nils-herrmann/clean_scirepeval huggingface dataset:
Accounting for Women's Orgasm and Sexual Enjoyment in College Hookups and Relationships
Year: 2012

This article investigates the determinants of orgasm and sexual enjoyment in hookup and relationship sex among heterosexual college women and seeks to explain why relationship sex is better for women in terms of orgasm and sexual enjoyment. We use data from women respondents to a large online survey of undergraduates at 21 U.S. colleges and universities and from 85 in depth interviews at two universities. We identify four general views of the sources of orgasm and sexual enjoyment technically competent genital stimulation, partner specific learning, commitment, and gender equality. We find that women have orgasms more often in relationships than in hookups. Regression analyses reveal that specific sexual practices, experience with a particular partner, and commitment all predict women's orgasm and sexual enjoyment. The presence of more sexual practices conducive to women's orgasm in relationship sex explains some of why orgasm is more common in relationships. Qualitative analysis suggests a double standard also contributes to why relationship sex is better for women: both men and women question women's (but not men's) entitlement to pleasure in hookups but believe strongly in women's (as well as men's) entitlement to pleasure in relationships. More attention is thus given to producing female orgasm in relationships.
Fungal endophytic communities on twigs of fast and slow growing Scots pine (Pinus sylvestris L. in northern Spain.
Venue: Fungal biology
Year: 2015

Most plant species harbour a diverse community of endophytic, but their role is still unknown in most cases, including ecologically and economically important tree species. This study describes the culturable fungal endophytic community of Pinus sylvestris L. twigs in northern Spain and its relationship with diametric growth of the host. In all, 360 twig samples were collected from 30 Scots pines in fifteen stands. Isolates were obtained from all twig samples and 43 fungal taxa were identified by morphogrouping and subsequent ITS rDNA sequencing. All isolates were Ascomycetes, being Dothideomycetes and Sordariomycetes the most abundant classes. Half of the species were host generalists while the others were conifer or pine specialists. We found three new endophytic species for the Pinaceae: Biscogniauxia mediterranea, Phaeomoniella effusa and Plectania milleri, and additional six new species for P. sylvestris: Daldinia fissa, Hypocrea viridescens, Nigrospora oryzae, Ophiostoma nigrocarpum, Penicillium melinii and Penicillium polonicum. The endophytic community of fast and slow growing trees showed differences in species composition, abundance and evenness, but not in diversity. Phoma herbarum was associated to fast growing trees and Hypocrea lixii to those growing slow. Our results support the hypothesis that some endophytic species may affect growth of P. sylvestris.
Association between Children's Saving Account and Parent Rated Children's Health: A Preliminary Study
Year: 2020

Children's Savings Accounts (CSAs) are interventions designed to build educational assets for school age children. The positive effects of having a CSA has been established for mental health and developmental outcomes, yet no studies to date have examined how CSAs affect children's physical health. This study uses data from Harold Alfond College Challenge, the oldest and one of the most well known CSA programs in the United States, to evaluate the association between a CSA and children's physical health status measured by parent rated children's health. Results indicate CSA ownership is associated with a greater chance of reporting excellent or very good health than those families who did not receive a CSA. Implications on research and CSA programs are discussed.
A miniature prism based stereoscopic system for 3D machine vision applications
Venue: International Conference on Machine Vision
Year: 2019

We have developed a prototype of a miniature prism based optical system for simultaneous acquisition of two stereoscopic images on a single image sensor. The scheme and optical characteristics of the system are presented. We show that after a proper geometrical calibration and image processing it is possible to calculate three dimensional (3 D) shape of the inspected objects. The devices based on this system may be effectively used for 3 D machine vision applications and remote visual inspection.
Ultrathin metasurface based carpet cloak for terahertz wave.
Venue: Optics express
Year: 2017

Ultrathin metasurfaces with local phase compensation deliver new schemes to cloaking devices. Here, a large scale carpet cloak consisting of an ultrathin metasurface is demonstrated numerically and experimentally in the terahertz regime. The proposed carpet cloak is designed based on discontinuous phase metallic resonators fabricated on a polyimide substrate, offering a wide range of reflection phase variations and an excellent wavefront manipulation along the edges of the bump. The invisibility is verified when the cloak is placed on a reflecting triangular surface (bump) The multi step discrete phase design method would greatly simplify the design process and is probable to achieve large dimension cloaks, for applications in radar and antenna systems as a thin, lightweight, and easy to fabricate solution for radio and terahertz frequencies.
MACORD: Online Adaptive Machine Learning Framework for Silent Error Detection
Venue: 2017 IEEE International Conference on Cluster Computing (CLUSTER)
Year: 2017

Future high performance computing (HPC) systems with ever increasing resource capacity (such as compute cores, memory and storage) may significantly increase the risks on reliability. Silent data corruptions (SDCs) or silent errors are among the major sources that corrupt HPC execution results. Unlike fail stop errors, SDCs can be harmful and dangerous in that they cannot be detected by hardware. To remedy this, we propose an online MAchine learning based silent data CORruption Detection framework (abbreviated as MACORD) for detecting SDCs in HPC applications. In our study, we comprehensively investigate the prediction ability of a multitude of machine learning algorithms and enable the detector to automatically select the best fit algorithms at runtime to adapt to the data dynamics. Because it takes only spatial features (i.e. neighboring data values for each data point in the current time step) into the training data, our learning framework exhibits low memory overhead (less than 1% Experiments based on real world scientific applications/benchmarks show that our framework can elevate the detection sensitivity (i.e. recall) up to 99% Meanwhile the false positive rate is limited to 0.1% in most cases, which is one order of magnitude improvement compared with the latest state of the art spatial technique.
Additive manufacturing of multiple materials by selective laser melting: Ti alloy to stainless steel via a Cu alloy interlayer
Year: 2020

The ability to combine multiple materials (MM) into a single component to expand its range of functional properties is of tremendous value to the ceaseless optimization of engineering systems. Although fusion and solid state joining techniques have been typically used to join dissimilar metals, additive manufacturing (AM) has the potential to produce MM parts with a complex spatial distribution of materials and properties that is otherwise unachievable. In this work, the selective laser melting (SLM) process was used to manufacture MM parts which feature steep material transitions from 316L stainless steel (SS) to Ti 6Al 4V (TiA) through an interlayer of HOVADUR(r) K220 copper alloy (CuA) The microstructure in both the CuA/SS and TiA/CuA interfaces were examined in detail and the latter was found to be the critical interface as it contained three detrimental phases (i.e. L21 ordered phase, amorphous phase, and Ti2Cu) which limit the mechanical strength of the overall MM part. By making use of the non homogeneity within the melt pool and limiting the laser energy input, the relatively tougher interfacial a' Ti phase can be increased at the expense of other brittle phases, forming what is essentially a composite structure at the TiA/CuA interface. During tensile testing, the interfacial a' Ti phase is capable of deflecting cracks from the relatively brittle TiA/CuA interface towards the ductile CuA interlayer and an overall tensile strength in excess of 500 MPa can be obtained. This method of introducing an interfacial composite structure to improve MM bonding is envisioned to be applicable for the SLM of other metallic combinations as well.
A cooperative game approach applied to the furniture supply chain of clusters for improving its competitive value: A case study
Year: 2016

The paper studies a cooperative game, which is being played among the firms, involved in furniture industries, belonging to the same cluster. Due to the increased competition at the local and global levels, cooperation among the business entities is practically the only way to survive in the cluster. Consequently, a cooperative game model is proposed for the firms, associated in a vertical channel, where its performance indices are measured by one of its indicators of competitiveness at an entrepreneurial level versus the value of the cluster itself. As a case study, a competitive value analysis is done for the Colombian furniture cluster by indicating the characteristics and existing conditions of the cluster in the department of Atlantico in Colombia. Moreover, this paper analyzes and establishes an optimal feasible solution of cooperative game among the principal firms using Shapley value method.
Ectoparasite infestation of free scavenging chickens reared under traditional backyard production system in Wolayita Zone, southern Ethiopia
Year: 2015

This study was carried out to determine the prevalence and types of ectoparasite faunas and the associated host related risk factors in free scavenging chickens in Wolayita Zone, Southern Ethiopia. Physical examination that involves hand picking and skin scrapping and laboratory investigation was employed in a total 450 chickens (198 male and 252 female).The present study revealed an overall prevalence of 40% (180/450) Three genera and seven species of ectoparasites were identified. Of the three genera, mites were the dominant ones (24.9% followed by lice (13.8% and ticks (1.3%.Among the seven species of ectoparasites, Cnemidocoptes mutans (61.1 was the most prevalent species followed by Cuclotogaster heterographus (8.9% and Menopon gallinae (8.9% Goniocotes gallinae (8.3% and Menacanthus stramineus (8.3% while Argaspersicus 3.3%(6/180) was the least identified. There was no significant difference (p>0.05) in prevalence of ectoparasites with regard to sex, age and breeds of chickens except for Cnemidocoptes mutans which was more significantly (p<0.05) prevalent in adults than growers and chicks, in local than exotic breeds, and in female than male chickens. This study revealed diverse fauna of ectoparasite in backyard chickens in the study area; hence integrated control strategies should be put in place to boost chicken productivity.  Lice; Mites; Prevalence; ticks; Wolayta zone
MULTIPLE INTENTIONS
Year: 2018

Recent advances in learning from demonstrations (LfD) with deep neural networks have enabled learning complex robot skills that involve high dimensional perception such as raw image inputs. LfD algorithms generally assume learning from single task demonstrations. In practice, however, it is more efficient for a teacher to demonstrate a multitude of tasks without careful task set up, labeling, and engineering. Unfortunately in such cases, traditional imitation learning techniques fail to represent the multi modal nature of the data, and often result in sub optimal behavior. In this paper we present an LfD approach for learning multiple modes of behavior from visual data. Our approach is based on a stochastic deep neural network (SNN) which represents the underlying intention in the demonstration as a stochastic activation in the network. We present an efficient algorithm for training SNNs, and for learning with vision inputs, we also propose an architecture that associates the intention with a stochastic attention module. Furthermore, we demonstrate our method on real robot visual object reaching tasks, and show that it can reliably learn the multiple behavior modes in the demonstration data. Video results are available at https:/vimeo.com/240212286/fd401241b9.
Is there a dysgenic secular trend towards slowing simple reaction time? Responding to a quartet of critical commentaries
Year: 2014

Previously Woodley, te Nijenhuis and Murphy (2013) tested the hypothesis that Victorian era British and American samples exhibited higher g on average than relatively more modern populations sampled from the US, UK, Canada, Australia and Finland, using measures of simple visual reaction time in a meta analytic study. Based on 13 age matched studies from Western countries conducted between 1884 and 2004 yielding 16 data points we estimated a decline of 13.35 IQ points. Here we respond to a quartet of critical commentaries on our paper penned by five prominent intelligence researchers (James Flynn, Theodore Nettelbeck, Irwin Silverman, Julia Dodonova and Yuri Dodonov) We show via various reanalyses of the data and also via careful consideration of the arguments presented that the original finding of a potential secular decline in simple reaction time performance is robust. A recurrent criticism of our finding stems from earlier work showing no secular trends with respect to inspection time over a 20 year period in Australia despite the possibility of co occurring dysgenic fertility. We deal with this via the method of correlated vectors, which reveals the presence of a 'genetic g common factor on which simple RTs, WAIS g loadings and subtest heritabilities load positively and significantly, but on which inspection time does not load. This indicates that inspection times are associated with local information processing, unlike simple reaction times, which are associated with global processing (i.e. g The robustness of our original finding is best illustrated however by our final meta regression, in which the use of six methods variance controlled reaction time means taken from the US and the UK between 1889 and 1993, coupled with a newly estimated age matched reference standard deviation, reveal a seemingly robust secular trend towards slowing reaction time in these two countries, which translates into a potential dysgenics rate of 1.21 IQ points per decade, or 13.9 points in total between 1889 and 2004. We conclude by arguing that the best way forward is to test novel predictions stemming from our finding relating to molecular genetics, neurophysiology and alternative cognitive indicators, thus shifting the research focus away from the purely methodological level towards the broader nomological level. We thank our critics for helping us to arrive at a much more precise estimate of the decline in general intelligence.
Fine tuned Pre trained Mask R CNN Models for Surface Object Detection
Venue: ArXiv
Year: 2020

This study evaluates road surface object detection tasks using four Mask R CNN models as a pre study of surface deterioration detection of stone made archaeological objects. The models were pre trained and fine tuned by COCO datasets and 15,188 segmented road surface annotation tags. The quality of the models were measured using Average Precisions and Average Recalls. Result indicates substantial number of counts of false negatives, i.e. left detection and unclassified detections. A modified confusion matrix model to avoid prioritizing IoU is tested and there are notable true positive increases in bounding box detection, but almost no changes in segmentation masks.
The essential factors for teaching learning English
Year: 2015

The aim of the research was to arrive at a detailed understanding of English language education for young learners in Korea. The study shows that Korea Ministry of Education introduced English language on the elementary level in order to bring up a global person from the early age. This paper examines the factors which influence English language teaching and learning in Korea: Early start (age factor, better pronunciation, time factor) the Ministry of Education involvement and support (well developed curriculum, well trained teachers, sufficient materials) and parental support. The study concludes that the most effective factor can be the age, as the theory of CPH strongly argues. Also, the content based instruction is one of the effective factors that the Korea Ministry of Education is trying to apply in public school curriculum. Moreover, the teachers' and parents' supports are the crucial matter for young learners in order to motivate them to learn English. In order to improve English language education for young learners in Korea, all these factors should be taken into account.
Prediction the Behavior of Piles in Clayey Soils
Year: 2018

This research includes a nonlinear finite element analysis of axisymmetric soil pile system. The analysis included piles of different length and diameter. The interface element was used as a thin layer separating the pile from surrounding soil. The load settlement curves for piles installed in soft to medium and stiff clays were obtained. Two consideration were studied; the ultimate capacity of pile and the settlement reduction factor. The results show that increase in the length and diameter of pile leads to increase in the ultimate load in range (3560% and in the range (3335) respectively. The distribution of lateral displacement along the depth of the pile gave the same trend in both soft to medium and stiff clay while the settlement reduction factor in soft soil is greater than for the stiff clay.
Mitigating the impact of COVID 19 on tuberculosis and HIV services: a cross sectional survey of 669 health professionals in 64 low and middle income countries
Venue: medRxiv
Year: 2020

The disruption of essential services for infectious diseases such as tuberculosis (TB) and HIV is likely to result in the indirect health impacts of COVID 19 being even greater than the direct impacts. The experiences of frontline health professionals are invaluable in understanding how to minimise disruption of healthcare services during emergency situations, but are insufficiently incorporated into policy planning. We synthesised information from frontline TB and HIV professionals to identify ways in which COVID 19 has affected services in low and middle income countries (LMIC) and strategies to minimise impacts on patients and healthcare providers.  We conducted a cross sectional study of TB and HIV healthcare delivery, management, and research professionals in LMIC around the world. Between May 12 and August 6 2020, we collected qualitative and quantitative data using an online survey disseminated through professional networks and social media in 11 languages. We used descriptive statistics and thematic analysis to analyse responses. Results 669 respondents from 64 countries completed the survey, representing a 72% response rate. Over 40% of respondents stated that it was impossible or much harder for TB and HIV patients to reach healthcare facilities since COVID 19. The most common barriers reported to affect patient utilisation of healthcare facilities were: fear of getting infected with SARS CoV 2, transport disruptions, movement restrictions, and reduced income. Healthcare provider access to healthcare facilities was also severely impacted according to 37% of TB respondents and 28% of HIV respondents. In line with this finding, qualitative responses focused on strategies to facilitate transport of patients and healthcare providers or service delivery adaptations to reduce the need for patients to travel to healthcare facilities. While only 16% and 11% of respondents reported major disruptions to provision of medical treatment for HIV or TB, access to non medical support for patients, such as food supplementation or counselling, was harder or impossible to access according to 35% and 31% of HIV and TB respondents respectively. Our qualitative data suggested that nutritional support became critical for some patients when movement restrictions and employment instability reduced access to income and food.  Our large multi country survey indicated that patients and healthcare providers across numerous LMIC faced substantial challenges in accessing healthcare facilities, and that critical non medical support for patients, such as food supplementation and counselling, was particularly impacted by COVID 19 disruptions. Frontline professionals identified important policies and healthcare service delivery adaptations that could mitigate disruptions in the future. It is essential to facilitate sharing of their experiences with policymakers and healthcare service delivery organisations.
Potential of quinoa in the development of fermented spoonable vegan products
Year: 2020

The aim of this work was to study the potential of two quinoa varieties, Pasankalla (PK) and Rosada de Huancayo (RH) in developing fermented spoonable vegan products. The quinoa flours were fermented by a candidate probiotic Lactobacillus plantarum Q823. Then, two experimental products were developed by flavoring fermented PK flours with date (QD) and fermented RH flour with bilberry and banana (QBB) The nutritional composition, storage time, and sensory properties (the check all that apply method) of QD and QBB were assessed in relation to four commercial vegan fermented snack products. The functionality of L. plantarum Q823 fermentation was demonstrated by high viable lactic acid bacteria counts (log cfu 1 9) of QD and QBB during the 28 day storage compared to commercial products (log cfu 1
Customer Experience in Retail: A Systematic Literature Review
Year: 2020

The customer experience (CX) is a concept that has been closely studied by companies in recent years. This is because it is one of the most important factors in maintaining a competitive advantage. In addition, it is customers who seek to create an experience that goes beyond the acquisition of a product. In this article, we present a systematic literature review of the CX in retail. We reviewed articles published over the last ten years related to (1) the definition of the CX; (2) dimensions, attributes, and factors that influence the CX in retail; (3) methods used to evaluate the CX in retail; and (4) potential heuristics to evaluate the CX in general and, in particular, in retail. We analyzed 67 articles, and the obtained result shows that (1) multiple definitions exist in different contexts; (2) the dimensions, such as the conceptualization of the CX, vary depending on the context; (3) the evaluation methods found do not comprehensively evaluate the CX; (4) there is no evidence of heuristics used to evaluate the CX.
Deep Learning Based Intelligent Fault Diagnosis Methods Toward Rotating Machinery
Venue: IEEE Access
Year: 2020

Fault diagnosis of rotating machinery plays a significant role in the industrial production and engineering field. Owing to the drawbacks of traditional fault diagnosis methods, such as heavily dependence on human knowledge and professional experience, intelligent fault diagnosis based on deep learning (DL) has aroused the interest of researchers. DL achieves the desirable automatic feature learning and fault classification. Therefore, in this review, DL and DL based intelligent fault diagnosis techniques are overviewed. DL based fault diagnosis approaches for rotating machinery are summarized and discussed, primarily including bearing, gear/gearbox and pumps. Finally, with respect to modern intelligent fault diagnosis, the existing challenges and possible future research orientations are prospected and analyzed.