bluuebunny/crossref_metadata_2025 huggingface dataset:
Investigating the Association Between Heavy Metals and Attention Deficit Hyperactivity Disorder in Children: An Exploratory Study
Authors: Kaur Sharanpreet , Canals-Sans Josefa , Morales-Hidalgo Paula , Alda José A. , Arija Victoria
Published: January 2025

Exposure to heavy metals has been associated with affecting children’s neurodevelopment, particularly increasing the risk of developing attention-deficit hyperactivity disorder (ADHD). The current exploratory study aims to investigate potential associations between presence of 15 different heavy metals in urine and ADHD. A total of 190 urine samples of participants from clinical and non-clinical population (non-ADHD = 66; ADHD = 124) aged between 6 and 15 years from Barcelona and Tarragona (Spain) were analysed. Logistic regressions adjusted by sex, age, SES, BMI and diet quality were performed. Highest quartiles (3rd and 4th) of Pb (lead) (aOR 5.33; CI [1.89, 14.98]), Cd (cadmium) (aOR 3.69, CI [1.38, 9.83]), Cu (copper) (aOR 16.46, CI [4.66, 58.14]) and Sb (antimony) (aOR 3.04, CI [1.12, 8.23]) were significantly associated with increased odds of ADHD DSM-5 diagnosis. Additionally, Cu and Cd were associated with higher scores of inattention symptoms. Whereas, Cu and Sb were associated with hyperactivity-impulsivity severity. This exploratory study provides preliminary valuable evidence, suggesting potential associations between environmental factors, such as metal exposure, with ADHD in school-aged children. These findings highlight the importance of further research to support these associations and, if confirmed, explore strategies to mitigate the potential impacts of these toxicants on children’s health.
Design of electronic slogging control system for double tricot machine
Authors: Fu Ruiyun
Published: January 2025

The work aims to construct a complete electronic slogging system in order to enrich the characteristics of pattern and get large slogging movement distance. Herein, first, the knitting principle of double tricot machine is studied, and the conclusion is drawn that the looping process is composed of the swing of guide bar and the slogging of guide bar. Second, taking the RD4N tricot machine as the research object, the minimum overlap angle of 25° and the minimum underlap angle of 80° are obtained, which occur on the GB1 and GB4 bar, respectively. Third, discussions are carried out over the scheme and principles of the slogging system, the controller, servo motor, etc., are analyzed and designed, an electronic slogging execution program is drafted, and the electronic cam curve adopts the non-dwell corrected trapezoidal acceleration motion curve, which completely meets the requirements of production. The actual test proves the smooth operation, precise slogging, and fast response of the control systems.
Design of wheat ear detection in natural environment based on improved YOLOv5s
Authors: Li Yawen , Yuan Xunfeng , Wang Bo , Zhang Jun
Published: January 2025

Aiming at the problems of slow target detection speed and low accuracy caused by occlusion, illumination and complex background environment interference in wheat ear detection of natural environment, the paper proposes to improve the network model based on YOLOv5s algorithm model to achieve fast and efficient target detection. The first improvement point is to add the attention mechanism. In the backbone and head parts, the CBAM attention mechanism module is added to reduce the interference of non-critical information, extract the key feature information of the image, and improve the detection accuracy. The second improvement point is to combine the lightweight network MobileNetV3 for target detection, using channel separable convolution and SE channel attention mechanism to improve the accuracy of target detection. The Shangmai 5226 as the research object, the optimized wheat ear database was built, and the training images were labeled and converted into yolo format. Under the operating environment of Pytorch, the improved YOLOv5s model was used to extract the image features of Shangmai 5226 series wheat ears with iteration of 300 times. The result was shown that compared with the single structure YOLOv5s model, the accuracy of the improved comprehensive network model is improved by 0.7 %, mAP reaches 91.1 %, which is increased by 1.3 %, and Fps reaches 25.821, which is increased by 5.7 %. The improved network model can effectively improve the speed and accuracy of wheat ear detection, improve the effect of wheat ear detection, and provide technical support for the development of agricultural automation and intelligent agriculture.
A depthwise separable convolution-based neural network for rolling bearing fault diagnosis
Authors: Jiang Rong , Wu Chenxi , Zhong Chao
Published: January 2025

A depthwise separable convolution-based neural network (DSCNN) is proposed to achieve deep feature extraction and efficient end-to-end identification for rolling bearing fault diagnosis. DSCNN is mainly stacked by depthwise separable convolution layers and their blocks with residual structures. The depthwise separable convolutions are firstly employed to untie the correlation between spatial dimensions and channel dimensions in the process of convolutional calculation, which enables DSCNN to extract fault features deeply and comprehensively via more depthwise separable convolution layers without efficiency reduction. Furthermore, the residual structures are designed to prevent DSCNN from learning degradation caused by multi-layer network. In addition, other layers are also considered to enhance the capabilities of DSCNN such as the global average pooling for generalization. The experimental results show that the prediction accuracy of the optimized DSCNN can not only reach 96.88–100% higher than the other methods in diagnostic of bearing fault, but also shows better performance in terms of convergence, robustness, sparsity, generalization, etc. Hence, DSCNN is a high-efficient approach to adaptively perform deep feature extraction and fault identification through end-to-end convolutional network, adapting to the development of fault diagnosis techniques in intelligent large-scale rotatory machinery.
Analysis of multiple physical fields and the study of optimal design method for PCA
Authors: Liu Xiaolan , Su Mingmin , Zhang Junliang , Wang Hongzhi , Sun Jinhai
Published: January 2025

Terahertz waves with large absolute bandwidth resources have a wide range of potential applications in communications, but low incident field strengths limit its radiation efficiency. Extraordinary Optical Transmission (EOT) causes the transmittance spectrum of light to show transmission peaks at some specific wavelengths that are inconsistent with classical theory. The electric field strength at the photoconductive antenna (PCA) electrode can be enhanced by EOT, thereby improving the radiation efficiency of photoelectric conversion. In this work, we etched rectangular grooves and small hole structures at appropriate locations on the grating electrodes, and investigated the effects of the size and location of the small holes on the transmittance. The simulation results show that the peak electric field of the metal electrode structure based on the EOT design reaches 1.67 × 107 V/m, and the localized electric field is increased by a factor of 4.05 compared with that of the non-slotted grating electrodes. The peak electric field values are input into the developed multi-physics model, and the results show that the peak photocurrent of the improved terahertz PCA is 7.1 times higher than that of the conventional one. By designing and analyzing the effect of the grating electrode structure of an EOT-based metal on the local electric field on the semiconductor surface, a method for the radiation efficiency of photocarrier generation is proposed. This is of great significance to promote the further application of terahertz PCA.
Empirical Bayesian estimation of parameters in step-stress accelerated life testing under exponential distribution with constant censoring
Authors: Wei Shi , Lan Xinhua , He Guoyuan
Published: January 2025

This study explores the Parametric Empirical Bayesian (PEB) estimation of average lifetime and acceleration factor parameters under the framework of exponential distribution with constant censoring, specifically when the hyperparameters of the prior distribution are completely unknown. Employing a weighted squared loss function, the performance of PEB estimations is compared against that of Maximum Likelihood Estimations (MLE) through numerical simulations. The results demonstrate the superiority of PEB estimations over MLE, particularly notable in scenarios involving small sample sizes, where it exhibits robust estimation capabilities. This paper extends the existing methodology by providing a comprehensive examination of the advantages and potential applications of empirical Bayesian approaches in the context of step-stress accelerated life testing, thereby offering valuable insights for researchers and practitioners in the field of reliability engineering.
Research progress of overhead conductors with carbon fiber composite core
Authors: Wang Yixin , Zhang Peng , Liu Hongliang , Liu Jie , Wu Guoqiang , Sun Cuiying
Published: January 2025

Carbon fiber composite core overhead conductor has a series of excellent performance, such as high strength, light weight, corrosion resistance, high temperature resistance, small sag, and so on. It is the preferred product for large span, large capacity transmission and capacity improvement lines. However, due to the limitations of structure and material properties, this conductor has some technical problems, such as poor bending performance and lack of effective means to diagnose defects in the core. The development of carbon fiber composite core overhead conductors is introduced, and the structures and properties of different types of conductors are analyzed. It is pointed out that using multi-strand core instead of single core is an effective means to improve the bending performance of the conductor. By implanting optical fiber in the composite core and using the optical fiber as a sensor, the internal defects in the core can be diagnosed. In addition, from the perspective of environmental protection, the multi-strand thermoplastic composite core conductor is expected to achieve great development in this field in the future.
Multi-objective optimization and seismic response analysis of concrete interlayer seismic isolation technology in prefabricated building
Authors: Wang Wenjing
Published: January 2025

With the continuous optimization of prefabricated concrete structures, they have been widely used in the field of construction. However, due to the existence of semi-rigid connections in prefabricated concrete structures, the seismic performance of the entire structure will be reduced. Therefore, how to improve the seismic performance of prefabricated concrete structures has become a current research hotspot. This study first combines interlayer isolation structures with prefabricated concrete to build a new type of semi-rigid connection prefabricated concrete interlayer isolation system. Then, to further optimize the seismic simulation performance of the system, a multi-objective optimization scheme of semi-rigid connection prefabricated concrete interlayer isolation structure is designed by combining the sequential quadratic programming algorithm and the interior point method. The research results indicate that the multi-objective optimization algorithm used has good optimization performance. The cost optimization accuracy under this algorithm can reach up to 0.98, and in addition, the displacement and acceleration objective function values under this algorithm can also be maintained at around 0.95. In summary, the multi-objective optimization algorithm proposed by this research institute has good optimization results, which can ensure that the building structure has good seismic performance while meeting the optimal cost, displacement, and acceleration objective function values.
Influence of Industry 4.0 on the sustainable development of urban economy under the background of fuzzy control and soft computing
Authors: Wang Jin
Published: January 2025

Industry 4.0 has not only brought about profound changes to the manufacturing industry itself but has also had a significant impact on the sustainable development of urban economies. By 2021, the urbanization rate of China’s resident population will reach 64.72%, with the urban population rising from 170 million in 1978 to 910 million, and the built-up area of cities reaching 63,000 square kilometers. Industry 4.0 is an important driver for sustainable urban economic development, which can improve the efficiency, quality, innovation, and competitiveness of urban manufacturing industries and promote urban economic growth, employment, environment, and social welfare. This paper analyzes the mechanism of the impact of Industry 4.0 on the sustainable development of China’s urban economy from the perspective of fuzzy control and soft computing, as well as the application practice of Industry 4.0 in the sustainable development of urban economy. The study shows that fuzzy control and soft computing, as an intelligent computing method capable of dealing with uncertainty, nonlinearity, and complexity, can effectively support the implementation of Industry 4.0 and improve the flexibility, adaptive, and innovative capabilities of the manufacturing industry, thus promoting the green growth, social equity, and resource efficiency of urban economy. The theoretical research and practical exploration with the sustainable development of urban economy provide some insights and lessons.
Dilemma and innovation countermeasures of enterprise marketing under the background of big data and Internet of Things
Authors: Wang Kang
Published: January 2025

This paper studies the dilemma and innovation countermeasures of enterprise marketing under the background of big data and Internet of Things. Through questionnaire survey and simulation data analysis, it is found that the development of big data and Internet of Things technology has brought new opportunities and challenges to enterprise marketing. Enterprises should make full use of new technologies, improve the precision of marketing, build a multi-channel and integrated marketing model, strengthen internal collaboration and innovation capabilities, and optimize policies, regulations, and industry standards, so as to improve their marketing performance and competitiveness. At the same time, enterprises should timely adjust marketing strategies and improve marketing agility and adaptability, in order to adapt to market changes. This study also analyzes the key factors that affect the marketing performance of enterprises, including product strategy, price strategy, channel strategy, promotion strategy, internal collaboration and innovation ability of enterprises, policies, regulations, and industry standards. In view of these factors, enterprises should be formulated and optimized to improve their marketing performance and competitiveness. The purpose of this study is to provide reference for the development of enterprise marketing.
Evaluation of regional ecological carrying capacity: A case study in Xiong’an New Area
Authors: Wang Qin , Yang Bo
Published: January 2025

Evaluation of regional ecological carrying capacity refers to evaluation of regional ecosystem carrying capacity for economic and social sustainable development requirement within a certain period of time under premise of ensuring ecological resilience (recoverable) and sustainability. Taking Xiong’an New Area as an example, through correlation analysis method and principal component analysis method, evaluation index system of ecological carrying capacity is designed from three dimensions of green governance, green production, and green life. Then ecological carrying capacity of the New Area from 2015 to 2020 is evaluated based on fuzzy comprehensive evaluation method, and evaluation results are 0.2436, 0.2646, 0.3404, 0.4256, 0.5007, and 0.5652, respectively, with an average annual growth rate of 18.33% and showing a steady growth trend. Finally, some countermeasures to enhance ecological carrying capacity are put forward, mainly including to continuously promote ecological dredging project of Baiyang Lake in the New Area, optimize industrial structure and strict control pollution emissions, and promote green life style of “green transportation + clean energy.”
The role of big data and artificial intelligence in the reform and innovation of intelligent English teaching
Authors: Li Yuehua , Han Lihao
Published: January 2025

With the development of information society, big data and artificial intelligence technology are increasingly introduced into English teaching, bringing a series of changes to English teaching. However, understanding these emerging technologies in theory and effectively applying them in practice remains a challenge. The purpose of this study is to comprehensively explore the application of big data and artificial intelligence in English teaching, to study the existing problems and solutions, and to predict its future development trend. The study found that big data and artificial intelligence have significant advantages in improving teaching effects, personalized teaching, intelligent assessment, etc., but there are also problems in practical applications such as data security, teacher technical proficiency, learning resource equity, and student privacy protection. This paper puts forward some strategies to solve these problems and discusses the future development trend of big data and artificial intelligence in English teaching. This study provides scientific and comprehensive theoretical support and practical guidance for the reform and development of English teaching.
The role of Internet marketing in improving enterprise economic benefits under the background of big data and Internet of Things
Authors: Yang Yan
Published: January 2025

This study aims to explore how big data and the Internet of Things can improve the economic benefits of enterprises in online marketing. We first introduced the concept and development trend of big data, Internet of Things, and Internet marketing and then collected a large number of empirical data through the design and implementation of questionnaire survey. Our data analysis results show that the level of use of big data and the Internet of Things has a significant positive impact on business sales. However, there are also some problems and challenges in the implementation of big data and the Internet of Things, such as resource and technology limitations, and legal and ethical issues such as data security and privacy protection. Therefore, we suggest that enterprises should reasonably plan the use of big data and the Internet of Things according to their own resources and capabilities, while constantly upgrading their own technical level, focusing on data security and privacy protection, and tracking the latest technology and market trends. In addition, the government and industry organizations should also formulate and improve relevant policies and standards to support the development of big data and the Internet of Things and protect the interests of consumers. In general, big data and the Internet of Things provide new opportunities and challenges for enterprise online marketing, which need further research and discussion.
Teaching optimization of virtual reality and augmented reality technology in vocational education
Authors: He Xingxing , Li Lei
Published: January 2025

With the increasing progress of science and technology, the field of education is actively exploring new teaching techniques to optimize the learning experience. In this context, this research focuses on exploring the applications and benefits of virtual reality (VR) and augmented reality (AR) technologies in vocational education. Through comparative analysis, the study aims to evaluate the teaching effects of these emerging technologies and traditional teaching methods in vocational education, so as to provide an empirical basis for educators and policymakers. The findings suggest that VR and AR provide an immersive learning environment that significantly increases student engagement and motivation. In addition, compared with traditional teaching methods, these techniques show clear advantages in some specific areas, especially those requiring simulation of practical operations. However, the best teaching strategy may involve using these techniques in combination with traditional methods to take full advantage of each. Overall, this study provides useful insights into how VR and AR technologies can be effectively utilized in the field of vocational education, highlighting the importance of an integrated teaching approach to meet diverse learning needs and achieve instructional optimization.
An analysis of influencing factors of undergraduate scientific research ability based on grounded theory under the background of big data
Authors: Jia Jingjing
Published: January 2025

The era of big data calls for innovation. In recent years, with the widespread application of big data, enterprises increasingly demand innovative talents. Research plays a crucial role in enhancing innovation abilities. However, the traditional training model in higher education institutions does not sufficiently emphasize undergraduate research, resulting in a lack of research skills among undergraduates, which in turn affects their capability to innovate. This paper uses the qualitative research method to root the theory, based on the 156 undergraduate questionnaires from Shanghai Dianji University. Through open coding, axial coding, and selective coding, the research analyzes factors influencing undergraduate students’ research capabilities and proposes corresponding strategic recommendations.
Experimental study on preparation and performance of high-performance anti-corrosion sealing wax for cable
Authors: Zhou Xiangtian , Wang Hongwei , Yuan You , Pang Zhonghua
Published: January 2025

In order to solve the problem of low durability of traditional cable anti-corrosion materials, a new type of anti-corrosion sealing wax for cable was developed by combining model test and real bridge test methods. Firstly, formulation design of the new anti-corrosion sealing wax was carried out. Secondly, dropping point test, steel mesh oil separation test, low temperature performance test, corrosion test, oxidation stability test, damp heat test, and salt spray test of the new anti-corrosion sealing wax were carried out, and pouring equipment of the new anti-corrosion material was developed. Test results show that the new anti-corrosion sealing wax and its pouring equipment can effectively meet the anti-corrosion requirements of actual project, and new anti-corrosion sealing wax was applied to the cable maintenance of Liuzhou Jinglan Bridge. Application results show that cable has no oil drop leakage, waterproof and anti-corrosion effects was excellent, and new anti-corrosion sealing wax can effectively meet the requirements of practical projects, which can provide reference for domestic cable maintenance and construction.
Multi-objective optimal routing algorithm translation conversion theory subtitle translation research
Authors: Huang Danhua , Xiang Shuaiqiu
Published: January 2025

At present, the traditional translation learning model lacks the construction of model network, which leads to low translation accuracy. In this paper, a multi-objective optimization routing algorithm is proposed to study Translation Shifts Theory subtitle translation. The multi-objective configuration method is used to optimize the parameters of the model, and the multi-objective constrained evolutionary feature solution is obtained by combining the semantic ontology feature decomposition method. The semantic association distribution model between ontologies is established, and the optimal output conversion control of English translation learning model is realized according to multi-objective optimization routing design. The experimental results show that the model has good convergence and high translation accuracy when this method is used in translation data processing, and this method has good performance.
Factors influencing China youth’s watch intentions for animated film adaptations of Chinese traditional literature based on the Theory of Planned Behavior
Authors: Wu Jiewei
Published: January 2025

The purpose of this study is to examine how the demographic factors of gender, income, and educational background, as well as attitude (ATT), subjective norm (SN), and perceived behavioral control (PBC) based on the Theory of Planned Behavior (TPB), influence China youth intention to watch animated films adapted from traditional literature. The study was conducted in two major cities in China, Guangzhou, and Shenzhen, and valid data were collected from 464 people aged between 18 and 40 years through questionnaires and snowball sampling methods. Data analysis was performed using SPSS and AMOS software. It was found that gender had no significant effect on watch intention, while educational background and income level made a significant difference in watch intention. Meanwhile, Perceived Behavioral Control (PBC) had the greatest effect on watch intention under the TPB framework (β = 0.313, p < 0.001), followed by attitude (β = 0.23, p < 0.001), and finally subjective norm (β = 0.143, p = 0.009). Based on these results, this study provides strategic recommendations for the production and marketing of animated films adapted from traditional Chinese literature, aiming to enhance the marketing and performance of such films.
Optimized design and energy consumption analysis of an improved feeding equipment structure based on numerical simulation
Authors: Wang Yizhi , Huang Tao , Tian Xiaomin , Chen Weina , Xiao Maohua
Published: January 2025

The development of unmanned feeding equipment for use in pond feeding is constrained, primarily by serious infrastructure inadequacies, limitations in the mechanisms used to dispense pellet feed, and feeding equipment designs that cannot perform advanced feeding strategies, such as uniform feeding, precise feeding, and on-demand feeding. In particular, existing unmanned feeding equipment structures are difficult to use when feeding iced trash fish, which is a type of feed that can significantly improve the flavor and protein content of carnivorous and omnivorous aquatic products. Therefore, to facilitate the feeding of iced trash fish, a hydraulic pushing rod was added to the structural design of a feeding mechanism during this study to achieve precise feeding. Additionally, a pre-treatment method for the iced trash fish was designed to achieve uniform feeding. Meanwhile, after an electromagnetic heating design was added to achieve on-demand feeding, the energy consumption was simulated for three different conditions as a comparison: one condition had no heat source, while the other two featured electromagnetic heating with two different heating power values. The results indicate that, for the proposed structural design and pre-treatment method, using an electromagnetic heating power of 19 kW enabled a full load of iced trash to be thawed in 10 min; thus, the unmanned feeding equipment could perform the heating and feeding processes simultaneously.
Influence of super-hazardous material shed composite foundation reinforcement on adjacent pile foundations in coastal soft soil areas
Authors: Su Shengxi , Yu Zenghui , Ma Xingya
Published: January 2025

During the use of a material shed in a coastal soft soil area, the settlement of the compacted threaded pile composite foundation was too large, and the bearing capacity could not meet the requirements of one-time stacking, resulting in the material shed being in a super-critical state. Bamboo joint piles are used to reinforce the composite foundation of compacted screw piles. Through numerical simulation, the deformation and stability of the composite foundation of squeezed screw pile reinforced by bamboo pile are analyzed, and the influence of bamboo pile sinking on the pile foundation of material shed is analyzed. The results show that the composite foundation strengthened by bamboo pile meets the design requirements; first, construct the three rows of bamboo piles near the column side to form a “retaining wall” with the original compacted threaded pile, and then construct the bamboo piles inside the “retaining wall,” which reduces the maximum displacement on the foundation pile near the composite foundation by 52%, ensuring the safety of the ultra-dangerous material shed.
Research on a novel intelligent bearing system with three-parameter measurement: integration structure design and state monitoring capability analysis
Authors: Shi Huaitao , Song Zhenting , Ye Xin , Zhang Ao
Published: January 2025

Bearing condition monitoring has become a key component in maintaining healthy operation of high-speed rotating and reciprocating machinery. The traditional fault diagnosis objects mostly focus on single-parameter measurements, which may lead to misdiagnosis. Due to the influence of background noise, it is difficult to extract and identify bearing fault signals in time. To tackle this problem, this paper proposes an external intelligent bearing system with three parameter monitoring capabilities. First, in order to accurately measure the bearing speed information in real time, Ansoft is used to perform electromagnetic simulation of the Hall sensor. Second, the finite-element software Simdroid is used to simulate the bearing structure, and the bearing is processed through the simulation results. Third, three sensors are combined to design and develop the program and display interface, which can display the monitored data in real time. Finally, the designed intelligent bearing system is manufactured to run on a bearing life testing machine; by comparing the data measured with traditional monitoring methods, the superiority of the intelligent bearing system in condition monitoring is verified. This work can provide a novel way for the research on multiparameter bearing condition monitoring.
Radicalizing spaces: Neighbourhood effects on susceptibility to radicalization
Authors: Kurtenbach Sebastian , Küchler Armin , Zick Andreas
Published: January 2025

This study examines neighbourhood effects and their impact on inhabitants’ susceptibility to radicalization by linking standardized survey data in three German cities to data from government statistics, followed by a multilevel analysis from a total of 145 units. This allows us to control for both local and individual factors with respect to the susceptibility to radicalization. Findings show that an increased level of self-control and income satisfaction have a deterring effect against the susceptibility to radicalization. Digital activities, on the other hand, have a positive effect on susceptibility. Sociostructural characteristics at the neighbourhood level do not show a clear effect on the susceptibility to radicalization, but differences in ‘legal cynicism’ and ‘collective efficacy’ are evident in a varying pattern across the three cities under study. In the city with the highest level of social segregation, legal cynicism had a positive effect and collective efficacy had a mitigating effect on the susceptibility to radicalization. The results show that the local environment should be taken into account when explaining radicalization.
Efficacy and safety of immunotherapy in locally advanced or metastatic pulmonary lymphoepithelioma-like carcinoma: a multicenter retrospective study
Authors: Yang Xiongwen , Xiao Yi , Zhou Yubin , Hu Hao , Deng Huiyin , Huang Jian , Liang Maoli , Yuan Zihao , Dong Longyan , Huang Shaohong
Published: January 2025

Background:

Pulmonary lymphoepithelioma-like carcinoma (pLELC) is a rare subtype of non-small-cell lung cancer that predominantly affects younger, non-smoking individuals in southern and southeast Asia, where Epstein–Barr virus (EBV) prevalence is high. The efficacy and safety of immunotherapy in pLELC, especially in second-line settings, remain inadequately explored.

Objectives:

This study aimed to evaluate the efficacy of immunotherapy, either alone or in combination with chemotherapy, in improving progression-free survival (PFS) and overall survival (OS) in patients with advanced pLELC.

Design:

This was a multicenter retrospective study.

Methods:

A retrospective analysis was conducted on 252 patients with stage IIIB–IV pLELC treated across six centers. Patients received chemotherapy, immunotherapy, or a combination of both (chemoimmunotherapy). The primary outcomes measured were PFS and OS across different treatment regimens.

Results:

Chemoimmunotherapy significantly improved both PFS and OS compared to chemotherapy alone, in both first- and second-line settings. In first-line treatment, chemoimmunotherapy resulted in a median PFS of 17.6 months and OS of 26.1 months, compared to chemotherapy alone (PFS 8.7 months, OS 19.2 months). In the second-line setting, chemoimmunotherapy achieved a median PFS of 5.1 months and OS of 13.5 months, surpassing the outcomes with chemotherapy alone (PFS 3.3 months, OS 8.9 months). High baseline EBV-DNA levels (>2000 copies/mL) and low programmed death ligand 1 (PD-L1) expression (<50%) were associated with poorer outcomes. In addition, patients with high baseline serum tumor markers (STMs) and a dynamic reduction of ⩽20% in STMs exhibited significantly worse PFS and OS.

Conclusion:

The study suggests that immunotherapy, particularly when combined with chemotherapy, offers significant survival benefits for patients with advanced pLELC. Baseline EBV-DNA levels, PD-L1 expression, and both baseline and dynamic STM changes serve as important predictors of treatment response, highlighting the need for personalized therapeutic approaches in this unique subtype of lung cancer.
Essential Oils: Chemical Composition and Diverse Biological Activities : A Comprehensive Review
Authors: Ben Miri Yamina
Published: January 2025

Essential oils (EOs) are complex mixtures of volatile compounds, primarily terpenoids and phenolic constituents, derived from plants. They have been widely studied for their diverse biological activities, including antibacterial, antifungal, antiviral, anticancer, and anti-inflammatory effects, among others. These bioactivities are attributed to the unique chemical composition of EOs, which enables multi-targeted modes of action such as disruption of microbial cell membranes, inhibition of spore germination, and modulation of inflammatory pathways. Their potential as alternatives to conventional antimicrobial therapies has gained attention, particularly in addressing antimicrobial resistance. Additionally, EOs exhibit significant antioxidant and antimicrobial properties, contributing to food preservation by preventing spoilage and extending shelf life. In agriculture, their roles in pest management and plant growth regulation highlight their sustainable applications. In conclusion, EOs present a promising avenue for sustainable applications in healthcare, food preservation, and agriculture, though further research is necessary to overcome challenges related to their variability and clinical validation.
Research Approaches for the Discovery of Trypanocidal Molecular Prototypes from Plants
Authors: Dofuor Aboagye Kwarteng
Published: January 2025

In the absence of vaccines, chemotherapy remains a viable alternative for the control of African trypanosomiasis. To facilitate the eradication of African trypanosomiasis, there is the need to pay attention to the chemotherapeutic potential of secondary metabolites obtained from natural sources. Despite the increasing level of attention paid towards the pharmacological and medicinal properties of trypanocidal molecular prototypes from plants, integrative synthesis of research methods relevant to this progress is lacking. Furthermore, the potential applications of machine learning in the discovery of plant-derived antitrypanosomal secondary metabolites have not been well explored. The aim of this study is thus to provide a critical appraisal of the antitrypanosomal potential of plant molecular prototypes in the context of research progress made, as well as to highlight standard and emerging investigative tools applicable in the drug discovery process. It explores the phytochemical, pharmacological and medicinal properties of plant-derived antitrypanosomals in the light of traditional and emerging research approaches. In vitro, in silico, and in vivo strategies and investigations that may be employed are highlighted. Finally, promising machine learning tools that may be of particular benefit in future antitrypanosomal investigations are also discussed. These insights may ultimately facilitate optimization, target identification and clinical investigations in the drug discovery and development process against African trypanosomiasis.
At the edges of the global philanthropic complex
Authors: Webber Sophie
Published: January 2025

In response to Fuentenebro and colleagues’ paper about the geographies of super-philanthropy, this commentary examines the edges and potential cracks of the global philanthropic complex. By briefly bringing the global philanthropic complex to everyday academic and activist life, I focus on its ambivalent and sometimes contradictory inclusions and relations. Using these illustrative cases, I suggest the need to consider when the philanthropic complex might form the basis for alternative – distinctively reparative, even decolonial – global futures.
Agile adoption at EzzyShip.com
Authors: Chauhan Deepak , Attili VS Prakash
Published: January 2025

EzzyShip is a logistics platform created to bridge the gap between global markets and remote communities worldwide. It leverages the power of networks to bring producers and consumers together to transact value, that is, delivering goods and services to customers in remote locations of the globe. The case discusses how agile ways of working were adopted at EzzyShip and the challenges and successes of Agile at EzzyShip. This case emphasizes that to become a truly agile enterprise, agility must be embraced by innovation and product development teams and across leadership, business operations, DevOps, and other support functions. It concludes with the message that agile transformation is a continuous journey.
Undermining competition, undermining markets? Implications of Big Tech and digital personal data for competition policy
Authors: Birch Kean , Adediji ‘Damola
Published: January 2025

Many countries and jurisdictions are reforming their competition policies in response to growing political and public concerns about market concentration, especially when it comes to the market power of Big Tech firms. A particular concern is the new dynamics in market competition resulting from the rise of digital personal data as the key resource or asset underpinning our economies. Our aim in this paper is to examine the competition policy investigations, proposals, and reforms emerging around the world in order to analyse the policy implications of digital personal data to market competition regimes. Our methodological approach entailed an analysis of policy materials (written in English) produced in various jurisdictions or by international institutions dealing with competition policy. We identified the underlying policy themes, concerns, and processes across these different jurisdictions and institutions in order to understand their concerns about how Big Tech and personal data affect competition and competition policy.
Rethinking Sustainability from a Gandhian Perspective: A Discourse on Cognitive Justice
Authors: Khattri Prashant
Published: January 2025

It was Gandhi who gave centrality to plural ways of thinking and knowing. His entire life and work are directed against the hegemonic order of knowledge production and dissemination. The hegemonic forms of knowledge spearheaded by scientism produce hierarchies between those who possess and profess it and those who do not. Other forms of knowing and acting upon, with and within the environment are rendered illegitimate and unscientific. It is within this context that we need to rethink the concept of sustainability that has emerged as another form of bio-power. Those ontologies that result in unsustainable activities and damage to the environment are also the ones through which sustainability is understood. It is now time to rethink and reimagine the entire discourse on sustainability from a Gandhian perspective that provides an antithesis to the dominant ideologies. The alternative ways of connecting with the environment and a need for a ‘politics’ that brings these alternative debates to the centre of our consciousness are something where Gandhian philosophy shows us the way.

This article tries to understand the concept of sustainability as bio-power and how the Gandhian perspective re-centres this debate around issues of relational ontology, pluriverse and cognitive justice. The utilitarian conception and an occupying ontology towards the environment led to a concept of sustainability powered by scientism. Opposed to this conception is the Gandhian perspective that gives ample space to the locals and the idea of ‘self’ in order to bring about sustainable development. The article also argues that the criticism directed against Gandhi regarding bringing up the issue of ‘moral politics’ through his idea of self is also unfounded and needs to be rejected. Gandhian ideas do not absolve the state from its responsibilities towards its people and the environment, but they bring in the active agency of the people and the ‘self’ in the process of bringing about change in the society.
No effect of apolipoprotein E polymorphism on MRI brain activity during movie watching
Authors: Raykov Petar P. , Daly Jessica , Fisher Simon E. , Eising Else , Geerligs Linda , Bird Chris M.
Published: January 2025

Apolipoprotein E ε4 is a major genetic risk factor for Alzheimer’s disease, and some apolipoprotein E ε4 carriers show Alzheimer’s disease–related neuropathology many years before cognitive changes are apparent. Therefore, studying healthy apolipoprotein E genotyped individuals offers an opportunity to investigate the earliest changes in brain measures that may signal the presence of disease-related processes. For example, subtle changes in functional magnetic resonance imaging functional connectivity, particularly within the default mode network, have been described when comparing healthy ε4 carriers to ε3 carriers. Similarly, very mild impairments of episodic memory have also been documented in healthy apolipoprotein E ε4 carriers. Here, we use a naturalistic activity (movie watching), and a marker of episodic memory encoding (transient changes in functional magnetic resonance imaging activity and functional connectivity around so-called ‘event boundaries’), to investigate potential phenotype differences associated with the apolipoprotein E ε4 genotype in a large sample of healthy adults. Using Bayes factor analyses, we found strong evidence against existence of differences associated with apolipoprotein E allelic status. Similarly, we did not find apolipoprotein E-associated differences when we ran exploratory analyses examining: functional system segregation across the whole brain, and connectivity within the default mode network. We conclude that apolipoprotein E genotype has little or no effect on how ongoing experiences are processed in healthy adults. The mild phenotype differences observed in some studies may reflect early effects of Alzheimer’s disease–related pathology in apolipoprotein E ε4 carriers.
Navigating barriers to dementia specialty care among vulnerable populations: Insight from a multidiscipline care navigation team
Authors: Windon Charles C , Pun Stephanie , Erickson Mitchel , Jackson Ashley J , Ruben Hannah , Smith Phil , Tirona-Bito Heather , Bui Nhat , Tumaneng Angelo , Degesys Nida , Hardy James , Harris Anna , Possin Katherine L
Published: January 2025

The emergency department evaluates many patients with undiagnosed cognitive impairment and presents an opportune setting to facilitate early detection and referral to memory care specialists. We evaluated a novel care navigation pathway that facilitated referrals of ethnoculturally diverse individuals with suspected cognitive impairment from geriatric professionals embedded in the emergency department to dementia specialist care. We compared rates of referrals and successful appointment attendance for patients in this pathway compared to patients in a traditional primary care provider referral pathway. The care navigation team successfully identified and mitigated multiple barriers to accessing dementia specialist care, thereby increasing access.
Peace agreements in a changing climate: Three ways in which climate change and peace processes interact
Authors: Epple Tim
Published: January 2025

Previous research has shown that climate change can exacerbate conflict drivers or, on the other hand, incentivise ‘environmental peacebuilding’. One might, therefore, expect to find references to climate issues in peace agreements. This study draws on the PA-X Peace Agreement Database to shed new light on climate–peace interactions. Only seven out of 2,003 peace agreements signed between 1990 and 2023 explicitly mention ‘climate change’. However, an analysis of provisions in 28 peace agreements reveals that climate–peace interactions are much more complex than the paucity of the term ‘climate change’ in agreements suggests. Based on PA-X data, I argue that there are three main ways in which climate change and peace processes interact: First, as existing literature shows, the consequences of climate change can affect conflict parties’ bargaining positions and lead to conflict (de-)escalation. Second, conflict parties agree on climate action – often implicitly and for political reasons. This article provides the first comparison of levels of climate action ambition in peace agreements, from incremental and transformational adaptation to mitigation. Third, the results of political bargaining in peace processes can have positive and negative unintended consequences for the climate. For example, although conflict de-escalation can produce a more conducive environment for climate action, its stabilising effect may also enable carbon-intensive economic activities.
“They Don’t Give You No Note If It’s Got Fentanyl”: Using Cognitive Interviews to Understand Self-report and Urine Drug Screen Discrepancies
Authors: Watson Dennis P , Clark Katie , Dennis Michael L , Grella Christine E , Hart M. Kate
Published: January 2025

Background:

Fentanyl, a highly potent synthetic opioid, is now involved in the majority of drug overdose deaths in the United States. Discrepancies between substance use self-reports and urine drug screens (UDS) are common, especially when users are unaware of fentanyl adulteration.

Objectives:

The objective of this study was to examine the cognitive processes underlying discrepancies between self-reported fentanyl use and UDS results, specifically focusing on participants unaware of their fentanyl exposure.

Design:

This was a cross-sectional qualitative study.

Methods:

This study conducted cognitive interviews with 10 participants from a larger clinical trial who tested positive for fentanyl in a UDS but reported no fentanyl use. The interviews explored participants’ understanding of survey questions about fentanyl use and their interpretation of UDS results. Responses were analyzed to identify themes related to self-report discrepancies.

Results:

Participants often underreported fentanyl use, not due to social desirability bias, but because they interpreted survey questions as asking about known, rather than suspected, fentanyl use. Many acknowledged their drugs were likely adulterated but only reported use when they were certain of fentanyl’s presence.

Conclusion:

The findings suggest that refining survey questions to capture both intentional and unintentional fentanyl exposure could improve the accuracy of self-reported data. These adjustments are critical to improve the accuracy of data collected to inform surveillance strategies, effective public health policies, and clinical interventions.