bluuebunny/crossref_metadata_2025 huggingface dataset:
A Multi-Modal Sarcasm Detection Model Based onCue Learning
Authors: Lu Ming , Dong Zhiqiang , Zhang Litian , Guo Ziming , Zhang Xiaoming
Published: September 2024

The rapid proliferation of internet data, particularly through social media, has amplified the need for effective sentiment analysis, including the complex task of sarcasm detection. This paper presents a novel multi-modal sarcasm detection model leveraging cue learning techniques to address the challenges posed by data scarcity, especially in low-resource languages. The proposed model builds upon the CLIP architecture, integrating text and image modalities to co-learn sarcasm cues. The methodology encompasses discrete prompt generation, learnable continuous vectors, and multi-modal fusion to enhance detection accuracy. The multi-modal fusion process demonstrates a symmetric integration of text and image data, leading to improved performance. Experimental results on the Twitter Multi-modal Sarcasm Detection Dataset (MSD) demonstrate significant performance improvements over traditional models, highlighting the model's robustness and adaptability in small-sample scenarios. This research contributes a practical solution for nuanced sentiment analysis, paving the way for advanced applications in public opinion monitoring and AI-driven decision-making processes.
Sleep disorders, electronic device use, and family support: looking for a link in type 1 diabetic adolescents regarding their glycemic control
Authors: Tafti Mahdi Falah , Talebian Niki , Shokri Pourya , Shabani-Derakhshan Soolmaz , Hadeiy Seyed Kaveh , Jafari Alimohamad , Pirdehghan Azar , Razavi Zahra
Published: September 2024

Background
Sleep is a key element in adolescent health and affects glycemic control in diabetic patients. Electronic device use and family support are contributing factors to sleep characteristics and glycemic management in type 1 diabetes (T1D) patients. This study aims to evaluate the influence of electronic device use and family support on sleep disorders and identify possible effects on glycemic control in T1D adolescents.
Methods
This cross-sectional study was conducted on T1D adolescents who attended the diabetes clinic at Besat Hospital, Hamadan, Iran, from February 2021 to February 2022. Valid Persian versions of the Pittsburgh Sleep Quality Index (PSQI) and Perceived Social Support from Family (PSS-Fa) questionnaires were employed to measure sleep quality and family support. A valid self-report questionnaire was used to obtain data on time spent on screen-based sedentary behaviors, including TV, video games, and the Internet. The demographic characteristics and hemoglobin A1C (HbA1c) and fasting blood sugar levels of the patients were obtained during the follow-up sessions. Statistical analysis was performed using SPSS 21. Kruskal-Wallis and Dunn’s tests were applied to compare different sleep disorder groups in terms of quantitative variables. Spearman’s correlation test examined the association of PSS-Fa scores and quantitative variables.
Results
We recruited 171 patients with a mean age of 12.48 ± 1.75 years. Nine patients (5.3%) had no/mild sleep disorders, 75 (43.9%) had moderate sleep disorders, and 87 (50.9%) had severe sleep disorders. No association was found between sleep disorders and HbA1c (P = 0.476). among electronic devices, only watching TV was associated with sleep disorders (P = 0.023). PSS-Fa scores were significantly lower in adolescents with severe sleep disorders compared with no/mild (P = 0.026) and moderate (P = 0.029) sleep disorder groups. PSS-Fa scores were positively correlated with the number of annual visits (P = 0.033; r = 0.164) and negatively correlated with the time since diabetes diagnosis (P = 0.003; r = -0.229) and the HbA1c level (P < 0.001; r = -0.271).
Conclusions
A supportive family can contribute not only to better sleep outcomes but also to more desirable glycemic management in T1D adolescents. Digital devices might deteriorate sleep quality but the pattern of this effect needs further investigation.
The impact of long-acting GnRHa pretreatment on the clinical pregnancy outcomes of hormone replacement therapy-frozen embryo transfer in RIF patients with PCOS: a retrospective clinical study
Authors: Huang Chenyang , Yan Yuan , Mei Jie , Jiang Yue , Sun Haixiang , Xing Jun
Published: September 2024

Background
Several studies have demonstrated that pre-treatment with long-acting Gonadotropin-Releasing Hormone agonists (GnRHa) can significantly enhance the clinical pregnancy rate among recurrent implantation failure (RIF) patients. Investigations have also suggested that GnRHa pre-treatment could ameliorate the clinical pregnancy and live birth rates in polycystic ovary syndrome (PCOS) patients. But there is a dearth of research on whether long-acting GnRHa pre-treatment yields superior clinical outcomes for RIF patients with PCOS.
Methods
The retrospective study enrolled 1602 patients under the age of 40 meeting the criteria for RIF at the Reproductive Medicine Center of Nanjing Drum Tower Hospital, who underwent frozen-thawed embryo transfer (FET) between January 2017 and December 2021. Univariate analysis and a multivariate logistic regression model were employed to assess the impact of GnRHa pretreatment on the clinical pregnancy rate in RIF patients. The influence of long-acting GnRHa pretreatment on clinical pregnancy outcomes was re-examined in PCOS and non-PCOS subgroups. Additionally, an interaction analysis was performed to evaluate the effect of PCOS on the relationship between long-acting GnRHa pretreatment and the clinical pregnancy rate.
Results
Multiple regression analysis showed that long-acting GnRHa pretreatment had a positive impact on the clinical pregnancy rate. We divided the RIF population into two subgroups, for PCOS patients, although the clinical pregnancy rate was higher in women who received GnRHa pretreatment compared to those who did not, it was not statistically significant. Interaction analysis suggested that for PCOS patients, there was no significant difference in the clinical pregnancy rate between women who received GnRHa pretreatment and those who did not, indicating that the effect of GnRHa pretreatment on the clinical pregnancy rate was not influenced by PCOS.
Conclusions
Our study demonstrates that long-acting GnRHa pretreatment can enhance clinical pregnancy outcomes in patients with RIF. Among RIF patients without PCOS, the clinical pregnancy rate exhibited a significant increase following GnRHa pretreatment compared to the control group. However, in RIF patients with concurrent PCOS, although there was no significant elevation in the clinical pregnancy rate post-GnRHa pretreatment. Additionally, the influence of GnRHa pretreatment on the clinical pregnancy rate was found not to be affected by the presence of PCOS.
Prospective Cohort Study of Fentanyl Test Strip Use and Distribution in Three States: The Stay Safe Study Protocol and Implementation Recommendations for Researchers
Authors: Childerhose Janet E. , Babineau Denise C. , Caspar Rachel , David James L. , Dzurec Megan E. , El-Bassel Nabila , Fanucchi Laura C. , Gilbert Louisa , Hall Megan E. , Harris Mallory , Linas Beth S. , Marks Katherine E. , Oga Emmanuel , Russo Mary , Vickers-Smith Rachel , Konstan Michael , Fallin-Bennett Amanda , Jackson Rebecca D. , Chandler Redonna K. , Gelberg Kitty , Walsh Sharon L. , Fernandez Soledad , Freisthler Bridget , Lancaster Kathryn E. , Roeber Carter , Villani Jennifer
Published: September 2024

Background
The Stay Safe Study is the first observational prospective cohort study investigating fentanyl test strip (FTS) use by people who use drugs (PWUD) and distribution by harm reduction organizations in three states (Kentucky, New York, and Ohio). The purpose of this paper is to describe the study design, along with implementation success and challenges. A related goal is to provide recommendations and encourage researchers to undertake multi-state and multilevel studies of FTS use and distribution.
Methods
The protocol has one primary, five secondary, and three exploratory objectives. From May-December 2023, the study collected survey, interview, and oral fluid drug test (ODT) data with the primary population of PWUD attending community harm reduction organizations that distribute FTS. We collected survey and interview data with a secondary population of community harm reduction organizations that have a distribution relationship to FTS. There was no intervention and the study did not distribute FTS.
Results
The full study sample was 732 PWUD participants (97.6% of the target) from 1,156 enrolled PWUD participants. Enrolled PWUD participants completed a baseline assessment and at least two of four weekly survey assessments. A subset of participants completed a one-time ODT (n=269) and one-on-one semi-structured interviews (n=120). From the secondary population of 36 harm reduction organizations, employees of 28 organizations (78%) in 22 counties across 3 states completed a web-based survey and employees of 24 organizations (66.7%) completed an interview. Study findings will be presented in subsequent publications.
Conclusion
The study team successfully enrolled a large sample of PWUD and organizational participants in three states, followed a cohort of PWUD participants and generated rich data using three types of instruments. Factors contributing to implementation success include drawing on the community expertise of the parent HEALing Communities Study, selecting incentive amounts that acknowledged the time and expertise of PWUD participants, centralizing survey data collection, and tracking implementation challenges and solutions. Areas of implementation complexity included conducting research on site at community harm reduction organizations, facilitating timely incentive payments, overseeing study staff, and returning ODT results to PWUD participants.
Baseline drug treatments and long-term outcomes in COVID- 19-hospitalized patients: results of the 2020 AUTCOV study
Authors: Graf Alexandra Christine , Reichardt Berthold , Wagenlechner Christine , Krotka Pavla , Traxler-Weidenauer Denise , Mildner Michael , Mascherbauer Julia , Aigner Clemens , Auer Johann , Wendt Ralph , Ankersmit Hendrik Jan
Published: September 2024

Limited data are available on long-term morbidity and mortality after COVID-19 hospitalization. In this population-based study, we investigated the long-term mortality and morbidity after COVID-19 hospitalization and associations with baseline drug treatments. Data were provided on hospitalized COVID-19 patients in 2020 and matched controls by the Austrian Health Insurance Funds. The primary outcome was all-cause mortality. Secondary outcomes were all-cause mortality conditional on COVID-hospital survival and re-hospitalization due to any reason. The median follow-up was 600 days. 22 571 patients aged > 18 years were hospitalized in Austria in 2020 due to COVID-19. The risk of all-cause mortality was significantly higher with polypharmacy. With the exception of the youngest age group (19–40 years), antiepileptics, antipsychotics and the medicament group of iron supplements, erythropoietic stimulating agents, Vitamin B12, and folic acid were significantly associated with a higher risk of death (all p < 0,001). For Non-steroidal anti-inflammatory drugs and other anti-inflammatory drugs, significantly increased survival was observed (all p < 0,001). Patients had a higher drug prescription load than the control population. Long-term mortality and the risk of re-hospitalization due to any reason were also significantly greater in the patients. Antipsychotics are assumed to be an underrecognized medication group linked to worse outcomes after COVID-19 hospitalization.
An Automatic Constructed Subway Construction Safety Risks Transmission Networks: A Pipeline Model Based on Named Entity Recognition and Relation Extraction
Authors: Xu Na , Liang Yanxiang , Chang Hong , Qian Shan , Liu Yao
Published: September 2024

Safety risk management is a critical part during the subway construction. However, conventional methods for risk identification heavily rely on experience from experts and fail to effectively identify the coupled relationship between risk factors and events embedded in accident texts. Consequently, they are unable to provide substantial guidance for subway safety risk management. The research developed a domain entity recognition model for subway construction safety risks based on Bidirectional Long Short-Term Memory Networks with Conditional Random Fields (BiLSTM-CRF) and a domain entity causal relation extraction model based on Convolutional Neural Networks (CNN), with a dataset consisting of 562 instances of subway construction accidents. Constructed models achieved automatically extract safety risk factors, safety events, and their causal relationships from subway accident texts. The results demonstrated that the precision, recall, and F1 scores of MCSR-NER-Model all exceeding 77%. Its performance in the specialized domain named entity recognition with a limited volume of textual data is satisfactory. The MCSR-CE-Model achieved an impressive accuracy, recall, and F1 score of 98.96%, exhibiting excellent performance. Moreover, the extracted entities are normalized and a domain dictionary was developed. Based on the processed entities and relationships processed by the domain dictionary, 533 domain entity causal relation triplets are obtained, facilitating the establishment of a directed and unweighted complex network for subway construction safety risks and a case database. This research successfully converted subway construction accident texts into a causal chain structure of "safety risk factors to risk events," providing detailed categorization of safety risks and events. Concurrently, it revealed the interrelationships and historical statistical patterns among various safety risk factors and categories of risk events through the complex safety risk network. The establishment of the database furnishes project management personnel with effective response measures for historical risk events.
Long Short-Term Memory Networks for Predicting Resilient Modulus of Stabilized Base Material Subject to Wet-Dry Cycles
Authors: Al‑Zubi Mohammad A. , Ahmad Mahmood , Abdullah Shahriar , Khan Beenish Jehan , Qamar Wajeeha , Abdullah Gamil M. S. , González-Lezcano Roberto Alonso , Paul Sonjoy
Published: September 2024

The resilient modulus (MR) of different pavement materials is one of the most important input parameters for the mechanistic-empirical pavement design approach. The dynamic triaxial test is the most often used method for evaluating the MR, although it is expensive, time-consuming, and requires specialized lab facilities. The purpose of this study is to establish a new model based on Long Short-Term Memory (LSTM) networks for predicting the MR of stabilized base materials with various additives during wet-dry cycles (WDC). A laboratory dataset of 704 records has been used using input parameters, including WDC, ratio of calcium oxide to silica, alumina, and ferric oxide compound, Maximum dry density to the optimal moisture content ratio (DMR), deviator stress (σd), and confining stress (σ3). The results demonstrate that the LSTM technique is very accurate, with coefficients of determination of 0.978 and 0.966 for the training and testing datasets, respectively. The LSTM model outperforms other developed models, such as support vector regression and least squares approaches, in the literature. A sensitivity analysis study has determined that the DMR parameter is the most significant factor, while the σd parameter is the least significant factor in predicting the MR of the stabilized base material under WDC. Furthermore, the SHapley Additive exPlanations approach is employed to elucidate the optimal model and examine the impact of its features on the final result.
Cardiovascular Effects of Growth Hormone: Preliminary Study on Oxidative Stress in Adults with Growth Hormone Deficiency
Authors: Kościuszko Maria , Buczyńska Angelika , Wiatr Aleksandra , Jankowska Dorota , Adamska Agnieszka , Siewko Katarzyna , Zaniuk Marcin , Krętowski Adam Jacek , Popławska-Kita Anna
Published: September 2024

Adult growth hormone deficiency (AO-GHD) is associated with increased mortality due to a higher risk of cardiovascular complications. Oxidative stress (OS) diminishes antioxidant capacity, leading to endothelial dysfunction and promoting thrombotic and inflammatory mechanisms. This increases the risk of cardiovascular diseases and metabolic disorders. Imbalances in the synthesis or signaling of endothelin-1 (ET-1) and nitric oxide (NO) are linked to hypertension, atherosclerosis, and heart failure. Additionally, elevated levels of asymmetric dimethylarginine (ADMA), an inhibitor of nitric oxide synthase, contribute to vascular endothelial dysfunction, increased vascular tension, higher blood pressure, and the activation of pro-atherogenic mechanisms. This preliminary study aims to investigate the cardiovascular effects of recombinant human growth hormone (rhGH) therapy in AO-GHD. The findings of this research suggest a potential association between rhGH replacement therapy in AO-GHD patients and a reduction in cardiovascular risk through its impact on ET-1, NO, ADMA concentrations, and OS status markers. These results have the potential to inform the optimization of rhGH replacement therapy protocols, thereby exerting a broader influence on the cardiovascular well-being of individuals undergoing such interventions.
Safety and Efficacy of Mini-percutaneous Nephrolithotomy in Management of Renal Stones in Pediatric Age Group
Authors: Mahmood Sarwar Noori , Said Shakhawan , Mohammed Rawa O. , Jaafar Mzhda Sahib
Published: September 2024

Background
Kidney stones frequently observed in children and teens over the past 20 years.
Objectives
To evaluate the safety and efficacy of mini-percutaneous nephrolithotomy (MPCNL) in managing renal stones in pediatric patients. Patients and
methods
This retrospective case series study included 115 consecutive patients aged < 11 years old who underwent MPCNL at Sulaimani Teaching Hospital and Mercy Medical City, Sulaimaniyah, Iraq, from January 2016 to March 2021. MPCNL was done on all patients through 16–20 Fourteen French (Fr) tracts. The stone-free rate, perioperative complications, tract number, operative time, postoperative hemoglobin change, and hospitalization time were assessed.
Results
The mean patients’ age was 6.53 ± 1.3 years, and the mean stone burden was 2.073 ± 1.03 cm. After a single session of MPCNL, 93.25 ± 0.34 of patients attained a complete stone clearance through a single tract in 109 patients (94%) and two tracts in 6 patients (5.2%). Hospitalization time, operative time, postoperative hemoglobin drop, and perioperative complications were 2.23 ± 0.93 days, 39.26 ± 8.22 minutes, 0.51 ± 0.34 g/dL, and 25.21%, respectively. No major complications (Clavien grade III and IV) were found. Most complications were minor, including Clavien grade I (n = 18, 15.6%) and II (n = 11, 9.56%), which were managed conservatively.
Conclusions
MPCNL is an effective and potentially safe procedure for treating complex renal stones in pediatric patients aged < 11 years, yielding an excellent stone-free rate and acceptable complications.
WITHDRAWN: Structural modelling and probabilistic seismic assessment of existing long-span precast industrial buildings
Authors: CAPACCI LUCA , Lago Bruno Dal
Published: September 2024

The full text of this preprint has been withdrawn by the authors due to author disagreement with the posting of the preprint. Therefore, the authors do not wish this work to be cited as a reference. Questions should be directed to the corresponding author.
Multi-Step Prediction of Greenhouse Temperature and Humidity Based on Temporal Position Attention LSTM
Authors: guo zihao , Feng Lei
Published: September 2024

Changes in the indoor environment of greenhouses significantly impact crop production. These microclimate changes, influenced by various environmental factors, can cause fluctuations in crop yield and quality. Accurate prediction of changes in these environmental factors is essential to preventing adverse impacts. However, greenhouse interiors are multivariable coupled systems with nonlinear, hysteretic and oscillatory behavior, posing challenges for short-term predictions. Addressing this, this study proposes a novel short-term multi-step prediction model for greenhouse microclimate using Temporal Position Attention Long Short-Term Memory (TPA-LSTM) based on position encoding and time sequence. The model uses true past environmental data, including indoor and outdoor air temperature and humidity, sunlight intensity and atmospheric pressure, employing a sliding window strategy with different lengths (30 min, 1 h, 2 h, 4 h) to predict future climate changes accurately in air temperature and humidity from 30 min to 240 min. Compared with the well-known models RNN, LSTM, and GRU, the proposed model achieves higher credibility and lower errors. In the single step prediction, the model with a 2 h sliding window yielded the best results: R2 of 0.992 and RMSE of 0.715°C for air temperature, R2 of 0.983 and RMSE of 2.775% for air humidity. For multi-step predictions of 2, 4, and 8 steps, the model achieved better results than other well-known models. The results demonstrate this model has superior short-term prediction ability for greenhouse microclimate, which significantly reducing prediction errors, enhancing environmental monitoring and early warning, and promoting intelligent greenhouse development and facility agriculture.
Horizontal Bone Augmentation with Simultaneous Implant Placement Using Ridge Splitting with Sticky Bone Versus Onlay Sticky Bone Graft
Authors: Bolot Mohammad YA. , Ghoraba Sahar M. , Badr Ahmed M.
Published: September 2024

Introduction: A variety of bone grafting techniques had been used to augment horizontally deficient alveolar bone ridges to provide a sufficient bone volume to achieve a correct prosthetic 3-dimensional placement of dental implants.
Objectives: to evaluate clinically and radiographically by cone beam computed tomography (CBCT) the amount of horizontal bone gain between two different augmentation techniques for horizontal ridge deficiency with simultaneous implant placement; using piezo-assisted ridge splitting technique with sticky bone graft versus Onlay sticky bone graft in patients who had bilateral posterior edentulous sites in the maxillary ridge.
Materials and methods: Seven patients including a total of 14 sites; 7 sites for each treatment modality. Each patient had bilateral posterior maxillary edentulous areas with horizontal ridge deficiency ranging from 3-5 mm. The augmentation sites were randomly divided into two groups; Piezo-assisted ridge splitting technique with simultaneous implant placement and Onlay sticky bone graft with simultaneous implant placement. Patients were evaluated for clinical parameters, including ridge width using a bone calliper, radiographic assessment of marginal bone width and alveolar bone density using CBCT, clinical attachment loss, plaque index, bleeding on probing and pocket depth. Results were obtained at surgery time, 6 months post-surgery, and 18 months post-surgery.
Results: there was a statistically significant increase in bone width in both groups, Also, bone density was slightly increased at implant and grafting sites at 6- and 18-months follow-ups. Furthermore, both groups showed a statistically significant increase in bone width measured by bone calliper at baseline and at 6 months post-surgically. There was no statistical difference between the two groups' bone gain measurements. No significant changes were observed in PI, BOP, or CAL.
Conclusion: Both surgical techniques provided promising clinical and radiographic outcomes with no statistically significant differences among them.
Faune associated with two giant ants in northern Brazil: Dinoponera gigantea (Perty, 1833) (Ponerinae) and Paraponera clavata (Fabricius, 1775) (Paraponerinae)
Authors: Cruz Anny Kelly Castanhede Fernades , Cruz Charles Darwin Ferreira , Mariano Cléa S.F. , Delabie Jacques H.C. , Castaño-Meneses Gabriela
Published: September 2024

The ant nests are inhabiting by great diversity of organisms. There is few information about the nests of giant ants and their associated fauna. We study the fauna in the nests of Dinoponera gigantea (Ponerinae) and Paraponera clavata (Paraponerinae) in two localities of the state of Maranhão, Brazil. A total of 15 nests were reviewed to D. gigantea and 10 to P. clavata, recorded their associated fauna and number of chambers in each one. The total abundance of organisms recorded in nests of both species were 1833, belonging to 43 families and 30 genera/species. In the nests of D. gigantea nests were recorded 571 organisms (average ± SD = 2.48 ± 4.5 individuals by nest) while to P. clavata nests were 1,262 (2.96 ± 8.5 individuals by nest). The maximum number of chambers recorder in D. gigantea were seven, while in P. clavata were recorded 24 chambers. Insecta represent 46% of the total, Arachnida 38%, Entognatha 14%, and groups as Chilopoda, Clitellata, Diplopoda, Gastropoda and Squamata represented less than 1%. There groups as Squamata were found only in P. clavate nests. The diversity of mites and springtails was high in both species but show differences in composition. The nests or these giant ants area a very important to conservation of diversity of mani groups of myrmecophiles but also to soil fauna.
Understanding the Landscape: A Review of Explainable AI in Healthcare Decision-Making
Authors: Ansari Zulfikar Ali , Tripathi Manish Madhava , Ahmed Rafeeq
Published: September 2024

Breast cancer remains a significant global health concern, impacting millions of women. Early and accurate diagnosis is crucial for improving treatment outcomes and reducing mortality rates. Machine learning (ML) has emerged as a powerful tool for breast cancer prediction, demonstrating its ability to identify complex patterns and relationships in large datasets. This paves the way for efficient collaboration between AI and healthcare professionals. This systematic review explores the diverse machine-learning techniques employed in breast cancer diagnosis. We comprehensively analyse and evaluate the effectiveness of various computational methodologies by synthesising findings from a wide range of peer-reviewed studies. Our analysis highlights the substantial advancements achieved in utilizing machine learning algorithms for breast cancer prediction. However, challenges remain in harnessing the full potential of machine learning for healthcare. These include the need for larger and more diverse datasets, the effective incorporation of imaging data, and the development of interpretable models. While AI offers immense potential for improving healthcare, ensuring transparency, interpretability, and trust is crucial, especially in complex domains like cancer diagnosis. This research emphasizes the importance of Explainable AI (XAI) for enhancing clinical decision-making and building trust between patients and healthcare providers. We advocate for fostering interdisciplinary collaboration among AI researchers, medical professionals, ethicists, and policymakers to ensure the responsible integration of AI in healthcare.
Comparative Morphological and Immunohistochemical Characteristics of the Human Fetal Organs of Zuckerkandl and Adrenal Medulla
Authors: Otlyga Ekaterina , Otlyga Dmitry , Junemann Olga , Krivova Yuliya , Proshchina Alexandra , Kharlamova Anastasia , Gulimova Victoria , Sonin Gleb , Saveliev Sergei
Published: September 2024

The adrenal medulla and organs of Zuckerkandl consist of chromaffin cells that produce, store, and secrete catecholamines. In humans, the adrenal medulla is known to function throughout postnatal life, while the organs of Zuckerkandl degenerate by 2–3 years of postnatal life. Although the history of investigation of chromaffin cells goes back more than a century, little is known about the interaction of the adrenal glands and organs of Zuckerkandl in human fetal development. In the current study, we attempted to compare these two organs using serial sectioning, routine histological staining, and immunohistochemical reactions in human embryos, prefetuses, and fetuses from 8 to 26 gestational weeks. In our study, we used antibodies for tyrosine hydroxylase, dopamine beta-hydroxylase, and phenylethanolamine N-methyltransferase, which are enzymes of catecholamine synthesis, β-III tubulin, and S100. We found two morphological cell types (large and small) in the developing ganglia, organs of Zuckerkandl, and adrenal medulla and two migration patterns of large cells and small cells from the developing paraganglia to the adrenal anlage. We determined the immunohistochemical characteristics of these migrating cells. We also determined that 12 gestational weeks was the age of the first appearance of phenylethanolamine N-methyltransferase reactivity in developing chromaffin cells, which is important data in the light of the controversial glucocorticoid theory of phenylethanolamine N-methyltransferase induction in humans.
Thirty-year changes in burden for refraction disorders in China, Japan, Korea and Singapore: a jointly prevention perspective analysis
Authors: Mao Xiuyu , Jia Wenchang , Ji Shunmei , Wu Lei , Chen Binghong , Li Xiaopan
Published: September 2024

Background
Refractive disorders are the primary causes of visual impairment; their impact and prevalence vary greatly throughout age groups and geographical locations. This study analyzes trends in the burden of refractive disorders from 1990 to 2021 and projects future trends to 2050, focusing on five Asian regions and different socio-demographic index (SDI) levels.
Methods
Data on the prevalence and YLDs of refractive disorders were obtained from the Global Burden of Disease Study 2021. Age-standardised rates were calculated for regions with different SDI levels and five Asian countries or regions including China (mainland), Taiwan (province of China), Japan, Republic of Korea, and Singapore. Trends were analyzed using jointpoint regression, and projections were made to 2050.
Results
From 1990 to 2021, the global age-standardised prevalence rate (ASPR) of refractive disorders decreased by 6.5%. The most significant declines were observed in low and low-middle SDI regions (11.8% and 20%, respectively). Among the Asian regions, Taiwan (province of China) showed the greatest decrease in both ASPR (10.1%) and age-standardized YLDs (ASYLDs) (15.2%). Projections indicate that the prevalence and impact of refractive disorders in Japan and Taiwan are expected to surpass those in mainland China by the 2030s.
Conclusion
The burden of refractive disorders varies considerably across regions and age groups, with socioeconomic factors playing a crucial role. Targeted interventions and public health initiatives are needed to address this growing concern, particularly in aging populations and regions with limited access to eye care services.
Improved catalytic stability of immobilized Candida antarctic lipase B on macroporous resin with organic polymer coating for biodiesel production
Authors: Liu Jiale , Zhao Shufan , Wei Wan , Yu Shupeng , Wang Zhao , Zheng Jianyong
Published: September 2024

Lipase is one of the most widely studied and applied biocatalysts. Due to the high enzyme leakage rate of the immobilization method of physical adsorption, we propose a new lipase immobilization method, which based on the combination of macroporous resin adsorption and organic polymer coating. The immobilized Candida antarctic lipase B (CALB@resin-CAB) was prepared by combining the macroporous resin adsorption with cellulose acetate butyrate coating, and its structure was characterized by various analytic methods. Immobilized lipase was applied for biodiesel production using acidified palm oil as the starting material, the conversion rate achieved as high as 98.5% in two steps. Furthermore, immobilized lipase displayed satisfactory stability and reusability in biodiesel production. When the aforementioned reaction was carried out in a continuous flow packed-bed system, the yield of biodiesel was 94.8% and space-time yield was 2.88 g/(mL∙h). CALB@resin-CAB showed high catalytic activity and stability, which has good potential for industrial application in the field of oil processing.
Artificial Intelligence Driven Integrated Wireless Sensor Network, Industrial Ethernet, and Non-Orthogonal Multiple Access for Secure Nuclear Power Plants
Authors: Aboshosha Ashraf
Published: September 2024

Wireless Sensor Networks (WSNs) have recently garnered attention for various applications in Nuclear Power Plants (NPPs), such as radiation monitoring, data acquisition, instrumentation, control, and fault diagnosis. This study suggests an integrated solution for NPP's WSN by combining WSN, Industrial Ethernet (IE), and Non-Orthogonal Multiple Access (NOMA) to enhance performance, prolong lifespan, and improve security. It also incorporates Artificial Intelligence (AI)-driven decision making to speed up routing of the NPP's WSN in both indoor and outdoor environments. This research work proposes the development of an international radiation monitoring network for robust international nuclear Defense in Depth (DiD). Evaluation with various simulated WSNs has shown the viability of the proposed approach, effectively monitoring data even in scenarios with similar response patterns across multiple process variables.
Stage-based Neural Network for Reflow Profile Prediction and Reflow Recipe Optimization for Quality and Energy Saving
Authors: Zhang Zhenxuan , Li Yuanyuan , Yoon Sangwon , Won Daehan
Published: September 2024

During the reflow process, solder joints are formed on the boards with the placed components, so the temperature settings in the reflow oven chamber are vital to the quality of the PCB. Inappropriate profiles cause various defects such as cracks, bridging, delamination, etc. Solder paste manufacturers have generally provided the ideal thermal profile (i.e., target profile), and PCB manufacturers have attempted to meet the given profile by fine-tuning the oven’s recipe. The conventional method tunes the recipe to gather thermal data with a thermal measurement device. It adjusts the profile, which relies on the trial-and-error method which takes much time and effort. This paper proposes (1) a recipe initialization method for determining the initial recipe for collecting training data, (2) a stage-based (ramp, soak, and reflow) input data segmentation method for data preprocessing, (3) a backpropagation neural network, (BPNN) model for predicting the required zone temperature to reduce the gap between the actual processing profile and the target profile, (4) a mixed-integer linear programming (MILP) algorithm for generates the optimal recipe to minimize the temperature settings. This paper aims to enable non-contact prediction of required air temperature from one experiment. The MILP optimization model utilized the constraints of the upper and lower bounds obtained from the prediction result. The model has been cross-validated with different initial recipes and different target profiles. As a result, within 10 minutes of starting the experiment, the generated optimal recipe improved the fitness to the targeted profile by 4.2%, which resulted in 99% and, in the meanwhile, lowered the energy cost by 23%.
Reaserch of the surface residual stress of TC4 titanium alloy under longitudinal-torsional ultrasonic grinding and nanofluid minimum quantity lubrication
Authors: Yan Yanyan , Zhang Qipeng , Ma Qianli , Yuan Dengke
Published: September 2024

The machining difficulty of TC4 titanium alloy is higher than that of other metal alloys because of its poor thermal conductivity, high chemical reactivity and so on. Under this background, a system of longitudinal-torsional ultrasonic grinding and nanofluid minimum quantity lubrication (LTUG&NMQL) was established to achieve the high-quality machining of titanium alloy, and its special machining mechanism is firstly analyzed, then the surface residual stress (SRS) model under LTUG&NMQL was built. The theoretical analysis shows that the total residual stress is related to the grinding arc length of single abrasive grain in longitudinal-torsional ultrasonic grinding (lc), the average contact area (sm), the friction coefficient (µ) and the heat flux density of workpiece (qw), especially, under LTUG&NMQL condition, lc is changed by ultrasonic vibration, and sm, µ and qw are altered by nanofluid minimum quantity lubrication. Subsequently, the SRS values are different from those of common grinding. Finally, the grinding experiments were carried out to investigate the influences of LTUG&NMQL on the SRC of titanium alloy, and the experimental results showed that the surface compressive residual stress of titanium alloy under LTUG&NMQL was higher than that under common grinding and longitudinal-torsional ultrasonic grinding when the same machining parameters were used, and it increased with the flow rates of nanofluids and the ultrasonic amplitudes, which showed that LTUG&NMQL may improve the service performance of the parts. This study provides a theoretical foundation and technical support for the high-performance machining of TC4 titanium alloy.
Evaluation criteria and dehydration method for EPB shield spoil in sandy gravel– mudstone composite stratum
Authors: Zhao Dongping , Wang Feng , Peng Yuelei , Tang Weichao , Xiao Li , Zhang Wei
Published: September 2024

Shield tunnels in composite strata of mudstone and pebble produce a large amount of high-water-content spoil during excavation using earth pressure balance machines. This spoil not only has high transportation costs but also poses environmental pollution. We evaluated the moisture content, liquid and plastic limits of the moisture content, and permeability coefficient of the shield slag in the shield tunnel project of the first phase of the Chengdu Metro Line 30. Shield spoil dehydration tests were performed in gravel–mudstone composite strata, and a spoil dehydration evaluation method using slump and fluidity as the indicators was proposed. The results of the self-weight dehydration test showed that the moisture content of the spoil was reduced by approximately 7% after 24 h and the dehydration effect on the spoil was poor. The results of a vacuum–electroosmotic dehydration orthogonal test showed that by controlling parameters such as voltage and electrode spacing, the moisture content of the spoil can be reduced to a value close to the liquid-limit moisture content. The fluidity and slump of the spoil after dehydration meet the requisite standards, indicating the potential for market application of this method.
Coal permeability evolution under coupled mining disturbance and gas extraction conditions: an experimental study
Authors: Zhang Lei , Kan Zi-Hao , Liu Xinyuan , Wang Chen , Hao Dingyi , Ye Zhiwei
Published: September 2024

A simplified stress path was designed based on decompression mining to explore coal seam permeability variation during stress relief gas extraction in protective layers. This involved axial, confining, and pore stress to simulate coal seamstress during mining and pore pressure during gas extraction. Experiments were conducted on intact and fractured coal samples from Huainan using gas flow and displacement testing equipment. Key findings include: The first unloading cycle significantly impacted fracture volume, with vertically fractured coal showing the greatest variation, followed by horizontally fractured and intact samples, with reductions of 29, 23, 21, and 20%, respectively. Irreversible permeability loss rate is directly proportional to porosity. Both intact and fractured samples showed a porosity decrease followed by an increase, with the third loading/unloading cycle having the greatest impact. As pore pressure decreases, its influence on permeability is greater in fractured samples than in intact samples. The correlation between pore pressure and permeability is stronger in fractured samples. With the increased number of cycles, intact samples' stress sensitivity to pore pressure increases, while that of fractured samples decreases. After three cycles, new fractures develop in both intact and fractured samples, enhancing gas extraction efficiency.
Beyond boundaries - genetic implications of urbanisation and isolation in eastern grey kangaroos (Macropus giganteus)
Authors: Brunton Elizabeth Ann , Levengood Alexis L , Brunton Aaron James , Clarke Neil , Coulson Graeme , Wimpenny Claire , Conroy Gabriel
Published: September 2024

Understanding the long-term influences that urbanisation and associated habitat fragmentation can have on wildlife species is increasingly important for biodiversity conservation. Habitat fragmentation and subsequent isolation of previously connected populations can lead to smaller populations that are more likely to experience loss of genetic diversity. However, there is still a paucity of research directed at the genetic implications for species exposed to urbanisation. Eastern grey kangaroos (Macropus giganteus) are large macropodid marsupials that occur across a vast range on the eastern coast of Australia, inhabiting landscapes often subject to processes of habitat fragmentation and urbanisation. Using single nucleotide polymorphism (SNP) data obtained from scat and tissue samples, we compared genetic characteristics of urban and non-urban kangaroo populations across three study regions. We assessed the influence of habitat isolation characteristics on genetic diversity and relatedness of kangaroos at 18 study sites within these regions. On average, urban populations did not exhibit lower genetic diversity than those in less built-up areas (p > 0.05, Urban mean HO = 0.196, Non-urban mean HO = 0.188), but populations that were fully isolated by physical structures (i.e., roads, buildings and fences) had lower genetic diversity and higher rates of inbreeding. Significant regional differences were also found in the kangaroo population genetic characteristics. This study provides important insights into how attributes of complex and expanding urban landscapes can impact the genetics of large terrestrial mammals and has implications for guiding effective urban planning and management practices at an appropriate spatial scale.
Precision Dosing Cylinder Gluing Operations Using Model Predictive Control-Enhanced Reinforcement Learning
Authors: Wu Liangshun , Zhu Huibiao , Liu Qinyuan , Ying Rendong , Zhang Bin , Qu Junsuo
Published: September 2024

This paper presents the development of an advanced servo system for gluing operations, which integrates a dosing cylinder enhanced by reinforcement learning algorithms to optimize efficiency and accuracy. The system consists of an upper computer, a programmable logic controller (PLC), a main controller (featuring a core board and an IO board), and a dosing cylinder equipped with a servo motor and a glue gun. A comprehensive system model was developed by 1 analyzing the interactions among mechanical, hydraulic, and servo motor subsystems. The implementation of an enhanced Deep Deterministic Policy Gradient (DDPG) reinforcement learning algorithm, augmented with Model Predictive Control (MPC), enables precise control over voltage inputs and glue gun temperature adjustments. The MPC component predicts future states of the system based on the current state and actions, refining the action selection process by considering the long-term effects of actions. Rigorous simulation testing of the enhanced DDPG algorithm, alongside other algorithms, in configurations involving single and dual cylinder setups, validates its effectiveness, demonstrating significant enhancements in the automated control of the gluing process. The real-world experimental results indicate high positioning accuracy, consistent glue dispensing , and overall stability, making this system suitable for industrial applications requiring precise and reliable gluing.
Rising Tides, Sinking Crops: Assessing the Impact of Extreme Sea Level Rise on Coastal Agriculture in Europe and North Africa
Authors: Martellozzo Federico , Vaglie Matteo Dalle , Randelli Filippo , Falaguasta Carolina , Tongeren Pim van , Negacz Katarzyna , Bruning Bas , Vellinga Pier
Published: September 2024

The accelerating impact of climate change on sea level rise (SLR) has intensified the examination of its effects on coastal regions. This study focuses on Extreme Sea Level Rise (ESLR) and its potential impacts on Europe and North Africa up to 2050, in particular for agriculture. Utilising Joint Research Centre (JRC) Global Extreme Sea Level projections and Copernicus GLO30 Digital Terrain Models (DTM), we mapped areas vulnerable to ESLR under Representative Concentration Pathway (RCP) scenarios 4.5 and 8.5. Through a topological approach, we generated spatially explicit maps of at-risk regions in the Mediterranean basin and northern coastal EU, overlaying them with data from FAO on crop locations, yields, and values (GAEZ). This method allowed us to estimate the magnitude of ESLR's impact on local agricultural systems. Findings reveal that ESLR can severely affect coastal agriculture, suggesting significant potential agricultural losses, impacting food security and economic stability. This research underscores the urgent need for adaptive strategies, including saline agriculture, to mitigate ESLR impacts.
The evolution of long-range hunting with stone-tipped weapons during the Afrotropic Middle Stone Age: A testable framework based on tip cross-sectional area
Authors: Sahle Yonatan , Lombard Marlize
Published: September 2024

In the Afrotropic biogeographic realm, with its diverse and high-density mammal population, early humans may have been hunting with stone-tipped weapons since ~ 500 000 years ago. Being able to hunt effectively from a distance has several important adaptive advantages. Yet, until now, African long-range javelin hunting remained unexplored as intermediate between short/medium-range, hand-delivered and long-range, mechanically projected weapons. Insights gained from a new Afrotropic comparative dataset with 950 weapon tips of known use – including several javelin types – provide a contextually appropriate middle-range tool for assessing the probable effective hunting ranges of Middle Stone Age points. We use a novel application of the ballistically relevant tip cross-sectional area (TCSA) statistic to define contact, short-, medium-, long- and maximum-range hunting and discuss the adaptive advantages for each. The approach is applied to suggest developments and variations in the best-fit hunting ranges of 5597 stone points from 62 Middle Stone Age Afrotropic assemblages. By aligning our results with the Marine Isotope Stage (MIS) record we hypothesize that long-range hunting with stone-tipped weapons at ~ 20–30 m was probably not practiced by ≥ MIS 8, and that experimentation with long-range javelins – similar to those used by contemporary Ethiopian hunters – over this distance may have started during MIS 6, becoming part of the everyday Afrotropic hunting arsenal by the end of MIS 5.