into the C ITS standards. To provide the base infrastructure for such mechanisms, here we introduce a dynamic network discovery and selection framework relying on the tools of Local Dynamic Map (LDM) and Cooperative Awareness Message (CAM) A proof of concept implementation that demonstrates the feasibility of our approach is also presented and evaluated.
Direct Fabrication of IC Sacrificial Patterns via Rapid Prototyping Approaches
Venue: Int. J. Autom. Technol.
Year: 2012

Patterns made from conventional wax materials in the Investment Casting (IC) process can easily be distorted, damaged, or broken in transportation or routine handling or due to exposure to heat. Alternatively, the strength and toughness of most Rapid Prototyping (RP) materials virtually eliminates this drawback due to their resistance to heat, humidity, and post curing. The current study is conducted to investigate the feasibility of using RP processes such as FDM and MJM to fabricate IC patterns from Acrylonitrile Butadine Styrene (ABS) and acrylate based materials respectively to be used directly in IC process. Evaluation of the effects of different internal pattern designs of the RP parts are conducted based on the thermal analysis approach and burnout properties of the RP patterns. Ceramic shell molds are fabricated on both RP patterns and subsequently placed in an oven which is gradually heated to 1000 degC. The decomposition temperature and the residual ash of the RP pattern materials is determined and analyzed. Results show that the acrylate pattern ofMJMdecomposes rapidly compared to the ABS pattern from the FDM process. It is also observed that quasi and square hollow internal structures show better collapsibility or burnout properties, with no cracks, compared to cross pattern and cross hatch designs.
ASSESSMENT OF NEONATAL OUTCOME OF OPERATIVE VAGINAL DELIVERY AND ITS DETERMINANTS AT DILLA UNIVERSITY REFERRAL HOSPITAL, SOUTH ETHIOPIA
Year: 2019

Assisting laboring women to deliver vaginally using specialized instruments is a practice that dates back several centuries. Forceps and vacuum are the most popular of the operative vaginal procedures used in medical practice. Both are associated with increased risk of neonatal morbidity when compared to normal spontaneous vaginal delivery.  This study was aimed to assess neonatal outcome of operative vaginal delivery and its determinants.  Hospital based cross sectional retrospective study of women delivered between September 2013 and August 2015 in Dilla University Referral Hospital was conducted. All records of women delivered within the specified period of time was used as a total sample size. Data was entered into SPSS version 20 for analysis. Descriptive, bivariate multivariate logistic regression was done to assess factors associated with the neonatal outcome.  Data was collected from 216 women delivered by operative vaginal delivery of which 133 (61.6% were delivered by vacuum, 76 (35.2% were delivered by forceps and 7 (3.2% by sequential use. Significant number of neonates 91(42.1% delivered by operative vaginal delivery ended up with poor APGAR score. Birth weight of the neonate [AOR: 3.0 8, (CI: 1.16 8.20 and ind ication for operative vaginal d elivery [AOR: 2.56 (CI: 1.22, 5.38) were found to increase the risk of poor neonatal outcome.  Neonatal outcome with respect to APGAR score was significantly poor among operative vaginal deliveries in this study. Neonates with lower birth weight and operation done with the indication of fetal distress resulted in higher risk of poor outcome.  APGAR Score; Operative vaginal delivery; Dilla University Referral Hospital
Second order multi object filtering with target interaction using determinantal point processes
Year: 2019

The Probability Hypothesis Density (PHD) filter, which is used for multi target tracking based on sensor measurements, relies on the propagation of the first order moment, or intensity function, of a point process. This algorithm assumes that targets behave independently, an hypothesis which may not hold in practice due to potential target interactions. In this paper, we construct a second order PHD filter based on Determinantal Point Processes (DPPs) which are able to model repulsion between targets. Such processes are characterized by their first and second order moments, which allows the algorithm to propagate variance and covariance information in addition to first order target count estimates. Our approach relies on posterior moment formulas for the estimation of a general hidden point process after a thinning operation and a superposition with a Poisson Point Process (PPP) and on suitable approximation formulas in the determinantal point process setting. The repulsive properties of determinantal point processes apply to the modeling of negative correlation between distinct measurement domains. Monte Carlo simulations with correlation estimates are provided.
Environmentally relevant concentrations of titanium dioxide nanoparticles pose negligible risk to marine microbes+
Venue: Environmental science. Nano
Year: 2021

Nano sized titanium dioxide (nTiO2) represents the highest produced nanomaterial by mass worldwide and, due to its prevalent industrial and commercial use, it inevitably reaches the natural environment. Previous work has revealed a negative impact of nTiO2 upon marine phytoplankton growth, however, studies are typically carried out at concentrations far exceeding those measured and predicted to occur in the environment currently. Here, a series of experiments were carried out to assess the effects of both research grade nTiO2 and nTiO2 extracted from consumer products upon the marine dominant cyanobacterium, Prochlorococcus, and natural marine communities at environmentally relevant and supra environmental concentrations (i.e. 1 mg L 1 to 100 mg L 1) Cell declines observed in Prochlorococcus cultures were associated with the extensive aggregation behaviour of nTiO2 in saline media and the subsequent entrapment of microbial cells. Hence, higher concentrations of nTiO2 particles exerted a stronger decline of cyanobacterial populations. However, within natural oligotrophic seawater, cultures were able to recover over time as the nanoparticles aggregated out of solution after 72 h. Subsequent shotgun proteomic analysis of Prochlorococcus cultures exposed to environmentally relevant concentrations confirmed minimal molecular features of toxicity, suggesting that direct physical effects are responsible for short term microbial population decline. In an additional experiment, the diversity and structure of natural marine microbial communities showed negligible variations when exposed to environmentally relevant nTiO2 concentrations (i.e. 25 mg L 1) As such, the environmental risk of nTiO2 towards marine microbial species appears low, however the potential for adverse effects in hotspots of contamination exists. In future, research must be extended to consider any effect of other components of nano enabled product formulations upon nanomaterial fate and impact within the natural environment.