Research Research Articles

Young Latinas/os’ Environmental Commitments: The Case of Waste

This participatory research project aimed to identify young people’s perceptions of the natural and built environment in their neighborhoods, including how social inequities shape those environments, and how their community and governments can improve them. The study took place with 25 young Latinas/os, ages 14 to 18, many of whom lived in a formerly unincorporated neighborhood (known as <em>colonia</em>) in Pharr, Texas, located in the state’s Rio Grande Valley region. Through a walkalong, photovoice, and focus groups, participants identified waste management as a resounding priority. Their reflections highlighted their motivations behind and actions toward addressing this problem. This study makes two empirical contributions to scholarly and applied discussions on young people’s outdoor experiences. First, young people’s prioritization of waste highlights the role that trash—often in the form of scattered objects, small and large—has in shaping young people’s outdoor experiences. Second, young people are committed to improving waste conditions through individual and group actions, and they identified needed structural changes. Pharr youths’ environmental commitments call for investment in waste management and set the stage for more generative ways of experiencing the natural environment.

Vegetal intimacies in science

ABSTRACT This paper examines relationships between Ugandan scientists and Their experimental banana plants. Transnational research project aims at introducing nutritionally improved bananas to Uganda, where over centuries the banana has written itself into everyday life, language, landscape and climate. The paper considers how the rhythms of the banana itself and the conventions of scientific handling shape forms of intimacy. In the context of biological research, where rapidly growing plants mean quick publications, scientists experience the banana’s slow pace as frustrating. While the banana’s temporality forces scientists to slow track their careers, biologists’ quotidian tasks consist of handling what they call ‘plant babies’ in the greenhouse, where vocabularies of love, nurturance and childcare abound. By examining the plant-scientist relationships, the paper proposes seeing intimacy as an embodied history. Unlike human-centred histories of great events and great men, foregrounding intimacy with plants draws attention to muted histories that perhaps have never been made explicit but still are sensed and felt, congealing in experience and quotidian practice. Thinking with such embodied histories allows appreciating unorthodox forms of expertise expressed in contemporary scientific practice and highlights their potential for reimagining convivial futures.

Circular economy education: student feedback from five higher education institutions in the Asia Pacific

Purpose The integration of circular economy (CE) into higher education programmes is a crucial step to facilitate a smooth transition towards circularity. Although existing studies highlight the lack of CE awareness as a primary barrier to achieving circularity, there is still limited research investigating the enhancement of CE understanding after completing CE-related training or courses. To address this gap, this study aims to examine how CE education transforms students’ mindsets to support the strategic application of CE principles and strategies in personal and professional activities. Design/methodology/approach An online survey was designed and distributed to students attending CE courses at five universities located in five countries. Ethics approval for this research project was obtained from University 3 as the lead of the research project. Out of a total of 138 students enrolled in these courses, 109 responses were collected. Findings The research findings demonstrate that CE education enhances students’ awareness of CE definitions, principles and strategies through developing their own descriptions of CE concepts and interpretation into personal and professional activities, showcasing practical circular applications. Practical implications This paper presents implications for programme coordinators, subject coordinators and lecturers/facilitators at universities/higher educational institutions to consider when designing a course or training workshop related to CE within a particular programme or discipline. Originality/value This study identifies invaluable insights of CE education to enhance students understanding and practical applications of circularity in their personal and professional activities. The research findings can be used for crafting and delivering CE courses in different universities. This study can be regarded as guidance to develop a CE curriculum for higher education nurturing a deep understanding of CE concepts while aligning with the industry demands for CE professionals.

Mentoring Early-Career Investigators of HIV/STI Health Disparities Research: A Study Examining the CAPS Visiting Professors Program.

To build research capacity for early-career faculty conducting HIV/STI research with minoritized communities and to enhance diversity in the scientific workforce, the University of California, San Francisco (UCSF) Center for AIDS Prevention (CAPS) conducts a training program for visiting professors (VPs), begun in 1996. VPs are in residence at CAPS for three summers, complete a pilot research project, and prepare National Institutes of Health (NIH) grant proposals. Best practices and key elements for successfully training scholars of color, and others who work with minoritized communities, are identified. This paper draws on qualitative interviews with 31 VPs and 10 program mentors (VPMs) who participated in the program between 1996 and 2016. All VPs were also invited to participate in an anonymous survey to assess potential differences between study participants and non-participants. Interviews took place between September 2017 and March 2018 and were audio-recorded, transcribed, and thematically coded. VPs and VPMs described key elements relevant to both human and social capital that contributed to Program success. Paramount among these were the importance of establishing trusting mentorship relationships; sustained collegial engagement over time; and fostering a training environment based on multidisciplinarity, skills-building, scholarly networking, and peer reviews. Participant voices from this objectively successful training program provide directions for future initiatives to support scholars of color and those working with minoritized groups. An indispensable value of such programs is to intentionally foster trusted scholarly communities to counterbalance systemic inequities in the academy.

Study of morphology, phase composition, optical properties, and thermal stability of hydrothermal zirconium dioxide synthesized at low temperatures.

Oxide nanoparticles exhibit unique features such as high surface area, enhanced catalytic activity, and tunable optical and electrical properties, making them valuable to various industry applications as well as for the development of new research projects. Nowadays, ZrO2 nanoparticles are widely used as catalysts and precursors in ceramic technology. Hydrothermal synthesis with metal salts is one of the most common methods for producing stable tetragonal-phase zirconium dioxide nanoparticles. However, hydrothermal synthesis requires relatively high process temperatures (160-200°C) and the use of advanced heat-resistant autoclaves capable of maintaining high pressure. This paper investigates how different precursors (ZrOCl₂·8H₂O and ZrO(NO₃)₂·2H₂O) and synthesis temperatures (110-160°C) affect the phase composition, optical properties, size, and shape of ZrO₂ nanoparticles produced by hydrothermal synthesis without calcination. In addition, the effect of temperature exposure in the range of 100-1000°C on the phase stability of the synthesized nanoparticles was studied. X-ray diffraction and Raman spectroscopy techniques were used to determine the structure and phase composition, while the optical properties were examined through the analysis of transmission and absorption spectra in the visible and UV ranges. It was found that the obtained particles at synthesis temperatures of 110-130°C have predominantly cubic c-ZrO2 phase, which changes to monoclinic phase when heated above 500°C. Analysis of visible and UV spectroscopy data reveals that the experimental samples have pronounced absorption in the middle UV range (200-260nm) and have an energy band gap Eg varying from 4.8 to 5.1eV. The hydrothermal powders synthesized in this study can be used as absorbers in the mid-UV range and as reinforcing additives in the preparation of technical ceramics.

The digital transformation of the construction industry: a review

PurposeAlthough the recent increased efforts to implement digital transformation (DT), the construction sector field lags behind other sectors, and the academic research on the DT process remains rather fragmented. This study is an integrative review of the construction related literature concerning the context, interventions and outcomes of the DT process.Design/methodology/approachWe have reviewed 15 cases presenting the DT process of construction companies, by employing the context-intervention-mechanism-output (CIMO) framework.FindingsRegarding the context (C), the major drivers of DT are top management support, organizational culture pro DT and customer requirements. Concerning the intervention (I), BIM technology dominates construction firms' approaches to DT, followed by cloud computing and Internet of Things (IoT). The outcomes (O) of DT include direct and indirect benefits related to accurate cost calculations, cost reduction, improved work efficiency, high quality, as there are more complex results related to new business models and increased long-term competitiveness. DT in this field can be described considering three mechanisms (M), similar to a maturity model: traditional DT, niche DT and advanced DT.Originality/valueThis review contributes to the literature by integrating existing studies on the context, interventions and outcomes of the DT process of the construction industry.

Comprehensive Survey of Web Security Threats in 2024

In recent years, the landscape of web security threats has evolved rapidly, driven by advancements in technology and increasingly sophisticated attack vectors. This paper presents a comprehensive survey of prominent web security threats in 2024, examining both traditional vulnerabilities and emerging risks that have intensified in the digital environment. We explore a range of threats, including but not limited to application-layer attacks, network- layer intrusions, and data privacy concerns. The study draws upon a wealth of sources, including industry reports, academic research, and standards from leading organizations. Our findings underscore the critical need for web application developers, security professionals, and organizations to adopt proactive defense mechanisms and stay informed on current threats to effectively protect web-based assets. This survey aims to serve as a reference for security practitioners and researchers, highlighting essential vulnerabilities and encouraging further exploration of effective countermeasures. Keywords Web Security, Threat Detection, Data Privacy, Cross-Site Scripting (XSS), SQL Injection, DDoS Attacks, Zero-Trust Architecture, Quantum-Resistant Encryption, Cloud Security, Machine Learning in Security

Oxidative/Nitrosative Stress and Brain Involvement in Sepsis: A Relationship Supported by Immunohistochemistry

Background and Objectives: A large amount of recent evidence suggests that cellular inability to consume oxygen could play a notable part in promoting sepsis as a consequence of mitochondrial dysfunction and oxidative stress. The latter could, in fact, represent a fundamental stage in the evolution of the “natural history” of sepsis. Following a study previously conducted by the same working group on heart samples, the present research project aims to evaluate, through an immunohistochemical study, the existence and/or extent of oxidative stress in the brains of subjects who died due to sepsis and define, after reviewing the literature, its contribution to the septic process to support the use of medications aimed at correcting redox anomalies in the management of septic patients. Materials and Methods: 10 cases of subjects who died in healthcare facilities with ante-mortem clinical-laboratory signs that allowed the diagnosis of septic shock were selected as case studies, and 1 case of a subject who died immediately following a road traffic accident was used as a negative control. Samples of the cerebral cortex were then taken, fixed in formalin, and subjected to sections on which an immunohistochemical study was performed using anti-NOX-2, NT, iNOS, and 8-OHdG antibodies. Results: The results emerging from the present study demonstrate that despite a variable expressivity for the NT, iNOS, and NOX2 markers, the brain samples demonstrated univocal and high positivity for the 8-OHdG marker. Conclusions: This would allow us to hypothesize how, regardless of the mechanism of production of ROS and NOS (iNOS or NOX2 mediated) and the pathophysiological mechanisms that are triggered during sepsis, oxidative damage to DNA represents the event to which this whole process leads and, in fact, in the literature, is directly correlated to sepsis-dependent mortality. Neurons, conversely, appear to be more sensitive to oxidative stress because of a low number of protective or scavenger molecules (catalase, glutathione peroxidase, GSH, or vitamin E). Therefore, despite reduced production, the manifestation of the damage remains high. This evidence, together with that of the previous study, can only support the introduction of substances with an antioxidant function in the guidelines for the treatment of sepsis.

Numerical validation of an innovative 3D calculation method of high‐rise buildings under consideration of component and soil stiffness

AbstractAt the end of the PORR Bau GmbH research project, which ran from 2015 to 2022 and which provided data on strain and settlement sensors from a total of four high‐rise buildings, an innovative calculation method for three‐dimensional building models was finally developed. This is based on a stiffness combination vector that can be applied independently of the finite element program and the modeling quality of the responsible structural engineer. Furthermore, the bedding modulus for supporting the floor slab is varied within the limits specified by the soil expertise by dividing the floor slab into quadrants.

Supporting Public Humanities at the Critical Intersections: An Imagining America Manifesto

Abstract Drawing upon findings from an Imagining America research project funded by the Mellon Foundation (2019–2023), this research paper and manifesto proposes five critical ways in which institutions of higher education can better support public humanities. Through over one hundred individual interviews, twenty multimedia case studies, a national graduate scholar survey, an online study group, and public conversations, we learned how public scholars have consistently conducted research that matters – responding to urgent challenges in the world, including on the pressing ecological, social, racial, and economic justice issues of our time. However, the diverse inter-generational Imagining America (IA) research team also found that most academic institutions are still not designed to support this important work. By favoring narrow disciplinary boundaries and norms and individualized methods over collective commitments and reciprocal partnerships, most institutions marginalize and disincentivize public humanities. Our research respondents overwhelmingly agreed that instead of change initiatives led from the top of the university, publicly engaged scholars themselves lead the way by virtue of their groundbreaking collaborative, relational, reflective, critical yet hopeful grounded research. The manifesto shared at the end of the paper proposes how to support this important work today.

EXPLOITING REMOTE SENSING IMAGERY FOR VEHICLE DETECTION AND CLASSIFICATION USING ROBUST COMPETITIVE ALGORITHM WITH DEEP CONVOLUTIONAL NEURAL NETWORK

Fast and robust vehicle recognition from remote sensing images (RSIs) has excellent economic analysis, emergency management, and traffic surveillance applications. Additionally, vehicle density and location data are vital for intelligent transportation systems. However, correct and robust vehicle recognition in RSIs has been complex. Conventional vehicle recognition approaches depend on handcrafted extracted features in sliding windows with distinct scales. Recently, the convolutional neural network can be executed for aerial image object recognition, and it has accomplished promising outcomes. This research projects an automatic vehicle detection and classification utilizing an imperialist competitive algorithm with a deep convolutional neural network (VDC-ICADCNN) technique. The primary purpose of the VDC-ICADCNN technique is to develop the RSI and apply deep learning (DL) models for the recognition and identification of vehicles. Three main procedures were involved in the presented VDC-ICADCNN technique. At the primary stage, the VDC-ICADCNN technique employs the EfficientNetB7 approach for the feature extractor. Then, the hyperparameter fine-tuning of the EfficientNet approach takes place utilizing ICA, which aids in attaining improved performance in the classification process. The VDC-ICADCNN technique utilizes a variational autoencoder (VAE) model for the vehicle recognition method. Extensive experiments can be implemented to establish the superior solution of the VDC-ICADCNN technique. The obtained outcomes of the VDC-ICADCNN technique highlighted a superior accuracy value of 96.77% and 98.59% with other DL approaches under Vehicle Detection in Aerial Imagery (VEDAI) and Potsdam datasets.

Water quality classification using self-organizing maps and cluster analysis: Case of Meknes-El Hajeb Springs, Morocco.

The Ouislane sub-watershed is currently experiencing severe water shortages and is highly dependent on its water supply. The sub-watershed spans two communes: Meknes to the north and El Hajeb to the south. It serves as the primary water source for irrigation and drinking purposes for the local population. Consequently, it is crucial to assess the spatio-temporal variations of water quality to identify and address potential gaps; these focused on effective monitoring systems to detect contaminants, pollutants and health risks. This research project aims on the application of self-organizing map (SOM) techniques combined with cluster analysis to classify water quality in springs for drinking and irrigation purposes. The present study evaluates the water quality variations using physicochemical parameters of twelve water springs, collected during the wet and dry seasons of 2022. For this purpose, the water quality index (WQI), self-organizing map (SOM), hierarchical cluster analysis (HCA), and principal component analysis (PCA) are used as evaluation and classification methods. As a result, the SOM algorithm with a size of 5 × 5 units identified as the most suitable, based on the minimum quantization error (QE) and topographic error (TE), yielding a QE of 0.379 and a TE of 0.000. It grouped the water quality data into five distinct clusters, Cluster I represented 37.5% of the total samples, while cluster II represented 25%. Cluster III and IV each accounted for 8.33% of the samples, while 20.83% of the sampling water are classified in cluster V. Clusters I, II, and IV indicate good water suitable for drinking. However, cluster V had the highest WQI, suggesting very high contamination due to increased levels of the 10 studied physicochemical parameters. The water quality in this region (cluster V) is influenced by natural processes, such as precipitation intensity, weathering and vegetation cover, as well as anthropogenic factors like agriculture and urban concentration. PCA confirmed the clustering results obtained by SOM. However, SOM provides a more detailed classification and additional insights into the dominant variables influencing the classification processes. The results of this study suggest that SOM was an effective tool for gaining a better understanding of the patterns and processes driving water quality in the Ouislane sub-watershed and provides valuable avenues for further research to establish and monitor water quality for effective management of water resources.

Machine Learning-Based Predictions of Metal and Non-Metal Elements in Engine Oil Using Electrical Properties

This study investigates the influence of six metallic and non-metallic elements (Fe, Cr, Pb, Cu, Al, Si) on the quality of engine oil under normal, cautious, and critical conditions. To achieve this, the research employs the Design of Experiments (DoE) approach, specifically the Box–Behnken Design (BBD) method, for designing experiments. The electrical properties of 70 engine oil samples prepared under varying conditions were analyzed. Machine learning models, including RBF, ANFIS, MLP, GPR, and SVM, were utilized to predict the concentrations of the six pollutants in the lubricant oil samples based on their electrical characteristics. The models’ performance was assessed using RMSE and R2 indicators during train, test, and All stages. The results revealed that the Radial Basis Function (RBF) model exhibited the best overall performance (RMSE = 0.01, R2 = 0.99). The study proceeds with optimizing RBF model parameters, such as hidden size (best = 17), spread (best = 0.4 or higher), and training algorithm (best = trainlm), to estimate each pollutant individually. The generalizability of the model was assessed by reducing the training data percentage and increasing the testing data percentage. The results demonstrated the model’s proper performance for all pollutants in various training sizes (RMSE = 0.01, R2 = 0.99). However, as the training data ratio reduced to 60:40 and 50:50, the model’s performance in estimating Cu deteriorated, resulting in increased RMSE values (10.76 or 11.85) and decreased R2 values (0.89 or 0.87) across the All step. This academic research hopes to contribute to the field of applied studies, considering the inherent complexities of lubricants and the challenges in measuring small-scale electrical properties.

Resilience as a Concept for Convergence Across Health, Systems, and Well-Being: An AI-Augmented Mapping of 50 Years of Resilience Research

Resilience has become a focal point of academic research investigating the impact of adverse disruption to the well-being of people, systems, the built environment, ecosystems, and climate. However, the proliferation of this work has not been accompanied by increasing clarity about the core meaning of resilience as a singular construct, threatening its relevance and complicating its use in practice. To improve the application of resilience in cross-disciplinary and convergence approaches to sustainability and well-being research, this work synthesized resilience conceptualizations across disciplines with novel artificial intelligence (AI)-augmented approaches. Using open-source applications for text mining and machine-learning-based natural language processing algorithms for the examination of text-as-data, this work mapped the content of 50 years of academic resilience work (24,732 abstracts). Presented as thematic and statistical textual associations in a series of network maps and tables, the findings highlight how specific measurements, components, and terminologies of resilience relate to one another within and across disciplines, emphasizing what concepts can be used to bridge disciplinary boundaries. From this, a converged conceptualization is derived to answer theoretical questions about the nature of resilience and define it as a dynamic process of control through the stages of disruption and progression to an improved state thereafter. This conceptualization supports a cross-disciplinary meaning of resilience that can enhance its shared understanding among a variety of stakeholders, and ultimately, the rigor and uniformity of its application in addressing sustainability and well-being challenges across multiple domains.

Early outcomes of the novel Myval THV series compared to SAPIEN THV series and Evolut THV series in individuals with severe aortic stenosis.

There are limited head-to-head randomised trials comparing the performance of different transcatheter heart valves (THVs). We aimed to evaluate the non-inferiority of the balloon-expandable Myval THV series compared to the balloon-expandable SAPIEN THV series or the self-expanding Evolut THV series. The LANDMARK trial randomised 768 patients in a 1:1 ratio, (Myval THV series [n=384] vs contemporary series with 50% SAPIEN THV series [n=192] and 50% Evolut THV series [n=192]). The non-inferiority of Myval over the SAPIEN or Evolut THV series in terms of the 30-day primary composite safety and effectiveness endpoint as per the third Valve Academic Research Consortium (VARC-3) was tested in an intention-to-treat population with a predefined statistical power of 80% (1-sided alpha of 5%) for a non-inferiority margin of 10.44%. The Myval THV series achieved non-inferiority for the primary composite endpoint over the SAPIEN THV series (24.7% vs 24.1%, risk difference [95% confidence interval {CI}]: 0.6% [not applicable {NA} to 8.0]; p=0.0033) and the Evolut THV series (24.7% vs 30.0%, risk difference [95% CI]: -5.3% [NA to 2.5]; p<0.0001). The incidences of pacemaker implantation were comparable (Myval THV series: 15.0%, SAPIEN THV series: 17.3%, Evolut THV series: 16.8%). At 30 days, the mean pressure gradient and effective orifice area were significantly better with the Myval THV series compared to the SAPIEN THV series (p<0.0001) and better with the Evolut THV series than with the Myval THV series (p<0.0001). At 30 days, the proportion of moderate to severe prosthetic valve regurgitation was numerically higher with the Evolut THV series compared to the Myval THV series (7.4% vs 3.4%; p=0.06), while not significantly different between the Myval THV series and the SAPIEN THV series (3.4% vs 1.6%; p=0.32). The Myval THV series is non-inferior to the SAPIEN THV series and the Evolut THV series in terms of the primary composite endpoint at 30 days. ClinicalTrials.gov: NCT04275726; EudraCT number 2020-000,137-40.

Designing and Evaluating Games for Landslides, Earthquakes, and Fires: Lesson Learned from Schools in Nepal

The Himalayan country of Nepal is vulnerable to landslides, earthquakes, and fires. Its inhabitants need to be empowered on how to react in emergencies to prevent fatalities and respond to crises efficiently while promoting longer-term sustainability and resilience. This research project, a collaborative effort involving teachers, students, and researchers, highlights the design and implementation of games for disaster risk reduction tested in remote schools. Three interactive games were developed using an iterative game design process and testing in workshops aiming to ensure the inclusivity and diversity of the project. The games targeted preparedness and response to landslides, earthquakes, and house fires. The outcome has proven that the game-based approach to teaching and learning is crucial in empowering underserved school children often left out in formal and informal disaster management processes. This study has shown that game-based learning of disaster preparedness and response effectively empowers resource-deficient communities and regions of the Global South.

Quantification of Facial Geometrical Dimension for Student Attendance Tracking

The traditional method of manual attendance-taking has been used in educational institutions for decades which have consumed one-sixth amount of class time for attendance marking. Great research on attendance systems has come up with techniques like biometrics, NFC’s and QR codes. Moreover, with advancements in technology, this research project can provide a more efficient and effective solution. This research project utilizes image processing, computer vision and facial recognition technology to mark the attendance of the students in class. The objectives of the system are registration of facial image, perform landmarking of the facial image and develop automated attendance system. As a result, this project works by installing a camera on top of the board which detects the student faces and performs attendance marking. Now is the time to implement this system in schools, institutions, colleges, and universities to streamline the attendance-taking process. This automated system will not only save time and effort but will also provide accurate attendance records, which will benefit both management and students.

Healthcare Professionals' Views on the Use of Passive Sensing and Machine Learning Approaches in Secondary Mental Healthcare: A Qualitative Study.

Globally, many people experience mental health difficulties, and the current workforce capacity is insufficient to meet this demand, with growth not keeping pace with need. Digital devices that passively collect data and utilise machine learning to generate insights could enhance current mental health practices and help service users manage their mental health. However, little is known about mental healthcare professionals' perspectives on these approaches. This study aims to explore mental health professionals' views on using digital devices to passively collect data and apply machine learning in mental healthcare, as well as the potential barriers and facilitators to their implementation in practice. Qualitative semi-structured interviews were conducted with 15 multidisciplinary staff who work in secondary mental health settings. Interview topics included the use of digital devices for passive sensing, developing machine learning algorithms from this data, the clinician's role, and the barriers and facilitators to their use in practice. Interview data were analysed using reflexive thematic analysis. Participants noted that digital devices for healthcare can motivate and empower users, but caution is needed to prevent feelings of abandonment and widening inequalities. Passive sensing can enhance assessment objectivity, but it raises concerns about privacy, data storage, consent and data accuracy. Machine learning algorithms may increase awareness of support needs, yet lack context, risking misdiagnosis. Barriers for service users include access, accessibility and the impact of receiving insights from passively collected data. For staff, barriers involve infrastructure and increased workload. Staff support facilitated service users' adoption of digital systems, while for staff, training, ease of use and feeling supported were key enablers. Several recommendations have arisen from this study, including ensuring devices are user-friendly and equitably applied in clinical practice. Being with a blended approach to prevent service users from feeling abandoned and provide staff with training and access to technology to enhance uptake. The study design, protocol and topic guide were informed by a lived experience community group that advises on research projects at the authors' affiliation.

Identification of the P24 Gene Family Related to Vesicular Transport in Cyclocarya paliurus and Their Expression Analysis Under Salt Stress

Vesicle transport is a fundamental mechanism for intracellular substance transfer and signal transduction, involving the formation, transport, fusion with target membranes, and release of vesicle contents within cells. Issues such as disruption of water balance, difficulty in regulating osmotic pressure, and oxidative stress caused by salt stress can lead to disturbances in the secretion system of plants, thus affecting plant growth and development. Cyclocarya paliurus (C. paliurus), widely used in traditional Chinese medicine, has not been previously reported in terms of how the vesicle transport P24 gene regulates its adaptation to salt stress. In this research project, a total of eight CpP24 genes were successfully identified. Upon examination of gene architecture and conserved sequence elements, the CpP24 genes exhibited a variation in exon count, ranging from 4 to 6. Moreover, the CpP24 gene family’s reaction to salt stress and specific stressors including methyl jasmonate (MeJA), sodium hydrosulfide (NaHS), and sodium nitroprusside (SNP) was further explored in our study. Comprehensive analysis of the expression patterns of CpP24 genes under various conditions showed that salt stress induced the expression of these genes, and the combined treatment of salt stress with specific stresses caused changes in their expression. This study lays a theoretical foundation for further probing into the physiological functions of C. paliurus and the underlying mechanisms regarding its response to environmental stress.

Visual insights into translation: demystifying trends of adopting eye-tracking techniques in translation studies

IntroductionThe increasing use of eye-tracking techniques in translation studies offers valuable insights into cognitive processes and behavioral strategies of translators, reflecting a significant trend within cognitive linguistics and translator training methodologies.MethodsThis review harnesses quantitative bibliometric analysis through Bibliometrix R-package with qualitative content assessment to evaluate the trajectory and thematic evolution of eye-tracking research in translation studies. Through a dataset from the Web of Science, 56 articles were analyzed, revealing distinct thematic dimensions and trend dynamics.ResultsThe analysis revealed that eye-tracking is increasingly pivotal in exploring the cognitive and technological dimensions of translation. Central themes include interactions with translation tools, machine translation, and human-computer interaction, highlighting the importance of cognitive research in technology-driven translation. Niche areas such as English-Chinese translation and online consultation suggest specialized topics that warrant further investigation. Additionally, emerging themes like cognitive load and sight translation demonstrate a shift toward exploring real-time translation processing. Declining traditional topics, such as broader translation theories, indicate a growing integration of cognitive research with technological advancements.ConclusionThese findings elucidate the growth and diversification of eye-tracking applications in translation studies, emphasizing the method’s importance in both academic research and practical applications, thereby informing future studies and enhancing translator training programs.