ArgumentIn the United States, scientific knowledge is brought before the courts by way of testimony – the testimony of scientific experts. We argue that this expertise is best understoodfirstas related to the quality of the underlying scienceand thenin terms of who delivers it. Bloodstain pattern analysis (BPA), a contemporary forensic science, serves as the vaulting point for our exploration of objectivity as a metric for the quality of a science in judicial contexts. We argue that BPA fails (...) to meet the minimal standard set by Helen Longino’s social-procedural account of objectivity (1990, 2002). In light of some pressing issues for social-procedural accounts, we offer an infrastructural account of objectivity. This account offers what amounts to a friendly amendment to Longino’s account and adds to the ways in which we might analyze social-procedural objectivity. Finally, we address an issue that is pressing in the legal context: given that scientific knowledge is delivered by individuals, not communities, at least in U.S. courts, we (may) need a way to evaluate individual scientific and epistemic agents. We suggest a means for making this evaluation that is derived from our infrastructural account of objectivity. (shrink)

Multivariate pattern analysis, or MVPA, has become one of the most popular analytic methods in cognitive neuroscience. Since its inception, MVPA has been heralded as offering much more than regular univariate analyses, for—we are told—it not only can tell us which brain regions are engaged while processing particular stimuli, but also which patterns of neural activity represent the categories the stimuli are selected from. We disagree, and in the current paper we offer four conceptual challenges to the use (...) of MVPA to make claims about neural representation. Our view is that the use of MVPA to make claims about neural representation is problematic. (shrink)

We present a technique for the analysis of pattern formation by a class of models for the formation of ocular dominance stripes in the striate cortex of some mammals. The method, which employs the adiabatic approximation to derive a set of ordinary differential equations for patterning modes, has been successfully applied to reaction-diffusion models for striped patterns [1]. Models of ocular dominance stripes have been studied [2,3] by computation, or by linearization of the model equations. These techniques do (...) not provide a rationale for the origin of the stripes. We show here that stripe formation is a non-linear property of the models. Our analysis indicates that stripe selection is closely linked to a property in the dynamics of the models which arises from a symmetry between ipsilateral and contralateral synapses to the visual cortex of a given hemisphere. (shrink)

We investigate the topological properties of scalar field configurations influenced by non-commutative geometry and time-dependent perturbations. Specifically, we analyze the connectedness of level sets of scalar fields, compute the fractal dimensions of generated patterns, and study the impact of varying non-commutative parameters. Utilizing numerical simulations, we provide evidence of topological bifurcations induced by non-commutative corrections. The analysis is framed within point set topology, and the results are formalized using the theorem-proof structure.

The creation of the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES) in 1973 has significantly altered the dynamics of trade in fauna and flora. Despite this effort, curbing of criminal trade in endangered species of wild fauna and flora has remained a key challenge for some countries. The objective of this study was to identify and establish the trafficking routes of illegal wildlife and forest products, analyzing the patterns and trends of wildlife and forest (...) crime including their drivers, actors and modus operandi, and assessing the criminal justice response including the legislative, enforcement, prosecutorial and judicial systems. The analysis was based on the methodologies and principles embedded in African environmental ethics. It was concluded that African ethics allows for ‘sustainable poaching’ under the framework of Eco-Afrocentricism; but condemns poaching done for trafficking purposes. Five canons of sustainability were developed to guide ‘sustainable poaching’. African capitalism thesis was used to support the analysis from political and economic perspectives. (shrink)

Background: Tuberculosis is among the major causes of illness and death worldwide especially in Asia. Smoking is associated with recurrent tuberculosis and its related mortality. Also, it could affect clinical manifestations, bacteriological conversion and outcome of treatment. This study aimed to evaluate the pattern of tobacco smoking, history of previous quit attempts and attitude towards quitting in tuberculosis patients. Materials and Methods: It was a cross-sectional study done amongst tuberculosis patients presented to DOTS corner of Rajshahi Medical College Hospital. (...) 315 patients entered the study as "First Come First Serve". Selfreported questionnaires were designed according to the standard questionnaires of smoking pattern. Results: Sixty one percent (61%) patients (n=192) were smoker before the diagnosis of tuberculosis. 51.1% were current smokers at the time of interview and were continuing smoking after the diagnosis of tuberculosis. Only 10.2% discontinued smoking after diagnosis. 68.2% smokes less than 10 cigarettes per day. 53.1% was between 31-50 age group. 21-30 is the commonest age group (62%) to start smoking is and 66.1% smoked less than 10 years before diagnosis. To reduce stress was the most common cause to continue smoking (48.9%). 71.9% smokers showed keen interest to stop smoking. Conclusion: Considering the prevalence of smoking in tuberculosis patients, evaluation of tobacco smoking status in such patients and motivating them to quit smoking could be considered as important steps in their treatment process. (shrink)

About thirty years ago, when the Internet started to be commercialised, access to the medium became a topic of research and debate. Up-to-date evidence about key predictors, such as age, is crucial because of the Internet's ever-changing nature and the challenges associated with gaining access to it. This paper aims to give an overview of New Zealand's Internet access trends and how they relate to age. It is based on secondary analysis of data from a larger online panel survey (...) with 1,001 adult respondents. The Chi-square test of independence and Cramer's V were used in the analysis. The study provides new evidence to understand the digital divide. Specifically, it uncovers a growing disparity in the quality of Internet connectivity. Even though fibre is the most common type of broadband connection at home, older adults are less likely to have it and more likely to use wireless broadband, which is a slower connection type. Additionally, a sizable majority of people in all age categories have favourable opinions on the Internet. Interestingly, this was more prevalent among older people, although they report an increased concern about the security of their personal information online. The implications of the results are discussed and some directions for future research are proposed. (shrink)

Introduction: There is a general agreement among previous studies that gender, merit and catchment area criteria allows for access to university education, but the pattern of these variables over the years has not been proven in these studies. Purpose: This study used a times series approach to evaluate the enrolment patterns in federally owned universities in South-South Zone, Nigeria, based on the gender, merit and catchment area criteria. Methodology: The descriptive survey design was adopted for this study. A purposive (...) sampling technique was adopted to choose three universities based on the generation of their establishment. The evaluation covered from 2010 to 2019 using stationary time-bound data collected from the academic planning units of the institutions through a checklist. Future enrolment forecasts were made to 2031 using the moving average forecasting technique. Results: A gender-based difference in enrolment, in favour of males was recorded between 2010 and 2019; there were notable fluctuations in the enrolment pattern based on the merit criterion from 2010 to 2019; the enrolment pattern in terms of the catchment area criterion was consistent from 2010 – 2019. In terms of the projection, it was predicted that enrolment at the aggregate level would rise continuously across federal universities, but not at the institutional level. more women than men are expected to be enrolled in academic programmes at federal institutions, while at the institutional level, gender-based enrolment can fluctuate. Recommendations/Classroom Implications: Based on these findings, implications are discussed for future enrolment decisions at both the institutional and national levels. (shrink)

The present study collected a larger set of three-dimensional data on human crania from the Kofun period (as well as from previous periods, i.e., the Jomon and Yayoi periods) in the Japanese archipelago (AD 250 to around 700) than previous studies. Three-dimensional geometric morphometrics were employed to investigate human migration patterns in finer-grained phases. These results are consistent with those of previous studies, although some new patterns were discovered. These patterns were interpreted in terms of demic diffusion, archaeological findings, and (...) historical evidence. In particular, the present results suggest the presence of a gradual geological cline throughout the Kofun period, although the middle period did not display such a cline. This discrepancy might reflect social changes in the middle Kofun period, such as the construction of keyhole-shaped mounds in the peripheral regions. The present study implies that a broader investigation with a larger sample of human crania is essential to elucidating macro-level cultural evolutionary processes. (shrink)

The Ukraine conflict has profoundly affected global trade and international relations, particularly for Germany, a major player in Europe and the European Union. This study utilizes a Gravity Model analysis to explore Germany’s trade network and assess the impact of the conflict on its trade partnerships.

Objectives The study aims to evaluate the impact of the Revised Health Insurance Law 2014 on the utilisation of outpatient and inpatient care services, healthcare services utilisation at different levels of providers, types of providers and types of visits across different entitlement groups. Design/setting Secondary data from two waves of the Vietnam Household Living Standard Survey (VHLSS) 2016, VHLSS 2014 were used. A cross-sectional study applying propensity score matching was conducted. Participants A total of 4900 individuals who reported using healthcare (...) services are analysed. Outcomes measure Numbers of outpatient and inpatient visits, frequency of healthcare service utilisation at commune health stations, district hospitals, provincial hospitals, public and private health facilities, number of visits at health facility for medical treatment and health checks per year. Results The result indicates that health insurance (HI) policy increased the number of outpatient visits for the enrolled between 0.87 and 1.29. The greatest impact was found on participants of heavily subsidised health insurance (HSHI) programmes with 1.29 visits per person per year. Similarly, an increase between 0.08 and 0.16 in the number of inpatient admissions was because of participation in HI. With regard to type of healthcare providers, the study found that participation in HI has the most effect on the use of healthcare services at district hospitals. However, the study demonstrated that the impacts of HI on the increase in the frequency of visiting commune health stations, number of visits at the provincial hospital for HSHI groups, and number of visits at health facilities for health check and consultation were sensitive to unobserved characteristics. Conclusion Our findings imply that policy-makers in Vietnam could continue expanding health insurance coverage to increase access to healthcare services for citizens, especially vulnerable groups. In addition, the government should draw more attention to primary healthcare level. (shrink)

Populism has become one of the most intensely discussed topics in both public debate and academic research. So far there has been no systematic argumentation theoretic analysis of populism, however. This paper is intended to provide first steps towards such an analysis by giving a full argumentation theoretic reconstruction of the political manifesto of the German right-wing populist party “Alternative for Germany” (AfD). This allows to draw preliminary conclusions about the AfD’s argumentative strategy as exemplary for right-wing populism.

Among philosophical analyses of Darwin’s Origin, a standard view says the theory presented there had no concrete observational consequences against which it might be checked. I challenge this idea with a new analysis of Darwin’s principal geographical distribution observations and how they connect to his common ancestry hypothesis.

Dredging operations are essential for maintaining navigable waterways, but determining the ideal time to dredge requires a multifaceted approach, incorporating both environmental and operational variables. This paper presents the Dredging Analysis and Decision Support System (DADSS), a data-driven solution that employs historical sedimentation data, weather patterns, and water flow statistics to optimize dredging decisions. The system leverages Random Forest Classifier and Regressor models to predict the need for dredging and estimate associated costs. Key inputs include sedimentation depth, water flow (...) rate, sediment type, and precipitation levels. By providing real-time insights and cost-effective guidance without reliance on physical sensors, this solution enhances waterway management efficiency while reducing environmental impact. Results demonstrate a clear optimization in dredging operations with a reduced frequency of unnecessary dredging. (shrink)

Climate Change is a long-term change in the statistical distribution of weather patterns over periods of time that range from decades to millions of years. It may be a change in the average weather conditions or a change in the distribution of weather events with respect to an average, for example, greater or fewer extreme weather events. It is of keen interest to identify climatological behaviour to discover spatial relationships in climate variables, so that the trend of the climatic changes (...) can be analyzed and studied. Data Mining is a technology that blends traditional data analysis methods with sophisticated algorithms for processing large volumes of data. It has also opened up exciting opportunities for exploring and analyzing new types of data and for analyzing old types of data in new ways. As Data Mining is an analytic process designed to explore data in search of consistent patterns and systematic relationships between variables and then to validate the findings by applying the detected patterns to new subsets of data, the present study has been conducted to apply various Data Mining techniques to the climatic data collected and to study the trend, pattern and finally to predict. (shrink)

This study focuses on developing a comprehensive sentiment analysis framework aimed at understanding sentiments expressed in social media posts, enhancing online reputation management for brands. Given the overwhelming volume of user-generated content across platforms, we instituted a methodical approach leveraging advanced machine learning techniques. Specifically, we used Python libraries such as TensorFlow for deep learning functionalities and PyTorch for natural language processing tasks. Our models classify sentiments into three categories: positive, negative, and neutral, while simultaneously analyzing trending patterns and (...) user opinions. The results demonstrate a significant classification accuracy, providing evidence for the framework’s efficacy in real-time social media monitoring. Ultimately, our findings emphasize the strategic role of sentiment analysis in improving brand reputation, enabling better consumer engagement, and informing marketing strategies. (shrink)

Reification is a standard technique in conceptual modeling, which consists of including in the domain of discourse entities that may otherwise be hidden or implicit. However, deciding what should be rei- fied is not always easy. Recent work on formal ontology offers us a simple answer: put in the domain of discourse those entities that are responsible for the (alleged) truth of our propositions. These are called truthmakers. Re-visiting previous work, we propose in this paper a systematic analysis of (...) truthmaking patterns for properties and relations based on the ontolog- ical nature of their truthmakers. Truthmaking patterns will be presented as generalization of reification patterns, accounting for the fact that, in some cases, we do not reify a property or a relationship directly, but we rather reify its truthmakers. (shrink)

Although the controversy between Malthus and Ricardo has long been considered to be an important source for the history of economic thought, it has hardly been the object of a careful study qua controversy, i.e. as a polemical dialogical exchange. We have undertaken to fill this gap, within the framework of a more ambitious project that places controversies at the center of an account of the history of ideas, in science and elsewhere. It is our contention that the dialogical co-text (...) is essential for reconstructing the meaning and the evolution of science. In the present paper we try to substantiate this contention by means of a pragma-rhetorical study of this particular controversy. First, we reconstruct, through an analysis of a chunk of the correspondence, a micro-level of specific moves and countermoves which constitute a sequential structure within which also meta-scientific and meta-controversial considerations play a role. We then move to a macro-level of analysis, looking for recurrent patterns of argumentation. Finally, we draw epistemological conclusions on the nature of rationality and progress as manifested in actual scientific controversies. (shrink)

Recent studies tend to explain the importance of communication in the organisation as well as prescribing the most commonly practised techniques adopted by school managers. Studies on financial management are quite limited with the available ones suggesting that poor financial management is a source of conflict between school leaders and host communities. Little seems to be known on the connection between principals’ communication patterns and funds’ management as predictors of school-community relationship. This study builds on existing studies and appears to (...) be the first to assess the linkages between principals’ communication patterns, fund management practices and school- community relationship based on empirical rather than subjective data. A structural modelling approach was adopted to examine the nexus using quantitative primary data obtained from a random sample of 2108 respondents. A questionnaire which was designed and validated by the researchers served as the data collection device. Collected data were subjected to Exploratory and Confirmatory Factor Analyses, as well as Multiple Regression Analysis. Findings revealed various significant communication, funds management and school-community relationship practices that are available for adoption. However, it was found that the extent to which principals utilised such practices were below expected minimum standards. It was also found that there were no significant partial and composite effects of principals’ communication and funds management practices on school-community relationship (SCR). Based on these results, relevant theoretical, policy and practical implications are discussed. (shrink)

The "Malware App Detection System" project enhances mobile security by detecting malicious apps through machine learning (ML) analysis of app behaviours. It examines behaviours like system calls (requests apps make to the operating system), permissions (levels of access apps have), and network connections (internet interactions). This focus on behaviour, rather than relying on specific malware signatures, enables the system to identify both known and new threats. The detection system is built using a dataset of both benign (harmless) and malicious (...) apps, with each app’s behaviour categorized and labelled. By analysing system calls, the system identifies unusual requests, which may indicate malicious intent. Permissions are also reviewed, as apps that seek abnormal access levels, like to contacts or storage, might have harmful intentions. Network connections are monitored to detect suspicious activities, such as connections to unauthorized servers, which could indicate data theft. To achieve this, ML models like Random Forest are trained on these behaviour patterns, learning to distinguish between safe and harmful apps. Once deployed, the system provides real-time detection, alerting users if it finds potentially dangerous activities. This proactive, behaviour-based approach protects users from unauthorized access and data leaks, adapting to new malware types as they arise. In doing so, the project offers a flexible and effective solution to the evolving challenges of mobile security. (shrink)

Network analysis as a tool for ecological interactions studies has been widely used since last decade. However, there are few studies on the factors that shape network patterns in communities. In this sense, we compared the topological properties of the interaction network between flower-visiting social wasps and plants in two distinct phytophysiognomies in a Brazilian savanna (Riparian Forest and Rocky Grassland). Results showed that the landscapes differed in species richness and composition, and also the interaction networks between wasps and (...) plants had different patterns. The network was more complex in the Riparian Forest, with a larger number of species and individuals and a greater amount of connections between them. The network specialization degree was more generalist in the Riparian Forest than in the Rocky Grassland. This result was corroborated by means of the nestedness index. In both networks was found asymmetry, with a large number of wasps per plant species. In general aspects, most wasps had low niche amplitude, visiting from one to three plant species. Our results suggest that differences in structural complexity of the environment directly influence the structure of the interaction network between flower-visiting social wasps and plants. (shrink)

This paper proposes an analysis of statements about universals according to which such statements assert nothing more than that the evidence we’d take to confirm them obtains, where this evidence is understood to consist solely of patterns in the behavior of particulars that cannot be explained by other regularities in the way things behave. On this analysis, to say that a universal exists is simply to say that there is such a pattern in the behavior of certain (...) particulars, and for any predicate F that is presumed to correspond to a universal, to say that a particular is F is simply to say that its behavior exhibits a pattern of this sort. I argue that there is no theoretical work that we want postulations and ascriptions of universals to do that they’d be unfit for if analyzed in this way, and consequently that there is no reason to treat such statements as asserting anything more than what the proposed analysis suggests. (shrink)

In this study, we analyzed the blinking behavior of players in a video game tournament. Our aim was to test whether spontaneous blink patterns differ across levels of expertise. We used blink rate, blink duration, blink frequency, and eyelid movements represented by the Eye Aspect Ratio (EAR) to train a machine learning classifier to discriminate between different levels of expertise. Classifier performance was highly influenced by features such as the mean, standard deviation and median EAR. Moreover, further analysis suggests (...) that blinking rate and blink duration are likely to increase along with the level of expertise. We speculate this may be indicative of a reduction in cognitive load and lowered stress of expert players. In general, our results suggest that EAR and blink patterns can be used to identify different levels of expertise of video game players. (shrink)

Despite the various criteria presented in the literature, most authors engaged in the debate about emergence agree on a fundamental distinction between strong/ontologically robust cases of emergence and weak/metaphysically innocent ones. The former typically involve entities that exhibit new causal capacities, while the latter are primarily associated with deductive unpredictability, conceptual novelty, and other qualities that highlight our epistemic limitations in understanding them. In this paper, I initially examine a paradigmatic example of weak emergence, namely the higher-level patterns generated by (...) virtual Cellular Automata (CAs) as analysed by Mark Bedau. Then, I demonstrate that the same mechanism can be observed in real biological systems, such as the dynamics governing the pigmentation ontogeny of the ocellated lizard (Timon lepidus). Unlike virtual CAs, however, real CAs produce patterns that seem to perform non-reducible functions. Therefore, I propose that despite the similarities between virtual and real CAs, the pigmentation pattern of the ocellated lizard should be regarded as a case of strong emergence. Moreover, I suggest that this analysis may shed light on the nature of biological emergent entities in general. Finally, the paper includes an Addendum introducing an issue that, while not exhaustively addressed here, is highly relevant: how to metaphysically conceptualise the causal efficacy exhibited by the pigmentation patterns. (shrink)

Throughout history, a relatively small number of individuals have made a profound and lasting impact on science and society. Despite long-standing, multi-disciplinary interests in understanding careers of elite scientists, there have been limited attempts for a quantitative, career-level analysis. Here, we leverage a comprehensive dataset we assembled, allowing us to trace the entire career histories of nearly all Nobel laureates in physics, chemistry, and physiology or medicine over the past century. We find that, although Nobel laureates were energetic producers (...) from the outset, producing works that garner unusually high impact, their careers before winning the prize follow relatively similar patterns as ordinary scientists, being characterized by hot streaks and increasing reliance on collaborations. We also uncovered notable variations along their careers, often associated with the Nobel prize, including shifting coauthorship structure in the prize-winning work, and a significant but temporary dip in the impact of work they produce after winning the Nobel. Together, these results document quantitative patterns governing the careers of scientific elites, offering an empirical basis for a deeper understanding of the hallmarks of exceptional careers in science. (shrink)

This study analyzed consumers' preferences for local textiles, specifically Tie-dye and Batik, in the Itoku Local Government Area of Ogun State, Nigeria. Itoku markets were purposefully selected due to their high sales of Adire and Batik. One hundred and fifty respondents were randomly selected from two markets in Itoku. Data was collected through a structured questionnaire and analyzed using descriptive statistics such as means. T-test was used to analyze differences in preference between tie-dye and batik. The results (t = -7.97, (...) P = 0.003) showed a significant difference in consumers' attitudes towards tie-dye and batik. It was also found that the factors influencing consumers' preferences significantly affected both Adire and Batik (t = -4.11, P = 0.001). Further analysis revealed that there was no significant difference in the factors responsible for consumers' preferences between tie-dye and batik (t = 0.008, P = 0.940). Thus, a good number of the respondents preferred tie-dye to batik, just as there were a good number of them who also preferred batik to tie-dye, regardless of factors such as aesthetic values, design patterns, color combinations, durability, attractiveness, production cost, and selling prices. (shrink)

Abstract Introduction Logically valid deductive arguments are clear examples of abstract recursive computational proce‐ dures on propositions or on probabilities. However, it is not known if the cortical time‐consuming inferential pro‐ cesses in which logical arguments are eventually realized in the brain are in fact physically different from other kinds of inferential processes. Methods In order to determine whether an electrical EEG discernible pattern of logical deduction exists or not, a new experimental paradigm is proposed contrasting logically valid and (...) invalid inferences with exactly the same content (same premises and same relational variables) and distinct logical complexity (propositional truth‐functional operators). Electroencephalographic signals from 19 subjects (24.2 ± 3.3 years) were acquired in a two‐condition para‐ digm (100 trials for each condition). After the initial general analysis, a trial‐by‐trial approach in beta‐2 band allowed to uncover not only evoked but also phase asynchronous activity between trials. Results showed that (i) deductive inferences with the same content evoked the same response pattern in logically valid and invalid conditions, (ii) mean response time in logically valid inferences is 61.54% higher, (iii) logically valid inferences are subjected to an early (400 ms) and a late reprocessing (600 ms) verified by two distinct beta‐2 activa‐ tions (p‐value < 0,01, Wilcoxon signed rank test). Conclusion We found evidence of a subtle but measurable electrical trait of logical validity. Results put forward the hypothesis that some logically valid deductions are recursive or computational cortical events. Keywords Beta‐2 band, Evoked potentials, Induced potentials, Deductive inference, Logical validity, Cortical bases of logical reasoning. (shrink)

The rapid advancements in healthcare technologies have resulted in an enormous increase in biomedical data, creating the need for innovative approaches to harness this information for early disease detection. Big Data Analytics (BDA) combined with Artificial Intelligence (AI) offers unprecedented opportunities to analyze complex biomedical signal patterns and predict the onset of diseases at an early stage. The application of AI techniques like machine learning and deep learning in conjunction with BDA allows for the detection of subtle patterns in large (...) datasets that might be missed by conventional diagnostic methods. This paper explores the integration of Big Data Analytics and AI for early disease detection through the analysis of biomedical signal patterns, such as electrocardiograms (ECG), electroencephalograms (EEG), and wearable sensor data. AI algorithms, trained on vast datasets, can recognize early warning signals of various diseases such as cardiovascular disorders, neurodegenerative diseases, and respiratory conditions. The ability to analyze these signals in real time enables early intervention, potentially improving patient outcomes and reducing healthcare costs. A comprehensive literature review highlights the use of BDA and AI in biomedical applications and the challenges associated with data volume, quality, and heterogeneity. We propose a system methodology that combines AI models with real-time Big Data Analytics to process biomedical signals efficiently and accurately. The proposed system leverages AI for feature extraction and classification while utilizing Big Data tools to handle the massive influx of data from biomedical devices and sensors. This approach not only enhances diagnostic precision but also paves the way for personalized healthcare solutions. (shrink)

Emotional creativity (EC) is a pattern of cognitive abilities and personality traits related to originality and appropriateness in emotional experience. EC has been found to be related to various constructs across different fields of psychology during the past 30 years, but a comprehensive examination of previous research is still lacking. The goal of this review is to explore the reliability of use of the Emotional Creativity Inventory (ECI) across studies, to test gender differences and to compare levels of EC (...) in different countries. Thirty-five empirical studies focused on EC were retrieved and the coefficients required for the meta-analysis extracted. The meta-analysis revealed that women showed significantly higher EC than men (total N = 3,555). The same gender differences were also found when testing scores from three ECI subscales, i.e. emotional novelty, emotional preparedness and emotional effectiveness/authenticity. When comparing EC in 10 different countries (total N = 4,375), several cross-cultural differences were revealed. The Chinese sample showed a significantly lower average ECI total score than all the other countries. Based on the integration of results, the avenues for future research on EC and the breadth of influence of the concept of EC across different fields of psychology are discussed. Keywords: Emotional Creativity, Review, Meta-Analyses, Meta-Analysis, Definition, Emotional Creativity Inventory, ECI, Reliability, Gender Differences, Cross-cultural, Cross-culture, Personality Traits, NEO Personality Inventory, Big Five, Extraversion, Agreeableness, Openness to Experience, Introversion, Neuroticism, Emotions, Creativity, Cognition, Cognitive Abilities, Affect, Fantasy, Coping, Alexithymia, Anhedonia, Self-understanding, Motivation, Creativeness, Innovative Performance, Creative Ability, Artistic Creativity, Creative Thinking. MeSH Headings: Emotions, Creativity, Affect, Affective Symptoms, Gender, Sex, Gender Identity, Cross-Cultural Comparison, Transcultural Studies, Temperament, Extraversion, Neuroticism, Anhedonia, Creativeness, Cognition, Cognitive Function, Artistic Creativity, Creative Ability, Creative Thinking. (shrink)

Fraudulent activities in insurance claims have become a significant challenge for the insurance industry, leading to substantial financial losses annually. This project, titled "Fraud Detection and Analysis for Insurance Claim using Machine Learning" aims to develop a robust and an efficient system to identify and analyze fraudulent claims. The system leverages machine learning techniques to analyze patterns, anomalies, and inconsistencies in claim data, enabling early detection of potentially fraudulent activities.

Family has always been an important unit of analysis in an effort to improve and understand human development. Studying the changes in the institution of family and households keeping in view the demographic, social, and economic transitions also becomes imperative. So far, in our knowledge, there are very few studies based in India have investigated the household size and family formation patterns, while a few of them have looked into its possible causes or associations and demographic, economic, and social (...) repercussions. In particular, as per our knowledge, there is no evidence on who is losing and who is gaining among family members due to the unprecedented transition in family forms in India. This paper serves a twofold purpose as first it seeks to explore and enrich the field of family demography in India by studying the existing evidence in the field as well as allied fields to understand how family serves as the nuclei directing individuals and communities toward certain behaviors and choices which consequently translate into larger social, economic and demographic transitions. Second, it also discusses the missing links and scope in the field of family demography in India as compared to the developed societies to provide future research prospects in this area. (shrink)

Text classification is one of the most important task in natural language processing, In this research, we carried out several experimental research on three (3) of the most popular Text classification NLP classifier in Convolutional Neural Network (CNN), Multinomial Naive Bayes (MNB), and Support Vector Machine (SVN). In the presence of enough training data, Deep Learning CNN work best in all parameters for evaluation with 77% accuracy, followed by SVM with accuracy of 76%, and multinomial Bayes with least performance of (...) 69% accuracy. CNN has the best performance in the presence of large enough training dataset because of the presence of filter/ kernels which help to indentify patterns in text data regardless of their position in the sentence. We repeated the training again with just one-third of our data, at this point SVM comes with the best performance, the performance of CNN noticeably drops but still better than Multinomial Naive Bayes, the reason why SVM works best when we reduce the training data was because of its ability to look for a hyper-plane that creates a boundary between different classes of data so as to properly classify them, so we believed that getting the hyper-plane was more efficient when we reduce the dataset, hence reason for the good performance. Multinomial Naive Bayes have the least performance which we attributed to its assumption of independency between the features which sometimes does not hold true. We concluded that availability of data should be an important factor when choosing classifier for Natural Language Processing Text Classification task. CNN should be use in the presence of enough dataset, and SVM should be use when data is not enough. Multinomial Naive Bayes must not be trusted with state of the art NLP task due to its assumption of independency between the features . (shrink)

Presently, there is a lack of psychological and quantitative studies in Singapore about discriminatory attitudes. This paper aimed to contribute to this aspect. However, to examine actual behavior can be difficult due to the sensitive nature of the needed data. Hence, this study approached discrimination at an attitudinal level. Six vulnerable groups were examined in this study. They consisted of people of a different race, immigrants or foreign workers, homosexuals, people living with HIV/AIDS, people of a different religion, and unmarried (...) couples living together. Two research questions were posed: 1) What is the prevalence of having discriminatory attitude toward vulnerable groups? and 2) What are the predictors of these discriminatory attitudes? Using a sample population of 1,972 Singaporeans, descriptive analysis and binomial logistic regression analysis were conducted. Firstly, based on the results, the prevalence ranged between 10.76% to 42.46%. Singaporeans have discriminatory attitude toward vulnerable groups who can be categorized into two: the least discriminated (three groups ranging between 10.76% to 15.48%) and the highly discriminated (three groups ranging between 30.86% to 42.46%). Secondly, binomial logistic regression showed support for several significant predictors such as emphasis on the importance of religion and tradition, and employment status, depending on the model assessed. However, one pattern was observed in all the models, that a person who discriminates one group is more likely to discriminate another group. The findings were then discussed and explained within the context of Singapore. (shrink)

nanological gates, in order to design nano-scale computers with dual-scale capabilities. All living biological systems function due to the molecular interactions of different subsystems. Molecular components (proteins and nucleic acids, lipids and carbohydrates, DNA and RNA) can be used as an inspirational strategy on how to design high-performance NEMS and MEMS that have the required features and characteristics. Considered. In addition, analytical and numerical methods are available for dynamic analysis and three-dimensional geometry, bonding and other properties of atoms and (...) molecules. Thus, electromagnetic and mechanical, and other physical and chemical properties can be studied. Nanostructures and nanosystems can be widely used in medicine and health. Possible applications of nanotechnology include: drug synthesis and drug delivery (therapeutic potential is greatly increased due to the effective direct delivery of new types of drugs to specific sites in the body), nanosurgery and nanotherapy Synthesis and detection of genomes, nano-scale stimuli and sensors (diagnosis and prevention of disease), design and implantation of non-rejection artificial organs and design of high performance nanomaterials. It is important that these technologies change the manufacture of materials, devices and systems. (shrink)

It is tempting to always try to distinguish convincing from poor literary imitation by micro-analysis. The analysis observes various patterns of word and punctuation use in the original and compares those with the imitation. I argue that no such sophistication is needed when faced with Max Beerbohm’s imitation of Joseph Conrad.

In recent years, neuroscience has begun to transform itself into a “big data” enterprise with the importation of computational and statistical techniques from machine learning and informatics. In addition to their translational applications such as brain-computer interfaces and early diagnosis of neuropathology, these tools promise to advance new solutions to longstanding theoretical quandaries. Here I critically assess whether these promises will pay off, focusing on the application of multivariate pattern analysis (MVPA) to the problem of reverse inference. I (...) argue that MVPA does not inherently provide a new answer to classical worries about reverse inference, and that the method faces pervasive interpretive problems of its own. Further, the epistemic setting of MVPA and other decoding methods contributes to a potentially worrisome shift towards prediction and away from explanation in fundamental neuroscience. (shrink)

Writing strategic documents is a major practice of many actors striving to see their educational ideas realised in the curriculum. In these documents, arguments are systematically developed to create the legitimacy of a new educational goal and competence to make claims about it. Through a qualitative analysis of the writing strategies used in these texts, I show how two of the main actors in the Czech educational discourse have developed a proof that a new educational goal is needed. I (...) draw on the connection of the relational approach in the sociology of education with Lyotard’s analytical semantics of instances in the event. The comparison of the writing strategies in the two documents reveals differences in the formation of a particular pattern of justification. In one case the texts function as a herald of pure reality, and in the other case as a messenger of other witnesses. This reveals different regimens of proof, although both of them were written as prescriptive directives – normative models of the educational world. (shrink)

The evaluation of universities from different perspectives is important for their scientific development. Analyzing the scientific papers of a university under the bibliometric approach is one main evaluative approach. The aim of this study was to conduct a bibliometric analysis and visualization of papers published by Hamadan University of Medical Science (HUMS), Iran, during 1992-2018. This study used bibliometric and visualization techniques. Scopus database was used for data collection. 3753 papers were retrieved by applying Affiliation Search in Scopus advanced (...) search section. Excel and VOSviewer software packages were used for data analysis and bibliometric indicator extraction. An increasing trend was seen in the numbers of HUMS's published papers and received citations. The highest rate of collaboration in national level was with Tehran University of Medical Sciences. Internationally, HUMS's researchers had the highest collaboration with the authors from the United States, the United Kingdom and Switzerland, respectively. All highly-cited papers were published in high level Q1 journals. Term clustering demonstrated four main clusters: epidemiological studies, laboratory studies, pharmacological studies, and microbiological studies. The results of this study can be beneficial to the policy-makers of this university. In addition, researchers and bibliometricians can use this study as a pattern for studying and visualizing the bibliometric indicators of other universities and research institutions. (shrink)

This study aimed to investigate the longitudinal trends in mathematical competencies of Grade 8 students in a public high school located in Zamboanga del Sur, Philippines. The study collected data over a period of six academic years, allowing for a comprehensive analysis of students' performance in 16 distinct mathematical competences of basic education curriculum. These topics include, but are not limited to, special products and factors, factoring, and basic concepts of probability. Using a quantitative research design, the study analyzed (...) both numerical and secondary data to identify patterns or trends in students' mathematical competencies. Trends were analyzed through regression analysis using slopes. The significance of these trends was then evaluated using t-tests for the standard error of slopes. The statistical analysis revealed significant upward trends in certain mathematical topics, indicating an improvement in the students' competencies over the six academic years. However, certain topics displayed downward or stable trends, indicating areas for improvement in the teaching methods used for these topics. The study highlights the importance of flexible and adaptable approaches to mathematics education. It emphasizes the need for constant evaluation and improvement of teaching methods to enhance student learning outcomes. The findings of this study provide valuable insights for educators and policymakers to guide evidence-based decision-making and improve the quality of mathematics education in the new normal setup. Implications and future research directions are incorporated in the study. (shrink)

Overcoming Bias in Analysis and Decision-Making: Effective Psychological Techniques -/- Bias is a fundamental challenge in human thinking, affecting both individual and collective decision-making. It distorts our perceptions, limits rational analysis, and leads to poor choices. Overcoming bias requires a structured approach that integrates cognitive debiasing techniques, analytical thinking strategies, emotional regulation, decision-making frameworks, and data-driven methodologies. This essay explores these psychological techniques in detail, providing a comprehensive guide to improving judgment and decision-making. -/- Cognitive Debiasing Techniques -/- (...) Cognitive biases are mental shortcuts that influence our thinking and decision-making. To counter these biases, we must first recognize them and actively work to minimize their impact. -/- Awareness and Reflection -/- The first step in overcoming bias is recognizing that it exists. Awareness enables individuals to question their assumptions and consider alternative viewpoints. Reflection involves self-examination through questions such as: -/- Why do I believe this? -/- What if I am wrong? -/- Am I considering all perspectives? -/- Keeping a “bias journal” where instances of biased thinking are recorded can help individuals track patterns and improve their critical thinking skills. -/- Perspective-Taking -/- Perspective-taking is the practice of viewing a situation from different viewpoints, particularly from those who hold opposing beliefs. This method is effective in reducing confirmation bias—the tendency to favor information that supports our existing views. To implement perspective-taking, one should ask: -/- How would a scientist, historian, or someone from another culture interpret this issue? -/- What would someone with the opposite viewpoint say? -/- By expanding the scope of analysis, this technique allows for more balanced decision-making. -/- Devil’s Advocate Method -/- The devil’s advocate method involves intentionally arguing against one’s own position to uncover weaknesses in reasoning. This technique prevents groupthink, where individuals conform to the majority opinion without critical evaluation. It encourages intellectual humility and enhances the ability to recognize flaws in logic. Encouraging another person to play the devil’s advocate role can further strengthen decision-making. -/- Analytical Thinking Strategies -/- Analytical thinking strategies help break down problems systematically and ensure that decisions are based on logic rather than intuition. -/- Bayesian Thinking -/- Bayesian thinking involves updating beliefs based on new evidence rather than clinging to initial assumptions. Many individuals fall into the anchoring bias, where they give too much weight to first impressions. Bayesian reasoning teaches that beliefs should be flexible, constantly adjusting as new data emerges. -/- For example, if someone assumes that a new business will succeed but later receives data suggesting otherwise, Bayesian thinking encourages revising the initial expectation rather than dismissing the data. -/- Falsification Principle (Karl Popper’s Method) -/- Instead of looking for evidence that confirms a belief, the falsification principle emphasizes seeking evidence that could disprove it. This approach is crucial for reducing confirmation bias. -/- For instance, rather than only reading studies that support a particular political stance, individuals should actively search for research that contradicts their position. If a belief cannot be disproven under scrutiny, it becomes more reliable. -/- Red Team-Blue Team Analysis -/- Used in intelligence agencies and businesses, the Red Team-Blue Team strategy is a structured method where one team (Red) creates a plan or argument, and another team (Blue) challenges it. This structured opposition ensures that biases and weak points are identified before a final decision is made. -/- This technique is particularly useful in high-stakes decision-making, as it uncovers potential blind spots and prevents bias blind spots—the tendency to recognize bias in others but not in oneself. -/- Emotional and Psychological Regulation -/- Biases are often driven by emotions rather than facts. Managing emotions effectively is key to clear and objective thinking. -/- Mindfulness and Metacognition -/- Mindfulness involves staying present and observing thoughts without judgment. Metacognition is the ability to think about one’s own thinking process. These techniques help individuals recognize when they are making emotional, rather than rational, decisions. -/- For example, loss aversion bias causes people to fear losses more than they value equivalent gains. Mindfulness allows individuals to step back and assess whether their fear of loss is clouding their judgment. -/- Cognitive Reframing -/- Cognitive reframing involves changing the way one interprets a situation. This technique is useful in overcoming negativity bias, where individuals focus on negative experiences more than positive ones. -/- For example, instead of thinking, I failed my exam, so I am not smart, a person can reframe it as, This was a learning opportunity to improve my study methods. This shift in perspective fosters resilience and better decision-making. -/- Decision-Making Frameworks -/- Structured decision-making frameworks help reduce reliance on gut instincts and emotional biases. -/- Pros and Cons List -/- A simple yet effective technique, the pros and cons list forces objectivity by weighing the advantages and disadvantages of a decision. It helps differentiate between emotional reasoning and logical analysis. -/- Six Thinking Hats (Edward de Bono) -/- This framework encourages examining decisions from multiple perspectives by assigning different “hats” to different ways of thinking: -/- White Hat: Focus on facts and data. -/- Red Hat: Consider emotions and intuition. -/- Black Hat: Identify potential risks and problems. -/- Yellow Hat: Look for benefits and opportunities. -/- Green Hat: Think creatively and explore alternatives. -/- Blue Hat: Oversee the thinking process and maintain control. -/- This structured method ensures a comprehensive evaluation, preventing tunnel vision and overly emotional decisions. -/- Pre-Mortem Analysis -/- A pre-mortem is a mental exercise where individuals assume that a decision has already failed and then work backward to identify potential mistakes. -/- For example, if a company is launching a product, a pre-mortem would involve asking, What would cause this launch to fail? This technique prevents overconfidence bias and planning fallacy (underestimating risks). -/- Data-Driven Decision Making -/- Decisions should be based on empirical evidence rather than intuition. -/- Statistical Thinking -/- Many biases arise from relying on anecdotal evidence instead of statistical data. Statistical thinking involves analyzing patterns and probabilities rather than personal experiences or gut feelings. -/- For example, rather than assuming a hiring decision will succeed, checking historical hiring success rates in similar cases ensures more accurate predictions. -/- Double-Blind Analysis -/- In scientific research, double-blind analysis prevents bias by ensuring that neither the experimenter nor the participants know the expected outcome. -/- This approach can be applied in business and policy decisions by ensuring analysts review data without prior expectations, reducing observer bias and selection bias. -/- Conclusion -/- Bias is an inevitable part of human cognition, but it can be managed with the right psychological and analytical techniques. By implementing cognitive debiasing strategies, structured analytical thinking, emotional regulation, decision-making frameworks, and data-driven methodologies, individuals and organizations can make more rational, objective, and effective decisions. -/- These techniques not only improve personal decision-making but also enhance leadership, governance, and problem-solving in society. In an era of increasing information overload and misinformation, mastering these strategies is essential for sound reasoning and ethical decision-making. -/- . (shrink)

Community detection is a major issue in network analysis. This paper combines a socio-historical approach with an experimental reconstruction of programs to investigate the early automation of clique detection algorithms, which remains one of the unsolved NP-complete problems today. The research led by the archaeologist Jean-Claude Gardin from the 1950s on non-numerical information and graph analysis is retraced to demonstrate the early contributions of social sciences and humanities. The limited recognition and reception of Gardin's innovative computer application to (...) the humanities are addressed through two factors, in addition to the effects of historiography and bibliographies on the recording, discoverability, and reuse of scientific productions: (1) funding policies, evidenced by the transfer of research effort on graph applications from temporary interdisciplinary spaces to disciplinary organizations related to the then-emerging field of computer science; and (2) the erratic careers of algorithms, in which efficiency, flaws, corrections, and authors’ status, were determining factors. (shrink)

With the previous technical reports, we presented the main insights from the qualitative analysis of the reflection of the mathematical dimension of gambling in gambling-related sites, in its structural, linguistic, epistemic, and informative aspects. In this report we will focus on the factors responsible for the patterns that the content of the gambling-related sites exhibit and the way that the mathematical dimension of gambling is reflected in this content, namely the factors that influence the content policies of these sites. (...) The report will also point to further directions of research-for both this project and for other investigators-for finding the appropriate balance and relation between the commercial policies on the one hand, and the adequacy and ethics of the content on the other hand. (shrink)

Students do not necessarily use the definitions presented to them when determining examples or non-examples of given mathematical ideas. Instead, they utilize the concept image they carry with them as a result of experiences with such examples and nonexamples. Hence, teachers should try exploring students‟ images of various mathematical concepts in order to improve communication between students and teachers. This suggestion can be addressed through error analysis. This study therefore is a descriptive-qualitative type that looked into the errors committed (...) by senior high school students in dealing with mathematical functions, explored the underlying reasons for such errors, and provided recommendations on how students could learn to manage their errors and how teachers could realize how to manage students‟ errors. Initial findings showed that the students generally demonstrated mathematical, logical and strategic errors. Mathematical error was generally exhibited in their inability to use properties and operations properly. Logical error was exhibited in their false arguments, rearranging concepts, improper classifications, arguing cyclically, and using equivalent transforms. Strategic error was manifested in their not being able to distinguish patterns, lack of integral concept, and not being able to transform a word problem into symbols. Errors prevailed despite the students‟ positive view and confidence in mathematics not only because of poor image concepts but because of lack of exposure to certain important mathematical tasks. Further investigation on the other sources of these errors is therefore necessary. (shrink)

The current report presents results of the qualitative analysis of the usage of the key math terms in the content of the reviewed websites in the current sample, with emphasis on the necessary distinctions for the word and concept of ‘odds’. Patterns, motivations, conceptual and contextual aspects of the usage are discussed. The theoretical norms of adequacy of this usage in the context of gambling are briefly presented. -/- Technical report of the research project 'Reflection of the mathematical dimension (...) of gambling in iGaming online content - A qualitative analysis'. (shrink)

AI-powered records science is revolutionizing the way facts are analyzed and understood. It can significantly improve the exceptional of information evaluation and boost its speed. AI-powered facts technological know-how enables access to more extensive, extra complicated information sets, faster insights, faster trouble solving, and higher choice making. Using the use of AI-powered information technological know-how techniques and tools, organizations can provide more accurate outcomes with shorter times to choices. AI-powered facts technology also offers more correct predictions of activities and developments (...) and superior accuracy in sample reputation.Furthermore, AI-powered facts science techniques can help agencies discover anomalies in datasets, learn new patterns, and better understand the points. This paper discusses the advantages of AI-powered statistics science and how it may enhance data analysis. It additionally discusses a number of the challenges going through organizations in imposing AI-powered records science projects and gives excellent practices for deploying and coping with records technology projects. (shrink)

Background: Smart sensors have been developed as diagnostic tools for rehabilitation to cover an increasing number of geriatric patients. They promise to enable an objective assessment of complex movement patterns. -/- Objective: This research aimed to identify and analyze the conflicting ethical values associated with smart sensors in geriatric rehabilitation and provide ethical guidance on the best use of smart sensors to all stakeholders, including technology developers, health professionals, patients, and health authorities. -/- Methods: On the basis of a systematic (...) literature search of the scientific databases PubMed and ScienceDirect, we conducted a qualitative document analysis to identify evidence-based practical implications of ethical relevance. We included 33 articles in the analysis. The practical implications were extracted inductively. Finally, we carried out an ethical analysis based on the 4 principles of biomedical ethics: autonomy, beneficence, nonmaleficence, and justice. The results are reported in categories based on these 4 principles. -/- Results: We identified 8 conflicting aims for using smart sensors. Gains in autonomy come at the cost of patient privacy. Smart sensors at home increase the independence of patients but may reduce social interactions. Independent measurements performed by patients may result in lower diagnostic accuracy. Although smart sensors could provide cost-effective and high-quality diagnostics for most patients, minorities could end up with suboptimal treatment owing to their underrepresentation in training data and studies. This could lead to algorithmic biases that would not be recognized by medical professionals when treating patients. -/- Conclusions: The application of smart sensors has the potential to improve the rehabilitation of geriatric patients in several ways. It is important that patients do not have to choose between autonomy and privacy and are well informed about the insights that can be gained from the data. Smart sensors should support and not replace interactions with medical professionals. Patients and medical professionals should be educated about the correct application and the limitations of smart sensors. Smart sensors should include an adequate representation of minorities in their training data and should be covered by health insurance to guarantee fair access. (shrink)

The right temporo-parietal junction (rTPJ) has been associated with two apparently disparate functional roles: in attention and in social cognition. According to one account, the rTPJ initiates a “circuit-breaking” signal that interrupts ongoing attentional processes, effectively reorienting attention. It is argued this primary function of the rTPJ has been extended beyond attention, through a process of evolutionarily cooption, to play a role in social cognition. We propose an alternative account, according to which the capacity for social cognition depends on a (...) network which is both distinct from and in tension with brain areas involved in focused attention and target detection: the default mode network. Theory characterizing the rTPJ based on the area’s purported role in reorienting may be falsely guided by the co-occurrence of two distinct effects in contiguous regions: activation of the supramarginal gyrus (SMG), associated with its functional role in target detection; and the transient release, during spatial reorienting, of suppression of the angular gyrus (AG) associated with focused attention. Findings based on meta-analysis and resting functional connectivity are presented which support this alternative account. We find distinct regions, possessing anti-correlated patterns of resting connectivity, associated with social reasoning (AG) and target detection (SMG) at the rTPJ. The locus for reorienting was spatially intermediate between the AG and SMG and showed a pattern of connectivity with similarities to social reasoning and target detection seeds. These findings highlight a general methodological concern for brain imaging. Given evidence that certain tasks not only activate some areas but also suppress activity in other areas, it is suggested that researchers need to distinguish two distinct putative mechanisms, either of which may produce an increase in activity in a brain area: functional engagement in the task versus release of suppression. (shrink)

The present research compares the efficiency of AI-based user behavior analysis to conventional security mechanisms in cloud environments. It specifically tests their precision, velocity, and predictive capacity for identifying and acting upon cyber attacks. As the adoption of the cloud continues to increase, incorporating Artificial Intelligence (AI) and machine learning into security infrastructures has become increasingly important. The study investigates the performance of AI-based security systems, using sophisticated pattern recognition and anomaly detection, compared to conventional methods in detecting (...) deviations from normal user behavior in cloud environments. Adopting a quantitative research approach, the study utilizes a systematic survey of cybersecurity professionals in various industries like finance, healthcare, IT, retail, and government. The survey, comprising closed- ended and Likert-scale questions, collects information on professionals' attitudes and experiences with AI-based versus conventional security methods. Data from a purposive sample of 243 cybersecurity professionals are examined through multiple regression methods to evaluate the effect of such security systems on threat detection and response effectiveness in cloud environments. Results show that although both AI-based and conventional methods improve threat detection accuracy significantly, conventional methods have a marginal advantage. Yet, AI-based solutions show better predictive ability and overall security performance. These results suggest that a hybrid security strategy is essential for cloud security, combining AI’s advanced predictive analytics and adaptability with the reliability and speed of traditional security measures. Such an integrated approach is recommended to address the complex and evolving nature of cloud-based cyber threats effectively. This research provides useful information for IT practitioners and companies on how to best optimize AI-powered security integration in cloud environments. It highlights the changing role of AI in cloud security and the need to strike a balance between new AI-based solutions and proven security practices in order to construct an integrated and robust cloud security framework. (shrink)

Obituaries represent a prominent way of expressing the human universal of grief. According to philosophers, obituaries are a ritualized way of evaluating both individuals who have passed away and the communities that helped to shape them. The basic idea is that you can tell what it takes to count as a good person of a particular type in a particular community by seeing how persons of that type are described and celebrated in their obituaries. Obituaries of those killed in conflict, (...) in particular, are rich repositories of communal values, as they reflect the values and virtues that are admired and respected in individuals who are considered to be heroes in their communities. In this paper, we use natural language processing techniques to map the patterns of values and virtues attributed to Australian military personnel who were killed in action during World War I and World War II. Doing so reveals several clusters of values and virtues that tend to be attributed together. In addition, we use named entity recognition and geotagging the track the movements of these soldiers to various theatres of the wars, including North Africa, Europe, and the Pacific. (shrink)

Abstract:We analyzed co-citation patterns in 332,498 articles published in Anglophone psychology journals between 1946 and 1990 to estimate (1) when cognitive psychology first emerged as a clearly delineated subdiscipline, (2) how fast it grew, (3) to what extent it replaced other (e.g., behaviorist) approaches to psychology, (4) to what degree it was more appealing to scholars from a younger generation, and (5) whether it was more interdisciplinary than alternative traditions. We detected a major shift in the structure of co-citation networks (...) between approximately 1955 and 1975 and draw novel conclusions about the developments commonly referred to as "the cognitive turn.". (shrink)