nils-herrmann/clean_scirepeval huggingface dataset:
Evaluating the Sustainable Intensification of arable farms.
Venue: Journal of environmental management
Year: 2015

Sustainable Intensification (SI) of agriculture has recently received widespread political attention, in both the UK and internationally. The concept recognises the need to simultaneously raise yields, increase input use efficiency and reduce the negative environmental impacts of farming systems to secure future food production and to sustainably use the limited resources for agriculture. The objective of this paper is to outline a policy making tool to assess SI at a farm level. Based on the method introduced by Kuosmanen and Kortelainen (2005) we use an adapted Data Envelopment Analysis (DEA) to consider the substitution possibilities between economic value and environmental pressures generated by farming systems in an aggregated index of Eco Efficiency. Farm level data, specifically General Cropping Farms (GCFs) from the East Anglian River Basin Catchment (EARBC) UK were used as the basis for this analysis. The assignment of weights to environmental pressures through linear programming techniques, when optimising the relative Eco Efficiency score, allows the identification of appropriate production technologies and practices (integrating pest management, conservation farming, precision agriculture, etc. for each farm and therefore indicates specific improvements that can be undertaken towards SI. Results are used to suggest strategies for the integration of farming practices and environmental policies in the framework of SI of agriculture. Paths for improving the index of Eco Efficiency and therefore reducing environmental pressures are also outlined.
In the Universe of Cassandra: The Ancient Topos of Clairvoyance in the Futuristic World of Minority Report (2002)
Year: 2020

The figure of Cassandra is well known from numerous representations in ancient and modern literature as an archetype of a woman who has the power to see the future, but whose visions are not believed. In ancient Greek literature, Cassandra was an important character serving as a prophet of an approaching catastrophe. In her modern adaptations, this figure became a metaphor in psychoanalytical research on human moral behaviour (Melanie Klein and the Cassandra complex) developed in feminist writing. Cassandra has also been of interest to filmmakers, with perhaps the best adaptation of the subject of Cassandra's clairvoyance being Steven Spielberg's film Minority Report. Loosely based on Philip K. Dick's 1956 short story The Minority Report, the plot presents a version of the Cassandra myth, in which a woman together with male twins operate as a group mind to predict future crimes. Their visions are used by the state to prevent the crimes and imprison the would be criminals. This article offers a thorough analysis of all the ancient and modern features of the metaphor of Cassandra employed in this movie within the overarching framework of the central theme of free will vs. determinism. According to this approach, the central theme is examined with reference to ancient Aristotelian and Stoic moral philosophy, the modern feminist psychoanalysis of Melanie Klein, and the political philosophy and legal issues in the post 9/11 world.
An Empirical Study on Large Scale Multi Label Text Classification Including Few and Zero Shot Labels
Venue: EMNLP
Year: 2020

Large scale Multi label Text Classification (LMTC) has a wide range of Natural Language Processing (NLP) applications and presents interesting challenges. First, not all labels are well represented in the training set, due to the very large label set and the skewed label distributions of LMTC datasets. Also, label hierarchies and differences in human labelling guidelines may affect graph aware annotation proximity. Finally, the label hierarchies are periodically updated, requiring LMTC models capable of zero shot generalization. Current state of the art LMTC models employ Label Wise Attention Networks (LWANs) which (1) typically treat LMTC as flat multi label classification; (2) may use the label hierarchy to improve zero shot learning, although this practice is vastly understudied; and (3) have not been combined with pre trained Transformers (e.g. BERT) which have led to state of the art results in several NLP benchmarks. Here, for the first time, we empirically evaluate a battery of LMTC methods from vanilla LWANs to hierarchical classification approaches and transfer learning, on frequent, few, and zero shot learning on three datasets from different domains. We show that hierarchical methods based on Probabilistic Label Trees (PLTs) outperform LWANs. Furthermore, we show that Transformer based approaches outperform the state of the art in two of the datasets, and we propose a new state of the art method which combines BERT with LWANs. Finally, we propose new models that leverage the label hierarchy to improve few and zero shot learning, considering on each dataset a graph aware annotation proximity measure that we introduce.
Novel Coronavirus (COVID 19) A Critical Review
Year: 2020

No one has even imagined that infection in the respiratory system in the form of pneumonia because of novel coronavirus (SARS CoV2) in small town of China, Wuhan during end of December in the year 2019 will come out as an extremely communicable infection. The World Health Organization (WHO) has acknowledged the current epidemic as a threat to whole population worldwide. At present, still we have not reached the advanced levels of research to treat and control this contagious disease. Due to lack of information about the pathogenesis and proliferation pathways of this novel corona virus, whole world is looking forward for its exact prophylaxis. On the basis of recent proofs provided by review and research articles from various gen uine sources, we tried thoroughly to summarize the various factors regarding COVID 19 like its epidemiology, clinical characteristics, diagnosis, treatment and prevention. Through this review we have made an effort to present a com mon conceptual literature on coronavirus to help community to fight against this dangerous virus, and will hope that this review will be a source of refer ence to young researchers for advanced studies.
Paradoxical side effects of green advertising: how purchasing green products may instigate licensing effects for consumers with a weak environmental identity
Venue: International Journal of Advertising
Year: 2019

Research into green advertising has mainly investigated how green appeals can enhance product attitudes, sales, and brand image. But what happens after people have purchased a 'green' product advertised in a green ad? In two experiments, we show that purchasing a green product may have paradoxical post purchase effects, such that it may lower intentions to engage in subsequent environmentally friendly behaviour (a so called licensing effect) Importantly, our results show that these post purchase effects are moderated by environmental identity: only people with a weak environmental identity show these paradoxical post purchase licensing effects, people with a strong environmental identity are more likely to continue behaving in an environmentally friendly way.
On establishing generalized analytical phase control conditions in two body self reacting point absorber wave energy converters
Year: 2020

It is widely suggested that step gains in wave energy converter power capture performance must be realized to achieve economic viability. One method of fulfilling power capture gains is to invoke resonant conditions between the device and the incoming ocean wave. However, a general method that can establish the prerequisites for achieving resonant conditions in an arbitrarily complex wave energy converter architecture is nonexistent. In this work, we present an analytical procedure, built on the mechanical circuit framework, for identifying the resonant conditions of an arbitrarily complex wave energy converter architecture. To demonstrate the procedure, we select three complex two body point absorber devices as a case study, each with a geometry controllable feature set. Through invoking resonant conditions in each architecture, we illustrate how the choice of topology has significant influence on the power capture characteristics of the WEC device. Selecting the highest performing architecture, we then reveal how the analytical equations can be applied to promote technology innovation by supplying design criterion prior to locking down the WEC design. Finally, we apply the analytics within a numerical case study and present a hierarchy describing the incremental performance improvements realized through implementing steps in control complexity for this device.
Deep Supervised Hashing for Fast Image Retrieval
Venue: International Journal of Computer Vision
Year: 2019

In this paper, we present a new hashing method to learn compact binary codes for highly efficient image retrieval on large scale datasets. While the complex image appearance variations still pose a great challenge to reliable retrieval, in light of the recent progress of Convolutional Neural Networks (CNNs) in learning robust image representation on various vision tasks, this paper proposes a novel Deep Supervised Hashing method to learn compact similarity preserving binary code for the huge body of image data. Specifically, we devise a CNN architecture that takes pairs/triplets of images as training inputs and encourages the output of each image to approximate discrete values (e.g. ,1$+1/ ,1$ 1) To this end, the loss functions are elaborately designed to maximize the discriminability of the output space by encoding the supervised information from the input image pairs/triplets, and simultaneously imposing regularization on the real valued outputs to approximate the desired discrete values. For image retrieval, new coming query images can be easily encoded by forward propagating through the network and then quantizing the network outputs to binary codes representation. Extensive experiments on three large scale datasets CIFAR 10, NUS WIDE, and SVHN show the promising performance of our method compared with the state of the arts.
Towards The Development Of A BIM Process For Infrastructure And Its Use In The Management Of Highways
Venue: 2020 IEEE International conference of Moroccan Geomatics (Morgeo)
Year: 2020

Morocco's highway infrastructure is considered as the engine of economic and social development of the country. Its monitoring and maintenance are of great importance but requires significant costs and time. With the advent of the BIM concept and its major contributions to the building sector, its projection on the road infrastructure sector is a promising solution. The creation of a BIM model reveals a great importance for monitoring the state of the highway infrastructure. The objective of our study is the development of a Scan to BIM process for the management of highway infrastructure and its exploitation in maintenance under a collaborative aspect. Our methodology is based on three steps. First, we experiment two approaches for the model creation: BIM oriented approach and infrastructure oriented approach. The second step is the integration of maintenance data in the BIM model of the highway and the third step is the collaboration around the BIM model. The study area is a highway section (Casablanca, Morocco) scanned by Mobile Mapping System. The results show that the visualization of the BIM model, the sharing of information between teams and the efficient resolution of problems are possible. The application of BIM process allows a more intelligent and efficient management of highways during their exploitation.
Eigenanalysis of Electromagnetic Structures Based on the Finite Element Method
Year: 2013

This article presents a review of our research effort on the eigenanalysis of open radiating waveguides and closed resonating structures. A two dimensional (2 D) hybrid Finite Element method in conjunction with a cylindrical harmonics expansion is established to formulate the open waveguide generalized eigenvalue problem. The key element of this approach refers to the adoption of a vector Dirichlet to Neumann map to rigorously enforce the continuity of the two field expansions along a truncation surface. The resulting algorithm was able to evaluate both surface and leaky eigenmodes. The eigenanalysis of three dimensional (3 D) structures involves vast research challenges, especially when they are electrically large and open radiating. The effort herein is focused on the electrically large case including the losses due to the finite conductivity of metallic walls and objects as well as the loading material losses. The former is introduced through impedance or Leontovich boundary condition, resulting to a non linear polynomial generalized eigenvalue problem. A straightforward linearization solution is adopted along with a more efficient alternative technique which mimics analytical approaches. For this one the linear eigenproblem formulated assuming metals as perfect electric conductors is initially solved and their finite conductivity is accounted through impedance boundary conditions enforced locally on the resulting eigenvectors. Finally, some numerical results are presented to verify the performance of these methodologies along with a discussion on their possibilities for extension to open 3D structures as well as to characteristic modes eigenanalysis.
Theories Of Social Order A Reader
Year: 2016

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TinyBERT: Distilling BERT for Natural Language Understanding
Venue: FINDINGS
Year: 2020

Language model pre training, such as BERT, has significantly improved the performances of many natural language processing tasks. However, pre trained language models are usually computationally expensive, so it is difficult to efficiently execute them on resource restricted devices. To accelerate inference and reduce model size while maintaining accuracy, we first propose a novel Transformer distillation method that is specially designed for knowledge distillation (KD) of the Transformer based models. By leveraging this new KD method, the plenty of knowledge encoded in a large "teacher" BERT can be effectively transferred to a small "student" TinyBERT. Then, we introduce a new two stage learning framework for TinyBERT, which performs Transformer distillation at both the pre training and task specific learning stages. This framework ensures that TinyBERT can capture the general domain as well as the task specific knowledge in BERT. TinyBERT4 with 4 layers is empirically effective and achieves more than 96.8% the performance of its teacher BERT Base on GLUE benchmark, while being 7.5x smaller and 9.4x faster on inference. TinyBERT4 is also significantly better than 4 layer state of the art baselines on BERT distillation, with only ~28% parameters and ~31% inference time of them. Moreover, TinyBERT6 with 6 layers performs on par with its teacher BERT Base.
HUBUNGAN PENYESUAIAN DIRI DAN MOTIVASI BELAJAR DENGAN PRESTASI BELAJAR SISWA
Year: 2020

Penelitian ini bertujuan: (1) mendeskripsikan penyesuaian diri siswa, (2) mendeskripsikan motivasi belajar siswa, (3) mendeskripsikan prestasi belajar siswa, (4) menguji apakah terdapat hubungan antara penyesuaian diri, motivasi belajar dengan prestasi belajar siswa, (5) implikasi pelayanan bimbingan dan konseling dalam meningkatkan penyesuaian diri, motivasi belajar dan prestasi belajar siswa. Penelitian ini menggunakan metode kuantitatif jenis deskriptif korelasional. Populasi penelitian adalah siswa SMP Pembangunan Laboratorium UNP Padang kelas VII dan VIII tahun ajaran 2014/2015 yang berjumlah 443 orang, sampel sebanyak 210 orang, yang dipilih dengan teknik proportional stratified random sampling. Instrumen yang digunakan adalah kuesioner untuk penyesuaian diri dan kuesioner motivasi belajar. Data dianalisis dengan statistik deskriptif, regresi sederhana dan regresi ganda. Temuan penelitian memperlihatkan bahwa (1) penyesuaian diri siswa secara umum berada pada kategori baik, (2) motivasi belajar siswa secara umum berada pada kategori tinggi, (3) prestasi belajar siswa berada pada kategori tinggi, (4) terdapat hubungan penyesuaian diri dengan prestasi belajar siswa, (5) terdapat hubungan motivasi belajar dengan prestasi belajar siswa, (6) terdapat hubungan penyesuaian diri, motivasi belajar dengan prestasi belajar siswa, dan (7) implikasi hasil penelitian dijadikan sebagai masukan untuk membuat program layanan bimbingan dan konseling yang dapat meningkatkan penyesuaian diri, motivasi belajar dan prestasi belajar siswa.
Agricultural Grade Apple Cider Vinegar Is Remarkably Attractive to Drosophila suzukii (Diptera: Drosophiliadae) in Mexico
Venue: Insects
Year: 2020

Due to its availability and low cost, apple cider vinegar (ACV) is a frequently used as an attractant for monitoring the invasive spotted wing drosophila, Drosophila suzukii. In laboratory cage experiments, the attraction of ACV alone was compared with ACV in mixtures with different concentrations of acetic acid, propionic acid, different hydrolyzed proteins, synthetic fruit flavors (strawberry, blackberry and apple) and the addition of fruit nectars (grape, pineapple and apple) The addition of 5% apple nectar to ACV significantly increased fly captures, whereas other combinations were similar to or less attractive than ACV alone. Apple flavored vinegar was not attractive to flies. Captures did not vary significantly among the brands of ACV commonly sold in Mexico, except for one poorly performing brand, but cup traps baited with an agricultural grade ACV unfit for human consumption captured approximately two fold more flies than the commercial attractants Suzukii Trap, Suzukii Trap Max Captures or ACV alone in cage experiments. Field trials performed in polytunnels planted with raspberry crops in Mexico resulted in two fold to ten fold higher numbers of D. suzukii captured by the agricultural grade ACV compared to Droskidrink (a mixture of ACV, red wine and sugar) Suzukii Trap, Suzukii Trap Max Captures or edible grade ACV alone. The species selectivity of the agricultural grade ACV was similar to that of other attractants tested. Agricultural grade ACV also captured higher numbers of female than male flies in field trials. We conclude that the remarkably high attractiveness and low cost of agricultural grade ACV makes it a useful tool for monitoring D. suzukii populations in berry crops.
Anthrax outbreaks in the humans livestock and wildlife interface areas of Northern Tanzania: a retrospective record review 2006 2016
Venue: BMC Public Health
Year: 2018

BackgroundAnthrax outbreaks in Tanzania have been reported from the human, livestock and wildlife sectors over several years, and is among the notifiable diseases. Despite frequent anthrax outbreaks, there is no comprehensive dataset indicating the magnitude and distribution of the disease in susceptible species. This study is a retrospective review of anthrax outbreaks from the human, livestock, and wildlife surveillance systems from 2006 to 2016. The objectives were to identify hotspot districts, describe anthrax epidemiology in the hotspot areas, evaluate the efficiency of the anthrax response systems and identify potential areas for further observational studies.MethodsWe prepared a spreadsheet template for a retrospective comprehensive record review at different surveillance levels in Tanzania. We captured data elements including demographic characteristics of different species, the name of health facility, and date of anthrax diagnosis. Also, we collected data on the date of specimen collection, species screened, type of laboratory test, laboratory results and the outcome recorded at the end of treatment in humans. After establishing the database, we produced maps in Quantum GIS software and transferred cleaned data to Stata software for supportive statistical analysis.ResultsAnthrax reported incidences over 4 years in humans were much higher in the Arusha region (7.88/100,000) followed by Kilimanjaro region (6.64/100,000) than other regions of Tanzania Mainland. The health facility based review from hotspot districts in parts of Arusha and Kilimanjaro regions from 2006 to 2016, identified 330 human anthrax cases from the selected health facilities in the two regions. Out of 161 livestock and 57 wildlife specimen tested, 103 and 18 respectively, were positive for anthrax.ConclusionThis study revealed that there is gross under reporting in the existing surveillance systems which is an obstacle for estimating a true burden of anthrax in the hotspot districts. Repeated occurrences of anthrax in livestock, wildlife and humans in the same locations at the same time calls for the need to strengthen links and promote inter disciplinary and multi sectoral collaboration to enhance prevention and control measures under a One Health approach.
SPUNTI PER LA RIFLESSIONE SULLA COMUNICAZIONE NELL'ERA GLOBALE A PARTIRE DALLE TEORIE DI GREGORY BATESON
Year: 2015

Starting Points for the Reflection on the Communication in a Global Era from Gregory Bateson's Theory Right in the era of communication there is a risk that by abusing the word, we would paradoxically reach a non communicative situation. Gregory Bateson reveals this risk and several others in his writings, suggesting some ways to avoid them. These ways include an economy of communication and flexibility, through which to harmonize in a relational framework, elements such as word, thought and feeling on the one hand, and fidelity to the past, flexibility and openness to the future on the other hand. He also proposes some aspects of an educational model to cope with these challenges.