nils-herrmann/clean_scirepeval huggingface dataset:
Vitamin D and the evolution of human depigmentation.

In his recent commentary, Robins (2009) disputed the role played by ultraviolet radiation (UVR), namely, the vitamin-D-producing wavelengths of ultraviolet B (UVB), in the evolution of human skin. He questioned the theory that reduced levels of pigmentation in human skin were selected to facilitate absorption of UVB. He provided evidence to support his idea that people can produce enough vitamin D in their skin, regardless of pigmentation, if they are not pursuing a modern lifestyle. He asserted that, within his framework, rickets was the only selective force that could have influenced the evolution of light pigmentation because other detrimental effects of vitamin D deficiency are unproven. As rickets is increased by industrialization, Robins concluded that ‘‘. . . vitamin D status could not have constituted the fitness differential between lightly pigmented and darkly pigmented individuals at high latitudes that favored the evolutionary selection of the former’’ (Robins, 2009). In this article, we examine the current evidence for what has been termed the ‘‘vitamin D theory,’’ and highlight the importance of UVB penetration in the evolution of human skin. We begin with an overview of the solar processes involved in cutaneous vitamin D synthesis, followed by a discussion of causal arguments and causation in the context of the vitamin D theory, and conclude with a review of physiological mechanisms and their evolutionary significance.
Rethinking Atrous Convolution for Semantic Image Segmentation

In this work, we revisit atrous convolution, a powerful tool to explicitly adjust filter’s field-of-view as well as control the resolution of feature responses computed by Deep Convolutional Neural Networks, in the application of semantic image segmentation. To handle the problem of segmenting objects at multiple scales, we design modules which employ atrous convolution in cascade or in parallel to capture multi-scale context by adopting multiple atrous rates. Furthermore, we propose to augment our previously proposed Atrous Spatial Pyramid Pooling module, which probes convolutional features at multiple scales, with image-level features encoding global context and further boost performance. We also elaborate on implementation details and share our experience on training our system. The proposed ‘DeepLabv3’ system significantly improves over our previous DeepLab versions without DenseCRF post-processing and attains comparable performance with other state-of-art models on the PASCAL VOC 2012 semantic image segmentation benchmark.
Sustainable intensification in agricultural systems.

Agricultural systems are amended ecosystems with a variety of properties. Modern agroecosystems have tended towards high through-flow systems, with energy supplied by fossil fuels directed out of the system (either deliberately for harvests or accidentally through side effects). In the coming decades, resource constraints over water, soil, biodiversity and land will affect agricultural systems. Sustainable agroecosystems are those tending to have a positive impact on natural, social and human capital, while unsustainable systems feed back to deplete these assets, leaving fewer for the future. Sustainable intensification (SI) is defined as a process or system where agricultural yields are increased without adverse environmental impact and without the conversion of additional non-agricultural land. The concept does not articulate or privilege any particular vision or method of agricultural production. Rather, it emphasizes ends rather than means, and does not pre-determine technologies, species mix or particular design components. The combination of the terms 'sustainable' and 'intensification' is an attempt to indicate that desirable outcomes around both more food and improved environmental goods and services could be achieved by a variety of means. Nonetheless, it remains controversial to some.



This review analyses recent evidence of the impacts of SI in both developing and industrialized countries, and demonstrates that both yield and natural capital dividends can occur. The review begins with analysis of the emergence of combined agricultural-environmental systems, the environmental and social outcomes of recent agricultural revolutions, and analyses the challenges for food production this century as populations grow and consumption patterns change. Emergent criticisms are highlighted, and the positive impacts of SI on food outputs and renewable capital assets detailed. It concludes with observations on policies and incentives necessary for the wider adoption of SI, and indicates how SI could both promote transitions towards greener economies as well as benefit from progress in other sectors.
EMOVO Corpus: an Italian Emotional Speech Database

This article describes the first emotional corpus, named EMOVO, applicable to Italian language,. It is a database built from the voices of up to 6 actors who played 14 sentences simulating 6 emotional states (disgust, fear, anger, joy, surprise, sadness) plus the neutral state. These emotions are the well-known Big Six found in most of the literature related to emotional speech. The recordings were made with professional equipment in the Fondazione Ugo Bordoni laboratories. The paper also describes a subjective validation test of the corpus, based on emotion-discrimination of two sentences carried out by two different groups of 24 listeners. The test was successful because it yielded an overall recognition accuracy of 80%. It is observed that emotions less easy to recognize are joy and disgust, whereas the most easy to detect are anger, sadness and the neutral state.
Realization of the Contrast Limited Adaptive Histogram Equalization (CLAHE) for Real-Time Image Enhancement

Acquired real-time image sequences, in their original form may not have good viewing quality due to lack of proper lighting or inherent noise. For example, in X-ray imaging, when continuous exposure is used to obtain an image sequence or video, usually low-level exposure is administered until the region of interest is identified. In this case, and many other similar situations, it is desired to improve the image quality in real-time. One particular method of interest, which extensively is used for enhancement of still images, is Contrast Limited Adaptive Histogram Equalization (CLAHE) proposed in  and summarized in . This approach is computationally extensive and it is usually used for off-line image enhancement. Because of its performance, hardware implementation of this algorithm for enhancement of real-time image sequences is sought. In this paper, a system level realization of CLAHE is proposed, which is suitable for VLSI or FPGA implementation. The goal for this realization is to minimize the latency without sacrificing precision.
Pointer Sentinel Mixture Models

Recent neural network sequence models with softmax classifiers have achieved their best language modeling performance only with very large hidden states and large vocabularies. Even then they struggle to predict rare or unseen words even if the context makes the prediction unambiguous. We introduce the pointer sentinel mixture architecture for neural sequence models which has the ability to either reproduce a word from the recent context or produce a word from a standard softmax classifier. Our pointer sentinelLSTM model achieves state of the art language modeling performance on the Penn Treebank (70.9 perplexity) while using far fewer parameters than a standard softmax LSTM. In order to evaluate how well language models can exploit longer contexts and deal with more realistic vocabularies and larger corpora we also introduce the freely available WikiText
Essential amino acids are primarily responsible for the amino acid stimulation of muscle protein anabolism in healthy elderly adults.

Nutritional supplementation may be used to treat muscle loss with aging (sarcopenia). However, if physical activity does not increase, the elderly tend to compensate for the increased energy delivered by the supplements with reduced food intake, which results in a calorie substitution rather than supplementation. Thus, an effective supplement should stimulate muscle anabolism more efficiently than food or common protein supplements. We have shown that balanced amino acids stimulate muscle protein anabolism in the elderly, but it is unknown whether all amino acids are necessary to achieve this effect.



We assessed whether nonessential amino acids are required in a nutritional supplement to stimulate muscle protein anabolism in the elderly.



We compared the response of muscle protein metabolism to either 18 g essential amino acids (EAA group: n = 6, age 69 +/- 2 y; +/- SD) or 40 g balanced amino acids (18 g essential amino acids + 22 g nonessential amino acids, BAA group; n = 8, age 71 +/- 2 y) given orally in small boluses every 10 min for 3 h to healthy elderly volunteers. Muscle protein metabolism was measured in the basal state and during amino acid administration via L-[ring-(2)H(5)]phenylalanine infusion, femoral arterial and venous catheterization, and muscle biopsies.



Phenylalanine net balance (in nmol x min(-1). 100 mL leg volume(-1)) increased from the basal state (P < 0.01), with no differences between groups (BAA: from -16 +/- 5 to 16 +/- 4; EAA: from -18 +/- 5 to 14 +/- 13) because of an increase (P < 0.01) in muscle protein synthesis and no change in breakdown.



Essential amino acids are primarily responsible for the amino acid-induced stimulation of muscle protein anabolism in the elderly.
Not Competent but Warm . . . Really ? Compensatory Stereotypes in the French-speaking World

Nutzungsbedingungen: Dieser Text wird unter dem "PEER Licence Agreement zur Verfügung" gestellt. Nähere Auskünfte zum PEER-Projekt finden Sie hier: http://www.peerproject.eu Gewährt wird ein nicht exklusives, nicht übertragbares, persönliches und beschränktes Recht auf Nutzung dieses Dokuments. Dieses Dokument ist ausschließlich für den persönlichen, nicht-kommerziellen Gebrauch bestimmt. Auf sämtlichen Kopien dieses Dokuments müssen alle Urheberrechtshinweise und sonstigen Hinweise auf gesetzlichen Schutz beibehalten werden. Sie dürfen dieses Dokument nicht in irgendeiner Weise abändern, noch dürfen Sie dieses Dokument für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, aufführen, vertreiben oder anderweitig nutzen. Mit der Verwendung dieses Dokuments erkennen Sie die Nutzungsbedingungen an. Terms of use: This document is made available under the "PEER Licence Agreement ". For more Information regarding the PEER-project see: http://www.peerproject.eu This document is solely intended for your personal, non-commercial use.All of the copies of this documents must retain all copyright information and other information regarding legal protection. You are not allowed to alter this document in any way, to copy it for public or commercial purposes, to exhibit the document in public, to perform, distribute or otherwise use the document in public. By using this particular document, you accept the above-stated conditions of use.
On the difficulty of automatically detecting irony: beyond a simple case of negation

It is well known that irony is one of the most subtle devices used to, in a refined way and without a negation marker, deny what is literally said. As such, its automatic detection would represent valuable knowledge regarding tasks as diverse as sentiment analysis, information extraction, or decision making. The research described in this article is focused on identifying key values of components to represent underlying characteristics of this linguistic phenomenon. In the absence of a negation marker, we focus on representing the core of irony by means of three conceptual layers. These layers involve 8 different textual features. By representing four available data sets with these features, we try to find hints about how to deal with this unexplored task from a computational point of view. Our findings are assessed by human annotators in two strata: isolated sentences and entire documents. The results show how complex and subjective the task of automatically detecting irony could be.
Real-Time Stereo Vision System: A Multi-Block Matching on GPU

Real-time stereo vision is attractive in many areas such as outdoor mapping and navigation. As a popular accelerator in the image processing field, GPU is widely used for the studies of the stereo vision algorithms. Recently, many stereo vision systems on GPU have achieved low error rate, as a result of the development of deep learning. However, their processing speed is normally far from the real-time requirement. In this paper, we propose a real-time stereo vision system on GPU for the high-resolution images. This system also maintains a low error rate compared with other fast systems. In our approach, the image is resized to reduce the computational complexity and to realize the real-time processing. The low error rate is kept by using the cost aggregation with multiple blocks, secondary matching and sub-pixel estimation. Its processing speed is 41 fps for  $2888\times 1920$  pixels images when the maximum disparity is 760.
Web Modeling Language (WebML): a modeling language for designing Web sites

Designing and maintaining Web applications is one of the major challenges for the software industry of the year 2000. In this paper we present Web Modeling Language (WebML), a notation for specifying complex Web sites at the conceptual level. WebML enables the high-level description of a Web site under distinct orthogonal dimensions: its data content (structural model), the pages that compose it (composition model), the topology of links between pages (navigation model), the layout and graphic requirements for page rendering (presentation model), and the customization features for one-to-one content delivery (personalization model). All the concepts of WebML are associated with a graphic notation and a textual XML syntax. WebML specifications are independent of both the client-side language used for delivering the application to users, and of the server-side platform used to bind data to pages, but they can be effectively used to produce a site implementation in a specific technological setting. WebML guarantees a model-driven approach to Web site development, which is a key factor for defining a novel generation of CASE tools for the construction of complex sites, supporting advanced features like multi-device access, personalization, and evolution management. The WebML language and its accompanying design method are fully implemented in a pre-competitive Web design tool suite, called ToriiSoft.
deeP ecoloGy : educational Possibilities for the twenty-first century by Fritjof Capra

Fritjof Capra’s two-part lecture presents the fundamentals of systems thinking and sustainability along with the power of an ecologically comprehensive theory to shape education to fit the needs of human development in relation to the environment. Dr. Capra aims for the big picture emphasizing that effective learning is a system embedded in the web of life, which is yet another system. It gives us the ability to see the interconnectedness of the environment, of the community, of the natural world all at once—“a network of phenomena that are fundamentally interconnected.” Capra maintains that systems theory, including systems learning, is a new way of seeing the world as living connections in which humans are playing their part in finding a real sense of belonging by working in direct contact with the natural world and all of its facets.
Block Chain Based Data Logging and Integrity Management System for Cloud Forensics

Along with the increasing use of cloud services, security threats are also increasing and attack methods are becoming more diverse. However, there are still few measures and policies to deal with security incidents in the cloud environment. Although many solutions have been proposed through research on digital forensics for responding to security incidents, but it is still difficult to prove the integrity of evidence collection and storage in the cloud environment. To solve these problems, in this paper, we propose a blockchain based data logging and integrity management system for cloud forensics. In addition, compare the performance of the proposed system with the other blockchain based cryptocurrency.
FreeCam: A Hybrid Camera System for Interactive Free-Viewpoint Video

We describe FreeCam a system capable of generating live free-viewpoint video by simulating the output of a virtual camera moving through a dynamic scene. The FreeCam sensing hardware consists of a small number of static color video cameras and state-of-the-art Kinect depth sensors, and the FreeCam software uses a number of advanced GPU processing and rendering techniques to seamlessly merge the input streams, providing a pleasant user experience. A system such as FreeCam is critical for applications such as telepresence, 3D video-conferencing and interactive 3D TV. FreeCam may also be used to produce multi-view video, which is critical to drive newgeneration autostereoscopic lenticular 3D displays.
A Study of Cloud Computing in the University Enterprise

The demand for computing resources in the university is on the increase on daily basis and the traditional method of acquiring computing resources may no longer meet up with the present demand. This is as a result of high level of researches being carried out by the universities. The 21st century universities are now seen as the centre and base of education, research and development for the society. The university community now has to deal with a large number of people including staff, students and researchers working together on voluminous large amount of data. This actually requires very high computing resources that can only be gotten easily through cloud computing. In this paper, we have taken a close look at exploring the benefits of cloud computing and study the adoption and usage of cloud services in the University Enterprise. We establish a theoretical background to cloud computing and its associated services including rigorous analysis of the latest research on Cloud Computing as an alternative to IT provision, management and security and discuss the benefits of cloud computing in the university enterprise. We also assess the trend of adoption and usage of cloud services in the university enterprise.
A Survey of Security in Software Defined Networks

The proposition of increased innovation in network applications and reduced cost for network operators has won over the networking world to the vision of software-defined networking (SDN). With the excitement of holistic visibility across the network and the ability to program network devices, developers have rushed to present a range of new SDN-compliant hardware, software, and services. However, amidst this frenzy of activity, one key element has only recently entered the debate: Network Security. In this paper, security in SDN is surveyed presenting both the research community and industry advances in this area. The challenges to securing the network from the persistent attacker are discussed, and the holistic approach to the security architecture that is required for SDN is described. Future research directions that will be key to providing network security in SDN are identified.
To Walk or Not to Walk: Crowdsourced Assessment of External Vehicle-to-Pedestrian Displays

Researchers, technology reviewers, and governmental agencies have expressed concern that automation may necessitate the introduction of added displays to indicate vehicle intent in vehicle-to-pedestrian interactions. An automated online methodology for obtaining communication intent perceptions for 30 external vehicle-to-pedestrian display concepts was implemented and tested using Amazon Mechanic Turk. Data from 200 qualified participants was quickly obtained and processed. In addition to producing a useful early-stage evaluation of these specific design concepts, the test demonstrated that the methodology is scalable so that a large number of design elements or minor variations can be assessed through a series of runs even on much larger samples in a matter of hours. Using this approach, designers should be able to refine concepts both more quickly and in more depth than available development resources typically allow. Some concerns and questions about common assumptions related to the implementation of vehicle-to-pedestrian displays are posed.
Cellular Architecture and Key Technologies for 5 G Wireless Communication Networks

--The fourth generation wireless communication systems have been deployed or are soon to be deployed in many countries. However, with an explosion of wireless mobile devices and services, there are still some challenges that cannot be accommodated even by 4G, such as the spectrum crisis and high energy consumption. Wireless system designers have been facing the continuously increasing demand for high data rates and mobility required by new wireless applications and therefore have started research on fifth generation wireless systems that are expected to be deployed beyond 2020. In this article, we propose a potential cellular architecture that separates indoor and outdoor scenarios, and discuss various promising technologies for 5G wireless communication systems, such as massive MIMO, energy-efficient communications, cognitive radio networks, and visible light communications. Future challenges facing these potential technologies are also
RACE: Large-scale ReAding Comprehension Dataset From Examinations

We present RACE, a new dataset for benchmark evaluation of methods in the reading comprehension task. Collected from the English exams for middle and high school Chinese students in the age range between 12 to 18, RACE consists of near 28,000 passages and near 100,000 questions generated by human experts (English instructors), and covers a variety of topics which are carefully designed for evaluating the students’ ability in understanding and reasoning. In particular, the proportion of questions that requires reasoning is much larger in RACE than that in other benchmark datasets for reading comprehension, and there is a significant gap between the performance of the state-of-the-art models (43%) and the ceiling human performance (95%). We hope this new dataset can serve as a valuable resource for research and evaluation in machine comprehension. The dataset is freely available at http://www.cs.cmu.edu/ ̃glai1/data/race/ and the code is available at https://github.com/ cheezer/RACE_AR_baselines.
A hybrid approach to fake news detection on social media

Fake news has grown tremendously in recent times and this growth has had a great impact on how we make a number of sensitive decisions daily including becomes our President. There have been a wide range of solutions developed to help humans distinguish between fake and real news however, the solutions rely on either a machinebased approach or a human-based approach to detection. Research in the fields of computer science, artificial intelligence and psychology research has shown the limitations in both approaches. Based on these research findings, this paper proposes a hybrid model for detecting fake news on social media using a combination of both the humanbased and machine-based detection approaches.