Rapid Development Research Articles

[Advances of pathological research and classification in malformations of cortical development associated with refractory epilepsy].

With rapid development of genetic testing techniques, neuroimaging and neuroelectrophysiological technologies, our understanding of malformations of cortical development continues to be deepened and updated. In particular, mutations in genes related to the mammalian target of rapamycin (mTOR) signaling pathway have been successively discovered in focal cortical dysplasia (FCD). At the same time, the classification consensus on FCD issued by the International League Against Epilepsy (ILAE) in 2011 has encountered problems and challenges in diagnostic practice. Therefore, in 2022, ILAE proposed an updated version of the FCD classification based on the progress in molecular genetics over the past decade. The main addition to the classification system is "white matter lesions, " and it is also suggested to integrate histopathological, neuroimaging, and molecular testing results for multi-level integrated diagnosis to achieve reliable, clinically relevant, and therapeutic targeted final diagnosis.

An update on tests used for intraoperative monitoring of cognition during awake craniotomy.

Mapping higher-order cognitive functions during awake brain surgery is important for cognitive preservation which is related to postoperative quality of life. A systematic review from 2018 about neuropsychological tests used during awake craniotomy made clear that until 2017 language was most often monitored and that the other cognitive domains were underexposed (Ruis, J Clin Exp Neuropsychol 40(10):1081-1104, 218). The field of awake craniotomy and cognitive monitoring is however developing rapidly. The aim of the current review is therefore, to investigate whether there is a change in the field towards incorporation of new tests and more complete mapping of (higher-order) cognitive functions. We replicated the systematic search of the study from 2018 in PubMed and Embase from February 2017 to November 2023, yielding 5130 potentially relevant articles. We used the artificial machine learning tool ASReview for screening and included 272 papers that gave a detailed description of the neuropsychological tests used during awake craniotomy. Comparable to the previous study of 2018, the majority of studies (90.4%) reported tests for assessing language functions (Ruis, J Clin Exp Neuropsychol 40(10):1081-1104, 218). Nevertheless, an increasing number of studies now also describe tests for monitoring visuospatial functions, social cognition, and executive functions. Language remains the most extensively tested cognitive domain. However, a broader range of tests are now implemented during awake craniotomy and there are (new developed) tests which received more attention. The rapid development in the field is reflected in the included studies in this review. Nevertheless, for some cognitive domains (e.g., executive functions and memory), there is still a need for developing tests that can be used during awake surgery.

An SSVEP-based BCI with 112 targets using frequency spatial multiplexing.

Objective.Brain-computer interface (BCI) systems with large directly accessible instruction sets are one of the difficulties in BCI research. Research to achieve high target resolution (⩾100) has not yet entered a rapid development stage, which contradicts the application requirements. Steady-state visual evoked potential (SSVEP) based BCIs have an advantage in terms of the number of targets, but the competitive mechanism between the target stimulus and its neighboring stimuli is a key challenge that prevents the target resolution from being improved significantly.Approach.In this paper, we reverse the competitive mechanism and propose a frequency spatial multiplexing method to produce more targets with limited frequencies. In the proposed paradigm, we replicated each flicker stimulus as a 2 × 2 matrix and arrange the matrices of all frequencies in a tiled fashion to form the interaction interface. With different arrangements, we designed and tested three example paradigms with different layouts. Further we designed a graph neural network that distinguishes between targets of the same frequency by recognizing the different electroencephalography (EEG) response distribution patterns evoked by each target and its neighboring targets.Main results.Extensive experiment studies employing eleven subjects have been performed to verify the validity of the proposed method. The average classification accuracies in the offline validation experiments for the three paradigms are 89.16%, 91.38%, and 87.90%, with information transfer rates (ITR) of 51.66, 53.96, and 50.55 bits/min, respectively.Significance.This study utilized the positional relationship between stimuli and did not circumvent the competing response problem. Therefore, other state-of-the-art methods focusing on enhancing the efficiency of SSVEP detection can be used as a basis for the present method to achieve very promising improvements.

Circular Polarization-Resolved Raman Optical Activity: A Perspective on Chiral Spectroscopies of Vibrational States.

Circular polarization-resolved Raman scattering methods include Raman optical activity (ROA) and its derivative─surface-enhanced Raman optical activity (SEROA). These spectroscopic modalities are rapidly developing due to their high information content, stand-off capabilities, and rapid development of Raman-active chiral nanostructures. These methods enable a direct readout of the vibrational energy levels of chiral molecules, crystals, and nanostructured materials, making it possible to study complex interactions and the dynamic interfaces between them. They were shown to be particularly valuable for nano- and biotechnological fields encompassing complex particles with nanoscale chirality that combine strong scattering and intense polarization rotation. This perspective dives into recent advancements in ROA and SEROA, their distinction from surface-enhanced Raman scattering, and the potential of these information-rich label-free spectroscopies for the detection of chiral biomolecules.

Rapid development and mass production of SARS-CoV-2 neutralizing chicken egg yolk antibodies with protective efficacy in hamsters

Despite the record speed of developing vaccines and therapeutics against the SARS-CoV-2 virus, it is not a given that such success can be secured in future pandemics. In addition, COVID-19 vaccination and application of therapeutics remain low in developing countries. Rapid and low cost mass production of antiviral IgY antibodies could be an attractive alternative or complementary option for vaccine and therapeutic development. In this article, we rapidly produced SARS-CoV-2 antigens, immunized hens and purified IgY antibodies in 2 months after the SARS-CoV-2 gene sequence became public. We further demonstrated that the IgY antibodies competitively block RBD binding to ACE2, neutralize authentic SARS-CoV-2 virus and effectively protect hamsters from SARS-CoV-2 challenge by preventing weight loss and lung pathology, representing the first comprehensive study with IgY antibodies. The process of mass production can be easily implemented in most developing countries and hence could become a new vital option in our toolbox for combating viral pandemics. This study could stimulate further studies, optimization and potential applications of IgY antibodies as therapeutics and prophylactics for human and animals.

Trends in the mobility of primary healthcare human resources in underdeveloped regions of western China from 2000 to 2021: Evidence from Nanning

ObjectiveThis research aimed to identify the fundamental and geographic characteristics of the primary healthcare personnel mobility in Nanning from 2000 to 2021 and clarify the determinants that affect their transition to non-primary healthcare institutions.MethodsThrough utilizing the Primary Healthcare Personnel Database (PHPD) for 2000–2021, the study conducts descriptive statistical analysis on demographic, economic, and professional aspects of healthcare personnel mobility across healthcare reform phases. Geographic Information Systems (QGIS) were used to map mobility patterns, and R software was employed to calculate spatial autocorrelation (Moran’s I). Logistic regression identified factors that influenced the transition to non-primary institutions.ResultsPrimary healthcare personnel mobility is divided into four phases: initial (2000–2008), turning point (2009–2011), rapid development (2012–2020), and decline (2021). The rapid development stage saw increased mobility with no spatial clustering in inflow and outflow. From 2016 to 2020, primary healthcare worker mobility reached its peak, in which the most significant movement occurred between township health centers and other institutions. Aside from their transition to primary medical institutions, the primary movement of grassroots health personnel predominantly directs towards secondary general hospitals, tertiary general hospitals, and secondary specialized hospitals. Since 2012, the number and mobility distance of primary healthcare workers have become noticeably larger and remained at a higher level from 2016 to 2020. The main migration of primary healthcare personnel occurred in their districts (counties). Key transition factors include gender, education, ethnicity, professional category, general practice registration, and administrative division.ConclusionsThis study provides evidence of the features of primary healthcare personnel mobility in the less developed western regions of China, in which Nanning was taken as a case study. It uncovers the factors that impact the flow of primary healthcare personnel to non-primary healthcare institutions. These findings are helpful to policy refinement and support the retention of primary healthcare workers.

A parameter to featuring the cultural landscape genes of traditional settlements in China: a perspective of geographical information

Creative transformation and innovative development of traditional cultures is a pressing social need in China because of the deep reform and rapid socio-economic developments. It is crucial to understand the natural features of cultural landscapes of traditional settlements because they are indispensable components of these heritages. Although there are significant findings on the cultural features of traditional settlements, people still face substantial difficulties in using Geographical Information Systems (GIS) to directly handle their cultural factors due to a lack of theoretical models or described methods. To address this issue, at first, this study analyzed the component elements and contents of Cultural Landscape Genes of Traditional Settlements (CLGTS) from the perspective of Geographical Information (GI). Then, the concept “Feature Parameter of Geographical Information of CLGTS (FPGI-CLGTS)” was proposed based on the above. Simultaneously, the connotations, identification rules, and mathematical meanings of FPGI-CLGTS were also explored deeply. Next, this study developed the identification methods of FPGI-CLGTS. Finally, this study examined FPGI-CLGTS through an experiment on the spatial layouts CLGTS of six samples in Hunan, China. Through this study, FPGI-CLGTS has enormous potential to reveal the critical cultural features and values of traditional settlements.

Microbial remediation of petroleum-contaminated soil focused on the mechanism and microbial response: a review.

The environmental pollution caused by petroleum hydrocarbons has received considerable attention in recent years. Microbial remediation has emerged as the preferred method for the degradation of petroleum hydrocarbons, which is experiencing rapid development driven by advancements in molecular biology. Herein, the capacity of different microorganisms used for crude oil bioremediation was reviewed. Moreover, factors influencing the effectiveness of microbial remediation were discussed. Microbial remediation methods, such as bioaugmentation, biostimulation, and bioventilation, are summarized in this review. Aerobic and anaerobic degradation mechanisms were reviewed to elucidate the metabolic pathways involved. The impacts of petroleum hydrocarbons on microorganisms and the environment were also revealed. A brief overview of synthetic biology and a unique perspective of technique combinations were presented to provide insight into research trends. The challenges and future outlook were also presented to stimulate contemplation of the mechanisms involved and the development of innovative techniques.

E-COMMERCE IN INTERNATIONAL BUSINESS

Opportunities abound for divers in the global economic arena, but maintaining a steady footing can be difficult. While combining IB with e-commerce will certainly make things more complicated, it will also make trade easier and eliminate a lot of other problems. The free flow of goods, services, and ideas has flourished as a result of the stronger bonds that have been forged between nations through international trade. Worldwide trade encompasses all economic activities that facilitate the exchange of products, services, people, ideas, and technology beyond national borders. Anything a business does inside its own country is considered to be part of its internal operations. International commerce refers to the purchasing and selling of products and services across international borders, whereas international businesses are those that participate in this activity. Such trade procedures can be owned by a private company or the state. Furthermore, the national economy remains stable. A dangerous country can overcome any obstacle. The strategic planning of a multinational firm should be based on the resources, goals, and objectives of the company. Keywords: International business, e-commerce integration, cross-border trade, rapid development, global relationships, flow of goods and services, cross-border allocation, internal business operations, international commerce, economic stability, strategic development.

Analysis Testing Black Box and White Box on Application To-Do List Based Web

The rapid development of information technology has led to the creation of numerous web-based applications designed to assist human activities and work. One such application is the To-Do List, which helps users manage their tasks and increase productivity. This study aims to analyze the quality of web-based To-Do List applications through black box and white box testing. The research focuses on the login and main pages of the application, where various scenarios are tested to ensure that the system functions as intended. The testing process includes designing test scenarios, creating test cases, executing the test cases, and collecting and processing test result data. The study also includes an analysis of the program's source code using flowcharts and flowgraphs to identify the number of independent logic execution paths and design test cases for white box testing. The results of the testing will help identify errors and weaknesses in the application, ensuring that the final product is of high quality.

A new framework for ethical artificial intelligence: keeping HRD in the loop

ABSTRACT As a result of the rapid development of technologies, artificial intelligence (AI) is changing human experiences and workplaces in ways that we are not prepared for. Recognized as a double-edged tool, AI has brought both positive and negative outcomes to organisations and employees. With its increasing popularity in the workplace and our daily practice, how to use AI intelligently and responsibly has become a top concern raised by both academics and practitioners. In this article, we discuss the desired and unintended consequences of AI as documented in current literature, examine the ethical concerns, and identify current solutions. We propose ‘keeping HRD in the loop’ as a means to addressing ethical challenges associated with AI and offer a new conceptual framework as a tool for reference. Integrating general AI principles and ethical guidelines developed by the Academy of HRD, we map out an ethical boundary consisting of nine human-centred principles and suggest a sample of six HRD interventions that can facilitate responsible AI practices and productive human-machine interfaces. By bringing HRD perspectives into the domain of AI practice, we hope to bring ethical considerations to the forefront of AI decision-making and stimulate more interest in interdisciplinary research and academic-industry collaboration.

Genetic Mutations in FKS1 Gene Associated with Acquired Echinocandin Resistance in Candida parapsilosis Complex.

Candida parapsilosis complex has recently received special attention due to naturally occurring FKS1 polymorphism associated with high minimal inhibitory concentrations for echinocandin and the increase of clonal outbreaks of strains resistant to commonly used antifungals such as fluconazole. Despite the previous fact, little is known about the genetic mechanism associated with echinocandin resistance. Therefore, the present study was designed to investigate the mechanism of acquired echinocandin resistance in C. parapsilosis complex strains. A total of 15 clinical C. parapsilosis complex isolates were sub-cultured for 30days at a low concentration of micafungin at ½ the lowest MIC value of the tested isolates (0.12µg/ml). After culturing, all the isolates were checked phenotypically for antifungal resistance and genotypically for echinocandin resistance by checking FKS1 gene hot spot one (HS1) and HS2 mutations. In vitro induction of echinocandin resistance confirmed the rapid development of resistance at low concentration micafungin, with no difference among C. parapsilosis, C. metapsilosis, and C. orthopsilosis in the resistance development. For the first time we identified different FKS1 HS1 and or HS2 mutations responsible for echinocandin resistance such as R658S and L1376F in C. parapsilosis, S656X, R658X, R658T, W1370X, X1371I, V1371X, and R1373X (corresponding to their location in C. parapsilosis) in C. metapsilosis, and L648F and R1366H in C. orthopsilosis. Our results are of significant concern, since the rapid development of resistance may occur clinically after short-term exposure to antifungals as recently described in other fungal species with the potential of untreatable infections.

Factors That Encourage Investors to Decide to Invest in Shares in the Capital Market for the 2020-2023 Period (Covid-19 Pandemic): Systematic Literature Review

Investment is a very important element for a country because it has two roles, namely as a supporter of income and a driver of economic growth. In this research, the author analyzes what factors encourage investors to decide to invest in shares in the capital market. This research uses the Systematic Literature Review (SLR) method. This research comes from articles published in 2020-2023 found in Publish or Perish and Google Scholar. Data is collected, identified and assessed before being systematically reviewed with the aim of supporting further research. The results of this review show that during the Covid-19 pandemic, many investors made stock investment decisions in the capital market due to psychological factors. As a result of the economic problems that have arisen as a result of the Covid-19 pandemic, many people's perspectives have changed from previously preferring traditional investments such as deposits to looking for investment options that provide high returns such as mutual funds and shares with different investment objectives. This is also supported by the rapid development of digital and information technology during the Covid-19 pandemic, which has caused public participation in the capital market to increase. Many fintech companies that adopt automatic investment technology are able to remove obstacles for potential investors who lack investment literacy and limited capital without having to study and understand the entire investment scheme in the capital market. Apart from that, financial literacy is also mentioned as a factor that can determine stock investment decisions because the knowledge that comes from literacy will strengthen stock investment decisions.

Enhancing Power Grid Data Analysis with Fusion Algorithms for Efficient Association Rule Mining in Large-Scale Datasets

Against the backdrop of the rapid development of information technology, the total amount of data has exploded, and efficient association rule mining methods for large-scale datasets have been studied. Conventional rule mining algorithms are subject to electrical constraints when working, and their convergence speed and data noise are currently the main problems they face. In order to accelerate the working process of the algorithm, this study introduces a data warehouse into the K-Means algorithm, and connects the time series and voltage interaction functions with the long-and-short-term memory network for efficient information analysis of power grid data, generating fusion algorithms. The study conducted experiments on the Netloss dataset and simultaneously conducted experiments on three models, including long-and-short-term memory networks, to verify the superiority of the fusion algorithm. Under the same experimental voltage, the circuit power flows of the four models were 0.37, 0.64, 0.79, and 0.82A, respectively, indicating that the algorithm effectively controlled the electrical dataset. Its measurement accuracy was the highest among the four models, at 91.7%. The experimental results show that the fusion algorithm proposed in the study has precise control ability in power grid datasets, and can effectively mine association rules on large-scale datasets.

Primary school students’ perceptions of artificial intelligence – for good or bad

AbstractSince the end of 2022, global discussions on Artificial Intelligence (AI) have surged, influencing diverse societal groups, such as teachers, students and policymakers. This case study focuses on Swedish primary school students aged 11–12. The aim is to examine their cognitive and affective perceptions of AI and their current usage. Data, comprising a pre-test, focus group interviews, and post-lesson evaluation reports, were analysed using a fusion of Mitcham’s philosophical framework of technology with a behavioural component, and the four basic pillars of AI literacy. Results revealed students’ cognitive perceptions encompassing AI as both a machine and a concept with or without human attributes. Affective perceptions were mixed, with students expressing positive views on AI’s support in studies and practical tasks, alongside concerns about rapid development, job loss, privacy invasion, and potential harm. Regarding AI usage, students initially explored various AI tools, emphasising the need for regulations to slow down and contemplate consequences. This study provides insights into primary school students perceptions and use of AI, serving as a foundation for further exploration of AI literacy in education contexts and considerations for policy makers to take into account, listening to children’s voices.

The Influence of Political Memes on Political Marketing Strategy in Malaysia

Rapid development and quick-moving media not only change how people behave and communicate but also completely alter the marketing approach used to promote politics to maintain political power. The usage of memes in politics has also altered the agenda-setting of social groups that are concerned with Malaysian politics. This study aims to examine the impact of political memes on Malaysian youth, particularly on their decision to vote in general elections at the age as early as of 18. It also tries to examine the elements that make memes effective political marketing tools. Using a quantitative study involving 400 young people, it discovered that politics and memes had an impact on the younger generation. Further study is imperative to investigate on the young people preference that influenced their political decision making.

Antitrust Law in the BRICS Countries: A Review and Critique

A growing trend shows that global economic power is shifting away from the United States and Europe and towards the BRICS nations. The BRICS nations are predicted to hold the dominant position in the world by 2050. The rapid development of these economies and their markets is also raising a serious concern for the national antitrust enforcement authorities of the BRICS countries in their respective jurisdictions. This study attempts to examine the effectiveness of antitrust law, with a special focus on new developing trends in each of the BRICS jurisdictions. In addition, the study examines the proposed changes and limitations of the Indian Competition (Amendment) Bill 2022. The study reveals that the national antitrust laws and their enforcement processes are not fully developed and in need of considerable changes. Furthermore, the study indicates that while the proposed Amendment Bill 2022 is a progressive step in the right direction, it fails to cover certain key areas of the digital era, requiring further modifications to anticipate future impacts of economic development. In conclusion, the author recommends some points for effective policymaking, along with their future implications.

Effect of Tip Gap Size on the Tip Flow Structure and Turbulence Generation in a Low Reynolds Number Compressor Cascade

Abstract Efficient and compact axial compressors are currently undergoing rapid development for use in microcooling systems and small-scale vehicles. Limited experimental work concentrates on the inner flow field of the compressors working at such low Reynolds numbers (Re∼104). This study examines the vortical structures and the resulting turbulence production in the transitional flow over a C4 compressor blade at a Reynolds number Re of 24,000, with a specific focus on the impact of tip clearance. The particle image velocimetry measurements reveal the tip flow structures in detail, including the tip leakage vortex (TLV) and its induced complex vortical structures. The tip secondary flow at the low Reynolds number can be divided as the tip leakage flow (TLF)/vortex and transitional boundary layer both at the end walls and the blade surfaces. The TLV propagates at the highest spanwise positions and farthest pitchwise positions at the middle tip gap size (τ/C = 3%) for the three tip gap sizes investigated. The tip flow fluctuations decrease from τ/C = 5% to τ/C = 3% and then increase from τ/C = 3% to τ/C = 1%. The spatial distribution, streamwise evolution, and individual Reynolds normal stress components contributing to the turbulent kinetic energy (TKE) are discussed. The primary contributors to the turbulence generation are examined to elucidate the flow mechanism leading to the distinct anisotropic turbulence structure in the tip region with various tip gap sizes.

ON SOME APPROACHES TO REGULATING DIGITAL ECOSYSTEMS

The dichotomy of development and regulation of digital ecosystems has attracted the attention of many theorists and practitioners over the past 10 years. The emergence and poorly regulated development of electronic platforms and ecosystems contributed to the formation of a new business model that did not fit into the coordinates of the legal institutions of the functioning of the traditional economy. In the process of their expansion, digital platforms have demonstrated a number of advantages over traditional business models, while simultaneously increasing their fundamental disadvantages. The article reveals the causes of the emergence and rapid development of digital ecosystems, the phenomenon of ecosystem's dependence. The pros and cons of ecosystem's functioning, the formation of their monopolistic essence, the violation of fundamental market laws, and the factors of their destructive influence on the modern economy, society, and consumers are analyzed. The main directions of activity of national regulators in the USA, the EU, and Russia are presented.

Multifunctional Hydroxylamine‐O‐Sulfonic Acid as Additives for Highly‐Efficient and Stable Perovskite Solar Cells

Despite the rapid development of perovskite solar cells (PSCs), defects in the devices continue to impede further improvements in power conversion efficiency (PCE) and operational stability. This work describes the use of hydroxylamine‐O‐sulfonic acid (HOSA) as a bifunctional molecule to enhance the performance of PSCs. Strong coordination between the sulfonic acid group and uncoordinated Pb2+, while the N‐H bond on amino group and uncoordinated I‐ are observed. Thus, due to the synergistic contribution of sulfonic acid group and amino groups, the high‐quality perovskite film with good crystallinity and low defect density is achieved. As a result, the optimal devices exhibit an enhanced efficiency of 23.33%, which is much higher than that of the control device (21.53%). Notably, the optimized target device exhibited excellent long‐term operational stability, retaining over 90% of its initial efficiency after 480 hours at 65 °C, over 93% after a continuous illumination test for 650 hours, and over 96% after nearly 1400 hours of air storage. In contrast, the control device demonstrated poorer stability. These results suggest that selecting a dual‐functional additive is a promising approach to enhance efficiency and maintain stability in PSCs.This article is protected by copyright. All rights reserved.