Readings in Political Economy is a peer-reviewed scholarly journal dedicated to publishing high-quality academic research that advances knowledge through rigorous theoretical, empirical, and methodological contributions. The journal is indexed in the ABDC Journal Quality List (Category C), reflecting its recognition within the international academic community. Journal Title Readings in Political Economy ISSN (Print) 0079-9874 & 0305-814X Publication Format Online Copyright Holder Journal Journal Ranking ABDC Category C Website https://politonomia.org.ua/rpe/
The Financialization of the Welfare State: Social Impact Bonds, Philanthrocapitalism, and the Privatization of Social Risk
As advanced capitalist economies grapple with the compounding crises of demographic aging, stagnant economic growth, and the structural erosion of the post-war social contract, a new paradigm of public administration has emerged under the banner of "innovative finance." This comprehensive paper provides a critical political economy analysis of the financialization of the welfare state, focusing on the proliferation of Social Impact Bonds (SIBs), pay-for-success contracting, and philanthrocapitalism. We argue that these mechanisms do not represent a neutral, technocratic evolution in public service delivery; rather, they constitute a profound structural shift that transforms systemic social vulnerability—such as homelessness, recidivism, and chronic illness—into highly liquid, yield-generating asset classes for transnational finance capital. By tracking the implementation of social finance frameworks across the United Kingdom, the United States, and Australia from 2015 to 2026, we deconstruct the mechanics of algorithmic risk assessment and datafied social evaluation required to secure investor dividends. The research demonstrates how SIBs operationalize a modern form of accumulation by dispossession, wherein the state socializes the fundamental risks of social reproduction while completely privatizing the financial rewards. Furthermore, we critique the anti-democratic nature of philanthrocapitalism, detailing how mega-foundations bypass public oversight to dictate domestic social policy. The study concludes that delegating the resolution of structural poverty to speculative financial markets inevitably subordinates the universal right to social care to the imperatives of short-term capital accumulation. We outline a radical policy alternative centered on the absolute decommodification of the welfare state, progressive wealth taxation, and the restoration of universal, publicly provisioned social infrastructure.
Copyright (c) 2026 Reading in Political Economy https://creativecommons.org/licenses/by-nc/4.0
The Political Economy of the "Great Decoupling": Strategic Autonomy, Regionalized Supply Chains, and the End of the Neoliberal Global Trade Order
The mid-2020s have definitively marked the end of the era of unfettered, efficiency-driven globalization, giving way to a volatile, multi-polar economic system defined by state-directed strategic autonomy. This comprehensive paper investigates the political economy of the "Great Decoupling"—the systemic, state-led restructuring of transnational production networks away from globally integrated supply chains toward geopolitically bounded, regionalized industrial blocs. We argue that this shift represents a profound contradiction within late-stage capitalism: the subordination of the historic imperative for the lowest-cost global production to the modern security imperative of preventing technological and material dependency on geopolitical rivals. By analyzing the massive, state-subsidized re-industrialization efforts in the United States, the European Union, and China, we deconstruct how the weaponization of trade—through export controls, tariffs, and "friend-shoring"—fundamentally reconfigures the global division of labor. The study provides a critical evaluation of the structural costs of this transition, including the permanent embedding of inflationary pressures, the duplication of industrial infrastructure, and the systematic marginalization of developing nations that cannot navigate this bifurcated trade order. We further critique the "techno-nationalist" paradigm, demonstrating how governments utilize the rhetoric of security to facilitate massive corporate subsidies for domestic oligopolies, while simultaneously eroding the few remaining global environmental and labor standards. The paper concludes that while the era of hyper-globalization is over, the emerging order of managed, regionalized trade holds no inherent promise of stability or equity. We propose a radical macroeconomic alternative centered on the localization of essential production, the democratization of trade governance, and the restoration of international cooperation predicated on ecological and social justice rather than competitive industrial supremacy.
The Political Economy of the "Great Transition": Material Throughput, Ecological Limits, and the Decommodification of the Post-Carbon Social Order
The mid-2020s have confirmed that the climate crisis is not merely a consequence of atmospheric carbon accumulation but a systemic crisis of the capitalist mode of production itself. This expansive paper critiques the prevailing "Green Growth" consensus, which suggests that technological innovation and market-led decarbonization can decouple economic expansion from material destruction. We argue that this framework is a dangerous delusion, failing to account for the fundamental thermodynamic and material limits of a closed planetary system. By analyzing a decade of global mineral extraction trends, energy consumption patterns, and industrial output metrics, we demonstrate that the transition to renewable infrastructure is generating an unprecedented escalation in resource throughput, accelerating the metabolic rift rather than closing it. The study provides a radical deconstruction of the political economy of the "Green Transition," detailing how it functions as a mechanism for the massive expropriation of the Global South’s remaining resource reserves. We examine the rise of "green extractivism," where renewable energy projects in the periphery are utilized to fuel the high-consumption lifestyles of the core. Furthermore, the paper critiques the financialization of ecological mitigation, exposing how carbon markets, ESG metrics, and private equity investments in transition infrastructure function as mechanisms of rent-seeking that prioritize short-term profit over long-term planetary survival. We reject the technocratic paradigm of mere energy substitution, arguing instead for a structural transition toward a post-carbon political economy rooted in degrowth, the absolute decommodification of foundational social services, and the radical democratization of resource governance. In conclusion, we outline a macroeconomic framework for an equitable, low-energy future that prioritizes universal well-being over the imperatives of infinite capital accumulation.
Exploring Factors Shaping Sustainable Human Resource Practices in Different Generation of Employees Performance: A Systematic Literature Review
This study aims to explore the factors affecting sustainable human resource practices from various generations of employees. The used analytical technique is systematic literature review and PRISMA method. For articles to be considered for publication, they are 50 selected articles which correspond to the conditions. The research used the information obtained from google scholar. It is found that the selected 50 articles are from different countries. Moreover, it is found that most of the selected articles were published in 2023. There are various factors that may impact sustainable human resource practices, which are Human Resource Management (HRM), Leadership, sustainable performance, age management, Employee Engagement, Organizational Culture, work attitude and Learning, employee development, health and safety, Motivation, paperless digital process and innovation, Digital Technology, Training, and Empowerment, employee expectation, work engagement, job satisfaction, employee retention, sustainable development goal, etc. This study contributes to existing literature, especially in the field of HR and organization, especially with regard to sustainable human resource practices among different generations of employees. It is found that the variables of the study results may be applied to improve sustainable human resource management.
Comparative Analysis of Supervised and Unsupervised Machine Learning Techniques
Machine Learning (ML) has become one of the most influential technologies in Artificial Intelligence, enabling computers to learn from data and make intelligent decisions with minimal human intervention. Among the various learning paradigms, Supervised Learning and Unsupervised Learning represent the two most widely adopted approaches for solving predictive and exploratory data analysis problems. While supervised learning utilizes labeled datasets to predict predefined outcomes through classification and regression models, unsupervised learning analyzes unlabeled data to discover hidden structures, clusters, and relationships. Understanding the comparative strengths, limitations, and practical applications of these two learning approaches is essential for selecting appropriate machine learning techniques in business, healthcare, finance, manufacturing, cybersecurity, marketing, and scientific research. a comprehensive comparative analysis of supervised and unsupervised machine learning techniques by examining their theoretical foundations, learning mechanisms, commonly used algorithms, performance characteristics, advantages, limitations, and real-world applications. widely adopted supervised learning algorithms, including Linear Regression, Logistic Regression, Decision Trees, Random Forest, Support Vector Machines, Naïve Bayes, K-Nearest Neighbors, and Artificial Neural Networks, alongside popular unsupervised learning techniques such as K-Means Clustering, Hierarchical Clustering, DBSCAN, Principal Component Analysis (PCA), and Association Rule Mining. Furthermore, the paper compares both approaches based on data requirements, learning objectives, computational complexity, interpretability, prediction accuracy, scalability, and business applicability. It also examines emerging trends such as hybrid learning models, semi-supervised learning, deep learning, explainable AI, and automated machine learning that increasingly integrate supervised and unsupervised techniques to improve predictive performance and knowledge discovery.
The Contribution of Digital Transformation to Expanding the Distribution of Insurance Services in Algeria: A Study Covering the Period 1995–2024
This study investigates the extent to which digital transformation has contributed to expanding the distribution of insurance services in Algeria over the period 1995–2024. To examine this relationship, an econometric model was developed and estimated using the Autoregressive Distributed Lag (ARDL) approach. The empirical findings reveal a statistically significant positive association between digital transformation and the development of insurance services. Specifically, a one-unit increase in internet usage is associated with a 0.0027-unit increase in the growth rate of insurance premiums, which serves as a proxy for the level of insurance services. The observed effect can be explained by the ability of digital technologies to improve access to insurance products while enhancing distribution and marketing channels. These improvements have contributed to a noticeable expansion in the volume of written premiums. Moreover, the increase in premiums should not be interpreted solely as a quantitative change; rather, it reflects the broader diffusion of insurance services and their growing accessibility to a wider range of economic agents, including both individuals and business entities. The results further indicate that this positive relationship is reinforced within a macroeconomic environment characterized by controlled inflation, thereby supporting financial stability and strengthening the contribution of the insurance sector to overall economic output.
The Effect of Organizational Culture on Change Management
Organizational culture plays a critical role in shaping the success or failure of change management initiatives in modern organizations. how shared values, beliefs, norms, and behavioral patterns within an organization influence employees’ responses to change and the overall effectiveness of transformation processes. In an era marked by rapid technological advancement, globalization, and evolving market demands, organizations must continuously adapt, making effective change management a strategic necessity. the relationship between organizational culture and change readiness, highlighting how supportive cultures characterized by openness, trust, and innovation facilitate smoother transitions. Conversely, rigid or hierarchical cultures may resist change, leading to employee dissatisfaction, reduced productivity, and potential failure of change initiatives. Key cultural dimensions such as leadership style, communication patterns, employee involvement, and organizational values are analyzed to understand their impact on change implementation. Empirical evidence suggests that organizations with adaptive and learning-oriented cultures are more successful in managing change, as they encourage flexibility, collaboration, and continuous improvement. the importance of aligning change strategies with existing cultural frameworks or, where necessary, transforming organizational culture to support change objectives.
The Reality of Gender Equality in The Management of Joint-Stock Companies According to Algerian Legislation
In embodiment of the principle of gender equality between women and men in the practice of commerce and political rights, as outlined in Article 59 of the Constitution, which advocates for expanding women's representation in elected councils further confirmed by Organic Law No. 12-03 this article aims to explore the extent to which this equality is applied in areas not explicitly addressed by Algerian legislation. Specifically, it examines the management of commercial companies, where men are predominantly appointed and preferred over women. This imbalance has led some legislations to enforce a rule of equality in political rights concerning the appointment of board members in commercial companies. However, this provision is not explicitly stipulated by Algerian lawmakers, which means that the appointment of women in managerial positions remains contingent upon their desire to join and the approval of the General Assembly members. This situation complicates the position of women within these governing bodies.
The Function of Bird Vocalization in Mating and Territory Defense
Bird calls help in courtship and territorial defense, and they are also an integral aspect of bird communication. birdsong and its evolutionary significance, particularly how variations in song structure, frequency, and complexity affect mating success and interactions across species. Birds utilize song as a dual signal—one to entice mates and another to ward off predators. Acoustic studies, field observations, and comparisons of behavior across different bird species led to this discovery. Physical conflict is reduced and energy is conserved when territorial defense is made easier through the use of loud, repetitive noises and species-specific musical signatures. In contrast, a male's condition, genetic fitness, and quality are reflected in his songs, which are often more intricate, melodious, and energy intensive, and which he uses to attract mates. Some musical traits linked with survival, like a broad repertoire, solid pitch, and consistent performance, seem to be preferred by females. Adaptive shifts in song time and frequency can be triggered by environmental factors such as habitat density, ambient noise, and temperature fluctuation, among others.
Corporate Social Responsibility Practices of Business Enterprises: Almarai Saudi Food Industries Company as a Model
Almarai is a leading company in the food industry sector in the Middle East and is widely recognized for its commitment and active engagement in sustainable development and, consequently, corporate social responsibility. Accordingly, the objective of this study is to identify the main corporate social responsibility practices implemented by Almarai. The study adopted the descriptive approach. The findings revealed that Almarai has succeeded in enhancing its reputation and increasing customer trust through numerous initiatives in areas such as health, education, and the environment. The company has demonstrated its commitment to its four key stakeholders (society, customers, employees, and the environment) by establishing programs dedicated to employee welfare and safety, as well as sponsoring numerous events and activities aimed at improving the quality of life in the communities in which it operates, without causing adverse environmental impacts.
Core Strength and Posture Improvement with Pilates for Inactive People
A loss of functional capacity and pain in the musculoskeletal system are the end outcomes of a sedentary lifestyle, which is associated with weak core muscles and poor posture. Pilates exercises, which target these issues head-on by focusing on the core, flexibility, and alignment, have become increasingly popular as of late. the feasibility of a twelve-week Pilates-based exercise program for improving core strength and posture in inactive individuals. Pre- and post-intervention assessments of participants were conducted using instruments for posture analysis and core strength testing. In particular, the results showed considerable improvements in core muscular endurance, spinal alignment, and postural stability. In addition, after the intervention, individuals felt less back pain and better about their physical health in general. The results show that Pilates-based activities are a viable and efficient substitute for addressing postural issues and weak cores in sedentary people. This emphasizes the value of Pilates-based workouts in reducing the detrimental effects of inactivity on musculoskeletal health.
Enhancing Entrepreneurial Experience in Higher Education: Lessons Learned from Case Studies
In recent years, fostering an entrepreneurial mindset has become essential in education and professional environments, with universities playing a strategic role. This paper examines how education influences entrepreneurial mindset development, with a entrepreneurial programs, significantly impacts students' attitudes and abilities towards entrepreneurship. Universities create supportive environments through dedicated programs and partnerships, enhancing (Anon n.d.) students' entrepreneurial capabilities. Case studies from Finland, Germany, France, the USA, and South Africa demonstrate successful implementation of entrepreneurial programs, each tailored to local needs and contexts. Algeria has made notable progress in promoting entrepreneurship through numerous awareness activities and support structures like the CATI and university entrepreneurial centers. These initiatives provide essential training, resources, and networking opportunities, preparing students for entrepreneurial careers and contributing to economic growth. Overall, these global examples underscore the critical role of educational institutions in nurturing the next generation of entrepreneurs.
Muscle Strength Recovery Following Anterior Cruciate Ligament (ACL) Surgery and the Use of Neuromuscular Electrical Stimulation
Restoring knee stability often requires surgery to repair the anterior cruciate ligament (ACL). While recovering from surgery, one major challenge is dealing with muscle weakness, especially in the quadriceps. As an additional treatment option, neuromuscular electrical stimulation (NMES) is gaining popularity for this illness. Muscle strength and functional recovery can be enhanced with the use of NMES. This study aims to examine the efficacy of non-mechanical exercise therapy (NMES) in reestablishing muscle strength following anterior cruciate ligament (ACL) surgery. Over the course of twelve weeks, a randomized controlled trial assessed the efficacy of standard rehabilitation techniques with and without NMES. Quadriceps strength, knee stability, and functional performance were all much improved in the NMES group compared to the control group. These alterations were far more pronounced, according to the findings. In the early phases of rehabilitation, NMES was very useful for correcting activation deficiencies and preventing muscular atrophy. These results provide credence to the idea that including non-muscular components (NMES) into rehabilitation programs following acromial ligament repair (ACL) can improve healing results and hasten the return to functional activities.
A Hybrid Multivariate GRNN–Fuzzy Goal Programming Framework for Fiscal Forecasting and Budget Optimization
Economic stability and fiscal sustainability remain fundamental priorities for modern economies, requiring proactive financial management and resilient forecasting frameworks. Traditional linear econometric models often struggle to capture the non-linear dynamics and volatile interactions between government revenues and expenditures. This paper proposes a novel multivariate hybrid framework that integrates Generalized Regression Neural Networks (GRNN) with **Multi-Objective Fuzzy Goal Programming (FGP) for fiscal forecasting and budget optimization under ambiguity. The proposed model captures the dynamic interactions between government revenues and expenditures through a lag-based multivariate structure . In the first stage, the lagged GRNN architecture is deployed to generate reliable, non-linear baseline forecasts for public revenues and expenditures. In the second stage, acknowledging the inherent vagueness and flexible tolerances of real-world budgetary targets, these forecasted trajectories are embedded into an operational layer using Fuzzy Goal Programming. By utilizing linguistic aspiration levels and fuzzy membership functions, the model optimizes budgetary allocations under conflicting and imprecise fiscal constraints, such as flexible deficit reduction and expenditure stabilization. Empirical validation demonstrates that the proposed fuzzy-intelligent hybrid architecture significantly outperforms traditional forecasting benchmarks and provides decision-makers with an adaptive, data-driven optimization tool for resilient fiscal policy and strategic budget planning
Technological Synergies and Obstacles in the Role of Autonomous Driving in the Adoption of Electric Vehicles
Electric vehicles (EVs) and autonomous driving technology may work together to speed up the transition to greener modes of transportation. where autonomous driving meets electric car technology, with a focus on the technical synergies that improve both fields and the challenges that remain unresolved. Combining AVs and EVs will increase their combined advantages over both technologies alone, making for a more environmentally friendly, safer, and more efficient transportation system. Electric vehicles benefit from optimized AV driving patterns since they reduce EV energy consumption, while autonomous vehicles (AVs) benefit from streamlined and efficient electric drivetrains. The widespread adoption of autonomous electric vehicles is hindered by numerous challenges, including concerns over safety, complex infrastructure, legal frameworks, and the integration of technology between autonomous systems and electric powertrains. an exhaustive analysis of these possibilities and dangers, shedding insight on the possible future effects of autonomous driving on the transportation scene.
The Contribution of Training to the Development of Human Resources Performance
The study aims to identify the impact of the training function on the performance of human resources in the Ministry of Interior, local groups and urban development. The study relied on the questionnaire to collect data. The study was based on a final sample of 50 employees, and the data was analyzed using the Statistical Packages System for Social Sciences (spss) The study concluded that there is a relationship between the training function and the performance of human resources, and the relationship strength reached 41.1%, based on the value of the correlation coefficient, and this indicates that the training will improve the performance of human resources in a medium way
Electric Vehicles and Sustainable Transportation: Challenges and Opportunities
Electric cars (EVs) are becoming increasingly popular as more and more people come to the realisation that they are an excellent method to mitigate the adverse effects that conventional automobiles that are fuelled by fossil fuels have on the environment. Electric vehicles have the potential to contribute to the diversification of energy sources, the reduction of air pollution, and the reduction of emissions of greenhouse gases in the fight against climate change. There are a number of factors that are preventing electric vehicles from gaining widespread acceptability. These include high initial costs, a lack of charging infrastructure, concerns about range anxiety, and the environmental implications of battery production and disposal. how electric vehicles have the potential to accomplish sustainable mobility by reducing carbon emissions and boosting energy efficiency, as well as the role that electric vehicles play in the endeavor to reach this goal. this article examines the challenges that are preventing the broad adoption of electric vehicles and investigates potential solutions to these issues. By placing these aspects in their proper context, it is possible to gain a clearer understanding of the potential impact that electric vehicles (EVs) could have on transportation patterns, technological advancements, and policy actions aimed at achieving a low-carbon future.
The Impact of Modern Technology on the Financing of Startups in South Africa: Using Artificial Neural Networks.
This study investigates the predictive impact of modern technology on startup financing, with a particular focus on the relative roles of government support policies and entrepreneurial initiatives in South Africa over the period 2001–2024. To this end, an artificial neural network (ANN) model was employed, implemented via Python software, owing to its robust predictive capabilities in complex economic environments. The empirical findings demonstrate the efficacy of both predictive models; however, forecasts derived from the government support variable consistently outperformed those based on the entrepreneurial initiatives variable. This outcome suggests that state-led policies are poised to exert a more pronounced influence on startup financing compared to entrepreneurial efforts, at least within the studied context. Nevertheless, the results do not undermine the potential for synergistic cooperation between the public and private sectors, which remains a critical avenue for advancing sustainable development objectives.
The Ability of Islamic Banks in Algeria to Adopt Basel III Standards: A Case Study of Al Salam Bank
This study aims to address the issue of risk management in Islamic banks in accordance with the supervisory standards issued by the Basel Committee, together with the amendments and guidelines introduced by the Islamic Financial Services Board (IFSB). It also seeks to explain the method of calculating the Capital Adequacy Ratio (CAR), which enables Islamic banks to cover the risks arising from their business activities. The study is structured around three main sections. The first section explains risk management according to the Basel Committee standards and the approaches it established for managing banking risks. The second section discusses the guidelines issued by the Islamic Financial Services Board to enable Islamic banks to comply with international standards in risk management. The third section presents the experience of Al Salam Bank in managing risks and evaluates its ability to comply with Basel standards in this field.
Quantifying Bias in Large Language Models: Comparing Fairness Algorithms
Despite the fact that Large Language Models (LLMs) have amazing capabilities across a wide range of applications, there is a need for some kind of systematic examination and mitigation of the underlying biases that they include. an analysis of fairness algorithms that are designed to measure and correct inequities in LLMs, with a specific focus on biases linked with gender, race, and socioeconomic status for inclusion in the analysis. In order to evaluate the effectiveness of various fairness strategies, such as re-weighting, adversarial debiasing, and counterfactual data augmentation, it is necessary to determine how successfully these methods reduce biased outputs without also reducing model performance. In this study, we conduct empirical tests on a variety of language tasks to determine how effectively each strategy eliminates bias, how efficiently it performs computationally, and how it influences the interpretability of the model. There are further challenges that we discuss, such as the ethical implications of algorithmic bias and the trade-offs that exist between the accuracy of the model and maintaining fairness. The findings of this study provide useful recommendations on how to develop more equitable LLMs, how to enhance our understanding of the fairness of AI, and how to put bias mitigation strategies into action in the actual world.
Digital Transformation as an Approach to Developing Governance and Smart Control in Economic Institutions: A Comparative Study between the Algerian Experience and Selected International Models
In light of the rapid developments in the digital world, economic institutions are increasingly required to reconsider their control systems to meet the demands of the Fourth Industrial Revolution. This study aims to examine the impact of digital transformation on the development of control systems within economic institutions by analyzing the relationship between digitization, governance, and smart control. The findings reveal that the integration of modern technologies such as artificial intelligence, big data, and the Internet of Things (IoT) contributes to enhancing transparency, efficiency, and accountability while reducing administrative and financial risks. The results also indicate that the success of digital transformation depends on a strong digital infrastructure, qualified human resources, and a supportive legal framework. The study concludes that digital transformation serves as a key driver for achieving good governance and building smart economic institutions capable of adapting to the challenges of the digital age.
Quantum Machine Learning: Accelerating AI Models with Quantum Computing
QML explores new paradigms for accelerating AI model training and inference using quantum computing and AI. This study discusses QML and how quantum methods like quantum annealing, variational quantum circuits, and quantum kernel estimation might improve machine learning. quantum computing's ability to solve high-dimensional data and complicated optimization problems faster than classical approaches, promising speedups in data clustering, model training, and feature selection. Current QML issues include hardware limits, error rates, and the necessity for hybrid quantum-classical algorithms, which combine quantum computing's benefits with traditional machine learning methods. Thru simulations and comparative analyzes, we evaluate quantum-enhanced algorithms and their potential for AI acceleration. QML has the potential to change AI, enabling quicker, more efficient model construction powered by quantum computing.
Balancing the Four Dimensions of Sustainable Development in Algeria: Lessons from Selected International Experiences
This study examines Algeria’s progress toward sustainable development across four interconnected dimensions: economic, social, environmental, and institutional. It addresses the extent to which Algeria has achieved a balanced development pathway and identifies lessons that can be adapted from the experiences of Singapore, Japan, Malaysia, and India. Using a descriptive-analytical and comparative approach, the study assesses Algeria’s performance through selected economic, social, environmental, and institutional indicators and compares it with the development mechanisms adopted by the selected countries. The findings show that Algeria has achieved notable progress in areas such as economic growth, electricity access, life expectancy, international reserves, and non-hydrocarbon activity. However, significant challenges remain, particularly hydrocarbon dependence, limited export diversification, water-resource pressure, low renewable-energy deployment, unemployment, and institutional constraints. The comparative analysis demonstrates that sustainable development cannot be achieved through a single transferable model. Accordingly, Algeria should adopt an adaptation rather than replication approach by selectively drawing on relevant mechanisms related to economic diversification, environmental governance, technological innovation, SME development, human-capital formation, resource management, and institutional effectiveness.
The Role of Art in Shaping Cultural Identity
Art is an important medium through which communities express, preserve, negotiate, and transmit cultural identity. Paintings, sculpture, music, dance, crafts, architecture, performance, photography, and digital forms can communicate shared histories, beliefs, values, memories, and experiences across generations. This paper examines the role of art in shaping cultural identity by considering artistic representation, collective memory, traditional practices, language and symbolism, community participation, identity formation, globalization, digital media, and cultural preservation. Art can strengthen a sense of belonging by making cultural experiences visible and by creating spaces in which communities recognize their histories and contemporary concerns. At the same time, artistic representation can challenge dominant narratives and provide marginalized groups with opportunities to express alternative identities. Globalization and digital technologies have expanded the circulation of cultural expressions, creating new possibilities for hybrid identities while also raising concerns about cultural appropriation, commercialization, and loss of local traditions. The paper argues that cultural identity is not static; it is continually produced through interaction between heritage, social experience, creativity, and changing cultural environments. Art contributes to this process by preserving cultural memory while allowing communities to reinterpret their identities in contemporary contexts. Supporting artists, cultural institutions, traditional practitioners, and community-based creative practices is therefore important for maintaining cultural diversity and strengthening social belonging.
COVID-19 and Stock Market Resilience in Algeria A Descriptive and Analytical Assessment of the Algiers Stock Exchange
The COVID-19 pandemic generated an unprecedented combination of health, economic, and financial shocks, disrupting production, consumption, investment, international trade, and financial-market activity. While the pandemic triggered severe volatility in major global financial markets, its consequences for small and relatively illiquid emerging markets require a more specific assessment. This study examines the impact of the COVID-19 pandemic on the Algerian stock market, with particular emphasis on the Algiers Stock Exchange. A descriptive and analytical approach is adopted using official market statistics and institutional reports covering the pre-pandemic, pandemic, and post-pandemic periods. The analysis focuses on market capitalization, transaction values, trading activity, and the evolution of the DZAIRINDEX. The findings show that the pandemic was associated with a significant deterioration in trading activity during 2020. The value of stock-market transactions declined from DZD 41.30 billion in 2019 to DZD 38.86 billion in 2020, while the first-semester market statistics showed a much sharper contraction in the value traded on the main equity market and in the number of transactions. However, the aggregate market capitalization and stock index did not experience a collapse comparable to that observed in several major international markets. The post-pandemic period subsequently witnessed a substantial expansion of the Algerian financial market. The value of transactions increased to DZD 103.66 billion in 2022, DZD 192.77 billion in 2023, DZD 350.16 billion in 2024, and DZD 599.20 billion in 2025. In 2024, market capitalization increased dramatically to DZD 521.669 billion, mainly following the initial public offering of Crédit Populaire d’Algérie. The evidence suggests that COVID-19 generated a temporary disruption in market activity but did not permanently impair the development of the Algerian stock market. Nevertheless, the crisis revealed persistent structural weaknesses related to liquidity, market depth, diversification, and investor participation. The study concludes that strengthening digital infrastructure, broadening the investor base, increasing the number of listed companies, improving disclosure, and developing crisis-management mechanisms are essential for enhancing the resilience of the Algerian financial market.
The Role of Artificial Intelligence in the Creation of Modern Art
Artificial intelligence is becoming an increasingly significant tool in modern artistic practice, influencing how artists generate ideas, create images, manipulate media, experiment with styles, and interact with audiences. Generative artificial intelligence systems can produce visual, textual, auditory, and multimedia outputs from human instructions and data, creating new possibilities for artistic experimentation. This paper examines the role of artificial intelligence in the creation of modern art, focusing on generative processes, human-machine collaboration, creative experimentation, personalization, digital workflows, audience participation, authorship, copyright, ethical concerns, and future directions. AI can accelerate the production of visual variations and enable artists to explore combinations that may be difficult to produce manually. It can also become a conceptual subject through which artists investigate automation, identity, technology, surveillance, and machine creativity. However, AI-generated art raises important questions about originality, authorship, attribution, training data, copyright, bias, labour, and the distinction between artistic intention and automated generation. The paper argues that AI should not be viewed simply as a replacement for human creativity. In many artistic contexts, it functions as a tool or collaborator whose outputs are selected, modified, contextualized, and interpreted by humans. The significance of AI in modern art therefore depends on the relationship between technological systems, human intention, cultural context, and audience interpretation.
Reflections on the Relationship Between Central Banks and Islamic Banks in the Context of a Traditional System
The article addresses the relationship between central banks and Islamic banks within a traditional banking system, focusing on monetary policy tools and their direct impact on the performance of Islamic banks. The study concludes that the use of traditional tools by central banks, such as reserve ratios, liquidity ratios, and discount rates, imposes constraints that conflict with Islamic principles, creating significant challenges for these institutions. These challenges include legal issues, the freezing of investment account funds, declining profits, and restrictions on investment areas, leading to an unbalanced competitive position compared to traditional banks.
Artificial Intelligence and Its Role in Modern Supply Chain Management
Artificial intelligence is increasingly transforming modern supply chain management by improving demand forecasting, inventory planning, logistics, supplier management, risk identification, warehouse operations, and decision-making. Supply chains generate large volumes of information across procurement, production, transportation, warehousing, sales, and customer service, creating opportunities for AI-based analytics and automation. This paper examines the role of artificial intelligence in modern supply chain management, focusing on demand prediction, inventory optimization, procurement, logistics, warehouse management, supplier risk, customer demand, supply chain visibility, and implementation challenges. AI and machine learning can identify patterns in historical and real-time data, helping organizations anticipate changes in demand and respond to disruptions. Automated systems can also support route planning, inventory replenishment, warehouse activities, and supplier evaluation. These applications can improve efficiency and reduce some operational costs while strengthening supply chain responsiveness. However, AI adoption requires reliable data, interoperable systems, skilled employees, cybersecurity, appropriate governance, and organizational readiness. Supply chain models can also produce inaccurate recommendations when data are incomplete or market conditions change unexpectedly. The paper argues that AI should function as a decision-support and automation capability that complements supply chain professionals rather than replacing human judgement. Responsible integration of AI with operational knowledge, digital infrastructure, and continuous monitoring can improve visibility, efficiency, resilience, and long-term supply chain performance.
Algerian-Moroccan Strategies and Redemption Mechanisms (1659–1727): Cross-Mediterranean Captivity
The issue of captivity constitutes one of the most critical topics defining relations between the northern and southern shores of the Mediterranean. This issue gained heightened gravity due to the historical conditions that dominated the region during the seventeenth and eighteenth centuries. With the escalation of European incursions—particularly French and Spanish—against Algerian and Moroccan coasts, the intensification of naval Jihad, and the prevalence of privateering practices pursued by both Muslims and Christians, numerous individuals were captured on both sides. Consequently, the prisoner question emerged as a pivotal element in stimulating diplomatic engagement between the opposing powers. Redemption orders played a significant role in securing the release of Christian captives, especially as the ransom process provided a substantial source of revenue and served as a vital factor in stimulating local economies, particularly that of Algeria.
Applications of Machine Learning in Predictive Maintenance and Industrial Operations
Machine learning is increasingly being applied in industrial environments to improve equipment reliability, reduce unplanned downtime, optimize maintenance activities, and strengthen operational decision-making. Traditional maintenance approaches often rely on fixed schedules or reactive responses after equipment failure, whereas predictive maintenance uses data to estimate equipment condition and identify potential failures before they occur. This paper examines applications of machine learning in predictive maintenance and industrial operations, focusing on sensor-based monitoring, anomaly detection, failure prediction, maintenance scheduling, production optimization, quality control, energy management, supply chain coordination, and implementation challenges. Machine learning models can process data generated by industrial equipment, including vibration, temperature, pressure, current, speed, and acoustic signals, to identify patterns associated with normal or abnormal operating conditions. Predictive information can help maintenance teams prioritize interventions, reduce unnecessary component replacement, and improve asset utilization. Machine learning can also contribute to broader industrial operations by supporting production planning, quality inspection, energy optimization, and process control. However, effective implementation requires reliable data, appropriate sensors, model validation, skilled personnel, cybersecurity, and integration with existing industrial systems. The paper argues that machine learning should complement engineering expertise and maintenance knowledge rather than replace them. When predictive models are integrated with human judgement and well-designed maintenance processes, organizations can improve reliability, reduce operational costs, extend asset life, and support more efficient industrial production.
Artificial Intelligence in Combating Tax Evasion: A Critical Comparative Analysis of the French and British Experiences and Its Applicability to the Algerian Tax Administration
Tax evasion remains a significant loss of public revenue in both advanced and developing economies, and more and more tax administrations are using artificial intelligence (AI) in their control functions. This article explores two of the most institutionalized AI-powered fiscal enforcement models worldwide: the French Ciblage de la Fraude et Valorization des Requêtes (CFVR) program and the UK’s HM Revenue and Customs (HMRC) Connect system. The study presents a critical comparative analysis of their institutional origins, quantitative performance and legal-ethical constraints, drawing on documentary and secondary sources, before assessing the conditions under which comparable tools could be meaningfully adapted to the Algerian tax administration. The findings show that European systems are based on the progressive integration of several interoperable data sources, including fiscal, cadastral, banking, and (increasingly) social media data, and they produce measurable results (albeit methodologically limited) in terms of revenue recovery. A direct evaluation of Algeria’s digital tax architecture, through cross-checking with official sources from the Ministry of Finance and the DGI, finds that while the Jibayatic declaration and payment system has achieved a true national rollout, there is no legal requirement for electronic invoicing and no standardized tax-gap indicator by which the extent of evasion can be monitored, as is the case in France and the UK. The article concludes that a direct transposition of the CFVR and Connect models is neither realistic nor recommendable in the short term and instead promotes a phased, context-sensitive roadmap based on Algeria’s existing declarative infrastructure and the introduction of an e-invoicing mandate.
Molecular Mechanisms of Cell Signaling and Communication
Cell signaling and communication are fundamental processes through which cells detect environmental changes, coordinate activities, maintain homeostasis, and generate appropriate physiological responses. Molecular signaling begins when extracellular or intracellular signals interact with specific receptors and is transmitted through interconnected networks of G proteins, protein kinases, phosphatases, second messengers, ion channels, and transcriptional regulators. Major receptor systems include G protein-coupled receptors, receptor tyrosine kinases, ligand-gated ion channels, cytokine receptors, and other signaling proteins. citeturn0search5turn0search7 Second messengers such as cAMP, Ca2+, IP3, DAG, and PIP3 amplify and distribute information within cells. citeturn0search0turn0search4 This paper examines nine major aspects of molecular cell signaling, including receptor recognition, intracellular transduction, second messengers, kinase cascades, signal amplification, pathway crosstalk, signal termination, cellular responses, and disease relevance. Understanding these mechanisms is essential for explaining normal cellular physiology and for identifying molecular targets involved in human disease and therapeutic development.
From Student to Entrepreneur: A Critical Human–Institutional Reading of the Impact of University Incubators on Human and Institutional Development in Algeria
This study examines the transformation from student to entrepreneur within Algerian university incubators through a critical human–institutional perspective that goes beyond reducing entrepreneurship to the creation of start-ups or the acquisition of an “Innovative Project” label. It investigates the transformations affecting students’ identities, motivations, and perceptions of work, the university, and risk, as well as the new roles of the university and the incubator in producing and valorizing knowledge and linking it to the labor market and development. The study is based on a central research problem: To what extent do Algerian university incubators contribute to achieving an actual and sustainable transition from student status to entrepreneurial status, and to building cognitive, social, and human capital capable of supporting development beyond the hydrocarbons sector? The research gap lies in the limited number of studies that combine the measurement of procedural incubation outcomes—such as the number of projects, patents, and enterprises—with an analysis of the human and institutional dimensions of the transformation, particularly professional identity, self-confidence, psychosocial and career support, equity among academic disciplines, and the tension between the traditional university and the entrepreneurial university. The study aims to analyze the nature of the support provided by incubators, measure its impact on students’ skills, values, autonomy, and capacity for initiative, and assess the effectiveness of the relationship between the university, the private sector, and public institutions within the framework of the Triple Helix model. The study adopts a mixed-methods approach by combining document analysis and official statistics with a questionnaire administered to student project holders and semi-structured interviews with incubator managers and faculty members. It employs descriptive analysis, distributions, percentages, and tables, together with thematic analysis of the participants’ accounts. The findings indicate that university incubators have made progress in training, developing presentation and planning skills, and strengthening students’ self-confidence and awareness of initiative. However, the actual transition to sustainable enterprises remains limited compared with the number of registered projects and is strongly associated with the quality of mentoring, networks, financing, and post-graduation follow-up. The study also reveals a relative tendency to favor technological projects at the expense of the humanities and social sciences, as well as the continued presence of bureaucratic obstacles and weak links with the market. It recommends broadening the concept of innovation, integrating psychological and human dimensions, strengthening partnerships, simplifying procedures, and adopting long-term impact indicators.
The Impact of Pollution on Aquatic Ecosystems
Pollution is a major pressure on freshwater and marine ecosystems and can alter water quality, biological communities, food webs, and ecosystem functions. Nutrients, heavy metals, pesticides, plastics, hydrocarbons, pharmaceuticals, and untreated wastewater can enter aquatic environments through agricultural runoff, industrial activity, urban drainage, and other pathways. Pollutants may cause direct toxicity, oxygen depletion, eutrophication, habitat degradation, and bioaccumulation. This paper examines nine major dimensions of aquatic pollution, including major pollution sources, nutrient enrichment, chemical contaminants, plastics, eutrophication, biological responses, freshwater ecosystems, marine and coastal systems, and pollution control and restoration.