bluuebunny/crossref_metadata_2025_split huggingface dataset:
A comparative analysis of pairwise image stitching techniques for microscopy images
Authors: Mohammadi Fatemeh Sadat , Mohammadi Seyyed Erfan , Mojarad Adi Parsa , Mirkarimi Seyed Mohammad Ali , Shabani Hasti 
Published: April 2024

AbstractStitching of microscopic images is a technique used to combine multiple overlapping images (tiles) from biological samples with a limited field of view and high resolution to create a whole slide image. Image stitching involves two main steps: pairwise registration and global alignment. Most of the computational load and the accuracy of the stitching algorithm depend on the pairwise registration method. Therefore, choosing an efficient, accurate, robust, and fast pairwise registration method is crucial in the whole slide imaging technique. This paper presents a detailed comparative analysis of different pairwise registration techniques in terms of execution time and quality. These techniques included feature-based methods such as Harris, Shi-Thomasi, FAST, ORB, BRISK, SURF, SIFT, KAZE, MSER, and deep learning-based SuperPoint features. Additionally, region-based methods were analyzed, which were based on the normalized cross-correlation (NCC) and the combination of phase correlation and NCC. Investigations have been conducted on microscopy images from different modalities such as bright-field, phase-contrast, and fluorescence. The feature-based methods were highly robust to uneven illumination in tiles. Moreover, some features were found to be more accurate and faster than region-based methods, with the SURF features identified as the most effective technique. This study provides valuable insights into the selection of the most efficient and accurate pairwise registration method for creating whole slide images, which is essential for the advancement of computational pathology and biology.
Application and comparative analysis of Intelligent Monitoring Technology for Grouted Pile Construction based on abaqus
Authors: Wu Rong , Jiang Yangyang , Zhao Shunzhi , Chen Min , Shang Shiqiang , Lang Xuedong 
Published: April 2024

AbstractIn order to realize the intelligent monitoring of the high-precision positioning of the hole position and the real-time control of the verticality of the pile, an intelligent monitoring system was developed based on the combination positioning technology of BDS and UWB and the biaxial tilt sensor, and the numerical simulation and comparative analysis of the verticality of the pile were carried out by abaqus. The deviation of pile foundation in different directions and the deviation of pile body are controlled by the monitoring system, and abnormal warning is made when the deviation exceeds the permissible range.Through the application of intelligent monitoring system in the pile foundation engineering area of Changshui Airport, it is found that the plane offset and perpendicularity of all piles meet the standard requirements and the construction error is controlled at a small value. The results show that the application of intelligent inspection system can not only ensure the construction quality of pile foundation, but also meet and improve the level of digitization and information technology of smart construction site.
Evaluating the effect of unidirectional loading on the piezoresistive characteristics of carbon nanoparticles
Authors: Alderete Bruno , Mücklich Frank , Suarez Sebastian 
Published: April 2024

AbstractThe piezoresistive effect of materials can be adopted for a plethora of sensing applications, including force sensors, structural health monitoring, motion detection in fabrics and wearable, etc. Although metals are the most widely adopted material for sensors due to their reliability and affordability, they are significantly affected by temperature. This work examines the piezoresistive performance of carbon nanoparticle (CNP) bulk powders and discusses their potential applications based on strain-induced changes in their resistance and displacement. The experimental results are correlated with the characteristics of the nanoparticles, namely, dimensionality and structure. This report comprehensively characterizes the piezoresistive behavior of carbon black (CB), onion-like carbon (OLC), carbon nanohorns (CNH), carbon nanotubes (CNT), dispersed carbon nanotubes (CNT-D), graphite flakes (GF), and graphene nanoplatelets (GNP). The characterization includes assessment of the ohmic range, load-dependent electrical resistance and displacement tracking, a modified gauge factor for bulk powders, and morphological evaluation of the CNP. Two-dimensional nanostructures exhibit promising results for low loads due to their constant compression-to-displacement relationship. Additionally, GF could also be used for high load applications. OLC’s compression-to-displacement relationship fluctuates, however, for high load it tends to stabilize. CNH could be applicable for both low and high loading conditions since its compression-to-displacement relationship fluctuates in the mid-load range. CB and CNT show the most promising results, as demonstrated by their linear load-resistance curves (logarithmic scale) and constant compression-to-displacement relationship. The dispersion process for CNT is unnecessary, as smaller agglomerates cause fluctuations in their compression-to-displacement relationship with negligible influence on its electrical performance.
Effects of different treatments on pain, functional disability, position sense and range of motion in elite bodybuilders with chronic low back pain
Authors: Papoli Amirmohammad Faal , Hosseini Seyed Mohammad , Mirkarimpour Seyed Hossein 
Published: April 2024

AbstractBack pain is one of the major global challenges and is one of the most prevalent musculoskeletal disorders occurring in 80% of people at least once in their lifetime. Therefore, the need to find appropriate treatment methods for this issue is very important. The objective is to examine the short-term and acute effects of a treatment session with dry needling, massage therapy, stretching exercises and Kinesio tape on pain, functional disability, position sense and range of motion in elite bodybuilders with non-specific chronic low back pain. The sample of this quasi-experimental study consisted of 48 bodybuilders with non-specific chronic low back pain (all male, mean age = 25.96 ± 2.18 years; mean weight = 74.45 ± 4.51 kg; mean height = 173.88 ± 3.74 cm; mean BMI = 24.60 ± 0.74 kg/m2) who randomly were placed in 4 dry needling, massage therapy, stretching exercises and Kinesio tape groups. The duration of each intervention was 30 min. The dependent variables in this study included the massage range of motion, position sense tests and visual pain scale that were taken separately from each subject in pretest, posttest (acute effect) and follow-up test (72 h after posttest; short-term effect). The results of a 4 (groups) × 3 (time) the mixed ANOVAs showed that pain in the short-term phase was significantly lower in the dry needling group than in the stretching and massage groups (P < 0.05). Also in the acute effect phase, the flexion range of motion was significantly lower in the dry needling group than in the massage group (P < 0.05). Furthermore, the two groups of stretching and massage exercises showed significantly greater range of motion (P < 0.05). Other comparisons were not significant (P > 0.05). The findings of the study showed that both massage and stretching treatment have higher acute effects, while dry needling treatment was more effective in follow up. On the other hand, these findings show that these treatment methods can have immediate and lasting positive effects in improving the performance in elite bodybuilders with non-specific chronic low back pain.
Design of three-component essential oil extract mixture from Cymbopogon flexuosus, Carum carvi, and Acorus calamus with enhanced antioxidant activity
Authors: Assaggaf Hamza , Jeddi Mohamed , Mrabti Hanae Naceiri , Ez-zoubi Amine , Qasem Ahmed , Attar Ammar , Goh Bey Hing , Tan Sang Loon , Bouyahya Abdelhakim , Goh Khang Wen , Hachlafi Naoufal El 
Published: April 2024

AbstractThe development of novel antioxidant compounds with high efficacy and low toxicity is of utmost importance in the medicine and food industries. Moreover, with increasing concerns about the safety of synthetic components, scientists are beginning to search for natural sources of antioxidants, especially essential oils (EOs). The combination of EOs may produce a higher scavenging profile than a single oil due to better chemical diversity in the mixture. Therefore, this exploratory study aims to assess the antioxidant activity of three EOs extracted from Cymbopogon flexuosus, Carum carvi, and Acorus calamus in individual and combined forms using the augmented-simplex design methodology. The in vitro antioxidant assays were performed using DPPH and ABTS radical scavenging approaches. The results of the Chromatography Gas-Mass spectrometry (CG-MS) characterization showed that citral (29.62%) and niral (27.32%) are the main components for C. flexuosus, while d-carvone (62.09%) and d-limonene (29.58%) are the most dominant substances in C. carvi. By contrast, β-asarone (69.11%) was identified as the principal component of A. calamus (30.2%). The individual EO exhibits variable scavenging activities against ABTS and DPPH radicals. These effects were enhanced through the mixture of the three EOs. The optimal antioxidant formulation consisted of 20% C. flexuosus, 53% C. carvi, and 27% A. calamus for DPPHIC50. Whereas 17% C. flexuosus, 43% C. carvi, and 40% A. calamus is the best combination leading to the highest scavenging activity against ABTS radical. These findings suggest a new research avenue for EOs combinations to be developed as novel natural formulations useful in food and biopharmaceutical products.
Optimization and establishment of laboratory rearing conditions for Cimex lectularius L. against variable temperature and relative humidity
Authors: Banerjee Amartya , Saha Achintya , Das Parikshit , Kakati Ajay , Saha Buddhadeb , Goyary Danswrang , Bhutia Yangchen D. , Karmakar Sanjeev , Kishor Sumit , Rahaman Saidur , Chattopadhyay Pronobesh 
Published: April 2024

AbstractEmerging infestations of bed bugs are affecting normal human lifestyle globally. This study has been designed to optimize the rearing conditions for Cimex lectularius L. (Hemiptera), to support the scientific research on them. Bed bugs have been projected onto three different temperature (20 °C, 25 °C, and 30 °C) and relative humidity (50%, 70%, and 90%) conditions to check their overall growth and survival rate. Adult mortality, weight loss, egg laying, percentage hatching, hatching initiation and completion, nymph mortality, and molting have been evaluated to optimize the best conditions. The temperature at 25 °C with 90% RH showed minimum mortality for adults (female 13.33 ± 3.33% and male 6.67 ± 3.33%) and nymphs (13.33 ± 3.33%), while maximum egg laying (40.33 ± 1.86), with highest percentage hatching (98.23 ± 0.58%). At 30 °C with 90% RH, hatching initiation and completion (5.19 ± 0.12 days and 7.23 ± 0.16 days) as well as molting initiation and completion (3.73 ± 0.12 days and 7.00 ± 0.24 days) were found to be fastest. Thus, it can be concluded that 25 °C with 90% RH is ideal for rearing of adults and 30 °C with 90% RH is appropriate for rapid growth of nymphs.
Molecular dynamics simulations suggest the potential toxicity of fluorinated graphene to HP35 protein via unfolding the α-helix structure
Authors: Zou Fangrong , Gu Zonglin , Perez-Aguilar Jose Manuel , Luo Yuqi 
Published: April 2024

AbstractFluorinated graphene, a two-dimensional nanomaterial composed of three atomic layers, a central carbon layer sandwiched between two layers of fluorine atoms, has attracted considerable attention across various fields, particularly for its potential use in biomedical applications. Nonetheless, scant effort has been devoted to assessing the potential toxicological implications of this nanomaterial. In this study, we scrutinize the potential impact of fluorinated graphene on a protein model, HP35 by utilizing extensive molecular dynamics (MD) simulation methods. Our MD results elucidate that upon adsorption to the nanomaterial, HP35 undergoes a denaturation process initiated by the unraveling of the second helix of the protein and the loss of the proteins hydrophobic core. In detail, substantial alterations in various structural features of HP35 ensue, including alterations in hydrogen bonding, Q value, and RMSD. Subsequent analyses underscore that hydrophobic and van der Waals interactions (predominant), alongside electrostatic energy (subordinate), exert influence over the adsorption of HP35 on the fluorinated graphene surface. Mechanistic scrutiny attests that the unrestrained lateral mobility of HP35 on the fluorinated graphene nanomaterial primarily causes the exposure of HP35's hydrophobic core, resulting in the eventual structural denaturation of HP35. A trend in the features of 2D nanostructures is proposed that may facilitate the denaturation process. Our findings not only substantiate the potential toxicity of fluorinated graphene but also unveil the underlying molecular mechanism, which thereby holds significance for the prospective utilization of such nanomaterials in the field of biomedicine.
Enhanced high β-carotene yeast cell production by Rhodotorula paludigena CM33 and in vitro digestibility in aquatic animals
Authors: Thumkasem Namphet , On-mee Thapanut , Kongsinkaew Chatchol , Chittapun Supenya , Pornpukdeewattana Soisuda , Ketudat-Cairns Mariena , Thongprajukaew Karun , Antimanon Sompot , Charoenrat Theppanya 
Published: April 2024

AbstractThis study assessed Rhodotorula paludigena CM33's growth and β-carotene production in a 22-L bioreactor for potential use as an aquatic animal feed supplement. Optimizing the feed medium's micronutrient concentration for high-cell-density fed-batch cultivation using glucose as the carbon source yielded biomass of 89.84 g/L and β-carotene concentration of 251.64 mg/L. Notably, using sucrose as the carbon source in feed medium outperforms glucose feeds, resulting in a β-carotene concentration of 285.00 mg/L with a similar biomass of 87.78 g/L. In the fed-batch fermentation using Sucrose Feed Medium, R. paludigena CM33 exhibited high biomass production rates (Qx) of 0.91 g/L.h and remarkable β-carotene production rates (Qp) of 2.97 mg/L.h. In vitro digestibility assays showed that R. paludigena CM33, especially when cultivated using sucrose, enhances protein digestibility affirming its suitability as an aquatic feed supplement. Furthermore, R. paludigena CM33's nutrient-rich profile and probiotic potential make it an attractive option for aquatic nutrition. This research highlights the importance of cost-effective carbon sources in large-scale β-carotene production for aquatic animal nutrition.
Development of grey wolf optimization based modified fast terminal sliding mode controller for three phase interleaved boost converter fed PV system
Authors: Krishnaram K. , Suresh Padmanabhan T. , Alsaif Faisal , Senthilkumar S. 
Published: April 2024

AbstractThe conventional MPPT method has drawbacks, such as that under partial shading conditions, several peaks occur and identifying the global peak is difficult. It may converge to a local peak and lead to poor conversion efficiency and tracking efficiency. Implementation of a hybrid algorithm by integrating P&O and metaheuristic algorithms can perform better under partial shading conditions. But the tracking speed is low and the response time is longer. To mitigate the issues mentioned above, a new hybrid algorithm has been suggested that integrates GWO and a modified fast terminal sliding mode controller (MFTSMC). The suggested method with three phase ILBC is incorporated into the PV system. The MATLAB tool is employed to experiment with this study. The performance of GWO-MFTSMC is analysed through MATLAB/ SIMULINK and compared with the performance of ANN-FTSMC and PSO-FTSMC algorithm based MPPT techniques. A hardware prototype is developed and tested for 5 × 200 W solar PV modules with the GWO-MFTSMC algorithm. The proposed method conversion efficiency is 99.72% and 96.15% under simulation and hardware realisation, respectively, which is higher than the ANN-FTSMC and PSO-FTSMC methods.
Inducing perceived group variability triggers the incorporation of counter-stereotypic information into a generalized stereotype change
Authors: Santos Ana Sofia , Garcia-Marques L. , Palma T. A. , Reese J. 
Published: April 2024

AbstractPerceived variability is the extent to which individuals perceive group members as being similar to one another. Previous research has focused on how: group variability is perceived (and measured); information indicative of group heterogeneity can lead to reductions in stereotypicality; or how stereotype-inconsistent information can result into increased perceived variability. The present combines the three lines of research into a single research venue. In previous studies the stereotypicality of a group representation was influenced by priming stereotype-unrelated traits in an unrelated-context, prior to stereotype measurement; but priming counter-stereotypic traits had no effect on stereotypicality, although it boosted perceptions of group's variability. The present study examines whether highlighting dissimilarities among members of the same professional groups results in subsequent changes in the reported stereotype for a, not yet mentioned, group. The more the dissimilarity among group members, the more likely individuals were to incorporate counter-stereotypic information into the targeted-group, described as less stereotypic, even in central tendency measures. Importantly, the generating mechanism may involve a modification of participants' overall perception of variability. When members within professional groups are perceived as dissimilar, the well-known resistance of stereotypes to counter-stereotypic information is lessened making the group representations more flexible and less biased.
Do AI models produce better weather forecasts than physics-based models? A quantitative evaluation case study of Storm Ciarán
Authors: Charlton-Perez Andrew J. , Dacre Helen F. , Driscoll Simon , Gray Suzanne L. , Harvey Ben , Harvey Natalie J. , Hunt Kieran M. R. , Lee Robert W. , Swaminathan Ranjini , Vandaele Remy , Volonté Ambrogio 
Published: April 2024

AbstractThere has been huge recent interest in the potential of making operational weather forecasts using machine learning techniques. As they become a part of the weather forecasting toolbox, there is a pressing need to understand how well current machine learning models can simulate high-impact weather events. We compare short to medium-range forecasts of Storm Ciarán, a European windstorm that caused sixteen deaths and extensive damage in Northern Europe, made by machine learning and numerical weather prediction models. The four machine learning models considered (FourCastNet, Pangu-Weather, GraphCast and FourCastNet-v2) produce forecasts that accurately capture the synoptic-scale structure of the cyclone including the position of the cloud head, shape of the warm sector and location of the warm conveyor belt jet, and the large-scale dynamical drivers important for the rapid storm development such as the position of the storm relative to the upper-level jet exit. However, their ability to resolve the more detailed structures important for issuing weather warnings is more mixed. All of the machine learning models underestimate the peak amplitude of winds associated with the storm, only some machine learning models resolve the warm core seclusion and none of the machine learning models capture the sharp bent-back warm frontal gradient. Our study shows there is a great deal about the performance and properties of machine learning weather forecasts that can be derived from case studies of high-impact weather events such as Storm Ciarán.
Developing countries can adapt to climate change effectively using nature-based solutions
Authors: Villamayor-Tomas Sergio , Bisaro Alexander , Moull Kevin , Albizua Amaia , Mank Isabel , Hinkel Jochen , Leppert Gerald , Noltze Martin 
Published: April 2024

AbstractEvidence on the effectiveness of climate change adaptation interventions in low- and middle-income countries has been rapidly growing in recent years, particularly in the agricultural and coastal sectors. Here we address the question of whether results are consistent across intervention types, and risk reduction versus development-related outcomes using a systematic review of 363 empirical observations published in the scientific literature. Generally, we found more evidence of risk reduction outcomes in the coastal sector than in the agricultural sector, and more evidence of development-related outcomes in the agricultural sector. Further, results indicate that nature-based solutions have the strongest positive effects for both the coastal and agricultural sectors. Social/behavioural interventions in the coastal sector show negative effects on development-related outcomes that will need to be further tested. Taken together, our results highlight the opportunity for development and climate adaptation practitioners to promote adaptation interventions with co-benefits beyond risk reduction, particularly in the case of nature-based solutions.
Practical approaches in evaluating validation and biases of machine learning applied to mobile health studies
Authors: Allgaier Johannes , Pryss Rüdiger 
Published: April 2024

Abstract
Background
Machine learning (ML) models are evaluated in a test set to estimate model performance after deployment. The design of the test set is therefore of importance because if the data distribution after deployment differs too much, the model performance decreases. At the same time, the data often contains undetected groups. For example, multiple assessments from one user may constitute a group, which is usually the case in mHealth scenarios.

Methods
In this work, we evaluate a model’s performance using several cross-validation train-test-split approaches, in some cases deliberately ignoring the groups. By sorting the groups (in our case: Users) by time, we additionally simulate a concept drift scenario for better external validity. For this evaluation, we use 7 longitudinal mHealth datasets, all containing Ecological Momentary Assessments (EMA). Further, we compared the model performance with baseline heuristics, questioning the essential utility of a complex ML model.

Results
Hidden groups in the dataset leads to overestimation of ML performance after deployment. For prediction, a user’s last completed questionnaire is a reasonable heuristic for the next response, and potentially outperforms a complex ML model. Because we included 7 studies, low variance appears to be a more fundamental phenomenon of mHealth datasets.

Conclusions
The way mHealth-based data are generated by EMA leads to questions of user and assessment level and appropriate validation of ML models. Our analysis shows that further research needs to follow to obtain robust ML models. In addition, simple heuristics can be considered as an alternative for ML. Domain experts should be consulted to find potentially hidden groups in the data.
Enabling white color tunability in complex 3D-printed composites by using lead-free self-trapped exciton 2D perovskite/carbon quantum dot inks
Authors: Luangwanta Tawanwit , Turren-Cruz Silver-Hamil , Masi Sofia , Das Adhikari Samrat , Recalde Ileana B. , Zanatta Marcileia , Iglesias Diego , Rodríguez-Pereira Jhonatan , Gené-Marimon Santi , Martinez-Ferrero Eugenia , Kaowphong Sulawan , Palomares Emilio , Sans Victor , Gualdrón-Reyes Andrés F. , Mora-Seró Iván 
Published: April 2024

This work reports a facile preparation of lead-free self-trapped exciton 2D A2SnX4 perovskite/carbon quantum dot inks with tunable white-light emission for luminescent 3D printed composites, and potential application in optoelectronic devices.