nils-herrmann/clean_scirepeval huggingface dataset:
Herbicide Resistant Crops: Utilities and Limitations for Herbicide Resistant Weed Management
Venue: Journal of agricultural and food chemistry
Year: 2011

Since 1996, genetically modified herbicide resistant (HR) crops, particularly glyphosate resistant (GR) crops, have transformed the tactics that corn, soybean, and cotton growers use to manage weeds. The use of GR crops continues to grow, but weeds are adapting to the common practice of using only glyphosate to control weeds. Growers using only a single mode of action to manage weeds need to change to a more diverse array of herbicidal, mechanical, and cultural practices to maintain the effectiveness of glyphosate. Unfortunately, the introduction of GR crops and the high initial efficacy of glyphosate often lead to a decline in the use of other herbicide options and less investment by industry to discover new herbicide active ingredients. With some exceptions, most growers can still manage their weed problems with currently available selective and HR crop enabled herbicides. However, current crop management systems are in jeopardy given the pace at which weed populations are evolving glyphosate resistance. New HR crop technologies will expand the utility of currently available herbicides and enable new interim solutions for growers to manage HR weeds, but will not replace the long term need to diversify weed management tactics and discover herbicides with new modes of action. This paper reviews the strengths and weaknesses of anticipated weed management options and the best management practices that growers need to implement in HR crops to maximize the long term benefits of current technologies and reduce weed shifts to difficult to control and HR weeds.
Confronting the Challenges of Graduate Education in Sub Saharan Africa and Prospects for the Future
Year: 2014

This study examines the current status of graduate education in Sub Saharan Africa. How has it been affected by the decline in donor funding, economic crises in much of Africa, the phenomenal growth in undergraduate education, and a shortage of faculty members with PhDs. One of the authors suggested in an earlier study that a short term response to the shortage of high quality graduate education might be regional graduate centers. Has that taken place? To what extent has graduate education improved and expanded? Where has growth taken place? We explore challenges facing the development of high quality graduate education including those of recruitment and retention, efforts to improve the qualifications of faculty members, funding issues, as well as research and publications. Several innovative graduate programs are examined. Finally, we make recommendations for the growth and quality improvement of graduate education including rekindling a culture of research, a focus on quality teaching, and the critical need for major investments in high quality graduate education. Cette analyse s'interesse au statut des etudes de master et de doctorat en Afrique subsaharienne. Comment ont elles ete affectees par la diminution des dons financiers, les crises economiques dans toute l'Afrique, la croissance phenomenale du nombre d'etudiants en licence, et le manque de professeurs titulaires d'un doctorat Un des auteurs a suggere dans de precedents travaux une reponse a court terme a la penurie de diplomes de master et de doctorat d'excellent niveau des centres regionaux consacres aux etudes de masters et de doctorat. Ceci a t il ete mis en place Dans quelle mesure les formations de master et de doctorat se sont elles ameliorees et leur nombre a t il augmente Ou la croissance a t elle eu lieu Nous nous attardons sur les obstacles au developpement de formations de master et de doctorat de qualite, en particulier ceux de recrutement et de retention des etudiants, les efforts pour ameliorer les qualifications des professeurs, la situation financiere ainsi que la recherche et les publications. Plusieurs formations innovantes de master et de doctorat sont examinees. Finalement, nous proposons des recommandations pour la croissance et l'amelioration de la qualite des etudes de master et de doctorat, notamment raviver la culture de recherche, se concentrer sur la qualite de l'enseignement, et le besoin critique d'investissements majeurs dans des masters et doctorats de qualite.
Business intelligence software as a service (SAAS)
Venue: 2011 IEEE 3rd International Conference on Communication Software and Networks
Year: 2011

One of the scariest aspects of doing business is the failure to come up with the right decision. This is one of the reasons why many businesses have failed because of one small wrong decision. So the aim of this paper is to develop web based business intelligence software as a service to help the enterprise to maximize the profit by analyzing the data and providing detailed graphical view of the business performance and to be able to take decision based on facts, and with the cloud computing technique the user will be able to access the data from anywhere.
The Catholic Invasion of China: Remaking Chinese Christianity
Year: 2015

Maps Chronology of Events in the Catholic Invasion of China Acknowledgments Chapter One: Catholicism and Western Imperialism in China Chapter Two: Spiritual Domination by European Catholics in Nineteenth Century China Chapter Three: European Resistance to the Emergence of an Indigenous Catholic Church Chapter Four: Love and Hysteria in Catholic Orphanages in China Chapter Five: Sexual Domination by Catholic Priests in China Chapter Six: The Misreading of the Missionary "Debacle"  List of the 120 Martyrs in China Canonized by John Paul II in 2000  Chinese Character Glossary Notes Bibliography Index About the Author
THE CONSEQUENCES OF DIVORCE FOR ADULTS AND CHILDREN: AN UPDATE
Year: 2014

The divorce rate has increased in the United States and most European countries since the 1960s. Public and scientific concern about the consequences of divorce for adults and children has generated a large research literature. Most studies find that divorced adults experience more mental and physical health problems than do married adults. Similarly, most studies find that children with divorced parents experience more mental and physical health problems than do children with continuously married parents. Available research suggests that these associations are partly spurious (due to selection effects) and partly due to the stress associated with marital disruption. People's reactions to divorce are highly variable, with the speed and degree of adjustment depending on a variety of resources and post divorce circumstances. In the United States, several types of court and community based programs appear to facilitate parents' and children's adjustment to divorce.
The HMGB1/RAGE axis triggers neutrophil mediated injury amplification following necrosis.
Venue: The Journal of clinical investigation
Year: 2019

In contrast to microbially triggered inflammation, mechanisms promoting sterile inflammation remain poorly understood. Damage associated molecular patterns (DAMPs) are considered key inducers of sterile inflammation following cell death, but the relative contribution of specific DAMPs, including high mobility group box 1 (HMGB1) is ill defined. Due to the postnatal lethality of Hmgb1 knockout mice, the role of HMGB1 in sterile inflammation and disease processes in vivo remains controversial. Here, using conditional ablation strategies, we have demonstrated that epithelial, but not bone marrow derived, HMGB1 is required for sterile inflammation following injury. Epithelial HMGB1, through its receptor RAGE, triggered recruitment of neutrophils, but not macrophages, toward necrosis. In clinically relevant models of necrosis, HMGB1/RAGE induced neutrophil recruitment mediated subsequent amplification of injury, depending on the presence of neutrophil elastase. Notably, hepatocyte specific HMGB1 ablation resulted in 100% survival following lethal acetaminophen intoxication. In contrast to necrosis, HMGB1 ablation did not alter inflammation or mortality in response to TNFor FAS mediated apoptosis. In LPS induced shock, in which HMGB1 Research Article Immunology
Conditional Facies Modeling Using an Improved Progressive Growing of Generative Adversarial Networks (GANs)
Year: 2020

10 Conditional facies modeling combines geological spatial patterns with different types of observed data, to build earth models for predictions of subsurface resources. Recently, researchers have used generative adversarial networks (GANs) for conditional facies modeling, where an unconditional GAN is first trained to learn the geological patterns using the original GANs loss function, then appropriate latent vectors are searched to generate facies models that 15 are consistent with the observed conditioning data. A problem with this approach is that the timeconsuming search process needs to be conducted for every new conditioning data. As an alternative, we improve GANs for conditional facies modeling by introducing an extra condition based loss function and adjusting the architecture of the generator to take the conditioning data as inputs, based on progressive growing of GANs. The condition based loss 20 function is defined as the inconsistency between the input conditioning value and the corresponding characteristics exhibited by the output facies model, and forces the generator to learn the ability of being consistent with the input conditioning data, together with the learning of geological patterns. Our input conditioning factors include global features (e.g. the mud facies proportion) alone, local features such as sparse well facies data alone, and joint combination of 25 global features and well facies data. After training, we evaluate both the quality of generated facies models and the conditioning ability of the generators, by manual inspection and quantitative assessment. The trained generators are quite robust in generating high quality facies models conditioned to various types of input conditioning information.
Probing Across Time: What Does RoBERTa Know and When?
Venue: ArXiv
Year: 2021

Models of language trained on very large corpora have been demonstrated useful for natural language processing. As fixed artifacts, they have become the object of intense study, with many researchers "probing" the extent to which they acquire and readily demonstrate linguistic abstractions, factual and commonsense knowledge, and reasoning abilities. Recent work applied several probes to intermediate training stages to observe the developmental process of a large scale model (Chiang et al. 2020) Following this effort, we systematically answer a question: for various types of knowledge a language model learns, when during (pre)training are they acquired? Using RoBERTa as a case study, we find: linguistic knowledge is acquired fast, stably, and robustly across domains. Facts and commonsense are slower and more domainsensitive. Reasoning abilities are, in general, not stably acquired. As new datasets, pretraining protocols, and probes emerge, we believe that probing across time analyses can help researchers understand the complex, intermingled learning that these models undergo and guide us toward more efficient approaches that accomplish necessary learning faster.
Would Moral Machines Close the Responsibility Gap?
Year: 2020

Questions about moral machines are ever present in contemporary discourse about robots and artificial intelligence. What would a machine that acts morally be like? Is it actually possible to build one? Should we work toward this goal and why? Would observable moral behavior be sufficient for a machine to count as a moral being, or would it need some 'subjective' foundation in its inner workings? In other words: Would it be enough for a 'moral machine' to behave as if it were sensitive to our moral affairs, or would it have to be able to sense and understand our moral concerns? The present paper focuses on a few selected aspects connecting moral machines to the so called responsibility gap. By introducing a number of clarifications and a certain perspective on the issues at hand, the question of whether a technological issue should be addressed by approximating machines to humans is answered in the negative. A reflection and debate on these and further similar issues would, therefore, have to shift its focus from the isolated technological artifacts to the much wider contexts of application and socio technological interactions.
ADEA Faculty Diversity Toolkit: A comprehensive approach to improving diversity and inclusion in dental education.
Venue: Journal of dental education
Year: 2020

Population demographic shifts in the United States and Canada have led to an increasingly diverse postsecondary student population. However, the largely homogenous dental faculty in the United States and Canada does not reflect the rapidly changing student body and the diverse patient population academic dentistry has been called to serve. Therefore, recruitment and retention of diverse dental faculty in dental education must be a priority. Substantial evidence also indicates improved outcomes for faculty, students, and institutions when faculty diversity on campus is increased. Beyond the positive impact faculty diversity can deliver to the learning and working environments of an academic institution, a variety of regulatory bodies mandate good faith efforts to maintain a diverse faculty, including the Commission on Dental Accreditation (CODA) standards for dental schools and dental therapy education programs. To assist its member institutions with answering the call for improved faculty diversity, the American Dental Education Association (ADEA) worked with its members to develop the ADEA Faculty Diversity Toolkit (ADEA FDT) a landmark evidence based resource designed to assist dental education with the design and implementation of faculty recruitment and retention initiatives that can be tailored to their unique needs. This article provides an overview of the changing landscape of the United States and Canadian populations, shares the historic homogeneity of dental education faculty, provides an overview of some of the benefits associated with faculty diversity and highlights the challenges and barriers related to recruiting and retaining diverse faculty. Most importantly, it introduces the ADEA FDT and the need for dental schools and allied dental programs to use the Toolkit as a proactive resource in increasing and maintaining faculty diversity. Furthermore, it provides an overview of how to utilize and adapt the highlighted best practices and model programs to improve faculty diversity on their campuses.
Young Saudi adults and peer group purchase influence: a preliminary investigation
Year: 2012

The role that peer influence plays in shaping young adult consumers' products purchase decision cannot be overemphasized. The purpose of this paper is to investigate the role of peer influence in shaping young adult male consumers' product purchase decisions in Saudi Arabia. To measure peer influence in this study, a survey of around 200 university students aged between 16 and 30 was conducted using a structured questionnaire. Constructs were measured using well established scales. Hypotheses are tested by investigating and comparing mean levels of the susceptibility of these young adults to peer influence across four product categories. With the products studied, the overall preliminary results suggest that the levels of influence were greater in normative influence than in informational situations. The results further provide a sense of the degree to which peer influence on purchase decision could be dictated by culture. Based on t.
Dirac fermions in antiferromagnetic FeSn kagome lattices with combined space inversion and time reversal symmetry
Year: 2020

The authors demonstrate experimentally the existence of theoretically predicted antiferromagnetic Dirac states in the kagome compound FeSn, where the $P$ and $T$ symmetries are individually broken but the combined $P\phantom{\rule{0}{0ex}}T$ symmetry is present. Moreover, their theoretical analysis reveals that, due to the salient antiferromagnetic structure, the Dirac fermions can be transformed into either massless/massive Weyl or massive Dirac fermions via symmetry manipulation, and the study does report the experimental observation of Weyl like cones at the surface driven by $P\phantom{\rule{0}{0ex}}T$ symmetry breaking that is induced by the Stark effect.
GSJ: Volume 8, Issue 12, December 2020, Online: ISSN 2320 9186
Year: 2020

This study aims to identify the level of use of coconut testa resulted from Neurospora sitophila fermentation in the most effective formulation of feed for the growth of red tilapia to providing a high survival rate. This research was conducted from December 2019 to February 2020 at the Building 4 of Aquaculture and Hatchery Laboratory, Faculty of Fisheries and Marine Sciences, Padjadjaran University. It applied an experimental method using a completely randomized design (CRD) with five treatments and three replications. The treatment used feed formulation with different concentration of coconut testa content of A (0% B (5% C (10% D (15% and E (20% The parameters measured include absolute weight growth, survival rate, and water quality. Absolute weight growth, and fish survival rates were analyzed using ANOVA with an error rate of 5% Meanwhile, the water quality was analyzed using descriptive comparative analysis. The result showed that the use of 20% coconut testa produced by N. sitophila fermentation produces an optimal growth rate of red tilapia which is 0,74% with an absolut value of 0,77 gram.
Document Classification with Deep Rectifier Neural Networks and Probabilistic Sampling
Venue: TSD
Year: 2014

Deep learning is regarded by some as one of the most important technological breakthroughs of this decade. In recent years it has been shown that using rectified neurons, one can match or surpass the performance achieved using hyperbolic tangent or sigmoid neurons, especially in deep networks. With rectified neurons we can readily create sparse representations, which seems especially suitable for naturally sparse data like the bag of words representation of documents. To test this, here we study the performance of deep rectifier networks in the document classification task. Like most machine learning algorithms, deep rectifier nets are sensitive to class imbalances, which is quite common in document classification. To remedy this situation we will examine the training scheme called probabilistic sampling, and show that it can improve the performance of deep rectifier networks. Our results demonstrate that deep rectifier networks generally outperform other typical learning algorithms in the task of document classification.
Severity of Autism is Related to Children's Language Processing
Venue: Autism research official journal of the International Society for Autism Research
Year: 2014

Problems in language processing have been associated with autism spectrum disorder (ASD) with some research attributing the problems to overall language skills rather than a diagnosis of ASD. Lexical access was assessed in a looking while listening task in three groups of 5 to 7 year old children; two had high functioning ASD (HFA) an ASD severe (ASD S) group (n 16) and an ASD moderate (ASD M) group (n 21) The third group were typically developing (TD) (n 48) Participants heard sentences of the form "Where's the x?" and their eye movements to targets (e.g. train) phonological competitors (e.g. tree) and distractors were recorded. Proportions of looking time at target were analyzed within 200 ms intervals. Significant group differences were found between the ASD S and TD groups only, at time intervals 1000 1200 and 1200 1400 ms postonset. The TD group was more likely to be fixated on target. These differences were maintained after adjusting for language, verbal and nonverbal IQ, and attention scores. An analysis using parent report of autistic like behaviors showed higher scores to be associated with lower proportions of looking time at target, regardless of group. Further analysis showed fixation for the TD group to be significantly faster than for the ASD S. In addition, incremental processing was found for all groups. The study findings suggest that severity of autistic behaviors will impact significantly on children's language processing in real life situations when exposed to syntactically complex material. They also show the value of using online methods for understanding how young children with ASD process language.
Social aware forwarding in opportunistic wireless networks: Content awareness or obliviousness?
Venue: Proceeding of IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks 2014
Year: 2014

Information Centric Networking (ICN) has gained increasing attention from the research community as it is able to improve content dissemination by releasing the dependency on content location. With the current host based Internet architecture, networking faces limitations in dynamic scenarios, due mostly to host mobility. The ICN paradigm mitigates such problems by releasing the need to have an end to end transport session established during the life time of the data transfer. Moreover, the ICN concept solves the mismatch between the Internet architecture and the way users would like to use it: currently a user needs to know the topological location of the hosts involved in the communication when he/she just wants to get the data, independently of its location. Most of the research efforts aim to come up with a stable ICN architecture in fixed networks, with few examples in ad hoc and vehicular networks. However, the Internet is becoming more pervasive with powerful personal mobile devices that allow users to form dynamic networks in which content may be exchanged at all times and with low cost. Such pervasive wireless networks suffer with different levels of disruption given user mobility, physical obstacles, lack of cooperation, intermittent connectivity, among others. This paper discusses the combination of content knowledge (e.g. type and interested parties) and social awareness within opportunistic networking as to drive the deployment of ICN solutions in disruptive networking scenarios. With this goal in mind, we go over few examples of social aware content based opportunistic networking proposals that consider social awareness to allow content dissemination independently of the level of network disruption. To show how much content knowledge can improve social based solutions, we illustrate by means of simulation some content oblivious/oriented proposals in scenarios based on synthetic mobility patterns and real human traces.
Volumetric and Multi view CNNs for Object Classification on 3D Data
Venue: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Year: 2016

3D shape models are becoming widely available and easier to capture, making available 3D information crucial for progress in object classification. Current state of theart methods rely on CNNs to address this problem. Recently, we witness two types of CNNs being developed: CNNs based upon volumetric representations versus CNNs based upon multi view representations. Empirical results from these two types of CNNs exhibit a large gap, indicating that existing volumetric CNN architectures and approaches are unable to fully exploit the power of 3D representations. In this paper, we aim to improve both volumetric CNNs and multi view CNNs according to extensive analysis of existing approaches. To this end, we introduce two distinct network architectures of volumetric CNNs. In addition, we examine multi view CNNs, where we introduce multiresolution filtering in 3D. Overall, we are able to outperform current state of the art methods for both volumetric CNNs and multi view CNNs. We provide extensive experiments designed to evaluate underlying design choices, thus providing a better understanding of the space of methods available for object classification on 3D data.