bluuebunny/crossref_metadata_2025 huggingface dataset:
Synergistic Catalysis of Water-Soluble Exogenous Catalysts and Reservoir Minerals during the Aquathermolysis of Heavy Oil
Authors: Wang Qian , Zhang Shu , Chen Xiang , Ni Jianjun , Du Jialu , Li Yongfei , Xin Xin , Zhao Bin , Chen Gang
Published: August 2024

Oil serves as the essential fuel and economic foundation of contemporary industry. However, the use of traditional light crude oil has exceeded its supply, making it challenging to meet the energy needs of humanity. Consequently, the extraction of heavy oil has become crucial in addressing this demand. This research focuses on the synthesis of several water-soluble catalysts that can work along with reservoir minerals to catalyze the hydrothermal cracking process of heavy oil. The goal is to effectively reduce the viscosity of heavy oil and lower the cost of its extraction. Based on the experimental findings, it was observed that when oil sample 1 underwent hydrothermal cracking at a temperature of 180 °C for a duration of 4 h, the amount of water added and catalyst used were 30% and 0.2% of the oil sample dosage, respectively. It was further discovered that the synthesized Mn(II)C was able to reduce the viscosity of oil sample 1 by 50.38%. The investigation revealed that the combination of Mn(II)C + K exhibited a significant synergistic catalytic impact on reducing viscosity. Initially, the viscosity reduction rate was 50.38%, which climbed to 61.02%. Subsequently, when catalyzed by the hydrogen supply agent isopropanol, the rate of viscosity reduction rose further to 91.22%. Several methods, such as freezing point analysis, thermogravimetric analysis, DSC analysis, component analysis, gas chromatography, wax crystal morphology analysis, and GC-MS analysis, were conducted on aqueous organic matter derived from heavy oil after undergoing different reaction systems. These analyses confirmed that the viscosity of the heavy oil was decreased. By studying the reaction mechanism of the model compound and analyzing the aqueous phase, the reaction largely involves depolymerization between macromolecules, breakdown of heteroatom chains, hydrogenation, ring opening, and other related consequences. These actions diminish the strength of the van der Waals force and hydrogen bond in the recombinant interval, impede the creation of a grid-like structure in heavy oil, and efficiently decrease its viscosity.
Maternal Malnutrition and Elevated Disease Risk in Offspring
Authors: Thornburg Kent L. , Valent Amy M.
Published: August 2024

US populations have seen dramatic increases in the prevalence of chronic disease over the past three generations. Rapid increases in type 2 diabetes and obesity have occurred in all the states but have been particularly striking in the Deep South. These increases have contributed to decreases in life expectancy and to painful elevations in health care costs. The causes of worsening population health are complex and incompletely understood. However, there is strong evidence that vulnerability to chronic conditions is determined in early life. Most chronic diseases are developmentally driven. There are specific stressors experienced in early life that influence epigenetic and structural changes during development. These include malnutrition, severe levels of social stress, toxic chemicals, and low oxygen levels. Most US populations have experienced a decrease in the quality of the food they consume as industrial foods have replaced garden-grown foods. Thus, the consumption of too few nutrients before and during pregnancy and during lactation influences the growth of the placenta and fetal organs and their level of resilience when faced with stresses in postnatal life and particularly as adults. Animal studies have shown that the effects of poor nutrition can be passed on to future generations. The most powerful way that the current epidemics of obesity and insulin resistance can be reversed is by providing key nutrients to prospective mothers and those already pregnant.
Advancement in Diagnosis, Treatment, and Vaccines against Fasciola hepatica: A Comprehensive Review
Authors: Rufino-Moya Pablo José , Zafra Leva Rafael , Martínez-Moreno Álvaro , Buffoni Leandro , Valderas García Elora , Pérez Arévalo José , Molina-Hernández Verónica , Ruiz-Campillo María T. , Herrera-Torres Guillem , Martínez-Moreno Francisco J.
Published: August 2024

In this review article, we aim to provide an overview of fasciolosis in ruminants. Diagnosis through new coprological methods (such as Flukefinder®, FLOTAC®, and Mini-FLOTAC®) remains the most suitable approach for farms. Regarding treatment, there is a scarcity of available drugs, and resistance to them has prompted new approaches (including drug combinations, enhanced metabolism, or the use of natural compounds) to address this issue. Additionally, several researchers have developed vaccines to control the disease, but their efficacy varies, and none are currently sufficient for commercial use. Further studies are needed to better understand all aspects discussed in this manuscript, with the goal of improving diagnosis, treatment, and disease control. It is important to note that this manuscript does not delve into in-depth knowledge of the discussed aspects; rather, it provides an overview of the different methodologies related to these three aspects of parasitic disease.
Oral Prevalence of Selenomonas noxia Differs among Orthodontic Patients Compared to Non-Orthodontic Controls: A Retrospective Biorepository Analysis
Authors: Hodges Kyle , Famuliner Payton , Kingsley Karl , Howard Katherine M.
Published: August 2024

The oral microbial flora may be significantly altered by orthodontic therapy and the use of fixed orthodontic brackets. Most orthodontic research has focused on cariogenic pathogens, while some evidence has demonstrated an increase in many known periodontal pathogens. However, little is known about the prevalence of the Gram-negative periodontal pathogen Selenomonas noxia (SN) among these patients. Using an existing saliva biorepository, n = 208 samples from adult and pediatric orthodontic and non-orthodontic patients were identified and screened for the presence of SN using qPCR and validated primers. In the pediatric study sample (n = 89), 36% tested positive for the presence of SN, with orthodontic patients comprising more SN-positive samples (87.5%) than SN-negative samples (78.9%), p = 0.0271. In the adult study sample (n = 119), SN was found in 28.6%, with orthodontic patients comprising 58.8% of positive samples and only 28.2% of negative samples (p < 0.0001). These data demonstrated that both pediatric and adult orthodontic patients exhibited higher prevalence of SN compared with age-matched non-orthodontic controls. As this microorganism is associated not only with periodontal disease but also long-term health issues such as obesity, more research is needed regarding the factors that increase the prevalence of this microbe.
Adherence to Cysteamine Therapy Among Patients Diagnosed with Cystinosis in Saudi Arabia: A Prospective Cohort Study
Authors: Algasem Reem , Zainy Nedaa , Alsabban Essam , Almojalli Hamad , Alhasan Khalid , Ali Tariq , Broering Deiter , Aleid Hassan
Published: August 2024

Cystinosis is a rare autosomal recessive disorder in which cystine crystals accumulate within the cellular lysosomes, causing damage to multiple organs. Due to challenges with the stringent cysteamine treatment regimen and side effects, adherence is often sub-optimal. This study aimed to assess the level of adherence to cysteamine therapy among cystinosis patients in Saudi Arabia and its impact on their quality of life. Electronic medical record data of 39 cystinosis patients from the Department of Nephrology at King Faisal Specialist Hospital and Research Center in Saudi Arabia were reviewed, and 25 patients were included in this study. Out of the 25 patients included in the final analysis, 64% (n = 16) were female. The mean age was 19.04 years. Almost all patients (23/25, 92%) were on oral IR cysteamine therapy, and 52% (13/25) were on topical cysteamine eye drop treatment. Of the 15 patients who responded to the Morisky Medication Adherence Scale-8 (MMAS-8) questionnaire, only 4 (26.7%) were highly adherent to cysteamine therapy. Most of the respondents (7/15, 46.7%) showed a medium level of treatment adherence. Based on the medication possession ratio for oral cysteamine, only 6 out of 23 patients (26.1%) were found to be 96–100% adherent. For the cysteamine eye drops, only 5/13 patients (38.4%) were 76–95% adherent. The 36-Item Short Form Health Survey (SF-36) used to assess patients’ health-related outcomes showed that their quality of life was affected in the domains of ‘social functioning’ and ‘energy/fatigue.’ Despite a small sample size, this study shows sub-optimal adherence to cysteamine treatment in patients from Saudi Arabia. The possible reasons for low treatment adherence could be a high frequency of administration and treatment-related side effects.
Ziziphus mauritiana Lam. Bark and Leaves: Extraction, Phytochemical Composition, In Vitro Bioassays and In Silico Studies
Authors: Nilofar Nilofar , Sinan Kouadio Ibrahime , Dall’Acqua Stefano , Sut Stefania , Uba Abdullahi Ibrahim , Etienne Ouattara Katinan , Ferrante Claudio , Ahmad Jamil , Zengin Gokhan
Published: August 2024

In this work, homogenizer-assisted extraction (HAE) and maceration (MAE) were applied on leaves and bark of Ziziphus mauritiana using water and methanol (MeOH) as solvents. HAE and MAE extracts were compared through liquid chromatography coupled with mass spectrometry (LC-MS) and evaluating the antioxidant activity, and enzyme inhibition against acetylcholinesterase (AChE), butrylcholinesterase (BChE), tyrosinase, α-amylase, and α-glucosidase. Considering the phytochemical contents and the bioassays results, the HAE extracts resulted favorably with larger content of phenolics and higher antioxidant activity. The MeOH extracts displayed the highest α-amylase inhibitory activity, with HAE MeOH leaf extract leading at 0.78 mmol acarbose equivalent (ACAE)/g. In conclusion, the study highlights that HAE can increase the extraction of phenolic and flavonoid from Z. mauritiana plant materials compared to maceration. Further research could explore the potential therapeutic applications of Z. mauritiana extracts, especially HAE MeOH leaf extracts, for their notable antioxidant and enzyme inhibitory activities, facilitating the way for the development of novel pharmaceutical interventions.
Mapping and Candidate Gene Analysis of an All-Stage Stem Rust Resistance Gene in Durum Wheat Landrace PI 94701
Authors: Li Hongyu , Li Kairong , Li Hongna , Yang Chen , Perera Geetha , Wang Guiping , Lyu Shikai , Hua Lei , Rehman Shams ur , Zhang Yazhou , Ayliffe Michael , Yu Haitao , Chen Shisheng
Published: August 2024

Puccinia graminis f. sp. tritici (Pgt), the causal agent of wheat stem rust, poses a significant threat to global wheat production. Genetic resistance offers a cost-effective and sustainable solution. The durum wheat landrace PI 94701 was previously hypothesized to carry two stem rust resistance (Sr) genes, but their chromosomal locations were unknown. In this study, we mapped and characterized an all-stage Sr gene in PI 94701, temporarily designated as SrPI94701. In seedling tests, SrPI94701 was effective against all six Pgt races tested. Using a large segregating population, we mapped SrPI94701 on chromosome arm 5BL within a 0.17-cM region flanked by markers pku69124 and pku69228, corresponding to 1.04 and 2.15 Mb genomic regions in the Svevo and Chinese Spring reference genomes. Within the candidate region, eight genes exhibited differential expression between the Pgt-inoculated resistant and susceptible plants. Among them, two nucleotide-binding leucine-rich repeat (NLR) genes, TraesCS5B03G1334700 and TraesCS5B03G1335100, showed high polymorphism between the parental lines and were upregulated in Pgt-inoculated resistant plants. However, the flanking and completely linked markers developed in this study could not accurately predict the presence of SrPI94701 in a survey of 104 wheat accessions. SrPI94701 is a promising resource for enhancing stem rust resistance in wheat breeding programs.
Genetic Control of Effective Seedling Leaf Rust Resistance in Aegilops biuncialis Vis. Accessions from the VIR Collection
Authors: Kolesova Maria A. , Tyryshkin Lev G.
Published: August 2024

Leaf rust (caused by Puccinia triticina Erikss., Pt) is a severe foliar disease of cultivated wheat worldwide. Severe development of the disease results in significant losses in seed yield and quality. Growing immune varieties is the most rational method for Pt control in terms of effectiveness and ecological safety. However, the gene pool of cultivated wheat is very narrow for seedling Pt effective resistance genes, which hampers breeding for this trait. One of the well-known methods to broaden genetic diversity for resistance is the introgression of highly effective genes from wild relatives into the genomes of cultivated wheat. The Aegilops L. species have been proven to be perfectly suited for this purpose. No gene for Pt resistance has been transferred to wheat from Aegilops biuncialis Vis. (Lorent’s goatgrass) up to now. Previously, we selected eight accessions of the species from the VIR (N.I. Vavilov All-Russian Institute of Plant Genetic Resources) genebank that showed a perfect level of resistance to leaf rust. In this research, we studied the genetic control of resistance using hybridological, phytopathological, and molecular analyses. According to the F1–F3 hybrid evaluation results, each accession possesses one dominant gene for Pt resistance, and genes in different accessions are allelic or very tightly linked. Phytopathological test clone analysis showed that this gene is not identical to Lr9, Lr19, Lr24, Lr39, and Lr47, which are effective against Pt populations in some areas of Russia. This conclusion was partially supported by the results of the identification of DNA markers specific to these genes in bread wheat. Thus, we identified one dominant gene (temporarily symbolized as LrBi1) for effective seedling Pt resistance; it is recommended for introgression to cultivated wheat via interspecific hybridization.
Prediction of Oil–Water Two-Phase Flow Patterns Based on Bayesian Optimisation of the XGBoost Algorithm
Authors: Wang Dudu , Guo Haimin , Sun Yongtuo , Liang Haoxun , Li Ao , Guo Yuqing
Published: August 2024

With the continuous advancement of petroleum extraction technologies, the importance of horizontal and inclined wells in reservoir exploitation has been increasing. However, accurately predicting oil–water two-phase flow regimes is challenging due to the complexity of subsurface fluid flow patterns. This paper introduces a novel approach to address this challenge by employing extreme gradient boosting (XGBoost, version 2.1.0) optimised through Bayesian techniques (using the Bayesian-optimization library, version 1.4.3) to predict oil–water two-phase flow regimes. The integration of Bayesian optimisation aims to enhance the efficiency of parameter tuning and the precision of predictive models. The methodology commenced with experimental studies utilising a multiphase flow simulation apparatus to gather data across a spectrum of water cut rate, well inclination angles, and flow rates. Flow patterns were meticulously recorded via direct visual inspection, and these empirical datasets were subsequently used to train and validate both the conventional XGBoost model and its Bayesian-optimised counterpart. A total of 64 datasets were collected, with 48 sets used for training and 16 sets for testing, divided in a 3:1 ratio. The findings highlight a marked improvement in predictive accuracy for the Bayesian-optimised XGBoost model, achieving a testing accuracy of 93.8%, compared to 75% for the traditional XGBoost model. Precision, recall, and F1-score metrics also showed significant improvements: precision increased from 0.806 to 0.938, recall from 0.875 to 0.938, and F1-score from 0.873 to 0.938. The training accuracy further supported these results, with the Bayesian-optimised XGBoost (BO-XGBoost) model achieving an accuracy of 0.948 compared to 0.806 for the traditional XGBoost model. Comparative analyses demonstrate that Bayesian optimisation enhanced the predictive capabilities of the algorithm. Shapley additive explanations (SHAP) analysis revealed that well inclination angles, water cut rates, and daily flow rates were the most significant features contributing to the predictions. This study confirms the efficacy and superiority of the Bayesian-optimised XGBoost (BO-XGBoost) algorithm in predicting oil–water two-phase flow regimes, offering a robust and effective methodology for investigating complex subsurface fluid dynamics. The research outcomes are crucial in improving the accuracy of oil–water two-phase flow predictions and introducing innovative technical approaches within the domain of petroleum engineering. This work lays a foundational stone for the advancement and application of multiphase flow studies.
Experimental Study on the Effect of Unloading Paths on Coal Damage and Permeability Evolution
Authors: Hao Congmeng , Wang Youpai , Liu Guangyi
Published: August 2024

Coal seam cavitation is one of the most effective techniques for gas disaster control in low-permeability coal. Due to the difference in cavitation method and process, the damage degree and fracture development range of the coal body around the cavern are greatly different, and the effect of increasing the permeability of the coal body is further changed. In order to further understand the permeability enhancement mechanism of cavitation technology on low-permeability coal and effectively guide engineering applications, this paper conducted experimental research on the unloading damage and permeability evolution characteristics of coal under different cavitation paths using a coal-rock “adsorption-percolation-mechanics” coupling test system. Through the analysis of coal strength and deformation characteristics, coal damage characteristics, and the evolution law of coal permeability combined with the macroscopic damage characteristics of coal, the strength degradation mechanism of unloaded coal and the mechanism of increased permeability and flow were revealed. The results show that unloading can significantly reduce the strength of coal, and the greater the unloading rate, the more obvious the reduction. The essence of this is that unloading reduces the cohesion and internal friction angle of coal—damage and breakage are the most effective ways to improve the permeability of the coal body. Unloading damaged coal bodies not only significantly improves the permeability of the coal body but also improves the diffusion ability of gas, and finally, shows a remarkable strengthening effect of gas extraction.
Comparison of Light Intensity Effect on Microalgal Growth in Cactus-like and Cylindrical Photo Bioreactors
Authors: Hijazi Rayane Mustafa , Mounsef Jihane Rahbani , Kanaan Hadi Youssef
Published: August 2024

Improving photobioreactor performance for microalgae cultivation has been the aim of many researchers over the past few years. One of the primary challenges associated with existing photobioreactors is light penetration. An effective photobioreactor design should maximize light penetration, ensuring uniform illumination throughout the reactor. This study aims to assess the impact of light intensity on microalgal growth from the perspective of energy efficiency and productivity in two photobioreactors. A novel cactus-like and a cylindrical photobioreactor were designed and fabricated using three-dimensional printing technology. These two photobioreactors were used to cultivate two strains of microalgae. The novel photobioreactor achieved a maximum biomass productivity of 1 g/L/d and a maximum energy efficiency of 0.31 g/d/kWh. The cylindrical photobioreactor reached a maximum biomass productivity of 0.74 g/L/d and energy efficiency of 0.22 g/d/kWh. The increase in biomass productivity can be linked to enhancements in the photobioreactor’s surface-to-volume ratio and better light utilization.
Research on Micropore Development Characteristics and Influencing Factors during CO2 Huff-n-Puff
Authors: Kang Jilun , Yang Shenglai , Zhang Wei , Zhang Hong , He Changsong , Wang Xuechun , Wei Shuangbao , Yang Kun , Wang Lilong
Published: August 2024

CO2 huff-n-puff is an important method for the development of shale oil reservoirs. In this study, HPMI and NMR technology was used to characterize the pore distribution of the cores. The CO2 huff-n-puff experiment experiments were conducted to study the effects of injection pressure, soaking time, and heterogeneity on the CO2 huff-n-puff. The results showed that the Jimsar core pores are predominantly nanopores. Mesopores with a pore radius between 2 nm and 50 nm accounted for more than 70%. CO2 huff-n-puff has been shown to effectively enhance shale oil recovery. When the injection pressure was greater than the miscible pressure, higher injection pressures were able to improve the recovery of macropores, particularly in cores with higher permeability. Appropriately extending the soaking time enhanced the diffusion of CO2 in the mesopores, and the recovery increased to above 10%. Determining the optimal soaking time is crucial to achieve maximum CO2 huff-n-puff recovery. Artificial fractures can enhance the recovery of mesopores around them, resulting in core recovery of up to 60%. However, artificial fractures exacerbate reservoir heterogeneity and reduce the CO2 huff-n-puff recovery of matrix. Increasing the cycles of CO2 huff-n-puff can effectively reduce the impact of heterogeneity on the recovery of matrix. In conclusion, expanding the area of the fracturing transformation zone and selecting the appropriate injection pressure and soaking time for the multiple cycles of CO2 huff-n-puff can effectively improve the recovery of shale oil reservoirs.
Silicon Kerf Recovery via Acid Leaching Followed by Melting at Elevated Temperatures
Authors: Mubaiwa Tinotenda , Garshol Askh , Azarov Alexander , Safarian Jafar
Published: August 2024

The aim of this work was to study the purification of silicon kerf loss waste (KLW) by a combination of single-acid leaching followed by inductive melting at high temperatures with an addition of fluidized bed reactor (FBR) silicon granules. The KLW indicated an average particle size (D50) of approximately 1.6 µm, and a BET surface area of 30.4 m2/g. Acid leaching by 1 M HCl indicated significant removal of impurities such as Ni (77%), Fe (91%) and P (75%). The combined two-stage treatment resulted in significant removal of the major impurities: Al (78%), Ni (79%), Ca (85%), P (92%) and Fe (99%). The general material loss during melting decreased with an increasing amount of FBR silicon granules which aided in the melting process and indicated better melting. It was observed that the melting behavior of the samples improved as the temperature increased, with complete melting being observed throughout the crucibles at the highest temperature (1800 °C) used, even without any additives. At lower temperatures (1600 °C–1700 °C) and lower FBR-Si (<30 wt.%) additions, the melting was incomplete, with patches of molten silicon and a lot of surface oxidation as confirmed by both visual observation and electron microscopy. In addition, it was indicated that more reactive and volatile elements (Ga, Mg and P) compared to silicon are partially removed in the melting process (51–87%), while the less reactive elements end up in the final silicon melt. It was concluded that if optimized, the combined treatment of single-acid leaching and inductive melting with the addition of granular FBR silicon has great potential for the recycling of KLW to solar cells and similar applications. Moreover, the application of higher melting temperatures is accompanied by a higher silicon yield of the process, and the involved mechanisms are presented.
Sensing with Molecularly Imprinted Membranes on Two-Dimensional Solid-Supported Substrates
Authors: Wang Lishuang , Li Nan , Zhang Xiaoyan , Bobrinetskiy Ivan , Gadjanski Ivana , Fu Wangyang
Published: August 2024

Molecularly imprinted membranes (MIMs) have been a focal research interest since 1990, representing a breakthrough in the integration of target molecules into membrane structures for cutting-edge sensing applications. This paper traces the developmental history of MIMs, elucidating the diverse methodologies employed in their preparation and characterization on two-dimensional solid-supported substrates. We then explore the principles and diverse applications of MIMs, particularly in the context of emerging technologies encompassing electrochemistry, surface-enhanced Raman scattering (SERS), surface plasmon resonance (SPR), and the quartz crystal microbalance (QCM). Furthermore, we shed light on the unique features of ion-sensitive field-effect transistor (ISFET) biosensors that rely on MIMs, with the notable advancements and challenges of point-of-care biochemical sensors highlighted. By providing a comprehensive overview of the latest innovations and future trajectories, this paper aims to inspire further exploration and progress in the field of MIM-driven sensing technologies.
DeepIOD: Towards A Context-Aware Indoor–Outdoor Detection Framework Using Smartphone Sensors
Authors: Dastagir Muhammad Bilal Akram , Tariq Omer , Han Dongsoo
Published: August 2024

Accurate indoor–outdoor detection (IOD) is essential for location-based services, context-aware computing, and mobile applications, as it enhances service relevance and precision. However, traditional IOD methods, which rely only on GPS data, often fail in indoor environments due to signal obstructions, while IMU data are unreliable on unseen data in real-time applications due to reduced generalizability. This study addresses this research gap by introducing the DeepIOD framework, which leverages IMU sensor data, GPS, and light information to accurately classify environments as indoor or outdoor. The framework preprocesses input data and employs multiple deep neural network models, combining outputs using an adaptive majority voting mechanism to ensure robust and reliable predictions. Experimental results evaluated on six unseen environments using a smartphone demonstrate that DeepIOD achieves significantly higher accuracy than methods using only IMU sensors. Our DeepIOD system achieves a remarkable accuracy rate of 98–99% with a transition time of less than 10 ms. This research concludes that DeepIOD offers a robust and reliable solution for indoor–outdoor classification with high generalizability, highlighting the importance of integrating diverse data sources to improve location-based services and other applications requiring precise environmental context awareness.
Enhanced Predefined-Time Control for Spacecraft Attitude Tracking: A Dynamic Predictive Approach
Authors: Yang Jinhe , Guo Tongjian , Yu Yi , Dong Quanliang , Jia Yifan
Published: August 2024

This study presents a predefined-time control strategy for rigid spacecraft, employing dynamic predictive techniques to achieve robust and precise attitude tracking within predefined time constraints. Advanced predictive algorithms are used to effectively mitigate system uncertainties and environmental disturbances. The main contributions of this work are introducing adaptive global optimization for period updates, which relaxes the original restrictive conditions; ensuring easier parameter adjustments in predefined-time control, providing a nonconservative upper bound on system stability; and developing a continuous, robust control law through terminal sliding mode control and predictive methods. Extensive simulations confirm the control scheme reduces attitude tracking errors to less than 0.01 degrees at steady state, demonstrating the effectiveness of the proposed control strategy.
Sensing Classroom Temperature, Relative Humidity, Illuminance, CO2, and Noise: An Integral Solution Based on an IoT Device for Dense Deployments
Authors: Hernandez Wilmar , Cañas Norberto
Published: August 2024

Maintaining optimal Indoor Environmental Quality (IEQ) requires continuous measurement of certain variables. To this end, ASHRAE and BPIE recommend that at least the following areas of interest be considered when measuring IEQ: thermal comfort, illuminance, indoor air quality, and noise. At this time, it is not common to find an IoT device that is suitable for dense deployments in schools, university campuses, hospitals, and office buildings, among others, that measures variables in all of the above areas of interest. This paper presents a solution to the problem previously outlined by proposing an IoT device that measures variables across all of the aforementioned areas of interest. Moreover, in a radio frequency network with a tree-like structure of IoT devices, this device is able to assume the roles of sensor and hub node, sensor and router node, and only sensor node. The experimental results are satisfactory, and the detailed system design ensures the replicability of the device. Furthermore, the theoretical analysis paves the way for high scalability.
Deep Learning Technology and Image Sensing
Authors: Lee Suk-Ho , Kang Dae-Ki
Published: August 2024

The scientific landscape is constantly evolving, marked by groundbreaking advancements in imaging, sensing, and machine learning that expand the realms of possibility across various disciplines [...]
Pantograph Slider Detection Architecture and Solution Based on Deep Learning
Authors: Guo Qichang , Tang Anjie , Yuan Jiabin
Published: August 2024

Railway transportation has been integrated into people’s lives. According to the “Notice on the release of the General Technical Specification of High-speed Railway Power Supply Safety Testing (6C System) System” issued by the National Railway Administration of China in 2012, it is required to install pantograph and slide monitoring devices in high-speed railway stations, station throats and the inlet and exit lines of high-speed railway sections, and it is required to detect the damage of the slider with high precision. It can be seen that the good condition of the pantograph slider is very important for the normal operation of the railway system. As a part of providing power for high-speed rail and subway, the pantograph must be paid attention to in railway transportation to ensure its integrity. The wear of the pantograph is mainly due to the contact power supply between the slide block and the long wire during high-speed operation, which inevitably produces scratches, resulting in depressions on the upper surface of the pantograph slide block. During long-term use, because the depression is too deep, there is a risk of fracture. Therefore, it is necessary to monitor the slider regularly and replace the slider with serious wear. At present, most of the traditional methods use automation technology or simple computer vision technology for detection, which is inefficient. Therefore, this paper introduces computer vision and deep learning technology into pantograph slide wear detection. Specifically, this paper mainly studies the wear detection of the pantograph slider based on deep learning and the main purpose is to improve the detection accuracy and improve the effect of segmentation. From a methodological perspective, this paper employs a linear array camera to enhance the quality of the data sets. Additionally, it integrates an attention mechanism to improve segmentation performance. Furthermore, this study introduces a novel image stitching method to address issues related to incomplete images, thereby providing a comprehensive solution.
Relationship between Fear-Avoidance Beliefs and Muscle Co-Contraction in People with Knee Osteoarthritis
Authors: Taniguchi Takanori , Tanaka So , Nishigami Tomohiko , Imai Ryota , Mibu Akira , Yoshimoto Takaaki
Published: August 2024

Excessive muscle co-contraction is one of the factors related to the progression of knee osteoarthritis (OA). A previous study demonstrated that pain, joint instability, lateral thrust, weight, and lower extremity alignment were listed as factors affecting excessive co-contraction in knee OA. However, this study aimed to assess the association between fear-avoidance beliefs and muscle co-contraction during gait and stair climbing in people with knee OA. Twenty-four participants with knee OA participated in this cross-sectional study. Co-contraction ratios (CCRs) were used to calculate muscle co-contraction during walking and stair climbing, using surface electromyography. Fear-avoidance beliefs were assessed by the Tampa Scale for Kinesiophobia-11 (TSK-11) for kinesiophobia and the Pain Catastrophizing Scale (PCS) for pain catastrophizing. Secondary parameters that may influence co-contraction, such as degree of pain, lateral thrust, weight, and lower extremity alignment, were measured. The relationships between the CCR during each movement, TSK-11, and PSC were evaluated using Spearman’s rank correlation coefficient and partial correlation analysis, adjusted by weight and lower extremity alignment. Partial correlation analysis showed a significant correlation only between medial muscles CCR and TSK-11 during stair descent (r = 0.54, p < 0.05). Our study revealed that kinesiophobia could be associated with co-contraction during stair descent in people with knee OA.
Comparative Analysis of Mixed Reality and PowerPoint in Education: Tailoring Learning Approaches to Cognitive Profiles
Authors: Petruse Radu Emanuil , Grecu Valentin , Chiliban Marius-Bogdan , Tâlvan Elena-Teodora
Published: August 2024

The term immersive technology refers to various types of technologies and perspectives that are constantly changing and developing. It can be used for different purposes and domains such as education, healthcare, entertainment, arts, and engineering. This paper aims to compare the effectiveness of immersive technologies used in education, namely mixed reality, generated with Microsoft HoloLens 2, with traditional teaching methods. The experiment involves comparing two groups of students who received different training methods: the first group saw a PowerPoint slide with an image of the human muscular system, while the second group saw a 3D hologram of the human body that showed the same muscle groups as in the PowerPoint (PPT). By integrating the Intelligence Quotient (IQ) levels of the participants as a predictive variable, the study sought to ascertain whether the incorporation of mixed reality technology could significantly influence the learning outcomes and retention capabilities of the learners. This investigation was designed to contribute to the evolving pedagogical landscape by providing empirical evidence on the potential benefits of advanced educational technologies in diverse learning environments. The main finding of this study indicates that while MR has potential, its effectiveness is closely tied to its interactivity. In cases where the content remains static and non-interactive, MR does not significantly enhance in-formation retention compared to traditional PPT methods. Additionally, the study highlights that instructional strategies should be adapted to individual cognitive profiles, as the technology type (MR or PPT) alone does not significantly impact learning outcomes when the information presented is identical.
The Development and Validation of an LC–Orbitrap–HRMS Method for the Analysis of Four Tetracyclines in Milk and Its Application to Determine Oxytetracycline Concentrations after Intramuscular Administration in Healthy Sarda Ewes and Those Naturally Infected with Streptococcus uberis
Authors: Salis Severyn , Dore Simone , Rubattu Nicola , D’Ascenzo Vittoria , Cherchi Francesca T. , Lollai Stefano A.
Published: August 2024

An LC–Orbitrap–HRMS method was developed and validated for the simultaneous determination of four tetracyclines—oxytetracycline (OTC), tetracycline (TC), doxycycline (DC), and chlortetracycline (CTC)—in milk. This method involves sample extraction with McIlvaine–EDTA buffer solution (pH 4) and solid-phase extraction (SPE) with Oasis HLB cartridges, followed by the evaporation of the extract and its reconstitution with a 14% methanol aqueous solution before injection into the instrumental system. This method has been validated in terms of linearity, sensitivity, selectivity, precision, and accuracy, in accordance with Commission Decision 2002/657/EC requirements. Compared to existing methods, this approach optimally combines a quantitative procedure for extracting analytes from the milk of different species, including sheep, bovines, and goats, with a very short LC–Orbitrap–HRMS instrumental analysis time (only 8 min), simultaneously ensuring high precision, sensitivity, and applicability as a rapid confirmation method in official food control laboratories. The proposed method was applied to determine the concentration levels of OTC in milk samples derived from healthy Sardinian sheep and those naturally infected with Streptococcus uberis, after the intramuscular administration of an antibiotic, in order to evaluate how much of the drug was “subtracted” during penetration from blood into milk, with a potential effect of reducing its therapeutic efficacy.
How to Compare Relative Age Effect in Different Sports? A New Methodological Approach—Example of Youth Olympic Games
Authors: Cular Drazen , Babic Matej , Katovic Darko , Beslija Tea , Kezic Ana
Published: August 2024

This research aimed to propose a new methodological approach for analyzing relative age effect (RAE) in different sports or samples named “Relative age effect overall scale” (RAEOS). The sample consisted of 1455 male and female young athletes who competed in four different sports (basketball, n = 159; handball, n = 215; swimming, n = 981; taekwondo, n = 100) at the Youth Olympic Games (YOG) in Buenos Aires in 2018. To construct the new model, the sample was classified into four unified quartiles of a specific range depending on the sport (swimming: 48-month range, taekwondo: 24-month range, and basketball and handball: 36-month range). Expected and observed frequencies for each sport, the winners/all athletes, and differences between team and individual sports were analyzed using a non-parametric Chi-square test. The obtained results confirm the existence of the RAE in all four analyzed sports (p > 0.01) in a sample of all participants and the sample of gold medalists. Differences between team and individual sports in the analyzed sample have also been found. The proposed methodological approach (RAEOS) is a simple and applicable tool that provides opportunities for comparison and analysis of different sports and competition formats, as well as improvement of the sports talent system in the context of RAE issues. It is suggested to the sports decision-makers to improve the YOG qualification and competition system to enable fairer competition and reduce the influence of RAE on the performance and development of young athletes.
Predictive Machine Learning Model to Assess the Adsorption Efficiency of Biochar-Heavy Metals for Effective Remediation of Soil–Plant Environment
Authors: Li Xiang , Chen Bing , Chen Weisheng , Yin Yilong , Huang Lianxi , Wei Lan , Awad Mahrous , Liu Zhongzhen
Published: August 2024

Biochar is crucial for agricultural output and plays a significant role in effectively eliminating heavy metals (HMs) from the soil, which is essential for maintaining a soil–plant environment. This work aimed to assess machine learning models to analyze the impact of soil parameters on the transformation of HMs in biochar–soil–plant environments, considering the intricate non-linear relationships involved. A total of 211 datasets from pot or field experiments were evaluated. Fourteen factors were taken into account to assess the efficiency and bioavailability of HM–biochar amendment immobilization. Four predictive models, namely linear regression (LR), partial least squares (PLS), support vector regression (SVR), and random forest (RF), were compared to predict the immobilization efficiency of biochar-HM. The findings revealed that the RF model was created using 5-fold cross-validation, which exhibited a more reliable prediction performance. The results indicated that soil features accounted for 79.7% of the absorption of HM by crops, followed by biochar properties at 17.1% and crop properties at 3.2%. The main elements that influenced the result have been determined as the characteristics of the soil (including the presence of different HM species and the amount of clay) and the quantity and attributes of the biochar (such as the temperature at which it was produced by pyrolysis). Furthermore, the RF model was further developed to predict bioaccumulation factors (BAF) and variations in crop uptake (CCU). The R2 values were found to be 0.7338 and 0.6997, respectively. Thus, machine learning (ML) models could be useful in understanding the behavior of HMs in soil–plant ecosystems by employing biochar additions.
The Accumulation of Abscisic Acid Increases the Innate Pool of Soluble Phenolics through Polyamine Metabolism in Rice Seedlings under Hexavalent Chromium Stress
Authors: Kang Yi , Li Cheng-Zhi , Ullah Abid , Zhang Qing , Yu Xiao-Zhang
Published: August 2024

Potential toxic element (PTE) pollution has emerged as a significant environmental and social concern in global agriculture. Chromium (Cr) occurs in different oxidation states naturally, among them Cr(VI), which is highly toxic. This study carried out biochemical and molecular tests to elucidate the accumulation of total soluble phenolics (TSPs) in rice plants exposed to Cr(VI) at 2.0, 8.0, and 16.0 mg Cr/L, emphasizing the interaction between polyamines (PAs) and abscisic acid (ABA). The results revealed significant Cr accumulation in different tissues of rice plants, which hindered their growth. Cr(VI) exposure increased the ABA concentration, with higher levels detected in the shoots than in the roots. The TSP concentration in rice tissues showed a positive relationship with the supplied concentrations of Cr(VI). The measured PAs, including spermine (Spm), putrescine (Put), and spermidine (Spd), exhibited varied responses to Cr(VI) stress, with only Spm concentration increasing with Cr(VI) concentrations. Real-time qRT-PCR showed PAs and ABA synthesis-associated genes such as OsADC1, OsAIH, OsCPA1, and OsCPA4 were significantly up-regulated in shoot of rice plants treated with Cr(VI). These genes are associated with the second pathway of Put synthesis, originating from Arg. Almost all genes activated in the Met pathway were significantly up-regulated as well. Moreover, the genes involved in the interconversion among the three species of PAs exhibited completely different responses to Cr(VI) exposure. Overall, the biochemical analysis and gene expression data indicate that the interaction between ABA and Spm is likely to enhance the TSP levels in rice plants subjected to Cr(VI) toxicity.
Short-Term Interaction Effects of PM2.5 and O3 on Daily Mortality: A Time-Series Study of Multiple Cities in China
Authors: Zhang Ying , Fan Lingling , Wang Shigong , Luo Huan
Published: August 2024

In recent years, PM2.5 and O3 have been the two main pollutants affecting public health in China, but the interaction of the two pollutants on human health remains unclear. A two-stage analytical approach was used to investigate the relationships of PM2.5–O3 co-pollution with nonaccidental, cardiovascular, and respiratory mortality levels across 14 cities in China. We first utilized a generalized additive model (GAM) to determine the city-specific associations of PM2.5 and O3 with daily mortality. The associations were then combined at the national and regional levels using meta-analysis. To investigate the potential interactions between the two pollutants and cause-specific mortality, we performed stratified analyses by co-pollutant exposure levels and the synergy index (SI) (SI > 1 indicates a synergistic interaction). The effect of changes in the two pollutants’ concentrations (in 10 μg/m3 increases) on mortality was assessed. The stratification analysis results suggested that each 10 μg/m3 increase in PM2.5 at lag0-1 (lag01) in the low, moderate, and high strata of the O3 concentrations increased nonaccidental mortality by 0.07% (95% confidence interval: −0.03%, 0.17%), 0.33% (0.13%, 0.53%), and 0.68% (0.30%, 1.06%), respectively, with significant between-group differences (p < 0.001). Moreover, each 10 μg/m3 increase in O3 (lag01) in the low, moderate, and high strata of the PM2.5 concentrations increased nonaccidental mortality by 0.15% (−0.06%, 0.36%), 0.53% (0.19%, 0.87%), and 0.75% (0.14%, 1.36%), respectively, with significant between-group differences (p < 0.001). We also found substantial synergistic interactions between the two pollutants and nonaccidental, cardiovascular, and respiratory mortality levels, with SI values of 1.48, 1.51, and 1.33, respectively. Additionally, a subgroup analysis revealed that the interaction of these two pollutants on nonaccidental mortality were greater in South China compared to elsewhere, and during the warm season compared to during the cold season. Our findings suggested that the simultaneous control of PM2.5 and O3 within the context of combined air pollution could significantly decrease the disease risk, especially in southern China and during the warm season.
Increasing Influenza Vaccination Rates among Patients with Type 2 Diabetes Mellitus in Chongqing, China: A Cross-Sectional Analysis Using Behavioral and Social Drivers Tools
Authors: Li Zhourong , Feng Luzhao , Long Jiang , Xiong Yu , Li Tingting , Jiang Binshan , Yang Shuang , Fu Lin , Shi Zumin , Zhao Yong , Qi Li
Published: August 2024

Background: Influenza vaccination is essential for type 2 diabetes mellitus (T2DM) patients due to their higher risks of severe complications and mortality from influenza. This study investigated the willingness of T2DM patients in Chongqing, China, to receive the influenza vaccination during the 2023/2024 season, using behavioral and social drivers (BeSD) tools to improve vaccination uptake in this high-risk group. Methods: A multi-stage sampling method was used to select participants, and face-to-face surveys were conducted in community health centers between March 1 and May 1, 2023. Binary logistic regression was used to analyze the factors influencing vaccination willingness, and standardized scores identified barriers and drivers. Results: Among 1672 T2DM patients, 11.7% had been vaccinated during the 2022/2023 season, and 59.6% were willing to receive the vaccination in the 2023/2024 season. Higher willingness was associated with ethnic minorities (odds ratio [OR], 3.18, 95% confidence interval [CI]: 1.58–6.39), being unemployed individuals (OR 2.69, 95% CI: 1.60–4.52), higher monthly household income per capita (OR 2.72, 95% CI: 1.65–4.50), having diabetes complications (OR 1.76, 95% CI: 1.23–2.51), sufficient vaccine knowledge (OR 1.87, 95% CI: 1.48–2.37), and previous vaccination (OR 7.75, 95% CI: 4.83–12.44). Concerning BeSDs, fear of infecting friends or family members and trust in vaccine efficacy were the predominant drivers, while high vaccine costs were the greatest barrier. Conclusions: Future strategies should focus on improving vaccine knowledge, supporting healthcare workers and peer recommendations, and enhancing vaccination policies. Key interventions such as health education among high-risk groups, such as unemployed individuals, advocacy campaigns, pay-it-forward strategies, and policies for free vaccination could improve coverage in Chongqing.