En el presente trabajo se investigan las similitudes y las diferencias entre Hongniang y Celestina. Mis observaciones tocarán sustancialmente estos aspectos: los personajes centrales en Xi Xiang Ji y ...La Celestina ; Meishuo y la alcahueta; el erotismo en Hongniang y Celestina; la dualidad en la caracterización de los personajes y su lado oportunista e interesado.
Our article
depicts and interrogates the claims for seeing coaching and mentoring as being distinct from each other, and rather suggests that context is agentic in determining which aspects of these ...two helping orientations are likely to be used by practitioners. To start with, our article traces the development of coaching and mentoring as two separate discourses. Traditionally, coaching has been associated with a shorter term performance focus, with the coach portrayed as a process‐ rather than a content knowledge−based expert. By contrast, mentoring has a longer‐term holistic focus, where the mentor has direct experience and knowledge in the setting that the mentee is operating in. Then, we discuss some limitations of seeking conceptual distinctiveness in purely theoretical terms, including accentuating differences of practices that cannot easily be disentangled from each other in practice. Therefore, on the basis of a case study, where coaching and mentoring behaviors are used by leaders and managers, we argue that context plays an agentic role and influences which of the helping orientations is used by practitioners. We conclude that, context being multifaceted, it leads to a kaleidoscope of coaching/mentoring behaviors, which supports a practice‐based approach to the debate.
Our article depicts and interrogates the claims for seeing coaching and mentoring as being distinct from each other, and rather suggests that context is agentic in determining which aspects of these two helping orientations are likely to be used by practitioners. On the basis of a case study where coaching and mentoring behaviors are used by leaders and managers, we argue that context plays an agentic role and influences which of the helping orientations is used by practitioners. We conclude that, context being multifaceted, it leads to a kaleidoscope of coaching/mentoring behaviors, which supports a practice‐based approach to the debate.
Over the past decade, there have been numerous extensions to the definition of Functional Dependency (FD), culminating in the introduction of Relaxed Functional Dependency (RFD), offering more ...flexible constraints compared to traditional FDs. This increased flexibility makes RFDs well-suited for exploring and profiling data in datasets with lower data quality. However, efficiently identifying RFDs within dynamic data sources presents a significant challenge, as it requires processing an entire dataset from scratch whenever modifications occur. To tackle this problem, incremental discovery algorithms have been defined, but they often suffer when the frequency and the size of batches of updates increase. This paper presents a new algorithm, namely D-INDIBITS, relying on a new decentralized architecture to balance the workload that drives the incremental discovery process of INDIBITS, which is based on bitwise operators for computing attribute similarities. Experiments demonstrate DINDIBITS's effectiveness compared to FD and RFD discovery algorithms on both static and dynamic real-world data. With batches of modifications of sizes 10k and 100k, D-INDIBITS is capable of updating the set of RFDs in a few seconds, whereas all other approaches often employ more than 3 hours.
Despite the common lay assumption that males and females are profoundly different, Hyde (2005) used data from 46 meta-analyses to demonstrate that males and females are highly similar. Nonetheless, ...the gender similarities hypothesis has remained controversial. Since Hyde's provocative report, there has been an explosion of meta-analytic interest in psychological gender differences. We utilized this enormous collection of 106 meta-analyses and 386 individual meta-analytic effects to reevaluate the gender similarities hypothesis. Furthermore, we employed a novel data-analytic approach called metasynthesis (Zell & Krizan, 2014) to estimate the average difference between males and females and to explore moderators of gender differences. The average, absolute difference between males and females across domains was relatively small (d = 0.21, SD = 0.14), with the majority of effects being either small (46%) or very small (39%). Magnitude of differences fluctuated somewhat as a function of the psychological domain (e.g., cognitive variables, social and personality variables, well-being), but remained largely constant across age, culture, and generations. These findings provide compelling support for the gender similarities hypothesis, but also underscore conditions under which gender differences are most pronounced.
Whether men and women are fundamentally different or similar has been debated for more than a century. This review summarizes major theories designed to explain gender differences: evolutionary ...theories, cognitive social learning theory, sociocultural theory, and expectancy-value theory. The gender similarities hypothesis raises the possibility of theorizing gender similarities. Statistical methods for the analysis of gender differences and similarities are reviewed, including effect sizes, meta-analysis, taxometric analysis, and equivalence testing. Then, relying mainly on evidence from meta-analyses, gender differences are reviewed in cognitive performance (e.g., math performance), personality and social behaviors (e.g., temperament, emotions, aggression, and leadership), and psychological well-being. The evidence on gender differences in variance is summarized. The final sections explore applications of intersectionality and directions for future research.
This paper presents a novel approach for measuring multi-shapes degrees of similarities. A new shape transformation concept is suggested through mapping the closed boundary of the shape using ...unfolded process into one-to-one equivalent graph (or signal) where ample number of approaches for similarity testing can be applied. The degree of similarity is then measured by calculating the discrepancies between each of the two transformed unfolded-graphs autocorrelation functions. The proposed method is also effective in applying clustering technique for clustering groups of shapes into three hierarchical similarity levels depending on their mutual degree of similarity. The suggested similarity method handles two categories of shapes: geometric and non-geometric. Unlike other well-known techniques in the subject of machine learning and deep learning, the presented method represents a powerful analytical-based technique for similarity analysis of both regular and irregular shapes regardless of size or orientation, and in effectively handling compound or multi-shapes degrees of similarities. The results of testing the approach on selected datasets have successfully demonstrated the great effectiveness of the developed technique in yielding output multi-shape degrees of similarities in new graphical and comprehensive forms. Finally, it is pointed out that the new approach will have many potential real-life applications such as in industry, medicine, biology, security, and authentications.
Since the establishment of the first biomedical ontology Gene Ontology (GO), the number of biomedical ontology has increased dramatically. Nowadays over 300 ontologies have been built including ...extensively used Disease Ontology (DO) and Human Phenotype Ontology (HPO). Because of the advantage of identifying novel relationships between terms, calculating similarity between ontology terms is one of the major tasks in this research area. Though similarities between terms within each ontology have been studied with in silico methods, term similarities across different ontologies were not investigated as deeply. The latest method took advantage of gene functional interaction network (GFIN) to explore such inter-ontology similarities of terms. However, it only used gene interactions and failed to make full use of the connectivity among gene nodes of the network. In addition, all existent methods are particularly designed for GO and their performances on the extended ontology community remain unknown.
We proposed a method InfAcrOnt to infer similarities between terms across ontologies utilizing the entire GFIN. InfAcrOnt builds a term-gene-gene network which comprised ontology annotations and GFIN, and acquires similarities between terms across ontologies through modeling the information flow within the network by random walk. In our benchmark experiments on sub-ontologies of GO, InfAcrOnt achieves a high average area under the receiver operating characteristic curve (AUC) (0.9322 and 0.9309) and low standard deviations (1.8746e-6 and 3.0977e-6) in both human and yeast benchmark datasets exhibiting superior performance. Meanwhile, comparisons of InfAcrOnt results and prior knowledge on pair-wise DO-HPO terms and pair-wise DO-GO terms show high correlations.
The experiment results show that InfAcrOnt significantly improves the performance of inferring similarities between terms across ontologies in benchmark set.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
With the development of smart grid technologies, residential and commercial loads have large potentialities to participate in demand response (DR) programs. This makes the data dimension reduction ...techniques and classification processing critical for the success of DR development. A novel load profile clustering method is proposed for load data classification which is based on the information entropy, piecewise aggregate approximation, and spectral clustering (SC). The variable temporal resolution technique is presented to model typical daily load datasets, and then an improved SC based on multi-scale similarities of distance and shape characteristics is proposed for clustering to obtain reasonable load classification. A case study with one hundred of commercial heating, ventilation, and air conditioning data analysis illustrates the approach. The results prove that the proposed method is feasible in terms of data dimension reduction, reasonable profile selection and classification, and the operation stability.
In recent years, the incidence of cancers is continuously increasing in young adults. Early-onset cancer (EOC) is usually defined as patients with cancers under the age of 50, and may represent a ...unique subgroup due to its special disease features. Overall, EOCs often initiate at a young age, present as a better physical performance but high degree of malignancy. EOCs also share common epidemiological and hereditary risk factors. In this review, we discuss several representative EOCs which were well studied previously. By revealing their clinical and molecular similarities and differences, we consider the group of EOCs as a unique subtype compared to ordinary cancers. In consideration of EOC as a rising threat to human health, more researches on molecular mechanisms, and large-scale, prospective clinical trials should be carried out to further translate into improved outcomes.
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•EOCs are considered as a unique subtype compared to other cancers due to clinical and molecular similarities and differences.•EOCs often share common risk factors, present as a better physical performance but high degree of malignancy.•More researches on molecular mechanisms, and large-scale, prospective clinical trials should be carried out.
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