The purpose of the startup approach is to find an appropriate course of action that adds value to the economy’s development. This study is aimed to determine the effect of the lean startup approach with mediating effect of business coaching to foster innovative work behavior in women entrepreneurs. Additionally, the study also examines the moderating effect of age on the lean startup approach and innovative work behavior. A quantitative approach was employed. The findings show that the relationship between the lean (...) startup approach and innovative work behavior is significant. Moreover, the findings also revealed a significant mediating effect of business coaching and moderating effect of age. This research encourages practitioners and scholars to deal with women entrepreneurship incubation initiatives in the lean startup methodology. Furthermore, this study also leads to a deeper understanding of women’s ideas for business exploration, growth, and implementation. The study contends that guidelines and directives are critical for creative entrepreneurial behavior. (shrink)

We show that the U.S. anti-discriminatory laws prohibiting discrimination in the workplace based on sexual orientation and gender identity identities) spur innovation, which ultimately leads to higher firm performance. We use the Human Rights Campaign’s Corporate Equality Index of 398 U.S. firms between 2011 and 2014, and find a significantly positive relationship between CEI and firm innovation. We also find that an interacting effect of CEI and firm innovation leads to higher firm performance. We use our understanding of Rawls’ Theory (...) of Justice and stakeholder theory to show that firms with workplace diversity policies are likely to be more innovative and perform better than those without such policies. Our results are robust to endogeneity, reverse causality and simultaneity issues. Our results will trigger debate in similar markets around the globe on the economic benefits of LGBT workplace diversity policies for firms. (shrink)

Online forums have become the main source of knowledge over the Internet as data are constantly flooded into them. In most cases, a question in a web forum receives several responses, making it impossible for the question poster to obtain the most suitable answer. Thus, an important problem is how to automatically extract the most appropriate and high-quality answers in a thread. Prior studies have used different combinations of both lexical and nonlexical features to retrieve the most relevant answers from (...) discussion forums, and hence, there is no standard/general set of features that could be effectively used for relevant answer/reply post classification. However, this study proposed an answer detection model that is exclusively relying on lexical features and employs a random forest classifier for classification of answers in discussion boards. Experimental results showed that the proposed answer detection model outperformed the baseline technique and other state-of-the-art machine learning algorithms in terms of classification accuracy on benchmark forum datasets. (shrink)

When the Taliban destroyed the famous statues of the Buddha in the Bamiyan Valley in Afghanistan more than a decade ago, the outrage of the global community, including that of prominent Muslim religious leaders, was matched perhaps only by the pious euphoria of Afghanistan’s hardliners. They had finally succeeded in removing visible signs of idolatry from their landscape, and fulfilled, at least in their own eyes, a long overdue religious mission. In the words of the Taliban leader Mullah Omar, “Muslims (...) should be proud to destroy idols. Our destroying them was an act of praise for God.”1Yet such extreme acts of puritanical iconoclasm at the hands of Muslim fundamentalists, at least within modern history, have more.. (shrink)

The doctrine of sunyata, or emptiness, is the cornerstone of Buddhist metaphysics. This article explores the doctrine as elaborated by Nagarjuna, as it developed in Mahayana Buddhism and extended into Chinese Hua-Yen teachings. It is the key to understanding the relationship between the discontinuous and continuous aspects of reality, the inter-penetration and identity of “emptiness” and phenomena, the cosmic permeation of Buddhahood, and the role of the Bodhisattva.

The article examines the nature of tawba, usually translated as ‘repentance’, in the thought of Abū Țālib al-Makkī . Makkī’s most comprehensive discussion of this topic appears in the thirty-second chapter of his Qūt al-qulūb , one of the most widely reads works of the early Sufi tradition. It is the longest single sustained treatment of tawba, written from the perspective of Sufi spiritual psychology, currently available to us from the first four centuries of Islam. By drawing on Revelation as (...) well as the earlier Sufi tradition he is heir to, Makkī delineates certain conditions which have to be met in order for tawba to be sound. The article explores Makkī’s treatment of these conditions as well as their relation to notions of tawba in the broader Islamic tradition. (shrink)

The article presents an analysis of Ibn al-ʿArabī’s treatment of fasting and hunger as it appears in chapters 106 and 107 of al-­Futūḥāt al-­makkiyya. In the process of examining this very short section of the encyclopedic text, the essay both draws out the deeper theological significance of hunger and fasting and highlights the virtues and trappings of the spiritual exercise in the mystic’s thought. An attempt is also made to situate some of Ibn al-ʿArabī’s ideas within the broader context of (...) the earlier Sufi tradition to which he was heir. (shrink)

Existing work in the field of business ethics has explored how concepts in philosophy and other disciplines can be applied to blame at work, and considers blame’s potential impact on organisations and their employees. However, there is little empirical evidence of organisational blaming practices and their effects. This article presents an analysis of interviews with twenty-seven employees from a range of occupations, exploring their experience of blame, its rationale and impact. A diversity of blaming practices and perspectives is revealed, and (...) in making sense of these the authors draw on recent theoretical developments—Skarlicki, Kay, Aquino, and Fushtey’s concept of ‘swift-blame,’ and Fricker’s notion of ‘communicative blame.’ The study also reveals a tension between a desire to avoid ‘blaming’ on the one hand, and a need for ‘accountability,’ on the other, and the authors explore the implications of the findings for organisations in seeking to ‘manage’ blame. (shrink)

Nowadays, online product reviews have been at the heart of the product assessment process for a company and its customers. They give feedback to a company on improving product quality, planning, and monitoring its business schemes in order to increase sale and gain more profit. They are also helpful for customers to select the right products in less effort and time. Most companies make spam reviews of products in order to increase the products sales and gain more profit. Detecting spam (...) product reviews is a challenging issue in NLP. Numerous machine learning approaches have attempted to detect and classify the product reviews as spam or nonspam. However, in order to improve the classification accuracy, this study has introduced an ensemble machine learning model that combines predictions from multilayer perceptron, K-Nearest Neighbour, and Random Forest and predicts the outcome of the review as spam or real, based on the majority vote of the contributing models. In order to accomplish the task of spam review classification, the proposed ensemble and other benchmark boosting approaches are tested with 25 statistical features extracted from mobile application reviews of Yelp Dataset. Then, three different selection techniques are exploited to diminish the feature space and filter out the top 10 optimal features. The effectiveness of the proposed ensemble, the individual models, and other benchmark boosting approaches is again evaluated with 10 optimal features in terms of classification accuracy. Experimental outcomes illustrate that the proposed ensemble model outperformed the individual classifiers and state-of-the-art boosting approaches like Generalized Boost Regression Model, Extreme Gradient Boost, and AdaBoost Regression Model in terms of classification accuracy. (shrink)

This paper examines the effect of state-level culture in the US on the adoption of firms’ workplace diversity policies. Using firm-level panel data over the period 2011–2014, we document that firms in highly individualistic states are less likely to adopt workplace diversity policies, which in turn negatively affects firm performance. Our results are robust to alternative variables and econometric specifications. Our findings provide insights into the contemporary debate on the economic aspects of workplace diversity policies for firms operating in different (...) cultural backgrounds. (shrink)

In step with rapid advancements in computer vision, vehicle classification demonstrates a considerable potential to reshape intelligent transportation systems. In the last couple of decades, image processing and pattern recognition-based vehicle classification systems have been used to improve the effectiveness of automated highway toll collection and traffic monitoring systems. However, these methods are trained on limited handcrafted features extracted from small datasets, which do not cater the real-time road traffic conditions. Deep learning-based classification systems have been proposed to incorporate the (...) above-mentioned issues in traditional methods. However, convolutional neural networks require piles of data including noise, weather, and illumination factors to ensure robustness in real-time applications. Moreover, there is no generalized dataset available to validate the efficacy of vehicle classification systems. To overcome these issues, we propose a convolutional neural network-based vehicle classification system to improve robustness of vehicle classification in real-time applications. We present a vehicle dataset comprising of 10,000 images categorized into six-common vehicle classes considering adverse illuminous conditions to achieve robustness in real-time vehicle classification systems. Initially, pretrained AlexNet, GoogleNet, Inception-v3, VGG, and ResNet are fine-tuned on self-constructed vehicle dataset to evaluate their performance in terms of accuracy and convergence. Based on better performance, ResNet architecture is further improved by adding a new classification block in the network. To ensure generalization, we fine-tuned the network on the public VeRi dataset containing 50,000 images, which have been categorized into six vehicle classes. Finally, a comparison study has been carried out between the proposed and existing vehicle classification methods to evaluate the effectiveness of the proposed vehicle classification system. Consequently, our proposed system achieved 99.68%, 99.65%, and 99.56% accuracy, precision, and F1-score on our self-constructed dataset. (shrink)

With the increase in market competition and dynamic work environment, work overload seems to have become a common issue suffered by almost every employee. Overload usually results in not only poor health conditions but also mental circumstances. These problems then become a threat to the organizations in the form of poor performance and lack of ability to reach standards. Workplace spirituality is one way to deal with stressful overload conditions. This research deals with the study of moderating affects of workplace (...) spirituality on job overload and employee’s satisfaction relationship. Having large piles of work in given targeted time results in employees becoming stressed out from their work as well as their organization. The motive of their job becomes to achieve targets and diminish the creativity within the employees. Workplace spirituality basic dimensions mentioned in this research help one achieve these targets and help employees cope with the symptoms caused by work overload. The research includes three variables, workplace spirituality, job overload, and job satisfaction. The samples of 76 respondents were asked to fill the questionnaire on all the three variables. The final results show interestingly different results then, as conceptualized according to theory. Workplace spirituality also showed to have quite an impact on job satisfaction. (shrink)

The robustness of a health system can often be assessed by its response to unpredictable circumstances that demand resourcefulness and resilience. The ongoing COVID-19 pandemic has similarly challe...

BackgroundIn Pakistan, drug promotion practices, ethical or unethical, have rarely been in the spotlight. We aimed to assess the perception and barriers of medical representatives (MRs) and doctors (MDs) regarding ethical promotion of pharmaceuticals in Pakistan.MethodsA cross sectional survey was conducted in seven major cities of Pakistan for 6-months period. Self-administered questionnaire was used for data collection. Logistic regression and five-point Likert scale scoring was used to estimate the perceptions and barriers.ResultsCompared to national companies (NCs), the medical representatives (MRs) of (...) multinational companies (MNCs) strongly believed that their companies follow World Health Organization (WHO) (OR; 5.31, p = 0.0005), International Federation of Pharmaceutical Manufacturers & Associations (IFPMA) (OR; 6.45, p = 0.0005) and national codes of ethics (OR; 5.84, p = 0.0005). MNCs trained their MRs (OR; 6.68, p = 0.0005), provide accurate and valid scientific data (OR; 4.01, p = 0.007) with adequate system of accountability and controls on product samples (OR; 1.96, p = 0.047), while, NCs sponsor social or entertainment activities, seminars and conferences, and all sort of facilitation in form of gifts of their choice and clinic renovation for medical doctors (MDs). MDs perceptions were similar to MRs mentioned above, yet strongly agreed that companies offer cash payments or equivalents to MDs. The MRs of NCs/mncs and MDs agreed/strongly agreed that no external accountability, profiteering, pressure on sale targets, job insecurity, condoning unethical promotion by high-ups’ and business promotion by junior MDs were the predominant barriers.ConclusionIn conclusion, MRs of MNCs and MDs believed that MNCs follow certain codes of ethics in the promotion of pharmaceuticals, while NCs tend to be more profit oriented and even condone unethical promotion. All stakeholders, MRs, MDs and companies, might pose certain barriers, intentionally or unintentionally, in ethical promotion. (shrink)

Nazariyat, Journal for the History of Islamic Philosophy and Sciences, issued twice a year in English and Turkish (Nazariyat İslam Felsefe ve Bilim Tarihi Araştırmaları Dergisi), is a refereed international journal. It publishes original studies, critical editions of classical texts and book reviews on Islamic philosophy, kalām, theoretical aspects of Sufism and the history of sciences. The goal of Nazariyat is to contribute to the discovery, examination and reinterpretation of the theoretical traditions in the history of Islamic thought, by giving (...) special attention to the post-classical period of it. **ISSN: 2148-8088 E-ISBN: 2547-9415**. (shrink)

Recently the World Health Organization has highlighted the need to strengthen mental health systems following emergencies, including natural and manmade disasters. Mental health services need to be informed by culturally attuned evidence that is developed through research. Therefore, there is an urgent need to establish rigorous ethical research practice to underpin the evidence-base for mental health services delivered during and following emergencies.

Manufacturing companies in today's industrial world are seeking to use the new manufacturing process methods. The primary goal of corporations is to achieve optimum production while deploying minimal capital. The fundamental purpose of this study is to examine the influence of various lean manufacturing practices on the sustainability performance of companies and the mediating role of green supply chain management. The data was gathered using questionnaires from 250 Pakistani manufacturing firms and analyzed using AMOS 25. Results demonstrate that process and (...) equipment, product design, supplier relationships, and customer relationships significantly affect sustainable performance. It is also recognized that Green Supply Chain Management mediates the interaction between HR processes, product design, supplier relationship, customer relationship, and environmental performance. The findings of this study will enable managers and decision-makers of manufacturing companies to increase sustainable efficiency and reduce waste through the use of lean manufacturing and GSCM implementation. (shrink)

One of the most important issues in contemporary epistemology is eliminating justification or replacing it by another factor in the structure of knowledge. The main problem in Virtue based epistemology that suggested by Ernes Sosa is the definition of knowledge structure. In this approach, the innovation of a new concept of the third factor in the structure of knowledge and replacing it with the justification is done in three stages. These stages are; criticizing and eliminating justification in its internalist meaning, (...) removing externalist problems and innovating apt belief instead of justified belief. Intellectual virtue and epistemic perspective are two key concepts that provide essential situation for this replacement. (shrink)

This paper aims to introduce a robust framework for forecasting demand, including data preprocessing, data transformation and standardization, feature selection, cross-validation, and regression ensemble framework. Bagging ), boosting and extreme gradient boosting regression ), and stacking are employed as ensemble models. Different machine learning approaches, including support vector regression, extreme learning machine, and multilayer perceptron neural network, are adopted as reference models. In order to maximize the determination coefficient value and reduce the root mean square error, hyperparameters are set using (...) the grid search method. Using a steel industry dataset, all tests are carried out under identical experimental conditions. In this context, STACK1 and STACK2 models provided better performance than other models. The highest accuracies of R2 of 0.97 and 0.97 are obtained using STACK1 and STACK2, respectively. Moreover, the rank according to performances is STACK1, STACK2, XGBR, GBR, RFR, MLP, ELM, and SVR. As it improves the performance of models and reduces the risk of decision-making, the ensemble method can be used to forecast the demand in a steel industry one month ahead. (shrink)

Acute Myeloid Leukemia is a kind of fatal blood cancer with a high death rate caused by abnormal cells’ rapid growth in the human body. The usual method to detect AML is the manual microscopic examination of the blood sample, which is tedious and time-consuming and requires a skilled medical operator for accurate detection. In this work, we proposed an AlexNet-based classification model to detect Acute Myeloid Leukemia in microscopic blood images and compared its performance with LeNet-5-based model in Precision, (...) Recall, Accuracy, and Quadratic Loss. The experiments are conducted on a dataset of four thousand blood smear samples. The results show that AlexNet was able to identify 88.9% of images correctly with 87.4% precision and 98.58% accuracy, whereas LeNet-5 correctly identified 85.3% of images with 83.6% precision and 96.25% accuracy. (shrink)

Text and Interpretation: Imam Jaʿfar al-Ṣādiq and His Legacy in Islamic Law. By Hossein Modarressi. Cambridge, MA: Program in Islamic Law, Harvard Law SchooL, 2022. Pp. v + 451. $60, £48.95, €54.

With the development of wireless technology, two basic wireless network models that are commonly used, known as infrastructure and wireless ad hoc networks, have been developed. In the literature, it has been observed that channel contention is one of the main reasons for packet drop in WANETs. To handle this problem, this paper presents a routing protocol named CCBR. CCBR tries to determine a least contended path between the endpoints to increase packet delivery ratio and to reduce packet delay and (...) normalized routing overhead. Moreover, throughout the active data section, each intermediate node computes its channel contention value. If an intermediate node detects an increase in channel contention, it notifies the source node. Then the source node determines another least contended route for transmission. The advantages of CCBR are verified in our NS2-based performance study, and the results show that CCBR outperforms ad hoc on-demand distance vector in terms of packet delivery ratio, end-to-end delay, and routing overhead by 4% to 9%. (shrink)

In a communication network with a source node, a multicast tree is defined as a tree rooted at the source node and all its leaves being recipients of the multicast originating at the source. The tree or bandwidth cost is normally measured by its utilization of tree links along with the quality of service measures such as delay constraint and end-to-end delay. However, if nodes are allowed to join or leave the multicast group at any time during the lifetime of (...) the multicast connection, then the problem is known as dynamic multicast routing problem. In this article, we combine a greedy approach with static multicast routing using Tabu Search to find a low-cost dynamic multicast tree with desirable QoS parameters. The proposed algorithm is then compared with several static multicast routing algorithms. The simulation results show that, on a large number of events, i.e., where nodes are leaving or joining, the proposed algorithm is able to find multicast trees of lower cost and more desirable QoS properties. (shrink)

Seasonal outbreaks have several different periods that occur primarily during winter in temperate regions, while influenza may occur throughout the year in tropical regions, triggering outbreaks more irregularly. Similarly, dengue occurs in the star of the rainy season in early May and reaches its peak in late June. Dengue and flu brought an impact on various countries in the years 2017–2019 and streaming Twitter data reveals the status of dengue and flu outbreaks in the most affected regions. This research work (...) presents that Social Media Analysis can be used as a detector of the epidemic outbreak and to understand the sentiment of social media users regarding various diseases. Providing awareness about seasonal outbreaks through SMA is an effective approach for researchers and healthcare responders to detect the early outbreaks. The proposed model aims to find the sentiment about the disease in tweets, and the seasonal outbreaks-related tweets are classified into two classes as disease positive and disease negative. This work proposes a machine-learning-based approach to detect dengue and flu outbreaks in social media platform Twitter, using four machine learning algorithms: Random Forest, K-Nearest Neighbor, Support Vector Machine, and Decision Tree, with the help of Term Frequency and Inverse Document Frequency. For experimental analysis, two datasets are analyzed individually. The experimental results show that the RF classifier has outperformed the comparison models in terms of improved accuracy, precision, recall, F1-measure, and Receiver Operating Characteristic curve. The proposed work offers favorable performance with total precision, accuracy, recall, and F1-measure ranging from 84% to 88% for conventional machine learning techniques. (shrink)

Emotion-based sentimental analysis has recently received a lot of interest, with an emphasis on automated identification of user behavior, such as emotional expressions, based on online social media texts. However, the majority of the prior attempts are based on traditional procedures that are insufficient to provide promising outcomes. In this study, we categorize emotional sentiments by recognizing them in the text. For that purpose, we present a deep learning model, bidirectional long-term short-term memory, for emotion recognition that takes into account (...) five main emotions. We use our experimental assessments on the emotion dataset to accomplish the emotion categorization job. The datasets were evaluated and the findings revealed that, when compared to state-of-the-art methodologies, the proposed model can successfully categorize user emotions into several classifications. Finally, we assess the efficacy of our strategy using statistical analysis. This research’s findings help firms to apply best practices in the selection, management, and optimization of policies, services, and product information. (shrink)

Efficient community detection in a complex network is considered an interesting issue due to its vast applications in many prevailing areas such as biology, chemistry, linguistics, social sciences, and others. There are several algorithms available for network community detection. This study proposed the Sigmoid Fish Swarm Optimization algorithm to discover efficient network communities. Our proposed algorithm uses the sigmoid function for various fish moves in a swarm, including Prey, Follow, Swarm, and Free Move, for better movement and community detection. The (...) proposed SiFSO algorithm’s performance is tested against state-of-the-art particle swarm optimization algorithms in Q-modularity and normalized mutual information. The results showed that the proposed SiFSO algorithm is 0.0014% better in terms of Q-modularity and 0.1187% better in terms of NMI than the other selected algorithms. (shrink)

Web search engines usually keep users’ profiles for multiple purposes, such as result ranking and relevancy, market research, and targeted advertisements. However, user web search history may contain sensitive and private information about the user, such as health condition, personal interests, and affiliations that may infringe users’ privacy since a user’s identity may be exposed and misused by third parties. Numerous techniques are available to address privacy infringement, including Private Information Retrieval protocols that use peer nodes to preserve privacy. Previously, (...) we have proved that PIR protocols are vulnerable to the QuPiD Attack. In this research, we proposed NN-QuPiD Attack, an improved version of QuPiD Attack that uses an Artificial Neural Network based model to associate queries with their original users. The results show that the NN-QuPiD Attack gave 0.512 Recall with the Precision of 0.923, whereas simple QuPiD Attack gave 0.49 Recall with the Precision of 0.934 with the same data. (shrink)

Currently, there is an increasing trend in the organizations towards examining the artificial intelligence and nonartificial intelligence for the innovation and success of the new product, as well as getting the intentions of the upcoming researchers. Thus, the purpose of the ongoing study is to examine the role of artificial and nonartificial intelligence in the new product success along with the moderating role of new product innovation in the manufacturing organizations of China. The quantitative methods have been followed by the (...) study and gathered the responses from the respondents using questionnaires, and analysis has been conducted by using the smart-PLS. The results exposed that artificial intelligence and nonartificial intelligence have positive and significant nexus with the new product success. The outcomes also revealed that the new product innovation significantly moderated the links among the nonartificial intelligence and new product success, but it insignificantly moderated the links among the artificial intelligence and new product success in the manufacturing organizations of China. These findings have provided the guidelines to the manufacturing companies and their policies developing authorities that they should be developed and implement the suitable policies regarding the adoption of artificial intelligence and nonartificial intelligence that enhance the success of the new product, which ultimately enhances the success of the organization. (shrink)

Nazariyat, Journal for the History of Islamic Philosophy and Sciences, issued twice a year in English and Turkish (Nazariyat İslam Felsefe ve Bilim Tarihi Araştırmaları Dergisi), is a refereed international journal. It publishes original studies, critical editions of classical texts and book reviews on Islamic philosophy, kalām, theoretical aspects of Sufism and the history of sciences. The goal of Nazariyat is to contribute to the discovery, examination and reinterpretation of the theoretical traditions in the history of Islamic thought, by giving (...) special attention to the post-classical period of it. **ISSN: 2148-8088 E-ISBN: 2547-9415**. (shrink)

Is translation of a particular concept from one religious-linguistic tradition into another possible? If so, how much precision and nuance is possible in translation? Even if the problem of translating between religious-linguistic traditions is removed, we are still confronted with the question of how a particular concept is understood differently across vast stretches of time and space within a particular tradition. Atif Khalil's Repentance and the Return to God: Tawba in Early Sufism addresses these fundamental questions in a particularly (...) salient manner. Khalil's object of analysis is the commonplace human experience of contrition, repentance and atonement and the consequences of transgression. More specifically... (shrink)

Repentance and the Return to God: Tawba in Early Sufism. By Atif Khalil. Albany, NY: State University of New York Press, 2018. Pp. xi + 260. $95 ; $32.95.

Dans les années 2000, Paul Ardenne avec l'art contextuel et Nicolas Bourriaud avec le concept d'esthétique relationnelle, donnaient forme à un nouvel ensemble de pratiques artistiques participatives. Qu'en est-il aujourd'hui de cette activité qui ne vise pas tant à produire des objets que des relations humaines? En donnant la parole à des artistes, des designers, des chercheurs de disciplines associées pour évoquer les questionnements qui sont les leurs, dans le cadre de la plate-forme de recherche Artem (ARt, TEchnologie, Management), ce (...) livre montre comment ces pratiques débordent désormais le champ de l'art et développent une nouvelle conception de la créativité où être créatif n'est pas seulement renouveler un ensemble de produits ou de gestes, mais aussi repenser les milieux auxquels ces produits sont destinés et au sein desquels ils sont conçus, posant les bases d'une nouvelle individuation individuelle et sociale. (shrink)

La nature fait aujourd'hui l'objet d'une prise de conscience écologique : une impulsion cependant trans-séculaire qui peut en fait inciter à la méditation, s'inscrire dans un rapport à la philosophie, voire au mysticisme. Cet ouvrage traite de la production artistique, littéraire de cinq artistes religieux par vocation (Léon Boudal, Sabine Desvallières, Franz Stock, Émile Legault et Dom Robert) engagés dans un processus créatif prenant appui justement sur un rapport au milieu naturel. Acteurs d'une société imprégnée de mutations socioculturelles, tous les (...) cinq ont été à la recherche d'une esthétisation de la nature que leur connaissance affinée de la Genèse a sacralisée. L'auteure analyse alors pour chacun d'eux la part de dimension esthétique du sacré et la part de subjectivité personnelle (conditionnée par le vécu, l'éducation, les valeurs sociales) en matière de perception esthétique de cette nature, de leur approche de l'Art, déterminant l'intérêt créatif de leurs productions respectives"--Page 4 of cover. (shrink)