Human-AI Co-Creation Approach to Find Forever Chemicals Replacements

Generative models are a powerful tool in AI for material discovery. We are designing a software framework that supports a human-AI co-creation process to accelerate finding replacements for the ``forever chemicals''-- chemicals that enable our modern lives, but are harmful to the environment and the human health. Our approach combines AI capabilities with the domain-specific tacit knowledge of subject matter experts to accelerate the material discovery. Our co-creation process starts with the interaction between the subject matter experts and a generative model that can generate new molecule designs. In this position paper, we discuss our hypothesis that these subject matter experts can benefit from a more iterative interaction with the generative model, asking for smaller samples and ``guiding'' the exploration of the discovery space with their knowledge.Comment: 5 pages, Generative AI and HCI (GenAICHI) Workshop at CHI 23 (ACM CHI Conference on Human Factors in Computing Systems

GUI2WiRe: Rapid wireframing with a mined and large-scale GUI repository using natural language requirements

High-fidelity Graphical User Interface (GUI) prototyping is a well-established and suitable method for enabling fruitful discussions, clarification and refinement of requirements formulated by customers. GUI prototypes can help to reduce misunderstandings between customers and developers, which may occur due to the ambiguity comprised in informal Natural Language (NL). However, a disadvantage of employing high-fidelity GUI prototypes is their time-consuming and expensive development. Common GUI prototyping tools are based on combining individual GUI components or manually crafted templates. In this work, we present GUI2WiRe, a tool that enables users to retrieve GUI prototypes from a semi-automatically created large-scale GUI repository for mobile applications matching user requirements specified in Natural Language (NLR). We extract multiple text segments from the GUI hierarchy data and employ various Information Retrieval (IR) models and Automatic Query Expansion (AQE) techniques to achieve ad-hoc GUI retrieval from NLR. Retrieved GUI prototypes mined from applications can be inserted in the graphical editor of GUI2WiRe to rapidly create wireframes. GUI components are extracted automatically from the GUI screenshots and basic editing functionality is provided to the user. Finally, a preview of the application is created from the wireframe to allow interactive exploration of the current design. We evaluated the applied IR and AQE approaches for their effectiveness in terms of GUI retrieval relevance on a manually annotated collection of NLR and discuss our planned user studies

The Silent Threat of Non-native Fish in the Amazon: ANNF Database and Review

Non-native fish (NNF) can threaten megadiverse aquatic ecosystems throughout the planet, but limited information is available for the Amazon Region. In this study we review NNF data in the Amazonian macroregion using spatiotemporal records on the occurrence and the richness of NNF from a collaborative network of 35 regional experts, establishing the Amazon NNF database (ANNF). The NNF species richness was analyzed by river basin and by country, as well as the policies for each geopolitical division for the Amazon. The analysis included six countries (Brazil, Peru, Bolivia, Ecuador, Venezuela, and Colombia), together comprising more than 80% of the Amazon Region. A total of 1314 NNF occurrence records were gathered. The first record of NNF in this region was in 1939 and there has been a marked increase in the last 20 years (2000–2020), during which 75% of the records were observed. The highest number of localities with NNF occurrence records was observed for Colombia, followed by Brazil and Bolivia. The NNF records include 9 orders, 17 families and 41 species. Most of the NNF species are also used in aquaculture (12 species) and in the aquarium trade (12 species). The most frequent NNF detected were Arapaima gigas, Poecilia reticulata and Oreochromis niloticus. The current data highlight that there are few documented cases on NNF in the Amazon, their negative impacts and management strategies adopted. The occurrence of NNF in the Amazon Region represents a threat to native biodiversity that has been increasing “silently” due to the difficulties of large-scale sampling and low number of NNF species reported when compared to other South American regions. The adoption of effective management measures by decision-makers is urgently needed and their enforcement needed to change this alarming trend and help protect the Amazon’s native fish diversity.

NEOTROPICAL ALIEN MAMMALS: a data set of occurrence and abundance of alien mammals in the Neotropics

Biological invasion is one of the main threats to native biodiversity. For a species to become invasive, it must be voluntarily or involuntarily introduced by humans into a nonnative habitat. Mammals were among first taxa to be introduced worldwide for game, meat, and labor, yet the number of species introduced in the Neotropics remains unknown. In this data set, we make available occurrence and abundance data on mammal species that (1) transposed a geographical barrier and (2) were voluntarily or involuntarily introduced by humans into the Neotropics. Our data set is composed of 73,738 historical and current georeferenced records on alien mammal species of which around 96% correspond to occurrence data on 77 species belonging to eight orders and 26 families. Data cover 26 continental countries in the Neotropics, ranging from Mexico and its frontier regions (southern Florida and coastal-central Florida in the southeast United States) to Argentina, Paraguay, Chile, and Uruguay, and the 13 countries of Caribbean islands. Our data set also includes neotropical species (e.g., Callithrix sp., Myocastor coypus, Nasua nasua) considered alien in particular areas of Neotropics. The most numerous species in terms of records are from Bos sp. (n = 37,782), Sus scrofa (n = 6,730), and Canis familiaris (n = 10,084); 17 species were represented by only one record (e.g., Syncerus caffer, Cervus timorensis, Cervus unicolor, Canis latrans). Primates have the highest number of species in the data set (n = 20 species), partly because of uncertainties regarding taxonomic identification of the genera Callithrix, which includes the species Callithrix aurita, Callithrix flaviceps, Callithrix geoffroyi, Callithrix jacchus, Callithrix kuhlii, Callithrix penicillata, and their hybrids. This unique data set will be a valuable source of information on invasion risk assessments, biodiversity redistribution and conservation-related research. There are no copyright restrictions. Please cite this data paper when using the data in publications. We also request that researchers and teachers inform us on how they are using the data

NEOTROPICAL CARNIVORES: a data set on carnivore distribution in the Neotropics

Mammalian carnivores are considered a key group in maintaining ecological health and can indicate potential ecological integrity in landscapes where they occur. Carnivores also hold high conservation value and their habitat requirements can guide management and conservation plans. The order Carnivora has 84 species from 8 families in the Neotropical region: Canidae; Felidae; Mephitidae; Mustelidae; Otariidae; Phocidae; Procyonidae; and Ursidae. Herein, we include published and unpublished data on native terrestrial Neotropical carnivores (Canidae; Felidae; Mephitidae; Mustelidae; Procyonidae; and Ursidae). NEOTROPICAL CARNIVORES is a publicly available data set that includes 99,605 data entries from 35,511 unique georeferenced coordinates. Detection/non-detection and quantitative data were obtained from 1818 to 2018 by researchers, governmental agencies, non-governmental organizations, and private consultants. Data were collected using several methods including camera trapping, museum collections, roadkill, line transect, and opportunistic records. Literature (peer-reviewed and grey literature) from Portuguese, Spanish and English were incorporated in this compilation. Most of the data set consists of detection data entries (n = 79,343; 79.7%) but also includes non-detection data (n = 20,262; 20.3%). Of those, 43.3% also include count data (n = 43,151). The information available in NEOTROPICAL CARNIVORES will contribute to macroecological, ecological, and conservation questions in multiple spatio-temporal perspectives. As carnivores play key roles in trophic interactions, a better understanding of their distribution and habitat requirements are essential to establish conservation management plans and safeguard the future ecological health of Neotropical ecosystems. Our data paper, combined with other large-scale data sets, has great potential to clarify species distribution and related ecological processes within the Neotropics. There are no copyright restrictions and no restriction for using data from this data paper, as long as the data paper is cited as the source of the information used. We also request that users inform us of how they intend to use the data