bluuebunny/crossref_metadata_2025 huggingface dataset:
Beyond Free Will: Variety in Understanding of Choice, Luck, and Necessity
Authors: Beinorius Audrius , Berniūnas Renatas , Dranseika Vilius , Rimkevičius Paulius , Silius Vytis , Veisaitė Agnė
Published: June 2022

Contemporary Western discourse on freedom and choice – some of the most championed modern values – is usually anchored in the concept cluster of free will and autonomous choice. In turn, academic research on free will in philosophy (including experimental philosophy) and psychology is largely based on a limited conceptual framework with roots in particular debates in Christianity and European philosophy. This framework is currently challenged by multidisciplinary and interdisciplinary approaches applied in the fields of area and Asian studies, comparative philosophy, and also empirical research in cross-cultural psychology, and anthropology. One reason for this challenge is that the dominant Western academic approach, with its almost exclusive focus on concepts of free will and causal determinism, neglects the multitude of non-Western cultural traditions. In most parts of the world, these traditions continue to shape everyday practices and conceptualizations of free action, choice, and decision. Traditions also provide various strategies for navigating the constraints on human agency.In the present multidisciplinary and interdisciplinary conference, we invited scholars from philosophy, psychology, anthropology, Asian studies, religious studies and other related fields to discuss theoretical alternatives to the dominant framework that are sensitive to cultural differences and local contexts as well as empirical research – especially crosscultural and cross-linguistic – on conceptualizations of free and constrained action and cultural practices in dealing with these constraints.This project “Between choice and determinism: cultural variations in experiencing and conceptualizing free will, luck and randomness” has received funding from European Social Fund (project No. 09.3.3-LMT-K-712-01-0111) under grant agreement with the Research Council of Lithuania (LMTLT).
Analysis of the performances of the Ukrainian national freestyle wrestling team at the U23 World and European Championships
Authors:   Borys Grinchenko Kyiv University, Latyshev M. , Havrylova N. ,   Borys Grinchenko Kyiv University, Lakhtadyr O. ,   Borys Grinchenko Kyiv University, Len Y. ,   Borys Grinchenko Kyiv University, Polianychko O. ,   Borys Grinchenko Kyiv University
Published: June 2022

Purpose: to analyze the performances of the Ukrainian national team at the U23 World and European Championships. Material and Methods. The following methods were used in the research: analysis of scientific and methodical literature and Internet sources, analysis of competitive activity, methods of mathematical statistics. The performances of the athletes of the national team of Ukraine at all U23 World and European Championships in freestyle wrestling were analyzed. During the international competitions in the U23 age category, seven European Championships (from 2015 to 2023) and five World Championships (from 2017 to 2022) were held. During this time, 64 athletes of the national team of Ukraine took part in the U23 European Championships and 48 athletes in the U23 World Championships. The following indicators were considered: the place taken, the number of athletes and the year of performance. Results: the total number of medalists at the U23 European Championships is 20 (31,3 %) athletes, of which 4 (6,3 %) athletes took the first place, 6 (9,4 %) athletes took the second place and 10 (15,6 %) athletes took the third place. At the same time, a significant number of athletes took fifth place (19 athletes or 29,7 %). From seventh to ninth place, 12 athletes took the seventh place, which is 18,8 % of the total number. The tenth place and below was taken by 13 athletes (or 20,3 %), which is also a significant share of the total number and indicates high competition. According to the analyzed information, at the U23 World Championships in freestyle wrestling, only one athlete out of 48 athletes of the national team of Ukraine took the first place, which is 2,1 % of the total. The 12 athletes who took third place account for 25,0 % of the total number of athletes. The athletes who took fifth and seventh places also make up 25,0 % of the total number. These are also promising athletes who were close to winning prizes. The 3 athletes in eighth place account for 6,25 % of the total number of athletes, and the 4 athletes in ninth place account for 8,33 %. Finally, the 16 athletes who took tenth place and below account for 33,33 % of the total number of athletes. Conclusions. The national team of Ukraine in freestyle wrestling at international U23 competitions has stable results, the athletes have always won prizes at all continental and world championships. The analysis showed that the percentage of winners from the total number of athletes who participated may vary depending on the preparation and performance of the team at a particular tournament. Thus, the percentage of winners at the championships ranged from 25,0 % to 40,0 %, while at the world championships from 20,0 % to 40,0 %.
Konservatisme Akuntansi dan Kinerja Perusahaan di Indonesia
Authors: Suwarno Suwarno , Suwandi Suwandi , Sholichah Mu'minatus
Published: June 2022

This study aims to confirm the relationship between accounting conservatism and the financial performance of companies in Indonesia in the 2019 period. Accounting conservatism is still debated between standard setters and accountants. The accountants argue that accounting conservatism is still needed to reduce the opportunistic behavior of managers. Meanwhile, accounting standard setters stated that accounting conservatism had an impact on biased financial statements. The research sample was selected with several criteria so that 564 companies were obtained. Panel data were analyzed by regression and the results showed that conservative accounting had an effect on Return On Assets (ROA). Accounting conservatism will reduce information asymmetry, which will reduce managers’ opportunistic behavior and increase investment efficiency and improve company performance. However, accounting conservatism has no effect on firm value (Tobin’s Q). Accounting conservatism will cause financial statements to tend to be biased because financial statements cannot describe the actual situation. Therefore, financial statements are not able to predict future cash flows.
Pengaruh Financing to Deposit Ratio, Capital Adequacy Ratio, dan Operating Cost Ratio terhadap Manajemen Laba di Perbankan Syariah
Authors: Astuti Iis Putri , Jasman Jasman
Published: June 2022

This study aims to examine the impact of financing to deposit ratio (FDR), capital adequacy ratio (CAR), and operating cost ratio (BOPO) on earnings management in islamic banks for the period 2014-2019. There are eight islamic banks as the research sample through purposive sampling method. The data used was the annual report data obtained from the official website of each bank. The data analysis technique used was multiple linear regression. The results of the study showed that financing to deposit ratio has no effect on earnings management, capital adequacy ratio has a significant and positive effect on earnings management, and operating cost ratio has a significant and positive effect on earnings management. These results provide empirical evidence that there are earnings management practices in islamic banks.
Ukuran Perusahaan Memoderasi Pengaruh Penilaian Aset Biologi dan Income Smoothing terhadap Volatilitas Laba
Authors: Lisnawati Lisna , Herawati Vinola
Published: June 2022

PSAK 69 effective January 1, 2016 has provided direction regarding the valuation of biological assets from historical value to Fair value which uses the basis of market prices which always fluctuate in line with the demand and supply of biological assets.The purpose of this study was to examine the effect of valuation of biological assets on earnings volatility by moderating firm size in manufacturing companies in the agricultural sector in Indonesia and Malaysia for the period 2016 to 2020. This study uses quantitative methods with secondary data sources with samples used through purposive sampling where the total data is 220 company year data. The results of this study are that Biological Asset Valuation and Income Smoothing have a positive effect on earnings volatility, then for the moderating variable Firm size cannot strengthen the effect of biological asset valuation on Earning Volatility and can strengthen the effect of Income Smoothing on Profit Volatility.
Marijuana and Breastfeeding: A Pilot Survey of Mothers
Authors: Crowley Hannah R. , Goyal Neera K. , Chung Esther K.
Published: June 2022

OBJECTIVE

To describe maternal knowledge, attitudes, and practices related to marijuana use and breastfeeding, and determine their association with knowledge about potential harmful effects of marijauna use while breastfeeding.

METHODS

Cross-sectional study design, using a 48-item survey, including previously validated questions, of postpartum mothers at a single urban, academic hospital from 2018 to 2019. Mothers ≥ 18 years with a newborn ≥ 35 weeks’ gestation were eligible. Descriptive statistics were tabulated, and associations were tested by using χ2 analysis.

RESULTS

Of 46 participants, 57% reported marijuana use, and 13% use within the past 12 months. The large majority (87%) knew that use while breastfeeding may be harmful to the infant, whereas just 46% knew that marijuana or THC is found in breast milk. Only 35% received prenatal and 30% postnatal counseling on the risks of marijuana use while breastfeeding. Those aware compared to those unaware that marijuana use during pregnancy may cause learning and behavior problems were more likely to know that use while breastfeeding may be harmful to the infant (75% vs. 25%, P = .03). Those reporting prenatal HCP discussion about the risks of marijuana use while breastfeeding compared to those without such counseling were more likely to know that marijuana/ or HC is found in breast milk (69% vs. 33%, P = .02).

CONCLUSIONS

The majority of mothers were aware that marijuana use while breastfeeding may be harmful to the infant, but a minority received counseling about the risks of marijuana use while breastfeeding.
Health Equity for Children and Youth With Special Health Care Needs: A Vision for the Future
Authors: Houtrow Amy , Martin Alison J. , Harris Debbi , Cejas Diana , Hutson Rachel , Mazloomdoost Yasmin , Agrawal Rishi K.
Published: June 2022

Health equity is a key pillar in supporting a future in which CYSHCN enjoy a full life and thrive, as envisioned by experts and community partners who gathered in 2019 and 2020 to develop the Blueprint for Change: Guiding Principles for a System of Services for Children and Youth With Special Health Care Needs and Their Families. However, a variety of contextual factors impact health outcomes across the life course and intergenerationally and must be addressed to achieve this goal. For example, poverty and discrimination, including by some health care professionals and systems, are important, modifiable root causes of poor health outcomes. There are numerous barriers to achieving health equity, including political will, lack of resources, insufficient training, and limited cross-sector collaborations. Political, cultural, societal, and environmental interventions are necessary to eliminate health disparities and achieve health equity. The entities that serve CYSHCN should be equitably designed and implemented to improve health outcomes and address health disparities. Many entities that serve CYSHCN are taking positive steps through workforce development, policy changes, community engagement, and other means. The purpose of this article is to frame health equity for CYSHCN, detail their health disparities, review barriers to health equity, provide examples of strategies to advance health equity for them, and describe a path toward the future in which all CYSHCN have a fair and just opportunity to be as healthy as possible.
Respiratory Distress: Three Patient Cases
Authors: Chickmagalur Sunil , Davitt Meghan , Lahoutiharahdashti Arash , Mitchell William , Arens Raanan , Wallace Marshall W. , Sutyla Ryan F. , Plemmons Gregory , Schmitz Anna , Town Ryan , Siembida Jakub , Wood Kelly E.
Published: June 2022

As mentioned in the January 2022 Pediatrics in Review Commentary, we now present three patients who have a common chief complaint followed by 5 questions for CME credit. All three cases have discussions on presentation, the differential diagnosis, and management that collectively serve as a Review article. The common theme here is that all three patients have difficulty breathing. We hope you will enjoy this review format.
Análisis del riesgo derivado de la amenaza de la inestabilidad de laderas bajo influencia del calentamiento global antropogénico: propuesta de un enfoque metodológico
Authors: Mora Sergio
Published: June 2022

Si el escenario de que el calentamiento global antropogénico (CGA) aumentaría las precipitaciones en algunos microclimas, podrían modificarse a mediano y largo plazo, los procesos de la geodinámica externa. En áreas con equilibrios hídricos inestables, CGA se superpondría a la variabilidad climática y otros factores naturales y antropogénicos: vulnerabilidad, terremotos, volcanismo, expansión urbana e infraestructural, El Niño-La Niña/ENOS, degradación de tierras. La inestabilidad de laderas sería más destructiva social, ambiental y económicamente, por lo cual conviene redefinir las prioridades de las políticas públicas, toma de decisiones y gestión del riesgo. Se propone un procedimiento analítico para áreas con microclimas influenciados por el CGA en donde aumentarían la intensidad, duración, frecuencia, volumen de las lluvias y el desequilibrio hídrico. Asimismo, ascenderían progresivamente el nivel freático y la presión intersticial, y las lluvias intensas críticas reducirían su período de recurrencia. La gestión del riesgo, apoyada en la geotecnia, deberá centrarse en acciones que reduzcan y transfieran el riesgo y disminuyan la vulnerabilidad, como mejor instrumento de adaptación para contrarrestar cualquier amenaza.
Contribuições da metodologia de Resolução de Problemas para o ensino de Probabilidade e Estatística
Authors: Paixão Oliveira Jean , De Castro Farias Darlan , De Freitas Madruga Zulma Elizabete
Published: June 2022

Este artigo apresenta resultados de uma pesquisa que teve como objetivo analisar as contribuições da metodologia de Resolução de Problemas para o ensino de Probabilidade e Estatística, por meio do mapeamento de teses e dissertações. Como abordagem metodológica realizou-se uma pesquisa bibliográfica utilizando como procedimentos o “Mapeamento na Pesquisa Educacional”, para levantamento, organização e análise dos dados. Os dados foram constituídos a partir da seleção de seis dissertações publicadas no banco de dados da CAPES, entre 2009 a 2019. Para a análise, estabelecemos quatro categorias definidas a priori: a) referenciais teóricos da pesquisa; b) problemas investigados e interesses de pesquisa; c) metodologias utilizadas; e, d) principais resultados e contribuições para o avanço do tema na área. Os resultados permitiram identificar aproximações teóricas e metodológicas entre os trabalhos analisados e se evidenciou convergência no que se refere aos estudos acerca da Resolução de Problemas enquanto metodologia de ensino.
Palavras-chave: Mapeamento; tratamento da informação; ensino.
A Rational Method fo Estimating Camber and Deflection of Precast Prestressed Members
Authors: Martin Leslie
Published: June 2022

The author presents a step-by-step rational procedure for determining long-time multipliers for camber and deflection of precast prestressed concrete members. The procedure begins with the equation in Section 9.5.2.3 of ACI 318-71 and ends with a table of numerical values (Table 3) that can be used for most members without appreciable error. Table 2 illustrates the sensitivity of the equations to various variables and shows that except for extremely long members the variations are within the tolerances prescribed by the PCI Manual for Quality Control. Table 4 illustrates how these multipliers should be used. Equations are provided for a more precise analysis.
Az emelkedett szérum B12-vitamin-szint klinikai jelentősége
Authors: Mikala Gábor , Szemlaky Zsuzsanna , Ceglédi Andrea
Published: June 2022

Bevezetés

A szérum B12-vitamin-szint vizsgálatát a hematológus elsősorban anaemia perniciosa, esetleg idült myeloproliferatív betegség gyanúja esetén szokta kérni, és tisztában van az eredmény értékével és jelentőségével. Konzultatív tevékenységünk során azonban szembesülhetünk más szakma által kért és kórosan magasnak talált B12-vitamin-szint jelentőségéről való nyilatkozás szükségességéről. A magas B12-vitamin-szint meglepően gyakori laborvizsgálati eredmény, hátterében myeloproliferatív szindrómák mellett primer és metasztatikus májdaganatok, egyéb daganatok, alkoholos májbetegség, akut és krónikus hepatitisek, vesebetegség gyakran szerepel, de gyógyszerhatások is felmerülhetnek. Összefoglalónkban ismertetjük a B12-vitamin metabolizmusát, az azt befolyásoló tényezőket, és rávilágítunk a magas szérum B12-vitamin-szint legfontosabb pathofiziológiai okaira és a követendő lépésekre.
Agyi myeloma képét utánzó toxoplasmosis
Authors: Nagy Eszter , Ceglédi Andrea , Szabó Bálint Gergely , Lakatos Botond , Kiss Anita Viktória , Kozma András , Balogh Attila , Rajnai Hajnalka , Reményi Péter , Mikala Gábor
Published: June 2022

Bevezetés

Myeloma multiplexben és társuló plazmasejtes leukémiában szenvedő 63 éves nőbetegünk másodvonalbeli carfilzomib-lenalidomid-dexamethason mentőkezeléssel komplett remissziót ért el, melyet autológ őssejt-átültetéssel konszolidáltunk. A transzplantációt követően gyors relapszusa alakult ki, melyre harmadvonalbeli daratumumab-lenalidomid-dexamethason kezelést indítottunk.

A kezelések szövődményeként Clostridioides difficile okozta pseudomembranosus colitis jelentkezett, mely során intenzív osztályra került, így a kúrát felfüggesztettük. Osztályunkra visszavéve szótalálási nehézséget, jobb oldali felső végtagi túlsúlyú hemiparesist, ködös tudatállapotot észleltünk. Az elvégzett koponya MRI-vizsgálat a capsula interna-thalamus határán 28 × 25 mm-es térfoglalást igazolt, perifokális ödémával, bal oldali oldalkamra kompresszióval és középvonali áttolással. A kép myeloma multiplex agyi relapszusának alapos gyanúját keltette, de felmerült gyulladásos folyamat lehetősége is. Idegsebészeti javaslatra sztereotaxiás biopsziás mintavétel történt, melynek szövettana toxoplasmosist igazolt. Infektológiai megbeszélés alapján pyrimethamin, sulfadiazin és folinsav kombinációt kezdtünk, melyre a beteg jól reagált, az ágyból kikelt, sétált, tudata feltisztult. A klinikai javulást képalkotó vizsgálat is megerősítette. Közben a myeloma multiplex betegség progressziója alakult ki, ezért a daratumumab adását újrakezdtük. Sajnos a beteg klinikai állapota hanyatlott, újból ágyhoz kötötté vált, Klebsiella pneumoniae véráram-infekció miatt ismételten intenzív osztályos ellátást igényelt. A kontroll koponya-MRI újabb agyi góc megjelenését igazolta.

A beteget progresszív myeloma multiplex és agyi toxoplasmosis együttes fennállásában elveszítettük. Esetünk legfontosabb tanulsága, hogy agyi toxoplasmosis lehetőségére immunszupprimált, myelomás betegeink agyi plasmocytomának megfelelő képe esetén is gondolnunk kell.
Krónikus limfocitás leukémiás beteg orbita és szem mucormycosisa
Authors: Szücs József Gábor , Tajti Balázs , Fullajtár Borbála , Sira Ágnes , Ilonczai Péter
Published: June 2022

Bevezetés

A mucormycosis ritka, de magas mortalitással járó fertőzés, melyet a Mucorales rendbe tartozó gyorsan növő, hőtűrő, opportunista gombafajok okoznak immunszupprimált betegekben. Incidenciája folyamatosan emelkedik a növekvő prevalenciájú cukorbetegség, a következményeként kialakuló ketoacidosis, a gyakoribb daganatos megbetegedések, a gyakrabban végzett szerv- és őssejt-transzplantációk, a nagydózisú kortikoszteroid kezelés és az elöregedő társadalom miatt. Napjainkban a koronavírus-betegség 2019-hez asszociált terjedése miatt vált szélesebb körben ismertté. A diagnózis megállapítása a mikrobiológiai tenyésztéseken, a radiológiai és a szövettani képen alapul. Egy idős, B-sejtes krónikus limfocitás leukémia miatt 8 éve gondozás alatt álló beteg esetén keresztül mutatjuk be ennek a gyakran csak későn felfedezett betegségnek a rhino-orbito-cerebrális típusát. Mivel a kezelés késői elindítása lényegesen növeli a mortalitást, ezért hematológiai betegekben noduláris bőrelváltozás megjelenésekor gondolnunk kell mucormycosis lehetőségére, hogy az időben elkezdett gyógyszeres és/vagy műtéti terápiákkal jelentősen növelhessük páciensünk túlélési esélyeit.
Pyrolytic Carbon Electrodes and Their Potential Application in Electrochemical Sensors
Authors: Nguyen Thi Thanh Ngan , Bui Thanh Giang , Nguyen Danh Thanh , Nguyen Duc Thanh , Nguyen Hoang Long , Nguyen Tuan Hong , Dang Thanh Binh , Vu Thi Thu
Published: June 2022

In this work, pyrolytic carbon electrodes were prepared through pyrolysis of well-patterned AZ 1505 positive photoresist films. The designed electrodes firstly were prepared via photolithography technique, then the polymer was thermally broken-down into carbon skeletons in an oxygen-free environment using pyrolysis technique. The effect of the highest temperature and ramping rate on the electrical properties of the carbon films were investigated. The results show that the pyrolysis process was optimal at the ramping rate of 3 °C/minute, annealing temperature of 900 °C, and annealing time of one hour. The lowest resistivity was obtained at 6.3 ´ 10-5 Wm for pyrolytic films prepared at the optimal pyrolysis conditions. Electrochemical measurements confirm the potential of this electrode for electrochemical sensing applications.
Toxoplasma gondii, Neospora caninum and Sarcocystis spp. in species of naturally infected birds
Authors: Alves Marta E.M. , Fernandes Fagner D. , Bräunig Patrícia , Murer Laurete , Minuzzi Camila E. , Santos Helton F. dos , Sangioni Luis A. , Vogel Fernanda S.F.
Published: June 2022

ABSTRACT: Toxoplasma gondii, Neospora caninum and Sarcocystis spp. are parasites detected in tissues of domestic and wild animals. Birds are relevant in the life cycle and epidemiology of protozoa due to the wide variety of bird species, feeding and migratory habits. The aim of this study was the molecular detection of T. gondii, N. caninum and Sarcocystis spp. in several species of naturally infected birds. Therefore, samples of brain and heart tissue were collected from birds received and necropsied at the Central Laboratory for the Diagnosis of Avian Pathologies (LCDPA), undergoing DNA extraction and amplification by the polymerase chain reaction (PCR) of the 18S rRNA gene to Sarcocystis spp., NC5 gene for N. caninum and repetitive gene 529 base pairs for T. gondii. N. caninum was detected in two birds (02/65, 3.07%), in a brain sample of Rupornis magnisrostris (accession number: ON182081, 267pb) and in a brain and heart sample of Dendrocygna bicolor (accession number: ON211312, 267pb). DNA of the genus Sarcocystis was detected in three birds (03/65, 4.62%), and in the genetic sequencing Sarcocystis spp. (accession number: MW463929) in brain of Nymphicus hollandicus and Sarcocystis speeri (accession number: MW464125) in brain and heart of Amazona aestiva. Phylogenetic analysis revealed that Sarcocystis spp. formed a clade with Sarcocystis spp. that use skunk (Didelphis aurita) as definitive host and Sarcocystis falcatula that use Moluccan loris (Trichoglossus moluccanus) as intermediate host. S. speeri formed a clade with S. speeri that used Mus musculus as an experimental intermediate host and formed a clade with Sarcocystis columbae, Sarcocystis corvusi, Sarcocystis halieti and Sarcocystis sp. that affect bird species. T. gondii DNA was not detected in any tissue. This is the first report of DNA detection of N. caninum, Sarcocystis spp. and S. speeri in tissue samples for these bird species extending the list of intermediate hosts.
Assistência a pacientes elegíveis para cuidados paliativos: visão de profissionais de uma Unidade de Terapia Intensiva
Authors: Rodrigues Martins Matheus , da Silva Oliveira Juliana , Ernesto Silva Alexandre , Souza da Silva Rudval , Constâncio Tatiane Oliveira de Souza , Vieira Sheylla Nayara Sales
Published: June 2022

RESUMO Objetivo: compreender a percepção da equipe multiprofissional sobre a qualidade da assistência à saúde prestada a pacientes em cuidados paliativos em Unidade de Terapia Intensiva. Método: estudo qualitativo, ancorado no referencial teórico de Donabedian, por meio de entrevistas semiestruturadas realizadas com 35 profissionais que atuam em Unidade de Terapia Intensiva. Para análise dos dados, utilizou-se a técnica de Análise de Conteúdo. Resultados: foram pré-estabelecidas três categorias: estrutura, processo e resultado, das quais emergiram cinco subcategorias: Déficit no quantitativo e na qualificação profissional; Ambiência e cuidados paliativos; (In)existência de uma assistência pautada nos princípios dos cuidados paliativos; Falhas na comunicação e na abordagem interdisciplinar; e Repercussões da (des)assistência. Conclusão: o estudo permitiu compreender as fragilidades institucionais para a operacionalização da assistência dispensada aos pacientes elegíveis para cuidados paliativos no cenário da Unidade de Terapia Intensiva. Dessa forma, para que essa filosofia de cuidado seja propagada, necessita-se da coparticipação dos gestores, profissionais, pacientes e familiares, uma vez que essas lacunas não conseguem ser supridas sem que haja um envolvimento coletivo.
Quality Expectation-Variance Tradeoffs in Crowdsourcing Contests
Authors: Gao Xi , Bachrach Yoram , Key Peter , Graepel Thore
Published: June 2022

We examine designs for crowdsourcing contests, where participants compete for rewards given to superior solutions of a task. We theoretically analyze tradeoffs between the expectation and variance of the principal's utility (i.e. the best solution's quality), and empirically test our theoretical predictions using a controlled experiment on Amazon Mechanical Turk. Our evaluation method is also crowdsourcing based and relies on the peer prediction mechanism. Our theoretical analysis shows an expectation-variance tradeoff of the principal's utility in such contests through a Pareto efficient frontier. In particular, we show that the simple contest with 2 authors and the 2-pair contest have good theoretical properties. In contrast, our empirical results show that the 2-pair contest is the superior design among all designs tested, achieving the highest expectation and lowest variance of the principal's utility.
Adaptive Polling for Information Aggregation
Authors: Pfeiffer Thomas , Gao Xi , Chen Yiling , Mao Andrew , Rand David
Published: June 2022

The flourishing of online labor markets such as Amazon Mechanical Turk (MTurk) makes it easy to recruit many workers for solving small tasks. We study whether information elicitation and aggregation over a combinatorial space can be achieved by integrating small pieces of potentially imprecise information, gathered from a large number of workers through simple, one-shot interactions in an online labor market. We consider the setting of predicting the ranking of $n$ competing candidates, each having a hidden underlying strength parameter. At each step, our method estimates the strength parameters from the collected pairwise comparison data and adaptively chooses another pairwise comparison question for the next recruited worker. Through an MTurk experiment, we show that the adaptive method effectively elicits and aggregates information, outperforming a naive method using a random pairwise comparison question at each step.
MCTS Based on Simple Regret
Authors: Tolpin David , Shimony Solomon
Published: June 2022

UCT, a state-of-the art algorithm for Monte Carlo tree search (MCTS) in games and Markov decision processes, is based on UCB, a sampling policy for the Multi-armed Bandit problem (MAB) that minimizes the cumulative regret. However, search differs from MAB in that in MCTS it is usually only the final ``arm pull'' (the actual move selection) that collects a reward, rather than all ``arm pulls''. Therefore, it makes more sense to minimize the simple regret, as opposed to the cumulative regret. We begin by introducing policies for multi-armed bandits with lower finite-time and asymptotic simple regret than UCB, using it to develop a two-stage scheme (SR+CR) for MCTS which outperforms UCT empirically. Optimizing the sampling process is itself a metareasoning problem, a solution of which can use value of information (VOI) techniques. Although the theory of VOI for search exists, applying it to MCTS is non-trivial, as typical myopic assumptions fail. Lacking a complete working VOI theory for MCTS, we nevertheless propose a sampling scheme that is ``aware'' of VOI, achieving an algorithm that in empirical evaluation outperforms both UCT and the other proposed algorithms.
Fast and Accurate Predictions of IDA*'s Performance
Authors: Lelis Levi , Zilles Sandra , Holte Robert
Published: June 2022

Korf, Reid and Edelkamp initiated a line of research for developing methods (KRE and later CDP) that predict the number of nodes expanded by IDA* for a given start state and cost bound. Independent of that, Chen developed a method (SS) that can also be used to predict the number of nodes expanded by IDA*. In this paper we advance both of these prediction methods. First, we develop a variant of CDP that can be orders of magnitude faster than CDP while producing exactly the same predictions. Second, we show how ideas developed in the KRE line of research can be used to substantially improve the predictions produced by SS. Third, we make an empirical comparison between our new enhanced versions of CDP and SS. Our experimental results point out that CDP is suitable for applications that require less accurate but very fast predictions, while SS is suitable for applications that require more accurate predictions but allow more computation time.
Non-Model-Based Search Guidance for Set Partitioning Problems
Authors: Kadioglu Serdar , Malitsky Yuri , Sellmann Meinolf
Published: June 2022

We present a dynamic branching scheme for set partitioning problems. The idea is to trace features of the underlying MIP model and to base search decisions on the features of the current subproblem to be solved. We show how such a system can be trained efficiently by introducing minimal learning bias that traditional model-based machine learning approaches rely on. Experiments on a highly heterogeneous collection of set partitioning instances show significant gains over dynamic search guidance in Cplex as well as instance-specifically tuned pure search heuristics.
Solving Dots-And-Boxes
Authors: Barker Joseph , Korf Richard
Published: June 2022

Dots-And-Boxes is a well-known and widely-played combinatorial game. While the rules of play are very simple, the state space for even very small games is extremely large, and finding the outcome under optimal play is correspondingly hard. In this paper we introduce a Dots-And-Boxes solver which is significantly faster than the current state-of-the-art: over an order-of-magnitude faster on several large problems. Our approach uses Alpha-Beta search and applies a number of techniques---both problem-specific and general---that reduce the search space to a manageable size. Using these techniques, we have determined for the first time that Dots-And-Boxes on a board of 4 x 5 boxes is a tie given optimal play; this is the largest game solved to date.
Social Cognition: Memory Decay and Adaptive Information Filtering for Robust Information Maintenance
Authors: Reitter David , Lebiere Christian
Published: June 2022

Two information decay methods are examined that help multi-agent systems cope with dynamic environments. The agents in this simulation have human-like memory and a mechanism to moderate their communications: they forget internally stored information via temporal decay, and they forget distributed information by filtering it as it passes through a communication network. The agents play a foraging game, in which performance depends on communicating facts and requests and on storing facts in internal memory. Parameters of the game and agent models are tuned to human data. Agent groups with moderated communication in small-world networks achieve optimal performance for typical human memory decay values, while non-adaptive agents benefit from stronger memory decay. The decay and filtering strategies interact with the properties of the network graph in ways suggestive of an evolutionary co-optimization between the human cognitive system and an external social structure.
Non-Intrusive Load Monitoring Using Prior Models of General Appliance Types
Authors: Parson Oliver , Ghosh Siddhartha , Weal Mark , Rogers Alex
Published: June 2022

Non-intrusive appliance load monitoring is the process of disaggregating a household's total electricity consumption into its contributing appliances. In this paper we propose an approach by which individual appliances can be iteratively separated from an aggregate load. Unlike existing approaches, our approach does not require training data to be collected by sub-metering individual appliances, nor does it assume complete knowledge of the appliances present in the household. Instead, we propose an approach in which prior models of general appliance types are tuned to specific appliance instances using only signatures extracted from the aggregate load. The tuned appliance models are then used to estimate each appliance's load, which is subsequently subtracted from the aggregate load. This process is applied iteratively until all appliances for which prior behaviour models are known have been disaggregated. We evaluate the accuracy of our approach using the REDD data set, and show the disaggregation performance when using our training approach is comparable to when sub-metered training data is used. We also present a deployment of our system as a live application and demonstrate the potential for personalised energy saving feedback.
Sensing the Air We Breathe — The OpenSense Zurich Dataset
Authors: Li Jason Jingshi , Faltings Boi , Saukh Olga , Hasenfratz David , Beutel Jan
Published: June 2022

Monitoring and managing urban air pollution is a significant challenge for the sustainability of our environment. We quickly survey the air pollution modeling problem,introduce a new dataset of mobile air quality measurements in Zurich, and discuss the challenges of making sense of these data.
Learning Non-Stationary Space-Time Models for Environmental Monitoring
Authors: Garg Sahil , Singh Amarjeet , Ramos Fabio
Published: June 2022

One of the primary aspects of sustainable development involves accurate understanding and modeling of environmental phenomena. Many of these phenomena exhibit variations in both space and time and it is imperative to develop a deeper understanding of techniques that can model space-time dynamics accurately. In this paper we propose NOSTILL-GP - NOn-stationary Space TIme variable Latent Length scale GP, a generic non-stationary, spatio-temporal Gaussian Process (GP) model. We present several strategies, for efficient training of our model, necessary for real-world applicability. Extensive empirical validation is performed using three real-world environmental monitoring datasets, with diverse dynamics across space and time. Results from the experiments clearly demonstrate general applicability and effectiveness of our approach for applications in environmental monitoring.
Pre-Symptomatic Prediction of Plant Drought Stress Using Dirichlet-Aggregation Regression on Hyperspectral Images
Authors: Kersting Kristian , Xu Zhao , Wahabzada Mirwaes , Bauckhage Christian , Thurau Christian , Römer Christoph , Ballvora Agim , Rascher Uwe , Leon Jen , Plümer Lutz
Published: June 2022

Pre-symptomatic drought stress prediction is of great relevance in precision plant protection, ultimately helping to meet the challenge of "How to feed a hungry world?". Unfortunately, it also presents unique computational problems in scale and interpretability: it is a temporal, large-scale prediction task, e.g., when monitoring plants over time using hyperspectral imaging, and features are `things' with a `biological' meaning and interpretation and not just mathematical abstractions computable for any data. In this paper we propose Dirichlet-aggregation regression (DAR) to meet the challenge. DAR represents all data by means of convex combinations of only few extreme ones computable in linear time and easy to interpret.Then, it puts a Gaussian process prior on the Dirichlet distributions induced on the simplex spanned by the extremes. The prior can be a function of any observed meta feature such as time, location, type of fertilization, and plant species. We evaluated DAR on two hyperspectral image series of plants over time with about 2 (resp. 5.8) Billion matrix entries. The results demonstrate that DAR can be learned efficiently and predicts stress well before it becomes visible to the human eye.
Lagrangian Relaxation Techniques for Scalable Spatial Conservation Planning
Authors: Kumar Akshat , Wu Xiaojian , Zilberstein Shlomo
Published: June 2022

We address the problem of spatial conservation planning in which the goal is to maximize the expected spread of cascades of an endangered species by strategically purchasing land parcels within a given budget. This problem can be solved by standard integer programming methods using the sample average approximation (SAA) scheme. Our main contribution lies in exploiting the separable structure present in this problem and using Lagrangian relaxation techniques to gain scalability over the flat representation. We also generalize the approach to allow the application of the SAA scheme to a range of stochastic optimization problems. Our iterative approach is highly efficient in terms of space requirements and it provides an upper bound over the optimal solution at each iteration. We apply our approach to the Red-cockaded Woodpecker conservation problem. The results show that it can find the optimal solution significantly faster---sometimes by an order-of-magnitude---than using the flat representation for a range of budget sizes.
Complex Task Learning from Unstructured Demonstrations
Authors: Niekum Scott
Published: June 2022

Much work in learning from demonstration has focused on learning simple tasks from structured demonstrations that have a well-defined beginning and end. As we attempt to scale robot learning to increasingly complex tasks, it becomes intractable to learn task policies monolithically. Furthermore, it is desirable to be able to learn from natural, unstructured demonstrations, which are unsegmented, possibly incomplete, and may come from different tasks. We propose a three-part approach to designing a natural, scalable system that allows a robot to learn tasks of increasing complexity by automatically building and refining a library of skills over time. First, we describe a Bayesian nonparametric model that can segment unstructured demonstrations into appropriate numbers of component skills and recognize repeated skills across demonstrations and tasks. These skills can then be parameterized and generalized to new situations. Second, we propose to create a system that allows the user to provide unstructured corrections and feedback to the robot, without requiring any knowledge of the robot's underlying representation of the task or its component skills. Third, we propose to infer the user's intentions for each segmented skill and autonomously improve these skills using reinforcement learning. This approach will be applied to learn and generalize complex, multi-step tasks that are beyond the reach of current LfD methods, using the PR2 mobile manipulator as a testing platform.
A Sequential Decision Approach to Ordinal Preferences in Recommender Systems
Authors: Tran Truyen , Phung Dinh , Venkatesh Svetha
Published: June 2022

We propose a novel sequential decision approach to modeling ordinal ratings in collaborative filtering problems. The rating process is assumed to start from the lowest level, evaluates against the latent utility at the corresponding level and moves up until a suitable ordinal level is found. Crucial to this generative process is the underlying utility random variables that govern the generation of ratings and their modelling choices. To this end, we make a novel use of the generalised extreme value distributions, which is found to be particularly suitable for our modeling tasks and at the same time, facilitate our inference and learning procedure. The proposed approach is flexible to incorporate features from both the user and the item. We evaluate the proposed framework on three well-known datasets: MovieLens, Dating Agency and Netflix. In all cases, it is demonstrated that the proposed work is competitive against state-of-the-art collaborative filtering methods.
On Completeness Classes for Query Evaluation on Linked Data
Authors: Harth Andreas , Speiser Sebastian
Published: June 2022

The advent of the Web of Data kindled interest in link-traversal (or lookup-based) query processing methods, with which queries are answered via dereferencing a potentially large number of small, interlinked sources. While several algorithms for query evaluation have been proposed, there exists no notion of completeness for results of so-evaluated queries. In this paper, we motivate the need for clearly-defined completeness classes and present several notions of completeness for queries over Linked Data, based on the idea of authoritativeness of sources, and show the relation between the different completeness classes.
The Parameterized Complexity of Abduction
Authors: Fellows Michael , Pfandler Andreas , Rosamond Frances , Rümmele Stefan
Published: June 2022

Abduction belongs to the most fundamental reasoning methods. It is a method for reverse inference, this means one is interested in explaining observed behavior by finding appropriate causes. We study logic-based abduction, where knowledge is represented by propositional formulas. The computational complexity of this problem is highly intractable in many interesting settings. In this work we therefore present an extensive parameterized complexity analysis of abduction within various fragments of propositional logic together with (combinations of) natural parameters.
Conflict-Based Belief Revision Operators in Possibilistic Logic
Authors: Qi Guilin , Wang Kewen
Published: June 2022

In this paper, we investigate belief revision in possibilistic logic, which is a weighted logic proposed to deal with incomplete and uncertain information. Existing revision operators in possibilistic logic are restricted in the sense that the input information can only be a formula instead of a possibilistic knowledge base which is a set of weighted formulas. To break this restriction, we consider weighted prime implicants of a possibilistic knowledge base and use them to define novel revision operators in possibilistic logic. Intuitively, a weighted prime implicant of a possibilistic knowledge base is a logically weakest possibilistic term (i.e., a set of weighted literals) that can entail the knowledge base. We first show that the existing definition of a weighted prime implicant is problematic and need a modification. To define a revision operator using weighted prime implicants, we face two problems. The first problem is that we need to define the notion of a conflict set between two weighted prime implicants of two possibilistic knowledge bases to achieve minimal change. The second problem is that we need to define the disjunction of possibilistic terms. We solve these problems and define two conflict-based revision operators in possibilistic logic. We then adapt the well-known postulates for revision proposed by Katsuno and Mendelzon and show that our revision operators satisfy four of the basic adapted postulates and satisfy two others in some special cases.
Reformulating Temporal Action Logics in Answer Set Programming
Authors: Lee Joohyung , Palla Ravi
Published: June 2022

Temporal Action Logics (TAL) is a class of temporal logics for reasoning about actions. We present a reformulation of TAL in Answer Set Programming (ASP), and discuss some synergies it brings. First, the reformulation provides a means to compute TAL using efficient answer set solvers. Second, TAL provides a structured high-level language for ASP (possibly with constraint solving). Third, the reformulation allows us to compute integration of TAL and ontologies using answer set solvers, and we illustrate its usefulness in the healthcare domain in the context of medical expert systems.
Generalized Sampling and Variance in Counterfactual Regret Minimization
Authors: Gibson Richard , Lanctot Marc , Burch Neil , Szafron Duane , Bowling Michael
Published: June 2022

In large extensive form games with imperfect information, Counterfactual Regret Minimization (CFR) is a popular, iterative algorithm for computing approximate Nash equilibria. While the base algorithm performs a full tree traversal on each iteration, Monte Carlo CFR (MCCFR) reduces the per iteration time cost by traversing just a sampled portion of the tree. On the other hand, MCCFR's sampled values introduce variance, and the effects of this variance were previously unknown. In this paper, we generalize MCCFR by considering any generic estimator of the sought values. We show that any choice of an estimator can be used to probabilistically minimize regret, provided the estimator is bounded and unbiased. In addition, we relate the variance of the estimator to the convergence rate of an algorithm that calculates regret directly from the estimator. We demonstrate the application of our analysis by defining a new bounded, unbiased estimator with empirically lower variance than MCCFR estimates. Finally, we use this estimator in a new sampling algorithm to compute approximate equilibria in Goofspiel, Bluff, and Texas hold'em poker. Under each of our selected sampling schemes, our new algorithm converges faster than MCCFR.
Security Games for Controlling Contagion
Authors: Tsai Jason , Nguyen Thanh , Tambe Milind
Published: June 2022

Many strategic actions carry a ‘contagious’ component beyond the immediate locale of the effort itself. Viral marketing and peacekeeping operations have both been observed to have a spreading effect. In this work, we use counterinsurgency as our illustrative domain. Defined as the effort to block the spread of support for an insurgency, such operations lack the manpower to defend the entire population and must focus onthe opinions of a subset of local leaders. As past researchers of security resource allocation have done, we propose using game theory to develop such policies and model the interconnected network of leaders as a graph. Unlike this past work in security games, actions in these domains possess a probabilistic, non-local impact. To address this new class of security games, we combine recent research in influence blocking maximization with a double oracle approach and create novel heuristic oracles to generate mixed strategies for a real-world leadership network from Afghanistan, synthetic leadership networks, and a real social network. We find that leadership networks that exhibit highly interconnected clusters can be solved equally well by our heuristic methods, but our more sophisticated heuristics outperform simpler ones in less interconnected social networks.