bluuebunny/crossref_metadata_2025 huggingface dataset:
Effects of Garlic on Glucose Parameters and Lipid Profile: A Systematic Review and Meta-Analysis on Randomized Controlled Trials
Authors: Zhao Xinyu , Cheng Tao , Xia Hui , Yang Yanhong , Wang Shaokang
Published: May 2024

(1) Background: The effect of garlic on glucose and lipid metabolism in humans remains controversial. The aim of this study was to investigate the effects of garlic on blood lipid levels and glucose levels in humans through a systematic review and meta-analysis. (2) Methods: We extensively searched four databases, including PubMed, Web of Science, Embase, and the Cochrane Library, up to February 2024. To assess the collective impact of garlic and its supplements on fasting blood glucose (FBG), glycosylated hemoglobin (HbA1c), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglycerides (TG), an analysis was conducted using a random effects model. Subgroup analyses were performed when I2 < 50%. (3) Result: We found that the garlic intervention was effective in controlling FBG (mean difference = −7.01; 95% CI: −8.53, −5.49, p < 0.001), HbA1c (mean deviation = −0.66; 95% CI: −0.76, −0.55, p < 0.001, I2 = 62.9%), TC (mean difference = −14.17; 95% CI: −19.31, −9.03, p < 0.001), and LDL-C (mean difference = −8.20; 95% CI: −15.58, −0.81, p = 0.03); moreover, it also increased the level of HDL-C in humans (mean difference = 2.06; 95% CI: 1.54, 2.59; p < 0.001). Nonetheless, the intervention involving garlic did not yield a substantial impact on triglyceride (TG) levels. (4) Conclusion: The intervention of garlic is beneficial to control blood glucose and blood lipids in humans.
Assessment of Vitamin Concentrations in Patients with Hashimoto’s Thyroiditis and Their Relationships with Thyroid Function, Biochemical Status, and Anthropometric Parameters—A Preliminary Study
Authors: Mikulska-Sauermann Aniceta Ada , Resztak Matylda , Karaźniewicz-Łada Marta , Filipowicz Dorota , Ruchała Marek , Główka Franciszek K.
Published: May 2024

Hashimoto’s thyroiditis (HT) is the leading cause of hypothyroidism, affecting mainly the female population. Many patients with HT have metabolic disorders and nutritional deficiencies. The aim of this study was to evaluate vitamin D, A, E, B2, and B6 concentrations, thyroid function, metabolic profile, and anthropometric parameters of patients with Hashimoto’s thyroiditis. In 81 female patients with HT (study group), vitamin A and B2 concentrations were significantly lower than in 34 healthy women (control group). No differences were noted in vitamin D, E, and B6 concentrations between groups. Moreover, HT patients had similar anthropometric parameters, lipid profiles, and glucose and insulin concentrations compared to controls. This study showed some relationships between vitamin concentrations and anthropometric or biochemical profiles in HT patients. Among others, in the HT group, the concentration of vitamin D was positively correlated with the level of HDL and negatively correlated with BMI, total fat mass, and insulin level, which influence cardiovascular risk. The results indicate that patients with HT should be routinely tested for vitamin concentrations to prevent nutritional deficiencies. Further studies are also needed on the role of vitamins in the development and progression of HT and the presence of metabolic complications in this population.
High-Protein Processed Foods: Impact on Diet, Nutritional Status, and Possible Effects on Health
Authors: Ortega Rosa , Arribas-López Nerea , Salas-González María , Aparicio Aránzazu , González-Rodríguez Liliana , Bermejo Laura , Lozano-Estevan María , Cuadrado-Soto Esther , López-Sobaler Ana , Loria-Kohen Viviana
Published: May 2024

Proteins are macronutrients with multiple health benefits, but excessive consumption can negatively affect health. This study aimed to evaluate the characteristics of a sample of high-protein processed foods (HPPFs), describe how their consumption affects dietary balance, and acquire knowledge of the consumption patterns of these products in a Spanish population. A sample of HPPFs available in supermarkets and on websites was collected. The contribution to recommended protein intakes was calculated using national and international references and considering the single consumption of the HPPFs and the product plus 150 g of meat. Furthermore, an online survey was conducted among a convenience sample. A total of 36 enriched protein products were evaluated. The percentage of proteins in these products ranges from 10 to 88%. The contribution of the protein recommended intake was within a range of 87.4–306.6% and 66.4–232.8% (women and men, respectively), only considering the additional proteins from 150 g of meat. One hundred thirty-nine participants completed the survey; 67.6% affirmed that they had consumed HPPFs, and half consumed them without following any consumption control. Since these products are accessible to everyone in supermarkets and protein intake is generally higher than the recommended limits, regulating the mass sale of HPPFs is essential to ensure they do not lead to protein overconsumption.
Astragalus Polysaccharide Modulates the Gut Microbiota and Metabolites of Patients with Type 2 Diabetes in an In Vitro Fermentation Model
Authors: Zhang Xin , Jia Lina , Ma Qian , Zhang Xiaoyuan , Chen Mian , Liu Fei , Zhang Tongcun , Jia Weiguo , Zhu Liying , Qi Wei , Wang Nan
Published: May 2024

This study investigated the effect of astragalus polysaccharide (APS, an ingredient with hypoglycemic function in a traditional Chinese herbal medicine) on gut microbiota and metabolites of type 2 diabetes mellitus (T2DM) patients using a simulated fermentation model in vitro. The main components of APS were isolated, purified, and structure characterized. APS fermentation was found to increase the abundance of Lactobacillus and Bifidobacterium and decrease the Escherichia-Shigella level in the fecal microbiota of T2DM patients. Apart from increasing propionic acid, APS also caused an increase in all-trans-retinoic acid and thiamine (both have antioxidant properties), with their enrichment in the KEGG pathway associated with thiamine metabolism, etc. Notably, APS could also enhance fecal antioxidant properties. Correlation analysis confirmed a significant positive correlation of Lactobacillus with thiamine and DPPH-clearance rate, suggesting the antioxidant activity of APS was related to its ability to enrich some specific bacteria and upregulate their metabolites.
A Systematic Review over the Effect of Early Infant Diet on Neurodevelopment: Insights from Neuroimaging
Authors: Gilbreath Dylan , Hagood Darcy , Larson-Prior Linda
Published: May 2024

The optimization of infant neuronal development through nutrition is an increasingly studied area. While human milk consumption during infancy is thought to give a slight cognitive advantage throughout early childhood in comparison to commercial formula, the biological underpinnings of this process are less well-known and debated in the literature. This systematic review seeks to quantitatively analyze whether early diet affects infant neurodevelopment as measured by various neuroimaging modalities and techniques. Results presented suggest that human milk does have a slight positive impact on the structural development of the infant brain—and that this impact is larger in preterm infants. Other diets with distinct macronutrient compositions were also considered, although these had more conflicting results.
Trends and Missing Links in (De)Hydration Research: A Narrative Review
Authors: Rebelo-Marques Alexandre , Coelho-Ribeiro Bruna , De Sousa Lages Adriana , Andrade Renato , Afonso José , Pereira Rogério , Batista Ana Sofia , Teixeira Vitor Hugo , Jácome Cristina
Published: May 2024

Despite decades of literature on (de)hydration in healthy individuals, many unanswered questions remain. To outline research and policy priorities, it is fundamental to recognize the literature trends on (de)hydration and identify current research gaps, which herein we aimed to pinpoint. From a representative sample of 180 (de)hydration studies with 4350 individuals, we found that research is mainly limited to small-scale laboratory-based sample sizes, with high variability in demographics (sex, age, and level of competition); to non-ecological (highly simulated and controlled) conditions; and with a focus on recreationally active male adults (e.g., Tier 1, non-athletes). The laboratory-simulated environments are limiting factors underpinning the need to better translate scientific research into field studies. Although, consistently, dehydration is defined as the loss of 2% of body weight, the hydration status is estimated using a very heterogeneous range of parameters. Water is the most researched hydration fluid, followed by alcoholic beverages with added carbohydrates (CHO). The current research still overlooks beverages supplemented with proteins, amino acids (AA), and glycerol. Future research should invest more effort in “real-world” studies with larger and more heterogeneous cohorts, exploring the entire available spectrum of fluids while addressing hydration outcomes more harmoniously.
Nutraceuticals for Diabetic Retinopathy: Recent Advances and Novel Delivery Systems
Authors: Ye Xiaoyuan , Fung Nicholas Siu Kay , Lam Wai Ching , Lo Amy Cheuk Yin
Published: May 2024

Diabetic retinopathy (DR) is a major vision-threatening disease among the working-age population worldwide. Present therapeutic strategies such as intravitreal injection of anti-VEGF and laser photocoagulation mainly target proliferative DR. However, there is a need for early effective management in patients with early stage of DR before its progression into the more severe sight-threatening proliferative stage. Nutraceuticals, natural functional foods with few side effects, have been proposed to be beneficial in patients with DR. Over the decades, many studies, either in vitro or in vivo, have demonstrated the advantages of a number of nutraceuticals in DR with their antioxidative, anti-inflammatory, neuroprotective, or vasoprotective effects. However, only a few clinical trials have been conducted, and their outcomes varied. The low bioavailability and instability of many nutraceuticals have indeed hindered their utilization in clinical use. In this context, nanoparticle carriers have been developed to deliver nutraceuticals and to improve their bioavailability. Despite its preclinical nature, research of interventive nutraceuticals for DR may yield promising information in their clinical applications.
Recombinant Bile Salt Hydrolase Enhances the Inhibition Efficiency of Taurodeoxycholic Acid against Clostridium perfringens Virulence
Authors: Alenezi Tahrir , Alrubaye Bilal , Fu Ying , Shrestha Janashrit , Algehani Samar , Wang Hong , Liyanage Rohana , Sun Xiaolun
Published: May 2024

Clostridium perfringens is the main pathogen of chicken necrotic enteritis (NE) causing huge economic losses in the poultry industry. Although dietary secondary bile acid deoxycholic acid (DCA) reduced chicken NE, the accumulation of conjugated tauro-DCA (TDCA) raised concerns regarding DCA efficacy. In this study, we aimed to deconjugate TDCA by bile salt hydrolase (BSH) to increase DCA efficacy against the NE pathogen C. perfringens. Assays were conducted to evaluate the inhibition of C. perfringens growth, hydrogen sulfide (H2S) production, and virulence gene expression by TDCA and DCA. BSH activity and sequence alignment were conducted to select the bsh gene for cloning. The bsh gene from Bifidobacterium longum was PCR-amplified and cloned into plasmids pET-28a (pET-BSH) and pDR111 (pDR-BSH) for expressing the BSH protein in E. coli BL21 and Bacillus subtilis 168 (B-sub-BSH), respectively. His-tag-purified BSH from BL21 cells was evaluated by SDS-PAGE, Coomassie blue staining, and a Western blot (WB) assays. Secretory BSH from B. subtilis was analyzed by a Dot-Blot. B-sub-BSH was evaluated for the inhibition of C. perfringens growth. C. perfringens growth reached 7.8 log10 CFU/mL after 24 h culture. C. perfringens growth was at 8 vs. 7.4, 7.8 vs. 2.6 and 6 vs. 0 log10 CFU/mL in 0.2, 0.5, and 1 mM TDCA vs. DCA, respectively. Compared to TDCA, DCA reduced C. perfringens H2S production and the virulence gene expression of asrA1, netB, colA, and virT. BSH activity was observed in Lactobacillus johnsonii and B. longum under anaerobe but not L. johnsonii under 10% CO2 air. After the sequence alignment of bsh from ten bacteria, bsh from B. longum was selected, cloned into pET-BSH, and sequenced at 951 bp. After pET-BSH was transformed in BL21, BSH expression was assessed around 35 kDa using Coomassie staining and verified for His-tag using WB. After the subcloned bsh and amylase signal peptide sequence was inserted into pDR-BSH, B. subtilis was transformed and named B-sub-BSH. The transformation was evaluated using PCR with B. subtilis around 3 kb and B-sub-BSH around 5 kb. Secretory BSH expressed from B-sub-BSH was determined for His-tag using Dot-Blot. Importantly, C. perfringens growth was reduced greater than 59% log10 CFU/mL in the B-sub-BSH media precultured with 1 vs. 0 mM TDCA. In conclusion, TDCA was less potent than DCA against C. perfringens virulence, and recombinant secretory BSH from B-sub-BSH reduced C. perfringens growth, suggesting a new potential intervention against the pathogen-induced chicken NE.
A Transcriptome Response of Bread Wheat (Triticum aestivum L.) to a 5B Chromosome Substitution from Wild Emmer
Authors: Muterko Alexandr , Kiseleva Antonina , Salina Elena
Published: May 2024

Over the years, alien chromosome substitution has attracted the attention of geneticists and breeders as a rich source of remarkable genetic diversity for improvement in narrowly adapted wheat cultivars. One of the problems encountered along this way is the coadaptation and realization of the genome of common wheat against the background of the introduced genes. Here, using RNA-Seq, we assessed a transcriptome response of hexaploid wheat Triticum aestivum L. (cultivar Chinese Spring) to a 5B chromosome substitution with its homolog from wild emmer (tetraploid wheat T. dicoccoides Koern) and discuss how complete the physiological compensation for this alien chromatin introgression is. The main signature of the transcriptome in the substituted line was a sharp significant drop of activity before the beginning of the photoperiod with a gradual increase up to overexpression in the middle of the night. The differential expression altered almost all biological processes and pathways tested. Because in most cases, the differential expression or its fold change were modest, and this was only a small proportion of the expressed transcriptome, the physiological compensation of the 5B chromosome substitution in common wheat seemed overall satisfactory, albeit not completely. No over- or under-representation of differential gene expression was found in specific chromosomes, implying that local structural changes in the genome can trigger a global transcriptome response.
Introgression of the Self-Pruning Gene into Dwarf Tomatoes to Obtain Salad-Type Determinate Growth Lines
Authors: Pereira Lucas Medeiros , Maciel Gabriel Mascarenhas , Siquieroli Ana Carolina Silva , Luz José Magno Queiroz , Ribeiro Ana Luisa Alves , Oliveira Camila Soares de , Pinto Frederico Garcia , Ikehara Brena Rodrigues Mota
Published: May 2024

The use of dwarf plants in tomato breeding has provided several advantages. However, there are no identified dwarf plants (dd) containing the self-pruning habit (spsp). The aim of this work was to obtain future generations, characterize the germplasm, and select potential dwarf plants with a determinate growth habit to obtain Salad-type lines. The work was started by carrying out hybridization, followed by the first, second, and third backcrosses. Once F2BC3 seeds became available, the introgression of the self-pruning gene (spsp) into dwarf plants (dd) began. Three strains of normal architecture and a determinate growth habit were hybridized with two strains of dwarf size and an indeterminate growth habit, thus yielding four hybrids. Additionally, donor genotype UFU MC TOM1, the commercial cultivar Santa Clara, and the wild accession Solanum pennellii were used in the experiment. Agronomic traits, fruit quality, metabolomics, and acylsugars content were evaluated, and dwarf plants with a determinate growth habit were selected. Hybrid 3 exhibited the highest yields. Visual differences between determinate and indeterminate dwarf plant seedlings were observed. It is suggested to carry out five self-pollinations of the best dwarf plant determined and subsequent hybridization with homozygous lines of normal plant architecture and determinate growth habit to obtain hybrids.
Classification of Microseismic Signals Using Machine Learning
Authors: Chen Ziyang , Cui Yi , Pu Yuanyuan , Rui Yichao , Chen Jie , Mengli Deren , Yu Bin
Published: May 2024

The classification of microseismic signals represents a fundamental preprocessing step in microseismic monitoring and early warning. A microseismic signal source rock classification method based on a convolutional neural network is proposed. First, the characteristic parameters of the microseismic signals are extracted, and a convolutional neural network is constructed for the analysis of these parameters; then, the mapping relationship model between the characteristic parameters of the microseismic signals and the rock class is established. The feasibility of the proposed method in differentiating acoustic emission signals under different load conditions is verified by using acoustic emission data from laboratory uniaxial compression tests, Brazilian splitting tests, and shear tests. In the three distinct laboratory experiments, the proposed method achieved a source rock classification accuracy of greater than 90% for acoustic emission signals. The proposed and verified method provides a new basis for the preprocessing of microseismic signals.
The Influence of Complex Piston Movement on the Output Flow Rate of a Hingeless Bent-Axis Axial Piston Pump
Authors: Shi Junqiang , Shi Jiaxing , Gao Jingcheng , Chen Dongjing , Li Xiaotao , Li Ying , Zhang Jin
Published: May 2024

Wobble-plate axial piston pumps, characterized by the lack of a slipper mechanism, experience reduced leakage in comparison to their swash-plate counterparts, which contributes to their higher volumetric efficiency. Presently, the primary focus of the research conducted by scholars both domestically and internationally is concentrated on wobble-plate axial piston pumps. The performance studies within this field are predominantly focused on investigating flow pulsation. They also investigate pressure pulsation. Additionally, they investigate cavitation phenomena. Research on inclined-axis axial piston pumps has been limited. This study focused on analyzing the operational form of the piston within an inclined-axis axial piston pump. A correction factor k was introduced based on the motion characteristics of the piston. The application of this factor significantly improved the accuracy of the simulations when compared to the experimental results. Specifically, at a load pressure of 10 MPa, the discrepancy between the simulation and the experimental data was reduced from 8.95% to 0.23%. Similarly, at a load pressure of 20 MPa, the error rate was minimized. It was reduced from 9.15% to 0.35%. This demonstrates the effectiveness of the proposed correction factor. The correction factor enhances the predictive accuracy of the pump’s performance. This enhancement is observed under varying load conditions.
Unsupervised Domain Adaptation with Contrastive Learning-Based Discriminative Feature Augmentation for RS Image Classification
Authors: Xu Ren , Samat Alim , Zhu Enzhao , Li Erzhu , Li Wei
Published: May 2024

High- and very high-resolution (HR, VHR) remote sensing (RS) images can provide comprehensive and intricate spatial information for land cover classification, which is particularly crucial when analyzing complex built-up environments. However, the application of HR and VHR images to large-scale and detailed land cover mapping is always constrained by the intricacy of land cover classification models, the exorbitant cost of collecting training samples, and geographical changes or acquisition conditions. To overcome this limitation, we propose an unsupervised domain adaptation (UDA) with contrastive learning-based discriminative feature augmentation (CLDFA) for RS image classification. In detail, our method first utilizes contrastive learning (CL) through a memory bank in order to memorize sample features and improve model performance, where the approach employs an end-to-end Siamese network and incorporates dynamic pseudo-label assignment and class-balancing strategies for adaptive domain joint learning. By transferring classification models trained on a source domain (SD) to an unlabeled target domain (TD), our proposed UDA method enables large-scale land cover mapping. We conducted experiments using a massive five billion-pixels dataset as the SD and tested the HR and VHR RS images of five typical Chinese cities as the TD and applied the method on the completely unlabeled world view 3 (WV3) image of Urumqi city. The experimental results demonstrate that our method excels in large-scale HR and VHR RS image classification tasks, highlighting the advantages of semantic segmentation based on end-to-end deep convolutional neural networks (DCNNs).
Retrieval of Atmospheric Temperature Profiles from FY-4A/GIIRS Hyperspectral Data Based on TPE-MLP: Analysis of Retrieval Accuracy and Influencing Factors
Authors: Xu Xiaoze , Han Wei , Gao Zhiqiu , Li Jun , Yin Ruoying
Published: May 2024

In this study, a novel method for retrieving atmospheric temperature profiles with tree-structured Parzen estimator (TPE) and multilayer perceptron (MLP) algorithms was proposed, using FY-4A/GIIRS (Geosynchronous Interferometric Infrared Sounder) and ERA5 data. Firstly, by adding solar altitude angle, satellite zenith angle, 2m temperature, and surface temperature to the input layer of MLP, there is an improvement in retrieval accuracy. Secondly, TPE is effective in optimizing the hyper-parameters of MLP, and a set of optimized hyper-parameters is obtained through iterative optimization. Thirdly, comparing the retrieved temperature profiles with ERA5 data, we found that retrieval accuracy is influenced by detector, signal-to-noise ratio, terrain, solar altitude angle, satellite zenith angle, and the horizontal temperature gradient. The mean biases of the two adjacent detectors show significant differences, and the retrieval accuracy of the center detectors is greater than that of the north and south sides. The retrieval accuracy is relatively poor in areas with high terrain and large satellite zenith angle. There is a monthly variation in the retrieval accuracy due to the horizontal temperature gradient and signal-to-noise ratio and a significant diurnal variation due to solar altitude angle and signal-to-noise ratio. Compared to in situ sounding data, the mean biases vary from −0.56 K to 0.60 K, and the standard deviations vary from 1.26 K to 2.17 K. The analysis of factors influencing retrieval accuracy provides important insights into improving the ability to retrieve atmospheric temperatures from geostationary hyperspectral IR sounder observations for near real-time (NRT) applications.
On Evaluating Black-Box Explainable AI Methods for Enhancing Anomaly Detection in Autonomous Driving Systems
Authors: Nazat Sazid , Arreche Osvaldo , Abdallah Mustafa
Published: May 2024

The recent advancements in autonomous driving come with the associated cybersecurity issue of compromising networks of autonomous vehicles (AVs), motivating the use of AI models for detecting anomalies on these networks. In this context, the usage of explainable AI (XAI) for explaining the behavior of these anomaly detection AI models is crucial. This work introduces a comprehensive framework to assess black-box XAI techniques for anomaly detection within AVs, facilitating the examination of both global and local XAI methods to elucidate the decisions made by XAI techniques that explain the behavior of AI models classifying anomalous AV behavior. By considering six evaluation metrics (descriptive accuracy, sparsity, stability, efficiency, robustness, and completeness), the framework evaluates two well-known black-box XAI techniques, SHAP and LIME, involving applying XAI techniques to identify primary features crucial for anomaly classification, followed by extensive experiments assessing SHAP and LIME across the six metrics using two prevalent autonomous driving datasets, VeReMi and Sensor. This study advances the deployment of black-box XAI methods for real-world anomaly detection in autonomous driving systems, contributing valuable insights into the strengths and limitations of current black-box XAI methods within this critical domain.
Methods for Estimating the Detection and Quantification Limits of Key Substances in Beer Maturation with Electronic Noses
Authors: Kruse Julia , Wörner Julius , Schneider Jan , Dörksen Helene , Pein-Hackelbusch Miriam
Published: May 2024

To evaluate the suitability of an analytical instrument, essential figures of merit such as the limit of detection (LOD) and the limit of quantification (LOQ) can be employed. However, as the definitions k nown in the literature are mostly applicable to one signal per sample, estimating the LOD for substances with instruments yielding multidimensional results like electronic noses (eNoses) is still challenging. In this paper, we will compare and present different approaches to estimate the LOD for eNoses by employing commonly used multivariate data analysis and regression techniques, including principal component analysis (PCA), principal component regression (PCR), as well as partial least squares regression (PLSR). These methods could subsequently be used to assess the suitability of eNoses to help control and steer processes where volatiles are key process parameters. As a use case, we determined the LODs for key compounds involved in beer maturation, namely acetaldehyde, diacetyl, dimethyl sulfide, ethyl acetate, isobutanol, and 2-phenylethanol, and discussed the suitability of our eNose for that dertermination process. The results of the methods performed demonstrated differences of up to a factor of eight. For diacetyl, the LOD and the LOQ were sufficiently low to suggest potential for monitoring via eNose.
A Recommendation System for Prosumers Based on Large Language Models
Authors: Oprea Simona-Vasilica , Bâra Adela
Published: May 2024

As modern technologies, particularly home assistant devices and sensors, become more integrated into our daily lives, they are also making their way into the domain of energy management within our homes. Homeowners, now acting as prosumers, have access to detailed information at 15-min or even 5-min intervals, including weather forecasts, outputs from renewable energy source (RES)-based systems, appliance schedules and the current energy balance, which details any deficits or surpluses along with their quantities and the predicted prices on the local energy market (LEM). The goal for these prosumers is to reduce costs while ensuring their home’s comfort levels are maintained. However, given the complexity and the rapid decision-making required in managing this information, the need for a supportive system is evident. This is particularly true given the routine nature of these decisions, highlighting the potential for a system that provides personalized recommendations to optimize energy consumption, whether that involves adjusting the load or engaging in transactions with the LEM. In this context, we propose a recommendation system powered by large language models (LLMs), Scikit-llm and zero-shot classifiers, designed to evaluate specific scenarios and offer tailored advice for prosumers based on the available data at any given moment. Two scenarios for a prosumer of 5.9 kW are assessed using candidate labels, such as Decrease, Increase, Sell and Buy. A comparison with a content-based filtering system is provided considering the performance metrics that are relevant for prosumers.
Design of Path-Planning System for Interventional Thermal Ablation of Liver Tumors Based on CT Images
Authors: Song Ziwei , Ding Feifei , Wu Weiwei , Zhou Zhuhuang , Wu Shuicai
Published: May 2024

Objective: Aiming at the shortcomings of artificial surgical path planning for the thermal ablation of liver tumors, such as the time-consuming and labor-consuming process, and relying heavily on doctors’ puncture experience, an automatic path-planning system for thermal ablation of liver tumors based on CT images is designed and implemented. Methods: The system mainly includes three modules: image segmentation and three-dimensional reconstruction, automatic surgical path planning, and image information management. Through organ segmentation and three- dimensional reconstruction based on CT images, the personalized abdominal spatial anatomical structure of patients is obtained, which is convenient for surgical path planning. The weighted summation method based on clinical constraints and the concept of Pareto optimality are used to solve the multi-objective optimization problem, screen the optimal needle entry path, and realize the automatic planning of the thermal ablation path. The image information database was established to store the information related to the surgical path. Results: In the discussion with clinicians, more than 78% of the paths generated by the planning system were considered to be effective, and the efficiency of system path planning is higher than doctors’ planning efficiency. Conclusion: After improvement, the system can be used for the planning of the thermal ablation path of a liver tumor and has certain clinical application value.
Camera-Based Dynamic Vibration Analysis Using Transformer-Based Model CoTracker and Dynamic Mode Decomposition
Authors: Cheng Liangliang , de Groot Justin , Xie Kun , Si Yanxin , Han Xiaodong
Published: May 2024

Accelerometers are commonly used to measure vibrations for condition monitoring in mechanical and civil structures; however, their high cost and point-based measurement approach present practical limitations. With rapid advancements in computer vision and deep learning, research into tracking the motion of individual pixels with vision cameras has increased. The recently developed CoTracker, a transformer-based model, has demonstrated excellence in motion tracking, yet its performance in measuring structural vibrations has not been fully explored. This paper investigates the efficacy of the CoTracker model in extracting full-field structural vibrations using cameras. It is initially applied to capture the dense point movements in video sequences of a cantilever beam recorded using a high-speed camera. Subsequently, modal analysis using delay-embedding dynamic mode decomposition (DMD) is conducted to extract modal parameters including natural frequencies, damping ratios, and mode shapes. The results, benchmarked against those from a reference accelerometer and the Finite Element Method (FEM) result, demonstrate CoTracker’s high potential for general applicability in structural vibration measurements.
An Improved YOLOv7-Based Model for Real-Time Meter Reading with PConv and Attention Mechanisms
Authors: Peng Xiancheng , Chen Yangzhuo , Cai Xiaowen , Liu Jun
Published: May 2024

With the increasing complexity of the grid meter dial, precise feature extraction is becoming more and more difficult. Many automatic recognition solutions have been proposed for grid meter readings. However, traditional inspection methods cannot guarantee detection accuracy in complex environments. So, deep-learning methods are combined with grid meter recognition. Existing recognition systems that utilize segmentation models exhibit very high computation. It is challenging to ensure high real-time performance in edge computing devices. Therefore, an improved meter recognition model based on YOLOv7 is proposed in this paper. Partial convolution (PConv) is introduced into YOLOv7 to create a lighter network. Different PConv introduction locations on the base module have been used in order to find the optimal approach for reducing the parameters and floating point of operations (FLOPs). Meanwhile, the dynamic head (DyHead) module is utilized to enhance the attention mechanism for the YOLOv7 model. It can improve the detection accuracy of striped objects. As a result, this paper achieves mAP50val of 97.87% and mAP50:90val of 62.4% with only 5.37 M parameters. The improved model’s inference speed can reach 108 frames per second (FPS). It enables detection accuracy that can reach ±0.1 degrees in the grid meter.
A High-Throughput Circular Tumor Cell Sorting Chip with Trapezoidal Cross Section
Authors: Lu Shijie , Ma Ding , Mi Xianqiang
Published: May 2024

Circulating tumor cells are typically found in the peripheral blood of patients, offering a crucial pathway for the early diagnosis and prediction of cancer. Traditional methods for early cancer diagnosis are inefficient and inaccurate, making it difficult to isolate tumor cells from a large number of cells. In this paper, a new spiral microfluidic chip with asymmetric cross-section is proposed for rapid, high-throughput, label-free enrichment of CTCs in peripheral blood. A mold of the desired flow channel structure was prepared and inverted to make a trapezoidal cross-section using a micro-nanotechnology process of 3D printing. After a systematic study of how flow rate, channel width, and particle concentration affect the performance of the device, we utilized the device to simulate cell sorting of 6 μm, 15 μm, and 25 μm PS (Polystyrene) particles, and the separation efficiency and separation purity of 25 μm PS particles reached 98.3% and 96.4%. On this basis, we realize the enrichment of a large number of CTCs in diluted whole blood (5 mL). The results show that the separation efficiency of A549 was 88.9% and the separation purity was 96.4% at a high throughput of 1400 μL/min. In conclusion, we believe that the developed method is relevant for efficient recovery from whole blood and beneficial for future automated clinical analysis.
Three-Dimensional-Scanning of Pipe Inner Walls Based on Line Laser
Authors: Kong Lingyuan , Ma Linqian , Wang Keyuan , Peng Xingshuo , Geng Nan
Published: May 2024

In this study, an innovative laser 3D-scanning technology is proposed to scan pipe inner walls in order to solve the problems of the exorbitant expenses and operational complexities of the current equipment for the 3D data acquisition of the pipe inner wall, and the difficulty of both the efficiency and accuracy of traditional light stripe-center extraction methods. The core of this technology is the monocular-structured light 3D scanner, the image processing strategy based on tracking speckles, and the improved gray barycenter method. The experimental results demonstrate a 52% reduction in the average standard error of the improved gray barycenter method when compared to the traditional gray barycenter method, along with an 83% decrease in the operation time when compared to the Steger method. In addition, the size data of the inner wall of the pipe obtained using this technology is accurate, and the average deviation of the inner diameter and length of the pipe is less than 0.13 mm and 0.41 mm, respectively. In general, it not only reduces the cost, but also ensures high efficiency and high precision, providing a new and efficient method for the 3D data acquisition of the inner wall of the pipe.
Assessment of Gait Patterns during Crutch Assisted Gait through Spatial and Temporal Analysis
Authors: Narvaez Dorado Marien , Salazar Miguel , Aranda Joan
Published: May 2024

The use of crutches is a common method of assisting people during recovery from musculoskeletal injuries in the lower limbs. There are several different ways to walk with crutches depending on the patient’s needs. The structure of crutch gaits or crutch gait patterns varies based on the delay between the aid and foot placement, the number of concurrent points of contact, and laterality. In a rehabilitation process, the prescribed pattern may differ according to the injury, the treatment and the individual’s condition. Clinicians may improve diagnosis, assessment, training, and treatment by monitoring and analyzing gait patterns. This study aimed to assess and characterize four crutch walking patterns using spatial and temporal parameters obtained from the instrumented crutches. For this purpose, 27 healthy users performed four different gait patterns over multiple trials. Each trial was recorded using a portable system integrated into the crutches, which measured force, position, and acceleration. Based on the data angle, an algorithm was developed to segment the trials into gait cycles and identify gait phases. The next step was to determine the most appropriate metrics to describe each gait pattern. Several metrics were used to analyze the collected data, including force, acceleration, angle, and stride time. Among 27 participants, significant differences were found between crutch gait patterns. Through the use of these spatial and temporal parameters, promising results were obtained for monitoring assisted gait with crutches. Furthermore, the results demonstrated the possibility of using instrumented crutches as a clinical tool.
Effect of Weight Distribution and Active Safety Systems on Electric Vehicle Performance
Authors: Gori Valerio , Hendrix Will , Das Amritam , Sun Zhiyong
Published: May 2024

This paper describes control methods to improve electric vehicle performance in terms of handling, stability and cornering by adjusting the weight distribution and implementing control systems (e.g., wheel slip control, and yaw rate control). The vehicle is first simulated using the bicycle model to capture the dynamics. Then, a study on the effect of weight distribution on the driving behavior is conducted. The study is performed for three different weight configurations. Moreover, a yaw rate controller and a wheel slip controller are designed and implemented to improve the vehicle’s performance for cornering and longitudinal motion under the different loading conditions. The simulation through the bicycle model is compared to the experiments conducted on a rear-wheel driven radio-controlled (RC) electric vehicle. The paper shows how the wheel slip controller contributes to the stabilization of the vehicle, how the yaw rate controller reduces understeering, and how the location of the center of gravity (CoG) affects steering behavior. Lastly, an analysis of the combination of control systems for each weight transfer is conducted to determine the configuration with the highest performance regarding acceleration time, braking distance, and steering behavior.
A Residual Dense Attention Generative Adversarial Network for Microscopic Image Super-Resolution
Authors: Liu Sanya , Weng Xiao , Gao Xingen , Xu Xiaoxin , Zhou Lin
Published: May 2024

With the development of deep learning, the Super-Resolution (SR) reconstruction of microscopic images has improved significantly. However, the scarcity of microscopic images for training, the underutilization of hierarchical features in original Low-Resolution (LR) images, and the high-frequency noise unrelated with the image structure generated during the reconstruction process are still challenges in the Single Image Super-Resolution (SISR) field. Faced with these issues, we first collected sufficient microscopic images through Motic, a company engaged in the design and production of optical and digital microscopes, to establish a dataset. Secondly, we proposed a Residual Dense Attention Generative Adversarial Network (RDAGAN). The network comprises a generator, an image discriminator, and a feature discriminator. The generator includes a Residual Dense Block (RDB) and a Convolutional Block Attention Module (CBAM), focusing on extracting the hierarchical features of the original LR image. Simultaneously, the added feature discriminator enables the network to generate high-frequency features pertinent to the image’s structure. Finally, we conducted experimental analysis and compared our model with six classic models. Compared with the best model, our model improved PSNR and SSIM by about 1.5 dB and 0.2, respectively.
Intersex Epistemologies? Reviewing Relevant Perspectives in Intersex Studies
Authors: Suess-Schwend Amets
Published: May 2024

Over the last decades, intersex studies has achieved increasing development as a field of critical knowledge, in tight collaboration with discourses developed by intersex activism and human rights bodies. This paper proposes a self-reflexive review of epistemological perspectives in intersex studies within broader discursive fields, through a thematic analysis and comparative framing analysis. This analysis is based on a narrative literature review of academic contributions, activist declarations, and documents issued by human rights bodies conducted over the last decade as a work-in-progress project. Furthermore, it includes results of a scoping review of recent knowledge production in intersex studies carried out in Scopus within the subject area ‘social sciences’. This paper focuses on the analysis of the following epistemological perspectives: human rights frameworks, legal perspectives and citizenship theories, reflections on biopolitics, medicalization and iatrogenesis, sociology of diagnosis framework, depathologization perspective, respectful health care models, and reflections on epistemological, methodological, and ethical aspects. The literature review raises questions about the existence of specific intersex epistemologies in intersex studies, their interrelation with discourses contributed by intersex activism and human rights bodies, and the opportunities for a contribution of theory making in intersex studies to the human rights protection of intersex people.
Investigating the Effects of Misinformation as Infopathogens: Developing a Model and Thought Experiment
Authors: Magarey Roger D. , Chappell Thomas M. , Watson Kayla Pack
Published: May 2024

Previously, it has been shown that transmissible and harmful misinformation can be viewed as pathogenic, potentially contributing to collective social epidemics. In this study, a biological analogy is developed to allow investigative methods that are applied to biological epidemics to be considered for adaptation to digital and social ones including those associated with misinformation. The model’s components include infopathogens, tropes, cognition, memes, and phenotypes. The model can be used for diagnostic, pathologic, and synoptic/taxonomic study of the spread of misinformation. A thought experiment based on a hypothetical riot is used to understand how disinformation spreads.
An Integrated Multi-Criteria Decision Support Model for Sustainable Ship Queuing Policy Application via Vessel Traffic Service (VTS)
Authors: Çağlayan Önder , Aymelek Murat
Published: May 2024

The International Maritime Organization (IMO) persistently improves policies to mitigate greenhouse gas (GHG) emissions from maritime operations, emphasizing the significance of operational measures. Simultaneously, heightened recognition of collaborative efforts within the maritime sector has increased the applicability of arrival policies like Just-In-Time Arrival (JITA), aimed at curtailing unnecessary anchorage time and emissions affecting adjacent communities in port vicinities. Nevertheless, ongoing initiatives advocate adopting JITA over the prevailing First Come, First Served (FCFS) policy, which is perceived as inefficient and, in the meantime, fair in the shipping industry. This research introduces an integrated decision support model to facilitate the implementation of a sustainable ship queuing policy by the VTS. The model addresses critical concerns, including the priorities of relevant authorities, the duration of nautical services for incoming vessels, and carbon dioxide (CO2) emissions attributable to anchorage waiting times. The decision support framework presented integrates the Fuzzy Analytical Hierarchy Process (FAHP) and PROMETHEE II methodologies; the study’s outcomes suggest that the model significantly reduces ships’ unnecessary CO2 emissions during anchorage waiting periods compared to the FCFS policy, with reduction rates ranging from 32.8% to 45% based on case analysis. Moreover, the proposed model ensures fairness by treating competing arriving ships equitably according to predefined criteria.
Comparative Analysis of Japanese Soils: Exploring Power Generation Capability in Relation to Bacterial Communities
Authors: Yue Zihan , Yuan Kun , Seki Mayuko , Agake Shin-Ichiro , Matsumura Keisuke , Okita Naohisa , Naoi Wako , Naoi Katsuhiko , Toyota Koki , Tanaka Haruo , Sugihara Soh , Yasuda Michiko , Ohkama-Ohtsu Naoko
Published: May 2024

This study explores the complex relationship between soil electricity generating capacity, bacterial community dynamics, and soil chemical and physical properties across diverse regions of Japan. First, soil samples were systematically collected and analyzed. Subsequent investigations evaluated soil microbial biomass carbon, dissolved organic carbon (DOC), and total dissolvable iron (DFeT) concentrations. In the experiments, soil samples underwent a rigorous 60-day microbial fuel cell trial, wherein power density and total energy output were measured. Significant variations in power density were observed among different soil samples; specifically, a sugarcane field designated as Okinawa-3 and a peach orchard soil as Nagano-2 demonstrated relatively high total energy output. Analysis of soil bacterial community structures identified some families which showed positive correlations with increased electricity generation capabilities. Correlation analyses revealed associations between these bacterial communities and key soil parameters, particularly with DOC and DFeT concentrations. Redundancy analysis revealed intricate connections between soil properties and electricity generation capacities. Particularly noteworthy was the positive correlation between Acidobacteriaceae and DOC, as well that between Sphingomonadaceae and electricity generation, highlighting the crucial roles of soil microbial communities and chemical compositions in driving electricity generation processes.
Sustainable Treatment of Swine Wastewater: Optimizing the Culture Conditions of Tetradesmus cf. obliquus to Improve Treatment Efficiency
Authors: Bai Kailong , Qu Wenying , Song Duo , Li Junfeng , Ho Shih-Hsin
Published: May 2024

To enhance the sustainability of microalgae-based swine wastewater treatment, this study aims to address the challenges of low efficiency in treating raw swine wastewater, collection difficulties, and high energy consumption treatment processes. The microalgae with strong environmental tolerance were first screened from swine wastewater, and its cultivation conditions were optimized to examine the effect of microalgae treatment on swine wastewater under optimal cultivation conditions. Additionally, the flocculation efficiency and mechanism of microalgae were analyzed. The results showed that Tetradesmus cf. obliquus ZYY1 exhibited the most robust heterotrophic growth. In the BG11 medium supplemented with glucose, the growth rate of T. cf. obliquus ZYY1 under chemoheterotrophic conditions was superior to its growth under photoheterotrophic conditions, reaching its peak with an optimal glucose concentration of 15 g/L. The biomass concentration of T. cf. obliquus ZYY1 in raw wastewater was significantly higher than that in sterilized wastewater, which reached 1.65 ± 0.01 g/L on the 10th day of treatment, with removal efficiencies of NH4+-N, PO43−-P, and the chemical oxygen demand reached 71.36%, 96.09%, and 93.13%, respectively. After raw wastewater treatment, the flocculation efficiency of T. cf. obliquus ZYY1 reached 97.71 ± 5.81%. This was attributed to the bacteria present in the raw wastewater, which induced T. cf. obliquus ZYY1 to secrete aromatic proteins. This study emphasizes the potential of microalgae as a green technology for sustainable wastewater treatment, offering a practical pathway for environmental protection and resource conservation.