bluuebunny/crossref_metadata_2025 huggingface dataset:
Transitive taxonomic systems (TTS) and speciation during range dynamics
Authors:   National Museum of Natural History, NAS of Ukraine (Kyiv, Ukraine), Zagorodniuk Igor
Published: June 2022

The system of views on the structure of geographic ranges of species (superspecies) and their dynamics as one of the key features of species and the basis of taxonomic differentiation and evolution is considered. The mechanisms leading to the formation of new taxa in several ways are analysed, including (1) the formation of transitive taxonomic systems (TTS), in which spatial differentiation leads to the formation of geographically differentiated races as ‘small’ species; (2) the formation of new geographical races in relation to the maternal species (plesions), distributed within the primary ranges; (3) the formation of sibling species as a result of dispersal of one ‘small’ species into the range of the sister species. All such groups of ‘small’ species coexist in time and illustrate models that correspond to E. E. Reclus’s view of ‘geography is history in space.’ A number of illustrative cases discovered in the analysis of the taxonomic heterogeneity of different groups of mammals of the European fauna or the Palaearctic as a whole are considered. In particular, there were analysed the features of spatial-taxonomic differentiation in allospecies complexes that fall under the definition of TTS, in which the distribution of allospecies reflects the patterns of spatial differentiation of the ‘large’ species over time (phylogeographic patterns). Similar complexes have been demonstrated on the example of ground squirrels, birch mice, and wood mice. The formation of TTS, as well as new forms as a result of invasions into new ranges (or dispersal to ranges of adjacent forms) is considered within the amplificative species concept (ASCo), according to which specialization occurs not as a result of reduction of both the range and variability (classic models with founder effect or bottleneck), but in the phase of flourishing of the species, in particular when new populations emerge outside the initial natural ranges due to expansions or invasions. The invasive model of speciation was formed based on this idea, and a partial example of it is the formation of sympatric pairs of sibling species formed as a result of secondary sympatry, i.e. expansion. Examples from other groups, in particular regarding the formation of compilospecies and other variants of hybridogenic taxa provoked by introductions or invasions, are considered. All this is viewed through the prism of the concept of speciesness as the level of achievement of evolutionary separateness.
The prominent Ukrainian ichthyologist and museologist Yuriy Movchan (1936–2021)
Authors:   National Museum of Natural History, NAS of Ukraine (Kyiv, Ukraine), Manilo Leonid , Peskov Volodymyr ,   National Museum of Natural History, NAS of Ukraine (Kyiv, Ukraine)
Published: June 2022

A brief overview of the life and scientific achievements of Yuriy Movchan, an outstanding Ukrainian zoologist, museologist, collector of zoological collections, fish expert, and author of the ichthyological exhibition of the National Museum of Natural History NAS of Ukraine is presented. Biographic data are given based on the scientist’s personal file, which is preserved in the archive of the National Museum of Natural History NAS of Ukraine, as well as according to his autobiography published in the jubilee volume of the Proceedings of the Zoological Museum (Vol. 50, 2019). In the context of Yuriy Movchan’s scientific achievements, a list of his main publications is given, including handbooks, scientific monographs, catalogues, and guides to the zoological museum. Yuriy Movchan’s creative life was practically entirely related to the zoological museum of the National Academy of Sciences of Ukraine. Working in the zoological museum, Yuriy Vasyliovych has grown from museum attendant to a prominent ichthyologist, specialist of fish fauna of all kinds of water bodies of Ukraine, including inland and marine waters, aborigine and adventive fauna components, rare and industrial fishes, etc. The fish collection of NMNH includes more than 47 740 specimens of 567 fishes collected by Yu. Movchan personally and with fellow scientists. Yu. Movchan paid a great deal of attention to the conservation of rare and threatened species of Ukraine’s fish fauna. Voluntarily he worked as academic secretary of the zoological section at the National Commission on the Red Data Book of Ukraine, coordinated and edited the chapter ‘Cyclostomes and Fishes,’ authored 11 species reviews in the second (1994) and 24 in the third (2009) edition of the Red Data Book of Ukraine. His most cited works are presented. Yuriy Movchan worked until his last days, even when he was chained to his wheelchair, completing the editing of the second edition of his fundamental work ‘Fishes of Ukraine’ and seeking an opportunity to publish it. His late publications are devoted to the history of creation of the zoological exhibition and scientific collection of cyclostomes and fishes of NMNH.
Governance and Bank Performance: Do Bank Risk Matter ?
Authors: Widarwati Estu , Karmila Soni , Nurmalasari Nunik
Published: June 2022

Governance becomes a guideline for the banking management system and is essential for banking survival during regular economic crises. We investigate the impact of governance on performance in the Indonesians' conventional and examine the mediating role of bank risk in bank governance and performance relationship. The samples are 18 conventional banks listed on Indonesia Stock Exchange (IDX) from 2014 to 2021 and analyzed using panel data regression and sobel test. We find the risk of state-own bank higher than private bank and foreign bank that could leads to lower performance. Then the results indicate that board size and board age influence bank risk and bank performance. Banks should consider the board size for efficiency and also the maximum standard of their directors' age based on arguments related to innovation-based work productivity in the competitive banking industry. The subsequent exploration of banking governance research is needed by examining the differences in bank ownership and bank characteristics linked to bank risk which is strong evidence as mediation in this study.JEL Classification: G20, G30, G32, G34
Do Fraud Hexagon Components Promote Fraud in Indonesia?
Authors: Alfarago Dio , Mabrur Azas
Published: June 2022

This study provides information about the likelihood of the natureof fraud companies so that investors and stakeholders can makebetter decisions. The Beneish model and the fraud theory aretwo well-developed ideas for understanding fraud motivationsand detecting earnings manipulation in a corporation. Unlikeprevious studies using the fraud triangle, this study uses the latesttheory (the fraud hexagon) perspective to detect fraud actions.Thus, this study aims to examine the applicability of the fraudhexagon components in combination with the M-score fromthe Beneish model. Seventy-six manufacturing firms listed onIndonesia Stock Exchange from 2015 to 2019 were chosen assamples. The findings confirmed that enterprises with fraud tendto: be more financially stable, be more leveraged, have higherprofitability, have cooperation projects with the government, havemore related-party transactions, have more auditor changes, beless liquid, less changing directors, be less supervised, and lessdisplay CEO.’s picture.JEL Classification: K40, K42
Machine Learning Forecasts to Reduce Risk of Entrainment Loss of Endangered Salmonids at Large-Scale Water Diversions in the Sacramento–San Joaquin Delta, California
Authors:   ICF, Tillotson Michael , Hassrick Jason ,   ICF, Collins Alison ,   The Metropolitan Water District of Southern California, Phillis Corey ,   The Metropolitan Water District of Southern California
Published: June 2022

Incidental entrainment of fishes at large-scale state and federal water diversion facilities in the Sacramento-San Joaquin Delta, California, can trigger protective management actions when limits imposed by environmental regulations are approached or exceeded. These actions can result in substantial economic costs, and likewise they can affect the status of vulnerable species. Here, we examine data relevant to water management actions during January–June; the period when juvenile salmonids are present in the Delta. We use a quantile regression forest approach to create a risk forecasting tool, which can inform adjustments of diversions based on near real-time predictions. Models were trained using historical entrainment data (Water Years 1999–2019) for Sacramento River winter-run Chinook Salmon or Central Valley Steelhead and a suite of environmental and water operations metrics. A range of models was developed; their performance was evaluated by comparison of a quantile loss metric. The models were validated through examination of partial dependence plots, cross-validation procedures, and further evaluated through WY 2019 pilot testing, which integrated real-world uncertainty in environmental parameters into model predictions. For both species, the strongest predictor of loss was the previous week’s entrainment loss. In addition, risk increased with higher water exports and more negative Old and Middle Rivers (OMR) flows. Point estimates of loss were modestly correlated with observations (R2 0.4 to 0.6), but the use of a quantile regression approach provided reliable prediction intervals. For both species, the predicted 75th quantile appears to be a robust and conservative estimator of entrainment risk, with overprediction occurring in fewer than 20% of cases. This quantile balances the magnitude of over- and under-prediction and results in a low probability (< 5% of predictions) of unexpected high-take events. These models, and the web-based application through which they are made accessible to non-technical users, can provide a useful and complementary approach to the current system of managing entrainment risk.
HIPONIMI DALAM TERJEMAHAN MAULID DIBA’ KARYA ACHMAD SUNARTO
Authors: Fauzi Ahmad Riza , Sumarlam Sumarlam
Published: June 2022

Hyponymy is one of the studies in lexical discourse. Translation as a linguistic product certainly has various perspectives in language studies, for example, the study of hyponymy in the translation of maulid diba'. Maulid diba 'is a book of poetry that is well-known among the Muslim community in Indonesia and the world. This book contains the life history of the prophet and after it, therefore it is assumed that there is hyponymy in the translation of the text. This study discusses the hyponymy in the translation of Maulid diba' by Achmad Sunarto and its context. This research is a qualitative descriptive study. The data collection method used in this research is the listen and note method. The data analysis method uses the matching method and the agih method. The source of data in this study is the book Translation of Maulid Diba' by Achmad Sunarto published by Thulus Harapan, in the city of Surabaya in 2016. Finally, the results of this study found seven categories of hyponymy, namely 1) hyponymy category of the characteristics of Rasululah, 2) hyponymy of the attributes of Allah, 3) hyponymy of human anatomy (the majesty of Allah), 4) hyponymy of human anatomy (attributes of the Prophet), 5) hyponymy of the names of the prophets, 6) hyponymy of the solar system, and 7) the names of animals.Keywords: hyponymy, translation of maulid diba', Achmad Sunarto
ANALISIS TEKNIK PENERJEMAHAN BAHASA ARAB KE BAHASA INDONESIA DALAM CERAMAH HABIB UMAR BIN HAFIDZ
Authors: Hensa Utama Muhammad Apridho
Published: June 2022

Penelitian ini bertujuan untuk mendeskripsikan dan menjabarkan teknik penerjemahan bahasa Arab ke bahasa Indonesia dalam ceramah Habib Umar Bin Hafidz. Penelitian ini merupakan penelitian terjemahan dengan menggunakan data kualitatif dan metode deskriptif. Sumber data dalam penelitian ini berupa 10 menit awal dari 39 menit video youtube dari kanal “Al Murid Ahbaab” dengan judul “Ceramah Agama Terbaru Habib Umar bin Hafidz | Terjemahan Habib Ali Zainal Abidin dan Habib Jindan” dan data berupa kalimat-kalimat hasil terjemahan oleh Habib Ali Zainal Abidin dan Habib Jindan. Hasil penelitian dan simpulan dari artikel ini adalah terdapat beberapa jenis teknik penerjemahan yang dominan digunakan pada salah satu video youtube dari kanal “Al Murid Ahbaab”, seperti teknik kesepadanan lazim, amplifikasi, deskripsi, penerjemahan harfiah, reduksi. Teknik-teknik tersebut memudahkan penerjemah untuk mendapatkan hasil terjemahan yang ideal.
Kritik Narasi Sejarah Terhadap Sosok Alauddin Khalji Dalam Film Padmaavat
Authors: Setyorini Fitri Sari
Published: June 2022

Tulisan ini terutama untuk menjawab tiga persoalan. Pertama, bagaimana penggambaran Sultan Alauddin Khalji dalam film Padmaavat. Kedua, bagaimana sumber-sumber sejarah India mencatat tentang sosok Alauddin Khalji.  Ketiga, bagaimana analisis perbandingan Alauddin Khalji dalam film dan dari data sejarah. Penelitian ini bertujuan untuk mengungkapkan rekonstruksi sejarah secara menyeluruh terhadap sosok Alauddin Khalji berdasarkan fakta sejarah secara ilmiah sehingga dapat menampilkan narasi yang objektif. Penelitian ini merupakan penelitian kualitatif dengan studi kepustakaan dan sinematografi serta menggunakan pendekatan dan metode  sejarah dalam analisisnya. Analisa digunakan dalam mengurai dan menyatukan fakta-fakta sejarah yang bersifat fragmentaris menjadi satu kesatuan yang utuh. Hasil penelitian menunjukkan bahwa Rani Padmini atau Padmaavat yang terdapat dalam film maupun di dalam karya sastra Malik Muhammad Jayasi adalah tokoh fiktif. Karya sastra tidak bisa dijadikan sebagai sumber sejarah karena di dalamnya terdapat imajinasi tak terbatas dan interpretasi dari sastrawan, namun peristiwa sejarah baik tokoh, tempat, waktu dan peristiwanya dapat dijadikan sebagai latar belakang dalam karya sastra. Sementara proses adaptasi dari karya sastra ke dalam film merupakan salah satu perwujudan kemajuan di dalam seni pertunjukkan. Apa yang terdapat dalam film tidak harus sama persis dalam karya sastra maupun peristiwa sejarah. Sutradara memiliki kewenangan dalam memahami, mengembangkan, dan mengimprovisasi tema yang ia angkat.
PELARANGAN DAN PERJUANGAN: PEMAKAIAN JILBAB PELAJAR PUTRI PADA MASA ORDE BARU TAHUN 1982-1991
Authors: Nuraeni Leni , Nuraeni Leni , Gumilar Setia
Published: June 2022

Jilbab merupakan baju kurung atau penutup kepala yang lapang dan dapat menutupi aurat perempuan kecuali wajah. Di Indonesia jilbab mulai populer dan digunakan oleh masyarakat khususnya para pelajar pada tahun 80an. Pemakaian jilbab dikalangan pelajar tersebut disebabkan oleh adanya gerakan-gerakan dakwah seperti yang terjadi di Mesjid Salman ITB dalam bentuk pelatihan LMD, SII, dan sebagainya. Maraknya pemakaian jilbab pada masa pemerintahan Orde Baru tahun 1982-1991 menimbulkan tantangan dan perjuangan bagi para pelajar, karena bertentangan dengan kebijakan  pemerintah. Untuk menjawab masalah tersebut, arah penulisan dalam artikel ini menggunakan metode penelitian sejarah yang bertujuan untuk menjelaskan Pelarangan dan Perjuangan Pemakaian Jilbab Bagi Kalangan Pelajar pada Masa Orde Baru Tahun 1982-1991. Pengumpulan data mengenai tema tersebut dilakukan melalui penelusuran literature. Temuan-temuannya yaitu berupa polemik yang terjadi antara para pelajar dan sekolah-sekolah negeri. Para pelajar memakai jilbab ke sekolah telah melanggar SK 052/C/Kep/D.1982. Polemik pemakaian jilbab tersebut tidak bisa dilepaskan dari hubungan antara umat Islam dan pemerintah Orde Baru. Dimana pada masa itu pemerintah banyak mencurigai umat Islam. Namun, diakhir pemerintahannya, pemerintah Orde Baru mendekati dan mengakomodasi Islam. Kebijakan mengenai seragam sekolah diperbaharuhi hingga di keluarkanlah SK No. 100/C/Kep/D/1991 yang memperbolehkan para pelajar memakai jilbab ke sekolah. Keluarnya SK 100, selain disebabkan oleh akomodasi pemerintah terhadap Islam, tetapi juga adanya upaya penyelesaian dari beberapa Organisasi-organisasi Massa dan MUI.
Relationship between cold executive functions and self-regulated learning management in college students
Authors: Pinochet-Quiroz Palmenia , Lepe-Martínez Nancy , Gálvez-Gamboa Francisco , Ramos-Galarza Carlos , Del-Valle-Tapia Milenko , Acosta-Rodas Pamela
Published: June 2022

The aim of this research was to analyze the relationship between cold executive functions (cEFs), and self-regulated learning management (SRLM) in college students. There is a positive and a statistically significant relationship between cold executive functions (cEFs) and self-regulated learning management (SRLM). This research is a quantitative, cross-sectional, descriptive, and inferential study, with a correlational approach. The sample was non-probabilistic, by convenience sampling, composed of n = 379 college students belonging to pedagogy careers, 64.1% were males, and 35.9% females, aged between 17 and 34 years old (M = 19.82, SD = 2.41). The results show that there is a strong association between cold executive functions and self-regulated learning management since high performance in cEFs would imply a high performance on learning management. On the other hand, it is also observed a predictive value of planning cEF on SRLM, meaning that, an optimal level of planning would imply adequate management of learning processes. The original contribution of this study is to provide evidence to consider supporting plans for college students to improve their skills in the cEFs, due to the negative impact that failure in higher education represents for the student, their families, and university system. Finally, we think it is necessary to continue the research in depth of these variables, and their influence in higher education academic performance.
Nieznana brązowa szpila uchata
Authors:   Instytut Archeologii UMCS, Lublin, Polska, Kłosińska Elżbieta Małgorzata
Published: June 2022

At the end of the last century, a damaged pin with an eyelet was found. The connection of this find with the vicinity of Biłgoraj and the territories east of the Vistula River in general raises serious doubts. Unfortunately, after the death of the collector, whose collection had contained the find for many years, it was not possible to verify the earlier findings. The analysed pin was probably discovered in Silesia or Greater Poland, where there is a concentration of such decorations, which in the literature are generally referred to as type C pins with an eyelet and dated to II period and the beginning of III period of the Bronze Age, at the same time marking the early stage of the Lusatian culture on these areas. In Silesia and Greater Poland, however, there are no such artefacts that could be considered analogous to the discussed pin. It is somewhat similar to the item of the Jelenin variant discovered in Silesia (unknown place), Greater Poland (Gąsawa) and Moravia.
‘With a Weapon in Hand and a Horse by Side.’ Weapons and Horse Harness in Graves of Vekerzug Culture from an Interregional Perspective
Authors:   Institute of Archaeology of the Slovak Academy of Sciences, Nitra, Slovak Republic, Kozubová Anita
Published: June 2022

This study deals with graves of Vekerzug culture, which contained weapons and horse harness. These graves reflect an evident social differentiation of Vekerzug society. Special attention in the study was paid to the most accurate geographic and cultural determination of the origin of individual weapon types and horse harness components in the context of new knowledge about Vekerzug culture and answering the question to what extent these finds reflect its interregional contacts. Important is also definition of possible armament schemes of Vekerzug culture and their comparison with armament schemes in the neighbouring cultural regions, especially with the forest-steppe Western Podolian group, Ciumbrud culture and Ferigile culture. Cultural and spatial analyses of individual types of weapons and horse harness as well as of the armament schemes of Vekerzug culture show that the problem of interregional contacts of this culture, mainly the eastern ones, must be considered more differentially than it has been previously presented in scientific literature. At the same time, they confirm the recent knowledge that the effect of eastern influences on Vekerzug culture is in scientific literature without a reason constantly overestimated.
Elementy obuwia odnalezione na ulicy Kościuszki w Rzeszowie
Authors:   Instytut Archeologii Uniwersytetu Rzeszowskiego, Polska, Gorazd-Dziuban Paulina
Published: June 2022

This article is an attempt to outline the issues related to the elements of footwear discovered at Kościuszko Street in Rzeszow. Considering the collected artefacts, awls and protective shoe taps are the best preserved items. The former were used for the production of footwear, while the latter were used to protect it during its use. The chronology of these artefacts, based on the analysis of shoe taps by T. Cymbalak, covered the period from the 16th to the beginning of the 18th century (one of them can also be dated at the beginning of the 20th century). Their shape and size were related to the size of the heel, and the one to the size of the shoe. Borrowings from Western Europe as well as the East had a significant impact on the use of this type of element of footwear, although the location of Rzeszow suggests the possibility of stronger eastern influences. Undoubtedly, all discovered shoe taps should be associated with the relics of the Modern Period footwear. The discussed artefacts appeared as individual finds in layers related to the use of the street which connected the market square with the parish church. In the course of the archaeological watching brief, 427 fragments of shoes were found. The assemblage of artefacts was discovered in layers dated from the turn of the 16th and 17th centuries to the beginning of 18th century. In the analysed material, there were components of footwear, both the upper and bottom parts of shoes, as well as numerous post-production scraps and unidentified elements. Researching the analysed footwear from Rzeszow, we can observe a significant progress in the technology of cut and sewing, from simple forms, made of one piece of leather, to shoes made of several layers and several parts. Foot covers are an example of not very rich footwear for this period of time. The cut and the form of shoes are very similar to this type of artefacts found at other sites in Poland.
Diagnóstico clínico integral de adultos mayores atendidos en Perú
Authors:   Universidad Nacional Autónoma de Chota, Asenjo-Alarcón José Ander
Published: June 2022

Introducción: Los adultos mayores constituyen el grupo poblacional más vulnerable y el menos favorecido por los sistemas de salud, transitan por un proceso de involución progresiva que puede repercutir en su salud; por tanto, se torna relevante el diagnóstico clínico oportuno y adecuado para identificar eventuales alteraciones. Objetivo: Establecer el diagnóstico clínico integral según sexo y edad de adultos mayores atendidos a nivel nacional en el Perú. Materiales y métodos: Se realizó un estudio descriptivo, transversal y retrospectivo, durante marzo y abril del 2021, en 60698 adultos mayores atendidos en todos los departamentos del Perú. La valoración física, funcional, mental y social de los adultos mayores se realizó mediante la Historia Clínica de Atención Integral de Salud del Adulto Mayor y se interpretó con su guía técnica. Se describieron frecuencias absolutas, relativas, intervalos de confianza para proporciones al 95% y el chi cuadrado de homogeneidad. Resultados: El 49,4% de adultos mayores estaban enfermos, de los cuales el 50,8% fueron mujeres y el 47,4% varones, el 50,0% tenían de 60 a 69 años, el 50,6% de 70 a 79 años y el 46,1% de 80 a más años. Se encontraron diferencias estadísticamente significativas entre el diagnóstico clínico integral por sexo y edad (p = 0,000). Discusión: Independientemente del número de participantes en todos los contextos estudiados, al menos una enfermedad crónica coexiste medianamente en los adultos mayores, sin ser determinante el lugar donde viven, pues el proceso de envejecimiento solo puede ser distinto en su velocidad de progresión y en las condiciones en que se presenta. Conclusión: Los adultos mayores en su mayoría estaban enfermos, fueron mujeres y tenían de 70 a 79 años, las diferencias por sexo y edad en el diagnóstico clínico integral fueron significativas. Las intervenciones en etapas previas contribuirían de manera importante en un envejecimiento saludable. Como citar este artículo: Asenjo-Alarcón José Ander. Diagnóstico clínico integral de adultos mayores atendidos en Perú. Revista Cuidarte. 2022;13(2): e2485. http://dx.doi.org/10.15649/cuidarte.2485
Face Behind Makeup
Authors: Wang Shuyang , Fu Yun
Published: June 2022

In this work, we propose a novel automatic makeup detector and remover framework. For makeup detector, a locality-constrained low-rank dictionary learning algorithm is used to determine and locate the usage of cosmetics. For the challenging task of makeup removal, a locality-constrained coupled dictionary learning (LC-CDL) framework is proposed to synthesize non-makeup face, so that the makeup could be erased according to the style. Moreover, we build a stepwise makeup dataset (SMU) which to the best of our knowledge is the first dataset with procedures of makeup. This novel technology itself carries many practical applications, e.g. products recommendation for consumers; user-specified makeup tutorial; security applications on makeup face verification. Finally, our system is evaluated on three existing (VMU, MIW, YMU) and one own-collected makeup datasets. Experimental results have demonstrated the effectiveness of DL-based method on makeup detection. The proposed LC-CDL shows very promising performance on makeup removal regarding on the structure similarity. In addition, the comparison of face verification accuracy with presence or absence of makeup is presented, which illustrates an application of our automatic makeup remover system in the context of face verification with facial makeup.
On the Minimum Differentially Resolving Set Problem for Diffusion Source Inference in Networks
Authors: Zhou Chuan , Lu Wei-Xue , Zhang Peng , Wu Jia , Hu Yue , Guo Li
Published: June 2022

In this paper we theoretically study the minimum Differentially Resolving Set (DRS) problem derived from the classical sensor placement optimization problem in network source locating. A DRS of a graph G = (V, E) is defined as a subset S ⊆ V where any two elements in V can be distinguished by their different differential characteristic sets defined on S. The minimum DRS problem aims to find a DRS S in the graph G with minimum total weight Σv∈S w(v). In this paper we establish a group of Integer Linear Programming (ILP) models as the solution. By the weighted set cover theory, we propose an approximation algorithm with the Θ(ln n) approximability for the minimum DRS problem on general graphs, where n is the graph size.
MUST-CNN: A Multilayer Shift-and-Stitch Deep Convolutional Architecture for Sequence-Based Protein Structure Prediction
Authors: Lin Zeming , Lanchantin Jack , Qi Yanjun
Published: June 2022

Predicting protein properties such as solvent accessibility and secondary structure from its primary amino acid sequence is an important task in bioinformatics. Recently, a few deep learning models have surpassed the traditional window based multilayer perceptron. Taking inspiration from the image classification domain we propose a deep convolutional neural network architecture, MUST-CNN, to predict protein properties. This architecture uses a novel multilayer shift-and-stitch (MUST) technique to generate fully dense per-position predictions on protein sequences. Our model is significantly simpler than the state-of-the-art, yet achieves better results. By combining MUST and the efficient convolution operation, we can consider far more parameters while retaining very fast prediction speeds. We beat the state-of-the-art performance on two large protein property prediction datasets.
Hospital Stockpiling Problems with Inventory Sharing
Authors: Lofgren Eric , Vullikanti Anil
Published: June 2022

Hospitals are typically optimized to operate near capacity, and there are serious concerns that our healthcare system is not prepared for the next pandemic. Stockpiles of different supplies, e.g., personal protective equipments (PPE) and medical equipment, need to be maintained in order to be able to respond to any future pandemics. Large outbreaks occur with a low probability, and such stockpiles require big investments. Further, hospitals often have mutual sharing agreements, which makes the problem of stockpiling decisions a natural game-theoretical problem. In this paper, we formalize hospital stockpiling as a game-theoretical problem. We use the notion of pairwise Nash stability as a solution concept for this problem, and characterize its structure. We show that stable strategies can lead to high unsatisfied demands in some scenarios, and stockpiles might not be maintained at all nodes. We also show that stable strategies and the social optimum can be computed efficiently.
Poker-CNN: A Pattern Learning Strategy for Making Draws and Bets in Poker Games Using Convolutional Networks
Authors: Yakovenko Nikolai , Cao Liangliang , Raffel Colin , Fan James
Published: June 2022

Poker is a family of card games that includes many varia- tions. We hypothesize that most poker games can be solved as a pattern matching problem, and propose creating a strong poker playing system based on a unified poker representa- tion. Our poker player learns through iterative self-play, and improves its understanding of the game by training on the results of its previous actions without sophisticated domain knowledge. We evaluate our system on three poker games: single player video poker, two-player Limit Texas Hold’em, and finally two-player 2-7 triple draw poker. We show that our model can quickly learn patterns in these very different poker games while it improves from zero knowledge to a competi- tive player against human experts. The contributions of this paper include: (1) a novel represen- tation for poker games, extendable to different poker vari- ations, (2) a Convolutional Neural Network (CNN) based learning model that can effectively learn the patterns in three different games, and (3) a self-trained system that signif- icantly beats the heuristic-based program on which it is trained, and our system is competitive against human expert players.
Reuse of Neural Modules for General Video Game Playing
Authors: Braylan Alexander , Hollenbeck Mark , Meyerson Elliot , Miikkulainen Risto
Published: June 2022

A general approach to knowledge transfer is introduced in which an agent controlled by a neural network adapts how it reuses existing networks as it learns in a new domain. Networks trained for a new domain can improve their performance by routing activation selectively through previously learned neural structure, regardless of how or for what it was learned. A neuroevolution implementation of this approach is presented with application to high-dimensional sequential decision-making domains. This approach is more general than previous approaches to neural transfer for reinforcement learning. It is domain-agnostic and requires no prior assumptions about the nature of task relatedness or mappings. The method is analyzed in a stochastic version of the Arcade Learning Environment, demonstrating that it improves performance in some of the more complex Atari 2600 games, and that the success of transfer can be predicted based on a high-level characterization of game dynamics.
Judgment Aggregation under Issue Dependencies
Authors: Costantini Marco , Groenland Carla , Endriss Ulle
Published: June 2022

We introduce a new family of judgment aggregation rules, called the binomial rules, designed to account for hidden dependencies between some of the issues being judged. To place them within the landscape of judgment aggregation rules, we analyse both their axiomatic properties and their computational complexity, and we show that they contain both the well-known distance-based rule and the basic rule returning the most frequent overall judgment as special cases. To evaluate the performance of our rules empirically, we apply them to a dataset of crowdsourced judgments regarding the quality of hotels extracted from the travel website TripAdvisor. In our experiments we distinguish between the full dataset and a subset of highly polarised judgments, and we develop a new notion of polarisation for profiles of judgments for this purpose, which may also be of independent interest.
Lift-Based Bidding in Ad Selection
Authors: Xu Jian , Shao Xuhui , Ma Jianjie , Lee Kuang-chih , Qi Hang , Lu Quan
Published: June 2022

Real-time bidding has become one of the largest online advertising markets in the world. Today the bid price per ad impression is typically decided by the expected value of how it can lead to a desired action event to the advertiser. However, this industry standard approach to decide the bid price does not consider the actual effect of the ad shown to the user, which should be measured based on the performance lift among users who have been or have not been exposed to a certain treatment of ads. In this paper, we propose a new bidding strategy and prove that if the bid price is decided based on the performance lift rather than absolute performance value, advertisers can actually gain more action events. We describe the modeling methodology to predict the performance lift and demonstrate the actual performance gain through blind A/B test with real ad campaigns. We also show that to move the demand-side platforms to bid based on performance lift, they should be rewarded based on the relative performance lift they contribute.
Strategyproof Peer Selection: Mechanisms, Analyses, and Experiments
Authors: Aziz Haris , Lev Omer , Mattei Nicholas , Rosenschein Jeffrey , Walsh Toby
Published: June 2022

We study an important crowdsourcing setting where agents evaluate one another and, based on these evaluations, a subset of agents are selected. This setting is ubiquitous when peer review is used for distributing awards in a team, allocating funding to scientists, and selecting publications for conferences. The fundamental challenge when applying crowdsourcing in these settings is that agents may misreport their reviews of others to increase their chances of being selected. We propose a new strategyproof (impartial) mechanism called Dollar Partition that satisfies desirable axiomatic properties. We then show, using a detailed experiment with parameter values derived from target real world domains, that our mechanism performs better on average, and in the worst case, than other strategyproof mechanisms in the literature.
Counterfactual Regret Minimization in Sequential Security Games
Authors: Lisy Viliam , Davis Trevor , Bowling Michael
Published: June 2022

Many real world security problems can be modelled as finite zero-sum games with structured sequential strategies and limited interactions between the players. An abstract class of games unifying these models are the normal-form games with sequential strategies (NFGSS). We show that all games from this class can be modelled as well-formed imperfect-recall extensive-form games and consequently can be solved by counterfactual regret minimization. We propose an adaptation of the CFR+ algorithm for NFGSS and compare its performance to the standard methods based on linear programming and incremental game generation. We validate our approach on two security-inspired domains. We show that with a negligible loss in precision, CFR+ can compute a Nash equilibrium with five times less computation than its competitors.
Strategy-Based Warm Starting for Regret Minimization in Games
Authors: Brown Noam , Sandholm Tuomas
Published: June 2022

Counterfactual Regret Minimization (CFR) is a popular iterative algorithm for approximating Nash equilibria in imperfect-information multi-step two-player zero-sum games. We introduce the first general, principled method for warm starting CFR. Our approach requires only a strategy for each player, and accomplishes the warm start at the cost of a single traversal of the game tree. The method provably warm starts CFR to as many iterations as it would have taken to reach a strategy profile of the same quality as the input strategies, and does not alter the convergence bounds of the algorithms. Unlike prior approaches to warm starting, ours can be applied in all cases. Our method is agnostic to the origins of the input strategies. For example, they can be based on human domain knowledge, the observed strategy of a strong agent, the solution of a coarser abstraction, or the output of some algorithm that converges rapidly at first but slowly as it gets closer to an equilibrium. Experiments demonstrate that one can improve overall convergence in a game by first running CFR on a smaller, coarser abstraction of the game and then using the strategy in the abstract game to warm start CFR in the full game.
Linearized Alternating Direction Method with Penalization for Nonconvex and Nonsmooth Optimization
Authors: Wang Yiyang , Liu Risheng , Song Xiaoliang , Su Zhixun
Published: June 2022

Being one of the most effective methods, Alternating Direction Method (ADM) has been extensively studied in numerical analysis for solving linearly constrained convex program. However, there are few studies focusing on the convergence property of ADM under nonconvex framework though it has already achieved well-performance on applying to various nonconvex tasks. In this paper, a linearized algorithm with penalization is proposed on the basis of ADM for solving nonconvex and nonsmooth optimization. We start from analyzing the convergence property for the classical constrained problem with two variables and then establish a similar result for multi-block case. To demonstrate the effectiveness of our proposed algorithm, experiments with synthetic and real-world data have been conducted on specific applications in signal and image processing.
On the Completeness of Best-First Search Variants That Use Random Exploration
Authors: Valenzano Richard , Xie Fan
Published: June 2022

While suboptimal best-first search algorithms like Greedy Best-First Search are frequently used when building automated planning systems, their greedy nature can make them susceptible to being easily misled by flawed heuristics. This weakness has motivated the development of best-first search variants like epsilon-greedy node selection, type-based exploration, and diverse best-first search, which all use random exploration to mitigate the impact of heuristic error. In this paper, we provide a theoretical justification for this increased robustness by formally analyzing how these algorithms behave on infinite graphs. In particular, we show that when using these approaches on any infinite graph, the probability of not finding a solution can be made arbitrarily small given enough time. This result is shown to hold for a class of algorithms that includes the three mentioned above, regardless of how misleading the heuristic is.
Unsupervised Feature Selection by Heuristic Search with Provable Bounds on Suboptimality
Authors: Arai Hiromasa , Maung Crystal , Xu Ke , Schweitzer Haim
Published: June 2022

Identifying a small number of features that can represent the data is a known problem that comes up in areas such as machine learning, knowledge representation, data mining, and numerical linear algebra. Computing an optimal solution is believed to be NP-hard, and there is extensive work on approximation algorithms. Classic approaches exploit the algebraic structure of the underlying matrix, while more recent approaches use randomization. An entirely different approach that uses the A* heuristic search algorithm to find an optimal solution was recently proposed. Not surprisingly it is limited to effectively selecting only a small number of features. We propose a similar approach related to the Weighted A* algorithm. This gives algorithms that are not guaranteed to find an optimal solution but run much faster than the A* approach, enabling effective selection of many features from large datasets. We demonstrate experimentally that these new algorithms are more accurate than the current state-of-the-art while still being practical. Furthermore, they come with an adjustable guarantee on how different their error may be from the smallest possible (optimal) error. Their accuracy can always be increased at the expense of a longer running time.
Expressive Recommender Systems through Normalized Nonnegative Models
Authors: Stark Cyril
Published: June 2022

We introduce normalized nonnegative models (NNM) for explorative data analysis. NNMs are partial convexifications of models from probability theory. We demonstrate their value at the example of item recommendation. We show that NNM-based recommender systems satisfy three criteria that all recommender systems should ideally satisfy: high predictive power, computational tractability, and expressive representations of users and items. Expressive user and item representations are important in practice to succinctly summarize the pool of customers and the pool of items. In NNMs, user representations are expressive because each user's preference can be regarded as normalized mixture of preferences of stereotypical users. The interpretability of item and user representations allow us to arrange properties of items (e.g., genres of movies or topics of documents) or users (e.g., personality traits) hierarchically.
Knowledge Graph Completion with Adaptive Sparse Transfer Matrix
Authors: Ji Guoliang , Liu Kang , He Shizhu , Zhao Jun
Published: June 2022

We model knowledge graphs for their completion by encoding each entity and relation into a numerical space. All previous work including Trans(E, H, R, and D) ignore the heterogeneity (some relations link many entity pairs and others do not) and the imbalance (the number of head entities and that of tail entities in a relation could be different) of knowledge graphs. In this paper, we propose a novel approach TranSparse to deal with the two issues. In TranSparse, transfer matrices are replaced by adaptive sparse matrices, whose sparse degrees are determined by the number of entities (or entity pairs) linked by relations. In experiments, we design structured and unstructured sparse patterns for transfer matrices and analyze their advantages and disadvantages. We evaluate our approach on triplet classification and link prediction tasks. Experimental results show that TranSparse outperforms Trans(E, H, R, and D) significantly, and achieves state-of-the-art performance.
Automated Verification and Tightening of Failure Propagation Models
Authors: Bittner Benjamin , Bozzano Marco , Cimatti Alessandro , Zampedri Gianni
Published: June 2022

Timed Failure Propagation Graphs (TFPGs) are used in the design of safety-critical systems as a way of modeling failure propagation, and to evaluate and implement diagnostic systems. TFPGs are a very rich formalism: they allow to model Boolean combinations of faults and events, also dependent on the operational modes of the system and quantitative delays between them. TFPGs are often produced manually, from a given dynamic system of greater complexity, as abstract representations of the system behavior under specific faulty conditions. In this paper we tackle two key difficulties in this process: first, how to make sure that no important behavior of the system is overlooked in the TFPG, and that no spurious, non-existent behavior is introduced; second, how to devise the correct values for the delays between events. We propose a model checking approach to automatically validate the completeness and tightness of a TFPG for a given infinite-state dynamic system, and a procedure for the automated synthesis of the delay parameters. The proposed approach is evaluated on a number of synthetic and industrial benchmarks.
Qualitative Spatio-Temporal Stream Reasoning with Unobservable Intertemporal Spatial Relations Using Landmarks
Authors: De Leng Daniel , Heintz Fredrik
Published: June 2022

Qualitative spatio-temporal reasoning is an active research area in Artificial Intelligence. In many situations there is a need to reason about intertemporal qualitative spatial relations, i.e. qualitative relations between spatial regions at different time-points. However, these relations can never be explicitly observed since they are between regions at different time-points. In applications where the qualitative spatial relations are partly acquired by for example a robotic system it is therefore necessary to infer these relations. This problem has, to the best of our knowledge, not been explicitly studied before. The contribution presented in this paper is two-fold. First, we present a spatio-temporal logic MSTL, which allows for spatio-temporal stream reasoning. Second, we define the concept of a landmark as a region that does not change between time-points and use these landmarks to infer qualitative spatio-temporal relations between non-landmark regions at different time-points. The qualitative spatial reasoning is done in RCC-8, but the approach is general and can be applied to any similar qualitative spatial formalism.
Agenda Separability in Judgment Aggregation
Authors: Lang Jérôme , Slavkovik Marija , Vesic Srdjan
Published: June 2022

One of the better studied properties for operators in judgment aggregation is independence, which essentially dictates that the collective judgment on one issue should not depend on the individual judgments given on some other issue(s) in the same agenda. Independence, although considered a desirable property, is too strong, because together with mild additional conditions it implies dictatorship. We propose here a weakening of independence, named agenda separability: a judgment aggregation rule satisfies it if, whenever the agenda is composed of several independent sub-agendas, the resulting collective judgment sets can be computed separately for each sub-agenda and then put together. We show that this property is discriminant, in the sense that among judgment aggregation rules so far studied in the literature, some satisfy it and some do not. We briefly discuss the implications of agenda separability on the computation of judgment aggregation rules.
A Semantical Analysis of Second-Order Propositional Modal Logic
Authors: Belardinelli Francesco , Van der Hoek Wiebe
Published: June 2022

This paper is aimed as a contribution to the use of formal modal languages in Artificial Intelligence. We introduce a multi-modal version of Second-order Propositional Modal Logic (SOPML), an extension of modal logic with propositional quantification, and illustrate its usefulness as a specification language for knowledge representation as well as temporal and spatial reasoning. Then, we define novel notions of (bi)simulation and prove that these preserve the interpretation of SOPML formulas. Finally, we apply these results to assess the expressive power of SOPML.