How Much Consistency Is Your Accuracy Worth?

Contrast set consistency is a robustness measurement that evaluates the rate at which a model correctly responds to all instances in a bundle of minimally different examples relying on the same knowledge. To draw additional insights, we propose to complement consistency with relative consistency -- the probability that an equally accurate model would surpass the consistency of the proposed model, given a distribution over possible consistencies. Models with 100% relative consistency have reached a consistency peak for their accuracy. We reflect on prior work that reports consistency in contrast sets and observe that relative consistency can alter the assessment of a model's consistency compared to another. We anticipate that our proposed measurement and insights will influence future studies aiming to promote consistent behavior in models.Comment: BlackboxNLP 2023 accepted paper camera-ready version; 6 pages main, 3 pages appendi

Evaluating Convolutional Neural Networks as a Method of EEG–EMG Fusion

Wearable robotic exoskeletons have emerged as an exciting new treatment tool for disorders affecting mobility; however, the human–machine interface, used by the patient for device control, requires further improvement before robotic assistance and rehabilitation can be widely adopted. One method, made possible through advancements in machine learning technology, is the use of bioelectrical signals, such as electroencephalography (EEG) and electromyography (EMG), to classify the user\u27s actions and intentions. While classification using these signals has been demonstrated for many relevant control tasks, such as motion intention detection and gesture recognition, challenges in decoding the bioelectrical signals have caused researchers to seek methods for improving the accuracy of these models. One such method is the use of EEG–EMG fusion, creating a classification model that decodes information from both EEG and EMG signals simultaneously to increase the amount of available information. So far, EEG–EMG fusion has been implemented using traditional machine learning methods that rely on manual feature extraction; however, new machine learning methods have emerged that can automatically extract relevant information from a dataset, which may prove beneficial during EEG–EMG fusion. In this study, Convolutional Neural Network (CNN) models were developed using combined EEG–EMG inputs to determine if they have potential as a method of EEG–EMG fusion that automatically extracts relevant information from both signals simultaneously. EEG and EMG signals were recorded during elbow flexion–extension and used to develop CNN models based on time–frequency (spectrogram) and time (filtered signal) domain image inputs. The results show a mean accuracy of 80.51 ± 8.07% for a three-class output (33.33% chance level), with an F-score of 80.74%, using time–frequency domain-based models. This work demonstrates the viability of CNNs as a new method of EEG–EMG fusion and evaluates different signal representations to determine the best implementation of a combined EEG–EMG CNN. It leverages modern machine learning methods to advance EEG–EMG fusion, which will ultimately lead to improvements in the usability of wearable robotic exoskeletons

Consequences of long-term infrastructure decisions—the case of self-healing roads and their CO2 emissions

What could be the reduction in greenhouse gas emissions if the conventional way of maintaining roads is changed? Emissions of greenhouse gases must be reduced if global warming is to be avoided, and urgent political and technological decisions should be taken. However, there is a lock-in in built infrastructures that is limiting the rate at which emissions can be reduced. Self-healing asphalt is a new type of technology that will reduce the need for fossil fuels over the lifetime of a road pavement, at the same time as prolonging the road lifespan. In this study we have assessed the benefits of using self-healing asphalt as an alternative material for road pavements employing a hybrid input–output-assisted Life-Cycle Assessment, as only by determining the plausible scenarios of future emissions will policy makers identify pathways that might achieve climate change mitigation goals. We have concluded that self-healing roads could prevent a considerable amount of emissions and costs over the global road network: 16% lower emissions and 32% lower costs compared to a conventional road over the lifecycle

Carex phyllostachys (Cyperaceae), a new species in Croatia

The occurrence of Carex phyllostachys (Cyperaceae) in the Croatian flora is documented here for the first time. This rare Euro-Caucasian species was found in June 2019 in deciduous sub-Mediterranean Quercus pubescens-Carpinus orientalis forests on Mt Mosor in central Dalmatia. This record represents the north-western distribution limit of this species. The habitat and ecology of C. phyllostachys in the Croatian flora is presented, and morphological similarities with allied species (C. distachya and C. illegitima) are discussed. An identification key for Carex species belonging to the subgenus Indocarex in Croatia is provided

Agreement on Access and Benefit-sharing for Academic Research: A toolbox for drafting Mutually Agreed Terms for access to Genetic Resources and to Associated Traditional Knowledge and Benefit-sharing

This manual contains a set of model clauses that enables users and providers of genetic resources and associated traditional knowledge to set up a legal contract that is adapted to the individual academic research situation. If mutually negotiated and agreed upon by the involved partners this agreement can yield a “Mutually Agreed Terms” ABS contract

Slant, Fan, and Narrow: the Response of Stellar Streams to a Tilting Galactic Disk

Stellar streams are sensitive tracers of the gravitational potential, which is typically assumed to be static in the inner Galaxy. However, massive mergers like Gaia-Sausage-Enceladus can impart torques on the stellar disk of the Milky Way that result in the disk tilting at rates of up to 10-20 deg/Gyr. Here, we demonstrate the effects of disk tilting on the morphology and kinematics of stellar streams. Through a series of numerical experiments, we find that streams with nearby apocenters $(r_{\rm apo} \lesssim 20~\rm{kpc})$ are sensitive to disk tilting, with the primary effect being changes to the stream's on-sky track and width. Interestingly, disk tilting can produce both more diffuse streams and more narrow streams, depending on the orbital inclination of the progenitor and the direction in which the disk is tilting. Our model of Pal 5's tidal tails for a tilting rate of 15 deg/Gyr is in excellent agreement with the observed stream's track and width, and reproduces the extreme narrowing of the trailing tail. We also find that failure to account for a tilting disk can bias constraints on shape parameters of the Milky Way's local dark matter distribution at the level of 5-10%, with the direction of the bias changing for different streams. Disk tilting could therefore explain discrepancies in the Milky Way's dark matter halo shape inferred using different streams.Comment: 24 pages (+2 appendix), 15 figures, submitted to ApJ. Comments welcome. v2: fixed rendering issue with Fig. 11 on some device

Linking a Community-based ESL Program with the MA in TESOL Practicum Course: The Tale of a Program

Immigrant adults in the United States often have limited opportunities to learn English. To address this issue and to strengthen the preparation of future English language teachers, a practicum course offered in a Master of Arts in Teaching English to Speakers of Other Languages (MA TESOL) program in California was modified to engage student teachers in the design and implementation of a community-based ESL program. This article describes how a teacher educator and three student teachers collaborated to design and implement the program; identifies the program's teaching philosophy, centered around the communicative approach; and discusses the program's learning outcomes, ranging from introducing oneself to participating in the Individualized Educational Plan meeting. As explained in the article, breaking down the walls that existed between the MA TESOL program and the community of students about whom the program theorized not only helped the ESL students the community-based program served, but it also strengthened the MA TESOL program as a whole

Glyphosate influence on nitrogen, manganese, iron, copper and zinc nutritional efficiency in glyphosate resistant soybean

Com o desenvolvimento da soja resistente ao glifosato, Roundup Ready (RR), observa-se um aumento considerável no uso desse herbicida, com aplicações de três a quatro vezes durante o ciclo da cultura. Dessa forma, essas aplicações podem estar influenciando a nutrição mineral da cultura. Objetivou-se realizar este experimento para avaliar a influência do glifosato na eficiência nutricional de N, Mn, Cu, Zn e Fe pela soja transgênica cv. 'P98R31 RR'. O experimento foi realizado em casa de vegetação, na ESALQ/USP, Piracicaba (SP), em 2009. A unidade experimental foi constituída por vaso contendo 11kg de substrato (NITOSSOLO VERMELHO Eutroférrico latossólico), com duas plantas por vaso. Os tratamentos foram arranjados em um esquema fatorial 5X5, com cinco níveis do fator Mn (0, 20, 40, 60 e 80mg dm-3) e cinco de glifosato (0; 0,648; 1,296; 1,944 e 2,592kg i.a. ha-1), sendo que o Mn foi fornecido a partir do sulfato de manganês (MnSO4.H2O). O delineamento experimental foi em blocos casualizados, com quatro repetições. Não houve influência na resposta das plantas com relação ao fator Mn. A aplicação de glifosato interferiu de forma negativa na eficiência nutricional da planta e nos teores totais de N, Mn, Cu, Zn e Fe. A utilização de glifosato causou redução ao número de nódulos e redução na produção de massa seca.After development of glyphosate-resistant (GR) soybean, there is a considerable raise in the use of this herbicide, with three to four applications during the culture cycle. Thus, these applications may be influencing the mineral nutrition of the crop. So, the aim of this research was evaluate the glyphosate influence on uptake, translocation and use efficiency of N, Mn, Cu, Zn and Fe by (GR) soybean 'P98R31' cultivar. The experiment was conducted in the greenhouse at ESALQ/USP, Piracicaba, State of São Paulo, Brazil, in 2009. The experimental unit was formed by 11kg vase-1 of soil (Rhodic Paleudult) with two plants in each vase. The treatments have been arranged in a factorial pathway 5X5, with five levels of the factor Mn (0, 20, 40, 60 and 80mg dm-3) and five of glyphosate drifts (0; 0,648; 1,296; 1,944 e 2,592kg e.a. ha-1) and the Mn was supplied by the manganese sulfate (MnSO4.H2O). The experimental design was randomized blocks, with four repetitions. There was no influence on response from plants concerning the levels of Mn used into the experiment. The application of glyphosate interfered on mineral nutrition of soybean and the total contents of N, Mn, Cu, Zn and Fe. The use of glyphosate has caused reduction of the nodules number and reduced the output of dry mass