bluuebunny/crossref_metadata_2025 huggingface dataset:
Corrección quirúrgica de ruptura traumática total de uretra membranosa en un canino: reporte de caso
Authors: Pedraza Castillo L. N. , Roque Rodríguez A. I.
Published: January 2024

Este reporte de caso describe la reparación quirúrgica de una ruptura traumática total de uretra membranosa de un paciente macho canino de 5 años de edad, raza mestiza que fue atropellado tres días atrás por un automóvil.

 En este procedimiento fue usada la técnica descrita por Fossum 2019 con modificaciones realizadas por la experiencia quirúrgica de los autores en donde se utilizó un punto de fijación prostático que permitió disminuir las fuerzas de tensión ejercidas por la vejiga y el tamaño del defecto. En casos de trauma abdominal la presencia de comorbilidades se asocia a peor pronóstico, en este caso, el uroabdomen que fue tratado de forma inmediata. El paciente permanece en posoperatorio durante 4 semanas y 14 meses después presenta perfecto funcionamiento del tracto urinario inferior con flujo normal de orina, considerándose que la técnica fue exitosa. Se administraron antibióticos sistémicos, antiinflamatorios y el cierre completo de la herida se da tres semanas después. El objetivo de este trabajo es presentar una técnica poco invasiva y sin complicaciones intraoperatorias en la cual se modifica el procedimiento conservador generando un resultado exitoso sin que sea necesaria la realización de una osteotomía púbica la cual además de ser altamente invasiva con los tejidos, es bastante dolorosa para el paciente.
Can debarking affects sex ratio, population structure and spatial segregation?: insights of unsustainable harvesting in a Mesoamerican tropical tree
Authors: Beltrán Leonardo , Romero-Manzanares Angélica , Ticktin Tamara , Blancas José , Martínez-Ballesté Andrea , Gaoue Orou , Bye Robert
Published: January 2024

The ecological mechanisms that contribute to maintaining plant populations have been exhaustively examined around the world, but the relative quantification of the effect of anthropogenic processes on these mechanisms in tropical dioecious tree species has not been revealed yet. The aim of this study was to analyze the effect of debarking on the sex ratio, population structure, distribution and spatial correlation between the sexes and growth stages of Amphipterygium adstringens (Anaciardiaceae), a dioecious tree species that is highly exploited for its medicinal bark. We found differences in plant density between harvested and non-harvested stands. The sex ratio was 1.33♂:1♀ in harvested stands while the opposite was true for non-harvested stands (1.27♀:1♂), which suggest that selective debarking drives androic-skewed and has an impact on reproductive performance. However, despite the dominance of a certain sex in the relative frequencies under each condition, we did not register spatial sex segregation since the analysis suggests that the spatial independence pattern does not differ between sites. In contrast, facilitation requirements (spatial attraction) between androic plants and seedlings, and between seedlings and saplings were found in non-harvested areas, while spatial uniformity patterns on a population level suggest strategies to avoid competition over space and finite resources in stressful environments. These novel findings point out that debarking constitutes a factor that not only modifies the spatial and population structure of a Mesoamerican tropical tree, but it can also influence sex ratio, consequently affecting the long-term conservation of A. adstringens stands.
Optimal time task in saccadic eye movement
Authors:   Lomonosov Moscow State University, Kruchinina Anna
Published: January 2024

This article is devoted to fast goal-directed human eye movements. Such movements are described in few ways. One of them is the time-optimal problem model. It this work, the saccade – fast single conformable ballistic eye movement, is under consideration. Saccadic eye trajectory is described by time-optimal task solution. Differential equations system are based on pendulum model. It defines control moment applied from extraocular muscles to eye globe and movement of it. Main feature of the system is all values in suggested system have physical meaning and were found in published experimental investigations. Consideration of the moment applied from extraocular muscles to eye glob as control is main difference of the system from other models for eye movement in submitted works. In this case, the open-loop system has two real roots and one zero. The particular case of the ratio of real roots of 1:3 is analyzed in the article. As a result of modelling, trajectory characteristics closed to the saccades observed in experimental studies is obtained. On the basis of the constructed model, the parameters of the synthesized saccades were compared with the parameters obtained on the experimental sample. The obtained models can be used both for problems of physiology and medicine, and for constructing virtual reality environments. For example, when developing 3D interfaces, the use of a mathematical model makes it possible to optimize the elements arrangement using game theory.
An electromyography system, kinetics and kinematics variables are insufficient to predict the failure-to-recover an impending loss of balance
Authors:   Pontifical Catholic University of Parana, Aguiar Matheus Lucas , Papcke Calue , Scheeren Eduardo Mendonca
Published: January 2024

The body balance maintenance is performed through synchronized motor strategies, to preserve functional mobility. The purpose of this study is to compare the balance recovery mechanisms among young adults in an impending loss of balance. Thirty healthy young adult [age 24.87±4.16; weight 72.69±14.73 kg; growth 1.72±0.08 m] participated in the study. Seven perturbations were applied with a progressive velocity of the perturbation, in the antero-posterior direction. The following variables were analyzed: active time of muscle contraction, latency and displacement amplitude of the center of pressure, and angular variation of the ankle. For each perturbation, the subjects were classified according to their ability to recover balance: “no step” and step forward or hold the rope of the safety vest support. There were no significant differences between groups in all variables analyzed. At lower velocities of displacement, the group of “no step” presented greater angular variation for the knee joint, lower pressure center displacement range, and lower active time of normalized contraction of the muscle anterior tibial. The results suggest that the variables analyzed were insufficient to identify significant differences in the adoption of strategies for recovery of balance in an impending loss of balance.
Students' Economic Status and Access to Technology in Relation to Their Academic Stress on Online Learning at the University of Bohol
Authors: Penaflor Kim , Acera Mae Arcely , Melencion Esther Jay , Ampac Ma. Ella May , Toribio Angela , Gaterin Karla Mari , Agan Marian , Doloritos Glenn Lawrence , Oracion Xenita Vera , Jamora Bonnibella , Lumanas Kristine Mae
Published: January 2024

Socioeconomic status refers to the family's social and economic standing in society. It is measured by combining an individual or group's economic and social position, which is often based on income, education, and occupation. It significantly affects academic performance and even one's health status. The pandemic changed the educational system, causing a huge transition from traditional learning methods to online learning. This shift resulted in confusion, burden, and difficulty among students from different walks of life. This study was conducted to determine the academic stress on online learning among nursing students in relation to their economic status and their ability to access technology. The study utilized a quantitative-correlational method aided by a standard questionnaire. Two hundred thirty-six University of Bohol nursing students enrolled in the second semester of SY 2021–2022 were included in the study by random selection. Data revealed a significant correlation between economic status and the level of stress related to academic expectations and a significant correlation between economic status and access to technology after being subjected to the Spearman rho test of correlation. However, no significant correlation was found between access to technology and the respondents' level of academic stress.
Siedemnastowieczne Nabożeństwo abo pozdrowienie Błogosławionej Bronisławy. Szkic teolingwistyczny
Authors: Mączyński Maciej
Published: January 2024

The paper reads the meanings contained in the language of the seventeenth century prayer entitled Devotion or Greetings to Blessed Bronisława. The text of the prayer comes from the manuscript prayer book held in the convent of the Norbertine nuns in Krakow in Zwierzyniec. The analysis showed that both the structure of the text and the meanings embedded in its linguistic layer do not differ from the prayers created in the circle of the Premonstratensian monastery. The text represents a prayer of petition addressed to God through Bronisława’s intercession for the necessary favors for the congregation, which will allow the nuns to imitate the life and virtues of Blessed Bronisława.
PISA Science Score: A Good Indicator of Competence in S & T?
Authors:   University of Science and Technology Liaoning, Anshan, China, Shi Wei-Zhao
Published: January 2024

In this study, the data from the Programme for International Student Assessment (PISA) are used to investigate whether the PISA science test score is a good indicator of competence in science and technology. The researcher uses a number of scientific and technical journal articles per million people as a measure instrument to represent the competence of science and technology. A regression model analysis suggests that the PISA science scores would significantly predict competence in S & T, even when controlling the number of researchers in R&D per million people and the R&D expenditure (% of GDP). Moreover, it shows that R&D expenditure (% of GDP) is another important determinant of the competence in S & T. Multicollinearity is also found between the R&D expenditure (% of GDP) and the number of researchers in R&D per million people. The policy implication is clear.
Latent Structure of the Curriculum for Primary Teacher Education in Serbia
Authors:   University of Novi Sad, Rodić Nedeljko , Rodić Lukić Vesna N. ,   University of Novi Sad
Published: January 2024

This paper attempts to determine the latent structure of the curriculum for primary school teacher education in the first cycle of studies at Serbian teacher training and education faculties. By applying the factor analysis into the first level of teacher education, four latent dimensions could be identified that could be nominated as General Education, Basic Education, Methodological Education, Specific Education, and one bipolar factor. The results indicate that learning outcomes and competences in certain fields of instruction should be re-examined and re-directed in line with the experience of the EU countries in order to harmonize and modernize the curriculum for primary teacher education in Serbia.
Language and Adaptation Barriers of Polish 1.5 Generation in Ireland
Authors:   Koszalin University of Technology, Augustyniak Joanna
Published: January 2024

The decision about emigration for economic reasons, including emigration to Ireland, after Poland joining the European Union, has been the object of research interests of a number of fields of knowledge. Sometimes, a tempting vision of improving Polish people’s own economic status makes them decide to leave the homeland without any knowledge about the culture of the adopted society. The article is focused on the analysis of the language competence of Polish grammar school students in Ireland. There are presented weaknesses and strategies for surviving in the new environment without language skills and its influence on adaptation to school and life in Ireland. The article is supported by the research conducted in Irish grammar schools and Polish weekend schools in Ireland (2010–2011).
Causes and Consequences of Labelling Gifted Pupils at Selected Elementary Schools
Authors:   Tomas Bata University in Zlín
Published: January 2024

The article describes qualitative research analyzing causes and consequences of labelling gifted pupils. Causes and consequences were identified after an analysis of semi-structured interviews with gifted pupils, their classmates and teachers. Identified causes included certain pedagogical strategies such as excluding a gifted pupil from a group of their peers, using specific names for classes, excessive media coverage of specialized classes and pupils. Labelling was further promoted by a curriculum differing in its content, processes and materials offered to gifted pupils only. Consequences of labelling included ostracism and ridiculing of gifted pupils by their classmates, rivalry and hostility. The article concludes with proposals which might help to reduce labelling.
Psychological Factors Determining the Choice of a Future Job
Authors:   Instytut Psychologii UMCS, Lublin, Markiewicz Katarzyna , Kaczmarek Bożydar ,   Wyższa Szkoła Ekonomii i Innowacji w Lublinie
Published: January 2024

At the time of an economic crisis and its psychological consequences the attitudes and activity of young adults, who are just starting their vocational life, are of great significance. Graduates from colleges and universities are a very important group among them. Their abilities have an impact upon the intellectual potential of the country’s economy, and consequently upon its novelty. The presented research concentrated upon the knowledge of graduates about ongoing changes and tendencies in the labour market, and their ability to communicate their needs in this respect. The study comprised 602 students of the final years of B.A. and M.A. studies, since they are confronted with making a decision concerning their future jobs. Decisions made at that time have a long-lasting influence on the quality of their life. It is therefore worthwhile to acquire better knowledge on the inner motives of their choices.
A Stigmatising Stereotype or a Universal Gap in Expectations? Lessons in Mathematics in the Perception of Polish and Ukrainian Students
Authors:   Maria Curie Skłodowska University, Turska Dorota
Published: January 2024

Referring to the results of the authors’ own research published in The New Educational Review (Turska, Bernacka 2010; Turska 2011), this article attempts at competitive verification of a hypothesis that explains differences in the perception of a mathematics teacher by Polish male and female students in view of a popular stereotype that Mathematics is a domain for males. It was assumed that diverse perceptions may result from different interpersonal expectations of the two genders. A comparative study carried out on a group of Ukrainians, established in accordance with the principles of ecological validity, seems to further substantiate the stigmatising effect of the stereotype in Poland.
Econometric Modelling of the Perceptions Students have Regarding the Probability of Finding a Job in the Field of the Master’s Programme
Authors:   Babes-Bolyai University of Cluj Napoca, Mare Codruta , Popa Irimie ,   Babes-Bolyai University of Cluj Napoca, Dinu Vasile ,   Bucharest University of Economic Studies, Dragos Cristian ,   Babes-Bolyai University of Cluj Napoca, Universite d’Orleans, Laboratoire d‘Economie d‘Orléans
Published: January 2024

The labour market in any field becomes more and more demanding and specialized, professional. For a more efficient absorption of graduates, the professional environment requires both advanced theoretical knowledge and practical abilities. During the study period, based on rational mechanisms, students form a perception related to the probability of finding an adequate job. In this article we model the constructed perceptions through Ordered Logit models. The application regards 88 students from two Romanian universities. The programme they are involved in is called “The Audit and Financial Management of European Funds”. The results obtained are in accordance with the logical mechanisms evidenced in the theoretical part. The explanatory variables that are statistically significant relate both to the scholarly results and to the student’s status on the labour market. The conclusions drawn are not limited only to the evaluated sample. They are easy to generalize, with necessary changes, to any university specialization.
A Cross-Cultural Study of Online Marketing in International Higher Education – a Keyword Analysis
Authors:   University of Economics, Prague, Kincl Tomáš , Novák Michal ,   University of Economics, Prague, Štrach Pavel ,   Škoda Auto University, Mladá Boleslav
Published: January 2024

Higher education is a dynamic global industry with a highly competitive and developed market. Universities communicate their international programs to attract prospective students interested in studying abroad. This study addresses a question whether there is a difference between communicated characteristics of international programs among universities from various cultures. Websites of seventy universities coming from different cultural clusters are analysed using data-mining methods. The results suggests that marketing communications in international higher education do not stand on cultural grounds as there are only minor differences between international program communications across the world. The only difference in the group of prime international higher education providers was found between the Anglo-Saxon universities and the rest of the world.
Pedagogy of the Heart – Needed or Inconvenient in the 21st Century? An Attempt at Critical Analysis
Authors:   Higher Vocational State School in Włocławek, Moraczewska Barbara ,   assistant professor at the Gdansk Higher School of Humanities
Published: January 2024

According to the assumptions of the pedagogy of the heart, the child must always feel secure and needs to have at least one close person beside him or her at all times. If this condition is not possible to be fulfilled, one should answer the following question: is the pedagogy of the heart still needed in child upbringing in the times which are not only difficult, but sometimes even hostile to contemporary man? Or perhaps the pedagogy of the heart becomes unnecessary, since it is inconvenient and unwanted by parents struggling with the everyday challenges of ever-changing, more and more demanding and unpredictable reality?
Respect between Pupils and School Staff – One of the Characteristic Features of Inclusion
Authors:   Masaryk University Brno, Kratochvílová Jana , Havel Jiří ,   Masaryk University Brno
Published: January 2024

We perceive communication, cooperation, application of differentiation and individualization, maximum expectation from pupils and respect among participants of education, as characteristic features of inclusive education. In this paper we carry out qualitative and quantitative analyses of data obtained from six selected indicators relating to respect in Czech primary schools, which we perceive as a necessary condition for inclusion.
The Contribution of Sport to Prosocial Behavior in Youth
Authors:   University of Novi Sad, Knežević Florić Olivera , Ninković Stefan ,   University of Novi Sad
Published: January 2024

For proper organization of sport and physical education in general, it is necessary to obtain empirical evidence on how sport influences youths’ social and moral development. To that effect, the research aim was to provide empirical data on the existence or non-existence of a connection between doing sport and prosocial behavior of the young. An appropriate questionnaire of pro-social behavior estimation was implemented on the sample of 61 students aged 12–14. The research findings show that there is a significant difference in the level of display of certain forms of prosocial behavior among the young athletes and their peers that are not engaged in some organized sport activities. Further, it was established that the type of sport influences the level of pro-social behavior manifestation. It was not found whether the length of doing sport is correlated with the pro-social behavior of adolescents. The results obtained point that organized sport activities represent the context having positive effects on the development of pro-social behavior of the young.
Mentoring Student Training, what Is Important?
Authors:   University of Vigo, Raposo-Rivas M. , Martinez-Figueira E. ,   University of Vigo
Published: January 2024

Numerous activities and tasks are performed in the course of the tutorial during student training, but not all have the same importance for the tutor. We approach this answer through a wider investigation (Martinez, 2010) conducted in two phases: an initial qualitative one using an interview as a tool for obtaining information, and a second one more quantitative with an electronic questionnaire. The results show the importance that tutors attribute to “being available for students”, “integration into the center” and “providing contextual knowledge and access to documentation of the institution”.
Use of Mobile Technologies to Promote Scientific Discovery Learning in Elementary School
Authors:   Hankuk University of Foreign Studies, Lee June , Koo Yangmi ,   Hankuk University of Foreign Studies, Kim Yong-Lyun ,   Hankuk University of Foreign Studies
Published: January 2024

The purpose of the study was to identify educational effects of a new learning method that integrates mobile-technology-based science learning with activity oriented discovery learning. The major finding of the study was that the mobile technology-based Science program enabled students to learn scientific knowledge through associated activities and creatively apply their knowledge to complete the mission of the learning. Also, the study found that the use of tablet PCs and SNS for scientific inquiry activities facilitated students to learn in fun ways, to collaborate with other students, and to share what they have learned with each other.
Extracting Features from the On-Line News for Making Templates Used in the Process of Educating the Next Generation of Politicians
Authors:   ", Cioca Marius ,   Lucian Blaga",   University of Sibiu, Romania, Cioca Lucian-Ionel ,   “Lucian Blaga” University of Sibiu, Romania, Cioranu Cosmin ,   UEFISCDI, Bucharest, Romania, Gifu Daniela ,   “A. I. Cuza” University of Iasi, Iasi, Romania
Published: January 2024

This paper presents an application for extracting features used in the process of education of politicians based on Open Source technologies, for extracting features from the public press; it enables the user to analyze data from text files and from the Internet. The analyzed data are from the field of politics, a topic which is both a current one and a cyclic process, occurring every four years for the parliamentary elections and every five years for the presidential elections. A specific political vocabulary was compiled for feature identification and analysis and for the interpretation of results obtained.
The Bologna Process and Teacher Training in the Czech Republic: Opinions of Academic Staff and Students about the Two-cycle System Implementation at the Faculty of Education of Charles University in Prague
Authors:   Charles University in Prague, Bendl Stanislav , Voňková Hana ,   Charles University in Prague, Zvírotský Michal ,   Charles University in Prague
Published: January 2024

One goal of the Bologna process is to restructure European university programs from monolithic five-year programs into two cycles, bachelor’s and master’s. In this paper, we ask academic staff (n=52) and students (n=126) at the Faculty of Education of Charles University in Prague about their opinions on the implementation of the two-cycle system at their faculty. Nine out of ten academic staff and three out of ten students prefer the old five-year programs, arguing that the two-cycle system is not suitable for teacher training, subject courses are not sufficiently linked with teaching courses and that bachelor’s graduates cannot find jobs at schools. Students tend to prefer the two-cycle system, mostly because they get the bachelor’s degree. Our results can be used as empirical evidence in discussion about possible changes of teacher training programs.
What do University Teachers Think about the Teaching in Ethics and Citizenship in the European Higher Education Area?
Authors:   University of Barcelona, Esteban Francisco , Buxarrais Maria Rosa ,   University of Barcelona, Mellen Teodor ,   ESADE University
Published: January 2024

Ethics and citizenship education has become the focus of considerable debate since the construction of the European Higher Education Area. That this should be so is interesting, as it is a type of education that forms part of the educational mission of the university, as its history plainly demonstrates. Ethics and citizenship education cannot be analyzed solely in terms of its pedagogical requirements, the competences that it seeks to develop, or the type of students and professionals that the world needs today. Its success also requires our exploring what university teachers understand by this type of education, the situation it currently finds itself in, and how students perceive such an education. This paper presents a case study conducted among university teachers of education, philosophy and the humanities at several European institutions.
The Principles of Education Described in Studying Education , an Introduction to the Key Disciplines in Education Studies, Edited by Barry Dufour and Will Curtis in Open University Press in 2011 in the UK
Authors:   The Maria Grzegorzewska Academy of Special Education, Suwalska Arleta
Published: January 2024

This book in an accessible manner examines education disciplines in one handy volume. It provides well prepared study activities and extra notes to texts, figures and journals of particular education disciplines. In chapter one Barry Dufour presents an introduction to the history of education. Next chapter reveals the political, economic and social context for changes in contemporary education. The third chapter considers the fundamental philosophical ideas beginning with Greek philosophers and taking us forward in time to today by looking at the influential educational ideas (Dufour, Curtis, 2011). Chapter four depicts the most significant areas of the economics of education. The main sociological perspectives in education are presented in chapter five. Next chapter presents behavior, learning and intelligence as parts of the psychology of education. Comparative education through the prism of research is presented in the last chapter.
Stability and reproducibility of solid electrolyte amperometry sensors at the analysis of hydrogen in nitrogen-containing gas mixtures
Authors:   Institute of High Temperature Electrochemistry of the Ural Branch of the Russian Academy of Sciences, Kalyakin Anatoly S. , Volkov Aleksander N. ,   Institute of High Temperature Electrochemistry of the Ural Branch of the Russian Academy of Sciences, Gorshkov Maxim Yu. ,   Institute of High Temperature Electrochemistry of the Ural Branch of the Russian Academy of Sciences
Published: January 2024

This paper illustrates the results of long-term tests on the stability of the output signal of the solid electrolyte amperometry sensor when measuring the hydrogen concentration in the H2 + N2 gaseous mixture. The obtained experimental data verify the stability and reproducibility of the sensor output signal for hydrogen concentration measurements in the nitrogen-containing gaseous mixture during > 8000 h of operation. The output signal drift, i.e., the limiting current value, was insignificant, less than ± 5 %. The sensor operation was performed at 3 temperature shifts with different time intervals; these changes did not have any impact either on the sensor integrity or on its operation. The structure of the solid electrolyte sensor, intermediate solid electrolyte / electrode layer and electrodes did not undergo any significant changes during operation. The dynamic characteristics of the sensor, the response time in particular, remained stable during the operation.
Effect of Adapting to Human Preferences on Trust in Human-Robot Teaming
Authors: Bhat Shreyas , Lyons Joseph B. , Shi Cong , Yang X. Jessie
Published: January 2024

We present the effect of adapting to human preferences on trust in a human-robot teaming task. The team performs a task in which the robot acts as an action recommender to the human. It is assumed that the behavior of the human and the robot is based on some reward function they try to optimize. We use a new human trust-behavior model that enables the robot to learn and adapt to the human's preferences in real-time during their interaction using Bayesian Inverse Reinforcement Learning.
We present three strategies for the robot to interact with a human: a non-learner strategy, in which the robot assumes that the human's reward function is the same as the robot's, a non-adaptive learner strategy that learns the human's reward function for performance estimation, but still optimizes its own reward function, and an adaptive-learner strategy that learns the human's reward function for performance estimation and also optimizes this learned reward function. Results show that adapting to the human's reward function results in the highest trust in the robot.
Hybrid Navigation Acceptability and Safety
Authors: Clement Benoit , Dubromel Marie , Santos Paulo E. , Sammut Karl , Oppert Michelle , Dayoub Feras
Published: January 2024

Autonomous vessels have emerged as a prominent and accepted solution, particularly in the naval defence sector. However, achieving full autonomy for marine vessels demands the development of robust and reliable control and guidance systems that can handle various encounters with manned and unmanned vessels while operating effectively under diverse weather and sea conditions. A significant challenge in this pursuit is ensuring the autonomous vessels' compliance with the International Regulations for Preventing Collisions at Sea (COLREGs). These regulations present a formidable hurdle for the human-level understanding by an autonomous systems as they were originally designed from common navigation practices created since the mid-19th century. Their ambiguous language assumes experienced sailors' interpretation and execution and, therefore, demands a high-level (cognitive) understanding of language and agent intentions that are beyond the capabilities of current state-of-the-art of intelligent system. This position paper highlights the critical requirement of a trustworthy control and guidance system and explores the complexities of adapting COLREGs for safe vessel-on-vessel encounters considering autonomous maritime technology competing and/or cooperating with manned vessels.
Steps towards Satisficing Distributed Dynamic Team Trust
Authors: Hunt Edmund R. , Baber Chris , Sobhani Mehdi , Milivojevic Sanja , Yusuf Sagir , Musolesi Mirco , Waterson Patrick , Maynard Sally
Published: January 2024

Defining and measuring trust in dynamic, multiagent teams is important in a range of contexts, particularly in defense and security domains. Team members should be trusted to work towards agreed goals and in accordance with shared values. In this paper, our concern is with the definition of goals and values such that it is possible to define ‘trust’ in a way that is interpretable, and hence usable, by both humans and robots. We argue that the outcome of team activity can be considered in terms of ‘goal’, 'individual/team values', and ‘legal principles’. We question whether alignment is possible at the level of 'individual/team values', or only at the 'goal' and ‘legal principles’ levels. We argue for a set of metrics to define trust in human-robot teams that are interpretable by human or robot team members, and consider an experiment that could demonstrate the notion of 'satisficing trust' over the course of a simulated mission.
Inferring the Goals of Communicating Agents from Actions and Instructions
Authors: Ying Lance , Zhi-Xuan Tan , Mansinghka Vikash , Tenenbaum Joshua B.
Published: January 2024

When humans cooperate, they frequently coordinate their activity through both verbal communication and non-verbal actions, using this information to infer a shared goal and plan. How can we model this inferential ability? In this paper, we introduce a model of a cooperative team where one agent, the principal, may communicate natural language instructions about their shared plan to another agent, the assistant, using GPT-3 as a likelihood function for instruction utterances. We then show how a third person observer can infer the team’s goal via multi-modal Bayesian inverse planning from actions and instructions, computing the posterior distribution over goals under the assumption that agents will act and communicate rationally to achieve them. We evaluate this approach by comparing it with human goal inferences in a multi-agent gridworld, finding that our model’s inferences closely correlate with human judgments (R = 0.96). When compared to inference from actions alone, we find that instructions lead to more rapid and less uncertain goal inference, highlighting the importance of verbal communication for cooperative agents.
Adversarial Threats in Climate AI: Navigating Challenges and Crafting Resilience
Authors: Calengor Sally , Katragadda Sai Prathyush , Steier Joshua
Published: January 2024

The convergence of Artificial Intelligence (AI) with climate science is a double-edged sword. AI-enhanced modeling has transformative potential for the field, but it comes with new vulnerabilities, especially from adversarial machine learning. Such adversarial tactics can distort AI-driven climate models, producing misleading projections on phenomena like sea-level changes and temperature predictions. Beyond just mod-eling, AI-enhanced systems in resource management, conserva-tion, and agriculture are at risk. Tampering with climate da-tasets can undermine decades of global research and erode trust, while adversarial misinformation campaigns can skew public discourse. Ethically, distorted data risks magnifying socio-environmental disparities. Addressing these challenges necessitates robust modeling using advanced techniques, data defense with cryptographic solutions, AI-driven infrastructure safeguards, and AI algorithms to detect and counter misinfor-mation. Simply put, securing AI in climate science is not just a technical challenge, but a global imperative.
A Generative AI Approach to Pricing Mechanisms and Consumer Behavior in the Electric Vehicle Charging Market
Authors: Chaturvedi Sarthak , Chen Edward W. , Sharma Ila P. , Isaac Asensio Omar
Published: January 2024

The electrification of transportation is a growing strategy to reduce mobile source emissions and air pollution globally. To encourage adoption of electric vehicles, there is a need for reliable evidence about pricing in pub-lic charging stations that can serve a greater number of communities. However, user-entered pricing information by thousands of charge point operators (CPOs) has created ambiguity for large-scale aggregation, increasing both the cost of analysis for researchers and search costs for consumers. In this paper, we use large language models to address standing challenges with price discovery in distributed digital data. We show that generative AI models can effectively extract pricing mechanisms from unstructured text with high accuracy, and at substantially lower cost of three to four orders of magnitude lower than human curation (USD 0.006 pennies per observation). We exploit the few-shot learning capabilities of GPT-4 with human-in-the-loop feedback—beating prior classification performance benchmarks with fewer training data. The most common pricing models include free, energy-based (per kWh), and time-based (per unit time), with tiered pricing (variable pricing based on usage) being the most prevalent among paid stations. Behavioral insights from a US nationally representative sample of 13,008 stations suggest that EV users are commonly frustrated with the slower than expected charging rates and the total cost of charging. This study uncovers additional consumer barriers to charging services concerning the need for better price standardization.
AI for Anticipatory Action: Moving beyond Climate Forecasting
Authors: Huynh Benjamin Q. , Kiang Mathew V.
Published: January 2024

Disaster response agencies have been shifting from a paradigm of climate forecasting towards one of anticipatory action: assessing not just what the climate will be, but how it will impact specific populations, thereby enabling proactive response and resource allocation. Machine learning models are becoming exceptionally powerful at climate forecasting, but methodological gaps remain in terms of facilitating anticipatory action. Here we provide an overview of anticipatory action, review relevant applications of machine learning, identify common challenges, and highlight areas where machine learning can uniquely contribute to advancing disaster response for populations most vulnerable to climate change.
NeuralFlood: An AI-Driven Flood Susceptibility Index
Authors: Lin Justice , Sreng Chhayly , Oare Emma , Batarseh Feras A.
Published: January 2024

Flood events have the potential to impact every aspect of life, economic loss and casualties can quickly be coupled with damages to agricultural land, infrastructure, and water quality. Creating flood susceptibility maps is an effective manner that equips communities with valuable information to help them prepare for and cope with the impacts of potential floods. Flood indexing and forecasting are nonetheless complex because multiple external parameters influence flooding. Accordingly, this study explores the potential of utilizing artificial intelligence (AI) techniques, including clustering and neural networks, to develop a flooding susceptibility index (namely, NeuralFlood) that considers multiple factors that are not generally considered otherwise. By comparing four different sub-indices, we aim to create a comprehensive index that captures unique characteristics not found in existing methods. The use of clustering algorithms, model tuning, and multiple neural layers produced insightful outcomes for county-level data. Overall, the four sub-indices’ models yielded accurate results for lower classes (accuracy of 0.87), but higher classes had reduced true positive rates (overall average accuracy of 0.68 for all classes). Our findings aid decision-makers in effectively allocating resources and identifying high-risk areas for mitigation.
Quantum Machine Learning in Climate Change and Sustainability: A Short Review
Authors: Nammouchi Amal , Kassler Andreas , Theocharis Andreas
Published: January 2024

Climate change and its impact on global sustainability are critical challenges, demanding innovative solutions that combine cutting-edge technologies and scientific insights. Quantum machine learning (QML) has emerged as a promising paradigm that harnesses the power of quantum computing to address complex problems in various domains including climate change and sustainability.
In this work, we survey existing literature that applies quantum machine learning to solve climate change and sustainability-related problems. We review promising QML methodologies that have the potential to accelerate decarbonization including energy systems, climate data forecasting, climate monitoring, and hazardous events predictions. We discuss the challenges and current limitations of quantum machine learning approaches and provide an overview of potential opportunities and future work to leverage QML-based methods in the important area of climate change research.
AB2CD: AI for Building Climate Damage Classification and Detection
Authors: Nitsche Maximilian , Mukkavilli S. Karthik , Kühl Niklas , Brunschwiler Thomas
Published: January 2024

We explore the implementation of deep learning techniques for precise building damage assessment in the context of natural hazards, utilizing remote sensing data. The xBD dataset, comprising diverse disaster events from across the globe, serves as the primary focus, facilitating the evaluation of deep learning models. We tackle the challenges of generalization to novel disasters and regions while accounting for the influence of low-quality and noisy labels inherent in natural hazard data. Furthermore, our investigation quantitatively establishes that the minimum satellite imagery resolution essential for effective building damage detection is 3 meters and below 1 meter for classification using symmetric and asymmetric resolution perturbation analyses. To achieve robust and accurate evaluations of building damage detection and classification, we evaluated different deep learning models with residual, squeeze and excitation, and dual path network backbones, as well as ensemble techniques. Overall, the U-Net Siamese network ensemble with F-1 score of 0.812 performed the best against the xView2 challenge benchmark. Additionally, we evaluate a Universal model trained on all hazards against a flood expert model and investigate generalization gaps across events, and out of distribution from field data in the Ahr Valley. Our research findings showcase the potential and limitations of advanced AI solutions in enhancing the impact assessment of climate change-induced extreme weather events, such as floods and hurricanes. These insights have implications for disaster impact assessment in the face of escalating climate challenges.
Deep Learning Ensembles for Improved Atmospheric Composition Modeling
Authors: Sleeman Jennifer , Keller Christoph A. , Ribaudo Christopher , Chung David , Szeto Mimi
Published: January 2024

Better forecasting of atmospheric composition is a critical aspect of environmental and climate monitoring.  Among climate and weather numeric modeling, often ensembles are used to improve the forecasting power and to quantify the uncertainty of the model. However, the numerical simulation of atmospheric chemistry, critical for composition simulations, is computationally too expensive to generate numerical composition ensembles. One way to address this problem is to use deep learning to emulate the slow physical model. In this work we study the feasibility of two different deep learning methods and show how an emulator could be used to realistically estimate uncertainties of atmospheric composition forecasts, bypassing the need to run costly numerical ensemble simulations. One of the methods builds upon Fourier neural operators and the NVIDIA FourCastNet architecture and the second method builds on conditional Generative Adversarial Networks. We design the models to respond to perturbations to the most important drivers of air pollution, including meteorology and pollutant emissions. We apply this framework to the NASA GEOS Composition Forecast System (GEOS-CF), which produces daily global composition forecasts at approximately 25 km^2 horizontal resolution. Due to computational constraints, GEOS-CF currently has limited capability to produce probabilistic estimates or to optimally assimilate trace gas observations. We show how a deep learning emulator has the potential to improve composition forecasts produced by GEOS-CF or other, similar types of applications. These methods could be applied to other types of ensemble-based models, potentially providing a large speed-up in overall modeling time.
Efficient Reinforcement Learning for Real-Time Hardware-Based Energy System Experiments
Authors: Stevenson Alexander , Panwar Mayank , Hovsapian Rob , Sarwat Arif
Published: January 2024

In the context of urgent climate challenges and the pressing need for rapid technology development, Reinforcement Learning (RL) stands as a compelling data-driven method for controlling real-world physical systems. However, RL implementation often entails time-consuming and computationally intensive data collection and training processes, rendering them inefficient for real-time applications that lack non-real-time models. To address these limitations, real-time emulation techniques have emerged as valuable tools for the lab-scale rapid prototyping of intricate energy systems. While emulated systems offer a bridge between simulation and reality, they too face constraints, hindering comprehensive characterization, testing, and development. In this research, we construct a surrogate model using limited data from simulated systems, enabling an efficient and effective training process for a Double Deep Q-Network (DDQN) agent for future deployment. Our approach is illustrated through a hydropower application, demonstrating the practical impact of our approach on climate-related technology development.
Towards a Natural Language Interface for Flexible Multi-Agent Task Assignment
Authors: Brawer Jake , Bishop Kayleigh , Hayes Bradley , Roncone Alessandro
Published: January 2024

Task assignment and scheduling algorithms are powerful tools for autonomously coordinating large teams of robotic or AI agents. However, the decisions these system make often rely on components designed by domain experts, which can be difficult for non-technical end-users to understand or modify to their own ends. In this paper we propose a preliminary design for a flexible natural language interface for a task assignment system. The goal of our approach is both to grant users more control over a task assignment system's decision process, as well as render these decisions more transparent. Users can direct the task assignment system via natural language commands, which are applied as constraints to a mixed-integer linear program (MILP) using a large language model (LLM). Additionally, our proposed system can alert users to potential issues with their commands, and engage them in a corrective dialogue in order to find a viable solution. We conclude with a description of our planned user-evaluation in the simulated environment Overcooked and describe next steps towards developing a flexible and transparent task allocation system.
Skill Development through Artificial Cognitive Systems and Social Robotics Applied at Tech-Education
Authors: Souza Rodrigo F. , Lima Jr Walter T.
Published: January 2024

The focus of this research is to demonstrate how a platform composed of systems of artificial cognitive agents and social robotics can interact, teach and learn with students and teachers, through a pedagogical practice and methodological integration of the psychological concepts of the Theory of Multiple Intelligences, the educational foundations of the Dialectic methodology and the relationship explored in the Man-Machine Symbiosis.
The objective of this article is to present the cognitive methodological concept of the project developed, grounding it from the theoretical principles, to the selection criteria for the models presented in the current discussions, taking as lines of thought that seek to define the strategy for creating personalized learning storytelling, the techniques for building social robotics in education and the interactivity between visual feedback in the challenging context of technological education.
On Using Generative Models in a Cognitive Architecture for Embodied Agents
Authors: Choi Dongkyu
Published: January 2024

Recent popularity of generative models brought research on a variety of applications. We take a more architectural point of view, where we discuss ways in which generative AI techniques and cognitive architectures can benefit each other for a more capable overall integrated system. We use a cognitive architecture, ICARUS, as the framework for our discussion, but most of the discussed points should carry over to other architectures as well.