bluuebunny/crossref_metadata_2025 huggingface dataset:
Threats to the Process of Receiving Political News from Echo Chambers and Filter Bubbles on Social Media
Authors: Januškevičiūtė Justina
Published: June 2022

The intensified selective exposure of political news on social media, personalization of the news receiving process, and emerging new information phenomena, such as filter bubbles and echo chambers, call for a rethink of the role of new digital media in a democratic society. This article analyzes the possible influence of new information phenomena on social media - information wells and filter bubbles - in receiving political news. The mechanisms and conditions of the formation of echo chambers and filter bubbles in social media are discussed in detail, and results of research conducted to date proving these phenomena are briefly presented. The article examines the possibilities of disseminating political news on social media and the restrictions on accessing comprehensive political information due to new information phenomena. The problems of political partisans' perception of the news related to these restrictions, their possible extreme actions, and their influence on democratic processes are discussed.
Intubálással biztosított spontán légzés módszerével elvégzett sublobaris tüdőreszekciók korai műtét utáni eredményei. Új műtéti eljárás
Authors: Furák József , Barta Zsanett , Lantos Judit , Németh Tibor , Pécsy Balázs , Buzás András , Vas Márton , Fabó Csongor , Szabó Zsolt , Rieth Anna , Lázár György
Published: June 2022

Bevezetés

A nem intubált spontán légző (NITS) minimál invazív (video-assisted thoracic surgery VATS) eljárás széles körben elterjedt, de felmerülnek kétségek az eljárás biztonságosságával kapcsolatosan. Ennek megoldására fejlesztettünk ki egy új, alacsonyabb kockázatú spontán légző mellkassebészeti módszert (intubált spontán ventilláció – SVI). Vizsgálatunkban az SVI sublobaris reszekciók korai posztoperatív eredményeit mutatjuk be.

Anyag és módszer

2020. május 25. és 2021. március 26. között 20 SVI VATS sublobaris reszekciót végeztünk kétlumenű intratrachealis tubus használatával.

Eredmények

A műtétre került betegek közül 9 nő és 11 férfi, az átlagos életkor 66,1 év, az átlag BMI 27,8, FEV1 89,1%, Carlson Comorbidity Index pedig 6,2 volt. A műtéti idő 61,5 perc volt, a behelyezett mellkasi drain átlagosan 1,85 nap után került eltávolításra. A kórházi ápolási napok száma 3,35 volt. A morbiditásra 5%-os értéket kaptunk. 9 esetben primer tüdődaganat került eltávolításra, 6 metastasectomiát végeztünk, 5 esetben pedig benignus elváltozás miatt történt a műtét.

Következtetés

A kétlumenű intratrachealis tubus melletti spontán ventillációs VATS sublobaris reszekciók a posztoperatív eredményeik alapján biztonságos mellkassebészeti eljárásnak tarthatók.
A neoadjuvans FLOT-terápia hatása az előrehaladott gyomor-cardia tumorok rövid távú onkológiai és sebészi kezelés eredményeire
Authors: Paszt Attila , Simonka Zsolt , Budai Krisztina , Erdős Márton , Vas Márton , Ottlakán Aurél , Szepes Zoltán , Torday László , Tiszlavicz László , Lázár György
Published: June 2022

Bevezetés

Napjainkban az előrehaladott T2–T4-stádiumú, akár regionalis nyirokcsomó érintettséggel bíró gyomor-cardia tumoros betegek esetében a terápiás algorytmus szerint neoadjuvans kezelés történik, majd azt követi a sebészeti beavatkozás.

Betegek és módszer

A neoadjuvans onkológiai kezelés − a gastro-oesophagealis junctio tumorainak esetében − korábban az epirubicin, cisplatin és fluorouracil (ECF) vagy epirubicin, cisplatin és capecitabin (ECX) kombinácioból állt (I. csoport). Az újonnan alkalmazott terápiás protokoll (FLOT-, F: 5-FU, L: leucovorin, O: oxaliplatin, T: docetaxel) vizsgálatába a resecabilisnak ítélt cT2 vagy magasabb stádiumba sorolandó nyirokcsomó-pozitív betegeket cN+) válogattuk be (II. csoport). Klinikánkon 2013. december 31. és 2021. június 1. között FLOT-kezelésen átesett, T2–T4-stádiumú cardiatumoros betegeink retrospectiv analízisét végeztük el (n = 9). Az eredményeket összehasonlítottuk a korábbi ECF/ECX-kezelésből random módon kiválasztott másik 9 beteg eredményével. Kutatásunk során vizsgáltuk az eltérő kezelési módszerek tumorregressziós változásait (TRG), lehetséges mellékhatás profiljait, az elvégzett műtétek típusait, azok onkológiai radikalitását (nyirokcsomószám, resectiós szélek).

Eredmények

A két csoport eredményeit összehasonlítva a FLOT neoadjuvans kezelésen átesett betegeknél szignifikánsan magasabb komplett pathológiai regressziót észleltünk, mint a – korábbi – ECX/ECF-kezeléseknél. A műtétek során eltávolított nyirokcsomók számában, a sebészi resectiós szélek (distalis, circumferentialis) nagyságában a csoportok között szignifikáns eltérés nem igazolódott. A vizsgálatban a leggyakoribb mellékhatásként a neutropenia jelentkezett. A leukopenia, neutropenia, hányinger jóval gyakrabban jelent meg a korábban alkalmazott (ECF/ECX) protokoll kapcsán.

Következtetés

Az előrehaladott stádiumú gyomor-cardia tumorok esetében alkalmazott új FLOT neoadjuvans kezelés szignifikánsan magasabb mértékű komplett pathológiai tumorregressziót eredményezett. Vizsgálati eredményeink alapján elmondható, hogy a kedvezőbb mellékhatás profillal rendelkező FLOT neoadjuvans kezelés, majd azt követő sebészeti beavatkozás a követendő eljárás késői cardia tumorok esetében.
A veseátültetés története Szegeden
Authors: Szederkényi Edit , Szenohradszky Pál+ , Csajbók Ernő , Lázár György
Published: June 2022

A veseátültetés magyar története 1962-ben Szegeden kezdődött, amikor Németh András (1924–1999) elvégezte az első magyarországi veseátültetést. A szegedi egyetemi oktatás centenáriuma kapcsán a szerző áttekinti az elmúlt közel 60 év eseményeit, fordulópontjait, a szegedi vesetranszplantáció fejlődését, felelevenítve az első veseátültetés hátterét, körülményeit. Az első veseátültetés során a donor a recipiens testvére volt, a műtét technikailag sikeres volt, azonban immunszuppresszió hiányában 79 nap után kilökődés következtében és dialíziskezelés hiányában a beteget elvesztették. A donor 50 év után is jó egészségnek örvendett, és mindenkit a donációra bíztatott. Több mint egy évtized után, 1973-ban Budapesten elkezdődött a szervezett veseátületési program, minisztériumi támogatással, amelyhez 1979-ben csatlakozott Szeged Csajbók Ernő és Szenohradszky Pál vezetésével. Az eltelt 42 év alatt a szegedi Transzplantációs Centrumban jelentős szakmai fejlődés, szervezeti átalakulás mellett 2021. november végéig 1701 veseátültetés történt.
Colorectális polypok ellátása
Authors: Ábrahám Szabolcs , Tóth Illés , Váczi Dániel , Lázár György
Published: June 2022

Bevezetés és célkitűzés

A colorectális polypok komplex ellátása komoly kihívást jelent nemcsak az endoszkópos szakemberek, hanem a sebészek számára is.

Anyag és módszerek

A colorectális polypok sebészeti ellátását 2014-ig a hagyományos sebészi per anum polypectomiák vagy lokális excisók (LE) jelentették a szegedi Sebészeti Klinikán. Ezen hagyományos transanális műtéti technikák hátrányai mindenki számára jól ismertek: magas resectiós szél pozitivitás arány, alacsony „en bloc” resectiós arány, valamint a magasabban, 5 cm felett elhelyezkedő léziók eltávolításának nehézségei stb. Mindezek alapján felmerült az igény, hogy a transanális műtétek technikai fejlődésével lépést tartva, nemcsak új műtéti módszert (TAMIS, transanális minimálisan invazív sebészet) vezessünk be, hanem a már jól ismert, de még nem alkalmazott műtéti technikát, úgymint a TEM (transanális endoszkópos mikrosebészet) is alkalmazni kezdjük. Klinikánkon az új sebészi módszerek bevezetése mellett fontosnak tartottuk a sebészi gasztroenterológia, azon belül is a sebészi endoszkópia humán és tárgyi feltételeinek fejlesztését, valamint bővítését is.

Eredmények/következtetések

Az újabb műtéti technikák bevezetése mellett a Sebészeti Klinika Endoszkópos Laborjának fejlesztésével komoly lépéseket tettünk a colorectalis polypok komplex, multidiszciplináris ellátásának terén.
Colitis ulcerosa laparoszkópos sebészi kezelése, rövid és hosszú távú eredmények a szegedi Sebészeti Klinikán
Authors: Tajti János , Ábrahám Szabolcs , Simonka Zsolt , Paszt Attila , Lázár György
Published: June 2022

Bevezetés

Régóta jól ismert a colorectalis sebészetben a laparoszkópos módszer evidenciákon alapuló előnye. A szegedi Sebészeti Klinikán 2005-ben került bevezetésre a minimálisan invazív technika használata a colorectalis kórképek sebészi kezelésében, mely módszer a gyulladásos bélbetegségek ellátásában is megjelent.

Anyag és módszer

A Szegedi Tudományegyetem Sebészeti Klinikáján 2005. január 1. és 2021. március 31. között 99 beteget (53 nőt és 46 férfit) műtöttünk colitis ulcerosa miatt; hagyományos módszerrel 25 (25,3%), laparoszkópos technikával 74 (74,7%) beavatkozást végeztünk. Vizsgáltuk a műtött betegek általános állapotát, a műtéti beavatkozások korai és késői eredményeit, szövődményeit.

Eredmények

Laparoszkópos műtéteket követően a passzázs megindulásának napja (1,2 ± 0,5 vs. 1,6 ± 0,7) szignifikánsan rövidebb volt. A két csoport ápolási napjainak számában (10,5 ± 3,3 vs. 11,2 ± 3,7), az intenzív osztályon töltött napok számában (2,1 ± 0,9 vs. 2,5 ± 1,6) és transzfúziós igényében (2,6 ± 2,2 vs. 2,8 ± 1,7) különbséget nem találtunk. Korai, reoperációt igénylő, illetve konzervatív kezelésre rendeződő szövődmények kapcsán a minimál invazív és a hagyományos műtéti technikák nem különböztek. Késői, 30 napon túli szövődmények terén azonban a laparoszkópia statisztikailag is igazolható előnye mutatkozott szignifikánsan alacsonyabban előforduló passzázszavar, szeptikus állapot, posztoperatív sérv kialakulása és „egyéb” szövődmények terén.

Következtetések

Tapasztalataink alapján elmondható, hogy a colitis ulcerosa sebészi kezelésében a laparoszkópos technika sürgősségi és programozott esetekben is biztonsággal, alacsony morbiditási mutatókkal alkalmazható eljárás, mely hosszú távon a nyitott műtétekhez képest kevesebb szövődménnyel jár.
Institute of the History of Religion of the USSR Academy of Sciences in 1946-47: Unsuccessful Project (According to the Letters from Klibanov's Archive)
Authors: Elena Vorontsova
Published: June 2022

In the post-war period by the efforts of V.D. Bonch-Bruevich and a number of his colleagues it was made an attempt to create a new institute in the structure of the USSR Academy of Sciences - the Institute of the History of Religion on the basis of the museums of the history of religion in Moscow and Leningrad. This project was never implemented but some materials about this period allow us to take a fresh look at the early stage of the Russian religious studies formation. The pages of the history of the Leningrad Museum of the History of Religion have been studied in sufficient detail in publications of recent years while little is known about the events in Moscow. We turn to A.I. Klibanov’s letters to his wife N.V. Yeltsina written from Moscow to Leningrad s the main source of information about these events. The letters cover the period from April 30, 1946 to February 27, 1948. The first date is the start time of work on the project of the new Institute, the last date is the re-arrest of A.I. Klibanov. The letters were prepared for printing (typed on a typewriter) and provided with handwritten comments by A.I. Klibanov. The scientist did not implement the plan of publishing his letters and memoirs. Currently these materials are stored in the A.I. Klibanov Foundation in the Archive of the Russian Academy of Sciences. The preface to the publication debunks the myth of A.I. Klibanov as a "false scientist", a "wolfhound". The difficult fate of Alexander Ilyich - scientific work, interspersed with camp terms, forced separation from his wife (also a biologist) largely reflects the path of the Soviet science. The fragments of correspondence cited in the publication, in addition to the actual history of religious studies, are full of details of post-war Soviet everyday life (the card system, difficulties with registration, problems with documents for former prisoners and, finally, the repeated wave of arrests in 1948-49). The publication of letters and comments were prepared by E.V. Vorontsova.
Drop motion during mass transfer accompanied by interphase convection
Authors: Titov Anatolii G. , Rusinova Zalina R. , Kalimullina Ekaterina A. , Vorobev Anatoliy M.
Published: June 2022

The article deals with the experimental study of the mass transfer of acetic acid from the dispersed phase (butyl acetate) to the continuous phase (water). The experiments were carried out on a laboratory column with single floating drops. The presence of the Marangoni effect during the movement of drops and its influence on the trajectories of movement of drops and the kinetics of mass transfer during extraction are shown. The influence of the Marangoni effect is most clearly observed when the driving force of the process is 0.1...0.2 mol/l.
ACADEMIC-PROFESSIONAL MOBILITY AND INTERNATIONALIZATION OF NURSING: CONTRIBUTIONS OF THE BOLOGNA PROCESS
Authors: Lino Murielk Motta , Martini Jussara Gue , Barbieri-Figueiredo Maria do Céu
Published: June 2022

ABSTRACT Objective: to understand the contributions of the Bologna Process to academic-professional mobility of Nursing. Method: a descriptive exploratory qualitative research. Open interviews were conducted with six PhD nurses, nursing professors, with more than 20 years of experience and who experienced the changes that occurred in higher education in post-Bologna nursing. The interviews took place in the Health or Nursing Schools of the north, center and south regions of Portugal, between January and March 2019, until saturation occurred by repetition. Content analysis was performed. Results: three perspectives are presented: 1) Mobility and internationalization as presuppositions to the strengthening of the economic bloc; 2) Mobility and internationalization contribute to the consolidation of a European identity; and 3) Diploma Supplement: fundamental aspect of academic-professional mobility. Conclusion: education proved to be a valid instrument for the construction of a common professional identity, considered indispensable for the strengthening of the block, with regard to the production of knowledge. The guidelines for the harmonization of university systems and the Diploma Supplement promoted scientific and cultural exchange through academic-professional mobility and intensified the dialogue between nations, which reverberate in social practices.
MOBILIDADE ACADÊMICO-PROFISSIONAL E INTERNACIONALIZAÇÃO DA ENFERMAGEM: CONTRIBUTOS DO PROCESSO DE BOLONHA
Authors: Lino Murielk Motta , Martini Jussara Gue , Barbieri-Figueiredo Maria do Céu
Published: June 2022

RESUMO Objetivo: compreender as contribuições do Processo de Bolonha para a mobilidade acadêmico-profissional de Enfermagem. Método: pesquisa descritiva, exploratória e de natureza qualitativa. Realizou-se entrevistas abertas com seis enfermeiros doutores, docentes de Enfermagem, com mais de 20 anos de atuação e que vivenciaram as mudanças ocorridas na formação superior em Enfermagem pós-Bolonha. As entrevistas ocorreram nas Escolas de Saúde ou de Enfermagem das regiões norte, centro e sul de Portugal, entre janeiro e março de 2019, até a saturação por repetição. Realizou-se análise de conteúdo. Resultados: apresentam-se três perspectivas: 1) A mobilidade e a internacionalização como pressupostos ao fortalecimento do bloco econômico; 2) A mobilidade e a internacionalização colaboram para a consolidação de uma identidade europeia; e 3) Suplemento ao Diploma: aspecto fundamental à mobilidade acadêmico-profissional. Conclusão: a educação provou ser um instrumento válido para a construção de uma identidade profissional comum, considerada indispensável para o fortalecimento do bloco, no que tange a produção de conhecimentos. As diretrizes para a harmonização dos sistemas universitários e o Suplemento ao Diploma promoveram o intercâmbio científico-cultural por meio da mobilidade acadêmico-profissional e intensificaram o diálogo entre as nações, que reverberam em práticas sociais.
Latin American bike sharing ecosystem overview: from data collection to implementation model portraits
Authors: Binatti Gabriela , Batalha Ycaro , de Castro Juliana , Oliveira Matheus de Sousa
Published: June 2022

Abstract The growth in the number of Bike Sharing Systems (BSSs) has sparked interest in their institutional arrangements, business models and operational characteristics. When compared to experiences developed in North America, Europe, and Asia, knowledge about implementing and operating BSSs in Latin America is still limited to specific case studies. Thus, this article aims to make an exploratory analysis of the characteristics of BSSs implemented in Latin American cities. To do so, the Multiple Correspondence Analysis (MCA) was applied, using data from the systems in operation during the month of December 2019, available on an online platform called LABIKS. The application of MCA proved to be an efficient and objective methodology to compare the various experiences of implementing BSSs in Latin America. Although countries share several challenges in common, the context of the region is very diverse, which justifies the different models of management and operation found in this research. Furthermore, results show significant differences in the implementation and expansion between dock-based and dockless systems in Latin America, highlighting challenges and possibilities for promoting this resilient and sustainable mode of transportation.
CULTURA INFORMACIONAL VIRTUAL E O ENSINO DE HISTÓRIA: ENTRE A PRÁXIS E AS IDENTIDADES
Authors: Soares Fabrício Antônio Antunes , Cardoso Vanilson Viana , Mueller Airton Adelar
Published: June 2022

RESUMO Na assim compreendida sociedade de conhecimento, vive-se diante de um processo de transferência da memória humana para meios eletrônicos, servidores, discos rígidos e nuvens de dados. Isso representa uma das mais notáveis modificações no ambiente da educação, sobretudo, no processo de ensino-aprendizagem da história. Diante dessa nova realidade, o artigo discute as principais diretrizes da Base Nacional Comum Curricular (BNCC), relativas ao ensino de história no ensino básico. Isso se faz com base em elementos teóricos da didática da história de Jörn Rüssen. Os resultados apontam que a BNCC, como orientação pedagógica, tem importantes limitações teóricas, identitárias e sociais, contribuindo, assim, para uma formação histórica deficitária.
CORPO EM TRANSFORMAÇÃO E A ESCOLA COMO ADVERBIO DE LUGAR: UMA REVISÃO SOBRE A FORMAÇÃO DE PROFESSORES EM EDUCAÇÃO FÍSICA
Authors: Sarti Renato , Ramos Paula
Published: June 2022

O histórico da formação em Educação Física no Brasil tem apresentado a predominância nos currículo da abordagem técnico-biológica e as fragilidades da articulação entre os cursos de licenciatura e a Escola. A presente pesquisa busca compreender como o campo de pesquisa em formação de professores de Educação Física vem explorando as temáticas corpo e escola, lançando mão de uma revisão de dissertações e teses. Foi realizada uma busca de teses e dissertações em dois bancos de dados: o Catálogo de Teses e Dissertações – CAPES; e o Banco Digital de Teses e Dissertações (BDTD). Foram três combinações para busca: Formação de professores AND educação física AND corpo AND escola; Formação docente AND educação física AND corpo AND escola; e Licenciatura AND educação física AND corpo AND escola. Foram excluídos os trabalhos repetidos e incluídos os trabalhos que tinham como cenário da pesquisa a formação inicial de professores de Educação Física e que contavam com os dois eixos de estudo de modo concomitante. A análise dos onze estudos encontrados permitiram a emergência de três categorias: as concepções de corpo; a Educação Física e/ou corpo na escola; a escola como instituição pesquisada. Ao mergulharem suas lentes sobre as compreensões do corpo, as pesquisas revelaram um importante movimento para o campo da formação de professores de Educação Física: o corpo tem contado com novas abordagens para além da perspectiva biomédica. No entanto, se a temática corpo vem sendo explorada em destaque no conjunto de pesquisas, a escola parece ostentar um espaço majoritariamente circunstancial.
Corrosion Testing for Risk Reduction in Chemical Process Development
Authors: Holt Jarle , Atkins Katie , Shapcott Stephen
Published: June 2022

This work explores some of the key factors to consider in design and implementation of corrosion testing at a laboratory scale for the development of new chemical technologies in order that process technology scale-up risks, not least those of safety, can be minimised. This is to ensure safe and reliable introduction of new process technologies, while also pursuing the minimum capital cost of often expensive plant materials of construction (MoC). Laboratory-based corrosion testing should never be used exclusively to replace inspection and monitoring of corrosion in operating process plants, as real-world conditions are rarely possible to be wholly replicated in the laboratory. However, testing as initial screening, or to provide deeper mechanistic insights is often an essential part of the development and design of first-of-a-kind process technologies. Several methodologies to assess corrosion under highly aggressive conditions have been developed and applied in the development of new chemical processes and are demonstrated in two case studies outlined in this article. This work focuses on testing of materials in contact with corrosive fluids.
Predicting Falls of a Humanoid Robot through Machine Learning
Authors: Kalyanakrishnan Shivaram , Goswami Ambarish
Published: June 2022

Although falls are undesirable in humanoid robots, they are also inevitable, especially as robots get deployed in physically interactive human environments. We consider the problem of fall prediction, i.e., to predict if a robot's balance controller can prevent a fall from the current state. A trigger from the fall predictor is used to switch the robot from a balance maintenance mode to a fall control mode. Hence, it is desirable for the fall predictor to signal imminent falls with sufficient lead time before the actual fall, while minimizing false alarms. Analytical techniques and intuitive rules fail to satisfy these competing objectives on a large robot that is subjected to strong disturbances and therefore exhibits complex dynamics. Today effective supervised learning tools are available for finding patterns in high-dimensional data. Our paper contributes a novel approach to engineer fall data such that a supervised learning method can be exploited to achieve reliable prediction. Specifically, we introduce parameters to control the tradeoff between the false positive rate and lead time. Several parameter combinations yield solutions that improve both the false positive rate and the lead time of hand-coded solutions. Learned predictors are decision lists with typical depths of 5-10, in a 16-dimensional feature space. Experiments are carried out in simulation on an Asimo-like robot.
Providing Decision Support for Cosmogenic Isotope Dating
Authors: Rassbach Laura , Bradley Elizabeth , Anderson Ken
Published: June 2022

Human experts in scientific fields routinely work with evidence that is noisy and untrustworthy, heuristics that are unproven, and possible conclusions that are contradictory. We present a fully implemented AI system, Calvin, for cosmogenic isotope dating, a domain that is fraught with these difficult issues. Calvin solves these problems using an argumentation framework and a system of confidence that uses two-dimensional vectors to express the quality of heuristics and the applicability of evidence. The arguments it produces are strikingly similar to published expert arguments. Calvin is in daily use by isotope dating experts.
Leveraging Mixed Reality Infrastructure for Robotics and Applied AI Instruction
Authors: Baltes Jacky , Anderson John
Published: June 2022

Mixed reality is an important classroom tool for managing complexity from both the students' and instructor's standpoints. It can be used to provide important scaffolds when introducing robotics, by allowing elements of perception and control to be abstracted, and these abstractions removed as a course progresses (or left in place to introduce robotics to younger groups of students). In prior work, we have illustrated the potential of this approach both in providing scaffolding, building an inexpensive robotics laboratory, and also providing control of evaluation of robotics environments for student evaluation and scientific experimentation. In this paper, we explore integrating extensions and improvements to the mixed reality components themselves as part of a course in applied artificial intelligence and robotics. We present a set of assignments that in addition to exploring robotics concepts, actively integrate creating or improving mixed reality components. We find that this approach better leverages the advantages brought about by mixed reality in terms of student motivation, and also provides some very useful software engineering experience to the students.
Teaching Introductory Artificial Intelligence with Pac-Man
Authors: DeNero John , Klein Dan
Published: June 2022

The projects that we have developed for UC Berkeley’s introductory artificial intelligence (AI) course teach foundational concepts using the classic video game Pac-Man. There are four project topics: state-space search, multi-agent search, probabilistic inference, and reinforcement learning. Each project requires students to implement general-purpose AI algorithms and then to inject domain knowledge about the Pac- Man environment using search heuristics, evaluation functions, and feature functions. We have found that the Pac-Man theme adds consistency to the course, as well as tapping in to students’ excitement about video games.
Time Complexity of Iterative-Deepening A*: The Informativeness Pathology (Abstract)
Authors: Lelis Levi , Zilles Sandra , Holte Robert
Published: June 2022

Korf, Reid, and Edelkamp launched a line of research aimed at predicting how many nodes IDA* will expand with a given depth bound. This paper advances this line of research in three ways. First, we identify a source of prediction error that has hitherto been overlooked. We call it the "discretization effect." Second, we disprove the intuitively appealing idea that a "more informed" prediction system cannot make worse predictions than a ``less informed'' one. More informed systems are more susceptible to the discretization effect, and in our experiments the more informed system makes poorer predictions. Our third contribution is a method, called "Epsilon-truncation," which makes a prediction system less informed, in a carefully chosen way, so as to improve its predictions by reducing the discretization effect. In our experiments Epsilon-truncation improved predictions substantially.
Adaptive Neighborhood Inverse Consistency as Lookahead for Non-Binary CSPs
Authors: Woodward Robert , Karakashian Shant , Choueiry Berthe , Bessiere Christian
Published: June 2022

Freuder and Elfe (1996) introduced Neighborhood Inverse Consistency (NIC) for binary CSPs. In this paper, we introduce RNIC, the extension of NIC to non-binary CSPs, and describe a practical algorithm for enforcing it. We propose an adaptive strategy to weaken or strengthen this property based on the connectivity of the network. We demonstrate the effectiveness of RNIC as a full lookahead strategy during search for solving difficult benchmark problems.
Medical Treatment Conflict Resolving in Answer Set Programming
Authors: Bao Forrest Sheng , Zhang Zhizheng , Zhang Yuanlin
Published: June 2022

Medical treatment decision making is a good application of knowledge representation and reasoning. We are particularly interested in using it to resolve treatment conflicts, a complicated condition when two treatments cannot be given simultaneously to a patient of multiple symptoms. The logic system is required to reason on cases with and without treatment conflicts. Thanks to the nonmonotonicity of Answer Set Programming (ASP), we elegantly automate medical treatment conflict resolving on an example problem and show the importance of nonmonotonicity in medical reasoning.
An Event-Based Framework for Process Inference
Authors: Joya Michael
Published: June 2022

We focus on a class of models used for representing the dynamics between a discrete set of probabilistic events in a continuous-time setting. The proposed framework offers tractable learning and inference procedures and provides compact state representations for processes which exhibit variable delays between events. The approach is applied to a heart sound labeling task that exhibits long-range dependencies on previous events, and in which explicit modeling of the rhythm timings is justifiable by cardiological principles.
Personalizing Your Web Services with Constructive DL Reasoning Join
Authors: Lecue Freddy
Published: June 2022

Nowadays web users have clearly expressed their wishes to receive and interact with personalized services directly. However, existing approaches, largely syntactic content-based, fail to provide robust, accurate and useful personalized services to its users. Towards such an issue, the semantic web provides technologies to annotate and match services’ descriptions with users’ features, interests and preferences, thus allowing for more efficient access to services and more generally information. The aim of our work, part of service personalization, is on automated instantiation of services which is crucial for advanced usability i.e., how to prepare and present services ready to be executed while limiting useless interactions with users? We introduce the constructive Description Logics reasoning join and couple it with concept abduction to i) identify useful parts of users profiles that satisfy services requirements and ii) compute the description required by a service to be executed but not provided by users profiles.
Transfer Learning for Multiple-Domain Sentiment Analysis — Identifying Domain Dependent/Independent Word Polarity
Authors: Yoshida Yasuhisa , Hirao Tsutomu , Iwata Tomoharu , Nagata Masaaki , Matsumoto Yuji
Published: June 2022

Sentiment analysis is the task of determining the attitude (positive or negative) of documents. While the polarity of words in the documents is informative for this task, polarity of some words cannot be determined without domain knowledge. Detecting word polarity thus poses a challenge for multiple-domain sentiment analysis. Previous approaches tackle this problem with transfer learning techniques, but they cannot handle multiple source domains and multiple target domains. This paper proposes a novel Bayesian probabilistic model to handle multiple source and multiple target domains. In this model, each word is associated with three factors: Domain label, domain dependence/independence and word polarity. We derive an efficient algorithm using Gibbs sampling for inferring the parameters of the model, from both labeled and unlabeled texts. Using real data, we demonstrate the effectiveness of our model in a document polarity classification task compared with a method not considering the differences between domains. Moreover our method can also tell whether each word's polarity is domain-dependent or domain-independent. This feature allows us to construct a word polarity dictionary for each domain.
Propagating Both Trust and Distrust with Target Differentiation for Combating Web Spam
Authors: Zhang Xianchao , Wang You , Mou Nan , Liang Wenxin
Published: June 2022

Propagating trust/distrust from a set of seed (good/bad) pages to the entire Web has been widely used to combat Web spam. It has been mentioned that a combined use of good and bad seeds can lead to better results. However, little work has been known to realize this insight successfully. A serious issue of existing algorithms is that trust/distrust is propagated in non-differential ways. However, it seems to be impossible to implement differential propagation if only trust or distrust is propagated. In this paper, we view that each Web page has both a trustworthy side and an untrustworthy side, and assign two scores to each Web page: T-Rank, scoring the trustworthiness, and D-Rank, scoring the untrustworthiness. We then propose an integrated framework which propagates both trust and distrust. In the framework, the propagation of T-Rank/D-Rank is penalized by the target's current D-Rank/T-Rank. In this way, propagating both trust and distrust with target differentiation is implemented. The proposed Trust-Distrust Rank (TDR) algorithm not only makes full use of both good seeds and bad seeds, but also overcomes the disadvantages of both existing trust propagation and distrust propagation algorithms. Experimental results show that TDR outperforms other typical anti-spam algorithms under various criteria.
The Glass Infrastructure: Using Common Sense to Create a Dynamic, Place-Based Social Information System
Authors: Havasi Catherine , Borovoy Richard , Kizelshteyn Boris , Ypodimatopoulos Polychronis , Ferguson Jon , Holtzman Henry , Lippman Andrew , Schultz Dan , Blackshaw Matthew , Elliott Greg , Ng Chaki
Published: June 2022

Most organizations have a wealth of knowledge about themselves available online, but little for a visitor to interact with on-site. At the MIT Media Lab, we have designed and deployed a novel intelligent signage system, the Glass Infrastructure (GI) that enables small groups of users to physically interact with this data and to discover the latent connections between people, projects, and ideas. The displays are built on an adaptive, unsupervised model of the organization developed using dimensionality reduction and common sense knowledge which automatically classifies and organizes the information.The GI is currently in daily use at the lab. We discuss the AI models development, the integration of AI into an HCI interface, and the use of the GI during the labs peak visitor periods. We show that the GI is used repeatedly by lab visitors and provides a window into the workings of the organization.
Learning by Demonstration Technology for Military Planning and Decision Making: A Deployment Story
Authors: Myers Karen , Kolojejchick Jake , Angiolillo Carl , Cummings Tim , Garvey Tom , Gervasio Melinda , Haines Will , Jones Chris , Knittel Janette , Morley David , Ommert William , Potter Scott
Published: June 2022

Learning by demonstration technology has long held the promise to empower non-programmers to customize and extend software. We describe the deployment of a learning by demonstration capability to support user creation of automated procedures in a collaborative planning environment that is used widely by the U.S. Army. This technology, which has been in operational use since the summer of 2010, has helped to reduce user workloads by automating repetitive and time-consuming tasks. The technology has also provided the unexpected benefit of enabling standardization of products and processes.
Monitoring Entities in an Uncertain World: Entity Resolution and Referential Integrit
Authors: Minton Steven , Macskassy Sofus , LaMonica Peter , See Kane , Knoblock Craig , Barish Greg , Michelson Matthew , Liuzzi Raymond
Published: June 2022

This paper describes a system to help intelligence analysts track and analyze information being published in multiple sources, particularly open sources on the Web. The system integrates technology for Web harvesting, natural language extraction, and network analytics, and allows analysts to view and explore the results via a Web application. One of the difficult problems we address is the entity resolution problem, which occurs when there are multiple, differing ways to refer to the same entity. The problem is particularly complex when noisy data is being aggregated over time, there is no clean master list of entities, and the entities under investigation are intentionally being deceptive. Our system must not only perform entity resolution with noisy data, but must also gracefully recover when entity resolution mistakes are subsequently corrected. We present a case study in arms trafficking that illustrates the issues, and describe how they are addressed.
Automatically Mapping Natural Language Requirements to Domain-Specific Process Models
Authors: Thayasivam Uthayasanker , Verma Kunal , Kass Alex , Vasquez Reymonrod
Published: June 2022

For large scale enterprise implementations, a key problem, that has not been tackled much, is the ability to automatically map users’ requirements to reference process models. We present a tool called Process Model Requirements Gap Analyzer (ProcGap), which uses a combination of natural language processing, information retrieval and semantic reasoning to automatically match and map textual requirements to industry-specific process models. We present the results of mapping requirements from an industry project to an existing process model. We compare our approach to two previously implemented approaches and show that our approach outperforms them. In a case study, we also found that a user group with ProcGap had better performance than a user group that performed the same task manually.
Advisor Agent Support for Issue Tracking in Medical Device Development
Authors: Drew Touby , Gini Maria
Published: June 2022

This case study concerns the use of software agent advisors to improve efficiency and quality in issue tracking activities of development teams at the world’s largest medical device manufacturer. Each software agent monitors, interacts with, and learns from its environment and user, recognizing when and how to provide different kinds of advice and support to facilitate issue tracking activities without directly modifying anything or otherwise violating domain constraints. The deployed software agent has not only enjoyed regular and growing use, but contributed to significant improvements. Issue rejection was significantly reduced and more focused, yielding significant quality and efficiency gains such as fewer reviews by quality assurance. This success reflects the benefits of the underlying AI technology.
eBird: A Human/Computer Learning Network for Biodiversity Conservation and Research
Authors: Kelling Steve , Gerbracht, Jeff , Fink Daniel , Lagoze Carl , Wong Weng-Keen , Yu Jun Yu , Damoulas Theodoros , Gomes Carla
Published: June 2022

In this paper we describe eBird, a citizen science project that takes advantage of human observational capacity and machine learning methods to explore the synergies between human computation and mechanical computation. We call this model a Human/Computer Learning Network, whose core is an active learning feedback loop between humans and machines that dramatically improves the quality of both, and thereby continually improves the effectiveness of the network as a whole. Human/Computer Learning Networks leverage the contributions of a broad recruitment of human observers and processes their contributed data with Artificial Intelligence algorithms leading to a computational power that far exceeds the sum of the individual parts.
Applying Automated Language Translation at a Global Enterprise Level
Authors: Rychtyckyj Nestor , Plesco Craig
Published: June 2022

In 2007 we presented a paper that described the application of Natural Language Processing (NLP) and Machine Translation (MT) for the automated translation of process build instructions from English to other languages to support Ford’s assembly plants in non-English speaking countries. This project has continued to evolve with the addition of new languages and improvements to the translation process. However, we discovered that there was a large demand for automated language translation across all of Ford Motor Company and we decided to expand the scope of our project to address these requirements. This paper will describe our efforts to meet all of Ford’s internal translation requirements with AI and MT technology and focus on the challenges and lessons that we learned from applying advanced technology across an entire corporation.
Toward Habitable Assistance from Spoken Dialogue Systems
Authors: Epstein Susan , Passonneau Rebecca , Ligorio Tiziana , Gordon Joshua
Published: June 2022

Spoken dialogue is increasingly central to systems that assist people. As the tasks that people and machines speak about together become more complex, however, users’ dissatisfaction with those systems is an important concern. This paper presents a novel approach to learning for spoken dialogue systems. It describes embedded wizardry, a methodology for learning from skilled people, and applies it to a library whose patrons order books by telephone. To address the challenges inherent in this application, we introduce RFW+, a domain-independent, feature-selection method that considers feature categories. Models learned with RFW+ on embedded-wizard data improve the performance of a traditional spoken dialogue system.
Local Search for Designing Noise-Minimal Rotorcraft Approach Trajectorie
Authors: Morris Robert , Venable K. , Pegoraro Marco , Lindsey James
Published: June 2022

NASA and the international community are investing in the development of a commercial transportation infrastructure that includes the increased use of rotorcraft, specifically helicopters and civil tilt rotors. However, there is significant concern over the impact of noise on the communities surrounding the transportation facilities. One way to address the rotorcraft noise problem is by exploiting powerful search techniques coming from artificial intelligence coupled with simulation and field tests to design low-noise flight profiles which can be tested in simulation or through field tests. This paper investigates the use of simulation based on predictive physical models to facilitate the search for low-noise trajectories using local search combined with a robust noise simulator.
Multi-Agent Simulation of En-Route Human Air-Traffic Controller
Authors: Šišlák David , Volf Přemysl , Pěchouček Michal , Cannon Christopher , Nguyen Duc , Regli William
Published: June 2022

The Next-Generation Transportation program coordinates the evolution and transformation of the current air-traffic management (ATM) system for the National Airspace System (NAS). Currently the NAS has a limited capacity and cannot handle the increasing future air traffic demands. However, before newly proposed ATM concepts are deployed they must be rigorously evaluated under realistic conditions. This paper presents AGENTFLY, an emerging NAS-wide highfidelity multi-agent ATM simulator with precise emulation of the human controller operation workload model and human-system interaction. The simulator is validated using a flight scenario developed by the U.S. Federal Aviation Administration that is based on real data. We present preliminary results focusing on the accuracy of the simulated controllers within AGENTFLY.
Statistical Relational Learning to Predict Primary Myocardial Infarction from Electronic Health Records
Authors: Weiss Jeremy , Page David , Natarajan Sriraam , Peissig Peggy , McCarty Catherine
Published: June 2022

Electronic health records (EHRs) are an emerging relational domain with large potential to improve clinical outcomes. We apply two statistical relational learning (SRL) algorithms to the task of predicting primary myocardial infarction. We show that one SRL algorithm, relational functional gradient boosting, outperforms propositional learners particularly in the medically-relevant high recall region. We observe that both SRL algorithms predict outcomes better than their propositional analogs and suggest how our methods can augment current epidemiological practices.
Heuristic Search for Large Problems with Real Costs
Authors: Hatem Matthew
Published: June 2022

Heuristic search is a fundamental technique for solving problems in artificial intelligence. However, many heuristic search algorithms, such as A* are limited by the amount of main memory available. External memory search overcomes the memory limitation of A* by taking advantage of cheap secondary storage, such as disk. Previous work in this area assumes that edge costs fall within a narrow range of integer values and relies on uniformed search order. The goal of this dissertation research is to develop novel techniques that enable heuristic search algorithms to solve problems with real values using a best-first search order while exploiting external memory and multiple processors. This work will be organized into four components. The first component will discuss external memory search and present a novel technique for incorporating real-valued edge costs. The second component will present a novel algorithm for solving problems with large branching factors with application to the challenging problem of Multiple Sequence Alignment (MSA). The third component will cover bounded suboptimal external search for practical MSA applications. The final component of this research will be the development of a novel distributed search framework; allowing parallel and external memory heuristic search algorithms to run cooperatively on a commodity computing cluster. Together these four components will enable heuristic search to scale to large problems in practical settings while exploiting modern hardware.
Steps Towards a Science of Heuristic Search
Authors: Wilt Christopher
Published: June 2022

There are many algorithms designed to solve the shortest path problem.Each of the published algorithms has a demonstrated use; a situationin which it is the clear choice.  Unfortunately, if faced with a novelproblem, there is no reliable robust way to figure out which algorithmshould be used to solve the new problem.When classifying things, the first step is to identify relevantfeatures for classifications.  In the context of heuristic search, itnot clear what pieces of information should be used to predict searchalgorithm performance, and the question of algorithm selection for anovel domain is an open question.We first analyze which domain attributes common algorithms leverage,and discuss how to identify domains containing these attributes.  Inaddition to discussing how to classify domains, we also discuss whythe classifications matter for various algorithms.  Ultimately, thiswill allow us to offer more accurate runtime predictions for variousalgorithms we analyze, allowing us to determine which algorithm willlikely offer the best performance.
Tools for Preference Reasoning
Authors: Zhu Ying
Published: June 2022

The problem of computing similar and dissimilar solutions to a given one has received much attention in constraint satisfaction and answer set programming (ASP). In many practical applications involving product configuration or planning, it is often the case that there are many valid solutions. To help the user see a small but representative sample, one needs algorithms that compute sets of dissimilar solutions. Once the user "zooms" in on one or two that she likes the most, it still makes sense to present several alternatives that are similar to the selected ones so that the user can find one that truly corresponds to her needs.
Backdoors to Tractability of Answer-Set Programming
Authors: Fichte Johannes
Published: June 2022

The practical results of answer-set programming indicate that classical complexity theory is insufficient as a theoretical framework to explain why modern answer-set programming solvers work fast on industrial applications. Complexity analysis by means of parameterized complexity theory seems to be promising, because we think that the reason for the gap between theory and practice is the presence of a "hidden structure" in real-world instances. The application of parameterized complexity theory to answer-set programming would give a crucial understanding of how solver heuristics work. This profound understanding can be used to improve the decision heuristics of modern solvers and yields new efficient algorithms for decision problems in the nonmonotonic setting. My research aims to explain the gap between theoretical upper bounds and the effort to solve real-world instances. I will further develop by means of parameterized complexity exact algorithms which work efficiently for real-world instances. The approach is based on backdoors which are small sets of atoms that represent "clever reasoning shortcuts" through the search space. The concept of backdoors is widely used in the areas of propositional satisfiability and constraint satisfaction. I will show how this concept can be adapted to the nonmonotonic setting and how it can be utilized to improve common algorithms.