bluuebunny/crossref_metadata_2025_split huggingface dataset:
One Never Knows
Authors: Nadin Mihai 
Published: September 2023

Abstract
Understanding anticipatory action as undergirding the dynamics of life is the prerequisite for defining what art is. Its change over time reflects the fact that life is purposeful and escapes prediction. Explaining art from the perspective of means and methods involved in producing it, from a deterministic view, leads to circular reasoning: the conclusion (machine art is the future) is in the premise (machines can make art). This fallacy becomes evident in the context of the current infatuation with automation of artmaking (especially through AI), and even art evaluation. The role art plays in defining the human condition is no less significant than that of science, itself indebted to aesthetics in its expression.
Coin Assemblages in Ancient Burials: Statement of the Problem
Authors: Tereshchenko Andrey E. 
Published: September 2023

Abstract
The present work is dedicated to the analysis of possible meanings of monetary offerings in ancient burial practice. It is clear from archaeological data that the placement of money in a grave was not an essential component of the funeral ceremony; therefore, the comparative variety of versions of this ritual is not surprising: the number and value of coins in burials varies rather widely. The author examines several possible situations of monetary offering (one, two, three, or four and more coins) and suggests, with the support of both literary and archaeological data, various interpretations (“Charon’s obol,” “return ticket,” unfixed transportation fee, gifts “just in case,” and an indicator of social status, respectively). The article focuses attention on the most recent find from the Taman Peninsula – a small deposit from the necropolis of Volna I settlement.
First Millennium Urbanism in Central Asia: Typology and Evolution of Dzhety-asar Settlements
Authors: Goffriller Martin , Arzhantseva Irina , Härke Heinrich 
Published: September 2023

Abstract
Despite its apparent size and length of its existence, the Dzhety-asar culture of Kazakhstan remains one of the great unknowns of Central Asian archaeology, comprising, as it did, several dozen now-ruined settlements with an almost thousand-year long occupational history. First settled around the 1st century BC and gradually abandoned in the second half of the 1st millennium AD, the Dzhety-asar towns and manors were located to the east of the Aral Sea within the Syr Darya delta, and may have functioned as a core element in Central Asia’s medieval trade networks. Despite past research efforts by the Khorezmian Archaeological Ethnographic Expedition (KhAEE), the cultural and political history of the Dzhety-asar people remains largely unclear, with as yet no consensus on the political structure or their ethnic, linguistic and religious make-up. The present paper does not presume to answer these questions at this stage, as it is the result of two fieldwork seasons documenting and surveying Dzhety-asar settlements. It is, instead, intended to lay out the preliminary findings, presenting a revised typology of sites, and suggest initial hypotheses regarding the structure and possible evolution of the culture.
“It Is Only Bad Priests and Outlaws Who Thrive NowAdays”
Authors: Fricke Felicia 
Published: September 2023

Abstract
In Caribbean historiography, rumors are often associated with enslaved people and sailors; less often are they associated with elite men. This article addresses the use of rumor by elite men in the Lesser Antilles during the late 1820s, following the story of Antony O’Hannan, Roman Catholic rector of Grenada, whose relationship with his enslaved and free congregation made him dangerous to both Catholic and colonial authorities. Although the White Catholics of Grenada were often discriminated against, here they aligned with the wider Church in supporting the colonial power. Similarly, the colonial administration was willing to collaborate with Catholics, to activate an interisland rumor network that mobilized anxieties about O’Hannan’s perceived threat to White women. Using Colonial Office documents and Caribbean newspapers, this article explores microregional rumor as part of the arsenal used to maintain colonial order, and complicates the internal workings of the Catholic Church in the Caribbean.
Exploring Crossmodal Associations Between Sound and the Chemical Senses: A Systematic Review Including Interactive Visualizations
Authors: Rodríguez Brayan , Reyes Luis H. , Reinoso-Carvalho Felipe 
Published: September 2023

Abstract
This is the first systematic review that focuses on the influence of product-intrinsic and extrinsic sounds on the chemical senses involving both food and aroma stimuli. This review has a particular focus on all methodological details (stimuli, experimental design, dependent variables, and data analysis techniques) of 95 experiments, published in 83 publications from 2012 to 2023. 329 distinct crossmodal auditory–chemosensory associations were uncovered across this analysis. What is more, instead of relying solely on static figures and tables, we created a first-of-its-kind comprehensive Power BI dashboard (interactive data visualization tool by Microsoft) on methodologies and significant findings, incorporating various filters and visualizations allowing readers to explore statistics for specific subsets of experiments. We believe that this review can be helpful for researchers and practitioners working in the food and beverage industry and beyond these scopes (e.g., cosmetics). Theoretical and practical implications discussed in this article point to computational approaches that facilitate decision-making regarding multisensory experimental methodology design.
Asymmetric Arctic and Antarctic Warming and Its Intermodel Spread in CMIP6
Authors: Zhang Yihan , Kong Yunqi , Yang Song , Hu Xiaoming 
Published: September 2023

Abstract
Under the background of global warming, the Arctic region has warmed faster than the Antarctic, which is referred to as asymmetric Arctic and Antarctic warming. The new generation of model simulations from the CMIP6 offers an opportunity to identify the major factors contributing to the asymmetric warming and its intermodel spread. In this study, the preindustrial and abrupt-4 × CO2 experiments from 18 CMIP6 models are examined to extract the asymmetric warming and its intermodel spread. A climate feedback-response analysis method is applied to reveal the contributions of external and internal feedback processes to the asymmetric warming and its intermodel spread, by decomposing total warming into the partial temperature changes caused by individual factors. It is found that a seasonal energy transfer mechanism (SETM) dominates in both polar warmings. The direct consequence of the sea ice declining in response to the anthropogenic forcing is an increase in the effective heat capacity of the ocean surface layer. Such an increase in the effective heat capacity temporally withholds most of the extra solar energy absorbed during summer and then releases it during winter, contributing to stronger warming in winter. However, the background oceanic circulation in the Southern Ocean, namely, the Antarctic Circumpolar Current, continually transports energy equatorward, resulting in a suppressed SETM and surface warming in the Antarctic. The key factor that accounts for intermodel spread in the asymmetric warming is the difference in their strengths of SETM. The poleward atmospheric transport and water vapor feedback also contribute to the intermodel spread.

Significance Statement
The asymmetric Arctic and Antarctic warming, as a response to the increase in CO2, can regulate global atmospheric and oceanic circulations via meridional temperature gradient. Previous studies have all ascribed the key role of the ocean in the asymmetric warming over the two poles with a lack of comprehensive understanding of the roles of other feedback processes. This study emphasizes that oceanic circulation is the root of the asymmetric warming via suppressing sea ice retreat and the associated SETM in the Antarctic, instead of increasing ocean heat uptake and equatorward transport only. For the intermodel spread in the asymmetric warming over two poles, the differences in the strength of all processes involving the SETM among models are the prominent issue.
Evaluating the Multiscale Implementation of Valid Time Shifting within a Real-Time EnVar Data Assimilation and Forecast System for the 2022 HWT Spring Forecasting Experiment
Authors: Gasperoni Nicholas A. , Wang Xuguang , Wang Yongming , Li Tsung-Han 
Published: September 2023

Abstract
Multiscale valid time shifting (VTS) was explored for a real-time convection-allowing ensemble (CAE) data assimilation (DA) system featuring hourly assimilation of conventional in situ and radar reflectivity observations, developed by the Multiscale Data Assimilation and Predictability Laboratory. VTS triples the base ensemble size using two subensembles containing member forecast output before and after the analysis time. Three configurations were tested with 108-member VTS-expanded ensembles: VTS for individual mesoscale conventional DA (ConVTS) or storm-scale radar DA (RadVTS) and VTS integrated to both DA components (BothVTS). Systematic verification demonstrated that BothVTS matched the DA spread and accuracy of the best-performing individual component VTS. The 10-member forecasts showed BothVTS performs similarly to ConVTS, with RadVTS having better skill in 1-h precipitation at forecast hours 1–6, while Both/ConVTS had better skill at later hours 7–15. An objective splitting of cases by 2-m temperature cold bias revealed RadVTS was more skillful than Both/ConVTS out to hour 10 for cold-biased cases, while BothVTS performed best at most hours for less-biased cases. A sensitivity experiment demonstrated improved performance of BothVTS when reducing the underlying model cold bias. Diagnostics revealed enhanced spurious convection of BothVTS for cold-biased cases was tied to larger analysis increments in temperature than moisture, resulting in erroneously high convective instability. This study is the first to examine the benefits of a multiscale VTS implementation, showing that BothVTS can be utilized to improve the overall performance of a multiscale CAE system. Further, these results underscore the need to limit biases within a DA and forecast system to best take advantage of VTS analysis benefits.
Machine Learning Algorithms Predict Long-Term Postoperative Opioid Misuse: A Systematic Review
Authors: Emam Omar S. , Eldaly Abdullah S. , Avila Francisco R. , Torres-Guzman Ricardo A. , Maita Karla C. , Garcia John P. , Anne Brown Sally , Haider Clifton R. , Forte Antonio J. 
Published: September 2023

Introduction A steadily rising opioid pandemic has left the US suffering significant social, economic, and health crises. Machine learning (ML) domains have been utilized to predict prolonged postoperative opioid (PPO) use. This systematic review aims to compile all up-to-date studies addressing such algorithms’ use in clinical practice. Methods We searched PubMed/MEDLINE, EMBASE, CINAHL, and Web of Science using the keywords “machine learning,” “opioid,” and “prediction.” The results were limited to human studies with full-text availability in English. We included all peer-reviewed journal articles that addressed an ML model to predict PPO use by adult patients. Results Fifteen studies were included with a sample size ranging from 381 to 112898, primarily orthopedic-surgery-related. Most authors define a prolonged misuse of opioids if it extends beyond 90 days postoperatively. Input variables ranged from 9 to 23 and were primarily preoperative. Most studies developed and tested at least two algorithms and then enhanced the best-performing model for use retrospectively on electronic medical records. The best-performing models were decision-tree-based boosting algorithms in 5 studies with AUC ranging from .81 to .66 and Brier scores ranging from .073 to .13, followed second by logistic regression classifiers in 5 studies. The topmost contributing variable was preoperative opioid use, followed by depression and antidepressant use, age, and use of instrumentation. Conclusions ML algorithms have demonstrated promising potential as a decision-supportive tool in predicting prolonged opioid use in post-surgical patients. Further validation studies would allow for their confident incorporation into daily clinical practice.
Predicting the Finite Population Distribution Function under a Multilevel Model
Authors: Das Sumonkanti , Salvati Nicola , Chambers Ray 
Published: September 2023

Chambers and Dunstan proposed a model-based predictor of the population distribution function that makes use of auxiliary population information under a general sampling design. Subsequently, Rao, Kovar, and Mantel proposed design-based ratio and difference predictors of the population distribution function that also use this auxiliary information. Both predictors (CD and RKM) assume a single level model for the target population. In this article we develop predictors of the finite population distribution function for a population that follows a multilevel model. These new predictors use the same smearing approach underpinning the CD predictor. We compare our new predictors with the CD and RKM predictors via design-based simulation, and show that they perform better than these single level predictors when there is significant intra-cluster correlation. The performances of these new two level predictors are also examined via an empirical study based on data from a large-scale UK business survey aimed at estimating the distribution of hourly pay rates. AMS Subject Classification: Primary 62G30, Secondary 62G32
Determinants of Foreign Direct Investment: A Systematic Review of the Empirical Studies
Authors: Islam Mohammad Shaiful , Beloucif Ahmed 
Published: September 2023

A growing body of literature is concerned with the factors that determine the inflows of foreign direct investment (FDI) into a host country. However, hardly any literature has been carried out to provide a systematic literature review (SLR) of the FDI determinants. An SLR methodology underlies this conceptual paper to evaluate and categorise a literature survey of 112 empirical studies published from 2000 to 2018. The result indicates that the size of the host market is the most robust determinant, followed by trade openness, infrastructure quality, labour cost, macroeconomic stability, human capital, and the growth prospect of the host country. Market size is highly significant in virtually all studies. This partly reflects the fact that most of the world’s FDI are market-seeking. This study provides a clear understanding of the scope of the research in the field of FDI determinants as the practical implication for future research. JEL Code: F14
Exploratory Development of Algorithms for Determining Driver Attention Status
Authors: Herbers Eileen , Miller Marty , Neurauter Luke , Walters Jacob , Glaser Daniel 
Published: September 2023

Objective Varying driver distraction algorithms were developed using vehicle kinematics and driver gaze data obtained from a camera-based driver monitoring system (DMS). Background Distracted driving characteristics can be difficult to accurately detect due to wide variation in driver behavior across driving environments. The growing availability of information about drivers and their involvement in the driving task increases the opportunity for accurately recognizing attention state. Method A baseline for driver distraction levels was developed using a video feed of 24 separate drivers in varying naturalistic driving conditions. This initial assessment was used to develop four buffer-based algorithms that aimed to determine a driver’s real-time attentiveness, via a variety of metrics and combinations thereof. Results Of those tested, the optimal algorithm included ungrouped glance locations and speed. Notably, as an algorithm’s performance of detecting very distracted drivers improved, its accuracy for correctly identifying attentive drivers decreased. Conclusion At a minimum, drivers’ gaze position and vehicle speed should be included when designing driver distraction algorithms to delineate between glance patterns observed at high and low speeds. Distraction algorithms should be designed with an understanding of their limitations, including instances in which they may fail to detect distracted drivers, or falsely notify attentive drivers. Application This research adds to the body of knowledge related to driver distraction and contributes to available methods to potentially address and reduce occurrences. Machine learning algorithms can build on the data elements discussed to increase distraction detection accuracy using robust artificial intelligence.
How Terminology Affects Users’ Responses to System Failures
Authors: Candrian Cindy , Scherer Anne 
Published: September 2023

Objective The objective of our research is to advance the understanding of behavioral responses to a system’s error. By examining trust as a dynamic variable and drawing from attribution theory, we explain the underlying mechanism and suggest how terminology can be used to mitigate the so-called algorithm aversion. In this way, we show that the use of different terms may shape consumers’ perceptions and provide guidance on how these differences can be mitigated. Background Previous research has interchangeably used various terms to refer to a system and results regarding trust in systems have been ambiguous. Methods Across three studies, we examine the effect of different system terminology on consumer behavior following a system failure. Results Our results show that terminology crucially affects user behavior. Describing a system as “AI” (i.e., self-learning and perceived as more complex) instead of as “algorithmic” (i.e., a less complex rule-based system) leads to more favorable behavioral responses by users when a system error occurs. Conclusion We suggest that in cases when a system’s characteristics do not allow for it to be called ”AI,” users should be provided with an explanation of why the system’s error occurred, and task complexity should be pointed out. We highlight the importance of terminology, as this can unintentionally impact the robustness and replicability of research findings. Application This research offers insights for industries utilizing AI and algorithmic systems, highlighting how strategic terminology use can shape user trust and response to errors, thereby enhancing system acceptance.
Clinical impact of turn-up anastomosis in the treatment of type A acute aortic dissection
Authors: Shimamoto Takeshi , Komiya Tatsuhiko , Matsuo Takehiko 
Published: September 2023

Background The management of anastomosis and hemostasis of the dissected aorta remains challenging. This study aims to establish an optimal surgical strategy for type A acute aortic dissection by reviewing single-center data using the turn-up anastomosis technique. Methods Between 2003 and 2015, 264 consecutive patients with type A acute aortic dissection who underwent emergency surgery within 14 days of symptom onset were enrolled. Results The mean age of the patients was 67.7 ± 13.4 years, and 129 were males. The operative time and surgical bleeding were 390.9 ± 144.5 min and 2983.8 ± 3026.5 mL, respectively. In-hospital mortality was observed in 25 patients (9.4%), and 3 (1.1%) experienced uncontrolled bleeding (from the aortic root in two patients and coagulopathy due to dabigatran in one patient). Immediate reopening for bleeding was performed in 20 patients, and bleeding from the aortic anastomosis was observed at three proximal and two distal sites. Proximal re-dissection was observed in 18 patients; in all of which, glue was used, although two re-ruptures of the aortic root were observed among those without glue use. The rates of freedom from all-cause death, aortic death, and aortic events at postoperative 5 years were 78.5 ± 2.7%, 86.8 ± 2.1%, and 74.4 ± 2.9%, respectively. When these values were stratified according to the operative extent, no significant differences were observed. Conclusions Turn-up anastomosis facilitates short circulatory arrest, short operative time, and stable hemostasis, with few anastomotic complications during surgery for type A acute aortic dissection.
Polyurethane Rigid Foam Systems for Metal-Faced Sandwich Panels for the 1990s
Authors: Jeffs G.M.F. , Rosbotham J.D. , Mathys B. , Frigo R. 
Published: September 2023

Sandwich panels with polyurethane rigid foam cores are important building elements for a wide variety of applications. They are used for the cost effective construction of industrial and commercial buildingsand in many stages of the food chain, including cold storage, cold rooms and refrigerated transport containers and trucks. The blowing agent used in the foam systems has traditionally been CFC-ll. This has contributed to the excellent thermal resistance of the panels but its use will be phased out by the year 2000. Foam systems have been developed based on a wide variety of alternatives. These are designed to suit various national and international CFC phase-out schedules. These include systems based on 100% CO2, HCFC-22, HCFC-123 and HCFC-141b. In all cases the formulations have been based around the particular blowingagent to obtain the best combination of processing, physical and thermal resistance properties. Because the HCFCs are now accepted to be transitional substances with a finite production lifetime, the foam systems based on HCFC-123 and -141b are designed to be “drop-In” replacements for those based on CFC-ll. This means that all changes are incorporated into the foam system rather than into the production process and that thermal resistance with those blowing agents equals that for systems based on CFC-11. These panels have an important structural role to play and, in addition to the retention of foam strength, the adhesion between the foam and facing plays an important role in the overall performance of the panel. The parameters affecting adhesion have been investigated with the alternative systems and optimised processing conditions determined. A family of foam systems has been developed to serve the metal-faced sandwich panel industry through the 1990s.
Amine-Free Catalyst Systems for Automotive Instrument Panels
Authors: Christfreund A. , Huygens E. , Eling B. 
Published: September 2023

The requirements, composition and performance of modern automotive instrument panels have been thoroughly examined. In particular the antagonistic behaviour of conventional semi-rigid PU foam with the decorative skin cover made from either an ABS/PVC vacuum formed sheet or slush moulded PVC powder was investigated. Extended exposure to high temperatures of such composites has been shown to result in staining and embrittlement of the skin material. ICI Polyurethanes, in conjunction with ICI EVC, has carried out an extensive programme of work to identify the mechanisms of discoloration and embrittlement. This paper summarises the results and shows the importance of PVC stabilizers, pigments and plasticizers and the use of amine catalysts in the polyurethane foam as the critical factors. Although amine-free catalysts were known the resulting polyurethane foams did not have the right balance of foam structure, physical properties and processing characteristics. Thus a novel amine-free catalyst system was developed which gave excellent staining resistance whilst maintaining the other foam properties and giving the required processing characteristics.