nils-herrmann/clean_scirepeval huggingface dataset:
Lost in Translation: Physiological Roles of Stored mRNAs in Seed Germination
Venue: Plants
Year: 2020

Seeds characteristics such as germination ability, dormancy, and storability/longevity are important traits in agriculture, and various genes have been identified that are involved in its regulation at the transcriptional and post transcriptional level. A particularity of mature dry seeds is a special mechanism that allows them to accumulate more than 10,000 mRNAs during seed maturation and use them as templates to synthesize proteins during germination. Some of these stored mRNAs are also referred to as long lived mRNAs because they remain translatable even after seeds have been exposed to long term stressful conditions. Mature seeds can germinate even in the presence of transcriptional inhibitors, and this ability is acquired in mid seed development. The type of mRNA that accumulates in seeds is affected by the plant hormone abscisic acid and environmental factors, and most of them accumulate in seeds in the form of monosomes. Release of seed dormancy during after ripening involves the selective oxidation of stored mRNAs and this prevents translation of proteins that function in the suppression of germination after imbibition. Non selective oxidation and degradation of stored mRNAs occurs during long term storage of seeds so that the quality of stored RNAs is linked to the degree of seed deterioration. After seed imbibition, a population of stored mRNAs are selectively loaded into polysomes and the mRNAs, involved in processes such as redox, glycolysis, and protein synthesis, are actively translated for germination.
Credit card literacy and financial well being of college students
Venue: International Journal of Bank Marketing
Year: 2019

By testing a moderated mediation model, the purpose of this paper is to examine the mediating role of credit card self efficacy in the relationship between credit card literacy and financial well being. The authors further examine if credit card number moderates this effect.  Data for the study were collected from 427 college students. The PROCESS macros in IBM SPSS Statistics 23 was used to assess the hypothesized relationships.  Credit card literacy positively influences financial well being through self efficacy. However, this effect is stronger when college students own fewer credit cards.  Banks and credit card issuers, policymakers and colleges and universities should place a greater emphasis on credit card literacy programs that enhance students' general understanding of credit card terms and conditions and confidence in their ability to effectively use and manage their credit cards.  To our knowledge, this is the first study to examine the relationship between credit card literacy, self efficacy and financial well being.
Improving the User Acceptability of Advanced Driver Assistance Systems Based on Different Driving Styles: A Case Study of Lane Change Warning Systems
Venue: IEEE Transactions on Intelligent Transportation Systems
Year: 2020

The low user acceptability of advanced driver assistance systems (ADASs) is one of the fundamental problems limiting their wider adoption. One of the key factors affecting the frequency of warning signals is the standard warning thresholds set in ADASs, which may not be compatible with all drivers owing to various driver characteristics affecting their cognition of risk, such as comfort, skill, and experience. The present study focuses on the lane change warning (LCW) system to evaluate driving styles according to the perception of lane change risk, and determine appropriate warning thresholds corresponding to the different driving styles. A theoretical lane change warning model is established to calculate the deceleration required for the rear approaching vehicle in the target lane. The results of risk assessment experiments conducted on an actual expressway using 15 proficient drivers are employed to evaluate the risk cognitions of the participants, where the participants are divided into four different driving styles according to their adaptive warning thresholds, which are denoted as very low threshold, low threshold, medium threshold, and high threshold driving styles. Signal detection theory is then employed to determine lane change warning thresholds appropriate to the different driving styles. Our results clearly demonstrate the disparate perceptions of lane change risk for the different drivers. Therefore, the LCW system should adopt different warning thresholds for different drivers according to their driving style. The findings provide evidence supporting the exploitation of driving styles for adopting different warning thresholds in the LCW system to enhance its user acceptability.
Patterns of vowel nasality in Brazilian Portuguese
Venue: The Journal of the Acoustical Society of America
Year: 2019

This study aims to establish differences in patterns of acoustic nasality between nasal and nasalized vowels in Brazilian Portuguese (BP) The difference in how nasality is implemented in the acoustic signal is hypothesized to reflect the different phonological status of these two vowel categories. Acoustic nasality is the difference between the amplitude of the first formant (A1) and the amplitude of a harmonic in the low region of the vowel spectrum (P0) (Chen, 1997) The smaller the difference between these peaks, the more nasal a vowel is. A1 P0 measurements were taken at different time points from recordings of oral, nasal, and nasalized vowels in BP of five qualities. Results show that nasal and nasalized vowels were similar in all qualities. However, the way nasality is implemented over time between the vowel categories are different, with acoustic nasality in nasal vowels increasing more rapidly than in the nasalized counterparts. Although the patterns of nasality found are not consistent with the expected nasal profile difference (Cohn, 1990) the difference in acoustic nasality between nasal and nasalized vowels is consistent enough to consider it result of how the feature [nasal] is implemented in the language due to its variable phonological status in BP. This study aims to establish differences in patterns of acoustic nasality between nasal and nasalized vowels in Brazilian Portuguese (BP) The difference in how nasality is implemented in the acoustic signal is hypothesized to reflect the different phonological status of these two vowel categories. Acoustic nasality is the difference between the amplitude of the first formant (A1) and the amplitude of a harmonic in the low region of the vowel spectrum (P0) (Chen, 1997) The smaller the difference between these peaks, the more nasal a vowel is. A1 P0 measurements were taken at different time points from recordings of oral, nasal, and nasalized vowels in BP of five qualities. Results show that nasal and nasalized vowels were similar in all qualities. However, the way nasality is implemented over time between the vowel categories are different, with acoustic nasality in nasal vowels increasing more rapidly than in the nasalized counterparts. Although the patterns of nasality found are not consistent with the.
Breeding vis a vis Genomics of Tropical Tree Crops
Year: 2016

Tree breeding is thought to have a pragmatic future. In the backdrop of climate change and exponential increase in population, developing plants, especially trees, resilient to unpredictable environmental conditions is more challenging than ever before. The benefits of tree species, especially fruit trees are multifold for the sustenance of humankind. Tree genotypes are selected and breeding values estimated for superior characteristics following long term and costly field based progeny trials, where provenance trials, clone trials and full sib progeny evaluations are the backbone of such experiments. Of late, efforts are on to manipulate functions at the level of gene and genome of tree species. The shift from traditional Sanger sequencing to massive parallel sequencing of millions of short DNA pieces simultaneously through Next Generation Sequencing (NGS) is a major breakthrough in the last decade. Among the DNA markers, microsatellites (SSRs Simple Sequence Repeats of 2 6 bases) which tend to be highly polymorphic, locus specific and co dominant are preferred in Marker Assisted Selection (MAS) and genetic linkage map construction. Reverse genetics, gene silencing through RNA interference (RNAi) Transcript profiling (DNA microarrays) Serial Analysis of Gene Expression (SAGE) and Massively Parallel Signature Sequencing (MPSS) are some of the latest techniques to learn more about functional genomics. The future of tree genomics is bright, but only serious investigations can help to accelerate the systems breeding that integrates information on gene function ensuring superior genotypes.
GridNet: Image Agnostic Conditional Anomaly Detection for Indoor Surveillance
Venue: IEEE Robotics and Automation Letters
Year: 2021

We present a deep autoencoder based anomaly detection method (GridNet) for indoor surveillance. Unlike similar studies, GridNet is image agnostic by taking a specific representation of a scene as inputs instead of the raw image itself. Its input is grid representations of scene images, which indicate spatial layouts of objects in a scene. This approach allows us to isolate the anomaly detection problem from any vision related issues, such as illumination variations. In addition to grid representations, GridNet takes a location vector of a scene as input to learn the normalities of each scene conditioned on its location. We also propose a novel loss function that increases the model's reconstruction capability for grid representations. It enables the network to increase its precision and recall throughout the reconstruction. In our experiments, we compare our method with the existing studies on simulated and real world data. The experimental results show the superiority of our method compared to the baseline methods. The code, data, and simulation environments will be available at https:/bozcani.github.io/gridnet.
XtarNet: Learning to Extract Task Adaptive Representation for Incremental Few Shot Learning
Venue: ICML
Year: 2020

Learning novel concepts while preserving prior knowledge is a long standing challenge in machine learning. The challenge gets greater when a novel task is given with only a few labeled examples, a problem known as incremental few shot learning. We propose XtarNet, which learns to extract task adaptive representation (TAR) for facilitating incremental few shot learning. The method utilizes a backbone network pretrained on a set of base categories while also employing additional modules that are meta trained across episodes. Given a new task, the novel feature extracted from the meta trained modules is mixed with the base feature obtained from the pretrained model. The process of combining two different features provides TAR and is also controlled by meta trained modules. The TAR contains effective information for classifying both novel and base categories. The base and novel classifiers quickly adapt to a given task by utilizing the TAR. Experiments on standard image datasets indicate that XtarNet achieves state of the art incremental few shot learning performance. The concept of TAR can also be used in conjunction with existing incremental few shot learning methods; extensive simulation results in fact show that applying TAR enhances the known methods significantly.
Human Robot Mutual Adaptation in Shared Autonomy
Venue: 2017 12th ACM/IEEE International Conference on Human Robot Interaction (HRI
Year: 2017

Shared autonomy integrates user input with robot autonomy in order to control a robot and help the user to complete a task. Our work aims to improve the performance of such a human robot team: the robot tries to guide the human towards an effective strategy, sometimes against the human's own preference, while still retaining his trust. We achieve this through a principled human robot mutual adaptation formalism. We integrate a bounded memory adaptation model of the human into a partially observable stochastic decision model, which enables the robot to adapt to an adaptable human. When the human is adaptable, the robot guides the human towards a good strategy, maybe unknown to the human in advance. When the human is stubborn and not adaptable, the robot complies with the human's preference in order to retain their trust. In the shared autonomy setting, unlike many other common human robot collaboration settings, only the robot actions can change the physical state of the world, and the human and robot goals are not fully observable. We address these challenges and show in a human subject experiment that the proposed mutual adaptation formalism improves human robot team performance, while retaining a high level of user trust in the robot, compared to the common approach of having the robot strictly following participants' preference.
A Regularized Model to Trade off between Accuracy and Diversity in a News Recommender System
Venue: 2020 IEEE International Conference on Big Data (Big Data)
Year: 2020

News recommender systems are usually designed to provide accurate and personalized recommendations to the readers. The diversity of the recommended results has received much less attention in this field. When it is considered, the current state of the art models often apply the re ranking mechanisms to promote the diversified results to the individual users. In this work, we propose a latent factor model to achieve the requisite level of accuracy while maintaining a reasonable level of diversity in a news recommender system. The existing latent factor methods mostly rely on Tikhonov regularization to improve the generality of the learnt models. These methods tend to focus mainly on accuracy measures, i.e. generating recommendations highly aligned with a user's past preference, which may cause a decrease in the diversity of information to which news readers are exposed. In our work, we make effective use of elastic net regression to regularize the model for both the accuracy and the diversity in a single optimization framework. We demonstrate the effectiveness of our model over the state of the art methods by conducting extensive experiments on a real world news dataset.
Social Support on the Adherence to Treatment of Tuberculosis in Cilacap, Indonesia
Year: 2016

Country Indonesia liquid high burden countries in the case of Tuberculosis resistant adenocarcinoma. One of the causes of MDR TB was OAT drink irregularly. Many of the changes that occur in people with tuberculosis physical, psychological and social influence on irregularity OAT drink. The purpose of this research is to know the contribution of the social support against tuberculosis treatment regularity in Cilacap Regency. This was a quantitative study with observational analytic design, carried out in twelve clinics and hospitals, inCilacap. A total of 128 samples were consisted of 42 groups and control group 86. The dependent variables was the regularity of the medication, and the independent variable were the intention, attitude, distance, self efficacy, social support, education and knowledge. The Data collected using the questionnaire and medical record data and analyzed usingpath analysis. There is a direct relationship between education with knowledge, education and knowledge, as well as attitudes toward intentions with the regularity of medical treatment. There is an indirect relationship between posture, distance, social support and self efficacy with the OAT drink regularity through intention. A positive relationship between education with knowledge (b 0.17; 95%CI 0.02 to 0.13; p 0.023) A positive relationship between education with attitude (b 1.23; 95% CI 0.29 to 2.16; p 0.01) Positive relationship knowledge with attitude (b 0.56; 95% CI 1.47 to 0.35; p 0.228) The relationship of positive attitude with the intention (b 0.99; CI 95% 0.05 to 1.94; p 0.039) Negative relationship of distance with the intention (b 0.59; 95% CI 1.49 to 0.31; p 0.202) Positive relationships support social (social support) and intention (b 0.5; 95% CI 0.22 to 1.89; p 0123) A positive relationship with self efficacy of intention (b 1.04;95% CI 0.16 to 2.26; p 0.089) A positive relationship with the intention to ordertreatment of TB (b 2.1; CI 95% 1.24 to 2.97; p 0.001).Conclusion: Education, knowledge, attitude, social support self efficacy related to improve the regularity of treatment of TB through the intention to treat.Attitude, Distance, Social Support, Self Efficacy, Consistency of Treatment of TBCorrespondence: Lina Puspitasari. Midwifery Academic Graha Mandiri Cilacap.  Lina_Puspitasari@yahoo.co.idJournal of Epidemiology and Public Health, 2016, 1(1) 58 65https:/doi.org/10.26911/jepublichealth.2016.01.01.07
PRODUCTION OF EDIBLE VACCINES FOR ORAL IMMUNIZATION IN TRANSGENIC PLAIITS CURRENT AND FUTURE
Year: 2017

This review highlights the recent advances made in the use oftransgenic plants as biofactories for the production of edible vaccines and its long term potentid with demonstrated utility to the medical community. The use oftransgenic plants to express orally immunogenic protein antigen is an ernerging strategy for vaccine production. Foods under study include legumes, potatoes, banan4 tobacco, rice, wheat soybean and com. This concept has particular suitability for developing countries. Although, the first human clinical trials for edible vaccine have been perforn.red recently, many challenges including maximization of expressign levels, stabilization during post hanest storage, remain to be met. Public acceptance of edible"vaccines is highly variable on the globil scale, and similar issues of social acceptance will influence the commercial feasibility ofa plant made vaccine. Edible vaccines can be improved for their oral immunogenecity by the use of appropriate adjuvant which could be used either as a fusion to the candidate gene or as an independent gene. Concern about immune tolerance and allergy to edible vaccines has been expressed and needs to be addressed suitably. The production ofantigenic proteins in genetically engineered plants provide an inexpensive source of edible vaccines, in tum, increases the vatue of plants as novel sources of medicinal drugs. Therefore, one would perhaps expect edible vaccines from transgenic plants to be safer than their counterparts derived from animal based sources, which have the potential for contamination with human pathogens.
Consensus Based Secondary Frequency and Voltage Droop Control of Virtual Synchronous Generators for Isolated AC Micro Grids
Venue: IEEE Journal on Emerging and Selected Topics in Circuits and Systems
Year: 2015

As the penetration of renewable energy sources is increasing in the AC micro grid, the stability of the closed loop system has raised a major concern since conventional distributed interface converters (DICs) used in the AC micro grid do not have a rotating mass, and hence low inertia. High penetration of DIC based micro grid may result in poor frequency and voltage response during large disturbance. In order to overcome this difficulty, the virtual synchronous generator (VSGs) was proposed recently in which the DIC mimics conventional synchronous generators (SGs) by designing proper parameters of the SG into each local droop control mechanism of the DIC. Meanwhile, due to the recent advances of distributed control, the concept of consensus based control can be applied to study this droop control problem of VSGs. One important feature of this consensus based control is that it can be implemented on each local DIC with communications among their neighboring DICs. In contrast to most existing secondary control schemes, no central controller is required. Under this framework, if DICs are redesigned as VSGs, the frequency and voltage of each DIC can be restored to their pre specified values obtained from the steady state analysis. In addition, the proper real and reactive power sharing still can be achieved according to the nominal rating of each DIC. The stability of the closed loop system is ensured by the transient energy function under certain mild conditions. Numerical experiments of a 14 bus/6 DIC micro grid system on real time simulators are performed to validate the effectiveness of the proposed control mechanism.
On Interactions of Quaternionic and Complex Structures of Linear Spaces
Venue: Advances in Applied Clifford Algebras
Year: 2021

On various occasions, when working with quaternionic linear spaces, there is a need to restrict them to their complex linear structure, then it becomes essential to understand whether the pre existing internal product or norm in the quaternionic space will continue to be compatible with the complex structure of the new space obtained. There are other situations in which these types of questions arise, for example, if a linear space is originally complex but it turns out that it also admits the quaternionic structure. The objective of this work is to present the different options to change the linearities of some linear spaces and to analyze what happens with the pre existing algebraic objects: to understand if they still work or if they induce some others that will be compatible with the new linear structure.
Improving Cohesion Measurement for Object Oriented Systems in Java
Year: 2015

High cohesion in classes is an essential property of Object Oriented (OO) software as it positively impacts understanding, reuse, and maintenance. Existing approaches to measure cohesion are largely based on using the structural information from the source code, such as attribute references in methods. The measure, named the Conceptual Cohesion of Classes (C3) for the cohesion of classes is based on the analysis of the unstructured information embedded in the source code, such as comments and identifiers. To retrieve the unstructured information from the source code Latent Semantic Indexing is used .C3, is inspired by the mechanisms used to measure textual coherence in cognitive psychology and computational linguistics. This measurement is used to construct models that predict software faults. This paper aims at developing a tool named "C CUBE "to compute the conceptual cohesion of OO classes.
Strategi Pencapaian Target RPJMN 2015 2019 pada PDAM Perpipaan Tirta Moedal
Year: 2018

National Medium Term Development Plan target's (RPJMN) 2015 2019 has mandated the 100 0 100 program, which is 100% safe access to drinking water, slums free, and 100% access to proper sanitation by the end of 2019. It should also be aligned with local and central government programs.The purpose of this research is to determine the problems experienced by PDAM in their effort to achieve target and what ideal strategies taken in order to achieve the target of RPJMN 2015 2019. This research is a quantitative research. This research uses SWOT analysis. The population in this research are the customer of PDAM Tirta Moedal Semarang in 2018. The results showed that in Matrix Grand Strategy can be seen that PDAM Tirta Moedal Semarang was in a position to support a competitive strategy. The diagram shows that is in quadrant II, the company is in a position to support the competitive strategy is to maximize the strength of the company to minimize threats.
Augmented attack tree modeling of SQL injection attacks
Venue: 2010 2nd IEEE International Conference on Information Management and Engineering
Year: 2010

The SQL injection attacks (SQLIAs) vulnerability is extremely widespread and poses a serious security threat to web applications with built in access to databases. The SQLIA adversary intelligently exploits the SQL statement parsing operation by web servers via specially constructed SQL statements that subtly lead to non explicit executions or modifications of corresponding database tables. In this paper, we present a formal and methodical way of modeling SQLIAs by way of augmented attack trees. This modeling explicitly captures the particular subtle incidents triggered by SQLIA adversaries and corresponding state transitions. To the best of our knowledge, this is the first known attack tree modelling of SQL injection attacks.