bluuebunny/crossref_metadata_2025 huggingface dataset:
Global epidemiology and socioeconomic correlates of hypopharyngeal cancer in 2020 and its projection to 2040: findings from GLOBOCAN 2020
Authors: Mousavi Seyed Ehsan , Ilaghi Mehran , Mirzazadeh Yasaman , Mosavi Jarrahi Alireza , Nejadghaderi Seyed Aria
Published: September 2024

Background

Hypopharyngeal cancer (HC) comprises less than 5% of all malignant tumors in the head and neck. They often present at an advanced stage, thereby resulting in high mortalities. We aimed to report the epidemiology of HC globally, regionally, and nationally by age, sex, and socioeconomic status in 2020 and its projection to 2040.

Methods

Data on HC incidence and mortality were extracted from the GLOBOCAN 2020. Age-standardized incidence rate (ASIR), age-standardized mortality rate (ASMR), and mortality-to-incidence ratios (MIRs) were calculated. We used bivariate correlation test, presenting results through Pearson’s correlation coefficient (r) to investigate the correlation between the metrics, human development index (HDI), and current healthcare expenditure (CHE) as a percentage of gross domestic product (GDP) (CHE/GDP).

Results

In 2020, there were 84254 new HC cases globally (ASIR: 0.91 per 100000). Moreover, HC resulted in 38599 mortalities in 2020 (ASMR: 0.41). Furthermore, the global MIR of HC was 0.45. The ASIR and ASMR of HC were higher in men than women. Also, HDI demonstrated significant correlations with HC ASIR (r= 0.249, p<0.01), ASMR (r= 0.185, p<0.05), and MIR (r= -0.449, p<0.001). Moreover, a weak significant correlation was also observed between CHE/GDP and MIR (r= -0.295, p<0.001). The number of new HC cases and mortalities were estimated to increase by 50% and 55% in 2040, respectively.

Conclusion

HC is a relatively rare cancer but with a substantial sex and geographic divide in distribution. Key priorities should thus include establishing high-quality cancer registries worldwide.
Research hotspots and future trends in lipid metabolism in chronic kidney disease: a bibliometric and visualization analysis from 2004 to 2023
Authors: Wang Ying , Liu Tongtong , Liu Weijing , Zhao Hailing , Li Ping
Published: September 2024

Background

Disorders of lipid metabolism play a key role in the initiation and progression of chronic kidney disease (CKD). Recently, research on lipid metabolism in CKD has rapidly increased worldwide. However, comprehensive bibliometric analyses in this field are lacking. Therefore, this study aimed to evaluate publications in the field of lipid metabolism in CKD over the past 20 years based on bibliometric analysis methods to understand the important achievements, popular research topics, and emerging thematic trends.

Methods

Literature on lipid metabolism in CKD, published between 2004 and 2023, was retrieved from the Web of Science Core Collection. The VOSviewer (v.1.6.19), CiteSpace (v.6.3 R1), R language (v.4.3.2), and Bibliometrix (v.4.1.4) packages (https://www.bibliometrix.org) were used for the bibliometric analysis and visualization. Annual output, author, country, institution, journal, cited literature, co-cited literature, and keywords were also included. The citation frequency and H-index were used to evaluate quality and influence.

Results

In total, 1,285 publications in the field of lipid metabolism in CKD were identified in this study. A total of 7,615 authors from 1,885 institutions in 69 countries and regions published articles in 466 journals. Among them, China was the most productive (368 articles), and the United States had the most citations (17,880 times) and the highest H-index (75). Vaziri Nosratola D, Levi Moshe, Fornoni Alessia, Zhao Yingyong, and Merscher Sandra emerged as core authors. Levi Moshe (2,247 times) and Vaziri Nosratola D (1,969 times) were also authors of the top two most cited publications. The International Journal of Molecular Sciences and Kidney International are the most published and cited journals in this field, respectively. Cardiovascular disease (CVD) and diabetic kidney disease (DKD) have attracted significant attention in the field of lipid metabolism. Oxidative stress, inflammation, insulin resistance, autophagy, and cell death are the key research topics in this field.

Conclusion

Through bibliometric analysis, the current status and global trends in lipid metabolism in CKD were demonstrated. CVD and DKD are closely associated with the lipid metabolism of patients with CKD. Future studies should focus on effective CKD treatments using lipid-lowering targets.
Integrative analysis of transcriptome and metabolome reveals how ethylene increases natural rubber yield in Hevea brasiliensis
Authors: Yang Hong , Dai Longjun , Liu Mingyang , Fan Xiaokang , Lu Liangruinan , Guo Bingbing , Wang Zhenhui , Wang Lifeng
Published: September 2024

Hevea brasiliensis is an important cash crop with the product named natural rubber (NR) for markets. Ethylene (ET) is the most effective yield stimulant in NR production but the molecular mechanism remains incomplete. Here, latex properties analysis, transcriptome analysis, and metabolic profiling were performed to investigate the mechanism of NR yield increase in four consecutive tappings after ET stimulation. The results revealed that sucrose and inorganic phosphate content correlated positively with dry-rubber yield and were induced upon ET stimulation. Stimulation with ET also led to significant changes in gene expression and metabolite content. Genes involved in phytohormone biosynthesis and general signal transduction as well as 51 transcription factors potentially involved in the ET response were also identified. Additionally, KEGG annotation of differentially accumulated metabolites suggested that metabolites involved in secondary metabolites, amino-acid biosynthesis, ABC transporters, and galactose metabolism were accumulated in response to ET. Integrative analysis of the data collected by transcriptomics and metabolomics identified those differentially expressed genes and differentially accumulated metabolites are mainly involved in amino-acid biosynthesis and carbohydrate metabolism. Correlation analysis of genes and metabolites showed a strong correlation between amino-acid biosynthesis during ET stimulation. These findings provide new insights into the molecular mechanism underlying the ET-induced increase in rubber yield and further our understanding of the regulatory mechanism of ethylene signaling in rubber biosynthesis.
Effect of Parenting Style, attachment to parents and self-compassion on the occurrence and recovery motivation for non-suicidal self-injury in adolescents
Authors: Liu Pei , Liu Jianbo , Li Yi , Lu Jianping
Published: September 2024

Background

Non-suicidal self-injury (NSSI) is a worldwide mental health problem that deserves thorough investigation. This study aims to explore the effect of parenting styles, attachment to parents, and self-compassion on the occurrence of non-suicidal self-injury (NSSI) behavior in adolescents and whether these factors influence their recovery motivation.

Methods

A total of 132 adolescents who had engaged in NSSI within the last year and 72 adolescents who had never engaged in NSSI were recruited from the Shenzhen Kangning Hospital and from primary and secondary schools and communities. Differences in the Hamilton Depression Scale (HAMD), Inventory of Parent and Peer Attachment (IPPA), Egma Minn av. Bardndosnauppforstran (EMBU), and Self-Compassion Scale (SCS) of participants were compared. A binary logistic model was established to measure the odds ratios of these variables on the occurrence of NSSI. In the NSSI adolescent sample, separate binary logistic models were created with NSSI impulse inhibition, NSSI resistance activity, and NSSI recovery motivation as dependent variables and with parenting styles, attachment to parents, and self-compassion as independent variables.

Results

Compared with adolescents with no NSSI behavior, those who had engaged in NSSI within the past year had higher scores on the HAMD, as well as higher EMBU-negative father parental behavior (punishment, excessive interference, rejection, and overprotection), EMBU-negative mother parental behavior (excessive interference, rejection, and punishment), and SCS negative self-compassion scores. Moreover, adolescents with NSSI had lower EMBU-father emotional warmth, EMBU-mother emotional warmth, IPPA-attachment to father, IPPA-attachment to mother, and SCS positive self-compassion scores. Current depressive symptoms and maternal punishment are risk factors for NSSI in adolescents, while positive self-compassion was a protective factor. Positive self-compassion can positively predict NSSI impulse inhibition, NSSI resistance activity, and NSSI recovery motivation. However, we unexpectedly found that the father’s emotional warmth negatively predicts NSSI resistance activity.

Conclusion

This study found that positive self-compassion has a significant impact on the prevention of and recovery from NSSI behavior in adolescents.
Negative impact of online gambling problematic in disabled and non-disabled university students: exploring the risk profile
Authors: Suriá-Martínez Raquel , García-Castillo Fernando , Villegas-Castrillo Esther , López-Sánchez Carmen , Carretón-Ballester Carmen
Published: September 2024

Introduction

The rise of online gambling has brought about significant concerns, particularly regarding its impact on university students. This issue becomes even more complex when considering students with disabilities.

Objectives

This research examines the gambling profile and beliefs of university students based on whether they have a disability. In turn, it seeks to identify if there is a typology of at-risk gamblers according to the disability variable. Finally, it aims to find out the prevalence of gambling among students depending on whether they have a disability and the typology of at-risk gambler.

Method

A total of 704 university students (135 with disabilities and 569 without disabilities) completed the NODS Belief Questionnaire to assess problems associated with gambling and to generate a typological grouping of risk gamblers, as well as a questionnaire designed specifically for the gambler profile.

Results

It was found that a small percentage of participants engage in gambling on a daily basis, with a higher frequency among students with disabilities. In addition, it was observed that the behavior and concern about financial expenditure on gambling interferes with their daily activities and is a cause for concern, with higher risk being observed to a greater extent in students with disabilities.

Discussion

These data suggest the importance for universities and relevant authorities to address these problems comprehensively, providing adequate resources for students with disabilities and promoting a culture of wellbeing that discourages problematic gambling activities and encourages healthy alternatives for entertainment and stress management.
Advanced interpretable diagnosis of Alzheimer's disease using SECNN-RF framework with explainable AI
Authors: AbdelAziz Nabil M. , Said Wael , AbdelHafeez Mohamed M. , Ali Asmaa H.
Published: September 2024

Early detection of Alzheimer's disease (AD) is vital for effective treatment, as interventions are most successful in the disease's early stages. Combining Magnetic Resonance Imaging (MRI) with artificial intelligence (AI) offers significant potential for enhancing AD diagnosis. However, traditional AI models often lack transparency in their decision-making processes. Explainable Artificial Intelligence (XAI) is an evolving field that aims to make AI decisions understandable to humans, providing transparency and insight into AI systems. This research introduces the Squeeze-and-Excitation Convolutional Neural Network with Random Forest (SECNN-RF) framework for early AD detection using MRI scans. The SECNN-RF integrates Squeeze-and-Excitation (SE) blocks into a Convolutional Neural Network (CNN) to focus on crucial features and uses Dropout layers to prevent overfitting. It then employs a Random Forest classifier to accurately categorize the extracted features. The SECNN-RF demonstrates high accuracy (99.89%) and offers an explainable analysis, enhancing the model's interpretability. Further exploration of the SECNN framework involved substituting the Random Forest classifier with other machine learning algorithms like Decision Tree, XGBoost, Support Vector Machine, and Gradient Boosting. While all these classifiers improved model performance, Random Forest achieved the highest accuracy, followed closely by XGBoost, Gradient Boosting, Support Vector Machine, and Decision Tree which achieved lower accuracy.
Unveiling the burden of COPD: perspectives on a patient-reported outcome measure to support communication in outpatient consultations—an interview study among patients
Authors: Gronhaug Louise Muxoll , Farver-Vestergaard Ingeborg , Frølund Jannie Christina , Lindström Egholm Cecilie , Ottesen Anders Løkke
Published: September 2024

Introduction

Chronic Obstructive Pulmonary Disease (COPD) profoundly affects physical, psychological, and social aspects of life, yet these issues often remain unaddressed. Patient-Reported Outcomes Measures (PROM) have the potential to address these issues by promoting person-centered communication. However, their impact in COPD practice remains uncertain. This study aimed to investigate how patients with COPD perceive the usefulness of a new holistic PROM for general palliative care (PRO-Pall) before and during outpatient consultations.

Methods

Semi-structured telephone interviews were conducted with patients diagnosed with moderate to very severe COPD, 2-5 days after consultation at a respiratory outpatient clinic in Denmark. Interviews were transcribed verbatim and analyzed inductively using qualitative content analysis.

Results

Nine patients (five males; mean age: 66 years) participated in the study with four themes emerging: (1) Unlocking thoughts: Completing PRO-Pall stimulated patients’ self-reflection, which revealed previously overlooked COPD-related issues, particularly psychosocial challenges. (2) Unmasking concerns: Patients felt encouraged to be honest, rather than concealing their concerns. (3) Breaking the ice: PRO-Pall responses enabled direct questioning by healthcare professionals during consultations, initiating discussions on patients’ sensitive yet vital COPD-related matters. (4) Deepening the dialogue: Healthcare professionals’ targeted and attentive approach fostered more holistic and meaningful discussions, providing most patients with a deeper understanding of psychosocial issues affecting their well-being.

Conclusion

Completing PRO-Pall prior to outpatient consultations prompted most patients with COPD to unveil previously unacknowledged psychosocial challenges. During consultations, addressing these challenges initiated open discussions on individual concerns, enhancing most patients’ understanding of the multifaceted burden of COPD.
Tangle- and contact-free path planning for a tethered mobile robot using deep reinforcement learning
Authors: Shimada Ryuki , Ishigami Genya
Published: September 2024

This paper presents a tangle- and contact-free path planning (TCFPP) for a mobile robot attached to a base station with a finite-length cable. This type of robot, called a tethered mobile robot, can endure long-time exploration with a continuous power supply and stable communication via its cable. However, the robot faces potential hazards that endanger its operation such as cable snagging on and cable entanglement with obstacles and the robot. To address these challenges, our approach incorporates homotopy-aware path planning into deep reinforcement learning. The proposed reward design in the learning problem penalizes the cable-obstacle and cable-robot contacts and encourages the robot to follow the homotopy-aware path toward a goal. We consider two distinct scenarios for the initial cable configuration: 1) the robot pulls the cable sequentially from the base while heading for the goal, and 2) the robot moves to the goal starting from a state where the cable has already been partially deployed. The proposed method is compared with naive approaches in terms of contact avoidance and path similarity. Simulation results revealed that the robot can successfully find a contact-minimized path under the guidance of the reference path in both scenarios.
Shhh! What Are Secrets and How Do They Affect Us?
Authors: Blomqvist Laura Pauliina , Csizmazia Ildikó Éva , Schnitzler Katja Pia , Weiss Cassandra Elisabeth , Franzen Minita , Van der Hallen Ruth
Published: September 2024

Have you ever kept something about yourself hidden from others? Throughout our day-to-day interactions, there are times when we might choose to keep certain information to ourselves. This is called secrecy, and the information we keep hidden from others is called a secret. Secret keeping is quite common—most people do it, and you have likely kept your fair share of secrets, too. But have you ever wondered how we learn to keep secrets, what goes on in our minds when we keep them, or how they can impact how we feel? In this article, we will reveal the secrets of secret keeping and share what you need to know about this fascinating topic.
Microbiome resilience of three-toed box turtles (Terrapene carolina triunguis) in response to rising temperatures
Authors: Guan Jimmy , Ramírez Gustavo A. , Eng Curtis , Oakley Brian
Published: September 2024

The gastrointestinal (GI) microbiome of chelonians (testudines) plays an important role in their metabolism, nutrition, and overall health but the GI microbiome of three-toed box turtles (Terrapene carolina triunguis) has yet to be characterized. How the GI microbiome responds to rapidly rising environmental temperatures has also not been studied extensively in ectotherms, specifically chelonians. In this study, twenty (20) T.c.triunguis were split into control and experimental groups. The experimental group experienced 4.5°C increases every two weeks while the control group stayed at a constant ambient temperature (24°C) through the entirety of the experiment. Before each temperature increase, all turtles had cloacal swab samples taken. These samples underwent DNA extraction followed by 16S rRNA gene sequencing and microbial community analyses. Differences in diversity at the community level in the controls compared to the experimental groups were not statistically significant, indicating microbiome resilience to rapid temperature changes in T.c.triunguis, although some differentially abundant lineages were identified. Interestingly, an amplicon sequence variant belonging to the Erysipelothrix spp. was exclusively enriched in the highest temperature group relative to controls. Overall, our work suggests that there may be an innate robustness to rapid temperature swings in the microbiome of T.c.triunguis which are native to temperate North America. Despite this resilience, Erysipelothrix spp. was enriched at the highest temperature. Phylogenetic analysis of this amplicon variant showed that it is a close relative of Erysipelothrix rhusiopathiae, a pathogen of zoonotic importance associated with both wildlife and livestock.
Diagnostic utility of ultrasonography for thoracic and abdominal bacterial and parasitic diseases in ruminants: a comprehensive overview
Authors: Tharwat Mohamed , Tsuka Takeshi
Published: September 2024

This review article describes the roles of ultrasound in assessing thoracic and abdominal infectious diseases, mainly bacterial and parasitic ones that affect farm animals, including cattle, camels, sheep, and goats. Ultrasonography is a non-invasive imaging technique used to diagnose infectious diseases affecting the cardiovascular, respiratory, digestive, urinary, and hepatobiliary systems. In cases of thoracic and abdominal infections, ultrasound typically reveals abnormalities in echogenicity and echotexture, the presence of unusual artifacts, and mass formation exerting pressure on surrounding structures. Inflammatory and degenerative changes within the viscera can be identified ultrasonographically by comparing the echogenicity of affected areas with that of the surrounding normal parenchyma, such as in fascioliasis. Bacterial and parasitic infections often result in capsular mass lesions with anechoic contents, as observed in hydatid cysts and cysticercosis, or varying echogenic contents, as observed in liver abscesses. Effusions within the pericardium, pleura, and peritoneum are common ultrasonographic findings in infectious thoracic and abdominal diseases. However, these effusions' echogenicity does not always allow for clear differentiation between transudates and exudates. The routine use of ultrasonography in the evaluation of the chest and abdomen in affected or suspected ruminants is highly beneficial for detection, guiding therapeutic decisions, assessing prognosis, and aiding in the eradication of highly contagious diseases that cause significant economic losses.
Fuzzy Modelling Algorithms and Parallel Distributed Compensation for Coupled Electromechanical Systems
Authors: Reyes Christian , Ramos-Fernández Julio C. , Espinoza Eduardo S. , Lozano Rogelio
Published: September 2024

Modelling and controlling an electrical Power Generation System (PGS), which consists of an Internal Combustion Engine (ICE) linked to an electric generator, poses a significant challenge due to various factors. These include the non-linear characteristics of the system’s components, thermal effects, mechanical vibrations, electrical noise, and the dynamic and transient impacts of electrical loads. In this study, we introduce a fuzzy modelling identification approach utilizing the Takagi–Sugeno (T–S) structure, wherein model and control parameters are optimized. This methodology circumvents the need for deriving a mathematical model through energy balance considerations involving thermodynamics and the non-linear representation of the electric generator. Initially, a non-linear mathematical model for the electrical power system is obtained through the fuzzy c-means algorithm, which handles both premises and consequents in state space, utilizing input–output experimental data. Subsequently, the Particle Swarm Algorithm (PSO) is employed for optimizing the fuzzy parameter m of the c-means algorithm during the modelling phase. Additionally, in the design of the Parallel Distributed Compensation Controller (PDC), the optimization of parameters pertaining to the poles of the closed-loop response is conducted also by using the PSO method. Ultimately, numerical simulations are conducted, adjusting the power consumption of an inductive load.
Comprehensive Analysis and Development of Electric-Drive-Wheel with Idler Gear
Authors: Ding Xiaoyu , Kong Aijing , Zhang Jiantao , Chen Xinbo
Published: September 2024

This paper provides a comprehensive analysis of the electric-drive-wheel (EDW) with idler gear. From the perspective of automotive engineering, the EDW is an integrated execution unit that combines the function of powertrain and suspension. As a result, the research on EDW involves the intersection of multiple disciplines. The evolution of idler gear configuration requires some geometric constraints. Under this premise, the longitudinal and vertical dynamic characteristics of the system were studied, respectively. There are several factors that influence the system performance, such as the gear parameters, the position of the electric motor, and the suspension K&C value. The principles of each parameter on the output indicators were studied, with an optimized plan and simulation comparison to check the correctness of theory. In the end, the prototype was equipped with a test bench, covering a wide range of working operations to examine the expected performance of EDW design. The step response test of the EDW result showed a balanced performance in transmission smoothness and responsiveness agility.
The Impact of Crop Year and Crop Density on the Production of Sunflower in Site-Specific Precision Farming in Hungary
Authors: Nagy János , Zalai Mihály , Illés Árpád , Monoki Szabolcs
Published: September 2024

Sunflower is considered a plant with extraordinary adaptability. However, the conditions of growing sunflower function as a limiting factor in its production. The hybrids used in production tolerate weather variability to a different level and utilise the nutrient and water resources of the soil, while the yield is also affected by the number of plants per hectare. In this study, the authors attempted to observe the environmental effects influencing sunflower cultivation, the heterogeneous productivity zones of the given production site and the correlation of the number of seeding plants used under various farm practices. The average rainfall of 2021 and the dry weather of 2022 created suitable conditions for examining the yearly weather effect. In the selected experimental areas, three distinguishable zones were defined in terms of productivity. In each productivity zone, three crop density steps were used in four replicates. Based on the performed comparative tests, the rainy year of 2021 resulted higher yield than the drier year of 2022 in the average- and high productivity zones, while in the low-productivity zone, higher yields were harvested under the drier conditions of 2022 than in the rainy year of 2021. In 2021, with the improvement in productivity, the obtained yield was also higher. However, in 2022, this clarity could not be demonstrated. In the zones with low productivity, identical yield results were observed in both weather conditions. Based on the examination of the obtained results, it was shown that the effect of weather conditions and the given number of plants have a smaller influence on the yield results of low-productivity zones, while these factors have a greater influence on the yields of high-productivity zones.
Nutrient Dynamics in Integrated Crop–Livestock Systems: Effects of Stocking Rates and Nitrogen System Fertilization on Litter Decomposition and Release
Authors: de Bortolli Marcos Antonio , Assmann Tangriani Simioni , de Bortolli Betania Brum , Maccari Marcieli , Bernardon Angela , Jamhour Jorge , Franzluebbers Alan J. , Soares Andre Brugnara , Severo Igor Kieling
Published: September 2024

Current fertilizer recommendations often neglect nutrient cycling across crop rotations. This study aimed to assess the decay rate and nutrient (N, P, K) release patterns of sorghum, black oat, and corn residues (omitido) in an integrated crop–livestock system. The experiment used factorial treatments based on two sward heights (high and low) and two nitrogen fertilization levels (N-pasture at 200 kg N ha−1 and N-corn at 0 kg N ha−1). Litter bags were collected at various intervals from each crop to measure nutrient release patterns and decomposition rates. The results showed that pasture height and nitrogen fertilization significantly influenced decomposition and nutrient release, affecting the subsequent grain crop phase. Potassium was released rapidly and in high amounts. Nitrogen fertilization during the pasture phase prevented nitrogen and phosphorus immobilization in black oat residue and reduced immobilization in corn residue. These findings highlight the importance of accounting for nutrient cycling and decomposition rates in fertilization strategies to enhance the sustainability of integrated crop–livestock systems.
Microstructure and Properties of Complex Concentrated C14–MCr2 Laves, A15–M3X and D8m M5Si3 Intermetallics in a Refractory Complex Concentrated Alloy
Authors: Tankov Nik , Utton Claire , Tsakiropoulos Panos
Published: September 2024

Abstract: The refractory complex concentrated alloy (RCCA) 5Al–5Cr–5Ge–1Hf–6Mo–33Nb–19Si–20Ti–5Sn–1W (at.%) was studied in the as-cast and heat-treated conditions. The partitioning of solutes in the as-cast and heat-treated microstructures and relationships between solutes, between solutes and the parameters VEC and Δχ, and between these parameters, most of which are reported for the first time for metallic UHTMs, were shown to be important for the properties of the stable phases A15–Nb3X and the D8m βNb5Si3. The nano-hardness and Young’s modulus of the A15–Nb3X and the D8m βNb5Si3 of the heat-treated alloy were measured using nanoindentation and changes in these properties per solute addition were discussed. The aforementioned relationships, the VEC versus Δχ maps and the VEC, Δχ, time, or VEC, Δχ, Young’s modulus or VEC, Δχ, nano-hardness diagrams of the phases in the as-cast and heat-treated alloy, and the properties of the two phases demonstrated the importance of synergy and entanglement of solutes, parameters and phases in the microstructure and properties of the RCCA. The significance of the new data and the synergy and entanglement of solutes and phases for the design of metallic ultra-high temperature materials were discussed.
C-MAC Video Stylet Assisted Endotracheal Intubation in Sedated but Spontaneously Breathing Patients Using Remimazolam and Trachospray Device: A Report of Two Cases
Authors: Witkam Richard L. , Mühling Jörg , Koch Rebecca , Bruhn Jörgen , van Eijk Lucas T.
Published: September 2024

The C-MAC video stylet (Karl Storz KG, Tuttlingen, Germany) is proposed as a successor to the familiar retromolar intubation endoscope. With its flexible tip, it may be especially useful for patients with a limited mouth opening. An awake or sedated airway management technique is often preferred when a difficult airway is anticipated. Due to the challenges in preparation, sedation, topical airway anesthesia and the execution of such an airway management technique itself, these techniques are often clinically underused. The C-MAC video stylet seems to be well suited for an awake or sedated airway approach, as its handling is easier and faster than a flexible fiberscope. It does not exert pressure on the tongue as direct laryngoscopy or video laryngoscopy do. We report two cases of a difficult airway in which intubation was performed by using the C-MAC video stylet in sedated, spontaneously breathing patients. After a low dose of 3 mg midazolam IV, remimazolam was administered continuously (0.46–0.92 mg/kg/h). This was supplemented with a low dose of remifentanil (0.04–0.05 µg/kg/min). The Trachospray device (MedSpray Anesthesia BV, Enschede, The Netherlands) was used for topicalization of the upper airway by means of 4 mL of lidocaine 5%. In addition, a further 5 mL of lidocaine 5% was sprayed via an epidural catheter advanced through the oxygenation port of the C-MAC video stylet for further topicalization of the vocal cords and proximal part of the trachea. The well-coordinated steps described in these two cases may represent a blueprint and a good starting point for future studies with a larger number of patients.
Anatomy of the Right and Left Ventricular Subvalvular Apparatus of the Horse (Equus caballus)
Authors: Bielińska Karolina , Butkiewicz Aleksander F. , Ziemak Hanna , Zdun Maciej
Published: September 2024

Due to the growing interest among veterinarians and the increasing market demands, the development of equine cardiology is necessary. Currently, veterinary medicine for companion animals needs to catch up to human medicine—equine medicine included. A common condition in older horses is aortic valve regurgitation resulting from fibrosis, while its more severe form occurs in younger horses or develops due to a bacterial infection. Mitral valve regurgitation, especially dangerous due to the possibility of sudden death, has a better prognosis if the horse has valve prolapse. Tricuspid valve regurgitation usually does not pose a clinical problem, although its severe cases may lead to heart failure. Some pathologies can be treated surgically, which requires excellent knowledge of anatomy. The object of this study consisted of twenty domestic horse hearts. The focus was on the normal and comparative anatomy of the left and right subvalvular apparatus. The number of muscular bellies of the papillary muscles and the type of connection of the muscles were analysed. Moreover, the height of muscle originating from the ventricle wall was determined, the morphological regularity of the papillary muscle was assessed, and the chordae tendineae originating from the papillary muscles were examined. The conducted research allowed for comparing domestic horses with different species through other studies, the authors of which described this particular aspect. Interspecies similarities which may be correlated with the evolutionary relatedness, as well as differences that could reflect adaptation to different lifestyles, environmental conditions, or metabolic requirements of the animals, have been found. This study expands the knowledge of animals’ normal and comparative anatomy, and contributes to the development of veterinary surgery, internal medicine, and biology.
Study of Damage Mechanism and Evolution Model of Concrete under Freeze–Thaw Cycles
Authors: Zhao Ning , Lian Shuailong
Published: September 2024

Researching the mechanical characteristics of concrete subjected to the freeze–thaw cycle is crucial for building engineering in cold climates. As a result, uniaxial compression tests were performed on concrete samples exposed to various freeze–thaw (F–T) cycles, and the measurements of the pore size distribution, porosity, and P-wave velocity of the saturated concrete samples were obtained, both before and after being exposed to the F–T cycles. Concrete’s F–T damage mechanism and damage evolution model were thoroughly examined. Using rock structure and moisture analysis test equipment to observe the T2 spectrum, the results showed that the F–T cycles can cause the internal structure of the samples to deteriorate. Porosity and F–T cycles have a positive correlation, although P-wave velocity has a negative correlation with the F–T cycles. As the F–T cycles increased, the specimens’ peak strength and elastic modulus steadily declined, while the peak strain clearly exhibited an increasing trend. A microscopic F–T damage model that takes into account the pore size distribution was developed, based on the relative changes in the pore structure distribution (PSD), before and after the F–T cycles. The concrete sample damage evolution law under various F–T cycles was examined using the following metrics: total energy, pore size distribution, static and dynamic elastic moduli, porosity, and P-wave velocity. Uniaxial compressive strength (UCS) and peak strain tests were used to evaluate the accuracy of the pore size distribution damage model, as well as that of five other widely used damage models.
A General Method for Solving Differential Equations of Motion Using Physics-Informed Neural Networks
Authors: Zhang Wenhao , Ni Pinghe , Zhao Mi , Du Xiuli
Published: September 2024

The physics-informed neural network (PINN) is an effective alternative method for solving differential equations that do not require grid partitioning, making it easy to implement. In this study, using automatic differentiation techniques, the PINN method is employed to solve differential equations by embedding prior physical information, such as boundary and initial conditions, into the loss function. The differential equation solution is obtained by minimizing the loss function. The PINN method is trained using the Adam algorithm, taking the differential equations of motion in structural dynamics as an example. The time sample set generated by the Sobol sequence is used as the input, while the displacement is considered the output. The initial conditions are incorporated into the loss function as penalty terms using automatic differentiation techniques. The effectiveness of the proposed method is validated through the numerical analysis of a two-degree-of-freedom system, a four-story frame structure, and a cantilever beam. The study also explores the impact of the input samples, the activation functions, the weight coefficients of the loss function, and the width and depth of the neural network on the PINN predictions. The results demonstrate that the PINN method effectively solves the differential equations of motion of damped systems. It is a general approach for solving differential equations of motion.
High Current Measurement of Commercial REBCO Tapes in Liquid Helium: Experimental Challenges and Solutions
Authors: Masi Andrea , Freda Rosa , Formichetti Andrea , Greco Alberto , Alimenti Andrea , Khan Masood Rauf , Celentano Giuseppe
Published: September 2024

Recent advances in high-temperature superconductors (HTS) have made them extremely attractive for low-temperature, high-magnetic-field-power applications such as in fusion technology, where the advantages over traditional low-temperature superconductors (LTS) allow for the design of fusion reactors operating in different and more convenient regimes. However, the performance enhancement exhibited by novel conductors poses several challenges for the measurement of their superconducting properties. The high critical currents coupled with the relatively low thermal stability of the conductors and their mechanical fragility render this task a challenge, as the angular anisotropies complicate the experimental setup. In this work, we describe the development of our novel high-current measurement facility, focusing on the solutions introduced regarding critical aspects such as the superconducting leads and the sample holder design. We show how simple but effectively designed solutions can be adopted to combat the complexity of the measurement. The results reported in this work guide the development of a measurement system able to withstand high critical currents (I > 1500 A) at high magnetic fields (µ0H > 12 T) by evaluating the angular response of 4 mm wide short samples (L ~ 7.5 cm) in a robust and reproducible manner.
ISAR Imaging Analysis of Complex Aerial Targets Based on Deep Learning
Authors: Wang Yifeng , Hao Jiaxing , Yang Sen , Gao Hongmin
Published: September 2024

Traditional range–instantaneous Doppler (RID) methods for maneuvering target imaging are hindered by issues related to low resolution and inadequate noise suppression. To address this, we propose a novel ISAR imaging method enhanced by deep learning, which incorporates the fundamental architecture of CapsNet along with two additional convolutional layers. Pre-training is conducted through the deep learning network to establish the mapping function for reference. Subsequently, the trained network is integrated into the electromagnetic simulation software, Feko 2019, utilizing a combination of geometric forms such as corner reflectors and Luneberg spheres for analysis. The results indicate that the derived ISAR imaging effectively identifies the ISAR program associated with complex aerial targets. A thorough analysis of the imaging results further corroborates the effectiveness and superiority of this approach. Both simulation and empirical data demonstrate that this method significantly enhances imaging resolution and noise suppression.
A Comprehensive Review of Theories, Methods, and Techniques for Bottleneck Identification and Management in Manufacturing Systems
Authors: Tang Jiachao , Dai Zongxu , Jiang Wenrui , Wu Xuemei , Zhuravkov Michael Anatolievich , Xue Zheng , Wang Jiazhi
Published: September 2024

With the advancement in global market integration, manufacturing enterprises face increasingly fierce competition, making the development of intelligent manufacturing systems a key factor in enhancing market competitiveness. However, manufacturing systems are characterized by varying characteristics of manufacturing resources and strong interdependencies, which make production control more complex. A bottleneck refers to the issue where the manufacturing system’s actual production capacity is less than or equal to the demand placed on a resource. After extensive research, scholars have concluded that the definition, identification methods, and related studies on bottlenecks are not fixed but depend on the specific research subject and the type of bottleneck. Therefore, scholars suggest that only by accurately defining the bottlenecks within a system can appropriate models be employed for prediction, thereby avoiding issues such as inefficient resource allocation and delivery delays, or implementing measures to minimize these negative impacts. Particularly under unstable production conditions, dynamic bottlenecks are likely to occur, making the prediction and identification of bottlenecks under dynamic environmental conditions crucial. Currently, there is still a lack of research in real-time state sensing and integration, as well as a lack of systematic review of related research. To fill this research gap, this review comprehensively introduces the current state and achievements in bottleneck research within manufacturing systems, focusing on bottleneck categories, identification, shifting, and management. It also provides an outlook on future research trends and directions in the study of manufacturing system bottlenecks.
Sensor Fault Detection and Classification Using Multi-Step-Ahead Prediction with an Long Short-Term Memoery (LSTM) Autoencoder
Authors: Hasan Md. Nazmul , Jan Sana Ullah , Koo Insoo
Published: September 2024

The Internet of Things (IoT) is witnessing a surge in sensor-equipped devices. The data generated by these IoT devices serve as a critical foundation for informed decision-making, real-time insights, and innovative solutions across various applications in everyday life. However, data reliability is often compromised due to the vulnerability of sensors to faults arising from harsh operational conditions that can adversely affect the subsequent operations that depend on the collected data. Hence, the identification of anomalies within sensor-derived data holds significant importance in the IoT context. This article proposes a sensor fault detection method using a Long Short-Term Memory autoencoder (LSTM-AE). The AE, trained on normal sensor data, predicts a 20-step window, generating three statistical features via SHapley Additive exPlanations from the estimated steps. These features aid in determining potential faults in the predicted steps using a machine learning classifier. A secondary classifier identifies the type of fault in the sensor signal. Experimentation on two sensor datasets showcases the method’s functionality, achieving fault detection accuracies of approximately 93% and 97%. It is possible to attain a perfect fault classification performance by slightly modifying the feature calculation approach. In a univariate prediction scenario, our proposed approach demonstrates good fault detection and classification performance.
Intelligent Framework Design for Quality Control in Industry 4.0
Authors: Ali Yousaf , Shah Syed Waqar , Arif Arsalan , Tlija Mehdi , Siddiqi Mudasir Raza
Published: September 2024

This research aims to develop an intelligent framework for quality control and fault detection in pre-production and post-production systems in Industry 4.0. In the pre-production system, the health of the manufacturing machine is monitored. In this study, we examine the gear system of induction motors used in industries. In post-production, the product is tested for quality using a machine vision system. Gears are fundamental components in countless mechanical systems, ranging from automotive transmissions to industrial machinery, where their reliable operation is vital for overall system efficiency. A faulty gear system in the induction motor directly affects the quality of the manufactured product. Vibration data, collected from the gear system of the induction motor using vibration sensors, are used to predict the motor’s health condition. The gear system is monitored for six different fault conditions. In the second part, the quality of the final product is inspected with the machine vision system. Faults on the surface of manufactured products are detected, and the product is classified as a good or bad product. The quality control system is developed with different deep learning models. Finally, the quality control framework is validated and tested with the evaluation metrics.
Hybrid Visual Odometry Algorithm Using a Downward-Facing Monocular Camera
Authors: Al-Hadithi Basil Mohammed , Thomas David , Pastor Carlos
Published: September 2024

The increasing interest in developing robots capable of navigating autonomously has led to the necessity of developing robust methods that enable these robots to operate in challenging and dynamic environments. Visual odometry (VO) has emerged in this context as a key technique, offering the possibility of estimating the position of a robot using sequences of onboard cameras. In this paper, a VO algorithm is proposed that achieves sub-pixel precision by combining optical flow and direct methods. This approach uses only a downward-facing, monocular camera, eliminating the need for additional sensors. The experimental results demonstrate the robustness of the developed method across various surfaces, achieving minimal drift errors in calculation.
Research and Evaluation of Multi-Sensory Design of Product Packaging Based on VR Technology in Online Shopping Environment
Authors: Xiao Yingzhe , Li Qianxi , Zhang Zhen , Zhang Yanyue
Published: September 2024

The development and application of virtual reality (VR) technology significantly enhances consumer immersion. Exploring a multi-sensory evaluation model for virtual packaging is valuable for integrating VR technology with packaging. This study developed a multi-sensory evaluation model for virtual packaging using the analytic hierarchy process (AHP). Eye-tracker experimentation was conducted to identify consumer attention indicators when interacting with virtual packaging. These indicators were quantified using Saaty’s nine-level importance scale and expert input, resulting in a comprehensive multi-sensory evaluation model. Subsequently, a VR shopping system focused on potato chips and cola as packaging design objects. This system was evaluated using the established model, and the results were analyzed. Based on the findings, improvements were made, and the system was re-evaluated using the modified model. The post-improvement evaluation demonstrated significantly enhanced sensory experiences. These results validate that the developed evaluation model effectively guides multi-sensory design approaches for packaging within a VR environment.
Determination of the Advanced Mining Influence Range in Coal Mines Based on the Statistical Analysis of Mining-Induced Seismicity
Authors: Zhou Kunyou , Deng Zhen , Kan Jiliang , Dou Linming , Li Jiazhuo , Duan Minke , Kong Peng
Published: September 2024

Determining the advanced mining influence range of an underground working face is crucial for preventing dynamic disasters, such as coal bursts and gas outbursts. In this study, the occurrence of advanced seismicity before the working face as well as its correlation with the acoustic emission (AE) activity of coal and rocks under axial loading was analyzed. Based on the results, a novel statistical method to determine the advanced mining influence range based on advanced seismicity data was proposed and then validated with a case study. The results show that advanced seismicity is caused by the combined effects of static and dynamic stresses at the working face. This seismicity can be used to assess the mining influence degree of the working face on the advanced coal and rock mass, and determine the advanced mining influence range. Using the novel statistical method, the normalized curves for the total number and total energy of the advanced mining-induced seismicity can be plotted. Then, the advanced mining influence range can be determined using thresholds. The thresholds can be established based on the AE activities observed in coal and rock samples under axial static loading. In the case study in this research, the thresholds for the total seismic number and total seismic energy are 0.076 and 0.052, respectively. The corresponding advanced mining influence ranges are 275 m and 245 m, respectively. Field monitoring confirms an advanced mining influence range of 255 m, which validates the results obtained using the novel statistical method.