Relevant Research Fields Research Articles

Bibliometricanalysis and visualization of endocrine therapy for breast cancer research in the last two decade.

Breast cancer endocrine therapy research has become a crucial domain in oncology since hormone receptor-positive breast cancers have been increasingly recognized, and targeted therapeutic interventions have been advancing over the past few years. This bibliometric analysis attempts to shed light on the trends, dynamics, and knowledge hotspots that have shaped the landscape of breast cancer endocrine therapy research between 2003 and 2022. In this study, we comprehensively reviewed the scientific literature spanning the above-mentioned period, which included publications accessible through the database of the Web of Science (WOS) and the National Center for Biotechnology Information (NCBI). Next, a systematic and data-driven analysis supported by sophisticated software tools was conducted, such that the core themes, prolific authors, influential journals, prominent countries, and critical citation patterns in the relevant research field can be clarified. A continuous and substantial expansion of breast cancer endocrine therapy research was revealed over the evaluated period. A total of 1,317 scholarly articles were examined. The results of the analysis suggested that research on endocrine therapy for breast cancer has laid a solid basis for the treatment of hormone receptor-positive breast cancer. From a geographical perspective, the US, the UK, and China emerged as the most active contributors, illustrating the global impact of this study. Furthermore, our analysis delineated prominent research topics that have dominated the discourse in the past two decades, including drug therapy, therapeutic efficacy, molecular biomarkers, and hormonal receptor interactions. This comprehensive bibliometric analysis provides a panoramic view of the ever-evolving landscape of breast cancer endocrine therapy research. The findings highlight the trajectory of past developments while signifying an avenue of vast opportunities for future investigations and therapeutic advancements. As the field continues to burgeon, this analysis will provide valuable guidance for to researchers toward pertinent knowledge hotspots and emerging trends, which can expedite the discoveries in the realm of breast cancer endocrine therapy.

Advanced two-objective optimization of thickness and large-area homogeneity of ZnO ultrathin films deposited by atomic layer deposition

Semiconductor thin films and coatings have become one of the most relevant research fields due to their significant applications in priority energy-related technologies such as solar cells, photocatalysts, and smart windows. Since all these fields are conceived as tools to fight against the effects of climate change, a real impact requires the successful deposition of semiconductor films on large-area substrates such as windows, panels, pipes, and containers, to give rise to photoactive components suitable for buildings, industries, cars, and parks. However, scalability remains one of the major issues in almost all methodologies known for the deposition of semiconductor films, irrespective of the phase approach used, i.e., either from vapor- or liquid-phase. Here, a mathematical metamodel was applied to simulate the atomic layer deposition (ALD) of zinc oxide (ZnO) ultrathin films (a versatile photoactive material in energy-related research) and optimized their thickness and homogeneity over the whole area of 8 in.-diameter Si wafers. Knowing all ALD parameters that define the quality and properties of the deposited films, we delimitated a set of four metamodel-inputs (zinc precursor dose, purge, and the inner and outer carrier gas flows) based on literature review, expertise, costs, and reactor design aspects specific to the deposition of ZnO. The average thickness and homogeneity of the films were established as the two outputs of the metamodel, which were the object of optimization. Using advanced iterative procedures, we carried out three rounds of experiments that lead us to a set of ALD parameters to deposit a ZnO ultrathin film with an average thickness of 11.38 nm that leads to a deposition rate of 1.9 Å/cycle, which represents 90% of the highest reported value for ZnO by ALD (2.1 Å/cycle). The homogeneity over the whole 8 in.-diameter wafer reached 2.61 nm, which represents the smoothest distribution of thickness values in the entire deposited area. Given the origin of the limits constraining this optimization procedure, our results hold promise in supporting the transition from the laboratory-level synthesis of thin-film-based optoelectronic devices to their large-scale production. This could ultimately help to circumvent the difficulties faced in scaling the ALD technology and enable alternative deposition methodologies such as thermal ALD, otherwise inaccessible to the production chain.

On the Application Potential of Chemically Tailored Metal Oxide and Higher Chalcogenide Nanoparticles for Nanoscale Resistive Switching Devices

Resistive switching (RS) for nonvolatile data storage is a highly relevant field of research. Up to now, RS devices are fabricated via semiconductor processing technologies. This poses the question of whether integration of chemically tailored nanoparticles, either consisting of valence change or phase change materials, can be integrated in nanoelectrode configurations in order to explore their functionality for RS applications. This review discusses the RS properties of such nanoparticles by means of selected examples of both nanoparticle assemblies as well as on the individual particle level. Although this field of research is rather unexplored, it becomes evident that chemically tailored nanoparticles bear great potential for RS applications.

Relationship between climate change and tourism: an integrative review

ABSTRACT The relationship between tourism and climate change has been explored and studied for a considerable amount of time. In the past quarter-century, more specialised research has emerged, and most recently, the subject of adaptation has been highlighted as an essential study requirement in tourism and climate change studies. This study offers a comprehensive literature assessment on climate change and tourism to date. We did a Boolean-based search on Scopus and got 703 records, which were then analysed bibliometrically using the bibliometrix package of R. It covers adaptation issues, the characteristics of vulnerability in a tourism setting, and the ramifications of such research for local communities. This study illustrates the difficulties associated with the interdependence of climate change and tourism by presenting the most relevant authors, countries, key terms, and research fields. In addition to descriptive insights into the field, we provide the conceptual framework (keyword analysis and thematic map). In addition to bibliometrically evaluating the publications, we closely reviewed the sample studies to gain a more comprehensive picture of the literature on climate change and tourism. Our evaluation reveals significant knowledge gaps and offers future research and policy objectives. Our study has suggested multiple research avenues for this topic.

Responses and Reflections on Scott's Study of Zomia in Recent Years in Domestic Academia

James Scott, a professor of political science and anthropology in the United States, proposed the influential "Zomia" theory in his book The Art of Not Being Governed: An Anarchist History of Upland Southeast Asia. The theory has garnered significant international interest and has yielded numerous research findings. Meanwhile, the domestic academic community has shown little regard for the book. Until 2016, when the Chinese translation of Scott’s "Zomia" was published in China, the impact of his theory in the Chinese literary world had been significant, prompting lively discussions among numerous scholars. Local scholars utilized their own research experience to either introduce it as a new theory and method into their research practice or thoroughly analyze its viewpoints, contents, theories, and methods. This paper analyzes the role and significance of Scott's book in relevant research fields by combining domestic research. The aim is to provide a reference for further research in these fields.

Reexamining the Impact of Global Value Chain Participation on Regional Economic Growth: New Evidence Based on a Nonlinear Model and Spatial Spillover Effects with Panel Data from Chinese Cities

This study utilizes panel data drawn from 239 Chinese cities, and it employs fixed-effects models, mediation models, and spatial spillover models to reexamine the actual impact of the global value chain’s (GVC) participation on regional economic growth. The findings reveal that this impact exhibits a U-shaped nonlinear pattern, with the turning point of GVC occurring at 0.45, which is higher than that of 222 cities. Most cities are on the left side of the U-shaped curve, which corresponds with the second stage of the “in-out-in-again” GVC participation pattern (i.e., the “out” stage). During this stage, a decline in foreign value-added ratio (FVAR), with regard to exports (accompanied by an increase in the domestic value-added ratio), promotes economic growth. Innovation capability acts as a mediator in the relationship between GVC participation and economic growth. Furthermore, GVC participation has significant spillover effects on neighboring cities, with siphon and spillover effects coexisting. Thus, China should focus on establishing domestic value chains and innovation systems, achieving relative independence from existing GVCs dominated by developed countries, enhancing indigenous innovation capabilities, and laying the foundation for the third stage (in-again) of reintegration into GVCs, at the high value-added end, to achieve a higher level of openness. This study explores the nonlinear impact of GVC participation on regional economic growth in China from both theoretical and empirical perspectives, focusing on the finest divisions that remain feasible—cities. This approach expands and supplements the relevant field of research in valuable ways, yielding more realistic research conclusions and policy recommendations.

S15-2 Physical activity, sedentary behaviour, and cognitive function among older adults: a bibliometric analysis of literature from 2002 to 2022

Abstract Purpose Physical activity and sedentary behaviour have received intense interest in recent decades from a variety of stakeholders due to their diverse association with cognitive function, which is a key component in maintaining health of older adults. The aim of this bibliometric analysis is to reveal the developmental structure, research hotspots, and predict future trends in the field of physical activity, sedentary behaviour, and cognitive function research among older adults. Methods This study adhered strictly to the step-by-step guideline of bibliometric analysis. Publications in this field from 2002 to 2022 were retrieved from the Web of Science Core Collection. Only original articles and review articles published in English were included in the analysis. A cubic polynomial was applied to determine the publication trends. CiteSpace (6.1.R4 Basic) and VOSviewer (1.6.18) were performed to obtain collaborative networks, reference co-cited networks, and keyword co-occurrence networks, as well as to perform burst analysis to predict future trends. Results A total of 1093 publications were retrieved, of which 73.56% obtained research grants. The publications were cited 30,317 times. Within two decades there was rapid growth in publications in this field. The USA (329 items, 30.10%) and China (136 items, 12.44%) were the top contributors, and the USA had the strongest collaborative network. University of British Columbia (41 items, 3.75%) and University of California System (40 items, 3.66%) were the most active institutions. Liu-Ambrose T (32 items, 2.93%) and Shimada H (20 items, 1.83%) contributed to the largest number of publications. Journal of Aging and Physical Activity, and Frontiers in Aging Neuroscience were the most active journals. Reference co-cited networks, and keyword co-occurrence networks revealed that hotspots in this field were age, nursing home resident, tai chi, and perceptions, while future trends in this field were healthy ageing, qi gong, sedentary behaviour, and falls. Conclusions There has been an increased research interest in the interrelationships between physical activity, sedentary behaviour, and cognitive function in older adults in the past two decades. Our findings will help researchers, practitioners, and other stakeholders to understand the structure and hotspots in this relevant field of research. Funding Not applicable.

Causal inference in the age of big data: blind faith in data and technology

PurposeIn the era of big data, there is doubt about the significance of causal inference as a paramount scientific task in the social sciences. Meanwhile, data-mining techniques rooted in big data and artificial intelligence (AI) have infiltrated numerous aspects of social science research. This study aims to expound the criticality of discerning causal relationships – beyond mere correlations – and scrutinizes the ramifications of big data and AI in the identification of causality.Design/methodology/approachThis study discusses the challenges and opportunities for causality identification in the era of big data under the framework of potential outcomes model and structural causal model.FindingsFirst, even in the age of big data, correlations that lack interpretability, robustness and feasibility cannot substitute causality. Second, the richness of the sample size does not help solve the problem of systematic bias in the process of causal inference. Furthermore, current AI research targets correlations rather than causality, thus creating difficulties in advancing from observations to counterfactuals.Originality/valueThis study provides insights into the impact of big data era on causal inference in the social sciences, with a view toward enhancing the pool of theoretical concepts available to researchers in relevant fields and accurately guiding the direction of scientific research in these fields.

NETWORK INTRUSION DETECTION USING HYBRID MACHINE LEARNING METHODS

Network intrusion detection is a relevant cybersecurity research field. The growing number of intrusions requires more sophisticated methods to protect computer networks. Various machine learning algorithms are used to detect network intrusions and anomalies, but their accuracy is limited. In this research, we address the problem of improving network-level intrusion detection by applying hybrid machine-learning algorithms. The paper proposes three new hybrid machine learning methods and investigates their accuracy using two publicly available datasets CSE-CIC-IDS2018 and NSW-NB-15. In order to increase the accuracy of the classification models, hyperparameter optimization was performed. The iteration method and the Chi-square χ2 test were used to identify significant features of the data set. Analyzing the research results, it was found that the highest network anomaly recognition accuracy of 99.34% was achieved by applying a hybrid algorithm consisting of a decision tree, naive Bayesian, and multilayer perceptron algorithms. Achieved result is 3.13% higher than the best accuracy achieved by individual machine learning algorithms. In order to comprehensively evaluate the studied machine learning algorithms and their suitability for detecting intrusions in a computer network, the algorithms were ranked using the SCR, DR, FR ranking methods.

Concept and signs of legal relations in the field of medical care

The paper is dedicated to clarifying the concept and characteristics of legal relations in the field of medical care. It is noted that no civil-legal problem, including the issue of legal relations in the provision of medical care, can be properly studied without prior analysis of the basic concepts in the relevant field of scientific research. It is pointed out that the study of the content of terms related to the implementation of the right to medical care is especially relevant at the current stage, when the domestic health care system, including the provision of medical assistance, is in a state of transformation, taking into account the unfinished medical reform and ongoing war. Today, it is obvious that further scientific developments in this direction are necessary to produce practical proposals for improving the relevant regulatory regulation, which, in turn, should provide the possibility of timely and proper medical care to those who need it to restore health, and often to save life. In addition, it is noted that the signs of personal non-property relationships, to which legal relations in the field of medical care belong, are derivative of the signs of personal non-property rights based on certain non-property benefits. Based on the characteristics of general and special legal relations in the field of medical care, the author proposes its own definition of the concept of these legal relations and concludes that they are of a civil-legal nature, since the participants are independent and equal subjects, and these legal relations arise mainly on the basis of civil contracts.

Pythagorean fuzzy information processing based on centroid distance measure and its applications

By using Pythagorean fuzzy set (PFS), people can quantitatively describe and process information with fuzziness, and then make reasonable and effective judgments or decisions. In this process, distance measure often serves as a useful and important tool. The purpose of this paper is to explore some information processing methods and techniques in Pythagorean fuzzy environment. Firstly, the research progress of PFS is reviewed, and the main research directions and some hot issues in relevant research fields are discussed. Secondly, by analyzing the information of hesitation degree of Pythagorean fuzzy number (PFN), definitions of hesitation factor and centroid distance measure based on the representation of centroid coordinates of the hesitation regions are proposed, and properties of hesitation factor and centroid distance measure are discussed. Finally, the novel clustering algorithm, ranking method and multi criteria decision making (MCDM) method are developed in Pythagorean fuzzy environment, which are based on the new centroid distance measure. The effectiveness of the proposed algorithm and methods are verified through numerical examples and comparative analysis. The research results indicate that the centroid distance measure proposed in this paper can effectively characterize the distance between PFNs, thus making the clustering algorithm of PFNs, the ranking method of PFNs, and the Pythagorean fuzzy MCDM method have obvious superiorities and advantages.

Application of Graphene-Combined Rare-Earth Oxide (Sm2O3) in Solar-Blind Ultraviolet Photodetection.

Rare-earth oxide Sm2O3 is theoretically expected to be used in the preparation of ultraviolet (UV) detectors with low dark currents and high radiation resistance due to its characteristics of a wide bandgap, a high dielectric constant, and high chemical stability. However, certain features that rare-earth oxides possess, such as high resistivity and weak photoelectric response currents, have hindered relevant research on these kinds of materials in the field of UV detection. In this work, a p-Gr/i-Sm2O3/n-SiC heterojunction photovoltaic solar-blind UV sensor was constructed for the first time. Because of the high mobility of graphene (Gr) and the contribution of double built-in electric fields in the heterojunction, the collection efficiency of photogenerated carriers has been greatly improved, with the typical shortcomings of high resistivity and poor photoelectric response performance of rare-earth oxides having been overcome. This detector has exhibited outstanding performance at 0 V, including a responsivity of 19.8 mA/W and an open-circuit voltage of 0.68 V. Additionally, this detector has a detectivity as high as 1.2 × 1011 jones, which is at the front position of most ultraviolet detectors. The fabrication of this high-performance Sm2O3-based photovoltaic UV detector has broadened the application fields of rare-earth oxide semiconductors. Therefore, this project has important value for future research in relevant fields.

Book Review Advanced Materials for Wastewater Treatment and Desalination: Fundamentals to Applications

Book Review Advanced Materials for Wastewater Treatment and Desalination: Fundamentals to Applications

Information and communication integration in smart factory design

Strategic smart factory design is essential to utilize Industry 4.0 technologies in production environments effectively. Although a series of earlier reviews in the context of smart manufacturing have been published, so far none addresses smart factory design, i. e. the planning and operation of smart factories. This review provides an overview of recent research in the field by systematizing opportunities, risks and success factors of smart factory design as available from recent empirical studies (2018-2022). Businesses are informed how smart factory design should be approached and implemented to realize cost advantages and increase competitiveness. Academic research benefits of a classification of relevant issues and open research fields are outlined.

Derivatives of 2-Pyridone Exhibiting Hot-Exciton TADF for Sky-Blue and White OLEDs.

Development of emissive materials for utilization in organic light-emitting diodes (OLEDs) remains a highly relevant research field. One of the most important aspects in the development of efficient emitters for OLEDs is the efficiency of triplet-to-singlet exciton conversion. There are many concepts proposed for the transformation of triplet excitons to singlet excitons, among which thermally activated delayed fluorescence (TADF) is the most efficient and widespread. One of the variations of the TADF concept is the hot exciton approach according to which the process of exciton relaxation into the lowest energy electronic state (internal conversion as usual) is slower than intersystem crossing between high-lying singlets and triplets. In this paper, we present the donor-acceptor materials based on 2-pyridone acceptor coupled to the different donor moieties through the phenyl linker demonstrating good performance as components of sky-blue, green-yellow, and white OLEDs. Despite relatively low photoluminescence quantum yields, the compound containing 9,9-dimethyl-9,10-dihydroacridine donor demonstrated very good efficiency in sky-blue OLED with the single emissive layer, which showed an external quantum efficiency (EQE) of 3.7%. It also forms a green-yellow-emitting exciplex with 4,4',4″-tris[phenyl(m-tolyl)amino]triphenylamine. The corresponding OLED showed an EQE of 6.9%. The white OLED combining both exciplex and single emitter layers demonstrated an EQE of 9.8% together with excellent current and power efficiencies of 16.1 cd A-1 and 6.9 lm W-1, respectively. Quantum-chemical calculations together with the analysis of photoluminescence decay curves confirm the ability of all of the studied compounds to exhibit TADF through the hot exciton pathway, but the limiting factor reducing the efficiency of OLEDs is the low photoluminescence quantum yields caused mainly by nonradiative intersystem crossing dominating over the radiative fluorescence pathway.

Effects of applied external fields on the nonlinear optical second harmonic generation in a GaAs/Ga0.7Al0.3As quantum dots

This work has studied some nonlinear optical properties of Al0.3Ga0.7As/GaAs quantum dot system with tangent-square potential (TSP), with special emphasis on the role of second harmonic generation (SHG) coefficient under hydrostatic pressure and temperature. Due to the strain of external application conditions, the changes of the energy level and wave function of the neutron band in the system structure provide valuable insights into the optical properties of the quantum dot structure. In this paper, we report the effects of structural parameters, temperature and hydrostatic pressure on the SHG coefficient. According to the results obtained in the work, it can be reported that the nonlinear optical properties of the quantum dot system can be improved by adjusting the hydrostatic pressure and temperature. At the same time, the interaction of various parameters has produced some interesting observations, which are relevant in relevant research fields.

Quantum Power Electronics: From Theory to Implementation

While impressive progress has been already achieved in wide-bandgap (WBG) semiconductors such as 4H-SiC and GaN technologies, the lack of intelligent methodologies to control the gate drivers has prevented exploitation of the maximum potential of semiconductor chips from obtaining the desired device operations. Thus, a potent ongoing trend is to design a fast gate driver switching scheme to upgrade the performance of electronic equipment at the system level. To address this issue, this work proposed a novel intelligent scheme for the control of gate driver switching using the concept of quantum computation in machine learning. In particular, the quantum principle was incorporated into deep reinforcement learning (DRL) to address the hardware limitations of conventional computers and the growing amount of data sets. Taking potential benefit of the quantum theory, the DRL algorithm influenced by quantum specifications (referred to as QDRL) not only ameliorates the performance of the native algorithm on traditional computers but also enhances the progress of relevant research fields like quantum computing and machine learning. To test the practicability and usefulness of QDRL, a dc/dc parallel boost converter feeding constant power loads (CPLs) was chosen as the case study, and several power hardware-in-the-loop (PHiL) experiments and comparative analysis were performed.

A proper orthogonal decomposition analysis upon aerodynamic structures under clean and rough conditions

A transitional flow regime is known to induce complex flow structures upon aerodynamic geometries such as airfoils, and the dynamics of laminar separation bubbles (LSBs) pose a relevant research field. In addition to being affected by the Reynolds value itself, LSBs are shown to be equally sensitive to the surface roughness of the airfoils. The study analyses wind tunnel-derived surface-pressure distribution datasets obtained for a particular airfoil of the standard family developed by the National Advisory Committee for Aeronautics (NACA), namely, the NACA0021, subjected to the range 0.8×104<Re<1.6×104 at different angles of attack under two flow configurations that correspond to a clean and roughened surface. The analysis is undertaken via the proper orthogonal decomposition (POD) technique. The results show that the decomposition of the temporal series of surface-pressure data and the processing of the most energetic POD modes recovers the position of the LSBs, properly capturing the closure point of the separation bubbles and, hence, the turbulence transition location. Some of the most energetic POD modes observed are closely related, in terms of shape, to the POD modes present at the reattachment point on a 5:1 rectangular cylinder. This could indicate there is a recognizable pattern in coherent structures of pressure fluctuations when it comes to a reattached flow. Therefore, a principal component analysis such as the POD presented in this study can be used to determine the reattachment position of the flow or the transition point in the presence of a LSB.

Guidelines to Analyze Preclinical Studies Using Perinatal Derivatives.

The last 18 years have brought an increasing interest in the therapeutic use of perinatal derivatives (PnD). Preclinical studies used to assess the potential of PnD therapy include a broad range of study designs. The COST SPRINT Action (CA17116) aims to provide systematic and comprehensive reviews of preclinical studies for the understanding of the therapeutic potential and mechanisms of PnD in diseases and injuries that benefit from PnD therapy. Here we describe the publication search and data mining, extraction, and synthesis strategies employed to collect and prepare the published data selected for meta-analyses and reviews of the efficacy of PnD therapies for different diseases and injuries. A coordinated effort was made to prepare the data suitable to make statements for the treatment efficacy of the different types of PnD, routes, time points, and frequencies of administration, and the dosage based on clinically relevant effects resulting in clear increase, recovery or amelioration of the specific tissue or organ function. According to recently proposed guidelines, the harmonization of the nomenclature of PnD types will allow for the assessment of the most efficient treatments in various disease models. Experts within the COST SPRINT Action (CA17116), together with external collaborators, are doing the meta-analyses and reviews using the data prepared with the strategies presented here in the relevant disease or research fields. Our final aim is to provide standards to assess the safety and clinical benefit of PnD and to minimize redundancy in the use of animal models following the 3R principles for animal experimentation.

From Millennium Development Goals to Sustainable Development Goals: Transforming development communication to sustainability communication

At the highest international political level, the United Nations declared the Sustainable Development Goals (SDGs) in 2015 after having announced (and later not fulfilled) the Millennium Development Goals (MDGs) in 2000. This shift from the MDGs to the SDGs, in which the term development was replaced by the concept of sustainability, also demands a paradigm shift within the research field of development communication and communication for social change which needs to put the focus on sustainability, embracing the concept of sustainability communication as key when analyzing and practicing social change by the use of communication and media. The article unfolds this argument by explaining the political shift from the MDGs to the SDGs and the relevant research fields analyzing these different goals and then sketching the research areas of development communication and communication for social change as well as the one of sustainability communication. In bringing all these areas together, it is argued that the change of the political goals provokes the above mentioned paradigm shift in the research area of development communication. Transforming development communication into sustainability communication also allows to focus the broad term of communication for social change on a specific aim – which is sustainability.