bluuebunny/crossref_metadata_2025 huggingface dataset:
Trends in surgical management of spinal metastases in a Singaporean tertiary referral center: a 17-year retrospective review
Authors: Tan Jiong Hao Jonathan , Hallinan James Thomas Patrick Decourcy , Lee Renick , Chan Yiong Huak , Tan Tuan Hao , Ang Shi Wei , Tan Le Tian Isaac , Tan Joelle Hwee Inn , Sin Qinxiang Shant , Hey Dennis Hwee Weng , Lau Leok Lim , Thambiah Joseph , Wong Hee Kit , Liu Gabriel , Kumar Naresh
Published: November 2023

Introduction

Surgical treatment is increasingly the treatment of choice in cancer patients with epidural spinal cord compression and spinal instability. There has also been an evolution in surgical treatment with the advent of minimally invasive surgical (MIS) techniques and separation surgery. This paper aims to investigate the changes in epidemiology, surgical technique, outcomes and complications in the last 17 years in a tertiary referral center in Singapore.

Methods

This is a retrospective study of 383 patients with surgically treated spinal metastases treated between January 2005 to January 2022. Patients were divided into 3 groups, patients treated between 2005 – 2010, 2011-2016, and 2017- 2021. Demographic, oncological, surgical, patient outcome and survival data were collected. Statistical analysis with univariate analysis was performed to compare the groups.

Results

There was an increase in surgical treatment (87 vs 105 vs 191). Lung, Breast and prostate cancer were the most common tumor types respectively. There was a significant increase in MIS(p<0.001) and Separation surgery (p<0.001). There was also a significant decrease in mean blood loss (1061ml vs 664 ml vs 594ml) (p<0.001) and total transfusion (562ml vs 349ml vs 239ml) (p<0.001). Group 3 patients were more likely to have improved or normal neurology (p=<0.001) and independent ambulatory status(p=0.012). There was no significant change in overall survival.

Conclusion

There has been a significant change in our surgical practice with decreased blood loss, transfusion and improved neurological and functional outcomes. Patients should be managed in a multidisciplinary manner and surgical treatment should be recommended when indicated.
Seasonal variation in telomerase activity and telomere dynamics in a hibernating rodent, the garden dormouse (Eliomys quercinus)
Authors: Galindo-Lalana Carlos , Hoelzl Franz , Zahn Sandrine , Habold Caroline , Cornils Jessica S. , Giroud Sylvain , Smith Steve
Published: November 2023

Telomere dynamics in hibernating species are known to reflect seasonal changes in somatic maintenance. Throughout hibernation, the periodic states of rewarming, known as inter-bout euthermia or arousals, are associated with high metabolic costs including shortening of telomeres. In the active season, if high energetic resources are available, telomere length can be restored in preparation for the upcoming winter. The mechanism for telomere elongation has not been clearly demonstrated, although the action of the ribonucleoprotein complex, telomerase, has been implicated in many species. Here we tested for levels of telomerase activity in the garden dormouse (Eliomys quercinus) at different seasonal time points throughout the year and across ages from liver tissues of male juveniles to adults. We found that telomerase is active at high levels across seasons (during torpor and inter-bout euthermia, plus in the active season) but that there was a substantial decrease in activity in the month prior to hibernation. Telomerase levels were consistent across age groups and were independent of feeding regime and time of birth (early or late born). The changes in activity levels that we detected were broadly associated with changes in telomere lengths measured in the same tissues. We hypothesise that i) telomerase is the mechanism used by garden dormice for maintenance of telomeres and that ii) activity is kept at high levels throughout the year until pre-hibernation when resources are diverted to increasing fat reserves for overwintering. We found no evidence for a decrease in telomerase activity with age or a final increase in telomere length which has been detected in other hibernating rodents.
Resources of emotional resilience and its mediating role in teachers’ well-being and intention to leave
Authors: Bagdžiūnienė Dalia , Kazlauskienė Aušra , Nasvytienė Dalia , Sakadolskis Emilija
Published: November 2023

The continuing attention of scholars and practitioners to the teaching profession, teachers and teaching is based above all on the fact that societal progress is impossible without an effective education system. Teachers are the “soft” dynamic, and at the same time, a driving force in this constantly changing system, and research into the prerequisites for their effective performance requires constant attention. In this study, the main phenomenon under analysis is the emotional resilience of teachers–the internal capacity to adapt, manage or cope with emotionally demanding situations. The purpose was to investigate work-related and personal resources that contribute to teachers’ emotional resilience and its role in the links between resources, teacher well-being, and the intention to leave. Data were collected using convenience sampling and included 522 teachers working in Lithuanian primary and secondary schools. An online self-administered questionnaire consisted of scales that assessed teachers’ job resources, self-efficacy, well-being, and intention to leave. The research revealed that perceived workplace characteristics – performance feedback, autonomy, social support, and opportunities for professional growth–along with self-efficacy were positively related and predicted teacher emotional resilience. Emotional resilience was found to be a direct positive predictor of teacher well-being along with job resources and self-efficacy and have a mediating effect on the relationships between work-related resources and self-efficacy as independent variables and teacher wellbeing as a dependent variable. Contrary to well-being is teachers’ intention to leave a school, which is usually an undesirable outcome for an organization. The study revealed that this intention is negatively affected by job resources and self-efficacy, however emotional resilience did not impact teachers’ intention to quit. Based on the results, the article outlines avenues for further research and provides implications for strengthening teachers’ emotional resilience.
What’s in store for females after breaking the glass ceiling? Evidence from the Chinese audit market
Authors: Cheng Hanxiu , Wang Jie
Published: November 2023

Given that female auditors’ representation in the audit market has averagely caught up to that of males, yet remains insufficient at the partner level, it is imperative to investigate gender discrimination in public accounting firms. Using data from the Chinese audit market, this paper analyzes the glass ceiling phenomenon faced by females as they aspire to promotion to partner positions. It also explores the professional barriers that may impede their career progression post-promotion. The findings illuminate that the opportunities for female promotion to partner positions are notably lower than for males. Furthermore, after their elevation to partner roles, females are more likely to be allocated to clients grappling with financial distress and high-risk situations. In contrast, opportunities to engage with auditing important clients are diminished, particularly within male-dominated audit firms. Additionally, the study reveals that female promotion to partner positions heightens their prospects for assuming the lead auditor role in audit projects. However, this phenomenon predominantly materializes within audit firms characterized by a higher proportion of female auditors. Instead, females face more significant challenges in garnering recognition within male-dominated audit firms. Lastly, the research examines investor reactions to female promotion to partner, revealing a generally negative response. In summary, this study contributes to a comprehensive exploration of gender discrimination within the public accounting firms, shedding light on women’s career development challenges after breaking the glass ceiling.
Non-Parametric Model-Based Estimation of the Effective Reproduction Number for SARS-CoV-2
Authors: Hermes Jacques , Rosenblatt Marcus , Tönsing Christian , Timmer Jens
Published: November 2023

Describing viral outbreaks, such as the COVID-19 pandemic, often involves employing compartmental models composed of ordinary differential equation (ODE) systems. Estimating the parameter values for these ODE models is crucial and relies on accessible data. To accurately represent realistic pandemic scenarios with diverse situations, it is necessary to consider model parameters as time dependent. However, estimating such time-dependent parameters, like transition rates in compartmental models, is notoriously challenging due to the unknown function class of these parameters. In this study, we propose a novel approach by using an Augmented Kalman Smoother (AKS) combined with an Expectation-Maximization (EM) algorithm to simultaneously estimate all time-dependent parameters in an SIRD compartmental model. Our approach can be applied to general ODE systems with time-varying parameters, requiring no prior knowledge of model parameters or additional assumptions on the function class of the ODE time dependencies. A key advantage of our method compared to other methods is that it does not require assumptions about the parameterization of the serial interval distribution for estimating SIRD model parameters. Applying our approach to COVID-19 data in Germany, we adequately describe time-series data with strong fluctuations and multiple waves, obtaining non-parametric model-based time-course estimates for the effective reproduction number.
Ship Detection Algorithm Based on YOLOv5 Network Improved with Lightweight Convolution and Attention Mechanism
Authors: Wang Langyu , Zhang Yan , Lin Yahong , Yan Shuai , Xu Yuanyuan , Sun Bo
Published: November 2023

Aiming at the problem of insufficient feature extraction, low precision, and recall in sea surface ship detection, a YOLOv5 algorithm based on lightweight convolution and attention mechanism is proposed. We combine the receptive field enhancement module (REF) with the spatial pyramid rapid pooling module to retain richer semantic information and expand the sensory field. The slim-neck module based on a lightweight convolution (GSConv) is added to the neck section, to achieve greater computational cost-effectiveness of the detector. And, to lift the model’s performance and focus on positional information, we added the coordinate attention mechanism. Finally, the loss function CIoU is replaced by SIoU. Experimental results using the seaShips dataset show that compared with the original YOLOv5 algorithm, the improved YOLOv5 algorithm has certain improvements in model evaluation indexes, while the number of parameters in the model does not increase significantly, and the detection speed also meets the requirements of sea surface ship detection.
An Optimized Pressure-Based Method for Thrust Vectoring Angle Estimation
Authors: Shi Nanxing , Gu Yunsong , Wu Tingting , Zhou Yuhang , Wang Yi , Deng Shuai
Published: November 2023

This research developed a pressure-based thrust vectoring angle estimation method for fluidic thrust vectoring nozzles. This method can accurately estimate the real-time in-flight thrust vectoring angle using only wall pressure information on the inner surface of the nozzle. We proposed an algorithm to calculate the thrust vectoring angle from the wall pressure inside the nozzle. Non-dominated sorting genetic algorithm II was applied to find the optimal sensor arrays and reduce the wall pressure sensor quantity. Synchronous force and wall pressure measurement experiments were carried out to verify the accuracy and real-time response of the pressure-based thrust vectoring angle estimation method. The results showed that accurate estimation of the thrust vectoring angle can be achieved with a minimum of three pressure sensors. The pressure-based thrust vectoring angle estimation method proposed in this study has a good prospect for engineering applications; it is capable of accurate real-time in-flight monitoring of the thrust vectoring angle. This method is important and indispensable for the closed-loop feedback control and aircraft attitude control of fluidic thrust vectoring control technology.
The Role of Rural Credit in Agricultural Technology Adoption: The Case of Boro Rice Farming in Bangladesh
Authors: Rayhan Shah Johir , Rahman Md. Sadique , Lyu Kaiyu
Published: November 2023

Rice agriculture provides millions of households with a steady source of income and employment. However, for small and marginal farmers, the exorbitant cost of production inputs presents a formidable obstacle in their pursuit of acquiring it. Credit constraints are a significant impediment to the adoption of agricultural technologies. Therefore, this paper identifies the determinant of access to rural credit and its impact on Boro rice production technology adoption in Bangladesh using cross-sectional data. The study employed probit regression, propensity score matching (PSM), inverse probability weighting (IPW), and inverse probability weighted regression adjustment (IPWRA) techniques. The findings indicate that age, family size, working members, and involvement in safety net programs negatively and significantly influence access to rural credit, while earning persons in the family, literacy, rice farming experience, remittance, and total income positively influence access to rural credit. The positive and significant ATT values suggested that access to rural credit has a positive and significant effect on technology adoption and the level of technology use. It was also found that access to rural credit has a heterogeneous effect. In particular, non-government organization (NGO) credit has a more significant impact on technology adoption than formal bank credit. Access to credit and the adoption of agricultural technologies can be greatly improved with the help of a location-specific rural credit policy and strong monitoring from the formal banking sector.
Deep Learning Tools for the Automatic Measurement of Coverage Area of Water-Based Pesticide Surfactant Formulation on Plant Leaves
Authors: Grazioso Fabio , Atsapina Anzhelika Aleksandrovna , Obaeed Gardoon Lukman Obaeed , Ivanova Natalia Anatolievna
Published: November 2023

A method to efficiently and quantitatively study the delivery of a pesticide-surfactant formulation in a water solution to plant leaves is presented. The methodology of measurement of the surface of the leaf wet area is used instead of the more problematic measurement of the contact angle. A method based on a Deep Learning model was used to automatically measure the wet area of cucumber leaves by processing the frames of video footage. We have individuated an existing Deep Learning model, called HED-UNet, reported in the literature for other applications, and we have applied it to this different task with a minor modification. The model was selected because it combines edge detection with image segmentation, which is what is needed for the task at hand. This novel application of the HED-UNet model proves effective, and opens a wide range of new applications, the one presented here being just a first example. We present the measurement technique, some details of the Deep Learning model, its training procedure and its image segmentation performance. We report the results of the wet area surface measurement as a function of the concentration of a surfactant in the pesticide solution, which helps to plan the surfactant concentration. It can be concluded that the most effective concentration is the highest in the range tested, which is 11.25 times the CMC concentration. Moreover, a validation error on the Deep Learning model, as low as 0.012 is obtained, which leads to the conclusion that the chosen Deep Learning model can be effectively used to automatically measure the wet area on leaves.
Semi-Supervised Semantic Segmentation-Based Remote Sensing Identification Method for Winter Wheat Planting Area Extraction
Authors: Zhang Mingmei , Xue Yongan , Zhan Yuanyuan , Zhao Jinling
Published: November 2023

To address the cost issue associated with pixel-level image annotation in fully supervised semantic segmentation, a method based on semi-supervised semantic segmentation is proposed for extracting winter wheat planting areas. This approach utilizes self-training with pseudo-labels to learn from a small set of images with pixel-level annotations and a large set of unlabeled images, thereby achieving the extraction. In the constructed initial dataset, a random sampling strategy is employed to select 1/16, 1/8, 1/4, and 1/2 proportions of labeled data. Furthermore, in conjunction with the concept of consistency regularization, strong data augmentation techniques are applied to the unlabeled images, surpassing classical methods such as cropping and rotation to construct a semi-supervised model. This effectively alleviates overfitting caused by noisy labels. By comparing the prediction results of different proportions of labeled data using SegNet, DeepLabv3+, and U-Net, it is determined that the U-Net network model yields the best extraction performance. Moreover, the evaluation metrics MPA and MIoU demonstrate varying degrees of improvement for semi-supervised semantic segmentation compared to fully supervised semantic segmentation. Notably, the U-Net model trained with 1/16 labeled data outperforms the models trained with 1/8, 1/4, and 1/2 labeled data, achieving MPA and MIoU scores of 81.63%, 73.31%, 82.50%, and 76.01%, respectively. This method provides valuable insights for extracting winter wheat planting areas in scenarios with limited labeled data.
Varietal Differences in the Root Systems of Rice (Oryza sativa L.) under Drip Irrigation with Plastic Film Mulch
Authors: Wang Junfa , Fawibe Oluwasegun Olamide , Isoda Akihiro
Published: November 2023

With the escalating water scarcity in agriculture, a novel water-saving technique has emerged: drip irrigation with plastic film mulch (DI). Root function is crucial for sustaining rice production, and understanding its response to DI is essential. However, few studies have evaluated root systems in rice varietals and examined which kind of root system contributes to improving rice grain yield and water productivity in DI. If varietal differences of root reactions for water regimes were made clear, it might be more effective to find suitable varieties for DI and to improve grain yield in the DI system. To fill this knowledge gap, we conducted a two-year field experiment comparing two irrigation systems: continuous flooding (CF) and DI. We analyzed their effectiveness with four rice cultivars, including upland, F1 lowland, animal feed lowland, and lowland cultivars. Vertical root distribution, root bleeding rate, photosynthetic-associated parameters, water productivity, and yield performance were analyzed. In our study, the average grain yield of cultivars in the DI system (6.4 t/ha) was equivalent to those in the CF system (6.6 t/ha). The average water productivity under DI (0.34–0.75 kg m−3) demonstrated significant water-saving potential, saving approximately 35% of the total water supplied, resulting in higher water productivity compared to CF (0.27–0.51 kg m−3). Among the cultivars, the deep root weight of the upland cultivar significantly increased by 51% under DI compared to CF. The deep root ratio was positively correlated with the transpiration rate, grain yield, and water productivity, suggesting its contribution to high transpiration, thus maintaining a high carbon assimilation rate that results in high yield and water productivity. Therefore, deep roots are a notable trait corresponding to high yield under DI, and should be considered for the development of rice growth models for DI and the breeding of aerobic-adapted cultivars.
Comparison of Estimated Wild Giant Anteater (Myrmecopahaga tridactyla Linnaeus, 1758) Diets with Commercial Diets for Insectivores: Implications for Anteater Health
Authors: Bissell Heidi , Alves Mario H. , Yogui Débora R. , Woc Colburn Margarita , Desbiez Arnaud L. J.
Published: November 2023

Using the stomach contents of 24 wild road-killed giant anteaters as proxies for their diet, we found that estimated wild diets were much lower in calcium (about ten times less) and phosphorus compared with manufactured feeds commonly fed to anteaters under human care. Indicators of soil consumption, such as ash, iron, and manganese were higher in the stomach contents than in either wild termites or manufactured diets, likely due to high levels of soil ingestion during feeding in the wild. Protein and fat levels in insects, stomach contents, and commercial diets all met carnivore recommendations. Both giant anteaters and tamanduas in managed care often develop hypercalcemia, perhaps because these taxa have an enhanced ability to retain calcium allowing them to survive on such low calcium diets. Results from this study indicate that, for anteaters in managed care, it is important to keep dietary calcium and vitamins D and K within recommended levels to prevent nutritional diseases such as hyper- and hypocalcemia and vitamin K deficiency.
Genomic Analysis Reveals Candidate Genes Underlying Sex-Linked Eyelid Coloboma, Feather Color Traits, and Climatic Adaptation in Huoyan Geese
Authors: Wen Junhui , Yu Jincheng , Zhang Li , Li Haiying , Wang Huie , Gu Hongchang , Zhao Xiurong , Zhang Xinye , Ren Xufang , Wang Gang , Chen Anqi , Qu Lujiang
Published: November 2023

Driven by natural and artificial selection, the domestic Huoyan geese from Northern China have gradually generated specific phenotypes and climatic adaptations. To understand the genetic basis of the two specific phenotypes that are sex linked, including upper eyelid coloboma and gosling feather color, as well as the climatic adaptations of the Huoyan goose, which can contribute to the artificial selection and breeding of geese. We selected Huoyan geese and nine Southern Chinese goose breeds and identified their divergence on the genomic level. Using selective sweep analysis, we found that PTPRM on chromosome Z influences the upper eyelid coloboma phenotype of the Huoyan goose, and TYRP1 is a plausible candidate gene for the Huoyan gosling feather color. We obtained a number of genes related to cold adaptation in Huoyan geese, mainly involved in physiological functions such as metabolism, angiogenesis contraction and circulatory system, apoptosis, immunity, stress, and neural system. The most interesting candidates for cold adaptation are PIP5K1B and NMNAT3 that are associated with energy metabolism and stress. We also obtained some genes related to heat adaptation, including AGTPBP1, associated with neurology; GDA, associated with skin pigmentation; and NAA35, associated with apoptosis. These findings deepen our understanding of the genetics of specific phenotypes and climate adaptation in local geese and provide insights for the selection of goose breeds.
Genomic Selection Using Single-Step Genomic BLUP on the Number of Services per Conception Trait in Thai–Holstein Crossbreeds
Authors: Boonkum Wuttigrai , Chankitisakul Vibuntita , Duangjinda Monchai , Buaban Sayan , Sumreddee Pattarapol , Sungkhapreecha Piriyaporn
Published: November 2023

Reproductive traits are important traits that directly affect a farmer’s income and are difficult to improve upon using traditional genetic methods. Therefore, there is a need to consider new options for increasing the accuracy of the genetic selection of dairy cows. The objective of this study was to compare the genetic methods of the traditional BLUP and ssGBLUP techniques in terms of the estimated genetic parameters and accuracy of the estimated breeding values. The data comprised 101,331 services per conception (NSPC) records from 54,027 Thai–Holstein crossbred cows, 109,233 pedigree data, and 770 genotyped animals. A Bayesian analysis via threshold Gibbs sampling was used to analyze the estimated variance components and genetic parameters. The results showed that the means of the NSPC data were 2.21, 2.31, and 2.42 for less than 87.5% for Holstein genetics (breed group; BG1), 87.5 to 93.6% for Holstein genetics (BG2), and greater than 93.7% for Holstein genetics (BG3), respectively. The estimated heritability values were 0.038 and 0.051, and the repeatability values were 0.149 and 0.157 for the traditional BLUP and ssGBLUP methods, respectively. The accuracy of the estimated breeding values from the ssGBLUP method was higher than that from the traditional BLUP method, ranging from 6.05 to 17.69%, depending on the dataset, especially in the top 20% of the bull dataset had the highest values. In conclusion, the ssGBLUP method could improve the heritability value and accuracy of the breeding values compared with the traditional BLUP method. Therefore, switching from traditional methods to the ssGBLUP method for the Thai dairy cattle breeding program is a viable option.
The Tibetan Antelope Population Depends on Lakes on the Tibetan Plateau
Authors: Zhang Li , Yan Lingyan , Kou Xiaojun , Ouyang Zhiyun
Published: November 2023

The influence of freshwater ecosystems on terrestrial taxa in high-altitude regions with challenging access, such as the Tibetan Plateau, remains inadequately understood. This knowledge gap is particularly significant due to the fragility of these ecosystems, characterized by low primary productivity. Ungulates, in particular, may exhibit high sensitivity to even minor alterations in plant availability, potentially stemming from global climate change. Consequently, the investigation of these ecosystems may offer valuable insights into addressing future challenges posed by climate change. Here, to fill this knowledge gap, we explore the relationship between lakes and Tibetan antelopes in an even more vulnerable region, the Tibetan Plateau. We found that the Tibetan antelope population was higher in areas with larger lakes, and where the terrain near the lakes was flatter. At the same time, vegetation cover and plant diversity were higher near the lake compared to areas farther away from the lake. This phenomenon can be elucidated by the fact that lakes offer Tibetan antelopes a richer food supply and reduced predation risk. Our study provides new perspectives for researchers to explore the cross-ecosystem impacts of climate change.
Molecular Cloning and Functional Characterization of the 5′ Regulatory Region of the SLC11A1 Gene from Yaks
Authors: Chong Yuqing , Wang Liping , Wang Bo , Gao Zhendong , Lu Ying , Deng Weidong , Xi Dongmei
Published: November 2023

The solute transport protein family 11 A1 (SLC11A1), also recognized as natural resistance-associated macrophage protein 1 (NRAMP1), represents a transmembrane protein encoded by the SLC11A1 gene. A variety of prior investigations have illuminated its involvement in conferring resistance or susceptibility to bacterial agents, positioning it as a promising candidate gene for breeding disease-resistant animals. Yaks (Bos grunniens), renowned inhabitants of the Qinghai-Tibet Plateau in China, stand as robust ruminants distinguished by their adaptability and formidable disease resistance. Notwithstanding these unique traits, there is scant literature on the SLC11A1 gene in the yak population. Our inquiry commences with the cloning of the 5′ regulatory region sequence of the Zhongdian yak SLC11A1 gene. We employ bioinformatics tools to identify transcription factor binding sites, delineating pivotal elements like enhancers and cis-acting elements. To ascertain the promoter activity of this region, we amplify four distinct promoter fragments within the 5′ regulatory region of the yak SLC11A1 gene. Subsequently, we design a luciferase reporter gene vector containing four site-specific deletion mutations and perform transient transfection experiments. Through these experiments, we measure and compare the activity of disparate gene fragments located within the 5′ regulatory region, revealing regions bearing promoter functionality and discerning key regulatory elements. Our findings validate the promoter functionality of the 5′ regulatory region, offering preliminary insights into the core and principal regulatory segments of this promoter. Notably, we identified single nucleotide polymorphisms (SNPs) that may be associated with important regulatory elements such as NF-1 and NF-1/L. This study provides a theoretical framework for in-depth research on the function and expression regulation mechanism of the yak SLC11A1 gene.
Characterization of Riemerella anatipestifer Strains Isolated from Various Poultry Species in Poland
Authors: Nowaczek Anna , Dec Marta , Stępień-Pyśniak Dagmara , Wilczyński Jarosław , Urban-Chmiel Renata
Published: November 2023

Riemerella anatipestifer (R. anatipestifer) is one of the common pathogens found in poultry flocks, resulting in serious economic losses for the poultry industry due to high mortality, reduced growth rate, poor feed conversion, increased condemnations, and high treatment costs. The aim of this study was to phenotypically characterize phylogenetic relationships and assess the presence of resistance gene strains of R. anatipestifer obtained from various poultry species in Poland. A total of 57 isolates of Riemerella were included in this study. A polymerase chain reaction (PCR) and matrix assisted laser desorption ionization mass spectrometry (MALDI-TOF MS) were used for identification of the strains. The phylogenetic relationship of the R. anatipestifer isolates was determined by analysing the rpoB gene sequence. The susceptibility to antibiotics was evaluated by minimum inhibitory concentration (MIC) in liquid media. All of the field strains of R. anatipestifer were grouped into one of two clades resulting from rpoB gene sequencing. High MIC50 and MIC90 values were obtained for gentamycin, amikacin, and colistin. Low MIC50 and MIC90 values were obtained for amoxicillin cefuroxime, cefoperazone, piperacillin, and trimethoprim/sulfamethoxazole. Among the resistance genes, tet(X) and ermF were identified most frequently. This is the first phenotypic characterization of R. anatipestifer strains obtained from poultry flocks in Poland.
REDOX Balance in Oligodendrocytes Is Important for Zebrafish Visual System Regeneration
Authors: Pérez-Montes Cristina , Jiménez-Cubides Jhoana Paola , Velasco Almudena , Arévalo Rosario , Santos-Ledo Adrián , García-Macia Marina
Published: November 2023

Zebrafish (Danio rerio) present continuous growth and regenerate many parts of their body after an injury. Fish oligodendrocytes, microglia and astrocytes support the formation of new connections producing effective regeneration of the central nervous system after a lesion. To understand the role of oligodendrocytes and the signals that mediate regeneration, we use the well-established optic nerve (ON) crush model. We also used sox10 fluorescent transgenic lines to label fully differentiated oligodendrocytes. To quench the effect of reactive oxygen species (ROS), we used the endogenous antioxidant melatonin. Using these tools, we measured ROS production by flow cytometry and explored the regeneration of the optic tectum (OT), the response of oligodendrocytes and their mitochondria by confocal microscopy and Western blot. ROS are produced by oligodendrocytes 3 h after injury and JNK activity is triggered. Concomitantly, there is a decrease in the number of fully differentiated oligodendrocytes in the OT and in their mitochondrial population. By 24 h, oligodendrocytes partially recover. Exposure to melatonin blocks the changes observed in these oligodendrocytes at 3 h and increases their number and their mitochondrial populations after 24 h. Melatonin also blocks JNK upregulation and induces aberrant neuronal differentiation in the OT. In conclusion, a proper balance of ROS is necessary during visual system regeneration and exposure to melatonin has a detrimental impact.
Electrochemical Sensing of Curcumin: A Review
Authors: Chiorcea-Paquim Ana-Maria
Published: November 2023

Curcumin is a natural polyphenol derived from turmeric (Curcuma longa) root that has been used for centuries as a spice, coloring agent, and medicine. Curcumin presents anti-inflammatory, antioxidant, anticarcinogenic, antimicrobial, antiviral, antimalarial, hepatoprotective, thrombosuppressive, cardiovascular, hypoglycemic, antiarthritic, and anti-neurodegenerative properties. It scavenges different forms of free radicals and acts on transcription factors, growth factors and their receptors, cytokines, enzymes, and genes, regulating cell proliferation and apoptosis. Curcumin is electroactive, and a relationship between its electron transfer properties and radical-scavenging activity has been highlighted. The objective of this review is to provide a comprehensive overview of the curcumin electron transfer reactions, with emphasis on the controversial aspects related to its oxidation mechanism. The final sections will focus on the electroanalysis of curcumin in natural products, highlighting the most important sensing strategies, based on functional electrodes and nanostructured materials, essential for the development of more efficient in vitro methods of detection and quantification of curcumin in food samples, supplements, and nutripharmaceuticals.
Optimization Method of the Clamping Force for Large Cabin Parts
Authors: Yao Shuangji , Luan Yijv , Ceccarelli Marco , Carbone Giuseppe
Published: November 2023

In order to realize the stable clamping of large cabin parts, this paper studied the clamping force optimization of the clamping mechanism for large-mass and large-size cabin parts. Firstly, three kinds of contact models are introduced. Then, a clamping matrix is constructed for a particular clamping configuration. The nonlinear friction cone constraint at the contact point is transformed into a linear affine constraint in a smooth Riemannian manifold using the special structure of the positive definite symmetric matrix. Finally, a large cabin part used in the aerospace field is used as an example for calculating and simulating the clamping force optimization. Different optimization algorithms are used to calculate the initial value which is put into the gradient flow optimization method of the clamping force for optimization calculation. Meanwhile, the normal clamping force value of a 2 t object is measured using relevant experimental equipment. The simulation results and experimental results show that the gradient flow optimization method of the clamping force can quickly complete the clamping force optimization of large-mass and large-size cabin parts. The actual measured value of the normal clamping force is close to the simulated convergence value. The distribution of the normal force of the clamping mechanisms and the convergence value of the clamping force for each clamping mechanism can provide some references for determining the output clamping force of the clamping mechanism and confirming a reasonable distribution of the clamping mechanism. It also confirms the feasibility and effectiveness of this method applied to the clamping force optimization for a large axial part.
Comparison of Cloud-Computing Providers for Deployment of Object-Detection Deep Learning Models
Authors: Rajendran Prem , Maloo Sarthak , Mitra Rohan , Chanchal Akchunya , Aburukba Raafat
Published: November 2023

As cloud computing rises in popularity across diverse industries, the necessity to compare and select the most appropriate cloud provider for specific use cases becomes imperative. This research conducts an in-depth comparative analysis of two prominent cloud platforms, Microsoft Azure and Amazon Web Services (AWS), with a specific focus on their suitability for deploying object-detection algorithms. The analysis covers both quantitative metrics—encompassing upload and download times, throughput, and inference time—and qualitative assessments like cost effectiveness, machine learning resource availability, deployment ease, and service-level agreement (SLA). Through the deployment of the YOLOv8 object-detection model, this study measures these metrics on both platforms, providing empirical evidence for platform evaluation. Furthermore, this research examines general platform availability and information accessibility to highlight differences in qualitative aspects. This paper concludes that Azure excels in download time (average 0.49 s/MB), inference time (average 0.60 s/MB), and throughput (1145.78 MB/s), and AWS excels in upload time (average 1.84 s/MB), cost effectiveness, ease of deployment, a wider ML service catalog, and superior SLA. However, the decision between either platform is based on the importance of their performance based on business-specific requirements. Hence, this paper ends by presenting a comprehensive comparison based on business-specific requirements, aiding stakeholders in making informed decisions when selecting a cloud platform for their machine learning projects.
Trajectory Prediction with Attention-Based Spatial–Temporal Graph Convolutional Networks for Autonomous Driving
Authors: Li Hongbo , Ren Yilong , Li Kaixuan , Chao Wenjie
Published: November 2023

Accurate and reliable trajectory prediction is crucial for autonomous vehicles to achieve safe and efficient operation. Vehicles perceive the historical trajectories of moving objects and make predictions of behavioral intentions for a future period of time. With the predicted trajectories of moving objects such as obstacle vehicles, pedestrians, and non-motorized vehicles as inputs, self-driving vehicles can make more rational driving decisions and plan more reasonable and safe vehicle motion behaviors. However, due to traffic environments such as intersection scenes with highly interdependent and dynamic attributes, the task of motion anticipation becomes challenging. Existing works focus on the mutual relationships among vehicles while ignoring other potential essential interactions such as vehicle–traffic rules. These studies have not yet deeply explored the intensive learning of interactions between multi-agents, which may result in evaluation deviations. Aiming to meet these issues, we have designed a novel framework, namely trajectory prediction with attention-based spatial–temporal graph convolutional networks (TPASTGCN). In our proposal, the multi-agent interaction mechanisms, including vehicle–vehicle and vehicle–traffic rules, are meticulously highlighted and integrated into one homogeneous graph by transferring the time-series data of traffic lights into the spatial–temporal domains. Through integrating the attention mechanism into the adjacency matrix, we effectively learn the different strengths of interactive association and improve the model’s ability to capture critical features. Simultaneously, we construct a hierarchical structure employing the spatial GCN and temporal GCN to extract the spatial dependencies of traffic networks. Profiting from the gated recurrent unit (GRU), the scene context in temporal dimensions is further attained and enhanced with the encoder. In such a way, the GCN and GRU networks are fused as a features extractor module in the proposed framework. Finally, the future potential trajectories generation tasks are performed by another GRU network. Experiments on real-world datasets demonstrate the superior performance of the scheme compared with several baselines.
Analysis of the Variation in Bearing Estimation Error with Frequency Bands for a Source Beneath the Arctic Ice Using a Geophone
Authors: Chen Sheng , Wen Hongtao , Yang Yanming , Zhou Hongtao , Ruan Hailin
Published: November 2023

To obtain better frequency bands for source bearing estimation, experiments using an ice-mounted geophone were performed at three sites on the Arctic ice cap. By transforming to the frequency domain, errors of the bearing estimation in a number of frequency bands within 1000 Hz and the horizontal peak displacements received by the geophone in the corresponding frequency bands were obtained. After comparing the variation in errors to the peak displacements in the same frequency band, it was found that the errors are related to the peak displacements, and higher peak displacement values mean smaller errors. When the incident angle of the acoustic source and the ice thickness meet certain conditions, some modes of the Lamb waves of the ice plate are excited, the peak displacements in the same frequency band are increased, the errors of bearing estimation are reduced, and the effective frequency band for bearing estimation is broadened. These results provide some new ideas for the bearing estimation of acoustic sources beneath the Arctic ice.
Boosting Lightweight Sentence Embeddings with Knowledge Transfer from Advanced Models: A Model-Agnostic Approach
Authors: Gunel Kadir , Amasyali Mehmet Fatih
Published: November 2023

In this study, we investigate knowledge transfer between two distinct sentence embedding models: a computationally demanding, highly performant model and a lightweight model derived from word vector averaging. Our objective is to augment the representational power of the lightweight model by exploiting the sophisticated features of the robust model. Diverging from traditional knowledge distillation methods that align logits or hidden states of teacher and student models, our approach uses only the output sentence vectors of the teacher model for the alignment with the student models’s word vector representations. We implement two minimization techniques for this purpose: distance minimization and distance and perplexity minimization Our methodology uses WMT datasets for training, and the enhanced embeddings are validated via Google’s Analogy tasks and Meta’s SentEval datasets. We found that our proposed models intriguingly retained and conveyed information in a model-specific fashion.
A Deep Learning-Based Mobile Application for Monkeypox Detection
Authors: Alhasson Haifa F. , Almozainy Elaf , Alharbi Manar , Almansour Naseem , Alharbi Shuaa S. , Khan Rehan Ullah
Published: November 2023

The recent outbreak of monkeypox has raised significant concerns in the field of public health, primarily because it has quickly spread to over 40 countries outside of Africa. Detecting monkeypox in its early stages can be quite challenging because its symptoms can resemble those of chickenpox and measles. However, there is hope that potential use of computer-assisted tools may be used to identify monkeypox cases rapidly and efficiently. A promising approach involves the use of technology, specifically deep learning methods, which have proven effective in automatically detecting skin lesions when sufficient training examples are available. To improve monkeypox diagnosis through mobile applications, we have employed a particular neural network called MobileNetV2, which falls under the category of Fully Connected Convolutional Neural Networks (FCCNN). It enables us to identify suspected monkeypox cases accurately compared to classical machine learning approaches. The proposed approach was evaluated using the recall, precision, F score, and accuracy. The experimental results show that our architecture achieves an accuracy of 0.99%, a Recall of 1.0%, an F-score of 0.98%, and a Precision of 0.95%. We believe that such experimental evaluation will contribute to the medical domain and many use cases.
Improving the IoT Attack Classification Mechanism with Data Augmentation for Generative Adversarial Networks
Authors: Chu Hung-Chi , Lin Yu-Jhe
Published: November 2023

The development of IoT technology has made various IoT applications and services widely used. Because IoT devices have weak information security protection capabilities, they are easy targets for cyber attacks. Therefore, this study proposes MLP-based IoT attack classification with data augmentation for GANs. In situations where the overall classification performance is satisfactory but the performance of a specific class is poor, GANs are employed as a data augmentation mechanism for that class to enhance its classification performance. The experimental results indicate that regardless of whether the training dataset is BoT-IoT or TON-IOT, the proposed method significantly improves the classification performance of classes with insufficient training data when using the data augmentation mechanism with GANs. Furthermore, the classification accuracy, precision, recall, and F1-score performance all exceed 90%.
Temporal and Spatial Variations in the Normalized Difference Vegetation Index in Shanxi Section of the Yellow River Basin and Coal Mines and Their Response to Climatic Factors
Authors: Chai Huabin , Guan Pengju , Hu Jibiao , Geng Sijia , Ding Yahui , Xu Hui , Zhao Yuqiao , Xu Mingtao
Published: November 2023

Investigating the spatiotemporal variations in the Normalized Difference Vegetation Index (NDVI) in the Shanxi section of the Yellow River Basin and its coal mining areas holds significant importance for dynamic vegetation monitoring and mining area management. This study employs MODIS NDVI data and combines various analytical methods, including trend analysis and coefficient of variation analysis, to reveal the characteristics of NDVI spatiotemporal variations and their response to climatic factors in the study area. The results indicate the following: (1) The overall NDVI in the Shanxi section of the Yellow River Basin exhibits a growth trend with an annual growth rate of 1.82% and a 36% increase. Among the mining areas, the NDVI increase is most prominent in the Hebaopian mining area with a 100% growth, while the QinYuan mining area shows the lowest increase at 21%; (2) The NDVI in the Shanxi section of the Yellow River Basin displays high fluctuations, with areas of moderate and high fluctuations accounting for 54.39% of the total. The Hebaopian mining area has a substantial portion of high-fluctuation areas at 38.85%; (3) According to the Hurst index analysis, future vegetation changes in the Shanxi section of the Yellow River Basin are uncertain, with approximately 9.77% of areas expected to continue improving; (4) The variations in the NDVI and climatic factors across the Shanxi section of the Yellow River Basin display spatial heterogeneity. The NDVI exhibits a positive correlation with both temperature and precipitation, with the correlation with precipitation being more pronounced than that with temperature. Precipitation exerts a more significant influence on the NDVI than temperature. These findings not only provide scientific guidance for vegetation restoration and area management in the Shanxi section of the Yellow River Basin and its mining areas but also serve as a scientific basis for decision making regarding vegetation management under the influence of climate change and human activities.