In this paper, according to the perspective of customers and products, by using clustering analysis and association rule technology, this paper proposes a cross-marketing model based on an improved sequential pattern mining algorithm, where an improved algorithm AP is applied. The algorithm can reduce the time cost of constructing a projection database and the influence of the increase of support on the algorithm efficiency. The improved idea is that when the first partition is used to generate the projection database, (...) the number of itemsets in the projection database is sorted from small to large, and when the second partition is used, the sequence patterns are generated directly from the mined sequence patterns, so as to reduce the construction of the database. The experimental results show that this method can quickly mine the effective information in complex data sets, improve the accuracy and efficiency of data mining, and occupy less memory consumption, which has good theoretical value and application value. (shrink)

The Automated External Defibrillator (AED) is an intuitive device used by witnesses of an incident without medical training in cases of sudden cardiac arrest. Its operation consists in delivering an electrical pulse to the cardiac conduction system, as a result of which normal heart rate is restored. The lack of awareness in society concerning the usefulness of the device and the inadequate deployment of AEDs result in their too infrequent application by witnesses of incidents. The aim of this paper is (...) to verify whether cluster analysis is the appropriate statistical method to determine the appropriate deployment of AED devices on the basis of cases of sudden cardiac arrest in out-of-hospital conditions. The initial cluster analysis showed the validity of using the method in question for planning the appropriate locations of AEDs. (shrink)

Part of a symposium devoted to ‘Prediction, Understanding, and Medicine’, in which Alex Broadbent argues that the nature of medicine is determined by its competences, i.e., which things it can do well. He argues that, although medicine cannot cure well, it can do a good job of enabling people not only to understand states of the human organism and of what has caused them, but also to predict future states of it. From this Broadbent concludes that medicine is (at least (...) in part) essentially a practice of understanding and predicting, not curing. In reply to this bold position, I mount two major criticisms. First, I maintain that the reasons Broadbent gives for doubting that medicine can cure provide comparable reason for doubting that medicine can provide an understanding; roughly, the best explanation of why medicine cannot reliably cure is that we still lack much understanding of health and disease. Second, I object to the claim that a practice is medical only if it facilitates understanding and prediction. Although Broadbent has brought to light certain desirable purposes of medicine that are under-appreciated, my conclusion is that he has not yet provided enough reason to think that understanding and prediction are essential to it. Instead of supposing that medicine has an essence, in fact, I suggest that its nature is best understood in terms of a property cluster. (shrink)

If connectionism is to be an adequate theory of mind, we must have a theory of representation for neural networks that allows for individual differences in weighting and architecture while preserving sameness, or at least similarity, of content. In this paper we propose a procedure for measuring sameness of content of neural representations. We argue that the correct way to compare neural representations is through analysis of the distances between neural activations, and we present a method for doing so. (...) We then use the technique to demonstrate empirically that different artificial neural networks trained by backpropagation on the same categorization task, even with different representational encodings of the input patterns and different numbers of hidden units, reach states in which representations at the hidden units are similar. We discuss how this work provides a rebuttal to Fodor and Lepore's critique of Paul Churchland's state space semantics. (shrink)

The continuous increase of carbon emissions is a serious challenge all over the world, and many countries are striving to solve this problem. Since 2020, a widespread lockdown in the country to prevent the spread of COVID-19 escalated, severely restricting the movement of people and unnecessary economic activities, which unexpectedly reduced carbon emissions. This paper aims to analyze the carbon emissions data of 30 provinces in the 2020 and provide references for reducing emissions with epidemic lockdown measures. Based on the (...) method of time series visualization, we transform the time series data into complex networks to find out the hidden information in these data. We found that the lockdown would bring about a short-term decrease in carbon emissions, and most provinces have a short time point of impact, which is closely related to the level of economic development and industrial structure. The current results provide some insights into the evolution of carbon emissions under COVID-19 blockade measures and valuable insights into energy conservation and response to the energy crisis in the post-epidemic era. (shrink)

In this article, cluster analysis is used to explore the conflicting results reported when the Defining Issues Test is used to explain moral reasoning ability in business situations. Using a convenience sample, gender, age, work experience, and ethics training were examined to determine their impact on the level of moral reasoning ability as measured by the Defining Issues Test. Using the whole sample, a significant difference was found for average P scores reported for males and females, but no (...) significant differences were found based on age, work experience, and ethics training. However, the sample fell into distinct clusters that identified distinct male and female groupings. While females naturally fell into two distinct high- and low-moral reasoning ability clusters, male clusters were dominated more by work experience and ethics training. Clearly there are other factors mitigating the level of moral reasoning ability for males which require further exploration. The findings suggest that while the P score provides an initial point of comparison, the real benefit to the test is in exploring what is different for males and females in terms of training needs, and the impact of work experience on the moral reasoning ability, and most importantly, how to make ethics training enticing. Recommendations for future research are also discussed. (shrink)

Maintenance of proper health and prevention of diseases of civilization are now significant public health problems. Nutrition is an important factor in the development of youth, as well as the current and future state of health. The aim of the study was to show the benefits of the application of cluster analysis to assess the dietary habits of high school students. The survey was carried out on 1,631 eighteen-year-old students in seven randomly selected secondary schools in Bialystok using (...) a self-prepared anonymous questionnaire. An evaluation of the time of day meals were eaten and the number of meals consumed was made for the surveyed students. The cluster analysis allowed distinguishing characteristic structures of dietary habits in the observed population. Four clusters were identified, which were characterized by relative internal homogeneity and substantial variation in terms of the number of meals during the day and the time of their consumption. The most important characteristics of cluster 1 were cumulated food ration in 2 or 3 meals and long intervals between meals. Cluster 2 was characterized by eating the recommended number of 4 or 5 meals a day. In the 3rd cluster, students ate 3 meals a day with large intervals between them, and in the 4th they had four meals a day while maintaining proper intervals between them. In all clusters dietary mistakes occurred, but most of them were related to clusters 1 and 3. Cluster analysis allowed for the identification of major flaws in nutrition, which may include irregular eating and skipping meals, and indicated possible connections between eating patterns and disturbances of body weight in the examined population. (shrink)

Intrauterine insemination is one of many treatments provided to infertility patients. Many factors such as, but not limited to, quality of semen, the age of a woman, and reproductive hormone levels contribute to infertility. Therefore, the aim of our study is to establish a statistical probability concerning the prediction of which groups of patients have a very good or poor prognosis for pregnancy after IUI insemination. For that purpose, we compare the results of two analyses: Cluster Analysis and (...) Kohonen Neural Networks. The k-means algorithm from the clustering methods was the best to use for selecting patients with a good prognosis but the Kohonen Neural Networks was better for selecting groups of patients with the lowest chances for pregnancy. (shrink)

Mental health is an important basic condition for college students to become adults. Educators gradually attach importance to strengthening the mental health education of college students. This paper makes a detailed analysis and research on college students’ mental health, expounds the development and application of clustering analysis algorithm, applies the distance formula and clustering criterion function commonly used in clustering analysis, and makes a specific description of some classic algorithms of clustering analysis. Based on expounding the (...) advantages and disadvantages of fast-clustering analysis algorithm and hierarchical clustering analysis algorithm, this paper introduces the concept of the two-step clustering algorithm, discusses the algorithm flow of clustering model in detail, and gives the algorithm flow chart. The main work of this paper is to analyze the clustering algorithm of students’ mental health database formed by mental health assessment tool test, establish a data mining model, mine the database, analyze the state characteristics of different college students’ mental health, and provide corresponding solutions. In order to meet the needs of the psychological management system based on the clustering analysis method, the clustering analysis algorithm is used to cluster the data. Based on the original database, this paper establishes the methods of selecting, cleaning, and transforming the data of students’ psychological archives. Finally, it expounds on the application of data mining in students’ psychological management system and summarizes and prospects the implementation of the system. (shrink)

Introduction Adolescents’ physical activity (PA) behavior can be driven by several psychosocial determinants at the same time. Most analyses use a variable-based approach that examines relations between PA-related determinants and PA behavior on the between-person level. Using this approach, possible coexistences of different psychosocial determinants within one person cannot be examined. Therefore, by applying a person-oriented approach, this study examined a) which profiles regarding PA-related psychosocial variables typically occur in female sixth-graders, b) if these profiles deliver a self-consistent picture according (...) to theoretical assumptions, and c) if the profiles contribute to the explanation of PA. Materials and Methods The sample comprised 475 female sixth-graders. Seventeen PA-related variables were assessed: support for autonomy, competence and relatedness in PE as well as their satisfaction in PE and leisure-time; behavioral regulation of exercise (five subscales); self-efficacy and social support from friends and family (two subscales). Moderate-to-vigorous PA was measured using accelerometers. Data were analyzed using the self-organizing maps (SOM) analysis, a cluster analysis including an unsupervised algorithm for non-linear models. Results According to the respective level of psychosocial resources, a positive, a medium and a negative cluster were identified. This superordinate cluster solution represented a self-consistent picture that was in line with theoretical assumptions. The three-cluster solution contributed to the explanation of PA behavior, with the positive cluster accumulating an average of six minutes more moderate-to-vigorous PA per day than the medium cluster and ten minutes more than the negative cluster. Additionally, SOM detected a subgroup within the positive cluster that benefited from a specific combination of intrinsic and external regulations with regard to PA. Discussion The results underline the relevance of the assessed psychosocial determinants of PA behavior in female sixth-graders. The results further indicate that the different psychosocial resources within a given person do not develop independently of one another, which supports the use of a person-oriented approach. In addition, the SOM analysis identified subgroups with specific characteristics, which would have remained undetected using variable-based approaches. Thus, this approach offers the possibility to reduce data complexity without overlooking subgroups with special demands that go beyond the superordinate cluster solution. (shrink)

ObjectiveWe wished to explore Parkinson's disease subtypes by clustering analysis based on the multimodal magnetic resonance imaging indices amplitude of low-frequency fluctuation and gray matter volume. Then, we analyzed the differences between PD subtypes.MethodsEighty-six PD patients and 44 healthy controls were recruited. We extracted ALFF and GMV according to the Anatomical Automatic Labeling partition using Data Processing and Analysis for Brain Imaging software. The Ward linkage method was used for hierarchical clustering analysis. DPABI was employed to compare (...) differences in ALFF and GMV between groups.ResultsTwo subtypes of PD were identified. The “diffuse malignant subtype” was characterized by reduced ALFF in the visual-related cortex and extensive reduction of GMV with severe impairment in motor function and cognitive function. The “mild subtype” was characterized by increased ALFF in the frontal lobe, temporal lobe, and sensorimotor cortex, and a slight decrease in GMV with mild impairment of motor function and cognitive function.ConclusionHierarchical clustering analysis based on multimodal MRI indices could be employed to identify two PD subtypes. These two PD subtypes showed different neurodegenerative patterns upon imaging. (shrink)

The COVID-19 pandemic has already had an enormous impact on numerous aspects of human society such as health, education, economy, business, or work and created favorable conditions for the expansion of teleworking. The aim of the paper is to identify and analyze five teleworking impact factors that affect thewellbeing and productivity of employees. The data were gathered by a quantitative research method through a questionnaire applied to 327 Romanian employees who hold a Bachelor or Master degree. Firstly, they were analyzed (...) and interpreted through a factorial analysis focusing on the five teleworking impact factors. Secondly, the authors carried on cluster analysis, followed by multiple linear regression, using R statistical software. This study shows that there is a plethora of factors that influence the wellbeing and productivity of employees: individual and societal factors, organizational and work-related factors, technological factors, social factors at home, and social factors at work. Also, the cluster analysis brings to light significant differences between various Romanian employees such as: their gender, income, age, education, and city size. (shrink)

Research has demonstrated large differences in the degree to which direct and indirect measures predict each other and variables including behavioural approach and attentional bias. We investigated whether individual differences in the co-variance of “implicit” and “explicit” spider fear exist, and whether this covariation exerts an effect on spider fear-related outcomes. One hundred and thirty-two undergraduate students completed direct and indirect measures of spider fear/avoidance, self-report questionnaires of psychopathology, an attentional bias task, and a proxy Behavioural Approach Task. TwoStep (...) class='Hi'>cluster analysis using implicit and explicit spider fear as criterion variables resulted in three clusters: low explicit/low implicit; average explicit/high implicit; and high explicit/low implicit. Clusters with higher explicit fear demonstrated greater disgust propensity and sensitivity and less willingness to approach a spider. No differences between clusters emerged on anticipatory approach anxiety or attentional bias. We discuss results in terms of dual-systems and cognitive–behavioural models of fear. (shrink)

Music rhythm detection and tracking is an important part of the music comprehension system and visualization system. The music signal is subjected to a short-time Fourier transform to obtain the frequency spectrum. According to the perception characteristics of the human auditory system, the spectrum amplitude is logarithmically processed, and the endpoint intensity curve and the phase information of the peak value are output through half-wave rectification. The Pulse Code Modulation characteristic value is extracted according to the autocorrelation characteristic of the (...) endpoint intensity curve. This article proposes a rhythm detection algorithm based on multipath search and cluster analysis; that is, based on the clustering algorithm, it absorbs the idea of multipath tracking and proposes its own detection and tracking algorithm. It overcomes the weakness of the clustering algorithm that needs to use Musical Instrument Digital Interface auxiliary input to achieve the desired effect. This algorithm completely uses the PCM signal as the input, which is more robust than the clustering algorithm. The whole process is carried out in the time domain, and the amount of calculation is much smaller than the frequency domain calculation of multipath tracking, and the linear relationship with the rhythm of the music is much better than the filter bank algorithm. This algorithm can successfully detect the rhythm of the music with a strong sense of rhythm and can track the specific position of the rhythm point. (shrink)

Societal attitude acceptance can influence the digital transformation in agriculture. Digital technologies, such as robots in dairy farming, can lead to more sustainable, animal welfare-friendly and consumer-oriented milk production. This study used the example of the milking and feeding robots to investigate whether society accepts the use of robots in dairy farming and whether there are differences in society based on perceived risks and opportunities of digitalization in dairy farming and acceptance. To this end, an online-based study was conducted with (...) a total of 1007 citizens in Germany. Overall, the respondents in this study suspect that the use of robots in dairy farming is associated with various risks but also with opportunities for society and for farmers in particular. However, these attitudes are quite heterogeneous. Four clusters could be identified: “proponents of robots”, “indifferent citizens”, “skeptical citizens”, and “critical supporters of robots”. Proponents of robots see only opportunities and little risks, whereas the critical citizens perceive not only opportunities but also many risks of using robots in dairy farming. The indifferent citizens show a rather indifferent attitude, in contrast to the skeptical citizens, who reject the opportunities at the societal level, while they agree with the opportunities of robots for farmers. This research contributes to understanding societal attitudinal acceptance and highlights differences in society that can help inform future decisions about the development and adoption of robots in dairy farming. (shrink)

Breast cancer treatments have multiple adverse effects, including concerns about body appearance and function that are experienced by most patients. Altered body image negatively affects mental health, social, and relationship functioning. While the relationship with a partner is critical for patients’ psychological wellbeing and partners can promote positive body image, limited research has investigated individual and relational factors affecting the experience of both. This cross-sectional study aimed at exploring rates of body image concerns among breast cancer patients, and identifying dyadic (...) profiles among participating dyads. Couples composed by patients who had undergone surgery and their romantic partners were recruited from the Breast Unit of a hospital in northern Italy. Both partners completed measures of personality characteristics, psychological distress, coping flexibility, dyadic coping, and closeness. Body image and adjustment to cancer measures were completed by patients only. K-mean cluster analyses identified 2-cluster solution among patients and partners, respectively. “Active patients” reported low rates of body image concerns, anxious preoccupation, negative dyadic coping, and self-oriented stress communication, compared to “worried patients”. “Comfortable partners” reported lower anxiety and depression, self-oriented negative dyadic coping and closeness than “uncomfortable partners”. Three different dyadic profiles emerged: functional, dysfunctional, and ambivalent. Significant variations by anxiety, depression, and delegating dyadic coping existed. Results indicate there are groups of couples at greater risk for impaired psychological distress and body image concerns, which should be addressed in the context of dyadic psychosocial interventions. (shrink)

Emotional labor generally exists in organization members. Emotional labor will not only affect employees’ interpersonal relationships, but also affect employees’ mental health. Affected by many factors such as the economic environment, they often need to bear multiple pressures. The degree of stress is positively correlated with the depth of the development of the times and people’s education. As mental health research has become the frontier and hot spot in the field of psychology, the role of mental health in the process (...) of employee creativity has been paid more and more attention. Therefore, this paper proposes a study on the causes of employees’ psychological stress based on emotional feature clustering. Based on the clustering of emotional characteristics, this paper analyzes the causes of employees’ mental health stress from an economic perspective. For teams with low level of team openness, with the improvement of team heterogeneity, team task performance shows a slight upward trend. It is clear from the experiment that when the number of experiments reaches 100, the task performance of high atmosphere level is 12.14, while the task performance of low atmosphere level is only 9.89. Therefore, the atmosphere of team employees is very important to team task performance. Through the cluster analysis of employees’ mental health characteristics, it not only increases employees’ spare time life, but also reduces employees’ daily contradictions. It eases the work pressure of employees, and becomes a platform for employees to improve their awareness and a promoter of harmonious employee relations. (shrink)

This paper makes a quantitative analysis of the comprehensive influence of music networks. Firstly, 11 music features are selected from energy, popularity, and other aspects to build a comprehensive evaluation index of music influence, and the PageRank algorithm is used to quantify the music influence. Secondly, the multiobjective logistic regression is used to construct the music similarity measurement model and, combined with music influence and music similarity, to judge whether the influence of different musicians is the actual influence. Thirdly, (...) the influence and similarity of the same music genre and different music genres are analyzed by using the two-way cluster analysis method. Finally, the lasso region is used for feature selection to obtain the change factors in the process of music evolution and analyze the dynamic changes in the process of music development. Therefore, this paper uses network science to build a dynamic network to analyze the similarity of music, the evolution process, and the impact of music on culture, which has certain research significance and practical value in the fields of music, history, social science, and practice. (shrink)

In this paper, we focus on the analysis of Eliezer Yudkowsky’s concept of “coherent extrapolated volition” (CEV) as a response to the need for a post-conventional, persuasive morality that meets the criteria of active trust in the sense of Anthony Giddens, which could be used in the case of autonomous machines. Based on the analysis of the results of the Moral Machine project, we formulate some guidelines for transformation of the idea of a coherent extrapolated volition into the (...) concept of a coherent, extrapolated and clustered volition. The argumentation used in the paper is intended to show that the idea of CEV transformed into its clustered version can be used to build a technically and socially efficient decision-making pattern database for autonomous machines. (shrink)

Abnormal behavior detection of social security funds is a method to analyze large-scale data and find abnormal behavior. Although many methods based on spectral clustering have achieved many good results in the practical application of clustering, the research on the spectral clustering algorithm is still in the early stage of development. Many existing algorithms are very sensitive to clustering parameters, especially scale parameters, and need to manually input the number of clustering. Therefore, a density-sensitive similarity measure is introduced in this (...) paper, which is obtained by introducing new parameters to transform the Gaussian function. Under this metric, the distance between data points belonging to different classes will be effectively amplified, while the distance between data points belonging to the same class will be reduced, and finally, the distribution of data will be effectively clustered. At the same time, the idea of Eigen gap is introduced into the spectral clustering algorithm, and the verified gap sequence is constructed on the basis of Laplace matrix, so as to solve the problem of the number of initial clustering. The strong global search ability of artificial bee colony algorithm is used to make up for the shortcoming of spectral clustering algorithm that is easy to fall into local optimal. The experimental results show that the adaptive spectral clustering algorithm can better identify the initial clustering center, perform more effective clustering, and detect abnormal behavior more accurately. (shrink)

Since the opening of the economy, China’s regional economy has developed rapidly, the overall national strength has been increasing, and the people’s living standards have been continuously improved. The issue of coordinated regional development has become an important issue in today’s society. Genetic algorithm is a kind of prediction algorithm that has developed rapidly in recent years and is widely used. However, when solving engineering prediction problems, there are often problems such as premature convergence and easiness to fall into local (...) optimal solutions. Therefore, on the basis of studying the related theories of genetic algorithm and artificial immune algorithm, this paper uses the advantages of the two algorithms, combines the two algorithms, and proposes an improved algorithm for genetic algorithm-adaptive immune genetic algorithm. Taking genetic algorithm as the basic framework, the operators and selection methods of artificial immune algorithm are integrated. Using the adaptive concept, the formulas of adaptive crossover probability and mutation probability are innovatively designed. Compared with the fixed value of the immune genetic algorithm, the introduction of the adaptive concept can intelligently adjust the optimization process and increase the optimization speed. Considering the double uncertain factors of product market demand and waste product recycling in the remanufacturing supply chain system, the maximization of logistics network operating profit, the minimization of environmental impact, and the maximization of customer satisfaction are the forecast goals. The market demand of uncertain products is effectively controlled through the option contract mechanism, and a multiobjective forecasting model based on the option contract mechanism is established. According to the characteristics of the model, an improved immune genetic algorithm is designed to solve the problem, and the effectiveness of the immune genetic algorithm is verified through an example. (shrink)

In the current digital era, the borders amongst firms are getting blurred when it comes to value creation. Therefore, the traditional configuration of the value chain is frequently replaced by other ones which include the collaborative participation of different agents. Within this context, global value chains, where the value activities are located in different countries, and industrial clusters, which combine competition and cooperation, are attracting a growing attention of both business leaders and scholars in the recent years. Through a bibliometric (...) analysis, this paper disentangles the intellectual and conceptual structure of the research topic of industrial clusters and global value chains. Results show the multidisciplinary character of the topic, including papers published in different areas, such as business, regional studies and world development, as well as its close link with aspects like innovation, regional development, governance or organization. Finally, this study remarks the research lines that could attract more attention in the immediate future. (shrink)

The increasing use of cluster randomised trials in low-resource settings raises unique ethical issues. The Ottawa Statement on the Ethical Design and Conduct of Cluster Randomised Trials is the first international ethical guidance document specific to cluster trials, but it is unknown if it adequately addresses issues in low-resource settings. In this paper, we seek to identify any gaps in the Ottawa Statement relevant to cluster trials conducted in low-resource settings. Our method is to analyse a (...) prototypical cluster trial conducted in a low-resource setting with the Ottawa Statement; to identify ethical issues in the design or conduct of the trial not captured adequately and to make recommendations for issues needing attention in forthcoming revisions to the Ottawa Statement. Our analysis identified six ethical aspects of cluster randomised trials in low-resource settings that require further guidance. The forthcoming revision of the Ottawa Statement should provide additional guidance on these issues: streamlining research ethics committee review for collaborating investigators who are affiliated with other institutions; the classification of lay health workers who deliver study interventions as health providers or research participants; the dilemma experienced by investigators when national standards seem to prohibit waivers of consent; the timing of gatekeeper engagement, particularly when researchers face funding constraints; providing ancillary care in health services or implementation trials when a routine care control arm is known to fall below national standards and defining vulnerable participants needing protection in low-resource settings. (shrink)

Aesthetic emotions are elicited by different sensory impressions generated by music, visual arts, literature, theater, film, or nature scenes. Recently, the AESTHEMOS scale has been developed to facilitate the empirical assessment of such emotions. In this article we report a semantic profile analysis of aesthetic emotion terms that had been used for the development of this scale, using the GRID approach. This method consists of obtaining ratings of emotion terms on a set of meaning facets which represent five components (...) of the emotion process. The aims here were to determine the dimensionality of the GRID features when applied to aesthetic emotions and compare it to published results for emotion terms in general, and to examine the internal organization of the domain of aesthetic emotion terms in order to identify salient clusters of these items based on the similarity of their feature profiles on the GRID. Exploratory Principal Component Analyses suggest a four-dimensional structure of the semantic space consisting of valence, power, arousal, and novelty, converging with earlier GRID studies on large sets of standard emotion terms. Using cluster analyses, 15 clusters of aesthetic emotion terms with similar GRID feature profiles were identified, revealing the internal organization of the aesthetic emotion terms domain and meaningful subgroups of aesthetic emotions. While replication for further languages is required, these findings provide a solid basis for further research and methodological development in the realm of aesthetic emotions. (shrink)

A recent concern in the debate on corporate social responsibility (CSR) in developing countries relates to the tension between demands for CSR compliance found in many global value chains (GVCs) and the search for locally appropriate responses to these pressures. In this context, an emerging and relatively understudied area of interest relates to small firm industrial clusters. Local clusters offer the potential for local joint action, and thus a basis for improving local compliance on CSR through collective monitoring and local (...) governance. This article explores the interrelationship between global governance, exercised through GVC ties, and local governance, via cluster institutions, in ensuring compliance with CSR pressures. It undertakes a comparative analysis of two leading export-oriented football manufacturing clusters in South Asia that have both faced common challenges on child labour. The article shows that both forms vertical and horizontal governance have played a part in shaping the response of the two clusters on child labour. Moreover, these two distinct forms of governance have also led to quite differentiated outcomes in terms of forms of work organization and child labour monitoring. This raises broader questions on how global CSR demands can locally be better embedded and the conditions under which football stitchers labour in these new work forms. (shrink)

Noah Rosenberg et al.'s 2002 article “Genetic Structure of Human Populations” reported that multivariate genomic analysis of a large cell line panel yielded reproducible groupings (clusters) suggestive of individuals' geographical origins. The paper has been repeatedly cited as evidence that traditional notions of race have a biological basis, a claim its authors do not make. Critics of this misinterpretation have often suggested that it follows from interpreters' personal biases skewing the reception of an objective piece of scientific writing. I (...) contend, however, that the article itself to some degree facilitates this misrepresentation. I analyze in detail several verbal and visual features of the original article that may predispose aspects of its racial interpretation; and, tracing the arguments of one philosopher and one popular science writer, I show how these features are absorbed, transformed into arguments for a biological basis of race, and re-attributed to the original. The essay demonstrates how even slight ambiguities can enable the misappropriation of scientific writing, unintentionally undermining the authors' stated circumspection on the relationship between cluster and race. (shrink)

BackgroundSome children appear to not hear well in class despite normal hearing sensitivity. These children may be referred for auditory processing disorder (APD) assessment but can also have attention, language, and/or reading disorders. Despite presenting with similar concerns regarding hearing difficulties in difficult listening conditions, the overall profile of deficits can vary in children with suspected or confirmed APD. The current study used cluster analysis to determine whether subprofiles of difficulties could be identified within a cohort of children (...) presenting for auditory processing assessment.MethodsNinety school-aged children (7–13 years old) with suspected APDs were included in a cluster analysis. All children had their reading, language, cognition and auditory processing assessed. Parents also completed the Children’s Auditory Performance Scale (CHAPS). Cluster analysis was based on tasks where age-norms were available, including word reading (Castles and Coltheart irregular and non-words test), phonological awareness (Queensland University Inventory of Literacy), language [Comprehensive Language of Assessment-4, Comprehensive Assessment of Spoken Language (CASL)], sustained attention (Continuous Performance Test), working memory (digits forward and backward), and auditory processing [Frequency Pattern Test (FPT), Dichotic Digits Test (DDT)]. Hierarchical cluster analysis was undertaken to determine the optimal number of clusters for the data, followed by... (shrink)

This work is devoted to the testing, research and comparative analysis of the most well-known and widely used methods and algorithms for clustering numerical data sets. Multidimensional scaling was applied to evaluate the results of solving the clustering problem by visualizing datasets at all stages of the implementation of the studied algorithms. All algorithms were tested for artificial and real data sets. As a result, for each of the investigated algorithms, the main characteristics were formulated in the form of (...) their relative strengths and weaknesses. Based on the test results, conclusions and recommendations for using these algorithms are formulated. (shrink)

Although the use of the cluster randomized trial (CRT) design to evaluate vaccines, public health interventions or health systems is increasing, the ethical issues posed by the design are not adequately addressed, especially in low- and middle-income country settings (LMICs). To help reveal ethical challenges, qualitative interviews were conducted with key stakeholders experienced in designing and conducting two selected CRTs in Malawi. The 18 interviewed stakeholders included investigators, clinicians, nurses, data management personnel and community workers who were invited to (...) share their experiences related to implementation of CRTs. Data analysis revealed five major themes with ethical implications: (1) The moral obligation for health care providers to participate in health research and its compensation; (2) Suboptimal care services compromising the integrity of CRT; (3) Ensuring scientific validity and withholding care service; (4) Obtaining valid consent and permission for waiver of consent; and (5) Inadequate risk assessment for trial participation. Understanding key ethical issues posed by CRTs in Malawi could improve ethical review and research oversight of this particular study design. (shrink)

The explosion of multiomics data poses new challenges to existing data mining methods. Joint analysis of multiomics data can make the best of the complementary information that is provided by different types of data. Therefore, they can more accurately explore the biological mechanism of diseases. In this article, two forms of joint nonnegative matrix factorization based on the sparse and graph Laplacian regularization method are proposed. In the method, the graph regularization constraint can preserve the local geometric structure of (...) data. L 2,1 -norm regularization can enhance the sparsity among the rows and remove redundant features in the data. First, SG-jNMF1 projects multiomics data into a common subspace and applies the multiomics fusion characteristic matrix to mine the important information closely related to diseases. Second, multiomics data of the same disease are mapped into the common sample space by SG-jNMF2, and the cluster structures are detected clearly. Experimental results show that SG-jNMF can achieve significant improvement in sample clustering compared with existing joint analysis frameworks. SG-jNMF also effectively integrates multiomics data to identify co-differentially expressed genes. SG-jNMF provides an efficient integrative analysis method for mining the biological information hidden in heterogeneous multiomics data. (shrink)

To explore religious orientations, 163 Christians answered the Intrinsic and Extrinsic Religious Orientation and Quest Scales. Cluster analysis showed that Extrinsic Item 2 did not fit in the two- or three-cluster model. One cluster of the two-cluster and one of the three-cluster models were exactly the same and reflected intrinsic, personal religion. The remaining clusters showed why a correlation is found between the Extrinsic and Quest scales and suggest refinements of the scales.

_BMC Medical Ethics_ is an open access journal publishing original peer-reviewed research articles in relation to the ethical aspects of biomedical research and clinical practice, including professional choices and conduct, medical technologies, healthcare systems and health policies. _BMC __Medical Ethics _is part of the _BMC_ series which publishes subject-specific journals focused on the needs of individual research communities across all areas of biology and medicine. We do not make editorial decisions on the basis of the interest of a study or (...) its likely impact. Studies must be scientifically valid; for research articles this includes a scientifically sound research question, the use of suitable methods and analysis, and following community-agreed standards relevant to the research field. Specific criteria for other article types can be found in the submission guidelines. _BMC series - open, inclusive and trusted_. (shrink)

This article contributes to literature on corporate social responsibility exhibited by industrial clusters in developing countries. The authors conceptualize and empirically investigate the role of donor-funded CSR initiatives aimed at promoting collective action by cluster-based small- and medium-sized enterprises. A case study of the Sialkot football-manufacturing cluster in Pakistan indicates that donor-funded support of CSR initiatives in industrial clusters in developing countries may be short-lived, due to the political economy of aid, the national context of CSR implementation, tensions (...) within SME networks, and negative perceptions of CSR by the cluster-based SMEs themselves. The findings and implications of this analysis can inform both research and policy making in this area. (shrink)