nils-herrmann/clean_scirepeval huggingface dataset:
Effect of fiber orientation on Mode I delamination resistance of glass/epoxy laminates incorporated with milled glass fiber fillers
Year: 2018

The present work is focused on improving the Mode I delamination resistance of glass/epoxy composite laminates with milled glass fiber fillers. The influence of the interface fiber orientation and also the effect of fillers on the Mode I interlaminar fracture toughness was experimentally investigated and the results were correlated with the baseline glass/epoxy samples. It was observed that the dispersion of milled glass fiber fillers by weight of 5% of the epoxy matrix into the resin rich domain improved the fracture toughness efficiently, in all the cases of interface fiber orientation. This improvement in interlaminar fracture toughness was due to additional toughening mechanisms through crack deflection, filler debonding, filler interlocking/bridging and filler pullout. The results showed that incorporation of milled glass fiber filler enhanced the GIC Initiation and GIC Propagation fracture toughness by 102% and 50% in 0 0deg interply orientations over the baseline glass/epoxy samples. Besides, fracture surface analysis of the samples using Scanning Electron Microscope (SEM) indicates that the different damage mechanisms correspond to the deviation in fracture toughness.
Data Driven Cervical Cancer Prediction Model with Outlier Detection and Over Sampling Methods
Venue: Sensors
Year: 2020

Globally, cervical cancer remains as the foremost prevailing cancer in females. Hence, it is necessary to distinguish the importance of risk factors of cervical cancer to classify potential patients. The present work proposes a cervical cancer prediction model (CCPM) that offers early prediction of cervical cancer using risk factors as inputs. The CCPM first removes outliers by using outlier detection methods such as density based spatial clustering of applications with noise (DBSCAN) and isolation forest (iForest) and by increasing the number of cases in the dataset in a balanced way, for example, through synthetic minority over sampling technique (SMOTE) and SMOTE with Tomek link (SMOTETomek) Finally, it employs random forest (RF) as a classifier. Thus, CCPM lies on four scenarios: (1) DBSCAN SMOTETomek RF, (2) DBSCAN SMOTE+ RF, (3) iForest SMOTETomek RF, and (4) iForest SMOTE RF. A dataset of 858 potential patients was used to validate the performance of the proposed method. We found that combinations of iForest with SMOTE and iForest with SMOTETomek provided better performances than those of DBSCAN with SMOTE and DBSCAN with SMOTETomek. We also observed that RF performed the best among several popular machine learning classifiers. Furthermore, the proposed CCPM showed better accuracy than previously proposed methods for forecasting cervical cancer. In addition, a mobile application that can collect cervical cancer risk factors data and provides results from CCPM is developed for instant and proper action at the initial stage of cervical cancer.
Salt Content of Dairy Farm Effluents as an Indicator of Salinization Risk to Soils
Year: 2018

Water used for irrigation is a leading source of induced salinity in semiarid areas. Within the Irrigation District 005 in northern Mexico, there are more than 100 dairy farms housing over 72,000 dairy cows, 74% of which are concentrated in approximately 30 intensive operation farms. Dairy farm effluents (DFE) and manure are collected and stored temporarily until they are applied to the land to fertilize pasture and other crops. DFE vary in salt content, depending on specific farm operations. The risk of soil salinization by DFE was estimated by measuring electrical conductivity (EC) of both well water and DFE, and comparing these values with 2.0 mS cm 1, a Mexican guideline for wastewater used in agriculture. Half of the effluents exceeded the EC limit, with values as high as 12.4 mS cm 1, whereas a few exceeded the EC limit in both well and effluent water. The generation of salt and its passing into soils expose a potential for soil salinization, if preventive measures are not taken. A salt load map was created that depicted the areas at higher risk of salinization. The simple technique utilized here can be applied in estimating salinization potential in areas where monitoring of soils, irrigation drains, and shallow groundwater is infrequent.
Impact of social influence and users' perception of coolness on smartwatch behavior
Year: 2018

We explored the motives behind switching one's smartwatch, focusing on 2 divergent motivations that relate to social influence and the mobile and visible nature of these watches. Our findings and a review of related work indicated that the social motive for switching a smartwatch was coolness, that is, distinguishing oneself from others, because owning the latest model of smartwatch is a way to demonstrate having ample financial resources. The perceived benefit of switching one's smartwatch was associated more with coolness and the identity formation process, and less with actual utility or social influence. Further, the effects of similarity avoidance based on smartwatch purchasing intention were mediated by the effect of identity formation. Our findings may shed light on the nature of smartwatch uses and the motives that drive smartwatch users' choice to upgrade their devices.
Move to Online Learning during COVID 19 Lockdown: Pre Service Teachers' Experiences in Ghana
Year: 2020

The coronavirus pandemic (COVID 19) has brought another dimension to teaching and learning across the levels of education. The lockdown imposed in many countries to curtail the pandemic forced many institutions of learning to shift to the online mode of teaching and learning. Using a descriptive survey research design, this study explored the online learning experiences of pre service teachers at a Ghanaian university during the COVID 19 lockdown. The study focused on the pre service teachers' preparedness for online learning in terms of their digital literacy and technological devices used for online learning, their positive online learning experiences, and the challenges they encountered learning online. The findings suggested that the pre service teachers were digitally literate and mostly accessed online learning using smartphones. Besides, online learning enabled them to communicate and collaborate actively with their course mates and lecturers. It was found that the flexibility of online learning increased the students' motivation to learn. However, poor internet connectivity, the high cost of data, erratic power supply, lack of appropriate devices, inability to effectively manage their time, and family interruptions were some of the challenges experienced by the pre service teachers. https:/doi.org/10.26803/ijlter.19.10.16
Improvement of Soft Clay Using Floating Cement Dust Lime Columns
Year: 2019

Sameh A Ahmed Improvement of Soft Clay Using Floating Cement Dust Lime Columns The two main criteria that control the design and performance of footings are bearing capacity and settlement of soil. In soft soils, the construction of buildings, storage tanks, warehouse, etc. on weak soils usually involves excessive settlement problems. To solve bearing capacity reduce settlement problems, soil improvement may be considered by using different techniques, including encased cement dust lime columns. The proposed research studies the effect of adding floating encased cement dust and lime mix columns to soft clay on the clay bearing capacity. Four experimental tests were carried out. Columns diameters of 3.0 cm, 4.0 cm, and 5.0 cm and columns length of 60% of the clay layer thickness were used. Numerical model was constructed and verified using commercial finite element package (PLAXIS 2D, V8.5) The verified model was used to study the effect of distributing columns around the footing at different distances. The study showed that the floating cement dust lime columns enhanced the clay bearing capacity with 262% The numerical model showed that the columns around the footing have a limit effect on the clay improvement.
Functional dysconnectivity within the emotion regulating system is associated with affective symptoms in major depressive disorder: A resting state fMRI study
Venue: The Australian and New Zealand journal of psychiatry
Year: 2019

Major depressive disorder (MDD) can be characterized as a multidimensional and system level disorder. The neuropathophysiological abnormalities have been reported to be distributed in emotion regulation system, involving the prefrontal cortex (PFC) limbic and striatum in convergent studies. Decrease of positive affect and increase of negative affect are recognized as a hallmark of MDD. However, the dysfunctions in affective processing in MDD within the emotion regulation system remains largely unclear. In this study, our goals are to characterize the dysconnectivity pattern within this system and explore the relationships between this kind of dysconnectivity pattern and affective symptoms, which might help us better look into the neuropathophysiological mechanisms underlying MDD.  A total of 34 MDD and 34 healthy controls (HCs) underwent resting state functional magnetic resonance imaging (rsfMRI) The alterations in functional connectivity (FC) within the emotion regulation system and their relationships with affective symptoms were explored.  Compared with HCs, MDD patients showed aberrant FC within this system. Importantly, deceased FC was mainly involved in the prefrontal limbic system, while elevated FC was observed in the prefrontal striatum system. In the MDD group, decreased FC of right posterior hippocampus left dorsolateral prefrontal cortex (dlPFC) was negatively associated with the negative affect scores and Hamilton Depression Rating Scale scores and the FC of left ventral striatum left dlPFC was significantly negatively related with the positive affect scores.  These findings demonstrated that MDD showed characteristic pathological alterations of the emotion regulation system. Dysconnectivity within prefrontal limbic system might be more related to the dysregulation of negative affect, whereas dysconnectivity within prefrontal striatum system might influence more on positive affect processing. The decrease in positive affect and increase in negative affect in MDD might have different pathological basis. These results could help better understand the dysconnectivity pattern in the emotion regulating system underlying depression.
Theoretical turns through tourism taste scapes: the evolution of food tourism research
Venue: Research in Hospitality Management
Year: 2019

This article reflects on the evolution of food tourism research by tracing its conceptual, theoretical and empirical twists and turns over the past few decades. Prompted by some recent systematic reviews of food tourism studies, I draw on literature to follow the journey of this multi dimensional subject area as it has weaved between economic focused positivistic traditions and more interpretative sociocultural perspectives. I suggest that food tourism research offers an illuminating conceptual vehicle which can be fostered to generate insightful understandings of the complexity and inter connectedness of diverse culinary artefacts, identities and the experience of practised place. By exploring its roots, its growth and its potential future, I suggest it provides opportunities to pursue more interpretative and critical modes of thinking and furthers our understanding of concepts such as sustainability, performativity, embodiment, liminality and "in betweenness" In looking forward, I argue that food tourism research is still on a journey and while it continues to offer us a multifaceted cultural phenomenon saturated with meaning and discursive potential to produce new knowledge about tourism, we should embrace it, and travel with it.
Deeply Recursive Convolutional Network for Image Super Resolution
Venue: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Year: 2016

We propose an image super resolution method (SR) using a deeply recursive convolutional network (DRCN) Our network has a very deep recursive layer (up to 16 recursions) Increasing recursion depth can improve performance without introducing new parameters for additional convolutions. Albeit advantages, learning a DRCN is very hard with a standard gradient descent method due to exploding/ vanishing gradients. To ease the difficulty of training, we propose two extensions: recursive supervision and skip connection. Our method outperforms previous methods by a large margin.
Prediction Correction Interior Point Method for Time Varying Convex Optimization
Venue: IEEE Transactions on Automatic Control
Year: 2018

In this paper, we develop an interior point method for solving a class of convex optimization problems with time varying objective and constraint functions. Using log barrier penalty functions, we propose a continuous time dynamical system for tracking the (time varying) optimal solution with an asymptotically vanishing error. This dynamical system is composed of two terms: a correction term consisting of a continuous time version of Newton's method, and a prediction term able to track the drift of the optimal solution by taking into account the time varying nature of the objective and constraint functions. Using appropriately chosen time varying slack and barrier parameters, we ensure that the solution to this dynamical system globally asymptotically converges to the optimal solution at an exponential rate. We illustrate the applicability of the proposed method in two applications: a sparsity promoting least squares problem and a collision free robot navigation problem.
Team Recommendation for the Pokemon GO Game Using Optimization Approaches
Venue: 2020 19th Brazilian Symposium on Computer Games and Digital Entertainment (SBGames)
Year: 2020

Pokemon GO is one of the most popular Pokemon games. This game consists of walking around the world and collecting Pokemon characters using augmented reality. In addition, you can battle with friends, join a gym, or make attacks. These battles must happen between teams with the same size, and this poses a question that is related to the best combination for a team to beat a given opposing team. In order to solve this problem, one can use optimization algorithms. In this paper, we investigate three optimization algorithms to solve this problem: genetic algorithm (GA) memetic algorithm (MA) and iterated local search (ILS) In our experiments, we use time and fitness as evaluation metrics. Our findings indicate that the fastest algorithm is ILS with an execution time of 1.49 0.11 seconds, followed by GA with an execution time of 1.51 0.10 seconds, and MA with an execution time of 13.41 1.00 seconds. However, when we consider the fitness metric, MA achieves the best average fitness of 50, 366.27 12, 055.53, followed by GA, 43,113.00 10, 482.30, and ILS, 31,224.32 7,943.70. All these results are statistically significant to the others according to the post hoc Friedman test. Analyzing all the obtained results, we recommend the use of the ILS algorithm when the execution time is of utmost importance. However, if fitness is important, then we recommend the use of the memetic algorithm. Finally, if both the execution time and fitness are deemed equally important, then, we recommend the usage of the genetic algorithm because it has a runtime similar to ILS and reasonable fitness.
Supply chain flexibility A systematic literature review and identification of directions for future research
Year: 2017

The conceptualization of flexibility in organizations historically emerged from three views which relate to economic, to organizational and to manufacturing perspectives. Despite the growing number of publications about supply chain flexibility in the area of supply chain management, there is a lack of consensus on how to define and to conceptualize supply chain flexibility from a management point of view. The purpose of this paper is to present a comprehensive overview of the literature on the supply chain flexibility perspective and contributes to our understanding of the current state of research and its future development.,The research methodology used is the systematic literature review. In total 92 articles were selected from databases of well known journal publishers in the field of economics, business studies and management sciences as well as grey literature to cover the topic of supply chain flexibility.,A limited number of studies in the field of supply chain flexibility apply theories and define the term supply chain flexibility. Instead they focus on a particular part or dimension of the supply chain. Based on the analysis, a distinction is made between flexibility in the supply chain and supply chain flexibility. Based on the function and characteristics of the supply chain, the authors selected 30 flexibility dimensions that cover supply chain flexibility by concentrating on the different business areas involved.,The results support researchers and practitioners by identifying relevant trends and gaps in the field of supply chain flexibility.,The authors review the dimensions and aspects of supply chain flexibility that are currently taken into account in the literature. In this way, the authors provide an overarching perspective on the flexibility literature relating to supply chains.
Rolling element bearing fault diagnosis based on Over Complete rational dilation wavelet transform and auto correlation of analytic energy operator
Year: 2018

Local damage in rolling element bearings usually generates periodic impulses in vibration signals. The severity, repetition frequency and the fault excited resonance zone by these impulses are the key indicators for diagnosing bearing faults. In this paper, a methodology based on over complete rational dilation wavelet transform (ORDWT) is proposed, as it enjoys a good shift invariance. ORDWT offers flexibility in partitioning the frequency spectrum to generate a number of subbands (filters) with diverse bandwidths. The selection of the optimal filter that perfectly overlaps with the bearing fault excited resonance zone is based on the maximization of a proposed impulse detection measure "Temporal energy operated auto correlated kurtosis" The proposed indicator is robust and consistent in evaluating the impulsiveness of fault signals in presence of interfering vibration such as heavy background noise or sporadic shocks unrelated to the fault or normal operation. The structure of the proposed indicator enables it to be sensitive to fault severity. For enhanced fault classification, an autocorrelation of the energy time series of the signal filtered through the optimal subband is proposed. The application of the proposed methodology is validated on simulated and experimental data. The study shows that the performance of the proposed technique is more robust and consistent in comparison to the original fast kurtogram and wavelet kurtogram.
ISSN 2320 5407 International Journal of Advanced Research (2014) Volume 2, Issue 8, 13 24
Year: 2014

Alaa Y. Moustafa Berthellina citrina is a pleurobranchid opisthobranch characterized by its skin acid secretion that contains sulphate and chloride ions with traces of organic matter. To identify defensive potential and bioactivity, we tested this secretion for the first time against Artemia salina, different strains of microorganisms, human RBCs and human cancer cell lines. It showed lethality to A. salina with LC50 values 83.86 and 25.84 mg/ml after 6 and 24 hours, respectively and it caused 100% mortality after 48 and 72 hours. It exhibited antibacterial activity against seven human pathogenic bacteria, with larger inhibition zone on Streptococcus pyogenes and Staphylococcus aureus and showed strong inhibition activity against seven fungal species, particularly towards Paecilomyces variotii, Aspergillus flavo furcatis, Fusarium oxysporum and Penicillium oxalicum. It caused significant haemolysis for human RBCs in a range from 38.5 to 77.6 Moreover, it showed cytotoxicity against prostate carcinoma cells (PC 3) colorectal carcinoma (HCT 116) and lung carcinoma (A549) with IC50 values 6.582, 9.843 and 9.352 mg/ml, respectively. Using HPLC, taurine is the major components of the free amino acids of the secretion with percentage of 52.32% Thus, the secretion is shown to be highly toxic, bioactive and is interpreted as a chemical defence system against natural predators, but also against fouling. In addition, it might be a new source for bioactive substances that could be used in biomedical research and drugs. Copy Right, IJAR, 2014, All rights reserved.
Cognitive and emotional correlates of different types of deception
Year: 2012

We examined whether or not psychophysiological measures could be used to discriminate between 4 types of lies. Alpha band event related desynchronization (ERD) and skin conductance response (SCR) measures successfully discriminated between deception and truth. However, when deception was divided into 4 subsets, different patterns of ERD and SCR values were observed. There were substantial differences in ERD produced by instructed memorized lies, instructed created lies, spontaneously memorized lies, and truth. In contrast, SCR was a strong discriminator between created lies and truth. The results indicated that ERD could be sensitive to the cognitive activation caused by deception. Also, the strengths and weaknesses of both SCR and ERD measures could be supplemented when used together to detect different types of deception.
National survey on the management of heart failure in individuals over 80 years of age in French geriatric care units
Venue: BMC Geriatrics
Year: 2019

BackgroundTo evaluate the prevalence and management of heart failure (HF) in very old patients in geriatric settings.MethodsMembers of the French Society of Geriatrics and Gerontology throughout France were invited to participate in a point prevalence survey and to include all patients =80 years old, hospitalized in geriatric settings, with HF (stable or decompensated) on June 18, 2012. General characteristics, presence of comorbidities, blood tests and medications were recorded.ResultsAmong 7,197 patients in geriatric institution, prevalence of HF was 20.5% (n 1,478) (27% in acute care, 24.2% in rehabilitation care and 18% in nursing home) Mean age was 88.2 (SD 5.2) and Charlson co morbidity score was high (8.49 (SD 2.21) Left ventricular ejection fraction (LVEF) was available in 770 (52% patients: 536 (69.6% had a preserved LVEF 50% 120 (15.6% a reduced LVEF 40% and 114 (14.8% a midrange LVEF (40 49% Prescription of recommended HF drugs was low: 42.6% (629) used Angiotensin Converting Enzyme Inhibitors (ACEI) or Angiotensin Receptor Blockers (ARBs) 48.0% (709) b blockers, and 21.9% (324) ACEI or ARB with b blockers, even in reduced LVEF. In multivariate analysis ACEI or ARBs were more often used in patients with myocardial infarction (1.36 (1.04 1.78) stroke (1.42 (1.06 1.91) and diabetes (1.54 (1.14 2.06) b blockers were more likely used in patients with myocardial infarction (2.06 (1.54 2.76) and atrial fibrillation (1.70 (1.28 2.28).ConclusionIn this large very old population, prevalence of HF was high. Recommended HF drugs were underused even in reduced LVEF. These results indicate that management of HF in geriatric settings can still be improved.