Introduction Current treatments for pain have limited benefits and worrying side effects. Some studies suggest that pain is reduced when clinicians deliver positive messages. However, the effects of positive messages are heterogeneous and have not been subject to meta-analysis. We aimed to estimate the efficacy of positive messages for pain reduction. -/- Methods We included randomized trials of the effects of positive messages in a subset of the studies included in a recent systematic review of context factors for (...) treating pain. Several electronic databases were searched. Reference lists of relevant studies were also searched. Two authors independently undertook study selection, data extraction, risk of bias assessment, and analyses. Our primary outcome measures were differences in patient- or observer-reported pain between groups who were given positive messages and those who were not. -/- Results Of the 16 randomized trials (1703 patients) that met the inclusion criteria, 12 trials had sufficient data for meta-analysis. The pooled standardized effect size was −0.31 (95% confidence interval [CI] −0.61 to −0.01, p = 0.04, I2 = 82%). The effect size remained positive but not statistically significant after we excluded studies considered to have a high risk of bias (standard effect size −0.17, 95% CI −0.54 to 0.19, P = 0.36, I2 = 84%). -/- Conclusion Care of patients with chronic or acute pain may be enhanced when clinicians deliver positive messages about possible clinical outcomes. However, we have identified several limitations of the present study that suggest caution when interpreting the results. We recommend further high-quality studies to confirm (or falsify) our result. -/- FUNDING -/- Alexander Mebius research has been funded through the ERC grant "Philosophy of Pharmacology: Safety, Statistical Standards, and Evidence Amalgamation" (GA: 639276). (shrink)

This study, by using 142 groups of data from 1990 to 2007 and the method of cross-temporal meta-analysis, researched the changing trend of status of mental health of 108736 members of the Chinese Army along with the change of years. All the data came from 94 related research reports, and all the research reports used SCL-90 (the Symptom Checklist 90) as the testing tool of mental health. The study found that: (1) mental health of members of (...) the Chinese Army steadily improved between 1990 and 2007; (2) during those 18 years, the Interpersonal Sensitivity factor of SCL-90 of Chinese Army members changed most significantly, and the least significantly changed factor was Somatization; (3) Chinese Army members showed evidence of fewest problems on the Photic Anxiety factor, in contrast to the consistent problems indicated by scores on the Obsessive-Compulsive and Interpersonal Sensitivity scales; (4) Chinese Army members from single-child families (N =1,944) showed significant lower evidence of positive mental health than soldiers from multiple child families (N =2,649); (5) The mental health of soldiers from non-agricultural backgrounds (N =7,808) was less positive than that of soldiers from agricultural households(N =11,459); (6) Chinese Army members with senior high school education level (N = 10,189) had less positive mental health than those with junior high school (N = 8,407) or university education (N = 863). (shrink)

Immunology researchers are beginning to explore the possibilities of reproducibility, reuse and secondary analyses of immunology data. Open-access datasets are being applied in the validation of the methods used in the original studies, leveraging studies for meta-analysis, or generating new hypotheses. To promote these goals, the ImmPort data repository was created for the broader research community to explore the wide spectrum of clinical and basic research data and associated findings. The ImmPort ecosystem consists of four (...) components–Private Data, Shared Data, Data Analysis, and Resources—for data archiving, dissemination, analyses, and reuse. To date, more than 300 studies have been made freely available through the ImmPort Shared Data portal , which allows research data to be repurposed to accelerate the translation of new insights into discoveries. (shrink)

It is a plausible speculation that conventional choices in outcome measures might influence the results of meta-analyses. We test that speculation by simulating data from trials on antidepressants. We vary real drug effectiveness while modulating conventional values for outcome measures. We had previously shown that one conventional choice used in meta-analyses of antidepressants falls in a narrow range of values that maximize estimates of effectiveness. Our present analysis investigates why this phenomenon occurs. Moreover, our results suggest (...) the superiority of absolute outcome measures over relative measures. This research program can be extended to test numerous other aspects of clinical research. (shrink)

The Emotion Ontology is an ontology covering all aspects of emotional and affective mental functioning. It is being developed following the principles of the OBO Foundry and Ontological Realism. This means that in compiling the ontology, we emphasize the importance of the nature of the entities in reality that the ontology is describing. One of the ways in which realism-based ontologies are being successfully used within biomedical science is in the annotation of scientific research results in publicly available databases. Such (...) annotation enables several objectives, including searching, browsing and cross-database data integration. A key benefit conferred by realismbased ontology is that suitably annotated research results are able to be aggregated and compared in a fashion that is based on the underlying reality that the science is studying. This has the potential of increasing the power of statistical analysis and meta-analysis in data-driven science. This aspect has been fruitfully exploited in the investigation of the functions of genes in molecular biology. Cognitive neuroscience uses functional neuroimaging to investigate the brain correlates of areas of mental functioning such as memory, planning and emotion. The use of functional neuroimaging to study affective phenomena such as the emotions is called ‘affective neuroscience’. BrainMap is the largest curated database of coordinates and metadata for studies in cognitive neuroscience, including affective neuroscience (Laird et al., 2005). BrainMap data is already classified and indexed using a terminology for classification, called the ‘Cognitive Paradigm Ontology’ (CogPO), that has been developed to facilitate searching and browsing. However, CogPO has been developed specifically for the BrainMap database, and the data are thus far not annotated to a realism-based ontology which would allow the discovery of interrelationships between research results across different databases on the basis of what the research is about. In this contribution, we describe ongoing work that aims to annotate affective neuroscience data, starting with the BrainMap database, using the Emotion Ontology. We describe our objectives and technical approach to the annotation, and mention some of the challenges. (shrink)

According to the PubMed resource from the U.S. National Library of Medicine, over 750,000 scientific articles have been published in the ~5000 biomedical journals worldwide in the year 2007 alone. The vast majority of these publications include results from hypothesis-driven experimentation in overlapping biomedical research domains. Unfortunately, the sheer volume of information being generated by the biomedical research enterprise has made it virtually impossible for investigators to stay aware of the latest findings in their domain of interest, let alone to (...) be able to assimilate and mine data from related investigations for purposes of meta-analysis. While computers have the potential for assisting investigators in the extraction, management and analysis of these data, information contained in the traditional journal publication is still largely unstructured, free-text descriptions of study design, experimental application and results interpretation, making it difficult for computers to gain access to the content of what is being conveyed without significant manual intervention. In order to circumvent these roadblocks and make the most of the output from the biomedical research enterprise, a variety of related standards in knowledge representation are being developed, proposed and adopted in the biomedical community. In this chapter, we will explore the current status of efforts to develop minimum information standards for the representation of a biomedical experiment, ontologies composed of shared vocabularies assembled into subsumption hierarchical structures, and extensible relational data models that link the information components together in a machine-readable and human-useable framework for data mining purposes. (shrink)

The research presented in this article is motivated by the increasing importance of complex human relations in linked data, either extracted from social networks, or found in existing databases. The FOAF vocabulary, targeted in our research, plays a central role in those data, and is a model for lightweight ontologies largely used in linked data, such as the DBpedia ontology and schema-org. We provide an overview of FOAF and other approaches for describing human relations, followed by a (...) detailed analysis and critique of the FOAF Relationship Vocabulary, the most important FOAF extension. We propose an explicit formal axiomatization of this vocabulary, and an ontological analysis concerning the properties used to describe human relationships. We analyze the distribution of human relations based on their epistemological status, and define an ontoepistemic meta-property as characteristic of some of these predicates. Our analysis is generalizable to semantic modeling of social networks. Additionally, the modeling patterns used in other relevant linked data vocabularies are analyzed for comparison. (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)

The Internet-of-Things (IoT) is gradually being established as the new computing paradigm, which is bound to change the ways of our everyday working and living. IoT emphasizes the interconnection of virtually all types of physical objects (e.g., cell phones, wearables, smart meters, sensors, coffee machines and more) towards enabling them to exchange data and services among themselves, while also interacting with humans as well. Few years following the introduction of the IoT concept, significant hype was generated as a result (...) of the proliferating number of IoT-enabled devices, which (according to many projections) are expected to amount to several billion in the next years. During recent years, this hype has been turning to reality, as a wave of IoT applications with significant social and economic has been emerging. Data analytics is the process of deriving knowledge from data, generating value like actionable insights from them. This article reviews work in the IoT and big data analytics from the perspective of their utility in creating efficient, effective and innovative applications and services for a wide spectrum of domains. We review the broad vision for the IoT as it is shaped in various communities, examine the application of data analytics across IoT domains, provide a categorization of analytic approaches and propose a layered taxonomy from IoT data to analytics. IoT data analysis is an integral element of any non- trivial IoT system. Nevertheless, IoT analytics are still in their infancy, as IoT data still remain largely unexploited. (shrink)

The notion of representation in neuroscience has largely been predicated on localizing the components of computational processes that explain cognitive function. On this view, which I call “algorithmic homuncularism,” individual, spatially and temporally distinct parts of the brain serve as vehicles for distinct contents, and the causal relationships between them implement the transformations specified by an algorithm. This view has a widespread influence in philosophy and cognitive neuroscience, and has recently been ably articulated and defended by Shea. Still, I am (...) skeptical about algorithmic homuncularism, and I argue against it by focusing on recent methods for complex data analysis in systems neuroscience. I claim that analyses such as principle components analysis and linear discriminant analysis prevent individuating vehicles as algorithmic homuncularism recommends. Rather, each individual part contributes to a global state space, trajectories of which vary with important task parameters. I argue that, while homuncularism is false, this view still supports a kind of “vehicle realism,” and I apply this view to debates about the explanatory role of representation. (shrink)

The article summarizes the software tool on astrophysical analysis with multi-wavelength space telescope data. It recaps the evidence analysis conducted on the Kerr-Newman black hole (KNBH). It was written prior to the article Research on the Kerr-Newman Black Hole in M82 Confirms Black Hole and White Hole Juxtapose not soon after the experiment. The conducted analysis suggested Hawking radiation is caused by the movement of ergosurfaces of the BH and serves as the primal evidence for black (...) hole and white hole juxtapose. A later data exploration was conducted with the radiation trails in the multi-wavelength data. The evidences produced corroborates with Yale professor Priyamvada Natarajan's black hole seeds theory. It implies that the electromagnetic dynamic of fusion and fission temperature determines the pressure of surface tension on the macro particles, and the mass density of the BH is determined by the electromagnetic tension between the outer ergosurface and inner ergosurface. The ring singularity of the BH and the Penrose-Hawking singularity of the BH determine the spin and gravitational singularity of the BH. Inside the ergosurfaces, the BH singularities' backward inflow causes the vicinity's rate on feeding the BH. It makes the active galactic nuclei (AGN) a semi-closed system. The density pressure is released on threshold. During the mass exchange observed by energy momentum upon the AGN's open, the macroparticle composition of the BH changes with the galactic event. This causes the expansion rate of the galaxy and contraction rate of the BH. AGN types and their relative motions determine the expansion rate of the cosmic universe in a generalized quantitative thinking. The article concludes that BH spin is caused by the asymmetric motions of AGN in the BH system. A set of the nuclear resonance caused by BH and white hole (WH) oscillation is processed with the same set of data. (shrink)

I develop a contractualist theory of just intelligence collection based on the collective moral responsibility to deliver security to a community and use the theory to justify certain kinds of signals interception. I also consider the rights of various intelligence targets like intelligence officers, service personnel, government employees, militants, and family members of all of these groups in order to consider how targets' waivers or forfeitures might create the moral space for just surveillance. Even people who are not doing anything (...) prejudicial to other states' security can be modeled as ceding rights against diagnostic collection--light touch collection limited to ascertaining if someone is likely an intelligence threat--as part of their duty to support just foreign institutions. Foreign intelligence officers could not perform the same job potential targets can reasonably demand their intelligence agencies perform on their behalf without this ceding of rights. More invasive forms of collection can only be justified if officers can reasonably model their citizens consenting to being the target of the same sort of collection by adversary states. (shrink)

An astonishing volume and diversity of evidence is available for many hypotheses in the biomedical and social sciences. Some of this evidence—usually from randomized controlled trials (RCTs)—is amalgamated by meta-analysis. Despite the ongoing debate regarding whether or not RCTs are the ‘gold-standard’ of evidence, it is usually meta-analysis which is considered the best source of evidence: meta-analysis is thought by many to be the platinum standard of evidence. However, I argue that meta-analysis (...) falls far short of that standard. Different meta-analyses of the same evidence can reach contradictory conclusions. Meta-analysis fails to provide objective grounds for intersubjective assessments of hypotheses because numerous decisions must be made when performing a meta-analysis which allow wide latitude for subjective idiosyncrasies to influence its outcome. I end by suggesting that an older tradition of evidence in medicine—the plurality of reasoning strategies appealed to by the epidemiologist Sir Bradford Hill—is a superior strategy for assessing a large volume and diversity of evidence. (shrink)

The outcomes of a bibliographic review on political communication, in particular electoral communication in social networks, are presented here. The electoral campaigning are a crucial test to verify the transformations of the media system and of the forms and uses of the linguistic acts by dominant actors in public sphere – candidates, parties, journalists and Gatekeepers. The aim is to reconstruct the first elements of an analytical model on the transformations of the political public sphere, with which to systematize the (...) results of the main empirical research carried out in recent years, in particular those conducted with a promising methodology: Digital Trace Data Analysis. (shrink)

This paper analyzes and synthesizes concepts and alternative perspectives of sociologist and author Allan G. Johnson’s book “Privilege, Power, and Difference” through the lens of the sociological imagination. The first phase of the review addresses the different chapter dimensions of the concept (or purported abstraction) of ‘inequality’ as social, economic, and historical concretion. The model is later elaborated upon, and the work is extrapolated into a meta-theoretical analysis of the first seven chapters of the textbook. By identifying and (...) reviewing the principal points within the book, we present a multitude of vantage points by which continuation and assimilation of material in qualitative sociology at the undergraduate level can be both experimental and comprehensive for students interested in the subject. (shrink)

Humans are obsolete. In the post-ChatGPT era, artificial intelligence systems have replaced us in the last sectors of life that we thought were our personal kingdom. Yet, humans still have a place in this life. But they can find it only if they forget all those things that we believe make us unique. Only if we go back to doing nothing, can we truly be alive and meet our Self. Only if we stop thinking can we accept the Cosmos as (...) it is and know what Being is. Only if we become irrational can we ever understand what AI will never understand. Humans need to destroy what they have created, because in the world they have built they have no place. Unless we become children once more. And laugh for no reason. In a cosmos that was meant to be our home. (shrink)

Big Data is a large-sized and complex dataset, which cannot be managed using traditional data processing tools. Mining process of big data is the ability to extract valuable information from these large datasets. Association rule mining is a type of data mining process, which is indented to determine interesting associations between items and to establish a set of association rules whose support is greater than a specific threshold. The classical association rules can only be extracted from (...) binary data where an item exists in a transaction, but it fails to deal effectively with quantitative attributes, through decreasing the quality of generated association rules due to sharp boundary problems. In order to overcome the drawbacks of classical association rule mining, we propose in this research a new neutrosophic association rule algorithm. The algorithm uses a new approach for generating association rules by dealing with membership, indeterminacy, and non-membership functions of items, conducting to an efficient decision-making system by considering all vague association rules. To prove the validity of the method, we compare the fuzzy mining and the neutrosophic mining. The results show that the proposed approach increases the number of generated association rules. (shrink)

Appropriate measurement scales are fundamental in data analysis, allowing researchers to categorise, select appropriate statistical methods, and analyse and interpret their data accurately. The nominal scale is one such measurement scale in behavioural sciences, which is crucial in organising data into distinct categories. This paper provides an overview of the nominal measurement scale in research data analysis. It explains the characteristics and role of the nominal scale in organising data into distinct categories. The (...) paper discusses methods of collecting nominal scale data, including surveys and observations. It explores the use of the nominal scale in descriptive (such as frequency counts, measures of dispersion and central tendencies), and inferential statistics (such as point biserial correlation, independent t-test, analysis of variance, logistic regression, discriminant analysis, differential item functioning, chi-square test of independence, Kruskal-Walli’s test, and Mann-Whitney U Test). Each technique is explained with assumptions and application areas. In conclusion, the paper emphasises the significance of the nominal scale in data analysis and its contribution to various statistical techniques. It serves as a comprehensive guide for researchers and practitioners looking to understand and utilise the nominal measurement scale in their data analysis. (shrink)

In a first investigation, a Lacan-motivated template of the Poe story is fitted to the data. A segmentation of the storyline is used in order to map out the diachrony. Based on this, it will be shown how synchronous aspects, potentially related to Lacanian registers, can be sought. This demonstrates the effectiveness of an approach based on a model template of the storyline narrative. In a second and more Comprehensive investigation, we develop an approach for revealing, that is, uncovering, (...) Lacanian register relationships. Objectives of this work include the wide and general application of our methodology. This methodology is strongly based on the “letting the data speak” Correspondence Analysis analytics Platform of Jean-Paul Benzécri, that is also the geometric data analysis, both qualitative and quantitative analytics, developed by Pierre Bourdieu. (shrink)

Abstract— The term Health Informatics represent a huge volume of data that is collected from different source of health sector. Because of its’ diversity in nature, quite a big number of attributes, numerous amount data, health informatics can be considered as Big Data. Therefore, different techniques used for analyzing Big Data will also fit for Health Informatics. In recent years, implementation of Data Mining on Health Informatics brings a lot of fruitful outcomes that improve the (...) overall healthcare system both in analyzing disease and improving healthcare services which eventually reduce expenses. This paper will define the term the health informatics with a detail discussion about different source of heath informatics. Finally, some case study will be illustrated as examples where data mining techniques are applied to produce more efficient, in depth outcomes in analyzing disease. (shrink)

Recent experimental studies dispute the position that commonsense morality accepts ‘Ought’ Implies ‘Can’, the view that, necessarily, if an agent ought to perform some action, then she can perform that action. This paper considers and supports explanations for the results of these studies on the hypothesis that OIC is intuitive and true.

In this paper, partly historical and partly theoretical, after having shortly outlined the development of the meta-ethics in the 1900?s starting from the Tractatus of Wittgenstein, I argue it is possible to sustain that emotivism and intuitionism are unsatisfactory ethical conceptions, while on the contrary, reason (intended in a logical-deductive sense) plays an effective role both in ethical discussions and in choices. There are some characteristics of the ethical language (prescriptivity, universalizability and predominance) that cannot be eluded (pain the (...) non significativity of the same language) by those who want to morally reason, i.e. by those who intend to regulate their own behaviour on the basis of knowledged and coherent principles. These characteristics can be found whether or not all possible ontological-metaphysics foundations of morals are taken into account. Furthermore the deontic logic systems allow the formalization of ethical theories and - at least in principle - a rigorous critical discussion of the same, but obviously nothing can be affirmed on the value of truth of the axioms of a system. In the deontic logic systems Hume?s law is assumed as an implicit result of inferential (conventional) rules and the acceptance of Hume?s law as a logical-linguistic thesis does not involve the cancellation of values (nihilism) or ethical relativism or indifferentism. (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)

Advancements in cloud technologies have increased the infrastructural needs of data centers due to storage needs and processing of extensive dimensional data. Many service providers envisage anomaly detection criteria to guarantee availability to avoid breakdowns and complexities caused due to large-scale operations. The streaming log data generated is associated with multi-dimensional complexity and thus poses a considerable challenge to detect the anomalies or unusual occurrences in the data. In this research, a hybrid model is proposed that (...) is motivated by deep belief criteria and meta-heuristics. Using Search-and-Rescue—BrainStorm Optimization (SAR-BSO), a hybrid feature selection (FS) and deep belief network classifier is used to localize and detect anomalies for streaming data logs. The significant contribution of the research lies in FS, which is carried out using SAR-BSO which increases the detection power of the model as it selects the most significant variables by minimizing redundant features. The evaluation of accuracy is efficiently improved when compared with the predictable methods, such as Extract Local Outlier Factor (ELOF), Track-plus, Hybrid Distributed Batch Stream (HDBS), IForestASD, DBN, BSO-based Feature Selection with DBN, Genetic Algorithm-Deep Belief Network (GA-DBN), Mutual Information-Deep Belief Network (MI-DBN), information entropy-Deep Belief Network(I + DBN), Flat Field-Deep Belief Network (FF + DBN), African Vulture Optimization Algorithm-Deep Belief Network(AVOA + DBN), Gorilla Troop Optimizer-Deep Belief Network(GTO-DBN), and SARO-based Feature Selection with DBN. Further, the accurate detection of the anomalies in the data stream is established by the Deep Belief Neural Network (DBN) classifier. The model’s efficacy is determined using Apache, Hadoop, HDFS, Spark, and Linux datasets and evaluated against existing similar models. The model efficiency is provided using multiple evaluation metrics and is found effective. From the experimentation, the accuracy of the proposed model is found to be 93.3, 95.4, 93.6, 94.2, and 93.5% respectively for the dataset such as Apache, Hadoop, HDFS, spark, and Linux. This enhancement in accuracy is due to the selection of optimal features by the proposed SAR-BSO algorithm. (shrink)

In the current chapter, I examined the relationship between the cerebellum, emotion, and morality with evidence from large-scale neuroimaging data analysis. Although the aforementioned relationship has not been well studied in neuroscience, recent studies have shown that the cerebellum is closely associated with emotional and social processes at the neural level. Also, debates in the field of moral philosophy, psychology, and neuroscience have supported the importance of emotion in moral functioning. Thus, I explored the potentially important but less-studies (...) topic with NeuroSynth, a tool for large-scale brain image analysis, while addressing issues associated with reverse inference. The result from analysis demonstrated that brain regions in the cerebellum, the right Crus I and Crus II in particular, were specifically associated with morality in general. I discussed the potential implications of the finding based on clinical and functional neuroimaging studies of the cerebellum, emotional functioning, and neural networks for diverse psychological processes. (shrink)

Meta-analysis is a statistical analysis that combines the results of relevant studies performed for same purpose and is used as a tool for evidence-based medicine to support clinical decision making. Because a meta-analysis includes advanced statistical analysis, the report is not easily understandable to clinicians. In this study, we aimed to write a guideline for clinicians to help them understand the statistical analysis part of a meta-analysis and interpret graphs and results (...) of a meta-analysis. (shrink)

This paper provides a thorough analysis of two often informally stated claims. First, successful argumentation in the sense of persuasive argumentation requires agreement between the interlocutors about the rationality of arguments. Second, a general agreement about rationality of arguments cannot itself be established via argumentation, since such an attempt leads to an infinite meta‐regress. Hence, agreement about the rationality of arguments is a precondition for successful argumentation. As the paper argues, these plausible claims hold under the assumption that (...) interlocutors are subjectively rational and follow their own standards of rationality when engaging in argumentation. (shrink)

The modern abundance and prominence of data has led to the development of “data science” as a new field of enquiry, along with a body of epistemological reflections upon its foundations, methods, and consequences. This article provides a systematic analysis and critical review of significant open problems and debates in the epistemology of data science. We propose a partition of the epistemology of data science into the following five domains: (i) the constitution of data (...) science; (ii) the kind of enquiry that it identifies; (iii) the kinds of knowledge that data science generates; (iv) the nature and epistemological significance of “black box” problems; and (v) the relationship between data science and the philosophy of science more generally. (shrink)

The meta-ethical commitments of folk respondents – specifically their commitment to the objectivity of moral claims – have recently become subject to empirical scrutiny. Experimental findings suggest that people are meta-ethical pluralists: There is both inter- and intrapersonal variation with regard to people’s objectivist commitments. What meta-ethical implications, if any, do these findings have? I point out that current research does not directly address traditional meta-ethical questions: The methods used and distinctions drawn by experimenters do not (...) perfectly match those of meta-ethicists. However, I go on to argue that, in spite of this mismatch, the research findings should be of interest to moral philosophers, including meta-ethicists. Not only do these findings extend the field of moral psychology with new data and hypotheses, but they also provide tentative evidence that touches on the adequacy of theses in moral semantics and moral metaphysics. Specifically, they put pressure on argum... (shrink)

The study was conducted to compare manual and computerized software techniques of data management and analysis in educational research. Specifically, the study investigated whether there was a significant difference in the results of Pearson correlation, independent t-test and ANOVA obtained from using manual and computerized software technique of data analyses. Three null hypotheses were formulated accordingly to guide the study. The study adopted a quasi-experimental research design where several data were generated by the researchers and analyzed (...) using manual and computerized software techniques. The data were generated to suit the required data of each statistical method of analysis. CASIO fx-991ES PLUS NATURAL DISPLAY scientific calculator and statistical tables were used for manual analysis; while data analysis tool pack of Microsoft Excel version 2013 were used for computerized software analysis. The results of the analysis revealed that both manual and computerized software techniques yielded the same results for Pearson correlation, independent t-test and ANOVA. It was concluded that though both manual and computerized techniques are reliable and dependable, computerized technique is faster and efficient in managing and analyzing data than manual technique. It was recommended, among other things, that any of the techniques should be used without fear when computing Pearson, independent t-test and one-way ANOVA as it is the same results that will be gotten. (shrink)

A huge amount of data is being generated everyday through different transactions in industries, social networking, communication systems etc. Big data is a term that represents vast volumes of high speed, complex and variable data that require advanced procedures and technologies to enable the capture, storage, management, and analysis of the data. Big data analysis is the capacity of representing useful information from these large datasets. Due to characteristics like volume, veracity, and velocity, (...) big data analysis is becoming one of the most challenging research problems. Semantic analysis is method to better understand the implied or practical meaning of the input dataset. It is mostly applied with ontology to analyze content mainly in web resources. This field of research combines text analysis and Semantic Web technologies. The use semantic knowledge is to aid sentiment analysis of queries like emotion mining, popularity analysis, recommendation systems, user profiling, etc. A new method has been proposed to extract semantic relationships between different data attributes of big data which can be applied to a decision system. (shrink)

Academic Placement Data and Analysis (APDA), a project funded by the American Philosophical Association (APA) and headed by Carolyn Dicey Jennings (UC Merced), aims “to make information on academic job placement useful to prospective graduate students in philosophy.” The project has just been updated to include new data, which Professor Jennings describes in a post at New APPS. She also announces a new interactive data tool with which one can sift through and sort information. (from Daily (...) Nous). (shrink)

Experimental research suggests that people draw a moral distinction between bad outcomes brought about as a means versus a side effect (or byproduct). Such findings have informed multiple psychological and philosophical debates about moral cognition, including its computational structure, its sensitivity to the famous Doctrine of Double Effect, its reliability, and its status as a universal and innate mental module akin to universal grammar. But some studies have failed to replicate the means/byproduct effect especially in the absence of other factors, (...) such as personal contact. So we aimed to determine how robust the means/byproduct effect is by conducting a meta-analysis of both published and unpublished studies (k = 101; 24,058 participants). We found that while there is an overall small difference between moral judgments of means and byproducts (standardized mean difference = 0.87, 95% CI 0.67 – 1.06; standardized mean change = 0.57, 95% CI 0.44 – 0.69; log odds ratio = 1.59, 95% CI 1.15 – 2.02), the mean effect size is primarily moderated by whether the outcome is brought about by personal contact, which typically involves the use of personal force. (shrink)

Visual imagery is a form of sensory imagination, involving subjective experiences typically described as similar to perception, but which occur in the absence of corresponding external stimuli. We used the Activation Likelihood Estimation algorithm (ALE) to identify regions consistently activated by visual imagery across 40 neuroimaging studies, the first such meta-analysis. We also employed a recently developed multi-modal parcellation of the human brain to attribute stereotactic co-ordinates to one of 180 anatomical regions, the first time this approach has (...) been combined with the ALE algorithm. We identified a total 634 foci, based on measurements from 464 participants. Our overall comparison identified activation in the superior parietal lobule, particularly in the left hemisphere, consistent with the proposed ‘top-down’ role for this brain region in imagery. Inferior premotor areas and the inferior frontal sulcus were reliably activated, a finding consistent with the prominent semantic demands made by many visual imagery tasks. We observed bilateral activation in several areas associated with the integration of eye movements and visual information, including the supplementary and cingulate eye fields (SCEFs) and the frontal eye fields (FEFs), suggesting that enactive processes are important in visual imagery. V1 was typically activated during visual imagery, even when participants have their eyes closed, consistent with influential depictive theories of visual imagery. Temporal lobe activation was restricted to area PH and regions of the fusiform gyrus, adjacent to the fusiform face complex (FFC). These results provide a secure foundation for future work to characterise in greater detail the functional contributions of specific areas to visual imagery. (shrink)

A distorted representation of one's own body is a diagnostic criterion and core psychopathology of both anorexia nervosa (AN) and bulimia nervosa (BN). Despite recent technical advances in research, it is still unknown whether this body image disturbance is characterized by body dissatisfaction and a low ideal weight and/or includes a distorted perception or processing of body size. In this article, we provide an update and meta-analysis of 42 articles summarizing measures and results for body size estimation (BSE) (...) from 926 individuals with AN, 536 individuals with BN and 1920 controls. We replicate findings that individuals with AN and BN overestimate their body size as compared to controls (ES= 0.63). Our meta-regression shows that metric methods (BSE by direct or indirect spatial measures) yield larger effect sizes than depictive methods (BSE by evaluating distorted pictures), and that effect sizes are larger for patients with BN than for patients with AN. To interpret these results, we suggest a revised theoretical framework for BSE that accounts for differences between depictive and metric BSE methods regarding the underlying body representations (conceptual vs. perceptual, implicit vs. explicit). We also discuss clinical implications and argue for the importance of multimethod approaches to investigate body image disturbance. (shrink)

Metaphilosophy, Volume 53, Issue 1, Page 100-133, January 2022.

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)

Abstract—Breast cancer is considered the second most common cancer in women compared to all other cancers. It is fatal in less than half of all cases and is the main cause of mortality in women. It accounts for 16% of all cancer mortalities worldwide. Early diagnosis of breast cancer increases the chance of recovery. Data mining techniques can be utilized in the early diagnosis of breast cancer. In this paper, an academic experimental breast cancer dataset is used to perform (...) a data mining practical experiment using the Waikato Environment for Knowledge Analysis (WEKA) tool. The WEKA Java application represents a rich resource for conducting performance metrics during the execution of experiments. Pre-processing and feature extraction are used to optimize the data. The classification process used in this study was summarized through thirteen experiments. Additionally, 10 experiments using various different classification algorithms were conducted. The introduced algorithms were: Naïve Bayes, Logistic Regression, Lazy IBK (Instance-Bases learning with parameter K), Lazy Kstar, Lazy Locally Weighted Learner, Rules ZeroR, Decision Stump, Decision Trees J48, Random Forest and Random Trees. The process of producing a predictive model was automated with the use of classification accuracy. Further, several experiments on classification of Wisconsin Diagnostic Breast Cancer and Wisconsin Breast Cancer, were conducted to compare the success rates of the different methods. Results conclude that Lazy IBK classifier k-NN can achieve 98% accuracy among other classifiers. The main advantages of the study were the compactness of using 13 different data mining models and 10 different performance measurements, and plotting figures of classifications errors. (shrink)

This study explores the effectiveness of brain-based learning (BBL) as a pedagogical approach to address the challenges of poor conceptual understanding, which may have worsened due to the COVID-19 pandemic aftermath. In this meta- analysis, 14 studies qualified using the Publish or Perish software and the Preferred Reporting Items for Systematic Reviews and Meta-analyses. Statistical analysis conducted using Comprehensive Meta-Analysis (CMA) Version 4 software by Biostat, Inc. Based on the results, the overall effect size (...) (ES = 3.135) indicates that the use and integration of BBL principles and strategies have a significantly large and positive effect on student conceptual understanding. The moderator analysis revealed a significant difference between individual studies (p < .001); however, the overall results for academic level (p > .05) and discipline (p > .05) revealed no significant differences. Hence, each study included in this analysis may differ from one another due to the differences in various BBL strategies implemented; however, when grouped, they shared common effect sizes. With these findings, the researchers advocate the use of BBL principles and strategies to improve students' conceptual understanding at various levels in basic education, be it in English and STEM. Moreover, empirical studies focusing on a particular BBL variable, such as health and nutrition, are recommended for in-depth analysis and discussion. (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 nominal ground that entwines human beings and animal behaviours is unwilling to admit moral valuing as a non-human act. Just to nail it down explicitly, two clauses ramify the moral conscience of human beings as follows: a) Can non-humans be moral beings?, b) Unconscious animal behaviours go beyond any moral judgments. My approach aims to rebuff these anthropomorphic clauses by justifying animals’ moral beings and animals’ moral behaviours from a meta-ethical stance. A meta-ethical outlook may enable an (...) analysis of ethical and normative views through the limit of moral motives and reasoning. Animals’ sense of moral motives and their apparatus of getting involved in moral acts cannot be compared with human actions. In human moral engagement, we abide by moral paradigmatic theories and their diversified attitudes that could have conceptual and linguistic use in our societal discourses. However, animals’ intentional apparatus may have the propensity to choose an act following the moral consequences (care, utility, responsibility, etc.) in their life-forms. (shrink)

This literature review explores the issues and risks in non-conscious data collection and evaluates people’s attitudes towards it. In the modern world, data is one of the most valuable resources, yet studies focused on the potential negative implications of the new data-driven technologies are lacking. Therefore, this thesis conducts a comprehensive literature review to identify and assess risks in non-conscious data collection technologies that are most relevant and referenced in current literature. Accordingly, the most prominent risks (...) are related to privacy issues with personal data, bias in algorithms creating inequality, and the difficulties in creating adequate legislation. Subsequently, the thesis will explore existing studies about people’s attitudes towards non-conscious data collection and examine the most significant socio-demographic determinants of those attitudes. Therefore, despite socio-demographic factors such as age, gender, and economic status affecting the attitudes people have towards data collection technologies, this thesis argues how these approaches can be explained by varying external factors such as prior experiences with similar technologies. (shrink)

Preparing students for the real challenges in life is one of the most important goals in education. Constructivism is an approach that uses real-life experiences to construct knowledge. Problem-Based Learning (PBL), for almost five decades now, has been the most innovative constructivist pedagogy used worldwide. However, with the rising popularity, there is a need to revisit empirical studies regarding PBL to serve as a guide and basis for designing new studies, making institutional policies, and evaluating educational curricula. This need has (...) led the researchers to do a meta-analysis to analyse the effectiveness of PBL on secondary students’ achievement in different scientific disciplines. Following the set of inclusion and exclusion criteria, 11 studies in Eurasia, Africa, and America conducted from 2016 to 2020 have qualified for this study. Six of which focused on JHS (n = 1047) and five on SHS (n = 375). Studies were obtained from various meta-search engines including Google, ERIC, and JSTOR. Further, the researchers used Harzing’s Publish and Perish software to exhaust the search process. Sample size, mean, and standard deviation were analysed using the Comprehensive MetaAnalysis version 3 to determine the effect sizes (Hedge’s g) and the results of moderator analysis, forest plot, funnel plot, and Begg-Mazumdar test. Findings have shown that PBL, as an approach to teaching science, had a large and positive effect (ES = .871) on the achievement of secondary students. However, grade levels and various scientific disciplines did not influence students’ learning achievement. The conduct of more studies on the different factors affecting PBL implementation and specific effects of PBL on various student domains is recommended to facilitate comparative educational research in the future. (shrink)

Ontologies, as the term is used in informatics, are structured vocabularies comprised of human- and computer-interpretable terms and relations that represent entities and relationships. Within informatics fields, ontologies play an important role in knowledge and data standardization, representation, integra- tion, sharing and analysis. They have also become a foundation of artificial intelligence (AI) research. In what follows, we outline the Coronavirus Infectious Disease Ontology (CIDO), which covers multiple areas in the domain of coronavirus diseases, including etiology, transmission, epidemiology, (...) pathogenesis, diagnosis, prevention, and treatment. We emphasize CIDO development relevant to COVID-19. (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)

As past studies of the association between parent-child relationship and problematic internet use show mixed results and are influenced by many factors, this meta-analysis of 75 primary Chinese and English language studies from 1990 to 2021 with 110,601 participants (aged 6−25 years) explored (a) the overall association between parent-child relationship and problematic internet use, and (b) whether the association is affected by their types, country, measures, objects of the parent-child relationship, gender, age, year and publication types. We used (...) funnel plots, Classic fail-safe N and Egger's test to test for publication bias and for moderation with the homogeneity tests. The results showed a negative association between quality of parent-child relationship and problematic internet use (r = −0.18, 95% CI = [−0.20, −0.15]). The moderation analysis found that compared with internet addiction tendency, the association between social media addiction and parent-child relationship was stronger. (shrink)

While the term “reactivity” has come to be associated with specific phenomena in the social sciences, having to do with subjects’ awareness of being studied, this paper takes a broader stance on this concept. I argue that reactivity is a ubiquitous feature of the psychological subject matter and that this fact is a precondition of experimental research, while also posing potential problems for the experimenter. The latter are connected to the worry about distorted data and experimental artifacts. But what (...) are experimental artifacts and what is the most productive way of dealing with them? In this paper, I approach these questions by exploring the ways in which experimenters in psychology simultaneously exploit and suppress the reactivity of their subject matter in order to produce experimental data that speak to the question or subject matter at hand. Highlighting the artificiality of experimental data, I raise the question of what distinguishes a genuine experimental result from an experimental artifact. My analysis construes experimental results as the outcomes of inferences from the data that take material background assumptions as auxiliary premises. Artifacts occur when one or more of these background assumptions are false, such that the data do not reliably serve the purposes they were generated for. I conclude by laying out the ways in which my analysis of data quality is relevant to, and informed by, recent debates about the replicability of experimental results. (shrink)

Appropriate information and consent has been one of the most intensely discussed topics within the context of biobank research. In parallel to the normative debate, many socio-empirical studies have been conducted to gather experiences, preferences and views of patients, healthy research participants and further stakeholders. However, there is scarcity of literature which connects the normative debate about justifications for different consent models with findings gained in empirical research. In this paper we discuss findings of a limited review of socio-empirical research (...) on patients’ and healthy research participants’ experiences and views regarding consent to biobank research in light of ethical principles for appropriate information and consent. (shrink)