bluuebunny/crossref_metadata_2025 huggingface dataset:
Numerical analysis and validation of an optical parametric oscillator considering crystal thermal effects
Authors: Wang Rui , Wang Shuilan , Tan Jiacheng , Li Yeqiu , Dai Qin
Published: December 2023

In this paper, a calculation model is proposed for the optical parametric oscillation (OPO) process considering the crystal thermal effects. Based on existing models, we combine a set of three-wave coupled equations with the Sellmeier equation. In order to optimize the calculation of the nonlinear process, a temperature variable t is introduced to describe the heat generated by the laser crystal during operation. The waveforms under different pump powers are analyzed. The effects of the reflectivity of the output mirror on the OPO threshold and inverse conversion are investigated. In addition, the optimal reflectivity under different pump powers can be estimated. Based on the simulation results, experiments are also performed in the near-infrared 1.57 µm band and mid-infrared 3.15 µm band. The experimental results are compared with the results of this model and a model that does not consider crystal thermal effects. The experimental results are consistent with the improved theoretical results, affirming that the proposed theoretical model can simulate the energy conversion process of OPO. This provides a theoretical basis for optimizing the parameters of the OPO output mirror and improving the efficiency of the parametric wave conversion.
A variant of the venom allergen-like protein, DdVAP2, is required for the migratory endoparasitic plant nematode Ditylenchus destructor parasitism of plants
Authors: Chang Qing , Yang Yiwei , Hong Bo , Zhao Yanqun , Zhao Mengxin , Han Shanshan , Zhang Feng , Peng Huan , Peng Deliang , Li Yingmei
Published: December 2023

The potato rot nematode, Ditylenchus destructor, poses a serious threat to numerous root and tuber crops, yet the functional characterization of effectors from this migratory endoparasitic plant nematode remains limited. Despite inhabiting distinct habitats, sedentary and migratory plant parasitic nematodes share the structurally conserved effectors, such as venom allergen-like proteins (VAPs). In this study, a variant of DdVAP2 was cloned from D. destructor. The transcription profile analysis revealed that DdVAP2 was higher expressed in D. destructor feeding on either potato or sweet potato compared to on fungus via qRT-PCR. And DdVAP2 was highly expressed at all life stages feeding on sweet potato, except for eggs. DdVAP2 was confirmed to be specifically expressed in the subventral esophageal glands of D. destructor through in situ hybridization assays. Combined with functional validation of the signal peptide of DdVAP2, it suggested that DdVAP2 could be secreted from nematode into host. Heterologous expression of DdVAP2 in Nicotiana benthamiana revealed that the protein localized in both cytosol and nuclei of plant cells. Knocking down DdVAP2 by RNAi in D. destructor resulted in infection and reproduction defects on plants. All the results suggest that DdVAP2 plays a crucial role in the interaction between D. destructor and plants by facilitating the nematode infection.
Loss function of NtGA3ox1 delays flowering through impairing gibberellins metabolite synthesis in Nicotiana tabacum
Authors: Deng Lele , Li Chaofan , Gao Qian , Yang Wenwu , Jiang Jiarui , Xing Jiaxin , Xiang Haiying , Zhao Jun , Yang Yekun , Leng Pengfei
Published: December 2023

Flowering time, plays a crucial role in tobacco ecological adaptation besides its substantial influence on tobacco production and leaf quality. Meanwhile, it is sensitive to biotic or abiotic challenges. The plant hormones Gibberellins (GAs), controlling a number of metabolic processes, govern plants growth and development. In this study, we created a late flowering mutant HG14 through knocking out NtGA3ox1 by CRISPR/Cas9. It took around 13.0 and 12.1 days longer to budding and flowering compared to wild type Honghuadajinyuan. Nearly all of the evaluated agronomic characters deteriorated in HG14, showing slower growth and noticeably shorter and narrower leaves. We found that NtGA3ox was more prevalent in flowers through quantitative reverse transcription PCR analysis. Transcriptome profiling detected 4449, 2147, and 4567 differently expressed genes at the budding, flowering, and mature stages, respectively. The KEGG pathway enrichment analysis identified the plant-pathogen interaction, plant hormone signal transduction pathway, and MAPK signaling pathway are the major clusters controlled by NtGA3ox1 throughout the budding and flowering stages. Together with the abovementioned signaling pathway, biosynthesis of monobactam, metabolism of carbon, pentose, starch, and sucrose were enriched at the mature stage. Interestingly, 108 up- and 73 down- regulated DEGs, impairing sugar metabolism, diterpenoid biosynthesis, linoleic and alpha-linolenic acid metabolism pathway, were continuously detected accompanied with the development of HG14. This was further evidenced by the decreasing content of GA metabolites such as GA4 and GA7, routine chemicals, alkaloids, amino acids, and organic acids Therefore, we discovered a novel tobacco flowering time gene NtGA3ox1 and resolved its regulatory network, which will be beneficial to the improvement of tobacco varieties.
How to make a difference: the impact of gender-fair language on text comprehensibility amongst adults with and without an academic background
Authors: Pabst Laura Mathilde , Kollmayer Marlene
Published: December 2023

Introduction

The proliferation of gender-fair language as a medium of communication that represents all genders can be considered as an exciting development in today's rapidly changing world. In this context, the use of the gender asterisk has become especially prominent in German, it being a grammatical gender language. However, critics often argue that gender-fair language makes texts less comprehensible and decreases its aesthetic appeal. The present study tests this assumption for the German language and is the first one to test the influence of an academic background on the comprehensibility of gender-fair language.

Method

A text, either written in gender-fair language using the gender star in its singular and plural form or a version using only masculine-only forms, was randomly assigned to 81 adults without an academic background and 82 adults with an academic background (77% women in both groups). Participants were asked to fill out a web-based questionnaire answering questions on text comprehensibility and on their attitudes toward gender-fair language.

Results

The results show no statistically significant difference in comprehensibility ratings between participants who read a text in gender-fair language and those who read a text in masculine-only language. In addition, attitudes toward gender-fair language did not affect comprehensibility ratings in participants who read the text written in gender-fair language using the gender star. Further, the academic background had no effect on the assessment of gender-fair language.

Discussion

To conclude, the present study suggests that there is no evidence that gender-fair language reduces the comprehensibility of texts.
Optimal strategy of in-game items with conspicuous consumption: whether to provide the grinding version?
Authors: Luo Feng , Chen Jiaqi , Xu Tiantong
Published: December 2023

In the virtual world, whether or not to spend money on in-game items distinguishes paying players from non-paying players. Due to the existence of conspicuous psychology, paying players will greatly increase their conspicuous utility after purchasing an item in addition to the utility of the item itself. In this case, whether providing different versions of items can bring greater revenue to the game company is a question worth investigating. In this study, two analytical models considering conspicuous intensity are developed to compare the optimal pricing strategy of the game company providing the single-version item or dual-version items. The single-version item can only be purchased, while a relatively low-quality version that can be obtained by grinding is provided in the dual-version strategy. Grinding means using time in games to get items instead of spending in games. The results suggest that it is more profitable for companies to offer dual-version items when conspicuous intensity is strong. Game companies can also adjust the time needed to acquire the grinding version item and the quality gap between the two versions to achieve greater revenue. The research contributes to providing a theoretical basis and decision support for game companies to decide whether to provide different versions of in-game items.
Factors and framing effects in support for net zero policies in the United Kingdom
Authors: Poortinga Wouter , Whitmarsh Lorraine , Steentjes Katharine , Gray Emily , Thompson Sophie , Brisley Rachel
Published: December 2023

Achieving ambitious carbon reduction targets requires transformative change to society, with behaviour change playing an important role. Climate change mitigation (‘net zero’) policies are needed to accelerate and support such behaviour change. This study examined factors and framing effects in public support for net zero policies in the United Kingdom (UK), making use of a large probability sample (ntotal = 5,665) survey conducted in August 2021. It found that net zero policies are widely supported, with only taxes on red meat and dairy products being supported by less than half of the UK public. Climate worry and perceived fairness were the strongest and most consistent predictors of policy support for net zero policies. The results further suggest that support for net zero policies can be increased by emphasising the co-benefits of the policies, in particular where they are beneficial for health. However, the framing effects were very small. In contrast, public support for net zero policies is lower when potential lifestyle and financial costs are mentioned. This suggests that perceived fairness of the distribution of costs and lifestyle implications of policies are crucial for building and maintaining support for net zero.
Serious gaming for graduates employability enhancement
Authors: Yanes Nacim , Bououd Ikram , Jamel Leila , Alturki Nazik
Published: December 2023

Higher Education Institutions (HEIs) are blamed for being insouciant about the business world and not efficiently steeling students with employment abilities. As a reply to this exigency from business owners, HEIs have started to show commitment to graduate employability through developing and adopting new educational material, such Serious Games (SGs), to help students acquire these soft skills. This paper explores the students’ perceptions of the significance of SGs on soft skills and therefore boosting graduate employability. We carried out a quantitative and qualitative study with 322 students from business colleges in the aim to focus on the impact of user experience in SGs on critical thinking and teamwork. The results highlight the strong influence of SGs to acquire these soft skills.
Cross-sectional analysis reveals COVID-19 pandemic community lockdown was linked to dysregulated cortisol and salivary alpha amylase in children
Authors: Lloyd Katherine M. , Gabard-Durnam Laurel , Beaudry Kayleigh , De Lisio Michael , Raine Lauren B. , Bernard-Willis Ysabeau , Watrous Jennifer N. H. , Whitfield-Gabrieli Susan , Kramer Arthur F. , Hillman Charles H.
Published: December 2023

The COVID-19 pandemic altered everyday life starting in March 2020. These alterations extended to the lives of children as their normal routines were disrupted by community lockdowns, online learning, limited in-person social contact, increased screen time, and reduced physical activity. Considerable research has investigated the physical health impact of COVID-19 infection, but far fewer studies have investigated the physiological impact of stressful pandemic-related changes to daily life, especially in children. The purpose of this study was to leverage an ongoing clinical trial to investigate physiological consequences associated with chronic stress of pandemic community lockdown on children. As a part of the clinical trial, children provided saliva samples. Saliva samples were analyzed for cortisol and salivary alpha amylase (sAA) content. This secondary cross-sectional analysis included 94 preadolescent children located within the Greater Boston, Massachusetts community. Children participated in the study either before, during, or following the pandemic community lockdown to form three groups for comparison. In response to chronic stress caused by the pandemic community lockdown, participants demonstrated dysregulation of fast-acting catecholamine response of the locus-coeruleus-norepinephrine system and slower-acting glucocorticoid response, resulting in an asymmetrical relationship of hypocortisolism (M = 0.78 ± 0.19 μg/mL, p < 0.001) paired with higher sAA (M = 12.73 ± 4.06 U/mL, p = 0.01). Results suggest that the abrupt COVID-19 disruption to daily life, including the stressful experience of community lockdown, had physiological effects on typically developing children. Further research is required to investigate mental health outcomes of children following the chronic stress of the pandemic community lockdown.
Assessing the impact of China’s river chief system on enterprise pollution discharge
Authors: Du Jianxiao , Li Bo
Published: December 2023

The River Chief System (RCS), a pivotal environmental governance policy promoted by the Chinese government, has far-reaching implications for public health. This study aims to comprehensively assess the impact of RCS on corporate pollution emissions, emphasizing its role in improving environmental quality and safeguarding public health. Utilizing a database of industrial enterprises and data from heavily polluting enterprises spanning 2003 to 2013. Manual collation of RCS policy implementation across prefecture-level cities during the same period. Application of the DID method to verify the impact of RCS on the extent of corporate pollution emissions. RCS significantly reduces pollution emissions from enterprises. Heterogeneity analysis reveals RCS to be more effective in addressing visible pollutants in rivers, non-provincial capitals, and heavily polluting industries, resulting in a notable reduction in pollution emissions. Mechanism testing underscores the importance of increasing government attention to environmental protection and strengthening environmental regulation as key factors contributing to RCS’s success in reducing pollution emissions from enterprises. Additionally, the study finds that improving the business environment of enterprises, measured through the marketization index, enhances the effectiveness of RCS in improving river pollution by enterprises. This study introduces a new perspective on examining the pollution reduction and abatement effects of RCS, addressing a gap in micro-level research. The findings not only contribute to the understanding of RCS’s impact on pollution but also offer valuable insights for governments and policymakers in promoting the further development and implementation of RCS policies. The results of this research are of significant importance in strengthening environmental governance and safeguarding public health. By effectively controlling corporate pollution emissions, RCS contributes positively to improving environmental quality and, consequently, enhancing public health outcomes.
Strategies for the implementation of the living guidelines for cochlear implantation in adults
Authors: Ramos-Macías Ángel , De Raeve Leo , Holcomb Meredith , Connor Ella , Taylor Aiya , Deltetto Irene , Taylor Colman
Published: December 2023

Introduction

Clinical guidelines for cochlear implants (CI) exist in several countries, however, they lack consistency and often do not encompass the full user journey. This study aims to explore the barriers and facilitators for implementing global Living Guidelines for cochlear implantation in adults with severe, profound or moderate sloping to profound sensorineural hearing loss (SPSNHL) as well as identify guideline implementation (GI) tools that may support uptake.

Methods

A convenience sample of Task Force members were recruited for semi-structured interviews. Interview transcripts were thematically analysed to group country-specific barriers, facilitators and GI tools into three levels: health care provider (HCP), consumer and structural. Once identified, barriers and facilitators were classified into four themes related to awareness, economic, guideline or other.

Results

Interviews were conducted with 38 Task Force members, representing 20 countries. Lack of CI and hearing loss awareness was a major barrier at the HCP (85% of countries), consumer (80%) and structural (20%) levels. Economic and guideline barriers followed at the HCP (35%; 25%), consumer (45%; 0%) and structural (55%; 30%) levels, respectively. Facilitators focused on raising awareness of hearing loss and CIs as well as guideline related initiates at the HCP (80%; 70%), consumer (70%; 10%) and structural (25%; 70%) levels. GI tools including education, economic evaluations, quick reference resources and social media can help improve awareness and uptake.

Conclusion

Awareness is the primary barrier to implementing Living Guidelines globally for adults with SPSNHL. Endorsement from key professional bodies and using the best available evidence can enhance uptake.
Settings, populations, and time: a conceptual framework for public health interventions
Authors: Aagaard-Hansen Jens , Bloch Paul
Published: December 2023

This paper presents a conceptual framework displaying how combinations of settings and populations seen in a long-term perspective may guide public health and health promotion planning and research. The notion of settings constitutes a key element of health promotion as stipulated by the Ottawa Charter from 1986. The setting approach highlights the individual, social and structural dimensions of health promotion. Likewise, the notion of populations and how they are selected forms a center pillar of public health. By joining the two perspectives, four combinations of intervention strategies appear by addressing: (1) a single population segment within a single setting, (2) multiple population segments within a single setting, (3) a single population segment within multiple settings or (4) multiple population segments within multiple settings. Furthermore, the addition of a time dimension inspired by the life-course perspective illustrates how trajectories of individuals and projects change settings and population segments as time goes by. The conceptual framework displays how systematic awareness of long-term, multi-setting, multi-population trajectories allow health promotion planners and researchers to systematically develop, plan and analyze their projects.
Revolutionizing ocular cancer management: a narrative review on exploring the potential role of ChatGPT
Authors: Alotaibi Saud S. , Rehman Amna , Hasnain Muhammad
Published: December 2023

This paper pioneers the exploration of ocular cancer, and its management with the help of Artificial Intelligence (AI) technology. Existing literature presents a significant increase in new eye cancer cases in 2023, experiencing a higher incidence rate. Extensive research was conducted using online databases such as PubMed, ACM Digital Library, ScienceDirect, and Springer. To conduct this review, Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines are used. Of the collected 62 studies, only 20 documents met the inclusion criteria. The review study identifies seven ocular cancer types. Important challenges associated with ocular cancer are highlighted, including limited awareness about eye cancer, restricted healthcare access, financial barriers, and insufficient infrastructure support. Financial barriers is one of the widely examined ocular cancer challenges in the literature. The potential role and limitations of ChatGPT are discussed, emphasizing its usefulness in providing general information to physicians, noting its inability to deliver up-to-date information. The paper concludes by presenting the potential future applications of ChatGPT to advance research on ocular cancer globally.
Quasi-one-dimensional carbon-based fractal lattices
Authors: Lage L. L. , Latgé A.
Published: December 2023

Fractal systems are now considered alternative routes for engineering physical properties on the nanoscale. In particular, stable annular quantum corrals have been demonstrated in distinct synthesis procedures and can provide interesting localized and resonant states. We here present a theoretical description of effective fractal lattices, mainly composed of annular Koch geometries based on carbon atoms, and of more complex organic molecules described by triangular Sierpinski geometries. A single band tight-binding approach is considered to derive electronic and transport properties. Fractal molecular linear chains composed of fractal Koch quantum corrals are proposed, and their electronic transport is discussed based on the complexity of the neighboring hopping. The spatial charge distributions at different energies highlight the contribution of the composing metallic and carbons atoms in the quantum corral features, serving as a guide to new functionalization applications based on the symmetry and fractal peculiarities of the proposed nanostructured lattices.
Visualized peritoneal fluid variation in adolescents and young adults with endometriosis: is there more to it?
Authors: Yousif Abdelrahman , DePari Mary , Vitonis Allison F. , Harris Holly R. , Shafrir Amy L. , Terry Kathryn L. , Missmer Stacey A. , Sasamoto Naoko
Published: December 2023

Background

Peritoneal fluid is a medium for endometriosis-associated biomarker discovery from which the local peritoneal environment and pathophysiologic pathways are often inferred. Therefore, we evaluated the associations between peritoneal fluid color and volume at time of endometriosis-related laparoscopic surgery with patient characteristics, endometriosis type and lesion location in adolescents and young adults with endometriosis.

Methods

We conducted a cross-sectional analysis among 545 patients undergoing surgery for endometriosis who enrolled in the Women's Health Study: from Adolescence to Adulthood cohort study. Patient characteristics, surgically visualized endometriosis phenotypes, and gross characteristics of peritoneal fluid were collected in compliance with World Endometriosis Research Foundation Endometriosis Phenome and Biobanking Harmonization Project (EPHect) tools. Chi-square or Fisher's exact tests were applied to test for differences across categories.

Results

Most of the patients were adolescents or young adults (86% age <25 years) of white race (89%), with only superficial peritoneal lesions and rASRM stage = I/II observed at surgery (both 95%). We observed variation in peritoneal fluid color across different menstrual cycle phases at time of surgery (p = 0.006). Among those who were cycling at time of surgery, endometriosis patients with red peritoneal fluid were most likely to be in the proliferative phase (49%) compared to the secretory phase (27%), while those with yellow or orange peritoneal fluid were most likely to be in the secretory phase (57% and 86% respectively). Yellow color was significantly less common in those taking combined oral contraceptives but much more common with progesterone only formulation exposure (p = 0.002). Peritoneal fluid volume did not differ by cycle phase but was more likely to be low (≤6 ml) for those exposed to hormones at time of surgery (p = 0.01). Those with acyclic pelvic pain were less likely to have red peritoneal fluid (p = 0.001) but had greater volume (p = 0.02) compared to those without.

Conclusion

Our findings highlight the importance of accounting for menstrual cycle phase and hormonal exposures when designing research using peritoneal fluid samples and inferring from biomarker results intended to advance our understanding of endometriosis and associated symptom pathophysiology.
Autologous full-thickness skin in the repair of complex ventral hernias: an innovative step into the future of complex hernia repair?
Authors: Holmdahl Viktor , Strigård Karin , Gunnarsson Ulf
Published: December 2023

The repair of complex ventral hernias, such as giant incisional or parastomal hernia, is associated with a high risk for complications and recurrence. Some serious complications are related to implantation of synthetic mesh as reinforcement material. Autologous full-thickness skin graft (FTSG) as reinforcement material in the repair of these complex hernias may offer a safe alternative. This is a review of the history of FTSG use in hernia surgery and the experiences of our research group regarding its application over the last decade. The results of FTSG used in the repair of giant ventral hernias are promising, and this method may already be recommended in selected cases. We have also conducted a translational chain of preclinical studies, based on a murine model, to gain a greater understanding of the behaviour of FTSG implanted in various positions in the abdominal wall. The use of intraperitoneal FTSG as reinforcement material in parastomal hernia repair is currently being evaluated in a randomised, controlled, multicentre study.
Generator of Fuzzy Implications
Authors: Daniilidou Athina , Konguetsof Avrilia , Souliotis Georgios , Papadopoulos Basil
Published: December 2023

In this research paper, a generator of fuzzy methods based on theorems and axioms of fuzzy logic is derived, analyzed and applied. The family presented generates fuzzy implications according to the value of a selected parameter. The obtained fuzzy implications should satisfy a number of axioms, and the conditions of satisfying the maximum number of axioms are denoted. New theorems are stated and proven based on the rule that the fuzzy function of fuzzy implication, which is strong, leads to fuzzy negation. In this work, the data taken were fuzzified for the application of the new formulae. The fuzzification of the data was undertaken using four kinds of membership degree functions. The new fuzzy functions were compared based on the results obtained after a number of repetitions. The new proposed methodology presents a new family of fuzzy implications, and also an algorithm is shown that produces fuzzy implications so as to be able to select the optimal method of the generator according to the value of a free parameter.
How Can Digitalization Mitigate Pandemic-Induced Demand Shocks? A Case Study from the Apparel Industry
Authors: Matyusz Zsolt , Pistrui Bence
Published: December 2023

This paper aims to explore how digitalization can be used as a risk mitigation tool against pandemic-induced demand shocks, when customer movements and activities are constrained by government regulations. Due to the disrupting events of the COVID-19 pandemic, we opted for an exploratory study to uncover the risk mitigation capabilities of digitalization under these circumstances, using a fast fashion case company as an empirical example. Several interviews were conducted with middle and top managers at the company. Our empirical insights about the risk mitigation capabilities of digitalization suggest that, as COVID-19-like events may become more frequent in the future, digital tools offering certain mitigations against physical constraints should be valued more highly than they have been previously. We encourage decision makers to look at the risk mitigation capabilities of digital solutions and include those into the cost–benefit discussion when thinking about new investments. In this way, our paper fills a pragmatic gap in this field, and is expected to help companies to identify the key success factors for the successful implementation of a digital transformation. Because of our chosen research approach, the research results may lack generalizability. Further company-wide, industry-wide, and country-wide extension of this research is possible.
Prediction of Transonic Flow over Cascades via Graph Embedding Methods on Large-Scale Point Clouds
Authors: Lan Xinyue , Wang Liyue , Wang Cong , Sun Gang , Feng Jinzhang , Zhang Miao
Published: December 2023

In this research, we introduce a deep-learning-based framework designed for the prediction of transonic flow through a linear cascade utilizing large-scale point-cloud data. In our experimental cases, the predictions demonstrate a nearly four-fold speed improvement compared to traditional CFD calculations while maintaining a commendable level of accuracy. Taking advantage of a multilayer graph structure, the framework can extract both global and local information from the cascade flow field simultaneously and present prediction over unstructured data. In line with the results obtained from the test datasets, we conducted an in-depth analysis of the geometric attributes of the cascades reconstructed using our framework, considering adjustments made to the geometric information of the point cloud. We fine-tuned the input using 1603 data points and quantified the contribution of each point. The outcomes reveal that variations in the suction side of the cascade have a significantly more substantial influence on the field results compared to the pressure side and explain the way graph neural networks work for cascade flow-field prediction, enhancing the comprehension of graph-based flow-field prediction among developers and proves the potential of graph neural networks in flow-field prediction on large-scale point clouds and design.
Unveiling the Microbiome Landscape: A Metagenomic Study of Bacterial Diversity, Antibiotic Resistance, and Virulence Factors in the Sediments of the River Ganga, India
Authors: Rout Ajaya Kumar , Tripathy Partha Sarathi , Dixit Sangita , Behera Dibyajyoti Uttameswar , Behera Bhaskar , Das Basanta Kumar , Behera Bijay Kumar
Published: December 2023

The global rise in antibiotic resistance, fueled by indiscriminate antibiotic usage in medicine, aquaculture, agriculture, and the food industry, presents a significant public health challenge. Urban wastewater and sewage treatment plants have become key sources of antibiotic resistance proliferation. The present study focuses on the river Ganges in India, which is heavily impacted by human activities and serves as a potential hotspot for the spread of antibiotic resistance. We conducted a metagenomic analysis of sediment samples from six distinct locations along the river to assess the prevalence and diversity of antibiotic resistance genes (ARGs) within the microbial ecosystem. The metagenomic analysis revealed the predominance of Proteobacteria across regions of the river Ganges. The antimicrobial resistance (AMR) genes and virulence factors were determined by various databases. In addition to this, KEGG and COG analysis revealed important pathways related to AMR. The outcomes highlight noticeable regional differences in the prevalence of AMR genes. The findings suggest that enhancing health and sanitation infrastructure could play a crucial role in mitigating the global impact of AMR. This research contributes vital insights into the environmental aspects of antibiotic resistance, highlighting the importance of targeted public health interventions in the fight against AMR.
The Impact of Follicular Fluid Oxidative Stress Levels on the Outcomes of Assisted Reproductive Therapy
Authors: Chen Yu , Yang Jiahao , Zhang Ling
Published: December 2023

Oocyte quality is a pivotal determinant of assisted reproductive outcomes. The quality of oocytes is intricately linked to their developmental microenvironment, particularly the levels of oxidative stress within the follicular fluid. Oxidative stress levels in follicular fluid may have a substantial influence on oocyte health, thereby impacting the outcomes of ART procedures. This review meticulously explores the intricate relationship between oxidative stress in follicular fluid and ART outcomes. Furthermore, it delves into strategies aimed at ameliorating the oxidative stress status of follicular fluid, with the overarching goal of enhancing the overall efficacy of ART. This research endeavors to establish a robust foundation and provide valuable guidance for clinical treatment approaches, particularly in the context of infertile women, including those of advanced maternal age.
A Novel Method for Predicting Residual Stress in GH4169 Machined Surfaces through Micro-Hardness Measurement
Authors: Yao Gonghou , Liu Zhanqiang , Ma Haifeng
Published: December 2023

The presence of residual stress seriously affects the mechanical performance and reliability of engineering components. Here, the authors propose a novel method to determine corresponding residual stress through micro-hardness measurements of machined surfaces. In this study, a mathematical model with equal biaxial stress indentation is established. Then, the correlation of micro-hardness with indentation and residual stress is used to determine the prediction equation of residual stress. The material applied in this study is the nickel-based Superalloy GH4169. The residual stress prediction formula for Superalloy GH4169 is ultimately determined through the finite element method by subjecting the indentation to residual stress and fitting the experimental test data. The relationship between the indentation modulus and indentation depth is given quantitatively. The relationship between residual stress and hardness is given quantitatively. The prediction results show that the compressive residual stress can enhance the material hardness and make the contact deformation only require a low indentation depth to achieve complete plastic deformation. Conversely, the tensile residual stress can result in a deeper depth and less hardness at the initial stage of the fully plastic state. For the materials that yield more easily (small ratio of elastic modulus to yield strength), the effect is more evident. The model presented in this paper can accurately forecast corresponding residual stress through measurements of the micro-hardness of machined surfaces.
Semi-Supervised Domain Adaptation for Individual Identification from Electrocardiogram Signals
Authors: Byeon Yeong-Hyeon , Kwak Keun-Chang
Published: December 2023

When acquiring electrocardiogram (ECG) signals, the placement of electrode patches is crucial for acquiring electrocardiographic signals. Constant displacement positions are essential for ensuring the consistency of the ECG signal when used for individual identification. However, achieving constant placement of ECG electrode patches in every trial for data acquisition is challenging. This is because different individuals may attach patches, and even when the same person attaches them, it may be difficult to specify the exact position. Therefore, gathering ECG data from various locations is necessary. However, this process requires a substantial amount of labor and time, owing to the requirement for multiple attempts. Nonetheless, persisting with these efforts enables the endurance of some ECG differences. To reduce labor and time, we propose a semi-supervised domain adaptation for individual identification using ECG signals. The method operates with a full set of original ECG signals and a small set of ECG signals from different placements to account for the differences between the signals in the generative adversarial network (CycleGAN). Specifically, to train the CycleGAN, the ECG signals were transformed into time–frequency representations, and the trained generator was used to generate ECG signals to expand the small set of ECG signals from different placements. Subsequently, both the original and generated signals were used to train the classifier for individual identification. This scenario can also be applied to the classification of ECG signals from different sensors. The PTB-ECG dataset was used for this experiment. We found that the proposed method showed higher accuracy than when only the original ECG signals were used for the training classifier.
Temporal Convolutional Network-Based Axle Load Estimation from Pavement Vibration Data
Authors: Bian Zeying , Zeng Mengyuan , Zhao Hongduo , Guo Mu , Cai Juewei
Published: December 2023

Measuring the axle loads of vehicles with more accuracy is a crucial step in weight enforcement and pavement condition assessment. This paper proposed a vibration-based method, which has an extended sensing range, high temporal sampling rate, and dense spatial sampling rate, to estimate axle loads in concrete pavement using distributed optical vibration sensing (DOVS) technology. Temporal convolutional networks (TCN), which consist of non-causal convolutional layers and a concatenate layer, were proposed and trained by over 6000 samples of vibration data and ground truth of axle loads. Moreover, the TCN could learn the complex inverse mapping between pavement structure inputs and outputs. The performance of the proposed method was calibrated in two field tests with various conditions. The results demonstrate that the proposed method obtained estimated axle loads within 11.5% error, under diverse circumstances that consisted of different pavement types and loads moving at speeds ranging from 0~35 m/s. The proposed method demonstrates significant promise in the field of axle load reconstruction and estimation. Its error, closely approaching the 10% threshold specified by LTPP, underscores its efficacy. Additionally, the method aligns with the standards set by Cost-323, with an error level-up to category C. This indicates its capability to provide valuable support in the assessment and decision-making processes related to pavement structure conditions.
Neuromuscular Assessment of a Stand-Up Paddle Stroke
Authors: Freitas João , Conceição Ana , Šťastný Jan , Louro Hugo , Leitão Luís , Torres Diana , Marinho Daniel A. , Neiva Henrique P.
Published: December 2023

This study analyzed muscle activity during the stand-up paddle stroke, considering the paddling side and the adjacent and opposing muscles relative to the position of the arms during paddling. Methods: Fourteen male paddleboarders performed three trials covering 195 m in which surface electromyography of the upper trapezius, biceps brachii, triceps brachii, tibialis anterior, and gastrocnemius medialis were recorded (four-cycle strokes on each side). The data were processed according to percentage of maximum voluntary contraction (% MVC). The MVC activation values (µV) for each muscle were then calculated and presented as percentage MVC (% MVC). Results: The recovery phase accounted for 60% of the paddle cycle, while the pull phase represented 39%. During right-side paddling, higher % MVC was found in the opposite-side upper trapezius (24.35%, p < 0.01) during the pulling phase and in the adjacent biceps brachii (8.36%, p < 0.03) during the recovery phase. In left-side paddling, greater % MVC was found in the opposite-side upper trapezius (27.60%, p < 0.01) during the pulling phase and in the opposite-side triceps brachii (42.25%, p < 0.04) during the recovery phase. Furthermore, the pulling phase exhibited higher MVC in the opposite-side upper trapezius compared to the recovery phase, both in the right-side (24.35%, p < 0.03) and left-side (27.60%, p < 0.01) paddling. Conclusions: these findings help establish the muscular activity of both sides of the paddling technique and the differences between the upper and lower limbs.
Finite Element Model of Scoliosis Brace with Increased Utility Characteristics
Authors: Grycuk Slawomir , Mrozek Piotr
Published: December 2023

Orthoses are of critical importance in the field of medical biomechanics, particularly in the correction of spinal deformities. The objective of the current research was to improve the utility characteristics of the scoliosis brace without compromising its corrective capabilities. The orthotic shell of the Boston brace was used as the basis for this investigation. The finite element method (FEM) was used to evaluate the distribution of corrective forces through the device. The flow of force lines within the orthotic shell was determined by mapping the paths of maximum principal stresses. Areas of the device that had a negligible effect on overall stiffness were identified and material from these areas was eliminated. Minor modifications were then made to the redesigned shell to maintain its corrective stiffness. As a result of these changes, the weight of the braces was reduced without compromising its corrective stiffness. When subjected to corrective forces, the shell’s displacement patterns in the transverse plane showed minimal changes from the original model, confirming that its corrective capacity remained largely intact. This research presents an innovative methodology for orthotic design and demonstrates that structural optimization based on the mapping of maximum principal stress pathways can significantly improve device functionality. The approach outlined here holds promise for future advances in the design of various orthotic devices, thereby contributing to the advancement of the field.
Thermal Analysis in the Evaluation of Solid Lipid Microparticles in the Form of Aqueous Dispersion and Fine Powder
Authors: Wolska Eliza , Regdon Géza
Published: December 2023

In the presented study, an attempt was made to investigate the most important attributes of solid lipid microparticles (SLM) using thermal analysis (DSC/TG) in order to determine the importance of this technique in the research and development of lipid microparticles. Particularly interesting in our studies were drug–lipid interactions and modifications of the SLM matrix structure induced by the production method (the hot emulsification method) and further processing (e.g., spray drying), as well as changes occurring during the stability studies. Cyclosporine A, indomethacin and spironolactone were used as model active substances incorporated into SLM. The conducted research demonstrated the significant potential of DSC/TG, especially for the analysis of SLM in the form of fine powder. The method of sample preparation, consisting of evaporation of water at room temperature, turned out to be crucial for the DSC/TG analysis of SLM dispersion. In the case of the tested SLM, the basic and usually the only observed thermal transformation in the DSC spectrum was the endothermic peak associated with the lipid forming a microsphere matrix. This peak is the main source of information about the properties and stability of the tested SLM. The obtained results show that glyceryl behenate (Compritol) is a significantly better lipid for forming lipid microparticles than stearic acid. Although thermal transformations of the incorporated drug substances are not directly visible in the DSC spectra, their impact on the SLM properties can be assessed indirectly, based on changes in the lipid melting point and the shape of the DSC and TG peaks and curves. DSC/TG studies confirmed the lack of an effect of the spray drying process on the properties of drug-loaded SLM with Compritol. Studies have also shown up to a 2-year stability of SLM with CsA.
Estimates of Lightning Activity and Terrestrial Gamma-ray Flash Detectability at Mount Etna for the ESTHER Project
Authors: Ursi Alessandro , Reitano Danilo , Virgilli Enrico , Bulgarelli Andrea , Tiberia Alessandra
Published: December 2023

The Experiment to Study Thunderstorm High-Energy Radiation (ESTHER) is a small project of the Italian National Institute for Astrophysics (INAF), devoted to the study of high-energy emissions from thunderstorms, such as Terrestrial Gamma-ray Flashes and gamma-ray glows, which will start in 2024. In order to reduce the absorption typically undergone by gamma-ray radiation in the lower layers of the atmosphere and make these events detectable on the ground, the ESTHER set-up will be installed at high altitudes on Mt. Etna (Italy). We carried out a detailed analysis of lightning occurrence in this geographic region in order to test how suitable such a location is for the installation of a detection system to investigate thunderstorms and related emissions. The analysis pointed out a strong clustering of lightning in the proximity of the mountain peak and over the main volcano craters, where the frequent presence of volcanic ashes could increase, under the conditions of humid air typical of thunderstorms, electrical conductivity. An estimate of the gamma-ray absorption in the air undergone by typical TGF radiation allowed us to evaluate the suitability of two possible installation sites suggested for the project. This study represents a preliminary work for ESTHER and serves as a launching pad for future analyses.
A Study of the Atomic Processes of Highly Charged Ions Embedded in Dense Plasma
Authors: Jha Alok Kumar Singh , Dimri Mayank , Dawra Dishu , Mohan Man
Published: December 2023

The study of atomic spectroscopy and collision processes in a dense plasma environment has gained a considerable interest in the past few years due to its several applications in various branches of physics. The multiconfiguration Dirac-Fock (MCDF) method and relativistic configuration interaction (RCI) technique incorporating the uniform electron gas model (UEGM) and analytical plasma screening (APS) potentials have been employed for characterizing the interactions among the charged particles in plasma. The bound and continuum state wavefunctions are determined using the aforementioned potentials within a relativistic Dirac-Coulomb atomic structure framework. The present approach is applied for the calculation of electronic structures, radiative properties, electron impact excitation cross sections and photoionization cross sections of many electron systems confined in a plasma environment. The present study not only extends our knowledge of the plasma-screening effect but also opens the door for the modelling and diagnostics of astrophysical and laboratory plasmas.
Qualitative Characterization of Lead–Acid Batteries Fabricated Using Different Technological Procedures: An EIS Approach
Authors: Bruj Olivia , Calborean Adrian
Published: December 2023

Electrochemical impedance spectroscopy techniques were applied in this work to nine industrially fabricated lead–acid battery prototypes, which were divided into three type/technology packages. Frequency-dependent impedance changes were interpreted during successive charge/discharge cycles in two distinct stages: (1) immediately after fabrication and (2) after a controlled aging procedure to 50% depth of discharge following industrial standards. To investigate their state of health behavior vs. electrical response, three methods were employed, namely, the Q-Q0 total charge analysis, the decay values of the constant-phase element in the equivalent Randles circuits, and the resonance frequency of the circuit. A direct correlation was found for the prediction of the best-performing batteries in each package, thus allowing for a qualitative analysis that was capable of providing the decay of the batteries’ states of health. We found which parameters were directly connected with their lifetime performance in both stages and, as a consequence, which type/technology battery prototype displayed the best performance. Based on this methodology, industrial producers can further establish the quality of novel batteries in terms of performance vs. lifespan, allowing them to validate the novel technological innovations implemented in the current prototypes.