bluuebunny/crossref_metadata_2025_split huggingface dataset:
Improving information retrieval through correspondence analysis instead of latent semantic analysis
Authors: Qi Qianqian , Hessen David J. , van der Heijden Peter G. M. 
Published: September 2023

AbstractThe initial dimensions extracted by latent semantic analysis (LSA) of a document-term matrix have been shown to mainly display marginal effects, which are irrelevant for information retrieval. To improve the performance of LSA, usually the elements of the raw document-term matrix are weighted and the weighting exponent of singular values can be adjusted. An alternative information retrieval technique that ignores the marginal effects is correspondence analysis (CA). In this paper, the information retrieval performance of LSA and CA is empirically compared. Moreover, it is explored whether the two weightings also improve the performance of CA. The results for four empirical datasets show that CA always performs better than LSA. Weighting the elements of the raw data matrix can improve CA; however, it is data dependent and the improvement is small. Adjusting the singular value weighting exponent often improves the performance of CA; however, the extent of the improvement depends on the dataset and the number of dimensions.
Evolutionary algorithms for a simheuristic optimization of the product-service system design
Authors: Meeß Henri , Herzog Michael , Alp Enes , Kuhlenkötter Bernd 
Published: September 2023

AbstractOffering Product-Service Systems (PSS) becomes an established strategy for companies to increase the provided customer value and ensure their competitiveness. Designing PSS business models, however, remains a major challenge. One reason for this is the fact that PSS business models are characterized by a long-term nature. Decisions made in the development phase must take into account possible scenarios in the operational phase. Risks must already be anticipated in this phase and mitigated with appropriate measures. Another reason for the design phase being a major challenge is the size of the solution space for a possible business model. Developers are faced with a multitude of possible business models and have the challenge of selecting the best one. In this article, a simheuristic optimization approach is developed to test and evaluate PSS business models in the design phase in order to select the best business model configuration beforehand. For optimization, a proprietary evolutionary algorithm is developed and tested. The results validate the suitability of the approach for the design phase and the quality of the algorithm for achieving good results. This could even be transferred to already established PSS.
Getting machines to do your dirty work
Authors: Francis Tomi , Karhu Todd 
Published: September 2023

Abstract
Autonomous systems are machines that can alter their behavior without direct human oversight or control. How ought we to program them to behave? A plausible starting point is given by the Reduction to Acts Thesis, according to which we ought to program autonomous systems to do whatever a human agent ought to do in the same circumstances. Although the Reduction to Acts Thesis is initially appealing, we argue that it is false: it is sometimes permissible to program a machine to do something that it would be wrong for a human to do. We advance two main arguments for this claim. First, the way an autonomous system will behave can be known in advance. This knowledge can indirectly affect the behavior of other agents, while the same may not be true at the time the system actually executes its programming. Second, a lack of knowledge of the identities of the victims and beneficiaries can provide a justification during the programming phase that would be unavailable to an agent at the time the autonomous system executes its programming.
Towards a better understanding of soil nutrient dynamics and P and K uptake
Authors: Schut Antonius G. T. , Reymann W. 
Published: September 2023

Abstract
Aim
Balanced crop nutrition is key to improve nutrient use efficiency and reduce environmental impact of farming systems. We developed and tested a dynamic model to predict the uptake of P and K in long-term experiments to better understand how changes in soil nutrient pools affect nutrient availability in crop rotations.

Methods
Our RC-KP model includes labile and stable pools for P and K, with separate labile pools for placed P and organic fertilizers including farm yard manure (FYM). Pool sizes and crop-specific relative uptake rates determined potential uptake. Actual crop uptake from labile pools was based on concepts developed by Janssen et al. (Geoderma 46:299-318, 1990). The model was calibrated on three long-term experiments from Kenia (Siaya), Germany (Hanninghof) and the United Kingdom (Broadbalk) to estimate parameter values for crop-specific relative uptake rates and site-specific relative transfer rates.

Results
The model described N, P and K uptake accurately with a Nash-Sutcliff modelling efficiency of 0.6–0.9 and root mean squared errors of 2.6–3.4 kg P ha−1 and 14–20 kg K ha−1. Excluding organic labile pools did not affect model accuracy in Broadbalk in contrast to Hanninghof where Mg deficiencies affected crop uptakes in treatments without Mg or FYM.

Conclusions
This relatively simple model provides a novel approach to accurately estimate N, P and K uptake and explore short- and long-term effects of fertilizers in crop rotations. Interactions between limiting nutrients affecting actual nutrient uptake were captured well, providing new options to include N, P and K limitations in crop growth models.
Where Merleau-Ponty Meets Dewey: Habit, Embodiment, and Education
Authors: Thorburn Malcolm , Stolz Steven A. 
Published: September 2023

AbstractThis paper utilises selective writings by John Dewey and Maurice Merleau-Ponty as the conceptual basis for considering how an enhanced synergistic focus on habit and embodiment could support practice gains in schools. The paper focuses on Dewey’s belief that established habits can help students to incorporate experiences into evaluations of educational progress and Merleau-Ponty’s spotlight on the body-subject, and how it provides a holistic way of conceiving relations that avoid over privileging abstraction and cognition and under-representing the centrality of the body in human experience. We then evaluate the role of language and reflection in relation to habit, embodiment, and education before discussing some of the general educational practice considerations which might improve the quality of students learning experiences. In conclusion, we consider the possibilities for Dewey’s pragmatism to function as a theoretical bridge to Merleau-Ponty’s phenomenology of perception and the nature of experience. We argue that while it is important to recognise points of difference, in relation to philosophical treatments of habit and embodiment, it is also important to consider the overlap and new connections between Merleau-Ponty and Dewey which are valuable to take forward in contemporary education.
Perspectives on prostate cancer: advances and pending challenges for a multidisciplinary oncological approach in South America
Authors: Diaz Kevin A. , Amaya Sandra Liliana , García-Perdomo Herney Andrés 
Published: September 2023

AbstractProstate cancer is one of the tumors with the highest incidence and mortality among men worldwide, and this situation is no different in South America. However, epidemiological data are highly variable for each country and even more so than in North America. These data may be influenced by the very low rate of early detection of disease, availability of diagnostic methods, proper data collection, and limited access to specialized multidisciplinary treatment. For many South American countries, academic referral centers can only offer state-of-the-art diagnostics and multidisciplinary cancer treatment for patients who live in or can travel to large cities, so most patients are cared for by non-expert urologists with limited resources, which can have a negative impact on their prognosis and worsen oncologic outcomes. We aimed to show the clinical management of prostate cancer patients, the current advances in management, limitations present in South America, and how a multidisciplinary approach in referral cancer centers conformed of specialized urologists, medical oncologists, and mental health professionals can maximize patient outcomes.
Structural similarity of human papillomavirus E4 and polyomaviral VP4 exhibited by genomic analysis of the common kestrel (Falco tinnunculus) polyomavirus
Authors: Fehér Enikő , Kaszab Eszter , Mótyán János András , Máté Dóra , Bali Krisztina , Hoitsy Márton , Sós Endre , Jakab Ferenc , Bányai Krisztián 
Published: September 2023

AbstractPolyomaviruses are widely distributed viruses of birds that may induce developmental deformities and internal organ disorders primarily in nestlings. In this study, polyomavirus sequence was detected in kidney and liver samples of a common kestrel (Falco tinnunculus) that succumbed at a rescue station in Hungary. The amplified 5025 nucleotide (nt) long genome contained the early (large and small T antigen, LTA and STA) and late (viral proteins, VP1, VP2, VP3) open reading frames (ORFs) typical for polyomaviruses. One of the additional putative ORFs (named VP4) showed identical localization with the VP4 and ORF-X of gammapolyomaviruses, but putative splicing sites could not be found in its sequence. Interestingly, the predicted 123 amino acid (aa) long protein sequence showed the highest similarity with human papillomavirus E4 early proteins in respect of the aa distribution and motif arrangement implying similar functions. The LTA of the kestrel polyomavirus shared <59.2% nt and aa pairwise identity with the LTA sequence of other polyomaviruses and formed a separated branch in the phylogenetic tree among gammapolyomaviruses. Accordingly, the kestrel polyomavirus may be the first member of a novel species within the Gammapolyomavirus genus, tentatively named Gammapolyomavirus faltin.
Would you let this guy into a bar? Identifying cues that signal a perceived increase in the propensity for violence of potential bar patrons
Authors: Summerell Elizabeth , Fanous Geneviv , Denson Thomas F. 
Published: September 2023

Abstract
Objectives
Bars, pubs, and clubs are hotspots for alcohol-related aggression. Consequently, admittance decisions made by security personnel have important implications for the safety inside these venues. However, the cues used by security personnel to determine the potential for intoxicated violence and inform admittance decisions vary substantially.

Methods
Here, we manipulate theoretically and practically relevant cues to determine the effects of their utilization on perceptions of violence and admittance decisions. Participants viewed images of real inmates convicted of violent or non-violent crimes, accompanied by cues derived from interviews with security staff.

Results
We found that body tenseness, drug and alcohol intoxication, searching behavior, avoidant behavior, and neck and face tattoos were positively associated with a greater perceived likelihood of violence. Admittance decisions mirrored these findings. Students and security personnel differed in their utilization of some of the cues.

Conclusions
To our knowledge, the current research was the first to take a quantitative approach to understanding the cues that security personnel and young adults might use to identify potentially violent patrons. These finding may help inform training for security personnel.
Range shift and introgression of three Japanese Abies species: insights from population genetic data and species distribution modeling
Authors: Uchiyama Kentaro , Fujii Sayaka , Tsuyama Ikutaro , Tanaka Nobuyuki , Setsuko Suzuki , Kimura Megumi K. , Suyama Yoshihisa , Tsumura Yoshihiko 
Published: September 2023

AbstractRange shifts during the Pleistocene shaped the unique phylogeographical structures of many species. Pleistocene range shifts gave currently allopatric species opportunities to occur in sympatry, likely resulting in ancient introgressions between related taxa. In our study, we investigate the range shifts and introgression patterns of three Japanese Abies species (A. firma, A. homolepis, and A. veitchii) by employing an extensive survey of 43 populations. This survey includes comprehensive analysis of both mitochondrial (mtDNA) and nuclear (18 microsatellites) genomes, in combination with species distribution modeling (SDM). It is important to note that these two types of markers provide distinct and complementary information, as they have different modes of inheritance and mutation rates. Bayesian clustering analysis indicates that the three species were clearly separated, with the exception of the A. homolepis var. umbellata population, which is considered a natural hybrid between A. homolepis and A. firma. However, mtDNA haplotypes of the four northern populations of A. firma were entirely replaced by two major haplotypes of A. homolepis and A. veitchii. The results of neighbor-net, NewHybrids, STRUCTURE analyses, and SDM suggest that historical introgression between species occurred in each geographic region, with mtDNA capture being the likely mechanism. However, contrary to these findings, the ABC coalescent analysis did not support an ancient introgression. Therefore, further validation with genome-wide level data is needed to clarify this issue. Our conclusion is that climate-induced range shifts during the Pleistocene/Holocene likely played a crucial role in the observed patterns of introgression in these species.
Evaluating false positive rates of standard and hierarchical measures of metacognitive accuracy
Authors: Rausch Manuel , Zehetleitner Michael 
Published: September 2023

AbstractA key aspect of metacognition is metacognitive accuracy, i.e., the degree to which confidence judgments differentiate between correct and incorrect trials. To quantify metacognitive accuracy, researchers are faced with an increasing number of different methods. The present study investigated false positive rates associated with various measures of metacognitive accuracy by hierarchical resampling from the confidence database to accurately represent the statistical properties of confidence judgements. We found that most measures based on the computation of summary-statistics separately for each participant and subsequent group-level analysis performed adequately in terms of false positive rate, including gamma correlations, meta-d′, and the area under type 2 ROC curves. Meta-d′/d′ is associated with a false positive rate even below 5%, but log-transformed meta-d′/d′ performs adequately. The false positive rate of HMeta-d depends on the study design and on prior specification: For group designs, the false positive rate is above 5% when independent priors are placed on both groups, but the false positive rate is adequate when a prior was placed on the difference between groups. For continuous predictor variables, default priors resulted in a false positive rate below 5%, but the false positive rate was not distinguishable from 5% when close-to-flat priors were used. Logistic mixed model regression analysis is associated with dramatically inflated false positive rates when random slopes are omitted from model specification. In general, we argue that no measure of metacognitive accuracy should be used unless the false positive rate has been demonstrated to be adequate.
Self-supervised anomaly detection based on foreground enhancement and autoencoder reconstruction
Authors: Zhao Lijie , Chai Yuan , Zhang Qichun , Karimi Hamid Reza 
Published: September 2023

AbstractAnomaly detection algorithms typically utilize generative models to reconstruct anomaly regions. Post-processing is used to pinpoint the anomalies. However, the paucity of real-world anomaly samples and the complex image backgrounds pose significant challenges for anomaly detection. The work innovatively proposed a self-supervised anomaly detection method. An efficient channel attention mechanism in the autoencoder was introduced to improve the reconstruction performance. Besides, a foreground enhancement strategy was designed to distinguish the foreground from the background by maximizing the inter-class variance. The strategy reduced the effect of background noises and simulated various anomalies that were rare in real samples. The MVTecAD and BTAD datasets were used to experiment with anomaly detection and location. Experimental results demonstrated that our method achieved higher AUC and AP scores at both the image level and pixel level compared to other advanced methods. In particular, the average AP score increased by 12.5% at the pixel level.
Indoor air quality for heritage objects and human health: just a different interpretation of the same measurements?
Authors: Carro Gustavo , Schalm Olivier , Storme Patrick , Blanckaert Griet , Demeyer Serge 
Published: September 2023

AbstractThe environmental conditions in a conservation-restoration studio for paintings induce an inherent risk to objects of art and to humans working on those objects. They are both subject to (sometimes dangerous) chemical substances and fluctuations in environmental conditions (e.g., temperature, relative humidity). In this paper, we report on a measuring campaign which lasted more than a year collecting data about the air quality within a painting studio of a higher education institute. An existing algorithm assessed the indoor air quality for heritage objects using international air quality standards. This contribution presents a new algorithm to assess indoor air quality for human health relying on thresholds imposed by legislation and recommended by reference institutes. This algorithm has been applied to the same measuring campaign. The assessments illustrate that the same environmental conditions have a different impact on canvas paintings, panel paintings, students, and staff. Air quality is thus a relative concept that depends on the object/subject that is considered in the analysis.
Graphical abstract
A systematic review and meta-analysis investigating the relationship between metabolic syndrome and the incidence of thyroid diseases
Authors: Alwan Heba , Ribero Valerie Aponte , Efthimiou Orestis , Del Giovane Cinzia , Rodondi Nicolas , Duntas Leonidas 
Published: September 2023

Abstract
Purpose
To assess the prospective association between metabolic syndrome (MetS), its components, and incidence of thyroid disorders by conducting a systematic review and meta-analysis.

Methods
A systematic search was performed in Ovid Medline, Embase.com, and Cochrane CENTRAL from inception to February 22, 2023. Publications from prospective studies were included if they provided data on baseline MetS status or one of its components and assessed the incidence of thyroid disorders over time. A random effects meta-analysis was conducted to calculate the odds ratio (OR) for developing thyroid disorders.

Results
After full-text screening of 2927 articles, seven studies met our inclusion criteria. Two of these studies assessed MetS as an exposure (N = 71,727) and were included in our meta-analysis. The association between MetS at baseline and incidence of overt hypothyroidism at follow-up yielded an OR of 0.78 (95% confidence interval [CI]: 0.52–1.16 for two studies, I2 = 0%). Pooled analysis was not possible for subclinical hypothyroidism, due to large heterogeneity (I2 = 92.3%), nor for hyperthyroidism, as only one study assessed this association. We found evidence of an increased risk of overt (RR: 3.10 (1.56–4.64, I2 = 0%) and subclinical hypothyroidism (RR 1.50 (1.05–1.94), I2 = 0%) in individuals with obesity at baseline. There was a lower odds of developing overt hyperthyroidism in individuals with prediabetes at baseline (OR: 0.68 (0.47–0.98), I2 = 0%).

Conclusions
We were unable to draw firm conclusions regarding the association between MetS and the incidence of thyroid disorders due to the limited number of available studies and the presence of important heterogeneity in reporting results. However, we did find an association between obesity at baseline and incidence of overt and subclinical hypothyroidism.
Development of a transformer model for predicting the prognosis of patients with hepatocellular carcinoma after radiofrequency ablation
Authors: Sato Masaya , Moriyama Makoto , Fukumoto Tsuyoshi , Yamada Tomoharu , Wake Taijiro , Nakagomi Ryo , Nakatsuka Takuma , Minami Tatsuya , Uchino Koji , Enooku Kenichiro , Nakagawa Hayato , Shiina Shuichiro , Koike Kazuhiko , Fujishiro Mitsuhiro , Tateishi Ryosuke 
Published: September 2023

Abstract
Introduction
Radiofrequency ablation (RFA) is a widely accepted, minimally invasive treatment modality for patients with hepatocellular carcinoma (HCC). Accurate prognosis prediction is important to identify patients at high risk for cancer progression/recurrence after RFA. Recently, state-of-the-art transformer models showing improved performance over existing deep learning-based models have been developed in several fields. This study was aimed at developing and validating a transformer model to predict the overall survival in HCC patients with treated by RFA.

Methods
We enrolled a total of 1778 treatment-naïve HCC patients treated by RFA as the first-line treatment. We developed a transformer-based machine learning model to predict the overall survival in the HCC patients treated by RFA and compared its predictive performance with that of a deep learning-based model. Model performance was evaluated by determining the Harrel’s c-index and validated externally by the split-sample method.

Results
The Harrel’s c-index of the transformer-based model was 0.69, indicating its better discrimination performance than that of the deep learning model (Harrel’s c-index, 0.60) in the external validation cohort. The transformer model showed a high discriminative ability for stratifying the external validation cohort into two or three different risk groups (p < 0.001 for both risk groupings). The model also enabled output of a personalized cumulative recurrence prediction curve for each patient.

Conclusions
We developed a novel transformer model for personalized prediction of the overall survival in HCC patients after RFA treatment. The current model may offer a personalized survival prediction schema for patients with HCC undergoing RFA treatment.
Horizontally Affine Functions on Step-2 Carnot Algebras
Authors: Le Donne Enrico , Morbidelli Daniele , Rigot Séverine 
Published: September 2023

AbstractIn this paper, we introduce the notion of horizontally affine, h-affine in short, function and give a complete description of such functions on step-2 Carnot algebras. We show that the vector space of h-affine functions on the free step-2 rank-n Carnot algebra is isomorphic to the exterior algebra of $${\mathbb {R}}^n$$

R

n

. Using that every Carnot algebra can be written as a quotient of a free Carnot algebra, we shall deduce from the free case a description of h-affine functions on arbitrary step-2 Carnot algebras, together with several characterizations of those step-2 Carnot algebras where h-affine functions are affine in the usual sense of vector spaces. Our interest for h-affine functions stems from their relationship with a class of sets called precisely monotone, recently introduced in the literature, as well as from their relationship with minimal hypersurfaces.