bluuebunny/crossref_metadata_2025_split huggingface dataset:
Using Clustering and Machine Learning Methods to Provide Intelligent Grocery Shopping Recommendations
Authors: Chabane Nail , Bouaoune Mohamed Achraf , Tighilt Reda Amir Sofiane , Mazoure Bogdan , Tahiri Nadia , Makarenkov Vladimir 
Published: December 2023

AbstractNowadays, grocery lists make part of shopping habits of many customers. With the popularity of e-commerce and plethora of products and promotions available on online stores, it can become increasingly difficult for customers to identify. products that both satisfy their needs and represent the best deals overall. In this paper, we present a grocery recommender system based on the use of traditional machine learning methods aiming at assisting customers with creation of their grocery lists on the MyGroceryTour platform which displays weekly grocery deals in Canada. Our recommender system relies on the individual user purchase histories, as well as the available products’ and stores’ features, to constitute intelligent weekly grocery lists. The use of clustering prior to supervised machine learning methods allowed us to identify customers profiles and reduce the choice of potential products of interest for each customer, thus improving the prediction results. The highest average F-score of 0.499 for the considered dataset of 826 Canadian customers was obtained using the Random Forest prediction model which was compared to the Decision Tree, Gradient Boosting Tree, XGBoost, Logistic Regression, Catboost, Support Vector Machine and Naive Bayes models in our study.
PcTVI: Parallel MDP Solver Using a Decomposition into Independent Chains
Authors: Gareau Jaël Champagne , Beaudry Éric , Makarenkov Vladimir 
Published: December 2023

AbstractMarkov Decision Processes (MDPs) are useful to solve real-world probabilistic planning problems. However, finding an optimal solution in an MDP can take an unreasonable amount of time when the number of states in the MDP is large. In this paper, we present a way to decompose an MDP into Strongly Connected Components (SCCs) and to find dependency chains for these SCCs. We then propose a variant of the Topological Value Iteration (TVI) algorithm, called parallel chained TVI (pcTVI), which is able to solve independent chains of SCCs in parallel leveraging modern multicore computer architectures. The performance of our algorithm was measured by comparing it to the baseline TVI algorithm on a new probabilistic planning domain introduced in this study. Our pcTVI algorithm led to a speedup factor of 20, compared to traditional TVI (on a computer having 32 cores).
Robustness Aspects of Optimized Centroids
Authors: Kalina Jan , Janáček Patrik 
Published: December 2023

AbstractCentroids are often used for object localization tasks, supervised segmentation in medical image analysis, or classification in other specific tasks. This paper starts by contributing to the theory of centroids by evaluating the effect of modified illumination on the weighted correlation coefficient. Further, robustness of various centroid-based tools is investigated in experiments related to mouth localization in non-standardized facial images or classification of high-dimensional data in a matched pairs design. The most robust results are obtained if the sparse centroid-based method for supervised learning is accompanied with an intrinsic variable selection. Robustness, sparsity, and energy-efficient computation turn out not to contradict the requirement on the optimal performance of the centroids.
A Trivariate Geometric Classification of Decision Boundaries for Mixtures of Regressions
Authors: Antonazzo Filippo , Ingrassia Salvatore 
Published: December 2023

AbstractMixtures of regressions play a prominent role in regression analysis when it is known the population of interest is divided into homogeneous and disjoint groups. This typically consists in partitioning the observational space into several regions through particular hypersurfaces called decision boundaries. A geometrical analysis of these surfaces allows to highlight properties of the used classifier. In particular, a geometrical classification of decision boundaries for the three most used mixtures of regressions (with fixed covariates, with concomitant variables and random covariates) was provided in case of one and two covariates, under Gaussian assumptions and in presence of only one real response variable. This work aims to extend these results to a more complex setting where three independent variables are considered.
Supervised Classification via Neural Networks for Replicated Point Patterns
Authors: Pawlasová Kateřina , Karafiátová Iva , Dvořák Jiří 
Published: December 2023

AbstractA spatial point pattern is a collection of points observed in a bounded region of $${\bf{\mathbb{R}}}^d$$, $$d \ge 2$$. Individual points represent, e.g., observed locations of cell nuclei in a tissue (d = 2) or centers of undesirable air bubbles in industrial materials (d = 3). The main goal of this paper is to show the possibility of solving the supervised classification task for point patterns via neural networks with general input space. To predict the class membership for a newly observed pattern, we compute an empirical estimate of a selected functional characteristic (e.g., the pair correlation function). Then, we consider this estimated function to be a functional variable that enters the input layer of the network. A short simulation example illustrates the performance of the proposed classifier in the situation where the observed patterns are generated from two models with different spatial interactions. In addition, the proposed classifier is compared with convolutional neural networks (with point patterns represented by binary images) and kernel regression. Kernel regression classifiers for point patterns have been studied in our previous work, and we consider them a benchmark in this setting.
Penalized Model-Based Functional Clustering: A Regularization Approach via Shrinkage Methods
Authors: Pronello Nicola , Ignaccolo Rosaria , Ippoliti Luigi , Fontanella Sara 
Published: December 2023

AbstractWith the advance of modern technology, and with data being recorded continuously, functional data analysis has gained a lot of popularity in recent years. Working in a mixture model-based framework, we develop a flexible functional clustering technique achieving dimensionality reduction schemes through aL1penalization. The proposed procedure results in an integrated modelling approach where shrinkage techniques are applied to enable sparse solutions in both the means and the covariance matrices of the mixture components, while preserving the underlying clustering structure. This leads to an entirely data-driven methodology suitable for simultaneous dimensionality reduction and clustering. Preliminary experimental results, both from simulation and real data, show that the proposed methodology is worth considering within the framework of functional clustering.
Clustering Validation in the Context of Hierarchical Cluster Analysis: An Empirical Study
Authors: Silva Osvaldo , Sousa Áurea , Bacelar-Nicolau Helena 
Published: December 2023

AbstractThe evaluation of clustering structures is a crucial step in cluster analysis. This study presents the main results of the hierarchical cluster analysis of variables concerning a real dataset in the context of Higher Education. The goal of this research is to find a typology of some relevant items taking into account both the homogeneity and the isolation of the clusters. Two similarity measures, namely the standard affinity coefficient and Spearman’s correlation coefficient, were used, and combined with three probabilistic (AVL, AVB and AV1) aggregation criteria, from a parametric family in the scope of the VL (Validity Link) methodology. The best partitions were selected based on some validation indices, namely the global STAT levels statistics and the measures P(I2, Σ) and γ, adapted to the case of similarity coefficients. In order to evaluate the clusters and identify their most representative elements, the Mann and Whitney U statistics and the silhouette plot were also used.
A Proposal for Formalization and Definition of Anomalies in Dynamical Systems
Authors: Spoor Jan Michael , Weber Jens , Ovtcharova Jivka 
Published: December 2023

AbstractAlthough many scientists strongly focus on anomaly detection in different applications and domains, there currently exists no universally accepted definition of anomalies and outliers. Using an approach based on control theory and dynamical systems, as well as a definition for anomalies as described by philosophy of science, the authors propose a generalized framework viewing anomalies as key drivers of progress for a better understanding of the dynamical systems around us. By mathematically defining anomalies and delimiting deviations within expectations from completely unforeseen instances, this paper aims to be a contribution to set up a universally accepted definition of anomalies and outliers.
A Review on Official Survey Item Classification for Mixed-Mode Effects Adjustment
Authors: Ashofteh Afshin , Campos Pedro 
Published: December 2023

AbstractThe COVID-19 pandemic has had a direct impact on the development, production, and dissemination of official statistics. This situation led National Statistics Institutes (NSIs) to make methodological and practical choices for survey collection without the need for the direct contact of interviewing staff (i.e. remote survey data collection). Mixing telephone interviews (CATI) and computer-assisted web interviewing (CAWI) with direct contact of interviewing constitute a new way for data collection at the time COVID-19 crisis. This paper presents a literature review to summarize the role of statistical classification and design weights to control cover-age errors and non-response bias in mixed-mode questionnaire design. We identified 289 research articles with a computerized search over two databases, Scopus and Web of Science. It was found that, although employing mixed-mode surveys could be considered as a substitution of traditional face-to-face interviews (CAPI), proper statistical classification of survey items and responders is important to control the nonresponse rates and coverage error risk.
Climate-Smart Technologies for Empowerment of Women Farmers in Africa
Authors: Adeola Ogechi , Evans Olaniyi , Ngare Innocent 
Published: December 2023

AbstractGiven the constraints women experience in adopting climate-smart technologies in Africa, it is crucial to conduct more rigorous research to understand the nature of these constraints and develop appropriate interventions. This chapter aims to explore the use of climate-smart technologies to empower women farmers in Africa. It emphasises the need for technologies that can enhance agricultural productivity and food security while benefiting women. Climate-smart agricultural practices, including those that address land degradation and desertification, can be adopted by women in African countries. Moreover, these practices can also be extended to improve timber production, enhance food security, and reduce the vulnerability of crops and livestock to the effects of climate change. This chapter underscores the importance of gender-sensitive approaches in developing and implementing climate-smart technologies to enhance the resilience of women farmers in Africa and promote sustainable agriculture.
From Uji to Being-Time (and Back): Translating Dōgen into Philosophy
Authors: Steineck Raji C. 
Published: December 2023

AbstractI seek to show that the declared aim of Dōgen’s writings, which were often edited versions of ritualised verbal teachings, was to guide disciples on the Buddha Way—a practical path to salvation that was clearly defined and delimited by an authoritative tradition. Dōgen, therefore, tried to preclude rather than foster the open-ended discussion of fundamental problems of human life that is otherwise usually associated with the concept of philosophy. Hence, Dōgen speaks a language of persuasion that is guided by aims and rules of discourse different from those of philosophy. This, or so I argue, is an aspect that is often lost when Dōgen’s thoughts are transferred into philosophical debates. The result is, in many instances, a rather facile alignment with the recipient’s own preconceptions. To substantiate my hypothesis, I start from factual observations concerning the modern philosophical reception of Dōgen’s teachings on time in Japan and the Anglophone world, focusing on the semantic shifts occurring in interpretations by prominent authors such as Tanabe Hajime, Ōmori Shōzō, Rein Raud, and others. I then turn to the theory of translation to analyse the seminal factors at play in this observed process of transformative reception. Finally, I reflect on how conceiving of the transfer of Dōgen’s thought into philosophical discourse as a process of translation can help to build interpretations that are both hermeneutically sound and philosophically interesting.
‘Nothing about us without us’. Including Lived Experiences of People with Intellectual Disabilities in Policy and Service Design
Authors: Anderson Sian , Bigby Christine 
Published: December 2023

AbstractThe rights of people with disabilities to be included in the design of policy and services are asserted in international treaties such as the United Nations Convention on the Rights of Persons with Disability and increasingly reflected in disability policies across the world. Approaches to facilitating the inclusion of lived experiences and the perspectives of people with disabilities include consultative, advisory or governance bodies, as well as co-design of projects, advocacy work of Disabled Person’s Organisations and self-advocacy groups. The success of these various approaches depends on their power to influence policy and services, the way they operate and the methods they use to support the participation of people with disabilities. This chapter reviews evidence about different approaches to tapping into the expertise people with disabilities have from their lived experiences of disability, and considers the types of practices most effective for working together with people with disabilities and some of the unresolved issues that support workers, managers and policy makers must grapple with to further the rights of people so that there is ‘nothing about us without us’.
Organisational Culture in Disability Accommodation Services
Authors: Humphreys Lincoln 
Published: December 2023

AbstractCulture refers to shared beliefs, values, basic assumptions, norms, and patterns of behaviour that influence how staff think, feel, and act. It exists at multiple levels within organisations (e.g., whole of organisation, senior managers, frontline service) and it enables and constrains what staff do. Most research on culture in disability organisations has occurred at the service level. Culture can account for poor practice and abuse of people with intellectual disabilities living in supported accommodation services. Conversely, it can contribute to good quality support and quality of life outcomes. This chapter explains what is culture, how it influences staff behaviour, the characteristics of culture in good and poor quality services, and how to change culture.
General gravitational charges on null hypersurfaces
Authors: Odak Gloria , Rignon-Bret Antoine , Speziale Simone 
Published: December 2023

Abstract
We perform a detailed study of the covariance properties of the symplectic potential of general relativity on a null hypersurface, and of the different polarizations that can be used to study conservative as well as leaky boundary conditions. This allows us to identify a one-parameter family of covariant symplectic potentials. We compute the charges and fluxes for the most general phase space with arbitrary variations. We study five symmetry groups that arise when different restrictions on the variations are included. Requiring stationarity as in the original Wald-Zoupas prescription selects a unique member of the family of symplectic potentials, the one of Chandrasekaran, Flanagan and Prabhu. The associated charges are all conserved on non-expanding horizons, but not on flat spacetime. We show that it is possible to require a weaker notion of stationarity which selects another symplectic potential, again in a unique way, and whose charges are conserved on both non-expanding horizons and flat light-cones. Furthermore, the flux of future-pointing diffeomorphisms at leading-order around an outgoing flat light-cone is positive and reproduces a tidal heating plus a memory term. We also study the conformal conservative boundary conditions suggested by the alternative polarization and identify under which conditions they define a non-ambiguous variational principle. Our results have applications for dynamical notions of entropy, and are useful to clarify the interplay between different boundary conditions, charge prescriptions, and symmetry groups that can be associated with a null boundary.
Unveiling the role of ABI3 and hub senescence-related genes in macrophage senescence for atherosclerotic plaque progression
Authors: Fu Yajuan , Zhang Juan , Liu Qiujun , Yang Lan , Wu Qianqian , Yang Xiaomin , Wang Lexin , Ding Ning , Xiong Jiantuan , Gao Yujing , Ma Shengchao , Jiang Yideng 
Published: December 2023

Abstract
Background
Atherosclerosis, characterized by abnormal arterial lipid deposition, is an age-dependent inflammatory disease and contributes to elevated morbidity and mortality. Senescent foamy macrophages are considered to be deleterious at all stages of atherosclerosis, while the underlying mechanisms remain largely unknown. In this study, we aimed to explore the senescence-related genes in macrophages diagnosis for atherosclerotic plaque progression.

Methods
The atherosclerosis-related datasets were retrieved from the Gene Expression Omnibus (GEO) database, and cellular senescence-associated genes were acquired from the CellAge database. R package Limma was used to screen out the differentially expressed senescence-related genes (DE-SRGs), and then three machine learning algorithms were applied to determine the hub DE-SRGs. Next, we established a nomogram model to further confirm the clinical significance of hub DE-SRGs. Finally, we validated the expression of hub SRG ABI3 by Sc-RNA seq analysis and explored the underlying mechanism of ABI3 in THP-1-derived macrophages and mouse atherosclerotic lesions.

Results
A total of 15 DE-SRGs were identified in macrophage-rich plaques, with five hub DE-SRGs (ABI3, CAV1, NINJ1, Nox4 and YAP1) were further screened using three machine learning algorithms. Subsequently, a nomogram predictive model confirmed the high validity of the five hub DE-SRGs for evaluating atherosclerotic plaque progression. Further, the ABI3 expression was upregulated in macrophages of advanced plaques and senescent THP-1-derived macrophages, which was consistent with the bioinformatics analysis. ABI3 knockdown abolished macrophage senescence, and the NF-κB signaling pathway contributed to ABI3-mediated macrophage senescence.

Conclusion
We identified five cellular senescence-associated genes for atherogenesis progression and unveiled that ABI3 might promote macrophage senescence via activation of the NF-κB pathway in atherogenesis progression, which proposes new preventive and therapeutic strategies of senolytic agents for atherosclerosis.
Partitions, multiple zeta values and the q-bracket
Authors: Bachmann Henrik , van Ittersum Jan-Willem 
Published: December 2023

AbstractWe provide a framework for relating certainq-series defined by sums over partitions to multiple zeta values. In particular, we introduce a space of polynomial functions on partitions for which the associatedq-series areq-analogues of multiple zeta values. By explicitly describing the (regularized) multiple zeta values one obtains as$$q\rightarrow 1$$q→1, we extend previous results known in this area. Using this together with the fact that other families of functions on partitions, such as shifted symmetric functions, are elements in our space will then give relations among (q-analogues of) multiple zeta values. Conversely, we will show that relations among multiple zeta values can be ‘lifted’ to the world of functions on partitions, which provides new examples of functions for which the associatedq-series are quasimodular.
A global climatology of tropical easterly waves
Authors: Hollis Margaret A. , McCrary Rachel R. , Stachnik Justin P. , Lewis-Merritt Carrie , Martin Elinor R. 
Published: December 2023

AbstractTropical easterly waves (TEWs) are westward-propagating off-equatorial waves that are typically convectively coupled. TEWs make significant contributions to the annual rainfall in many regions of the tropics, and often seed tropical cyclones. Climatologies of TEWs exist regionally and hemispherically, however, none exist at the global scale. The climatology in this study is the first attempt to study TEWs globally, applying a combination of the TRACK algorithm and objective criteria to all basins to identify TEW activity at both 850 and 700 hPa. In addition to areas of TEW activity in previously studied regions such as the North Atlantic and eastern North Pacific Ocean basins, this study has identified TEW activity in every other tropical ocean basin in both hemispheres. On average across the globe, the methods employed tracked 380 waves per year at 850 hPa and 638 waves per year at 700 hPa. There were no significant linear trends globally or hemispherically over the 41 years analyzed, but large interannual variability. Despite the variety of regions the TEWs occur in, the distribution of average speeds agrees with studies using other data and tracking methods, with averages between 7.5–8 m s−1 depending on the level and hemisphere. TEW activity shows a strong preference to the warm season, with approximately double the number of TEWs occurring in the warm season compared to the cold season, a pattern that is observed in both the northern and southern hemispheres. This database is publicly available to enable further work in understanding TEW behavior and predictability globally.
MMS hotspots: a cross-sectional comparison of U.S. counties with and without Mohs micrographic surgery
Authors: Sharma Ajay Nair , Peterman Nicholas , Juhasz Margit , Shive Melissa 
Published: December 2023

AbstractHealthcare access greatly impacts skin cancer diagnosis and mortality rates. Recognition of current disparities in Mohs micrographic surgery (MMS) access can assist future policy and clinical decisions to correct them. For the years 2014–2018, the CPT codes for MMS (17,311 and 17,313) were counted on a per county level across the United States per the Medicare Centers for Medicare & Medicaid Services (CMS) Medicare Prescriber Database. Any county with 0 MMS CPT codes recorded were classified as “without MMS cases.” MMS “hotspots” were identified as counties that possessed a high average number of MMS cases compared to the national average, while also being surrounded by counties that possessed a low average number of MMS cases compared to the national average. Three thousand eighty-four counties in the United States were analyzed; 785 (25%) counties were designated as “with MMS cases” and 2301 (75%) “without MMS cases.” There were no significant differences in age, ethnicity distribution, or cost per enrollee between the two designations. 74% of counties with MMS cases were considered urban, while only 25% of those without cases were urban (p < 0.01). The median household income was markedly higher in counties with MMS cases ($71,428 vs. $58,913, p < 0.01). With respect to education, more individuals in counties with MMS cases possessed their General Education Development (GED) (89% vs. 86%, p < 0.01) or a college degree (30% vs. 19%, p < 0.01). Forty-nine counties were considered MMS “hotspots.” The density of MMS procedures varies greatly based on geography, maintaining the urban–rural disparity matched by the distribution of MMS surgeons. Additionally, there remains a wide income and educational gap between counties with and without MMS. Identifying MMS hotspots may facilitate further investigation into potential surgical access disparities.