nils-herrmann/clean_scirepeval huggingface dataset:
Effects of Two Commercial Supplemental Fat Products on Body Condition Score and Cow and Herd Level Milk Yield and Composition in a Commercial Dairy Herd in Kansas
Year: 2019

Feeding fat supplements to lactating dairy cows is an effective strategy to increase energy density of rations and increase milk yield. However, it is not clear whether supplementing a specific fat supplement for the entire lactating herd provides better results than others in commercial dairy herds. The objective of this study was to compare the effects of fat supplementation with two commercial products on changes in body condition score (BCS) and cowand herd level milk production and composition in a large commercial dairy herd. The study was conducted in a herd milking approximately 1,500 Holstein cows. One of two treatments was assigned to the herd in a singlesubject crossover design with 4 periods. Treatments were inclusion of 0.24 lb/cow per day of a supplement rich in saturated fats (Propel; Propel Energy Plus) or 0.22 lb/cow per day of a supplement containing calcium salts of long chain fatty acids (Control) Treatments were applied to all lactating cows during four consecutive weeks. Milk yield recorded during the last week of each period was used for statistical analyses. In addition, milk samples were collected in the last week of each period to determine test day milk protein, fat, somatic cell count, and urea nitrogen concentrations. At the beginning and at the end of each experimental period, BCS was assessed from a subset of cows to evaluate BCS change. Herd level milk fat, protein, and somatic cell count were recorded daily by the milk cooperative. Bulk tank milk fat and protein contents on the fourth week of fat supplementation were similar between Control and Propel treatments. Average milk yield during the fourth week of fat supplementation (yield recorded daily in the last week of the experimental period) was greater for Control than Propel supplementation (83.4 vs. 82.1 1.7 lb/day) In the analyses that used test day data, milk yield did not differ between Control and Propel treatments. Supplementation with Propel resulted in greater milk fat (4.50 vs. 4.29 0.12% and reduced milk protein content (3.12 vs. 3.14 0.03% compared with Control. In addition, milk urea nitrogen was reduced for Control vs. Propel cows (12.5 vs. 13.1 0.04 mg/dL) Supplementation with Propel increased energy corrected milk (93.9 vs. 91.7 3.1 lb/ day) and fat corrected milk (96.3 vs. 93.5 3.3 lb/day) yields compared with Control supplementation. Proportion of cows that lost BCS during the fat supplementation periods did not differ between treatments; however, BCS change tended to be more pronounced during supplementation with Propel than Control treatment 0.03 vs. 0.02 0.04) In conclusion, fat supplementation using the Propel treatment resulted in greater milk fat content, energy corrected milk, and fat corrected milk compared with fat supplementation with Control. Our findings suggest that the type of market to which milk is sold should be considered in the choice of fat supplements.
Endurant Types in Ontology Driven Conceptual Modeling: Towards OntoUML 2.0
Venue: ER
Year: 2018

For over a decade now, a community of researchers has contributed to the development of the Unified Foundational Ontology (UFO) aimed at providing foundations for all major conceptual modeling constructs. This ontology has led to the development of an Ontology Driven Conceptual Modeling language dubbed OntoUML, reflecting the ontological micro theories comprising UFO. Over the years, UFO and OntoUML have been successfully employed in a number of academic, industrial and governmental settings to create conceptual models in a variety of different domains. These experiences have pointed out to opportunities of improvement not only to the language itself but also to its underlying theory. In this paper, we take the first step in that direction by revising the theory of types in UFO in response to empirical evidence. The new version of this theory shows that many of the meta types present in OntoUML (differentiating Kinds, Roles, Phases, Mixins, etc. should be considered not as restricted to Substantial types but instead should be applied to model Endurant Types in general, including Relator types, Quality types and Mode types. We also contribute a formal characterization of this fragment of the theory, which is then used to advance a metamodel for OntoUML 2.0. Finally, we propose a computational support tool implementing this updated metamodel.
Unsupervised Bilingual Word Embedding Agreement for Unsupervised Neural Machine Translation
Venue: ACL
Year: 2019

Unsupervised bilingual word embedding (UBWE) together with other technologies such as back translation and denoising, has helped unsupervised neural machine translation (UNMT) achieve remarkable results in several language pairs. In previous methods, UBWE is first trained using non parallel monolingual corpora and then this pre trained UBWE is used to initialize the word embedding in the encoder and decoder of UNMT. That is, the training of UBWE and UNMT are separate. In this paper, we first empirically investigate the relationship between UBWE and UNMT. The empirical findings show that the performance of UNMT is significantly affected by the performance of UBWE. Thus, we propose two methods that train UNMT with UBWE agreement. Empirical results on several language pairs show that the proposed methods significantly outperform conventional UNMT.
Engineering Application of Basic Level Materials of Red Mud High Level Pavement
Year: 2006

The influence role of red mud bulk percentage, composite moisture percentage, lime quantity and additive for pavement basic level strength has been discussed in this paper. The result shows that the percentage of bulk with diameter 10 mm from red mud has influenced the compression stress and the percentage should be controlled less than 10% The compression stress of test sample is the highest when the percentage of composite moisture is about 45% Old red mud:fly ash :lime 75:15:10, which is the best mix ratio in practical project application. Lime powder and pulping of the additive can improve the initial stress of basic level. A highway is 4 km, with pavement basic level of red mud through coring. And its stress has arrived at the first class of lime industry waste stable soil and the stress requirements of the expressway.
Attention Routing Between Capsules
Venue: 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW)
Year: 2019

In this paper, we propose a new capsule network architecture called Attention Routing CapsuleNet (AR CapsNet) We replace the dynamic routing and squash activation function of the capsule network with dynamic routing (CapsuleNet) with the attention routing and capsule activation. The attention routing is a routing between capsules through an attention module. The attention routing is a fast forward pass while keeping spatial information. On the other hand, the intuitive interpretation of the dynamic routing is finding a centroid of the prediction capsules. Thus, the squash activation function and its variant focus on preserving a vector orientation. However, the capsule activation focuses on performing a capsule scale activation function. We evaluate our proposed model on the MNIST, affNIST, and CIFAR 10 classification tasks. The proposed model achieves higher accuracy with fewer parameters (x0.65 in the MNIST, x0.82 in the CIFAR 10) and less training time than CapsuleNet (x0.19 in the MNIST, x0.35 in the CIFAR 10) These results validate that designing a capsule scale operation is a key factor to implement the capsule concept. Also, our experiment shows that our proposed model is transformation equivariant as CapsuleNet. As we perturb each element of the output capsule, the decoder attached to the output capsules shows global variations. Further experiments show that the difference in the capsule features caused by applying affine transformations on an input image is significantly aligned in one direction.
COVID 19 in patients with cutaneous immune mediated diseases in The Netherlands: real world observational data
Venue: Journal of the European Academy of Dermatology and Venereology JEADV
Year: 2020

Literature about COVID 19 infections in patients with chronic inflammatory (skin) diseases treated with or without systemic therapy is scarce and  6 Therefore, we aimed to investigate the incidence and clinical course of COVID 19 related symptoms and the effect on clinical and psychological symptoms in patients with atopic dermatitis (AD) and psoriasis vulgaris (PsO)
Transparency and System Support in Peru
Year: 2015

Powerful international actors have vigorously promoted transparency for developing countries, yet we know little about the actual effects of transparency. In this paper, we use a series of survey experiments conducted on the streets of Lima, Peru to investigate a fairly simple question: what are the effects of government transparency on attitudes regarding support for the Peruvian political system? Like many developing countries, Peru lacks much system support, making it more difficult to improve governance and democracy. We find that transparency has little impact on political attitudes, unless accompanied by either one of two conditions: the information is attributed to a credible third party (in our case, USAID) or the information provides a fram in which the government is associate with comparative socioeconomic wellbeing. Under those conditions, Peruvians increase their approval of the national political community, the regime's performance, regime institutions, and local government. The increases are substantively large, ranging between 6 to 11 points on our 100 point scales, or about half of a standard deviation of the variation in the control groups.
DeepSUM: Deep Neural Network for Super Resolution of Unregistered Multitemporal Images
Venue: IEEE Transactions on Geoscience and Remote Sensing
Year: 2020

Recently, convolutional neural networks (CNNs) have been successfully applied to many remote sensing problems. However, deep learning techniques for multi image super resolution (SR) from multitemporal unregistered imagery have received little attention so far. This article proposes a novel CNN based technique that exploits both spatial and temporal correlations to combine multiple images. This novel framework integrates the spatial registration task directly inside the CNN, and allows one to exploit the representation learning capabilities of the network to enhance registration accuracy. The entire SR process relies on a single CNN with three main stages: shared 2 D convolutions to extract high dimensional features from the input images; a subnetwork proposing registration filters derived from the high dimensional feature representations; 3 D convolutions for slow fusion of the features from multiple images. The whole network can be trained end to end to recover a single high resolution image from multiple unregistered low resolution images. The method presented in this article is the winner of the PROBA V SR challenge issued by the European Space Agency (ESA)
Early childhood attachment stability and change: a meta analysis.
Venue: Attachment human development
Year: 2020

Examining degrees of stability in attachment throughout early childhood is important for understanding developmental pathways and for informing intervention. Updating and building upon all prior meta analyses, this study aimed to determine levels of stability in all forms of attachment classifications across early childhood. Attachment stability was assessed between three developmental epochs within early childhood: infancy, toddlerhood, and preschool/early school. To ensure data homogeneity, only studies that assessed attachment with methods based on the strange situation procedure were included. Results indicate moderate levels of stability at both the four way (secure, avoidant, resistant, and disorganised; k 0.23) and secure/insecure (r 0.28) levels of assessment. Meta regression analysis indicated security to be the most stable attachment organisation. This study also found evidence for publication bias, highlighting a preference for the publication of significant findings.
Right to a Human in the Loop: Political Constructions of Computer Automation Personhood from Data Banks to Algorithms
Year: 2017

Building on recent scholarship investigating the governance of algorithms, this Article is an exploration of the role of dignity in data protection law addressing automated decision making. Delving into the historical roots of contemporary disputes between information societies, notably European Union and Council of Europe countries and the United States, reveals that the regulation of algorithms has a rich, culturally entrenched, politically relevant backstory. Methodologically, the Article compares the making of law in the area of data protection and privacy, where algorithmic decision making has thus far been housed, focusing on the role automation has played in the two regimes as they have confronted computing technologies. By situating diverse policy treatments within the cultural contexts from which they emerged, the Article uncovers and examines two different legal constructions of automated data processing, one that has furnished a right to a human in the loop that is intended to protect the dignity of the data subject and the other that promotes and fosters the fully automated to establish and celebrate the fairness and objectivity of computers. The existence of this right across European countries and its absence in the U.S. will no doubt continue to be relevant to international technology policy as smart technologies are introduced in more and more areas of society.
Incidence, predictors and patterns of care of patients with very severe hypertriglyceridemia in Ontario, Canada: a population based cohort study
Venue: Lipids in health and disease
Year: 2021

The incidence of severe (S HTG) and very severe hypertriglyceridemia (VS HTG) among Canadians is unknown. This study aimed to determine the incidence, characteristics, predictors and care patterns for individuals with VS HTG.  Using linked administrative healthcare databases, a population based cohort study of Ontario adults was conducted to determine incidence of new onset S HTG (serum triglycerides (TG) 10 20 mmol/L) and VS HTG (TG 20 mmol/L) between 2010 and 2015. Socio demographic and clinical characteristics of those with VS HTG were compared to those who had no measured TG value 3 mmol/L. Univariable and multivariable logistic regression were used to determine predictors for VS HTG. Healthcare patterns were evaluated for 2 years following first incidence of TG 20 mmol/L.  Incidence of S HTG and VS HTG in Ontario was 0.16 and 0.027% among 10,766,770 adults =18 years and 0.25 and 0.041% among 7,040,865 adults with at least one measured TG, respectively. Predictors of VS HTG included younger age [odds ratios (OR) 0.64/decade, 95% confidence intervals (CI) 0.62 0.66] male sex (OR 3.83; 95% CI 3.5 4.1) diabetes (OR 5.38; 95% CI 4.93 5.88) hypertension (OR 1.69; 95% CI 1.54 1.86) chronic liver disease (OR 1.71; 95% CI 1.48 1.97) alcohol abuse (OR 2.47; 95% CI 1.90 3.19) obesity (OR 1.49; 95% CI 1.13 1.98) and chronic kidney disease (OR 1.39; 95% CI 1.19 1.63)  The 5 year incidence of S HTG and VS HTG in Canadian adults was 1 in 400 and 1 in 2500, respectively. Males, those with diabetes, obese individuals and those with alcohol abuse are at highest risk for VS HTG and may benefit from increased surveillance.
Evaluating Recommendation Systems
Venue: Recommender Systems Handbook
Year: 2011

Recommender systems are now popular both commercially and in the research community, where many approaches have been suggested for providing recommendations. In many cases a system designer that wishes to employ a recommendation system must choose between a set of candidate approaches. A first step towards selecting an appropriate algorithm is to decide which properties of the application to focus upon when making this choice. Indeed, recommendation systems have a variety of properties that may affect user experience, such as accuracy, robustness, scalability, and so forth. In this paper we discuss how to compare recommenders based on a set of properties that are relevant for the application. We focus on comparative studies, where a few algorithms are compared using some evaluation metric, rather than absolute benchmarking of algorithms. We describe experimental settings appropriate for making choices between algorithms. We review three types of experiments, starting with an offline setting, where recommendation approaches are compared without user interaction, then reviewing user studies, where a small group of subjects experiment with the system and report on the experience, and finally describe large scale online experiments, where real user populations interact with the system. In each of these cases we describe types of questions that can be answered, and suggest protocols for experimentation. We also discuss how to draw trustworthy conclusions from the conducted experiments. We then review a large set of properties, and explain how to evaluate systems given relevant properties. We also survey a large set of evaluation metrics in the context of the properties that they evaluate.
Pine Wilt Disease in the Front Range 2.915
Year: 2020

Pine wilt disease is a lethal wilting disease caused by the pine wilt nematode (Bursaphelenchus xylophilus; PWN) PWN causes rapid wilting and mortality in susceptible host trees, typically Pinus species exotic to the US, including Scots (P. sylvestris) and Austrian (P. nigra) pines. Damage from PWN varies based on host species and environmental conditions especially temperature and moisture. PWN is thought to be endemic to the U.S. and has caused widespread damage to forested landscapes where it has been introduced including Europe, Japan, South Korea, and China. In the US, the westward movement of PWN has been tracked through Missouri and Kansas since 1979.
Survey of developments on multi agent formation control related problems
Year: 2013

Firstly,the fundamental sequence of ideas of formation control is investigated with introductions on three classic formation control methods,i.e.,the leader follower method,the behavior based method,and the virtual structure method.In addition,the results of the recently developed graph based method are reviewed,which embodies the above mentioned three methods,including the modeling of multi agent system by graphs,the algebra graph theory based and the rigid graph theory based formation control law designs and shape transformations between different formation patterns.Then,in the view of the graph theory,the recent developments of consensus,rendezvous/alignment,swarming/flocking and containment control are reviewed.Finally,towards to the practical applications,some topics which might be interesting for future investigation are raised as well.
FPGA based spectrum sensors with switchable RBW
Venue: IEICE Electron. Express
Year: 2016

Currently, low cost spectrum devices are required in order to monitor the overall frequency bands for CR (Cognitive Radio) systems and EMF (Electromagnetic Field) strength measurement. This study was conducted to develop an FPGA (Field Programmable Gate Array) based spectrum sensor adopting switchable RBW (Resolution Bandwidth) with resolutions of 1MHz and 100 kHz. In order to reduce the hardware complexity of the spectrum sensor, a shared multi stage FIR filter architecture was utilized, which resulted in nearly a 90% cost reduction compared to those without the proposed architecture.
Grounded cognition.
Venue: Annual review of psychology
Year: 2008

Grounded cognition rejects traditional views that cognition is computation on amodal symbols in a modular system, independent of the brain's modal systems for perception, action, and introspection. Instead, grounded cognition proposes that modal simulations, bodily states, and situated action underlie cognition. Accumulating behavioral and neural evidence supporting this view is reviewed from research on perception, memory, knowledge, language, thought, social cognition, and development. Theories of grounded cognition are also reviewed, as are origins of the area and common misperceptions of it. Theoretical, empirical, and methodological issues are raised whose future treatment is likely to affect the growth and impact of grounded cognition.
Demographic characteristics of the board of directors' structure and tax avoidance
Venue: International Journal of Social Economics
Year: 2019

PurposeThe structure of corporate governance, as one of the important elements to be considered based on the different characteristics than other companies, such as women, expertise, tenure and management is different. But two measures for the presence of women in the board of directors and the size of director's board are considered as corporate content characteristics that can affect corporate tax strategies in avoiding tax or taxes timely pay off. The purpose of this paper is to understand the demographic characteristics of the board of directors structure on the board and tax avoidance in Tehran Stock Exchange ( includes the 505 firm year observations from companies listed on the TSE during the years 2012 2016 and research hypothesis was tested using multivariate regression model based on panel data. results indicate that female presence on the board of directors reduces the corporate tax avoidance. Additionally, firms with a larger size of board of directors are associated with more tax avoidance.valueThe current study is almost the first study which has been conducted in Iran, so the findings of the study not only extend the extant theoretical literature concerning the tax avoidance in developing countries including emerging capital market of Iran, but also help investors, capital market regulators and accounting standard setters to make informed decisions.
Recent Advances in the Use of Galleria mellonella Model to Study Immune Responses against Human Pathogens
Venue: Journal of fungi
Year: 2018

The use of invertebrates for in vivo studies in microbiology is well established in the scientific community. Larvae of Galleria mellonella are a widely used model for studying pathogenesis, the efficacy of new antimicrobial compounds, and immune responses. The immune system of G. mellonella larvae is structurally and functionally similar to the innate immune response of mammals, which makes this model suitable for such studies. In this review, cellular responses (hemocytes activity: phagocytosis, nodulation, and encapsulation) and humoral responses (reactions or soluble molecules released in the hemolymph as antimicrobial peptides, melanization, clotting, free radical production, and primary immunization) are discussed, highlighting the use of G. mellonella as a model of immune response to different human pathogenic microorganisms.