Critical Aspects Research Articles

Criticism Towards the Ruler: Illustrations From the Letter of the Law and the Practice of the Polish Constitutional State

The publication is devoted to several examples of the practice of criticism of the Head of State and executive power in Polish history. The authors have chosen three moments of interest: the first one is the first decade of the “Congress” Polish Kingdom established in 1815, and the second refers to the Second Polish Republic in the period after the coup d’État by Józef Piłsudski in 1926. Finally, the authors refer to some practical aspects of criticism of the authority in the public space in recent times, also recalling the high-profile criminal trial that reached the highest instance – the Supreme Court in 2023. In these examples, the authors focus on aspects of the permissibility of criticism, its specific forms and the reaction of the executive in the early history of the constitutional state and camouflaged criticism of power respectively, through the interwar liberal model of protection of freedom of speech and of the press, which failed in the face of authoritarian changes and the political will to protect the good name of one particular individual; after the death of Piłsudski, the lack of adequate legal protection post mortem was finally “remedied” by a particular repressive law. The last section of the discussion refers to the contemporary Polish state of law, and here the focus is on the faces of criticism and the forms of its suppression. In particular, attention was paid to the problem of the extensive use of means used by the police against criticism particularly unpleasant to the power camp (up to the bizarre action with the hiring of a jib) and the question of maintaining specific protection of the Head of State against defamation in the Criminal Code.

Eco-friendly Approaches to Chromene Derivatives: A Comprehensive Review of Green Synthesis Strategies.

Synthetic routes of chromene are an area of thrust research due to its wide application as pigments, agrochemicals, cosmetics, and an important nucleus scaffold for various pharmaco-logically active drugs. The chromene nucleus is an important moiety for the discovery of new drug candidates owing to its broad range of pharmacological actions like antitumor, anti-inflammatory, antiviral, and many others. However, traditional synthesis techniques frequently use unsafe reagents and produce hazardous waste, presenting environmental issues. The eco-friendly production of chromene derivatives utilizes sustainable raw materials, non-toxic cata-lysts, and gentle reaction conditions to reduce ecological consequences. Innovative methods like microwave irradiation, ultrasound synthesis, the use of environmentally friendly solvents, a cata-lyst-based approach with minimal environmental impact, and mechanochemistry-mediated syn-thesis are implemented. These approaches provide benefits in scalability, cost-effectiveness, and ease of purification. This review compiles and presents various recently reported green synthetic strategies of chromene and its derivatives and gives the reader a clear idea of the detailed and crit-ical aspects of various synthetic protocols described.

Research on the Development form of Chinese Contemporary Oil Painting in Recent 30 Years

This paper analyzes and discusses the development form of Chinese contemporary oil painting in the past 30 years, and thinks that in the past 30 years, after the baptism of Western cultural thoughts, postmodern thoughts have been deeply rooted in the hearts of Chinese people. Under this background, Western modern culture has brought rich topics to Chinese oil painting, and Chinese oil painting language is also transforming under the impact of Western artistic thoughts. This paper also summarizes the two aspects of Chinese contemporary art criticism during the period of 1990-2020. This paper holds that only by accurately grasping the characteristics of The Times and starting from the simple life can contemporary Chinese oil painting see the truth, goodness and beauty of art from life, and only by returning to the real "contemporary" can it absorb the essence from it and have enduring vitality.

Aesthetic Tradition and Cultural Temperament

British and American literature is one of the bright gems in the history of world literature, which has formed a unique literature after many times of historical evolution and integration of national culture. This paper makes an in-depth study of the historical development of Britain and the United States, starting from the three dimensions of "aesthetic tradition", "cultural temperament" and "translation of British and American literature", and discussing from two aspects of literary criticism and aesthetic perception. It is helpful to understand the unique cultural connotation and temperament of British and American culture, so as to better understand the cultural connotation of British and American classics and improve the translation quality of British and America literary works.

Critical English medium instruction: problematising neocolonial language dominance

ABSTRACT English medium instruction (EMI) and critical language education are both relatively established areas of education and scholarship. While the booming trends of EMI have generally foregrounded the technical aspects of instruction and the related linguistic challenges, the ongoing development of EMI theory, research, policy, and practice can be further integrated with critical views. Although a stream of EMI research based on critical perspectives does already exist, there is still a considerable place for more serious critical engagements in this area. Therefore, in this paper we argue for the development of ‘Critical EMI’ praxis that embraces criticality in an explicit, inclusive, and coherent manner. Considering that EMI is a still emerging phenomenon in many contexts, we argue that this is the right time for endeavouring to help it grow as a sociopolitically sensitive area in essence while it is developing roots. We highlight issues of ideology, policy, identity, social justice, and the politics of English as five essential aspects of criticality in Critical EMI and further discuss some of the insights that it can offer in encountering the neocolonial spread and dominance of English.

Sustainability Aspects of Whale Shark Tourism: A Perspective from Tourist Blogs

This study explored tourists’ blogs to identify sustainability challenges and opportunities to inform best-practice management of the whale shark tourism industry worldwide. Few researchers have investigated blogs in the context of swim‐with whale shark experiences as recounted from the tourist perspective. This research was based on a content analysis of a sample of 58 tourist blogs, amounting to 31,509 words of content. The findings explored common sustainability themes within the whale shark tourist experience including proximity of the encounter, nature of the interaction, and whale shark tourist behavior. By comparing three whale shark tourism destinations–Mexico, the Philippines, and Australia–several sustainability challenges and opportunities were identified. The findings contribute to previous knowledge by advancing our understanding of whale shark tourists’ perception of critical aspects during their swim-with whale shark experience, which guided recommendations for improved and sustainable management.

Youth Character Building Through Quality Education in Realizing Golden Indonesia 2045

This article aims to explore adolescent character building through quality education in realizing a Golden Indonesia 2045. These two goals are part of Indonesia's SDGs. Adolescent character development in Indonesia is on an upward trend, so a character education strategy is needed to achieve the golden goal. The urgency of this article is to formulate character development that is qualified in terms of a series of opportunities and challenges faced by the Indonesian nation. This article uses a qualitative method with a literature study approach. The primary sources of this article are education policy documents and relevant recent literature. Meanwhile, the secondary data used in this study are reportage documents and supporting research. The results show that there are three domains that must be suppressed in achieving a Golden Indonesia 2045, namely: 1) Ongoing Conflict, 2) Safety and Security and 3) Militarization. In addition to peace, there are eight factors of justice and educational efforts that can be implemented in achieving SDG's point number 16. On the other hand, the realization of this Gold must be accompanied by multiracial, gender and multireligious knowledge. Building the ideal adolescent character in realizing a Golden Indonesia 2045 involves quality education that emphasizes moral integrity, social skills, a sense of responsibility, and awareness of justice values. Quality education that can realize a Golden Indonesia 2045 requires a holistic approach that integrates character building, multicultural inclusiveness, social skills development, and the participation of all relevant parties. Critical Pedagogy and Social Development theories have an important role in reviewing and creating novelty in this research. The focus of development rests on aspects of criticality, social skills and understanding by encouraging collaboration. Then local values, history and religion become one of the reinforcing factors in achieving a Just and Peaceful Indonesia.

AI in the discourse of the relationships between technology and education

The article reviews some of the relationships between AI and education, emphasizing the metaphors used, the difficulties in finding points of agreement, as well as aspects of the social criticism that is made of AI (e.g. considering that it can be a form of unwanted deviation). AI appears as one more case of technology that comes to improve education, as happened in the past with other less “intelligent” technologies, although now with more arguments in its favor. Secondly, it explores the logical mechanisms (abduction) that are widely used in human reasoning but also in AI, showing how their uncontrolled use can lead to certain conversation algorithms being able to lie, something that teachers would not do. An ethical rather than logical question is raised that deserves to be explored later.

Quinoline Derivatives as Promising Scaffolds for Antitubercular Activity: A Comprehensive Review.

Heterocyclic compounds and their derivatives play a significant role in the design and development of novel quinoline drugs. Among the various pharmacologically active heterocyclic compounds, quinolines stand out as the most significant rings due to their broad pharmacological roles, specifically antitubercular activity, and their presence in plant-based compounds. Quinoline is also known as benzpyridine, benzopyridine, and 1-azanaphthalene. It has a benzene ring fused with a pyridine ring, and both rings share two carbon atoms. The importance of quinoline lies in its incorporation as a key component in various natural compounds found in medicinal plant families like Fumariaceae, Berberidaceae, Rutaceae, Papavaraceae, and others. This article is expected to have a significant impact on the advancement of effective antitubercular drugs. Through harnessing the potent activity of quinoline derivatives, the research aims to make valuable contributions to combating tuberculosis more efficiently and ultimately reducing the global burden of this infectious disease. Numerous nitrogen-containing heterocyclic compounds exhibit significant potential as antitubercular agents. These chemicals have fused aromatic nitrogen-heterocyclic nuclei that can change the number of electrons they have, which can change their chemical, physical, and biological properties. This versatility comes from their ability to bind with the receptors in multiple modes, a critical aspect of drug pharmacological screening. Among these compounds, quinoline stands out as it incorporates a stable fusion of a benzene ring with a pyridine nucleus. Quinolines have demonstrated a diverse range of pharmacological activities, including but not limited to anti-tubercular, anti-tumor, anticoagulant, anti-inflammatory, antioxidant, antiviral, antimalarial, anti-HIV, and antimicrobial effects. Some molecules, such as lone-paired nitrogen species, include pyrrole, pyrazole, and quinoline. These molecules contain nitrogen and take part in metabolic reactions with other molecules inside the cell. However, an excessive accumulation of reactive nitrogen species can lead to cytotoxicity, resulting in damage to essential biological macromolecules. Among these compounds, quinoline stands out as the oldest and most effective one, exhibiting a wide range of significant properties such as antitubercular, antimicrobial, anti-inflammatory, antioxidant, analgesic, and anticonvulsant activities. Notably, naturally occurring quinoline compounds, such as quinine, have proven to be potent antimalarial drugs. This review highlights quinoline derivatives' antitubercular potential, emphasizing recent research advancements. Utilizing IC50 values, the study emphasizes the efficacy of various quinoline substitutions, hybrids, and electron-withdrawing groups against MTB H37Rv. Continued research is essential for developing potent, low-toxicity quinoline derivatives to combat tuberculosis.

Academic Electronic Health Record in Mental Health Clinical: A Quality Review.

Developing competency in the use of EHRs is essential for entry-level professional nurses. Although nursing education has been encouraged to integrate this technology into nursing curriculum, many students still graduate feeling unprepared in this area. As a result, nursing graduates lack the skills necessary to effectively use EHRs, which may have negative consequences for safe patient care. Use of academic EMRs provides students the opportunity to integrate informatics education, develop critical thinking, and incorporate problem-solving skills in the clinical area. An academic EMR was introduced to students in the second semester of a baccalaureate degree nursing program. Students completed documentation on one patient from the mental health clinical rotation. A retrospective chart review was conducted, using a rubric to determine charting efficacy. Data analysis indicated that students struggled with documentation of the mental health assessment, care plan development, and nursing notes. Student documentation was strongest in vital signs and basic information. Students need practice documenting on the critical aspects of nursing care. Utilization of an academic EMR for clinical charting provides an opportunity for students to practice documentation and develop necessary skills for clinical practice.

Hypoxia A Typical Target in Human Lung Cancer Therapy.

Lung cancer (LC) is the leading cause of cancer-related death globally. Comprehensive knowledge of the cellular and molecular etiology of LC is perilous for the development of active treatment approaches. Hypoxia in cancer is linked with malignancy, and its phenotype is implicated in the hypoxic reaction, which is being studied as a prospective cancer treatment target. The hypervascularization of the tumor is the main feature of human LC, and hypoxia is a major stimulator of neo-angiogenesis. It was seen that low oxygen levels in human LC are a critical aspect of this lethal illness. However, as there is a considerable body of literature espousing the presumed functional relevance of hypoxia in LC, the direct measurement of oxygen concentration in Human LC is yet to be determined. This narrative review aims to show the importance and as a future target for novel research studies that can lead to the perception of LC therapy in hypoxic malignancies.

The Concept Of Competence And Its Development Features In The Linguistic Field/ مفهوم الكفاية وملامح تطوُّره في الدرس اللساني

This research addresses the concept of competence in linguistics and the essential stages it has gone through since its manifestation at the hands of the linguistic scholar Chomsky until it reached the stage of stability and application. Subsequently, this research analyzed the concepts of competence and performance according to Chomsky and set forth its most essential characteristics according to his perspective. Then, it elucidated the most critical aspects of criticism that the subsequent linguists directed to his concept of competence, citing the essential alternatives they presented to understand this concept. Moreover, the research also treated the idea of communicative competence developed by Dell Hymes as the most prominent alternative to Chomsky’s competence. The research expounded his concept and explained its components and the differences between it and Chomsky’s competence. Furthermore, it explained the criteria that Hymes adopted in measuring the speaker’s competence and his ability to evaluate the performed speech. Consequently, the research dealt with developing communicative competence among those who succeeded Hymes. Hence, this research introduced the sub-competencies that constitute communicative competence according to Canale and Swain and showed their impact on applied linguistics. After that, it dealt with Bachman’s attempt to develop communicative competence through the model he presented under linguistic communicative ability. Finally, the research dilated the model introduced by Celce-Murcia and her colleagues, which is based on the intersection of communicative sub-competencies in discourse competence. The research results showed that the concept of competence passed through several stages that developed and spruced up its characteristics and contributed to stirring it from the theoretical basis to the applied framework. Moreover, Chomsky’s concept of competence differed from that of his successors among the linguists, whose criticisms were more constructive, which led to the development of the idea and made it applicable.

Advancements in machine learning for predicting phases in high-entropy alloys: a comprehensive review

High entropy alloys (HEAs) are distinguished by their enhanced physicochemical properties, attributed to the formation of various phases such as solid solution (SS), intermetallic (IM), or a combination (SS + IM). These phases contribute distinctively to the microstructure of the alloys. A critical aspect of alloy design revolves around accurately predicting these phases, which has led to the integration of sophisticated data vetting methods and Machine Learning (ML) algorithms in recent research. This review paper aims to provide a comprehensive analysis of the advancements in phase prediction accuracy within HEAs, an essential component in the development of these alloys. HEAs are known for their intricate compositions, offering a wide spectrum of material properties, making them particularly relevant for applications aimed at future sustainability. Phase engineering in HEAs unlocks the potential for creating materials tailored to eco-friendly technologies and energy-efficient solutions. The challenge in predicting phase selection in HEAs is accentuated by the limited data available on these complex materials. This review delves into how advanced data vetting techniques and ML algorithms are being employed to overcome these challenges, thus contributing significantly to sustainable material design. The paper examines various algorithms used in HEA phase prediction, including KNN (K-Nearest Neighbors), SVM (Support Vector Machines), ANN (Artificial Neural Networks), GNB (Gaussian Naive Bayes), and RF (Random Forest). It discusses the testing accuracy of these algorithms in classifying HEA phases, revealing variations in their effectiveness. The review highlights the superior accuracy of ANNs, followed closely by KNN and SVM, while noting the comparatively lower accuracy of GNB. This comprehensive review synthesizes current research efforts in utilizing computational methods to design HEAs, underlining their broader implications in expediting the discovery and development of diverse metal alloys. These efforts are pivotal in meeting the evolving demands of modern engineering applications, thereby contributing to the advancement of materials science.

The 85-electrode adaptive optics system of the Swedish 1-m Solar Telescope

We discuss the chosen concepts, detailed design, implementation and calibration of the 85-electrode adaptive optics (AO) system of the Swedish 1-meter Solar Telescope (SST), which was installed in 2013. The AO system is unusual in that it uses a combination of a monomorph mirror with a Shack-Hartmann (SH) wavefront sensor (WFS) and a second high-resolution SH microlens array to aid the characterization, calibration, and modal control of the deformable mirror. An Intel PC workstation performs the heavy image processing associated with cross-correlations and real-time control at a 2 kHz update rate with very low latency. The computer and software continue the successful implementation since 1995 of earlier generations of correlation tracker and AO systems at SST and its predecessor, the 50-cm Swedish Vacuum Solar Telescope, by relying entirely on work-station technology and an extremely efficient algorithm for implementing cross-correlations with the large field of view of the WFS. We describe critical aspects of the design, calibrations, software, and functioning of the AO system. The exceptionally high performance is testified through the highest Strehl ratio (inferred from the measured granulation contrast) of existing meter-class solar telescopes, as demonstrated here at wavelengths shorter than 400 nm and discussed in more detail in a previous separate publication We expect that some aspects of this AO system may also be of interest outside the solar community.

Wearable Activity Trackers: A Survey on Utility, Privacy, and Security

Over the past decade, wearable activity trackers (WATs) have become increasingly popular. However, despite many research studies in different fields (e.g. psychology, health, and design), few have sought to jointly examine the critical aspects of utility (i.e., benefits brought by these devices), privacy, and security (i.e., risks and vulnerabilities associated with them). To fill this gap, we reviewed 236 studies that researched the benefits of using WATs, the implications for the privacy of users of WATs, and the security vulnerabilities of these devices. Our survey revealed that these devices expose users to several threats. For example, WAT data can be mined to infer private information, such as the personality traits of the user. Whereas many works propose empirical findings about users’ privacy perceptions and their behaviors in relation to privacy, we found relatively few studies researching technologies to better protect users’ privacy with these devices. This survey contributes to systematizing knowledge on the utility, privacy, and security of WATs, shedding light on the state-of-the-art approaches with these devices, and discussing open research opportunities.

Research on the impact of sliding window and differencing procedures on the support vector regression model for load forecasting

Load forecasting is a critical aspect of energy management and grid operations. Machine learning techniques as support vector regression (SVR), have been widely used for load forecasting. However, the effectiveness of SVR is highly dependent on its hyperparameters, including the error sensitivity parameter, penalty factor, and kernel function. Furthermore, as the load data follows a time series pattern, the accuracy of the SVR model is influenced by the data's characteristics. In this regard, the present study aims to investigate the impact of combining the sliding window procedure and differencing the input data on the prediction accuracy of the SVR model. The study utilizes daily maximum load data from the Queensland and Victoria states in Australia. The analyses revealed that while the sliding window procedure had a minimal impact on the prediction results, the differencing of the input data significantly improved the accuracy of the predictions.

Applied Machine Learning for Information Security

Information security has undoubtedly become a critical aspect of modern cybersecurity practices. Over the past half-decade, numerous academic and industry groups have sought to develop machine learning, deep learning, and other areas of artificial intelligence-enabled analytics into information security practices. The Conference on Applied Machine Learning (CAMLIS) is an emerging venue that seeks to gather researchers and practitioners to discuss applied and fundamental research on machine learning for information security applications. In 2021, CAMLIS partnered with ACM Digital Threats: Research and Practice (DTRAP) to provide opportunities for authors of accepted CAMLIS papers to submit their research for consideration into ACM DTRAP via a Special Issue on Applied Machine Learning for Information Security. This editorial summarizes the results of this Special Issue.

Fast Finite-Time Composite Controller for Vehicle Steer-by-Wire Systems with Communication Delays

The modern steer-by-wire (SBW) systems represent a revolutionary departure from traditional automotive designs, replacing mechanical linkages with electronic control mechanisms. However, the integration of such cutting-edge technologies is not without its challenges, and one critical aspect that demands thorough consideration is the presence of nonlinear dynamics and communication network time delays. Therefore, to handle the tracking error caused by the challenge of time delays and to overcome the parameter uncertainties and external perturbations, a robust fast finite-time composite controller (FFTCC) is proposed for improving the performance and safety of the SBW systems in the present article. By lumping the uncertainties, parameter variations, and exterior disturbance with input and output time delays as the generalized state, a scaling finite-time extended state observer (SFTESO) is constructed with a scaling gain for quickly estimating the unmeasured velocity and the generalized disturbances within a finite time. With the aid of the SFTESO, the robust FFTCC with the scaling gain is designed not only for ensuring finite-time convergence and strong robustness against time delays and disturbances but also for improving the speed of the convergence as a main novelty. Based on the Lyapunov theorem, the closed-loop stability of the overall SBW system is proven as a global uniform finite-time. Through examination across three specific scenarios, a comprehensive evaluation is aimed to assess the efficiency of the suggested controller strategy, compared with active disturbance rejection control (ADRC) and scaling ADRC (SADRC) methods across these three distinct driving scenarios. The simulated results have confirmed the merits of the proposed control in terms of a fast-tracking rate, small tracking error, and strong system robustness.

Empowering Graph Neural Networks with Block-Based Dual Adaptive Deep Adjustment for Drug Resistance-Related NcRNA Discovery.

Drug resistance to chemotherapeutic agents remains a formidable challenge in cancer treatment, significantly impacting treatment efficacy. Extensive research has exposed the intimate involvement of noncoding RNAs (ncRNAs) in conferring resistance to cancer drugs. Understanding the intricate associations between ncRNAs and drug resistance is of pivotal importance in advancing clinical interventions and expediting drug development. However, traditional biological experimental methods are hampered by limitations, such as labor intensiveness, time consumption, and constraints in scalability. Addressing these challenges necessitates the development of efficient computational methods for the accurate prediction of potential ncRNA-drug resistance associations (NDRA). However, most existing predictive models primarily focus on known ncRNA-drug resistance associations, often neglecting the critical aspect of similarity information between ncRNAs and drug resistance. This oversight may hinder the accuracy of characterizing these associations. To overcome the limitations of existing computational models, we proposed B-NDRA, a computational framework designed for the discovery of drug resistance-related ncRNA. Initially, we constructed a heterogeneous graph that integrates ncRNA-drug resistance pairs, leveraging both known associations and similarity fusion information between ncRNAs and drug resistance. Subsequently, we employed an attention mechanism to aggregate local features of graph nodes following a dimensionality reduction of node features. Further, a graph neural network (GNN) facilitated the learning of global node embeddings. Notably, the integration of dual adaptive deep adjustment architectures, encompassing intrablock and interblock methodologies, enabled efficient extraction of global features while balancing local and global features. Finally, B-NDRA employed a multilayer perceptron to predict associations between ncRNAs and drug resistance. Through rigorous 5-fold cross-validation, B-NDRA achieved average AUC, AUPR, Accuracy, Precision, Recall, and F1-score values of 92.2%, 91.9%, 84.88%, 86.9%, 82.37%, and 84.44%, respectively. Furthermore, comparative evaluations were conducted on established models, namely, GAEMDA, GRPAMDA, and LRGCPND. The results, obtained through three distinct 5-fold cross-validation strategies, demonstrated a notable performance improvement across almost all metrics for our B-NDRA. Specific case studies targeting Doxorubicin and Imatinib further validated the practicality of our B-NDRA in discovering potential NDRA. These results confirm the potential of our B-NDRA as a valuable tool in advancing cancer research and therapeutic development. The source code and data set of B-NDRA can be found at https://github.com/XuanLi1145/B-NDRA.

CHALLENGES AND SUCCESSES IN RURAL ELECTRIFICATION: A REVIEW OF GLOBAL POLICIES AND CASE STUDIES

Rural electrification is a critical aspect of sustainable development, aiming to bridge the energy gap in remote and underserved areas. This paper provides a comprehensive review of global policies and case studies related to challenges and successes in rural electrification. The challenges in rural electrification are multifaceted and often rooted in economic, geographic, and social factors. Limited financial resources, vast and difficult terrains, and sparse population density pose significant hurdles. Additionally, socio-cultural aspects and community dynamics influence the acceptance and sustainability of electrification projects. Understanding and addressing these challenges is crucial for the success of rural electrification initiatives. On the policy front, various nations and international organizations have implemented diverse approaches to tackle these challenges. This review examines the effectiveness of different policy frameworks, exploring their impact on the speed and sustainability of rural electrification. Policies encompass financial incentives, regulatory frameworks, and technology deployment strategies, with an emphasis on fostering public-private partnerships. The paper also delves into case studies from different regions, providing insights into both successful and unsuccessful attempts at rural electrification. Examining these cases helps identify common patterns, lessons learned, and best practices that can inform future initiatives. Successful projects often involve a combination of innovative financing models, community engagement, and the integration of renewable energy sources tailored to local conditions. This paper underscores the importance of a holistic and context-specific approach to rural electrification. Global policymakers, practitioners, and stakeholders can draw valuable lessons from both challenges and successes to refine strategies and enhance the impact of rural electrification initiatives worldwide. As the world continues to strive for universal energy access, this review contributes to the ongoing dialogue on shaping effective policies and practices in the realm of rural electrification.
 Keywords: Rural Electrification, Global Policies, Renewable Energy, Energy Financing, Review.