nils-herrmann/clean_scirepeval huggingface dataset:
Same Day Delivery with Drone Resupply
Venue: Transp. Sci.
Year: 2020

Unmanned aerial vehicles, commonly referred to as drones have recently seen an increased level of interest as their potential use in same day home delivery has been promoted and advocated by large retailers and courier delivery companies. We introduce a novel way to exploit drones in same day home delivery settings: drone resupply. We consider a home delivery system in which delivery trucks are regularly resupplied by drones. Resupply can take place whenever a delivery truck is stationary and a drone can land on the truck's roof. We introduce the vehicle routing problem with drone resupply to capture and investigate this setting. We develop different algorithms and compare their performance. Finally, we quantify the potential benefits of drone resupply and generate valuable insights for advancing this concept.
Flash profile as a rapid descriptive analysis in sensory characterization of traditional dry fermented sausages
Year: 2020

Traditionally, sensory analysis techniques are separated on those performed with trained sensory panellists (analytical procedures) and those with consumers (hedonic tests) Nowadays, dividing line between these two approaches tends to blur. Following industrial needs for faster and more cost effective methods of descriptive sensory profiling, several methods have been developed as alternatives to classical descriptive analysis. This study aimed to evaluate the samples, three of commercial and three of traditionally produced dry fermented sausages using the Flash Profile (FP) as a rapid descriptive analysis method, in which a panel of 10 sensory experts chose and used his/her own words to evaluate the sausage samples while comparing several attributes. Total of 24 sensory attributes were chosen by the panel, and each assessor used from 9 to 16 sensory descriptors. The obtained results for the samples ranks were collected within matrices, and were analysed by using a multivariate statistical technique General Procrustes Analysis (GPA) The first two dimensions explained about 76.49% of data variability (Dimension 1: 57.23% and Dimension 2: 19.26% A good discrimination between traditional (B, C and D) and commercial (A, E and F) dry fermented sausages was observed. The obtained results of Flash profile proved to be a quick substitute method and also a good help as an initial comprehension of the most important attributes of a product's set.
PQ Controller for Single Phase Bridgeless Boost PFC Rectifiers Tek Fazli Koprusuz Yukseltici PFC Dogrultucular Icin PQ Kontroller
Year: 2019

Yasemin Onal orcid.org/0000 0003 0173 0948 harmonics and reactive power in the DG systems. The existence of harmonics in the DG systems ends up with some impacts, including increased heat losses in transformers, electrical motors, and power lines; low power factor; insufficient usage of distribution cable and plant. Conventional passive filters PF have been used in order to meet the standards such as IEEE 519 and IEC 555, to compensate DG systems harmonics, and to develop power quality, but are often not ideal due to increased cost, fixed compensation, large size, and resonance problems (Akagi et al. 2007)
Head on collision between capillary gravity solitary waves
Year: 2020

The present study deals with the head on collision process between capillary gravity solitary waves in a finite channel. The present mathematical modeling is based on Nwogu's Boussinesq model. This model is suitable for both shallow and deep water waves. We have considered the surface tension effects. To examine the asymptotic behavior, we employed the Poincare Lighthill Kuo method. The resulting series solutions are given up to third order approximation. The physical features are discussed for wave speed, head on collision profile, maximum run up, distortion profile, the velocity at the bottom, and phase shift profile, etc. A comparison is also given as a particular case in our study. According to the results, it is noticed that the free parameter and the surface tension tend to decline the solitary wave profile significantly. However, the maximum run up amplitude was affected in great measure due to the surface tension and the free parameter.
Disruptive innovation, business models, and encroachment strategies: Buyer's perspective on electric and hybrid vehicle technology
Year: 2021

According to disruptive innovation theory, customers are swayed by new market entrants through low end encroachment strategies and/or new market disruption, but these predictions do not account for the rising interest in product categories such as electric vehicles in emerging markets. To bridge this research gap, we draw comparisons between disruptive and incremental innovation to account for electric and hybrid vehicles, respectively. We explore the misalignment between technological growth and customer satisfaction by comparing the electric vehicle business model with the hybrid vehicle business model based on three parameters: channels, value propositions, and customer relationships. Primary empirical data are collected from 307 survey participants. Structural equation modeling is then employed to investigate the similarities and differences between electric vehicles based on their disruptive innovation and hybrid vehicles based on their incremental innovation. We find that electric vehicles' unique focus on channels leads to a positive influence on their business model and customer satisfaction, while focusing on value propositions leads to positive results for hybrid vehicles. Finally, we discuss the significance of the results considering electric vehicles' high end encroachment strategy within the luxury segment and contrast it with the relatively low end encroachment strategy adopted by sellers of hybrid vehicles.
A LOGICAL AND ONTOLOGICAL FRAMEWORK FOR KNOWLEDGE DISCOVERY ON GENE REGULATORY NETWORKS. CASE STUDY: BILE ACID AND XENOBIOTIC SYSTEM (BAXS)
Year: 2020

This work aims to develop a novel computational framework for automatic or semi automatic modeling of gene regulatory networks, in which possible connections between genetic structural knowledge and other forms of knowledge available about GRNs can be explored. To perform the modeling of such networks, we consult computing services available through portals on the Internet. Some of these portals are: GeneOntology, PDB, HGNC, PathwayCommons, UniProt, PubMed, Mesh, among others. The mentioned sites provide services that make possible automatic access and can, therefore, be used to organize knowledge bases that integrate their resources. Our team has developed a prototype system that allows such an integration and the analysis of information so obtained in different modalities. In our case, the knowledge automatically gathered and modeled, expresses the identity of the objects on a network and their interactions, as well as their biological functions, biological processes and cellular components. In this sense, our proposal aims at the semantic modeling of GRNs by layers, each layer representing a standard level of description. It starts with a basic level for the model of the transcription regulatory region and goes up to a level for extra cellular objects. Our platform consolidates all the information obtained from the different sources mentioned into one integrated representation. This representation can then be used for the discovery of biological signaling pathways and the discovery of regulatory sub networks. At the moment, we are running processes to model and analyze the Bile Acid and Xenobiotic System (BAXS) and some results are already available. For instance, given a set of ligands, a couple of proteins and their related DNA sequences, it is possible: a) to discover a GRN describing how the given proteins regulate each other; and b) to produce sets of user validated pathways for the proteins under consideration. Details about our system, named biopatternsg (biopatterns searching) can be viewed at: https:/github.com/biopatternsg/biopatternsg.
Observer variation for radiography, computed tomography, and magnetic resonance imaging of occult hip fractures
Venue: Acta radiologica
Year: 2011

Conventional radiography is insufficient for diagnosis in a small but not unimportant number of hip fractures, and secondary imaging with computed tomography (CT) or magnetic resonance imaging (MRI) is warranted. There are no convincing observer variation studies performed for conventional radiography or CT in occult fractures, and no large materials for MRI.  To assess observer variation in radiography, CT and MRI of suspected occult, non displaced hip fractures, and to evaluate to what extent observer experience or patient age may influence observer performance.  A total of 375 patients after hip trauma where radiography was followed by CT or MRI to evaluate a suspected occult hip fracture were collected retrospectively from two imaging centers. After scoring by three observers with varying degrees of radiologic experience, observer variation was assessed by using linear weighted kappa statistics.  For radiography, agreements between the three observers were moderate to substantial for intracapsular fractures, with kappa values in the ranges of 0.56 0.66. Kappa values were substantial for extracapsular fractures, in the ranges of 0.69 0.72. With increasing professional experience, fewer fractures were classified as equivocal at radiography. For CT and MRI, observer agreements were similar and almost perfect, with kappa values in the ranges of 0.85 0.97 and 0.93 0.97.  There were almost perfect observer agreements for CT and MRI in diagnosing non displaced, occult hip fractures. Observer agreements for radiography were moderate to substantial, and observer experience influenced agreement only at radiography.
A Model of Environmental Education Competency Development for Teachers in Secondary Schools
Year: 2019

This research was to create a model of environmental education (EE) competency development for teachers in secondary schools, which has been conducted by the multi research method. The data were collected by questionnaire for the operational teachers in eco schools, and structured interview for the experts from teacher advisors, and the mentor teachers of the eco school project, which analyzed by percentage, mean score, standard deviation, weight mean score, and index of congruence. The research findings revealed that most informants were having intermediate level of EE competency in 6 parts: environmental knowledge, fundamental understanding on EE, responsibility on EE teacher actualization, EE planning and operating, promoting of EE learning, and EE evaluation. The EE innovation was created to develop the teachers from various subjects to perform the integrated learning for the student's environmental actualization before conserving or solving the community environmental problems. This systematically consisted of 5 steps including: analyzing the environmental policy covering national, educational area, and school policies; studying the community environmental problem; designing the environmental learning project; identifying the learning standard; and performing the integrated lesson plan. The innovation efficiency was confirmed both internal and external skills by authentic assessment.
Comparison of serum concentrations of symmetric dimethylarginine and creatinine as kidney function biomarkers in healthy geriatric cats fed reduced protein foods enriched with fish oil, L carnitine, and medium chain triglycerides.
Venue: Veterinary journal
Year: 2014

The purpose of this study was to determine whether feeding cats reduced protein and phosphorus foods with added fish oil, L carnitine, and medium chain triglycerides (MCT) altered serum biomarkers of renal function. Thirty two healthy cats, mean age 14.0 (8.3 19.6) years, were fed control food or one of two experimental foods for 6 months. All foods had similar concentrations of moisture, protein, and fat (approximately 8.0% 26.5% and 20.0% respectively) Both experimental foods contained added fish oil (1.5% and L carnitine (500 mg/kg) Experimental food 2 also contained increased MCT (10.5% from coconut oil) 1.5% added corn oil, and reduced animal fat. Glomerular filtration rate (GFR) serum biochemistries, renal function biomarkers including serum creatinine (sCr) and symmetrical dimethylarginine (SDMA) and plasma metabolomic profiles were measured at baseline, and at 1.5, 3, and 6 months. Body composition was determined by dual energy X ray absorptiometry. Although both experimental foods altered plasma fatty acids, carnitine and related metabolites, and lysophospholipid concentrations, there were no changes in renal function biomarkers. There was, however, a benefit in using SDMA versus sCr to assess renal function in older cats with less total lean mass. Compared with cats <12 years, those >15 years had lower total lean mass (P 0.01) lower GFR (P 0.04) and lower sCr concentrations (P 0.01) However, SDMA concentrations (P 0.01) were higher in older cats. This study shows that in cats, serum SDMA concentration is more highly correlated with GFR than sCr concentration, and, unlike sCr, which declines with age because of muscle wasting, SDMA increases as GFR declines with age.
PATH 06. IMAGE BASED MACHINE LEARNING CLASSIFIER FOR PEDIATRIC POSTERIOR FOSSA TUMOR HISTOPATHOLOGY
Venue: Neuro Oncology
Year: 2020

Pediatric posterior fossa (PF) tumors can include astrocytomas, ependymomas, and medulloblastomas, all of which demonstrate unique histopathology. Whole slide image analyses can be time consuming and difficult. Therefore, we used machine learning to create a screenshot based histopathology image classifier that can distinguish between types of pediatric PF tumors.  We took 179 histopathology slides from Stanford University, dated from 2008 2019: 87 astrocytomas, 42 ependymomas, and 50 medulloblastomas, per pathology report. Each slide was viewed under a microscope at 20x. Then, a screenshot was taken of the region of interest representative of principal slide pathology, confirmed by a trained neuropathologist. These screenshots were used to train Resnet 18 models pre trained on the ImageNet dataset and modified to predict three classes. Various models with different hyperparameters were trained using a random hyperparameter search method. Trained models were evaluated using 5 fold cross validation, assigning 20% of the dataset for validation with each evaluation. Qualitative analysis of model performance was assessed by creating Class Activation Map (CAM) representations of image predictions.  The top performing Resnet 18 model achieved a cross validation F1 of 0.967 on categorizing screenshots of tumor pathology into three types. Qualitative analysis using CAMs indicated the model was able to identify salient distinguishing features of each tumor type.  We present a PF lesion classifier capable of distinguishing between astrocytomas, ependymomas, and medulloblastomas based on a histopathology screenshot. Given its ease of use, this tool has potential as an educational tool in an academic setting.
An update on the genetics, clinical presentation, and pathomechanisms of human riboflavin transporter deficiency
Venue: Journal of inherited metabolic disease
Year: 2019

Riboflavin transporter deficiency (RTD) is a rare neurological condition that encompasses the Brown Vialetto Van Laere and Fazio Londe syndromes since the discovery of pathogenic mutations in the SLC52A2 and SLC52A3 genes that encode human riboflavin transporters RFVT2 and RFVT3. Patients present with a deteriorating progression of peripheral and cranial neuropathy that causes muscle weakness, vision loss, deafness, sensory ataxia, and respiratory compromise which when left untreated can be fatal. Considerable progress in the clinical and genetic diagnosis of RTDs has been made in recent years and has permitted the successful lifesaving treatment of many patients with high dose riboflavin supplementation. In this review, we first outline the importance of riboflavin and its efficient transmembrane transport in human physiology. Reports on 109 patients with a genetically confirmed diagnosis of RTD are then summarized in order to highlight commonly presenting clinical features and possible differences between patients with pathogenic SLC52A2 (RTD2) or SLC52A3 (RTD3) mutations. Finally, we focus attention on recent work with different models of RTD that have revealed possible pathomechanisms contributing to neurodegeneration in patients.
A critical review on the applications of artificial neural networks in winemaking technology
Venue: Critical reviews in food science and nutrition
Year: 2017

Since their development in 1943, artificial neural networks were extended into applications in many fields. Last twenty years have brought their introduction into winery, where they were applied following four basic purposes: authenticity assurance systems, electronic sensory devices, production optimization methods, and artificial vision in image treatment tools, with successful and promising results. This work reviews the most significant approaches for neural networks in winemaking technologies with the aim of producing a clear and useful review document.
Immigrant or refugee: perceived effects of colonisation of academia by market forces
Year: 2011

Managers and personnel within tertiary institutions colonised by neo liberal ministrations and buffeted by the winds of a 'change culture' formed within the philosophical shifts of the last century can be considered in terms of 'immigrants' or 'refugees' within this new territory. The case story of this article is set in a college of education newly situated within a traditional university culture. Superimposed on that scenario is an ontology shift from academia to a neo liberal business model. The article considers how people, enculturated with an already established socio cultural paradigm where research, collegiality, democracy and the concept of academic freedom predominate, are challenged to reform their epistemologies to fit the definition of the new culture. The article is a theory based, qualitative report of a case study using anthropological parameters and terminology of cultures and culture change to map the impact of the change process on the epistemologies of people involved in claiming the post colonial space.
Investigating the Causes and Negative Effects of English Language Speaking Anxiety: A Case Study among EFL Learners at Kandahar University
Venue: American International Journal of Education and Linguistics Research
Year: 2019

The present study has been conducted to investigate the causes of English language speaking anxiety among EFL learners at Kandahar University. Furthermore, the second goal of the study to investigate the negative effects of speaking anxiety. This study uses a quantitative research approach. Similarly, the questionnaire had two parts the first part had comprised 14 items and the second part 7 items and applied randomly. Besides, the data analyzing was performed in SPSS (version, 24) and bring out the mean and standard division. Finally, the findings revealed those factors which caused EFL learners to feel anxiety during English speaking and numbered as follow: (1) I feel fear of making pronunciation mistakes, (2) I am afraid that my classmates will laugh at me when I speak English. (3) I feel worried during Performing communication orally. In addition, the following factors are the negative effects of anxiety on learners: (1) Anxiety limits my speaking fluency, (2) Anxiety causes me to become under pressure during presentation and (3) Anxiety decreases my oral performance and self confidence.
Memory Augmented Recurrent Neural Networks for Dense Video Captioning
Year: 2020

Dense video captioning is a challenging computer vision task that involves effectively understanding long video sequences. In this work, we address this problem by augmenting recurrent neural network architectures with external memory. We propose a dense captioning model that incorporates external memory augmentation both to encode video and densely caption it. We demonstrate that recurrent video encoder and dense captioner networks augmented with external memory can be used to effectively encode frames based on the content of the entire video, as well as for generating dense captions better than recurrent networks without external memory augmentation. We conduct experiments on the ActivityNet Captions and YouCook II datasets to demonstrate the potential of external memory augmentation.
Overexpression of Desmoglein 2 in a Mouse Model of Gorlin Syndrome Enhances Spontaneous Basal Cell Carcinoma Formation through STAT3 Mediated Gli1 Expression.
Venue: The Journal of investigative dermatology
Year: 2019

Activation of the hedgehog pathway is causative of virtually all sporadic and Gorlin syndrome related basal cell carcinomas (BCCs) with loss of function of Ptc1 being the most common genomic lesion. Sporadic BCCs also overexpress Dsg2, a desmosomal cadherin normally found in the basal layer. Using a mouse model of Gorlin syndrome (Ptc1+/lacZ mice) we found that overexpressing Dsg2 in the basal layer (K14 Dsg2/Ptc1+/lacZ mice) or the superficial epidermis (Inv Dsg2/Ptc1+/lacZ mice) resulted in increased spontaneous BCC formation at 3 and 6 months, respectively. The tumors did not show loss of heterozygosity of Ptc1, despite high levels of Gli1 and phosphorylated Stat3. A panel of sporadic human BCCs showed increased staining of both Dsg2 and phosphorylated Stat3 in all nine samples. Overexpression of Dsg2 in ASZ001 cells, a Ptc1 BCC cell line, induced Stat3 phosphorylation and further increased Gli1 levels, in both an autocrine and paracrine manner. Three different Stat3 inhibitors reduced viability and Gli1 expression in ASZ001 cells but not in HaCaT cells. Conversely, stimulation of Stat3 in ASZ001 cells with IL 6 increased Gli1 expression. Our results indicate that Dsg2 enhances canonical hedgehog signaling downstream of Ptc1 to promote BCC development through the activation of phosphorylated Stat3 and regulation of Gli1 expression.
Empirical Evaluation of Coupling Metrics in Software Fault Prediction
Venue: 2020 17th International Bhurban Conference on Applied Sciences and Technology (IBCAST)
Year: 2020

Software Fault Prediction (SFP) techniques are commonly used to determine the fault proneness of software modules to complement the development and testing process. In SFP, fault prediction is based on software metrics that reflect any aspect of the software, where coupling is one of them. Software coupling is one such metric, which is a measure of the interdependency of software modules. Coupling induces complexity in the coupled module and makes it difficult to comprehend. Eventually, more coupled modules are likely to be faultier. This spurs a need to evaluate the impact of coupling exclusively, on fault proneness. Since, coupling by inheritance is harmless, as it promotes reusability, so coupling through inheritance is not considered. We evaluated seven coupling metrics on 87 different publicly available datasets. After pre processing, selected datasets are split with all possible coupling metrics. Resulting 474 split datasets are used for the experiments. These datasets have only coupling metrics and nominal binary class labels. Model building and validation are done for Support Vector Machine. Results of entropy loss shows that coupling metrics are good predictors of faults in software. Furthermore, {Coupling Between Objects, Design Complexity, Fan in} outperform the rest of the 30 feature set. Finally, coupling metrics are ranked by keeping in view their position achieved and the number of accompanying metrics. This declares Efferent Coupling as the best coupling metric with respect to the other six coupling metrics in 474 datasets. The paper concludes the viability of coupling metrics in software fault prediction. Evaluating the absolute impact of coupling in SFP and then the relative ranking of coupling metrics is the significance of this paper.