bluuebunny/crossref_metadata_2025_split huggingface dataset:
Benchmarking ensemble docking methods in D3R Grand Challenge 4
Authors: Gan Jessie Low , Kumar Dhruv , Chen Cynthia , Taylor Bryn C. , Jagger Benjamin R. , Amaro Rommie E. , Lee Christopher T. 
Published: February 2022

AbstractThe discovery of new drugs is a time consuming and expensive process. Methods such as virtual screening, which can filter out ineffective compounds from drug libraries prior to expensive experimental study, have become popular research topics. As the computational drug discovery community has grown, in order to benchmark the various advances in methodology, organizations such as the Drug Design Data Resource have begun hosting blinded grand challenges seeking to identify the best methods for ligand pose-prediction, ligand affinity ranking, and free energy calculations. Such open challenges offer a unique opportunity for researchers to partner with junior students (e.g., high school and undergraduate) to validate basic yet fundamental hypotheses considered to be uninteresting to domain experts. Here, we, a group of high school-aged students and their mentors, present the results of our participation in Grand Challenge 4 where we predicted ligand affinity rankings for the Cathepsin S protease, an important protein target for autoimmune diseases. To investigate the effect of incorporating receptor dynamics on ligand affinity rankings, we employed the Relaxed Complex Scheme, a molecular docking method paired with molecular dynamics-generated receptor conformations. We found that Cathepsin S is a difficult target for molecular docking and we explore some advanced methods such as distance-restrained docking to try to improve the correlation with experiments. This project has exemplified the capabilities of high school students when supported with a rigorous curriculum, and demonstrates the value of community-driven competitions for beginners in computational drug discovery.
A Review on Metal Ion Sensors Derived from Chalcone Precursor
Authors: Mahesha Priyanka , Shetty Nitinkumar S. , Kulkarni Suresh D. 
Published: February 2022

AbstractDisclosure of new molecular probes as chromogenic and fluorogenic cation sensors is scientifically exigent work. Recently chalcone derivatives gained more attention because of their structural variability. A suitable donor and acceptor groups separated by delocalized π-orbitals display excellent chromogenic and fluorogenic properties because of intramolecular charge transfer (ICT). These designed molecular frameworks provide the coordination sites to the incoming metal ions results in small changes in the optical properties. In a typical sensing behavior, coordination leads to a large conjugation plane with the probe resulted in hypo/hyperchromic shifts or red/blue shifts. In this review, we tried to converge the reported chalcone-derived sensors and explored the design, synthesis, metal ion sensing mechanism, and practical application of the probes. We expect that this review gives a basic outline for researchers to explore the field of chalcone-based sensors further.
Long-term dynamic of nestedness in bird assemblages inhabiting fragmented landscapes
Authors: Dondina Olivia , Orioli Valerio , Tirozzi Pietro , Bani Luciano 
Published: February 2022

AbstractContextNestedness is a common pattern of species assemblages in fragmented landscapes. The spatial pattern and ecological drivers of nested communities have been widely explored, but few studies investigated their long-term variability.ObjectivesTo investigate the variability of nestedness and species-specific fragment occupancy of forest birds in a fragmented landscape affected by environmental changes over 16 years.MethodsData were obtained from the Monitoring Program of Breeding Birds in Lombardy (northern Italy). For two study periods (1997–2001, 2013–2017), we tested for overall nestedness and for sites and species nestedness independently using the NODF metric. We tested for nestedness drivers (variable selection on multiple linear regression models) and evaluated the effect of species ecological traits on fragment occupancy changes (variable selection on multiple linear regression model).ResultsThe community showed a significant nestedness driven by both selective extinction and selective colonization in both study periods. Sites nestedness was significant in the second study period only. Over 16 years the effect of distance from source areas was completely lost and only local isolation conditions drove selective colonization in the second study period. Between the two study periods, we discovered a general occupancy decrease of interior species and a significant occupancy increase of generalist species characterized by large size and large minimum area requirement.ConclusionsNestedness drivers of the investigated community significantly varied over time probably because of both environmental and demographic changes. Long-term studies are crucial to explore spatial pattern changes and to address management strategies for species conservation in fragmented landscapes.
Phenotypic and functional alterations of peritoneal macrophages in lupus-prone mice
Authors: Tejon Gabriela , Valdivieso Nicolás , Flores-Santibañez Felipe , Barra-Valdebenito Verónica , Martínez Víctor , Rosemblatt Mario , Sauma Daniela , Bono María Rosa 
Published: February 2022

AbstractBackgroundSeveral studies have demonstrated the contribution of innate immune cells, including macrophages, in promoting systemic lupus erythematosus (SLE). Macrophages, one of the most abundant cell populations in the peritoneal cavity, are considered multifunctional cells with phenotypic plasticity. However, the functional properties of peritoneal macrophages in steady-state and during the progression of SLE remain poorly defined.Methods and resultsUsing the [NZB × NZW]F1 (BWF1) murine model of SLE, we analyzed the phenotype and function of peritoneal macrophages during the disease’s onset. We found a higher frequency of peritoneal macrophages and B1a cells in BWF1-diseased mice than age-matched controls. Additionally, macrophages from diseased animals expressed lower levels of CD206, MHC-II, and Sirpα. RNAseq analysis identified 286 differentially expressed genes in peritoneal macrophages from diseased-BWF1 mice compared to control mice. Functional experiments demonstrate that peritoneal macrophages from diseased-BWF1 mice secrete higher levels of pro-inflammatory cytokines when activated with TLR7 and TLR9 agonists, and they were less efficient in suppressing the activation and proliferation of peritoneal LPS-activated B cells. These data demonstrate that peritoneal macrophages from BWF1-diseased mice present phenotypic and functional alterations shifting to a more pro-inflammatory state.ConclusionsThe increase of macrophages with an altered phenotype and function together with the accumulation of B1a cells in the peritoneal cavity of diseased-BWF1 mice may promote the progression of the disease. Advancing awareness of the role and phenotype of peritoneal macrophages in SLE may contribute to a better understanding of these types of diseases and the development of novel therapies.
Joint Income-Wealth Inequality: Evidence from Lucerne Tax Data
Authors: Gallusser David , Krapf Matthias 
Published: February 2022

AbstractUsing tax data from the Swiss canton of Lucerne, we study how measures of economic inequality change if they account for income and wealth rather than income alone. Joint income-wealth, the sum of labor income and annuitized wealth, serves as a measure of combined inequality of income and wealth. Inequality measured using joint income-wealth is higher than measured using income alone. We refine existing annuitization techniques by introducing heterogeneous returns. The joint distribution of labor income and annuitized wealth displays strong tail dependence at the top and a negative association for negative annuitized wealth. A decomposition shows that the underlying marginal distributions of labor income and annuitized wealth account for most of joint income-wealth inequality, whereas their association matters only in the tails.
Exploiting probability density function of deep convolutional autoencoders’ latent space for reliable COVID-19 detection on CT scans
Authors: Sarv Ahrabi Sima , Piazzo Lorenzo , Momenzadeh Alireza , Scarpiniti Michele , Baccarelli Enzo 
Published: February 2022

AbstractWe present a probabilistic method for classifying chest computed tomography (CT) scans into COVID-19 and non-COVID-19. To this end, we design and train, in an unsupervised manner, a deep convolutional autoencoder (DCAE) on a selected training data set, which is composed only of COVID-19 CT scans. Once the model is trained, the encoder can generate the compact hidden representation (the hidden feature vectors) of the training data set. Afterwards, we exploit the obtained hidden representation to build up the target probability density function (PDF) of the training data set by means of kernel density estimation (KDE). Subsequently, in the test phase, we feed a test CT into the trained encoder to produce the corresponding hidden feature vector, and then, we utilise the target PDF to compute the corresponding PDF value of the test image. Finally, this obtained value is compared to a threshold to assign the COVID-19 label or non-COVID-19 to the test image. We numerically check our approach’s performance (i.e. test accuracy and training times) by comparing it with those of some state-of-the-art methods.
Possibility, relevant similarity, and structural knowledge
Authors: Schoonen Tom 
Published: February 2022

AbstractRecently, interest has surged in similarity-based epistemologies of possibility. However, it has been pointed out that the notion of ‘relevant similarity’ is not properly developed in this literature. In this paper, I look at the research done in the field of analogical reasoning, where we find that one of the most promising ways of capturing relevance in similarity reasoning is by relying on the predictive analogy similarity relation. This takes relevant similarity to be based on shared properties that have structural relations to the property of interest. I argue that if we base our epistemology of possibility on similarity reasoning on the predictive analogy similarity relation, we require prior knowledge of the specifics of these structural relations. I discuss a number of possible responses to this on behalf of the similarity theorists given their methodological approach to the epistemology of modality more generally. They could either opt for making explicit the metaphysics underlying these structural relations, in which case they need to spell out how we can come to know these relations. Or they could opt for developing a theory that explains why we do not need to have explicit knowledge of these structural relations; for example by suggesting that we make use of epistemic shortcuts.
Multi-phase Fine-Tuning: A New Fine-Tuning Approach for Sign Language Recognition
Authors: Sarhan Noha , Lauri Mikko , Frintrop Simone 
Published: February 2022

AbstractIn this paper, we propose multi-phase fine-tuning for tuning deep networks from typical object recognition to sign language recognition (SLR). It extends the successful idea of transfer learning by fine-tuning the network’s weights over several phases. Starting from the top of the network, layers are trained in phases by successively unfreezing layers for training. We apply this novel training approach to SLR, since in this application, training data is scarce and differs considerably from the datasets which are usually used for pre-training. Our experiments show that multi-phase fine-tuning can reach significantly better accuracy in fewer training epochs compared to previous fine-tuning techniques
Evidence of the persistence and consistency of social signatures
Authors: Li Yue , Bond Robert M. 
Published: February 2022

AbstractHuman social networks are composed of multiple dynamic and overlapping communication networks, in which membership changes over time. However, less well understood are whether and how our communication patterns are similar or different over time and across various modes of communication. Here, we use data on the frequency of phone calls, text messages, and in-person interactions to examine the social signatures of more than 700 students in a university setting. Our analysis shows that although there is substantial turnover in participants’ networks, participants’ social signatures are persistent across time and consistent across communication modes. Further, we find that communication networks that are mediated via phone calls or text messages are more stable than are in-person networks. Our results show that, likely due to limitations in cognitive and emotional resources, people maintain networks of relatively stable size and structure their communication within those networks in predictable patterns. Our findings may help with formalizing social network theories, explaining individual-level attitudes and behaviors and aggregate-level social phenomena, and making predictions and detecting abnormalities in applied fields.
Camera traps reveal overlap and seasonal variation in the diel activity of arboreal and semi-arboreal mammals
Authors: Gracanin Ana , Mikac Katarina M. 
Published: February 2022

AbstractOur study aimed to investigate seasonal variation in the activity of arboreal and semi-arboreal mammals and investigate their overlap in temporal activity, as well temporal shifts in activity because of behavioural interference. In our camera trapping study in a fragmented landscape in south-eastern Australia, a total of ten arboreal and semi-arboreal species were found, with 35,671 independent observations recorded over 6517 camera trap nights. All species were found to be nocturnal; however, a notable number of daytime observations were made for several species (i.e. brown antechinus,Antechinus stuartii; sugar glider,Petaurus breviceps; bush rat,Rattus fuscipes; brown rat,Rattus norvegicus). Seasonal variations in diel activity were observed through an increase in crepuscular activity in spring and summer for antechinus, sugar gliders, brown rats,brushtail possums,Trichosurus vulpeculaand ringtail possums,Pseudocheirus peregrinus.Diel activity overlap between species was high, that is 26/28 species comparisons had overlap coefficients (Δ) > 0.75. The species pair with the least amount of overlap was between southern bobucks,Trichosurus cunninghamiand brown antechinus (Δ4 = 0.66). The species pair with the most overlap was between the native sugar glider and introduced brown rat (Δ4 = 0.93). When comparing the activity of sugar gliders in sites with low and high abundance of brown rats, sugar gliders appear to shift their activity relative to the brown rats. Similarly, behavioural interference was also observed between antechinus and sugar gliders, and when comparing sites of low and high abundance of sugar glider, antechinus had a shift in activity. Our work provides some of the first quantification of temporal patterns for several of the species in this study, and the first for a community of arboreal and semi-arboreal mammals. Our results indicate that some shifts in behaviour are potentially occurring in response to behavioural interference, allowing for coexistence by means of temporal partitioning.
Defining organizational AI governance
Authors: Mäntymäki Matti , Minkkinen Matti , Birkstedt Teemu , Viljanen Mika 
Published: February 2022

AbstractArtificial intelligence (AI) governance is required to reap the benefits and manage the risks brought by AI systems. This means that ethical principles, such as fairness, need to be translated into practicable AI governance processes. A concise AI governance definition would allow researchers and practitioners to identify the constituent parts of the complex problem of translating AI ethics into practice. However, there have been few efforts to define AI governance thus far. To bridge this gap, this paper defines AI governance at the organizational level. Moreover, we delineate how AI governance enters into a governance landscape with numerous governance areas, such as corporate governance, information technology (IT) governance, and data governance. Therefore, we position AI governance as part of an organization’s governance structure in relation to these existing governance areas. Our definition and positioning of organizational AI governance paves the way for crafting AI governance frameworks and offers a stepping stone on the pathway toward governed AI.
Some Indigenous Perspectives on Artifact Collecting and Archaeologist–Collector Collaboration
Authors: Kelley Alan D. , Neller Angela J. , Gover Carlton Shield Chief ,   AAP Thematic-Issue Editors
Published: February 2022

AbstractThis article attempts to bring Indigenous voices into the ongoing conversation about collecting practices and the archaeological record. The issue editors solicited responses to open-ended questions about those subjects from members of their own and issue contributors' networks of Indigenous collaborators and contacts. Alan D. Kelley (Deputy Tribal Historic Preservation Officer, Iowa Tribe of Kansas and Nebraska), Angela J. Neller (Curator, Wanapum Heritage Center, Washington), and Carlton Shield Chief Gover (PhD student in archaeology at the University of Colorado and member of the Skiri Band of the Pawnee Nation of Oklahoma) offered the answers reported here. We do not pretend to reflect the innumerable and highly varied Indigenous perspectives on the collection of their ancestors' material culture, but we do hope to plant the seeds of a more inclusive conversation than has been the norm in archaeology.
Research on lateral dynamics safety margins of carrier-based aircraft arresting
Authors: Zhang Z. , Peng Y. , Liang T. , Wei X. , Wang Y. 
Published: February 2022

AbstractFor the safety problems caused by the limited landing space of the deck during the arresting process of the carrier-based aircraft, a dynamic model of the carrier-based aircraft’s landing and arresting is built. Based on the batch simulation method, the lateral dynamics safety envelope of the aircraft during the arresting was defined, and the dynamic response of the key points in the envelope during the arresting process was investigated. Subsequently, the influence of engine thrust and aircraft quality on the arresting safety envelope was studied based on reasonable safety evaluation indicators, and the safety status envelope of the deck arresting was given. Then, the particular Hamilton-Jacobi partial differential equation is used to obtain the lateral dynamics safety envelope of the carrier-based aircraft in the process of landing and arresting by backward inversion. Results indicate that engine thrust and landing quality have little effect on the yaw angle in the arresting safety boundary during the arresting. Additionally, with the engine thrust and landing quality increase, the maximum safe off-centre distance gradually decreases, and the safety boundary decreases accordingly. During the phase of landing glide, the engine thrust and quality have little effect on the maximum safe eccentric distance. When the engine thrust is increased by 40%, the maximum safe yaw angle is reduced from 0.3°, and the safety boundary is reduced by 4.2%. When the aircraftquality increases by 40%, the maximum safe yaw angle is reduced by 0.4°, and the safety boundary is reduced by 2.8%. The findings of this paper can provide framework for the research on theaircraft-to-carrier dynamic matching characteristics of the carrier-based system, and is of great significance to the research on improving the safety of the carrier-based aircraft landing arresting.
Can machine learning models trained using atmospheric simulation data be applied to observation data?
Authors: Matsuoka Daisuke 
Published: February 2022

Abstract
Atmospheric simulation data present richer information in terms of spatiotemporal resolution, spatial dimension, and the number of physical quantities compared to observational data; however, such simulations do not perfectly correspond to the real atmospheric conditions. Additionally, extensive simulation data aids machine learning-based image classification in atmospheric science. In this study, we applied a machine learning model for tropical cyclone detection, which was trained using both simulation and satellite observation data. Consequently, the classification performance was significantly lower than that obtained with the application of simulation data. Owing to the large gap between the simulation and observation data, the classification model could not be practically trained only on the simulation data. Thus, the representation capability of the simulation data must be analyzed and integrated into the observation data for application in real problems.
Structures of adnominal possession in Austria’s traditional dialects: Variation and change
Authors: Bülow Lars , Vergeiner Philip C. , Elspaß Stephan 
Published: February 2022

AbstractBy means of the first comprehensive apparent-time study of Austria’s traditional dialects, this paper explores the use of adnominal syntactic constructions of expressing the semantic relation of possession. The article focuses on both the geographical variation and the interplay of syntax, semantics, and pragmatics. The analyses are based on data from direct recordings of 162 speakers from forty villages and on written questionnaire data from 103 of these speakers from thirty-seven villages. The analyses reveal clear geographical patterns for those constructions in which the possessor phrase precedes the possessum phrase within the entire construction. We propose to focus on the discursive-pragmatic properties of the possessor phrase to explain the fact that each of the observed dialects allows the possessor to precede the possessum. We provide evidence that referential anchoring, combined with the concept of accessibility, is the key to explaining the syntactic order within the used constructions.
How the “Jerusalem Scrolls” Became the Dead Sea Scrolls from Qumran Cave 1: Archaeology, the Antiquities Market, and the Spaces In Between
Authors: Nongbri Brent 
Published: February 2022

AbstractSeven animal hide scrolls with Hebrew and Aramaic writing were sold in Jerusalem in 1947. Additional smaller fragments of similar scrolls were sold from 1948 to 1950. Within a few years of their appearance, these “Jerusalem Scrolls” as they were then known, became “the Dead Sea Scrolls from Qumran Cave 1.” While this change of names may seem trivial, it glosses over some difficult questions about the provenance of these materials. What we now call “Cave 1Q” or “Qumran Cave 1” was excavated in 1949, but scholarship reveals considerable confusion concerning which purchased scrolls can be materially connected to fragments that were excavated by archaeologists under controlled conditions in Cave 1. Furthermore, Cave 1 is often treated as if it was a sealed context rather than the highly contaminated site that it actually was at the time of its excavation by archaeologists. For these reasons, it is not completely clear whether all the scrolls usually assigned to Cave 1 actually originated at this site. This article is an attempt to sort through the evidence to determine exactly which scrolls and fragments attributed to Cave 1 were purchased, when and from whom such pieces were purchased, and what can actually be known with confidence about the connection of these “Jerusalem Scrolls” with the site we now call Qumran Cave 1.