bluuebunny/crossref_metadata_2025 huggingface dataset:
Application of Mesenchymal Stem Cell-Derived Schwann Cell-like Cells Spared Neuromuscular Junctions and Enhanced Functional Recovery After Peripheral Nerve Injury
Authors: Nam Yu Hwa , Kim Ji-Sup , Yum Yoonji , Yoon Juhee , Song Hyeryung , Kim Ho-Jin , Lim Jaeseung , Park Saeyoung , Jung Sung-Chul
Published: December 2024

In general, the nerve cells of the peripheral nervous system regenerate normally within a certain period after the physical damage of their axon. However, when peripheral nerves are transected by trauma or tissue extraction for cancer treatment, spontaneous nerve regeneration cannot occur. Therefore, it is necessary to perform microsurgery to connect the transected nerve directly or insert a nerve conduit to connect it. In this study, we applied human tonsillar mesenchymal stem cell (TMSC)-derived Schwann cell-like cells (TMSC-SCs) to facilitate nerve regeneration and prevent muscle atrophy after neurorrhaphy. The TMSC-SCs were manufactured in a good manufacturing practice facility and termed neuronal regeneration-promoting cells (NRPCs). A rat model of peripheral nerve injury (PNI) was generated and a mixture of NRPCs and fibrin glue was transplanted into the injured nerve after neurorrhaphy. The application of NRPCs and fibrin glue led to the efficient induction of sciatic nerve regeneration, with the sparing of gastrocnemius muscles and neuromuscular junctions. This sparing effect of NRPCs toward neuromuscular junctions might prevent muscle atrophy after neurorrhaphy. These results suggest that a mixture of NRPCs and fibrin glue may be a therapeutic candidate to enable peripheral nerve and muscle regeneration in the context of neurorrhaphy in patients with PNI.
Improvement of Laser-Induced Breakdown Spectroscopy Quantitative Performance Using Minimizing Signal Uncertainty as Signal Optimization Target: Taking the Ambient Pressure as an Example
Authors: Zhang Kaifan , Ji Jianxun , Liu Zhitan , Hou Zongyu , Wang Zhe
Published: December 2024

Quantitative analysis performance is considered the Achilles’ heel of laser-induced breakdown spectroscopy. Improving the raw spectral signal is fundamental to achieving accurate quantification. Signal-to-noise ratio enhancement and uncertainty reduction are two targets to improve the raw spectral signal. Most LIBS studies choose the maximum signal-to-noise ratio as the target to optimize the signal. However, there are no precise conclusions about how to optimize signal until now. It has been insisted by our group that the lowest signal uncertainty should be the optimization criterion, which is verified in this article. This study performed quantitative analysis on brass samples at three typical pressures: atmospheric pressure (100 kPa), pressure corresponding to the maximal signal-to-noise ratio (60 kPa), and pressure corresponding to the lowest signal uncertainty (5 kPa) under the optimal spatiotemporal window at each pressure based on a previous study. The results indicate that a pressure of 60 kPa led to a decrease in the accuracy and an increase in the precision of the quantitative analysis; the pressure of 5 kPa led to the highest accuracy and the best precision of the quantitative analysis. Reasons for changes in quantitative analysis are analyzed in detail through matrix effects and signal uncertainty. Therefore, selecting the pressure that corresponds to the lowest signal uncertainty can better improve the LIBS quantitative analysis performance. Signal uncertainty reduction is recommended as a more important direction for the LIBS community.
High-Resolution Electrohydrodynamic Printing with Poly(3,4-ethylenedioxythiophene):Poly(styrenesulfonate) Conductive Polymers
Authors: Li Kaiyun , Jia Xiaokai , Cao Jie , Xu Jingkun , Wang Haibo , Liu Ximei
Published: December 2024

Conductive polymer materials, particularly PEDOT:PSS conductive polymers, have gained widespread attention due to their excellent conductivity, processability, and biocompatibility, making them highly applicable in fields such as bioelectrodes, flexible sensors, and soft robotics. With the rapid development of flexible electronics, the demand for micron-scale precision in the processing of conductive polymers grows. However, advanced fabrication techniques, such as 3D printing and screen printing, which are currently popular in research, face challenges in achieving a micron-level resolution, limiting the further application of conductive polymers. In this study, we demonstrate three types of PEDOT:PSS inks and systematically explore their suitability for electrohydrodynamic (EHD) jet printing. We investigate the impact of critical parameters, including voltage, printing speed, and printing height, on the accuracy of printed patterns. Among the formulations, the optimized PEDOT:PSS to ethylene glycol ratio of 1:1 achieves line widths of 20 µm. Based on this ink, we successfully print flexible conductive polymer patterns with line widths ranging from 20 µm to 90 µm and fabricate PEDOT:PSS conductive films with dimensions of 1.5 cm × 0.5 cm. This high-precision PEDOT:PSS ink demonstrates a strong potential for applications in high-density electrode arrays, electrochemical transistors, and brain–machine interfaces, paving the way for advanced flexible electronics.
Ontological Representation of the Structure and Vocabulary of Modern Greek on the Protégé Platform
Authors: Samaridi Nikoletta , Papakitsos Evangelos , Karanikolas Nikitas
Published: December 2024

One of the issues in Natural Language Processing (NLP) and Artificial Intelligence (AI) is language representation and modeling, aiming to manage its structure and find solutions to linguistic issues. With the pursuit of the most efficient capture of knowledge about the Modern Greek language and, given the scientifically certified usability of the ontological structuring of data in the field of the semantic web and cognitive computing, a new ontology of the Modern Greek language at the level of structure and vocabulary is presented in this paper, using the Protégé platform. With the specific logical and structured form of knowledge representation to express, this research processes and exploits in an easy and useful way the distributed semantics of linguistic information.
Assessment of the Diversity, Abundance and Range of Invasive Alien Plant Species in Córdoba, a Mediterranean Urban Area
Authors: García-Mozo Herminia
Published: December 2024

Invasive species are a major driver of environmental change and pose a significPant threat to native biodiversity due to their ability to invade and establish themselves in natural or semi-natural ecosystems. This study analyzed the presence, abundance, and distribution of invasive alien plant species in a Mediterranean urban area, the municipality of Córdoba (Andalusia region, southern Spain). It includes an important historic city center, urbanized areas but also peri-urban natural and semi-natural sites around. A detailed review of bibliography and computerized botanical databases was conducted prior to an extensive fieldwork and GIS analysis carried out during 2021, 2022, and 2023. Our research identified 227 populations of 17 invasive plant species from 10 different families. These species represent 35% of the invasive plant species reported in the Andalusia region and 27% of those reported in Spain. In total, 53% of the species were introduced from America, especially South America, but no alien invasive species from other European regions were detected. The highest concentrations were found in ruderal areas, followed by abandoned fields, but also in urbanized areas, including the UNESCO World Heritage historic city center. Seven invasive herbaceous species were identified (perennial herbs), compared to 10 invasive tree species, with phanerophytes being the most abundant life form. This likely reflects the predominant use of alien woody species for ornamental and reforestation purposes, as well as the greater resilience of woody and perennial species to the increasingly warm and dry conditions of the Mediterranean climate—a phenomenon exacerbated in recent years by climate change. Our findings suggest that the use of non-native species as ornamentals is the primary driver of the establishment, spread, and ecological impact of invasive plants in the study area. This study provides valuable insights into the current situation and the potential future trajectory of invasive species, facilitating the development of management strategies and restoration efforts to address the growing issue of biological invasions in the Mediterranean region.
Spatial Configuration and Sustainable Conservation of Ecotourism Resources in the Dabie Mountains, Eastern China, Using an Ecosystem Services Model
Authors: Hou Yingyue , Dai Yunchuan
Published: December 2024

Given the growing interest in sustainable tourism and the need to preserve ecological integrity, understanding how tourism resource development can coexist with biodiversity conservation is crucial, especially in ecologically sensitive regions. The Dabie Mountain region, with its rich biodiversity and cultural heritage, is a prime area for exploring the balance between tourism and environmental protection. Our study examined the spatial configuration of ecotourism resources in the Dabie Mountains, focusing on the role of ecosystem services, biodiversity hotspots, and traditional villages. Using the InVEST model, kernel density analysis, and a geographic detector, we found that the study area primarily consisted of lower-habitat-quality regions. Approximately 48,914.05 km2 (96.82% of the total area) was classified as low-quality habitat, presenting potential risks to biodiversity and ecosystem services in these regions. Higher habitat quality was observed in the eastern and southern regions, particularly in Yue Xi County, which exhibited superior biodiversity and habitat conditions compared to other administrative areas. Class V habitats, covering 39.89 km2 (31.69% of Class V area), were located in areas with greater terrain relief and proximity to water bodies, which contribute to higher biodiversity. This study identified a potential ecotourism development space of 649.79 km2, with a spatial distribution aligned with natural landscape features that support biodiversity conservation. Yue Xi and Jinzhai together accounted for 49.84% of the total ecotourism development space. Our study emphasizes the need to balance biodiversity conservation with tourism development, ensuring that ecotourism goals are met while preserving ecological integrity and cultural heritage. These findings provide a strong foundation for future research on biodiversity conservation in tourism development and offer insights for achieving sustainable ecological management in the region.
Adaptive Path Planning for Multi-UAV Systems in Dynamic 3D Environments: A Multi-Objective Framework
Authors: Airlangga Gregorius , Sukwadi Ronald , Basuki Widodo Widjaja , Sugianto Lai Ferry , Nugroho Oskar Ika Adi , Kristian Yoel , Rahmananta Radyan
Published: December 2024

This study evaluates and compares the computational performance and practical applicability of advanced path planning algorithms for Unmanned Aerial Vehicles (UAVs) in dynamic and obstacle-rich environments. The Adaptive Multi-Objective Path Planning (AMOPP) framework is highlighted for its ability to balance multiple objectives, including path length, smoothness, collision avoidance, and real-time responsiveness. Through experimental analysis, AMOPP demonstrates superior performance, with a 15% reduction in path length compared to A*, achieving an average path length of 450 m. Its angular deviation of 8.0° ensures smoother trajectories than traditional methods like Genetic Algorithm and Particle Swarm Optimization (PSO). Moreover, AMOPP achieves a 0% collision rate across all simulations, surpassing heuristic-based methods like Cuckoo Search and Bee Colony Optimization, which exhibit higher collision rates. Real-time responsiveness is another key strength of AMOPP, with an average re-planning time of 0.75 s, significantly outperforming A* and RRT*. The computational complexities of each algorithm are analyzed, with AMOPP exhibiting a time complexity of O(k·n) and a space complexity of O(n), ensuring scalability and efficiency for large-scale operations. The study also presents a comprehensive qualitative and quantitative comparison of 14 algorithms using 3D visualizations, highlighting their strengths, limitations, and suitable application scenarios. By integrating weighted optimization with penalty-based strategies and spline interpolation, AMOPP provides a robust solution for UAV path planning, particularly in scenarios requiring smooth navigation and adaptive re-planning. This work establishes AMOPP as a promising framework for real-time, efficient, and safe UAV operations in dynamic environments.
Enhancing Microcalcification Detection in Mammography with YOLO-v8 Performance and Clinical Implications
Authors: Shia Wei-Chung , Ku Tien-Hsiung
Published: December 2024

Background: Microcalcifications in the breast are often an early warning sign of breast cancer, and their accurate detection is crucial for the early discovery and management of the disease. In recent years, deep learning technology, particularly models based on object detection, has significantly improved the ability to detect microcalcifications. This study aims to use the advanced YOLO-v8 object detection algorithm to identify breast microcalcifications and explore its advantages in terms of performance and clinical application. Methods: This study collected mammograms from 7615 female participants, with a dataset including 10,323 breast images containing microcalcifications. We used the YOLO-v8 model for microcalcification detection and trained and validated the model using five-fold cross-validation. The model’s performance was evaluated through metrics such as accuracy, recall, F1 score, mAP50, and mAP50-95. Additionally, this study explored the potential applications of this technology in clinical practice. Results: The YOLO-v8 model achieved an mAP50 of 0.921, an mAP50-95 of 0.709, an F1 score of 0.82, a detection accuracy of 0.842, and a recall rate of 0.796 in breast microcalcification detection. Compared to previous similar deep learning object detection techniques like Mask R-CNN, YOLO-v8 has shown improvements in both speed and accuracy. Conclusions: YOLO-v8 outperforms traditional detection methods in detecting breast microcalcifications. Its multi-scale detection capability significantly enhances both speed and accuracy, making it more clinically practical for large-scale screenings. Future research should further explore the model’s potential in benign and malignant classification to promote its application in clinical settings, assisting radiologists in diagnosing breast cancer more efficiently.
Impact of Neutrophil-to-Lymphocyte Ratio on Stroke Severity and Clinical Outcome in Anterior Circulation Large Vessel Occlusion Stroke
Authors: Memiş Zülfikar , Gürkaş Erdem , Özdemir Atilla Özcan , Acar Bilgehan Atılgan , Ögün Muhammed Nur , Aytaç Emrah , Akpınar Çetin Kürşad , Akıl Eşref , Çabalar Murat , Özkul Ayça , Görgülü Ümit , Bayındır Hasan , Mehdiyev Zaur , Delibaş Katı Şennur , Baydemir Recep , Yabalak Ahmet , Önalan Ayşenur , Acar Türkan , Aykaç Özlem , Uysal Kocabaş Zehra , Yıldırım Serhan , Doğan Hasan , Arı Mehmet Semih , Çetiner Mustafa , Balgetir Ferhat , Eren Fettah , Eren Alper , Kızıldağ Nazım , Cenikli Utku , Şişman Bayar Aysel Büşra , Temel Ebru , Akbaş Alihan Abdullah , Saygın Uysal Emine , Gültekin Hamza , Durmaz Cebrail , Boncuk Ulaş Sena , Asil Talip
Published: December 2024

Background: The prognostic value of the neutrophil–lymphocyte ratio (NLR) in ischemic stroke remains debated due to cohort variability and treatment heterogeneity across studies. This study evaluates the relationship between admission NLR, stroke severity and 90-day outcomes in patients with anterior circulation large vessel occlusion (LVO) undergoing early, successful revascularization. Methods: A retrospective multicenter study was conducted with 1082 patients treated with mechanical thrombectomy for acute ischemic stroke. The relationship between admission NLR, baseline National Institutes of Health Stroke Scale (NIHSS), 24 h NIHSS and 90-day modified Rankin Scale (mRS) outcomes was analyzed using logistic regression. Results: Admission NLR correlated weakly but significantly with both baseline (p = 0.018) and 24 h (p = 0.005) NIHSS scores, reflecting stroke severity. However, multivariate analysis showed that higher 24 h NIHSS scores (OR 0.831, p = 0.000) and prolonged puncture-to-recanalization times (OR 0.981, p = 0.000) were independent predictors of poor 90-day outcomes, whereas NLR was not (p = 0.557). Conclusions: Admission NLR is associated with stroke severity but does not independently predict clinical outcomes at 90 days in patients achieving early and successful revascularization. These findings underscore the critical role of inflammation in the acute phase of stroke but suggest that its prognostic value for long-term outcomes is limited in this context.
Impact of Neurodynamic Sequencing on the Mechanical Behaviour of the Median Nerve and Brachial Plexus: An Ultrasound Shear Wave Elastography Study
Authors: Ciuffreda Gianluca , Estébanez-de-Miguel Elena , Albarova-Corral Isabel , Malo-Urriés Miguel , Shacklock Michael , Montaner-Cuello Alberto , Bueno-Gracia Elena
Published: December 2024

Background: When performing the Upper Limb Neurodynamic Test 1 (ULNT1), the order of joint movement can be varied to place more stress onto certain nerve segments. However, the mechanisms underlying this phenomenon are still unclear. This study aimed to analyze the differences in the stiffness of the median nerve (MN) and the brachial plexus (BP) using ultrasound shear wave elastography during three sequences of the ULNT1: standard (ULNT1-STD), distal-to-proximal (ULNT1-DIST), and proximal-to-distal (ULNT1-PROX). Methods: Shear wave velocity (SWV) was measured at the initial and final position of each sequence at the MN (wrist) and at the C5 and C6 nerve roots (interscalene level) in 31 healthy subjects. Results: A significant interaction was found between ULNT1 sequence and location (p < 0.001). The ULNT1-STD and ULNT1-DIST induced a greater stiffness increase in the MN (5.67 ± 0.91 m/s, +113.94%; 5.65 ± 0.98 m/s, +115.95%) compared to C5 and C6 (p < 0.001). The ULNT1-PROX resulted in a significantly smaller increase in stiffness at the MN (4.13 ± 0.86 m/s, +54.17%, p < 0.001), but a greater increase at C5 (4.88 ± 1.23 m/s, +53.39%, p < 0.001) and at C6 (4.87 ± 0.81 m/s, +31.55%). The differences for the ULNT1-PROX at C6 were only significant compared to the ULNT1-STD (p < 0.001), but not the ULNT1-DIST (p = 0.066). Conclusions: BP and MN stiffness vary depending on the joint movement sequence during neurodynamic testing. However, the influence of the surrounding tissues may have affected SWV measurements; consequently, these results should be interpreted with caution.
Establishment of Local Diagnostic Reference Levels for Head CT Imaging in the Madina Region, Saudi Arabia
Authors: Alhujaili Sultan F. , Alshabibi Abdulaziz S. , Alafer Feras , Alrowaili Ziyad , Salah Hasan , Sulieman Abdelmoneim , Subahi Mahmoud , Al-Raddadi Khaled , Abuzaid Mohamed
Published: December 2024

Background: Computed Tomography (CT) is crucial in medical diagnosis, particularly for head examinations. Diagnostic Reference Levels (DRLs) are pivotal in balancing diagnostic efficacy with radiation safety. International organizations such as the International Atomic Energy Agency (IAEA) and the International Commission on Radiological Protection (ICRP) provide guidelines for establishing DRLs, emphasizing their importance in optimizing radiation doses. Aim: This study aimed to establish and standardize DRLs for head CT imaging in institutional and regional settings, emphasizing the need for tailored reference levels specific to each region’s practices and standards. Method: Data collection included patient demographics, imaging parameters, and radiation dose indices, namely volume-weighted CT dose index (CTDIvol) and dose-length product (DLP). Statistical analyses were conducted to determine the median and 3rd quartile values for establishing DRLs. The results were compared with national and international benchmarks to assess variations in radiation doses across regions. Results: Demographic profiles detailed gender distributions and ages across hospitals. Imaging parameters exhibited variability in tube voltage, milliampere-seconds (mAs), pitch, scan length, and field of view (FOV). For CTDIvol, the 3rd quartile value was 65.8 mGy (range: 24.8–85.9 mGy), and for DLP, it was 1230.95 mGy·cm (range: 382.3–1189.0 mGy·cm). These values were slightly higher than the national DRLs for Saudi Arabia in 2021 and other international benchmarks, underscoring the need for further optimization and alignment of protocols. Conclusion: Optimizing and standardizing DRLs for head CT imaging is crucial for effectively managing radiation doses while ensuring diagnostic accuracy. Comparison with national and international benchmarks highlighted the importance of tailoring reference levels to regional practices and standards, ensuring patient safety without compromising diagnostic efficacy.
Fully Automated Assessment of Cardiac Chamber Volumes and Myocardial Mass on Non-Contrast Chest CT with a Deep Learning Model: Validation Against Cardiac MR
Authors: Schmitt Ramona , Schlett Christopher L. , Sperl Jonathan I. , Rapaka Saikiran , Jacob Athira J. , Hein Manuel , Hagar Muhammad Taha , Ruile Philipp , Westermann Dirk , Soschynski Martin , Bamberg Fabian , Schuppert Christopher
Published: December 2024

Background: To validate the automated quantification of cardiac chamber volumes and myocardial mass on non-contrast chest CT using cardiac MR (CMR) as a reference. Methods: We retrospectively included 53 consecutive patients who received non-contrast chest CT and CMR within three weeks. A deep learning model created cardiac segmentations on axial soft-tissue reconstructions from CT, covering all four cardiac chambers and the left ventricular myocardium. Segmentations on CMR cine short-axis and long-axis images served as a reference. Standard estimates of diagnostic accuracy were calculated for ventricular volumes at end-diastole and end-systole (LVEDV, LVESV, RVEDV, RVESV), left ventricular mass (LVM), and atrial volumes (LA, RA) at ventricular end-diastole. A qualitative assessment noted segmentation issues. Results: The deep learning model generated CT measurements for 52 of the 53 patients (98%). Based on CMR measurements, the average LVEDV was 166 ± 64 mL, RVEDV was 144 ± 51 mL, and LVM was 115 ± 39 g. The CT measurements correlated well with CMR measurements for LVEDV, LVESV, and LVM (ICC = 0.85, ICC = 0.84, and ICC = 0.91; all p < 0.001) and RVEDV and RVESV (ICC = 0.79 and ICC= 0.78; both p < 0.001), and moderately well with LA and RA (ICC = 0.74 and ICC = 0.61; both p < 0.001). Absolute agreements likewise favored LVEDV, LVM, and RVEDV. ECG-gating did not relevantly influence the results. The CT results correctly identified 7/15 LV and 1/1 RV as dilated (one and six false positives, respectively). Major qualitative issues were found in three cases (6%). Conclusions: Automated cardiac chamber volume and myocardial mass quantification on non-contrast chest CT produced viable measurements in this retrospective sample. Relevance Statement: An automated cardiac assessment on non-contrast chest CT provides quantitative morphological data on the heart, enabling a preliminary organ evaluation that aids in incidentally identifying at-risk patients who may benefit from a more targeted diagnostic workup.
Three-Dimensional Measurements of Sphenoid Sinus Size by Sex in a Korean Population: An Exploratory Study
Authors: Lee Jeong-Hyun , Park Jong-Tae
Published: December 2024

Background/Objectives: This study aims to investigate the three-dimensional morphological differences of the sphenoid sinus according to sex in the Korean adult population and conduct an exploratory study based on the findings. The sphenoid sinus, located deep within the skull, plays a crucial role in forensic identification due to its relative protection from external damage and its unique anatomical characteristics. Methods: Using cone-beam computed tomography (CBCT) data from 120 patients (60 males and 60 females) aged 20–29, the sphenoid sinus was visualized and measured in three dimensions using Mimics software (version 22.0). Measurements included the volume of the sphenoid sinus, as well as its dimensions in the X, Y, and Z axes. The measured data were analyzed using SPSS (version 23.0) with a t-test and linear regression analysis. Results: The results showed that the sphenoid sinus volume was significantly larger in males compared to females (p < 0.05), with an average male sinus volume of 16,957.9 mm3 and a female volume of 13,517.7 mm3. Additionally, the X-width, Y-width, and Z-width were all larger in males, with significant differences (p < 0.001) across all dimensions. Further regression analysis revealed that the volume of the sphenoid sinus was primarily influenced by the Z-axis height (measured from the coronal view) and the Y-axis width (measured from the sagittal view), while the X-axis width had a negligible effect on the overall volume. Conclusions: These findings suggest that sex-specific differences in the sphenoid sinus may provide important insights for clinical diagnoses and forensic personal identification. This study highlights the need for further research on different age groups and ethnic populations to enhance the understanding of anatomical variations in the sphenoid sinus and their potential applications in both medical and forensic fields.
Dimensional Accuracy of Intraoral Scanners in Recording Digital Impressions of Post and Core Preparations: A Systematic Review
Authors: Alqahtani Saeed M. , Almalki Mohammed Salman , Almarzouki Mai , AlResayes Saad Saleh , Hassan Nisreen Nabiel , Mohana Arwa Jaber I. , Altoman Majed S. , Sayed Mohammed E.
Published: December 2024

Background: This study aims to perform a review by selecting, analyzing, and evaluating articles that discuss the accuracy of intraoral scanners (IOSs) in recording post space compared to conventional impression-making techniques. Methods: The review question framed using the PITR framework (participant, index test, targeted condition, and reference standard) is as follows: What is the dimensional accuracy (T) of impressions made using intraoral scanners (I) for post space (P) compared to impressions made using conventional techniques and digitalized using extraoral scanners (R)? Four electronic databases were searched using pre-set keywords. The guidelines and strategies recommended by PRISMA formed the basis for planning, executing, and documenting this systematic review. QUADAS-2 was used to critically analyze the quality of all the selected articles. Results: After excluding ineligible articles, the end synthesis has nine studies (n = 9) for qualitative analysis. All nine evaluated studies were found to be at risk of bias, with high or unclear risk in one or more domains. Three out of nine evaluated studies had unclear concerns regarding the applicability, and the remaining six had low concerns. In all the included studies, the IOSs were reported to have deviations in accuracy compared to the conventional techniques for making digital impressions of post space. Conclusions: The accuracy of IOSs was found to be inversely proportional to the length of post space and directly proportional to the diameter of post space. IOSs, when used adequately in short post spaces, can be an alternative to conventional impression-making for making custom posts and cores.
Health and Liver Diagnostic Markers Influencing Glycemia in Subjects with Prediabetes: Preview Study
Authors: Ramos-Lopez Omar , Martinez-Urbistondo Diego , Navas-Carretero Santiago , Zhu Ruixin , Huttunen-Lenz Maija , Stratton Gareth , Handjieva-Darlenska Teodora , Handjiev Svetoslav , Sundvall Jouko Ensio , Silvestre Marta P. , Jalo Elli , Pietiläinen Kirsi H. , Adam Tanja C. , Westerterp-Plantenga Margriet , Simpson Elizabeth , MacDonald Ian , Taylor Moira A. , Poppitt Sally D. , Schlicht Wolfgang , Brand-Miller Jennie , Fogelholm Mikael , Raben Anne , Martinez J. Alfredo
Published: December 2024

Introduction: Glucose homeostasis may be dependent on liver conditions and influence health-related markers and quality of life (QoL) objective measurements. This study aimed to analyze the interactions of glycemia with liver and health status in a prediabetic population. Subjects and methods: This study included 2220 overweight/obese prediabetics from the multinational PREVIEW project. Anthropometrics; clinical, metabolic and other health-related markers; and QoL variables were analyzed. Univariate and multilinear-adjusted regression models were run to explain the interrelationships and effect modification between glycemia, health-related QoL (applying SF-12) and metabolic/liver health (using the HSI, a putative marker of fatty liver). Results: Relevant age/sex interactions were found concerning the levels of insulin, HOMA-IR, C peptide and transaminases in this prediabetic population. Multivariate models identified age, sex, glucose, WC and QoL as important predictors of HSI variability (adj. R value = 0.1393, p < 0.001), whereas the QoL status was statistically related to age, sex, HOMA-IR and HSI (adj. R value = 0.1130, p < 0.001) in this glycemia-impaired group. Furthermore, the QoL values declined with increased HSI scores, where a significant interaction was found (p = 0.011) when the data were analyzed when comparing lower glycemia vs. higher glycemia in prediabetics. Indeed, an effect modification was featured depending on the glycemia levels concerning the QoL and HSI worsening. Conclusion: Glycemia associations with the QoL status and liver metabolism markers were evidenced, with clinical implications for diabetes and liver disease precision management given the modification of the QoL outcomes depending on the liver status and glycemia concentrations. Notably, independent associations of circulating glucose with age, sex, adiposity, inflammation and C peptide levels were found.
Coverage Path Planning for UAVs: An Energy-Efficient Method in Convex and Non-Convex Mixed Regions
Authors: Wang Li , Zhuang Xiaodong , Zhang Wentao , Cheng Jing , Zhang Tao
Published: December 2024

As an important branch of path planning, coverage path planning (CPP) is widely used for unmanned aerial vehicles (UAVs) to cover target regions with lower energy consumption. Most current works focus on convex regions, whereas others need pre-decomposition to deal with non-convex or mixed regions. Therefore, it is necessary to pursue a concise and efficient method for the latter. This paper proposes a two-stage method named Shrink-Segment by Dynamic Programming (SSDP), which aims to cover mixed regions with limited energy. First, instead of decomposing and then planning, SSDP formulates an optimal path by shrinking the rings for mixed regions. Second, a dynamic programming (DP)-based approach is used to segment the overall path for UAVs in order to meet energy limits. Experimental results show that the proposed method achieves less path overlap and lower energy consumption compared to state-of-the-art methods.
Computing Entropy for Long-Chain Alkanes Using Linear Regression: Application to Hydroisomerization
Authors: Sharma Shrinjay , Baur Richard , Rigutto Marcello , Zuidema Erik , Agarwal Umang , Calero Sofia , Dubbeldam David , Vlugt Thijs J. H.
Published: December 2024

Entropies for alkane isomers longer than C10 are computed using our recently developed linear regression model for thermochemical properties which is based on second-order group contributions. The computed entropies show excellent agreement with experimental data and data from Scott’s tables which are obtained from a statistical mechanics-based correlation. Entropy production and heat input are calculated for the hydroisomerization of C7 isomers in various zeolites (FAU-, ITQ-29-, BEA-, MEL-, MFI-, MTW-, and MRE-types) at 500 K at chemical equilibrium. Small variations in these properties are observed because of the differences in reaction equilibrium distributions for these zeolites. The effect of chain length on heat input and entropy production is also studied for the hydroisomerization of C7, C8, C10, and C14 isomers in MTW-type zeolite at 500 K. For longer chains, both heat input and entropy production increase. Enthalpies and absolute entropies of C7 hydroisomerization reaction products in MTW-type zeolite increase with higher temperatures. These findings highlight the accuracy of our linear regression model in computing entropies for alkanes and provide insight for designing and optimizing zeolite-catalyzed hydroisomerization processes.
Problem of Existence of Joint Distribution on Quantum Logic
Authors: Nánásiová Oľga , Čipková Karla , Zákopčan Michal
Published: December 2024

This paper deals with the topics of modeling joint distributions on a generalized probability space. An algebraic structure known as quantum logic is taken as the basic model. There is a brief summary of some earlier published findings concerning a function s-map, which is a mathematical tool suitable for constructing virtual joint probabilities of even non-compatible propositions. The paper completes conclusions published in 2020 and extends the results for three or more random variables if the marginal distributions are known. The existence of a (n+1)-variate joint distribution is shown in special cases when the quantum logic consists of at most n blocks of Boolean algebras.
Instructional Design Models for Pervasive Learning Environment: Bridging Formal and Informal Learning in Collaborative Social Learning
Authors: Suartama I Kadek , Yasa I Nyoman , Triwahyuni Eges
Published: December 2024

In Indonesia, there is a significant gap between the skills, creativity, innovation abilities, and job awareness of college graduates as well as the demands of the modern workforce. This gap originates from a curriculum and learning design that has not kept pace with the rapidly evolving needs of society. In an era characterized by digitalization and the rapid development of technology, content, infrastructure, human, and environmental resources, it is essential to create an open and pervasive learning environment (PLE). Therefore, this research aimed to describe the design process and determine the feasibility and validity of a PLE model that integrated formal and informal cooperative social learning. Research and Development (R&D) for Education model was adopted in this study following the phases of analysis, design, development, and evaluation (ADDIE). Furthermore, the research procedure included two main stages, namely the development of the PLE model and validation of the product. The product validation process further included 13 experts in material design, 15 experts in learning media, and 95 students from state and private universities across Indonesia. Subsequently, descriptive statistical analysis was used in analyzing the obtained data from the validation process. The results showed that the developed PLE model design has utilized the power of technology, social interaction, and everyday environment, both formally and informally. The developed learning model design was suitable for implementation in educational settings. This learning design model offers a comprehensive, flexible, and inclusive learning ecosystem that is tailored to the needs of the twenty-first century.
The Effects of Social Identity Incompatibility on Student Mental Health
Authors: Harrold Katie , Fett Anne Kathrin , Haenschel Corinna
Published: December 2024

Background: Students from ethnic minority backgrounds have been shown to be more vulnerable to developing mental health disorders compared to White British students. They have also been shown to experience greater social identity incompatibility; however, it is not yet clear if this may explain some of the disparities in mental health. The aim of the current study was to investigate the relationship between social identity incompatibility and non-clinical generalised anxiety, depression and academic distress in students from ethnic minority backgrounds compared to White students. Methods: A total of 526 students from City St George’s, University of London, completed the Counselling Centre Assessment of Psychological Symptoms (CCAPS-62) and the student identity scale. Results: Results showed correlations between the measures of mental health and incompatibility across all students. Even though there were no significant group differences in the level of anxiety and depression, we found that the interaction between ethnic group and practical incompatibility predicted academic distress. Conclusions: The results may be specific to the multi-ethnic and cultural nature of this inner London city university, but they highlight the importance of practical incompatibility, in particular, in understanding student mental health across different ethnicities.
Research-Based Learning About Nature Conservation Influences Students’ Attitudes and Knowledge
Authors: Restović Ivana , Bulic Mila
Published: December 2024

(1) Background: A successful teaching practice and a proper understanding of environmental conservation require developed research abilities and a positive attitude toward nature. Nineteen female students at the Faculty of Humanities and Social Sciences spent ten days in one national park and participated in project activities related to nature conservation. This study aimed to investigate how the stay in nature and the active involvement of students will contribute to their attitudes and knowledge acquisition. (2) Methods: A questionnaire was used to assess the students’ attitudes and knowledge about protected areas before and after the project activities in the national park. The Wilcoxon test was used to determine the statistical significance of differences in attitudes, while the Chi-square test was used to examine the differences in their acquired knowledge. (3) Results: The research showed that students had positive attitudes towards nature protection before and after the project activities. The positive attitudes were confirmed after the project activities were carried out even among those students who did not have them initially. A significant increase in students’ knowledge after the ten-day stay in the national park was noticed. (4) Conclusions: The study results have provided insight into the ability of future teachers to promote sustainable lifestyles and ecological activities. Hands-on nature-based learning significantly foster future teachers’ ecological awareness, their environmental knowledge, attitudes, and behavior.
Using Artificial Intelligence to Support Peer-to-Peer Discussions in Science Classrooms
Authors: Billings Kelly , Chang Hsin-Yi , Lim-Breitbart Jonathan M. , Linn Marcia C.
Published: December 2024

In successful peer discussions students respond to each other and benefit from supports that focus discussion on one another’s ideas. We explore using artificial intelligence (AI) to form groups and guide peer discussion for grade 7 students. We use natural language processing (NLP) to identify student ideas in science explanations. The identified ideas, along with Knowledge Integration (KI) pedagogy, informed the design of a question bank to support students during the discussion. We compare groups formed by maximizing the variety of ideas among participants to randomly formed groups. We embedded the chat tool in an earth science unit and tested it in two classrooms at the same school. We report on the accuracy of the NLP idea detection, the impact of maximized versus random grouping, and the role of the question bank in focusing the discussion on student ideas. We found that the similarity of student ideas limited the value of maximizing idea variety and that the question bank facilitated students’ use of knowledge integration processes.
Developing an Effective System for Engineering Management Education: A Teaching Practice and Evaluation Perspective
Authors: Zhao Tengfei , Zhu Jianlin , Jian Zhiyu , Zhou Xian , Yang Siling , Zhang Puwei
Published: December 2024

In the field of engineering management, teaching emphasizes the cultivation of applied talents within the context of new engineering disciplines. Evaluating the effectiveness of this cultivation is particularly necessary. The evaluation system for teaching effectiveness plays a crucial role in enhancing teaching quality, promoting students’ comprehensive development, and driving educational reforms. In recent years, there have been numerous research achievements on the evaluation system for practice-oriented teaching quality. However, compared with other disciplines, the field of engineering management remains in its infancy. Therefore, this study clarified the ability goals that talents in this major should possess by studying the evaluation indicators of teaching effectiveness in the field. Based on an emphasis on cultivating different abilities, a practical teaching effectiveness evaluation system was constructed. This study used the Delphi method and the analytic hierarchy process (AHP) to construct a teaching evaluation indicator system for engineering management majors. The system assigns weights to each indicator based on the “Four Abilities”, including professional competence, practical skills, innovation abilities, and employability. This results in the establishment of a relatively scientific and reasonable teaching effectiveness evaluation system. Furthermore, based on the research results, teaching reform studies related to ability cultivation in the “Building Structures” course were carried out. The teaching effectiveness was verified through post-class student feedback, and a student assessment method was established. This study contributes to a better understanding of the path of practical teaching reform and provides a reference value for teaching practice research in related majors.
Manipulability-Aware Task-Oriented Grasp Planning and Motion Control with Application in a Seven-DoF Redundant Dual-Arm Robot
Authors: Wong Ching-Chang , Tsai Chi-Yi , Lai Yu-Cheng , Wong Shang-Wen
Published: December 2024

Task-oriented grasp planning poses complex challenges in modern robotics, requiring the precise determination of the grasping pose of a robotic arm to grasp objects with a high level of manipulability while avoiding hardware constraints, such as joint limits, joint over-speeds, and singularities. This paper introduces a novel manipulability-aware (M-aware) grasp planning and motion control system for seven-degree-of-freedom (7-DoF) redundant dual-arm robots to achieve task-oriented grasping with optimal manipulability. The proposed system consists of two subsystems: (1) M-aware grasp planning; and (2) M-aware motion control. The former predicts task-oriented grasp candidates from an RGB-D image and selects the best grasping pose among the candidates. The latter enables the robot to select an appropriate arm to perform the grasping task while maintaining a high level of manipulability. To achieve this goal, we propose a new manipulability evaluation function to evaluate the manipulability score (M-score) of a given robot arm configuration with respect to a desired grasping pose to ensure safe grasping actions and avoid its joint limits and singularities. Experimental results demonstrate that our system can autonomously detect the graspable areas of a target object, select an appropriate grasping pose, grasp the target with a high level of manipulability, and achieve an average success rate of about 98.6%.
Power-Optimized Field-Programmable Gate Array Implementation of Neural Activation Functions Using Continued Fractions for AI/ML Workloads
Authors: Hingu Chanakya , Fu Xingang , Saliyu Taofiki , Hu Rui , Mishan Ramkrishna
Published: December 2024

The increasing demand for energy-efficient hardware platforms to support artificial intelligence (AI) and machine learning (ML) algorithms in edge computing has driven the adoption of system-on-chip (SoC) architectures. Implementing neural network (NN) activation functions, such as the hyperbolic tangent (tanh), on hardware presents challenges due to computational complexity, high resource requirements, and power consumption. This paper aims to optimize the hardware implementation of the tanh function using continued fraction and polynomial approximations to minimize resource consumption and power usage while preserving computational accuracy. Five models of the tanh function, including continued fraction and quadratic approximations, were implemented on Intel field-programmable gate arrays (FPGAs) using VHDL and Intel’s ALTFP toolbox, with 32-bit floating-point outputs validated against MATLAB’s 64-bit floating-point results. Detailed analyses of resource utilization, power optimization, clock latency, and bit-level accuracy were conducted, focusing on minimizing logic elements and digital signal processing (DSP) blocks while achieving high precision and low power consumption. The most optimized model was further integrated into a four-input, two-output recurrent neural network (RNN) structure to assess real-time performance. Experimental results demonstrate that the continued fraction-based models significantly reduce resource usage, computation time, and power consumption, enhancing FPGA performance for AI/ML applications in resource-constrained and power-sensitive environments.
Classification of Multi-Value Chain Business Data Resources Based on Semantic Association
Authors: Fan Bo , Sun Linfu , Tan Dong , Han Min
Published: December 2024

Focusing on the classification of business data resources within a unified business semantic environment is an important method to simplify the data environment and a crucial approach to studying data intelligence. A multi-value chain data space is a typical business semantic heterogeneous complex data environment. This paper summarizes the characteristics of multi-value chain business data resources and proposes a study on their classification using business semantic logic. By constructing a semantic-based relational model for multi-value chain business data resources and a multi-value chain business lexicon, this paper unifies the semantics of business data resources. This creates conditions for their classification according to business logic. Based on the feature transformation of business data resources, this paper proposes a clustering algorithm for multi-value chain business data resources (Business data resource classification algorithm for multi-value chain data space, BDRCA4MVCDS) aimed at a data space, completing the classification of business data resources. Finally, comparative experiments with KMeans and KABSA demonstrate the clustering effectiveness of the proposed algorithm (BDRCA4MVCDS) as well as its good stability and adaptability.