bluuebunny/crossref_metadata_2025 huggingface dataset:
Taking advantage of opportunistically collected historical occurrence data to detect responses to climate change: The case of temperature and Iberian dung beetles
Authors: Lobo Jorge M. , Mingarro Mario , Godefroid Martin , García‐Roselló Emilio
Published: December 2023

This study introduces a novel approach to leverage high‐resolution historical climate data and opportunistically collected historical species occurrence data for detecting adaptive responses to global change. We applied this procedure to the temperature data and the most comprehensive Iberian dataset of dung beetle occurrences as an illustrative example. To understand how populations of different species are responding, we devised a procedure that compares the temporal trend of spatial and temperature variables at the locations and times of all the occurrence data collection (overall trend) with the specific temporal trends among the occurrences of each species. The prevalence of various species responses is linked to life history or taxonomic characteristics, enabling the identification of key factors influencing the propensity to experience different effects from climate change. Our findings suggest that nearly half of the Iberian dung beetle species may be adversely affected by temperature increases, with a geographic shift being the most common response. The results generated through the proposed methodology should be regarded as preliminary information, serving to formulate hypotheses about the diverse responses of species to climate change and aiding in the selection of candidate species capable of coping with challenges posed by changing temperatures.
Exploring liquid oxidants and metal‐free cathode for enhanced performance in a reusable 3D‐printed glycerol microfluidic fuel cell
Authors: Guima Katia‐Emiko , Zanata Cinthia R. , Martins Cauê A.
Published: December 2023

Microfluidic fuel cells (μFCs) offer a promising avenue for generating energy from glycerol, utilizing flow‐through electrodes to enhance reactant utilization. However, the cathodic reaction must efficiently consume the electrons harvested at the anode side to unlock its full potential. Here, we explore the feasibility of employing liquid oxidants as an alternative to O2 reduction on metal‐free carbon paper (CP) cathodes. We investigated the half‐cell reactions and the energy conversion in a new reusable 3D‐printed μFC. Half‐cell reactions predict spontaneous reactions by coupling glycerol electrooxidation in an alkaline medium with O2, Na2S2O8, and HClO from commercial bleach in an acidic medium. The μFC printed using the stereolithography apparatus technique build microchannels to place the Pt/C/CP anode and CP cathodes. The glycerol/Na2S2O8 μFC delivered a maximum of 32.4 mW cm−2, while glycerol/HClO μFC displayed 55.9 mW cm−2. This research sheds light on the potential of liquid oxidants as effective alternatives to O2 reduction, presenting a pathway toward optimizing μFCs and their practical applications in energy conversion from glycerol.
Probing the Optoelectronic Properties and Energy Conversion of Boron Nitride Quantum Dots: Impact of Oxygen Doping and Chemical Functionalization
Authors: Cui Peng , Wu Qiulan
Published: December 2023

Boron nitride quantum dots (BNQDs) are emerging nanomaterials with promising applications in photocatalysis and optoelectronics. Chemical functionalization effectively tunes the optoelectronic properties and photocatalytic performance of BNQDs. This study investigates the impact of oxygen doping and functionalization with urea, thiourea, and p‐phenylenediamine (PPD) on BNQD properties. Density functional theory calculations reveal that these functional groups introduce new electronic states within the bandgap, shifting absorption spectra and reducing the bandgap due to ligand molecular orbital contributions. Functionalization also adjusts the energy‐level alignment between BNQDs and cocatalysts, enhancing interfacial charge transfer. Oxygen‐doped, chemically functionalized BNQDs exhibit significantly higher first‐order hyperpolarizability, up to 17 times greater than pristine BNQDs, enabling superior optical nonlinearities. Additionally, PPD functionalization leads to a remarkable 18.2% photocatalytic energy conversion efficiency under simulated solar irradiation. These achieved quantum yields result from bandgap engineering, expanded light harvesting, increased exciton densities, prolonged exciton lifetimes, and improved charge separation and transfer dynamics. This study provides crucial insights into property tuning mechanisms, establishing the promising potential of chemically functionalized BNQDs for energy conversion and optoelectronic technologies.
Estimating the effect of policy entrepreneurship on individual vaccination behavior during the COVID‐19 pandemic
Authors: Taylor Kristin , DeLeo Rob A. , Albright Elizabeth , Koebele Elizabeth A. , Birkland Thomas A. , Crow Deserai A. , Zhang Manli , Shanahan Elizabeth A.
Published: December 2023

Most studies of policy entrepreneurship seek to understand how entrepreneurs influence the behavior of policy‐makers in the agenda‐setting or decision‐making phases of the policy process. Recent scholarship has sought to understand what role entrepreneurs might play in policy implementation by focusing on their ability to influence bureaucrats' discretion and behavior. However, these studies overlook the potentially critical influence of policy entrepreneurs during the implementation of “opt‐in” policies that require voluntary compliance by individuals to be successful. Here, we consider whether and how a visible policy entrepreneur can impact opt‐in policy implementation, focusing on their credibility—or ability to gain public trust—as a potential driving factor of their influence. Using the empirical context of COVID‐19 vaccination recommendations, we identify Dr. Anthony Fauci as a highly visible policy entrepreneur and assess his influence on individual vaccine intention and uptake. Drawing on data from a novel panel survey of the American public on attitudes about the virus, risk, politics, and vaccination during the first several months of the COVID‐19 vaccine rollout in the United States, we test the relationship between respondent trust in Dr. Fauci and changes in reported intention to vaccinate and vaccination uptake across time. We find that trust in Dr. Fauci is an important predictor for influencing individuals' intention to vaccinate and actual vaccination behavior.
Time course of EEG power during creative problem‐solving with insight or remote thinking
Authors: Bieth Théophile , Ovando‐Tellez Marcela , Lopez‐Persem Alizée , Garcin Béatrice , Hugueville Laurent , Lehongre Katia , Levy Richard , George Nathalie , Volle Emmanuelle
Published: December 2023

Problem‐solving often requires creativity and is critical in everyday life. However, the neurocognitive mechanisms underlying creative problem‐solving remain poorly understood. Two mechanisms have been highlighted: the formation of new connections among problem elements and insight solving, characterized by sudden realization of a solution. In this study, we investigated EEG activity during a modified version of the remote associates test, a classical insight problem task that requires finding a word connecting three unrelated words. This allowed us to explore the brain correlates associated with the semantic remoteness of connections (by varying the remoteness of the solution word across trials) and with insight solving (identified as a Eurêka moment reported by the participants). Semantic remoteness was associated with power increase in the alpha band (8–12 Hz) in a left parieto‐temporal cluster, the beta band (13–30 Hz) in a right fronto‐temporal cluster in the early phase of the task, and the theta band (3–7 Hz) in a bilateral frontal cluster just prior to participants' responses. Insight solving was associated with power increase preceding participants' responses in the alpha and gamma (31–60 Hz) bands in a left temporal cluster and the theta band in a frontal cluster. Source reconstructions revealed the brain regions associated with these clusters. Overall, our findings shed new light on some of the mechanisms involved in creative problem‐solving.
How do intangible assets and financial constraints affect stock returns in Vietnam before and during the COVID‐19 pandemic?
Authors: Duong Khoa Dang , Huynh Tran Ngoc , Truong Linh Thi Diem
Published: December 2023

We are the first to determine the effect of intangible intensity (INTANG) on cross‐sectional stock returns after controlling financial constraints in the Vietnam stock market. Our sample includes 37,938 firm‐month observations from 488 non‐financial firms from October 2008 to February 2021. We employ Fama and MacBeth regressions and portfolio analysis methodologies to estimate the impact of intangible assets and financial constraints on stock returns. Our findings show that a percentage increase in INTANG empowers stock returns by 0.922%. Meanwhile, the cross‐sectional stock returns decrease by 0.506% when the financial constraints index increases by a percentage point. Moreover, the results suggest that intangible assets in the entire sample and before COVID‐19 empower the stock return cross‐sectionally. Our findings are robust after employing alternative INTANG proxies. Our findings support the risk‐based explanation, the pecking order theory, and prior literature. Our findings suggest governments should promote intellectual property and copyright regulations to encourage Small and Medium Enterprises (SMEs) to expand intangible assets. Furthermore, investors can utilize our suggested models to construct their portfolios efficiently.
Does crop insurance influence crop yield impacts of warming temperatures? A farm‐level analysis
Authors: Regmi Madhav , Tack Jesse , Featherstone Allen M.
Published: December 2023

We examine the effects of the federal crop insurance program on crop production under extreme heat using farm‐level data from Kansas. We find that insured dryland corn is 38% more sensitive to extreme heat than uninsured dryland corn. Results also suggest that a uniform C warming scenario leads to yield reductions of 16.7% (11.8%) for insured (uninsured) corn production; and 6.0% (4.4%) for insured (uninsured) wheat production. Warming had a stronger impact with reduced rainfall, especially on insured farms compared with uninsured farms, while altered growing seasons showed potential benefits for wheat but limited improvements for corn.
Development of nanoparticle‐based drug delivery system for inflammation treatment and diagnosis
Authors: Qin Qin , Wang Mao , Zou Yu , Yang Dujiang , Deng Yuchuan , Lin Shuyu , Song Yiran , Li Rui , Zheng Yu
Published: December 2023

Inflammation is a prevalent pathological process that accompanies the onset and progression of numerous acute and chronic diseases including rheumatoid arthritis, sepsis, pancreatitis, atherosclerosis, ischaemic brain/heart disease and so forth. However, conventional anti‐inflammatory drugs have certain disadvantages such as nonspecific tissue distribution, low bioavailability, and a short half‐life, resulting in off‐target side effects and limited efficacy in disease control. To address these issues, nanoparticles have emerged as a novel therapeutic paradigm in this field to attain inflammation targeting and improve drug pharmacokinetic properties via the well‐recognized enhanced permeability and retention (EPR) effect at the inflammatory site. Existing reviews are predominantly centered on inflammatory pathology introduction and vector design. As a necessary complement, this review mainly elaborates on the introduction of inflammation core events, the history of the drug delivery system for anti‐inflammatory drugs, the action mechanism of inflammation targeting vectors, nanoparticle classification based on targeting moiety, methods to combine targeting moiety with core nanoparticles, techniques to assess targetability in vitro and in vivo and finally the challenges and prospects in this field. The information provided herein offers practical guidance to researchers seeking to develop and evaluate inflammation targeting vectors rationally.
Approximation properties by Bézier variant of the Baskakov–Schurer–Szász–Stancu operators
Authors: Braha Naim Latif , Mansour Toufik , Mursaleen Mohammad
Published: December 2023

In this paper, we have construct a new version of the Bézier‐type Baskakov–Schurer–Szász–Stancu operators. For this new class of operators, uniform convergence is shown in any compact subset or positive real line. We prove Korovkin‐type theorem, Voronovskaya‐type theorem, and Grüss–Voronovskaya‐type theorem. Moreover, at the end, we express the behavior of the operators in the Lipschitz‐type space using the modulus of continuity and smoothness.
Perforating Collagenosis
Authors: Oya Kazumasa , Saito Aki
Published: December 2023

We show a case of a 69-year-old man with perforating collagenosis, which is a rare dermatosis commonly associated with diabetes mellitus. Papules and plaques with keratotic plugs are distinctive clinical characteristic of perforating collagenosis. Representative clinical images in our article can enhance the understanding of key concepts of perforating collagenous.
Chalcones As Broad‐Spectrum Antimicrobial Agents: A Comprehensive Review And Analysis Of Their Antimicrobial Activities
Authors: Nawaz Tariq , Tajammal Affifa , Qurashi Aisha Waheed
Published: December 2023

The rise of drug‐resistant microbes necessitates the development of new antimicrobial agents. Increasing resistance among multidrug‐resistant microbes has spurred research efforts to overcome drug resistance through novel scaffolds and strategies. Chalcones, distinguished by their chemical structure of 1,3‐diphenylprop‐2‐en‐1‐one, have exhibited a multifaceted array of biological activities, prominently including antimicrobial and antiviral properties. Modifying the structure by adding substituent groups to the aromatic ring enhances potency, reduces toxicity, and expands pharmacological effects. This review highlights the potential of chalcones and analogues in preventing diseases affected by diverse antibiotic resistance genes, including viruses, bacteria, fungal spores, and Plasmodiidae. Our analysis underscores the fact that a multitude of chalcone compounds effectively obstruct various molecular targets pivotal in the development of antibiotic resistance, thus rendering bacteria vulnerable to conventional antibacterial agents and potentially obliterating resistance mechanisms. Certain chalcone compounds exhibit higher activity levels compared to traditional antibiotics like vancomycin and tetracycline. Additionally, Docking and SAR studies of chalcones summarize their role in developing novel drugs. Chalcones and their derivatives demonstrate promising broad‐spectrum antimicrobial activities. Investigating structure‐activity relationships (SAR) enhances our understanding of chalcone‐based drug design, enabling the development of more effective therapeutic interventions against the pressing global health challenge of antimicrobial resistance.
Phosphine‐Catalyzed C‐Methoxylation of para‐Quinone Methides with Methanol and Deuterated Methanol as C1 Sources
Authors: Zhong Yuan , Zhang Dan , Li Guichen , Jia Zhilong , Hao Long , Wang Xin
Published: December 2023

In this work, we developed a phosphine‐catalyzed C‐methoxylation process of para‐quinone methides (p‐QMs). By employing a metal‐free phosphine catalyst [P(4‐MeC6H4)3] together with methanol and deuterated methanol (d4, d1, and d3) as C1 sources, a series of methoxylated diarylmethanes and the corresponding deuterated products were obtained without additional solvent under mild reaction conditions.
Evaluating ChatGPT text mining of clinical records for companion animal obesity monitoring
Authors: Fins Ivo S. , Davies Heather , Farrell Sean , Torres Jose R. , Pinchbeck Gina , Radford Alan D. , Noble Peter‐John
Published: December 2023

Background

Veterinary clinical narratives remain a largely untapped resource for addressing complex diseases. Here we compare the ability of a large language model (ChatGPT) and a previously developed regular expression (RegexT) to identify overweight body condition scores (BCS) in veterinary narratives pertaining to companion animals.

Methods

BCS values were extracted from 4415 anonymised clinical narratives using either RegexT or by appending the narrative to a prompt sent to ChatGPT, prompting the model to return the BCS information. Data were manually reviewed for comparison.

Results

The precision of RegexT was higher (100%, 95% confidence interval [CI] 94.81%–100%) than that of ChatGPT (89.3%, 95% CI 82.75%–93.64%). However, the recall of ChatGPT (100%, 95% CI 96.18%–100%) was considerably higher than that of RegexT (72.6%, 95% CI 63.92%–79.94%).

Limitations

Prior anonymisation and subtle prompt engineering are needed to improve ChatGPT output.

Conclusions

Large language models create diverse opportunities and, while complex, present an intuitive interface to information. However, they require careful implementation to avoid unpredictable errors.
Integrated EPANET‐MSX process models of chlorine and its by‐products in drinking water distribution systems
Authors: Fisher Ian H.
Published: December 2023

EPANET and its commercial derivatives are the most widely‐used software packages for modeling free chlorine and its by‐products in drinking water distribution systems. Yet, they are not sufficiently accurate, general, or efficient for deriving optimal chlorine dosing strategies at different seasonal temperatures. To overcome EPANET's limitations, an integrated set of rigorously validated multispecies process models are proposed for application within the EPANET‐MSX environment. An executable (command‐line) version of these MSX models is supplied for use either within the MSX environment or embedded in commercial versions of MSX. A new general method was devised to obtain output of any intermediate coefficient or variable involved in the simulation. This overcomes MSX's limited output options. When the debugged models were applied to a real distribution system, the optimal chlorine dose for summer required almost double the chlorine dose needed in winter. A lower initial dose combined with a downstream booster dose required less chlorine in total. Formal optimization techniques are needed to efficiently obtain similar strategies in more complex systems.

Practitioner Points

EPANET water quality models are not accurate or general enough for deriving optimal chlorine dosing strategies in distribution systems.

Integrated EPNET‐MSX models of chlorine reactions in bulk water and at pipe walls, and associated by‐product formation, overcome EPANET’s limitations.

To verify model authenticity, a general technique was developed to obtain values of coefficients and variables within an EPANET‐MSX simulation.

EPANET‐MSX command lines implementing these integrated EPANET‐MSX models are presented with verified results for optimal initial and booster dosing strategies.

Optimal summer dosing in a real system of rough pipes was almost double that required in winter.
Numerical solution for cross nanofluid flow in porous medium over stretching cylinder under MHD and radiation effects
Authors: Munazza F. , Farooq M. Asif
Published: December 2023

The aim of the present study is to analyze heat source in unsteady MHD nanofluid flow subjected to convective boundary conditions past a stretching cylinder incorporated with variable thermal properties. This study is significant in industries involving chemical processing, oil and gas, and manufacturing. The problem possesses a nonsimilar solution when similarity variables are utilized in transforming governing partial differential equations into ordinary differential equations. The numerical solution is found using MATLAB packagebvp4c. The velocity, temperature, and concentration curves for various parameters are plotted graphically. The values for the coefficient of skin friction, heat transfer, and mass transfer rate are tabulated for the unsteadiness parameter, Weissenberg number, Prandtl number, Schmidt number, heat source/sink, thermal conductivity parameter, thermal and solutal Biot number, thermophoresis and Brownian parameter, radiation parameter, porosity parameter, and magnetic parameter. It is noted that, rise in porosity (–) and magnetic parameter (–) contributes to the decrease in velocity profile. It is found that, radiation effects help in incrementing rate of heat and mass transfer into fluid when radiation parameter ranges from to . Moreover, present results are in good agreement with the literature published in a limiting context.
A Topological Clustering of Individuals
Authors: Abdesselam Rafik
Published: December 2023

The clustering of objects-individuals is one of the most widely used approaches to exploring multidimensional data. The two common unsupervised clustering strategies are Hierarchical Ascending Clustering (HAC) and k-means partitioning used to identify groups of similar objects in a dataset to divide it into homogeneous groups. The proposed Topological Clustering of Individuals, or TCI, studies a homogeneous set of individual rows of a data table, based on the notion of neighborhood graphs; the columns-variables are more-or-less correlated or linked according to whether the variable is of a quantitative or qualitative type. It enables topological analysis of the clustering of individual variables which can be quantitative, qualitative or a mixture of the two. It first analyzes the correlations or associations observed between the variables in a topological context of principal component analysis (PCA) or multiple correspondence analysis (MCA), depending on the type of variable, then classifies individuals into homogeneous group, relative to the structure of the variables considered. The proposed TCI method is presented and illustrated here using a real dataset with quantitative variables, but it can also be applied with qualitative or mixed variables.
COVID-19 Pandemic: A Methodological Model for the Analysis of Government’s Preventing Measures and Health Data Records
Authors: Chadjipadelis Theodore , Magopoulou Sofia
Published: December 2023

The study aims to investigate the associations between the government’s response measures during the COVID-19 pandemic and weekly incidence data (positivity rate, mortality rate and testing rate) in Greece. The study focuses on the period from the detection of the first case in the country (26th February 2020) to the first week of 2022 (08th January 2022). Data analysis was based on Correspondence Analysis on a fuzzy-coded contingency table, followed by Hierarchical Cluster Analysis (HCA) on the factor scores. Results revealed distinct time periods during which interesting interactions took place between control measures and incidence data.
Trends in Data Stream Mining
Authors: Gama João
Published: December 2023

Learning from data streams is a hot topic in machine learning and data mining. This article presents our recent work on the topic of learning from data streams. We focus on emerging topics, including fraud detection and hyper-parameter tuning for streaming data. The first study is a case study on interconnected by-pass fraud. This is a real-world problem from high-speed telecommunications data that clearly illustrates the need for online data stream processing. In the second study, we present an optimization algorithm for online hyper-parameter tuning from nonstationary data streams.
Model Based Clustering of Functional Data with Mild Outliers
Authors: Anton Cristina , Smith Iain
Published: December 2023

We propose a procedure, called CFunHDDC, for clustering functional data with mild outliers which combines two existing clustering methods: the functional high dimensional data clustering (FunHDDC) [1] and the contaminated normal mixture (CNmixt) [3] method for multivariate data. We adapt the FunHDDC approach to data with mild outliers by considering a mixture of multivariate contaminated normal distributions. To fit the functional data in group-specific functional subspaces we extend the parsimonious models considered in FunHDDC, and we estimate the model parameters using an expectation-conditional maximization algorithm (ECM). The performance of the proposed method is illustrated for simulated and real-world functional data, and CFunHDDC outperforms FunHDDC when applied to functional data with outliers.
Some Issues in Robust Clustering
Authors: Hennig Christian
Published: December 2023

Some key issues in robust clustering are discussed with focus on the Gaussian mixture model based clustering, namely the formal definition of outliers, ambiguity between groups of outliers and clusters, the interaction between robust clustering and the estimation of the number of clusters, the essential dependence of (not only) robust clustering on tuning decisions, and shortcomings of existing measurements of cluster stability when it comes to outliers.
Detecting Differences in Italian Regional Health Services During Two Covid-19 Waves
Authors: Palazzo Lucio , Ievoli Riccardo
Published: December 2023

During the first twowaves of Covid-19 pandemic, territorial healthcare systems have been severely stressed in many countries. The availability (and complexity) of data requires proper comparisons for understanding differences in performance of health services. We apply a three-steps approach to compare the performance of Italian healthcare system at territorial level (NUTS 2 regions), considering daily time series regarding both intensive care units and ordinary hospitalizations of Covid-19 patients. Changes between the two waves at a regional level emerge from the main results, allowing to map the pressure on territorial health services.
Political and Religion Attitudes in Greece: Behavioral Discourses
Authors: Panagiotidou Georgia , Chadjipadelis Theodore
Published: December 2023

The research presented in this paper attempts to explore the relationship between religious and political attitudes. More specifically we investigate how religious behavior, in terms of belief intensity and practice frequency, is related to specific patterns of political behavior such as ideology, understanding democracy and his set of moral values. The analysis is based on the use of multivariable methods and more specifically Hierarchical Cluster Analysis and Multiple Correspondence Analysis in two steps. The findings are based on a survey implemented in 2019 on a sample of 506 respondents in the wider area of Thessaloniki, Greece. The aim of the research is to highlight the role of people’s religious practice intensity in shaping their political views by displaying the profiles resulting from the analysis and linking individual religious and political characteristics as measured with various variables. The final output of the analysis is a map where all variable categories are visualized, bringing forward models of political behavior as associated together with other factors such as religion, moral values and democratic attitudes.
The Death Process in Italy Before and During the Covid-19 Pandemic: A Functional Compositional Approach
Authors: Scimone Riccardo , Menafoglio Alessandra , Sangalli Laura M. , Secchi Piercesare
Published: December 2023

In this talk, based on [1], we propose a spatio-temporal analysis of daily death counts in Italy, collected by ISTAT (Italian Statistical Institute), in Italian provinces and municipalities. While in [1] the focus was on the elderly class (70+ years old), we here focus on the middle class (50–69 years old), carrying out analogous analyses and comparative observations. We analyse historical provincial data starting from 2011 up to 2020, year in which the impacts of the Covid-19 pandemic on the overall death process are assessed and analysed. The cornerstone of our analysis pipeline is a novel functional compositional representation for the death counts during each calendar year: specifically, we work with mortality densities over the calendar year, embedding them in the Bayes space B2 of probability density functions. This Hilbert space embedding allows for the formulation of functional linear models, which are used to split each yearly realization of the mortality density process in a predictable and an unpredictable component, based on the mortality in previous years. The unpredictable components of the mortality density are then spatially analysed in the framework of Object Oriented Spatial Statistics. Via spatial downscaling of the results obtained at the provincial level, we obtain smooth predictions at the fine scale of Italian municipalities; this also enable us to perform anomaly detection, identifying municipalities which behave unusually with respect to the surroundings.
Typology of Motivation Factors for Employees in the Banking Sector: An Empirical Study Using Multivariate Data Analysis Methods
Authors: Sousa Áurea , Silva Osvaldo , Batista M. Graça , Cabral Sara , Bacelar-Nicolau Helena
Published: December 2023

Leadership has been considerate as a competitive advantage for organizations, contributing to their success and effective and efficient performance. Motivation, on the other hand, is assumed as a basic competence of leadership. Therefore, the main purpose of this paper is to know the perceptions of bank employees on the main motivational factors in the organizational context. Data analysis was performed based on several statistical methods, among which the Categorical Principal Component Analysis (CatPCA) and some agglomerative hierarchical clustering algorithms from VL (V for Validity, L for Linkage) parametrical family, applied to the items that aim to assess the aspects most valued by bankers in the work context. The CatPCA allowed to extract four principal components which explain almost 70% of the total data variance. The dendrograms provided by the hierarchical clustering algorithms over the same data, exhibit four main branches, which are associated with different main motivational factors. Moreover, CatPCA and clustering results show an important correspondence concerning the main motivations in this sector.
Generalized Spatio-Temporal Regression with PDE Penalization
Authors: Arnone Eleonora , Cunial Elia , Sangalli Laura M.
Published: December 2023

We develop a novel generalised linear model for the analysis of data distributed over space and time. The model involves a nonparametric term 5, a smooth function over space and time. The estimation is carried out by the minimization of an appropriate penalized negative log-likelihood functional, with a roughness penalty on 5 that involves space and time differential operators, in a separable fashion, or an evolution partial differential equation. The model can include covariate information in a semi-parametric setting. The functional is discretized by means of finite elements in space, and B-splines or finite differences in time. Thanks to the use of finite elements, the proposed method is able to efficiently model data sampled over irregularly shaped spatial domains, with complicated boundaries. To illustrate the proposed model we present an application to study the criminality in the city of Portland, from 2015 to 2020.
New Metrics for Classifying Phylogenetic Trees Using K-means and the Symmetric Difference Metric
Authors: Tahiri Nadia , Koshkarov Aleksandr
Published: December 2023

The k-means method can be adapted to any type of metric space and is sometimes linked to the median procedures. This is the case for symmetric difference metric (or Robinson and Foulds) distance in phylogeny, where it can lead to median trees as well as to Euclidean Embedding. We show how a specific version of the popular k-means clustering algorithm, based on interesting properties of the Robinson and Foulds topological distance, can be used to partition a given set of trees into one (when the data is homogeneous) or several (when the data is heterogeneous) cluster(s) of trees. We have adapted the popular cluster validity indices of Silhouette, and Gap to tree clustering with k-means. In this article, we will show results of this new approach on a real dataset (aminoacyl-tRNA synthetases). The new version of phylogenetic tree clustering makes the new method well suited for the analysis of large genomic datasets.
Latent Block Regression Model
Authors: Boutalbi Rafika , Labiod Lazhar , Nadif Mohamed
Published: December 2023

When dealing with high dimensional sparse data, such as in recommender systems,co-clusteringturnsouttobemorebeneficialthanone-sidedclustering,even if one is interested in clustering along one dimension only. Thereby, co-clusterwise is a natural extension of clusterwise. Unfortunately, all of the existing approaches do not consider covariates on both dimensions of a data matrix. In this paper, we propose a Latent Block Regression Model (LBRM) overcoming this limit. For inference, we propose an algorithm performing simultaneously co-clustering and regression where a linear regression model characterizes each block. Placing the estimate of the model parameters under the maximum likelihood approach, we derive a Variational Expectation–Maximization (VEM) algorithm for estimating the model’s parameters. The finality of the proposed VEM-LBRM is illustrated through simulated datasets.
Living with Nature Across Time, Space and Cultural Perspectives: Introduction
Authors: Olko Justyna , Radding Cynthia
Published: December 2023

The introductory chapter describes conceptual frameworks and methodological approaches employed in the book to address environmentally informed histories. It also provides an overview of the thematic contents of individual chapters that combine archaeological data, oral history, linguistic research as well as ritual life and different testimonies of agency of Native communities, connected by major questions and overarching themes of the book. We argue that these interrelated studies, grounded in a variety of theoretical tools and representing different but complementary positionalities, build a multi-angled and diachronic account of complex entanglements between Indigenous peoples and their natural and social environs. Taken together, they offer a vivid and critical dialogue between different time periods, geographic areas, disciplines and epistemologies, driven by a fruitful interaction between academic perspectives and Indigenous methodologies. Referring to the environment as nature worked upon by historical and modern communities in culturally sensitive and transformative ways, we embrace the concepts of territory and place linked to the sense of identity and belonging. The introductory essay also highlights the importance of cultural continuity nurtured through ancestral languages and anchored in dynamic relationships with the environment, natural resources and community knowledge.
Gender Disparities in Guaraní Knowledge, Literacy, and Fashion in the Ecological Borderlands of Colonial and Early Nineteenth-Century Paraguay
Authors: Ganson Barbara A.
Published: December 2023

This essay analyzes the gender disparities in Guaraní education and literacy in the province of Paraguay during the colonial era through the mid-nineteenth century, based on original Guaraní texts and other archival sources, including school censuses and Guaraní schoolwork. The use of the Native language, in written and spoken forms, proved to be a contentious issue in Paraguay, reflecting the cultural resiliency of the Guaraní, the forces of cultural domination, and the relationship between education, literacy, and gender. Fashion is an element in this analysis as well, because the types of clothing worn reflected the Guaraníes’ changing sense of identity. While the Jesuits encouraged the study and use of the Guaraní language in the mission schools, Bourbon language reforms altered education in the missions in the mid-eighteenth century by the requirements of the colonial state to teach the Guaraní Spanish. Nonetheless, there was a degree of tolerance to the use of the Native language so that the Guaraní could understand their lessons. However, there was no formal education in Paraguay for women and girls until after 1856.
The Generational Gap and the Road to Well-Being: Language and Natural Environment in the Discourses of Indigenous Old and Young in Tlaxcala
Authors: Haimovich Gregory
Published: December 2023

In this paper, the attitudes of Indigenous people to the problems of language shift and ecological changes are examined through a lens of intergenerational gap. The area under study is the rural and historically Nahuatl-speaking communities of Tlaxcala that experienced urbanization as well as linguistic and cultural assimilation during the twentieth century. A disparity between the older and younger generations is an ordinary phenomenon in such context, but in this case, the interviews recorded with both young and elderly residents show that the gap is probably more perceived than real. In their discussions on well-being and a better future that they wish for themselves and their communities, the interviewees of different age groups raise the same or quite related themes, reflecting on what has been lost in comparison to the past and what benefits the modernity has brought. It appears that such aspects as fresh water resources, amount of trees, and speaking Nahuatl, which declined as a result of the industrialization, have value for the younger community members as well as for the elderly. These shared values still provide an opportunity for a dialog and transmission of knowledge between the two divided generations.
“¡Amo kitlapanas tetl!”: Heritage Language and the Defense Against Fracking in the Huasteca Potosina, Mexico
Authors: Dexter-Sobkowiak Elwira
Published: December 2023

In this chapter I explore the relationship between language and environment loss and the use of heritage languages in resistance related to the defense of natural resources. This link is shown by analyzing the case of Nahua and Tének communities of the Huasteca Potosina in northeastern Mexico, which between 2013 and 2018 were involved in a range of collective actions against the threat of fracking, a highly damaging method of gas and oil extraction. One particularly interesting aspect of these activities was the spontaneous use of the Indigenous languages Nahuatl and Tének in various anti-fracking activities. Against the backdrop of several centuries of gradual reduction of the vitality of the two languages, this new domain of their use is a surprising but very welcome development for language revitalization. Using insights from participant observation and interviews, I demonstrate that the motivation to use Indigenous languages was not only to facilitate communication, but also to strengthen the Indigenous regional identity as a tool for solidarity building and Indigenous resistance against damaging extraction projects. I also show that fracking is perceived as not only a threat to the environment but also to the native cultures of the region.
Explaining Gendered Vulnerability to Climate Change: The Contextual Conditions
Authors: Adeola Ogechi , Evans Olaniyi , Ngare Innocent
Published: December 2023

Undoubtedly, addressing the danger of extreme weather events is a major global concern. Questions regarding gender norms and women’s involvement in combating climate change have surfaced in the light of the growing attention. Currently, there is not enough information on how gender differences manifest in climate change, especially in Africa. This chapter explores how men and women experience distinct vulnerabilities to climate change due to existing inequalities, including their social roles, access to resources, and power relations, which can limit their ability to adapt to climate change impacts. Understanding the linkages between gender and climate change is increasingly essential for developing effective climate change policies and taking urgent actions to tackle the impacts of climate change, and for promoting gender equality and social justice in the face of this global challenge. By recognising and addressing the gendered dimensions of climate change, Africa can work towards a more equitable and sustainable future for all.
African Indigenous Knowledge and Climate Change Mitigation: Towards an Afro-Sensed Perspective
Authors: Adeola Ogechi , Evans Olaniyi , Ngare Innocent
Published: December 2023

Climate change is a widespread phenomenon characterised by a range of complex effects and, as a result, continues to generate considerable research interest. This chapter explores African indigenous knowledge as an alternative climate change mitigation approach. Specifically, local knowledge, perspectives, observations, and options of individuals affected by climate uncertainties are useful in gaining a broader understanding of climate change and practical mitigation strategies. A global paradigm shift from a market-based, individualistic approach is a necessity. Significantly, the application of the environmental ethics of Ubuntu, coupled with the effective incorporation of indigenous mitigation strategies, will facilitate the realisation of a green or environmentally sustainable Africa. In this light, the chapter echoes the need for an Afro-sensed perspective in climate change adaptation and mitigation.
Introduction: Matching Legal Proceedings to Problems in Custody Disputes
Authors: Kaldal Anna , Hellner Agnes , Mattsson Titti
Published: December 2023

The introductory chapter presents the aim, outline, and content of the anthology. First, it describes the dilemmas and challenges that arise in custody disputes, drawing on pre-existing empirical research, discussions among policymakers, and legal scholars. Second, the chapter outlines the child welfare family-law systems of the Nordic countries. It is also argued that the focus on gender equality and the awareness of domestic violence have affected law and policymaking—as well as created new dilemmas when handling custody disputes in practice. Third, the chapter presents the paradigm shift through which children’s rights have been strengthened, for example, the right of every child to freely express their views in all matters affecting them (Article 12, The United Nations Convention on the Rights of the Child). However, the right to participation raises demands for practical implementation that, so far, have not been fully met. It is proposed that the nature and complexity of custody disputes are serious challenges for society that call for an interdisciplinary and comparative discussion. Thus, the aim of the anthology is to transcend disciplinary, institutional, and jurisdictional boundaries, in search of new knowledge that can integrate multiple perspectives and experiences. The anthology will explore how legal proceedings, in and out-of-court, can be applied to the complex problems inherent in these disputes.
Children’s Participation and Perspectives in Family Disputes
Authors: Eriksson Maria
Published: December 2023

From a sociological perspective, this chapter discusses how agency interventions in the lives of children involved in family disputes, could become as child-centred and child-friendly as possible. It is divided into two parts, the first focusing on child health in family disputes, and the second on children’s participation and perspectives. The discussion sets out the results of several empirical studies of children in contact with family-law services and identifies implications for policy and practice. On a policy level, the author describes a need to dissolve boundaries between family-law proceedings and child welfare. To reach that objective in practice, the issue of children’s participation is connected to risk assessments and how best to communicate with children. The author explains how both the principle of care and the principle of participation can be simplified, then applied in practice, in order to contribute to the child’s sense of security and coherence. It is further argued that children’s participation can be enhanced, drawing on research of how best to communicate with them. Finally, the chapter explores children’s actions beyond participation, noting that, the children interviewed in one of the studies, emphasized their right to decide for themselves.
Challenges When Family Conflicts Meet the Law—A Proactive Approach
Authors: Barton Thomas D.
Published: December 2023

The final contributing chapter assumes that the effectiveness of addressing a social problem depends, in part, on the quality and appropriateness of the procedures used to address that problem. For the author, attributes of domestic relations problems—especially child custody issues—do not fit well with the capabilities of traditional legal procedures. However, this lack of fit between problem and procedure can be overcome and procedures improved. Using a proactive approach, the author identifies a need of acknowledging and incorporating different ways of speaking about domestic relations problems. He concludes that the legal system should supplement its traditional problem-solving methods with others, for example, the welfare system and psychology.
Introduction
Authors: Bigby Christine , Hough Alan
Published: December 2023

This book is about turning visionary policies about the rights of people with disabilities into reality in their everyday lives. It is a guide to knowledge for designing quality services and to the practices needed to deliver enabling support. The core argument of the book is that the quality of disability services and support rests on good practice—the moments of interaction between people with disabilities and services when knowledge is applied and principles become actions. Thus, we understand practice as conscious self-aware actions by support workers, managers or professionals where they apply knowledge, theories, principles and skills in real-life situations. Yet too often practice goes unnoticed and unmonitored, as paperwork—policies and procedures—dominates the attention of managers and expected practice remains abstract and ill defined.
Supporting Engagement in Everyday Life at Home and in the Community: Active Support
Authors: Bigby Christine
Published: December 2023

Many people with intellectual disabilities live in poor-quality supported accommodation services where they spend a significant part of their day disengaged—doing nothing. It is clear that it is the quality of staff support rather than the number of staff that makes the difference and that all people with intellectual disabilities can be engaged for much of their day. Engagement in meaningful activities and social interactions is a fundamental prerequisite to a good quality of life. When staff consistently use a practice known as Active Support, people with intellectual disabilities have higher levels of engagement and a better quality of life. This chapter lays out the essential elements of Active Support and the frontline managerial practices and organisational features necessary to embed it in services. Finally, it considers the connections between Active Support and other person-centred practices, such as support planning, positive behaviour support, and supported decision making.
Branched tyramides from males of the harvester ant, Pogonomyrmex badius
Authors: Jones Tappey H. , Chinta Satya P. , Vander Meer Robert K. , Cartwright Kaitie C.
Published: December 2023

Tyramides are produced in microgram quantities by males of species in the large Myrmicine ant sub-family (> 7000 species). Tyramides are transferred to female sexuals during mating where a specific female sexual evolved enzyme hydrolyzes the tyramides to the biogenic amine, tyramine. Tyramine is a ligand for receptors that rapidly activate reproductive development in the newly mated queen—previously reproductively inhibited by the mother queen. Without this elaborate biogenic amine precursor and co-evolved female sexual derived tyramide hydrolase, the defenseless newly mated queen’s worker production would be delayed by up to 6 days, which could be lethal to the new queen. This is one of possibly several ant species separation mechanisms evolved to maintain species integrity. Here we report two methyl-branched tyramides from harvester ant, Pogonomyrmex badius, males, including one highly branched tyramide not previously reported.