Miracle-dz/UniFAR-FTUs huggingface dataset:
A Preliminary Study on Grip-Induced Nerve Damage Caused by a Soft Pneumatic Elastomeric Gripper

Forceps, clamps, and haemostats are essential surgical tools required for all surgical interventions. While they are widely used to grasp, hold, and manipulate soft tissue, their metallic rigid structure may cause tissue damage due to the potential risk of applying excessive gripping forces. Soft pneumatic surgical grippers fabricated by silicone elastomeric materials with low Young’s modulus may offer a promising solution to minimize this unintentional damage due to their inherent excellent compliance and compressibility. The goal of this work is to evaluate and compare the grip-induced nerve damage caused by the soft pneumatic elastomeric gripper and conventional haemostats during surgical manipulation. Twenty-four Wistar rats (male, seven weeks) are subjected to sciatic nerve compression (right hind limb) using the soft pneumatic elastomer gripper and haemostats. A histopathological analysis is conducted at different time-points (Day 0, Day 3, Day 7 and Day 13) after the nerve compression to examine the morphological tissue changes between the rats in the ‘soft gripper’ group and the ‘haemostats’ group. A free walking analysis is also performed to examine the walking function of the rats after recovery from different time points. Comparing the rigid haemostats and soft gripper groups, there is a visible difference in the degree of axonal vacuolar degeneration between the groups, which could suggest the presence of substantial nerve damage in the ‘haemostats’ group. The rats in the haemostats group exhibited reduced right hind paw pressure and paw size after the nerve compression. It shows that the rats tend not to exert more force on the affected right hind limb in the haemostats group compared to the soft gripper group. In addition, the stance duration was reduced in the injured right hind limb compared to the normal left hind limb in the haemostats group. These observations show that the soft pneumatic surgical gripper made of silicone elastomeric materials might reduce the severity of grip-induced damage by providing a safe compliant grip compared to the conventional haemostats. The soft pneumatic elastomer gripper could complement the current surgical gripping tool in delicate tissue manipulation.
How Instagram Influencers Contribute to Consumer Travel Decision: Insights from SEM and fsQCA

In recent years, social media influencers (SMIs) have become independent entities capable of influencing their audiences. Businesses look towards SMIs on Instagram as a marketing communication tool due to their popularity and effectiveness. In tourism, few studies investigate the role of SMI in influencing travel behaviors. The study examines how SMI can influence Instagram followers' travel behaviors. This study determined SMI based on attractiveness, similarity, and expertise. SMI can generate parasocial interactions with followers and build trust by promoting destinations based on these three dimensions. This study tested the research hypothesis on 364 respondents using a dual-approach analysis of structural equation modeling and fuzzy set qualitative comparative analysis. The results of the SEM analysis confirm that consumers were more likely to trust SMI based on their expertise and similarity. Also, this study demonstrated that highly attractive SMI and similarity with followers can lead to parasocial interactions. When consumers trust and feel parasocial interaction with SMI, they are more likely to consider traveling. FsQCA results confirm the presence of two configurations with high travel intention. The causal conditions configuration presented in this study demonstrated the interdimensional relationship between SMIs (attractiveness, similarity, and expertise), trust, and parasocial interaction in terms of travel intention. This study also achieved theoretical contributions and managerial implications on how scholars and tourism managers leverage SMIs to create high travel intentions. Doi: 10.28991/ESJ-2023-07-01-02 Full Text: PDF
Phylogeography of Rotavirus G8P[8] Detected in Argentina: Evidence of Transpacific Dissemination

Rotavirus is one of the leading causes of diarrhea in children. In 2018, G8P[8], an unusual association of genotypes, was detected with moderate frequency in symptomatic children in Argen-tina, unlike a previous sporadic identification in 2016. The aim of this study was to analyze the dissemination pattern of the G8P[8]-lineage IV strains detected in Argentina. Nucleotide sequences of the VP7 gene of Argentine G8P[8] strains (2016, 2018 and 2019) were studied by discrete phylodynamic analyses, together with other worldwide relevant G8-lineage IV strains. Bayes Factor (BF) was used to assess the strength of the epidemiological association between countries. Phylodynamic analyses determined an evolutionary rate of 3.7 × 10−3 (HDP95%: 1.4 × 10−3–8.2 × 10−3) substitutions/site/year. Likewise, the most recent common ancestor was 32.2 years old, dating back to 1986 (HDP95% = 1984–1988). The spatiotemporal dynamics analysis revealed South Korea as being the country of origin of the Argentine strains (posterior probability of the ancestral state: 0.8471), which was also evidenced by a significant rate of diffusion from South Korea to Argentina (BF: 55.1). The detection of G8 in South America in 2016–2017 was not related to the cases detected in 2018–2019, revealing a new G8 introduction to the region and supporting a transpacific dissemination.
Finite element modelling and experimental verification of timber halved and tabled scarf joints

Carpentry joints are very common in existing timber structures and they may gain attention for contemporary structures, due to their high degree of reversibility. Therefore, reliable Finite Element (FE) models for carpentry joints can contribute to assessing their capacity and provide a better insight into the parameters influencing their mechanical properties. This paper presents a FE study (using Abaqus) of timber halved-and-tabled scarf joints, together with experimental results. The FE-model considers fracture due to combined shear and tension perpendicular-to-grain by using cohesive zone modelling. Experimental tests on spruce solid timber specimens were performed to validate the model. The specimens were constructed by the use of a CNC-machine. For comparative purposes, two handmade specimens were tested, resulting in a lower load capacity. The FE results showed that initial gaps have a considerable effect on capacity. For certain assumed initial gaps, the FE-model could predict the capacity, however, it underestimated the deformation.
Sliding Window Soft-SCL Decoders for Asynchronous Polar-Coded Modulation

Asynchronous polar-coded modulation (A-PCM) outperforms multilevel polar-coded modulation by taking advantage of spatial coupling among several coded blocks. To further improve the performance of A-PCM, a cyclic-redundancy-check (CRC) aided sliding window soft successive cancellation list (CA-SWSCL) decoder is proposed to exploit the benefits of spatial coupling and CRC-aided iterative message passing. This approach includes both soft-output and hard-output iteration processes, where the CRC results are not only used for early termination but also served as an execution flag of the hard-output iteration process. In the case of rate half polar-coded modulation with frame length 128, A-PCM with the proposed CA-SWSCL achieves the best block-error-rate (BLER) performance among the state-of-art polar-coded modulation schemes.
SOC estimation of lithium-ion battery at low temperature

The evolution of interfacial compatibility, stability of electronic impedance, ion migration mechanisms at grain boundaries and molecular dynamics properties within lithium-ion batteries under low-temperature conditions greatly challenges the prediction of the state of charge. In the present study, considering that the lithium-ion battery is susceptible to the operating temperature environment, an improved second-order RC equivalent circuit model is developed, and the parameters of the temperature model are identified by the least squares method to verify the accuracy of the model parameters. The extended Kalman filter algorithm is used to estimate the SOC value. The improved model and algorithm have high accuracy in a low-temperature environment, which is a method for battery SOC prediction under low-temperature conditions of lithium-ion batteries and an effective guarantee for stable operation and safe use of lithium-ion batteries at low temperatures.
Epigenetics of COVID-19 infected lung: systematic review and meta-analysis of gene expression data

Objective: To investigate homogeneity and efficiency of applicating models of lung/bronchial organoids for SARS-COV2 infection research and evaluate the role of differentially expressed cytokine genes of interest. Methods: in this systematic review and meta-analysis of Gene Expression ombious datasets, studies of lung/bronchial organoids as models of SARS-COV2 infection were evaluated. 4 datasets of GSE160435, GSE148697, GSE150819, and GSE152060 were selected for our study. DESeq / EdgeR technique was used to identify Differential Expressed Genes (DEGs). Results: the distribution of the pooled dataset showed small variations among the 4 selected datasets. K-means cluster analysis using the KEGG Pathway database revealed activation of a cluster of genes in response to coronavirus diseases including 51 genes in the pathway of KEGG, that could verify the organoids in comparison of real COVID-19 disease specimens. proinflammatory cytokines and Granulocyte-macrophage colony-stimulating factors were selected as our genes of interest-based on the literature. We only found significant upregulation of TNF-alpha, IL23A, and IL17A genes and significant Dowiregulation of CSF2RB, IL20RB/A, IL24B. while downregulation of CSF2 was in controversy with reported literature. Conclusion: Based on the data that ultimately reached the conclusion of the interferon 1 function in COVID-19 pathology, this work may confirm the models of SARS-COV-2 infection in lung organoids;nevertheless, the contradiction to real-world studies requires more research.
Bioactivity-Guided Fractionation and Identification of Antidiabetic Compound of Syzygium polyanthum (Wight.)’s Leaf Extract in Streptozotocin-Induced Diabetic Rat Model

(1) Background: An earlier study on the hypoglycemic activity of S. polyanthum (Wight.) leaf methanol extract identified squalene as the major chemical compound. The present study was conducted to assess the hypoglycemic effect of fractions and subfractions of the methanol extract of S. polyanthum compared to the squalene using a bioassay-guided in vivo study. (2) Methods: The methanol extract was fractionated using the liquid–liquid fractionation method. Streptozotocin-induced type 1 diabetic rat was used to study the hypoglycemic effect. (3) Results: The findings showed that chloroform fraction significantly (p < 0.05) lowered blood glucose levels of diabetic rats as compared to the control. Further fractionation of chloroform fraction yielded subfraction-1 and -2, whereby subfraction-1 exhibited a higher blood-glucose-lowering effect. The lipid profile test showed that the total cholesterol level of subfraction-1 and squalene-treated groups decreased significantly (p < 0.05). An immunohistochemistry study revealed that none of the treatments regenerated pancreatic β-cells. Gas chromatography–mass spectrophotometer analysis identified the presence of squalene in the active methanol extract, chloroform fraction, and subfraction-1. In silico analysis revealed a higher affinity of squalene against protein receptors that control lipid metabolism than metformin. (4) Conclusions: Data obtained from the present work suggested the crude methanol extract exerted the highest hypoglycemic effect compared to fraction, subfraction, and squalene, confirming synergistic effect may be responsible for the hypoglycemic activity of S. polyanthum.
Al2C4H2 Isomers with the Planar Tetracoordinate Carbon (ptC)/Aluminum (ptAl)

Forty-one isomers of Al2C4H2 that lie within 50 kcal mol−1 are theoretically identified in this work using density functional theory. Among these, isomers 3 and 14 contain a planar tetracoordinate carbon (ptC) atom that lies at 3.3 and 16.9 kcal mol−1, respectively, and are above the global minimum geometry 1 at the ωB97XD/6-311++G(2d,2p) level of theory. The other ten isomers that also contain unique bonding features are isomers 4, 18, 20, 21, 22, 27, 28, 31, 34, and 40. Out of these isomers, 4, 18, 20, 22, 27, 28, and 34 contain planar tetracoordinate aluminum (ptAl) whereas isomers 31 and 40 contain both ptC and ptAl atoms. Chemical bonding characteristic features are thoroughly analyzed for all these eleven isomers with various bonding and topological quantum chemical tools, such as NBO, AdNDP, WBI, and ELF, except isomer 27 due to the observed elongated Al-Al bond length. The current results indicate that ptC isomer 3 is more stable than other isomers because electron delocalization is more prevalent and it also has double aromaticity as observed from the ELF, NICS, and AdNDP analysis. Further, the structural stability of these isomers is investigated through ab initio molecular dynamics (AIMD) simulation. Isomer 21 shows the planar pentacoordinate aluminum but it is observed as a kinetically unstable geometry from AIMD and, further, one could notice that it isomerizes to isomer 12.
A Particleboard Surface Defect Detection Method Research Based on the Deep Learning Algorithm

Particleboard surface defects have a significant impact on product quality. A surface defect detection method is essential to enhancing the quality of particleboard because the conventional defect detection method has low accuracy and efficiency. This paper proposes a YOLO v5-Seg-Lab-4 (You Only Look Once v5 Segmentation-Lab-4) model based on deep learning. The model integrates object detection and semantic segmentation, which ensures real-time performance and improves the detection accuracy of the model. Firstly, YOLO v5s is used as the object detection network, and it is added into the SELayer module to improve the adaptability of the model to receptive field. Then, the Seg-Lab v3+ model is designed on the basis of DeepLab v3+. In this model, the object detection network is utilized as the backbone network of feature extraction, and the expansion rate of atrus convolution is reduced to the computational complexity of the model. The channel attention mechanism is added onto the feature fusion module, for the purpose of enhancing the feature characterization capabilities of the network algorithm as well as realizing the rapid and accurate detection of lightweight networks and small objects. Experimental results indicate that the proposed YOLO v5-Seg-Lab-4 model has mAP (Mean Average Precision) and mIoU (Mean Intersection over Union) of 93.20% and 76.63%, with a recognition efficiency of 56.02 fps. Finally, a case study of the Huizhou particleboard factory inspection is carried out to demonstrate the tiny detection accuracy and real-time performance of this proposed method, and the missed detection rate of surface defects of particleboard is less than 1.8%.
Sequential Bayes Factors for Sample Size Reduction in Preclinical Experiments with Binary Outcomes

Abstract Preclinical studies are an integral part of pharmaceutical drug development, yet traditional methods for designing and analyzing these types of studies can be inefficient and wasteful. Even worse, when the units of study are animals, ethical concerns can arise. The 3Rs initiative was established for the ethical treatment of animals through the replacement, reduction, and refinement of animal experiments. In this article, we focus on the reduction aspect of the 3Rs initiative through the use of sequential Bayes factors. The use of sequential Bayes factors has the potential to help design more efficient experiments, that can be analyzed sequentially, in order to reduce the average number of animals needed in preclinical studies. An added bonus, sequential Bayes factors provide a means of quantifying evidence both for and against the null hypothesis, a characteristic not common to traditional preclinical trial analysis methods. Illustrations highlighting the success of sequential Bayes factors are provided for two real seven-day preclinical experiments in rats, as well as extensive simulation studies.
Assessment of the Impact of a Toll-like Receptor 2 Agonist Synthetic Lipopeptide on Macrophage Susceptibility and Responses to African Swine Fever Virus Infection

Toll-like receptor 2 (TLR2) ligands are attracting attention as prophylactic and immunopotentiator agents against pathogens, including viruses. We previously reported that a synthetic diacylated lipopeptide (Mag-Pam2Cys_P48) polarized porcine macrophages towards a proinflammatory antimicrobial phenotype. Here, we investigated its role in modulating monocyte-derived macrophage (moMΦ) responses against African swine fever virus (ASFV), the etiological agent of one of the greatest threats to the global pig industry. Two ASFV isolates were compared: the attenuated NH/P68 and the virulent 26544/OG10. No effect on virus infection nor the modulation of surface markers’ expression (MHC I, MHC II DR, CD14, CD16, and CD163) were observed when Mag-Pam2Cys_P48 treated moMΦ were infected using a multiplicity of infection (MOI) of 1. Mag-Pam2Cys_P48 treated moMΦ released higher levels of IL-1α, IL-1β, IL-1Ra, and IL-18 in response to infection with NH/P68 ASFV compared to 26544/OG10-infected and mock-infected controls. Surprisingly, when infected using a MOI of 0.01, the virulent ASFV 26544/OG10 isolate replicated even slightly more efficiently in Mag-Pam2Cys_P48 treated moMΦ. These effects also extended to the treatment of moMΦ with two other lipopeptides: Mag-Pam2Cys_P80 and Mag-Pam2Cys_Mag1000. Our data suggested limited applicability of TLR2 agonists as prophylactic or immunopotentiator agents against virulent ASFV but highlighted the ability of the virulent 26544/OG10 to impair macrophage defenses.
Variations of dose rate observed by MSL/RAD in transit to Mars

Aims: To predict the cruise radiation environment related to future human missions to Mars, the correlation between solar modulation potential and the dose rate measured by the Radiation Assessment Detector (RAD) has been analyzed and empirical models have been employed to quantify this correlation. Methods: The instrument RAD, onboard Mars Science Laboratory's (MSL) rover Curiosity, measures a broad spectrum of energetic particles along with the radiation dose rate during the 253-day cruise phase as well as on the surface of Mars. With these first ever measurements inside a spacecraft from Earth to Mars, RAD observed the impulsive enhancement of dose rate during solar particle events as well as a gradual evolution of the galactic cosmic ray (GCR) induced radiation dose rate due to the modulation of the primary GCR flux by the solar magnetic field, which correlates with long-term solar activities and heliospheric rotation. Results: We analyzed the dependence of the dose rate measured by RAD on solar modulation potentials and estimated the dose rate and dose equivalent under different solar modulation conditions. These estimations help us to have approximate predictions of the cruise radiation environment, such as the accumulated dose equivalent associated with future human missions to Mars. Conclusions: The predicted dose equivalent rate during solar maximum conditions could be as low as one-fourth of the current RAD cruise measurement. However, future measurements during solar maximum and minimum periods are essential to validate our estimations.
Recent Advances in Plant-Mediated Zinc Oxide Nanoparticles with Their Significant Biomedical Properties

Compared to traditional physical and chemical approaches, nanobiotechnology and plant-based green synthesis procedures offer significant advantages, as well as having a greater range of medical and biotechnological applications. Nanoparticles of zinc oxide (ZnO NPs) have recently been recognized as a promising option for many industries, including optics, electrics, packaged foods, and medicine, due to their biocompatibility, low cytotoxicity, and cost-effectiveness. Several studies have shown that zinc ions are important in triggering cell apoptosis by promoting the generation of reactive oxygen species (ROSs) and releasing zinc ions (Zn2+), which are toxic to cells. The toxic nature of the chemicals used in the synthesis of ZnO nanoparticles limits their clinical utility. An overview of recent developments in green ZnO NP synthesis is presented in this review, emphasizing plant parts as reducing agents and their medical applications, including their antimicrobial, anticancer, antioxidant, and anti-inflammatory properties, as well as key mechanisms of action for these applications to facilitate further research on the biomedical fields in the future.
Tensors, non-Gaussianities, and the future of potential reconstruction

We present projections for reconstruction of the inflationary potential expected from ESA's upcoming Planck Surveyor CMB mission. We focus on the effects that tensor perturbations and the presence of non-Gaussianities have on reconstruction efforts in the context of non-canonical inflation models. We consider potential constraints for different combinations of detection/null-detection of tensors and non-Gaussianities. We perform Markov Chain Monte Carlo and flow analyses on a simulated Planck-precision data set to obtain constraints. We find that a failure to detect non-Gaussianities precludes a successful inversion of the primordial power spectrum, greatly affecting uncertainties, even in the presence of a tensor detection. In the absence of a detection of tensors, we will be unable to determine the energy scale of inflation. However, a detection of non-Gaussianity will allow us to place tight constraints on suitably chosen combinations of the potential and its derivatives. Constraints are optimized for a positive detection of both tensors and non-Gaussianities.
Chiral Solutions to Generalized Burgers and Burgers-Huxley Equations

We investigate generalizations of the Burgers and Burgers-Huxley equations. The investigations we offer focus attention mainly on presenting explict analytical solutions by means of relating these generalized equations to relativistic 1+1 dimensional systems of scalar fields where topological solutions are known to play a role. Emphasis is given on chiral solutions, that is, on the possibility of finding solutions that travel with velocities determined in terms of the parameters that identify the generalized equation, with a definite sign.
Molecular Characterization of Wild and Cultivated Strawberry (Fragaria × ananassa) through DNA Barcode Markers

Background DNA barcoding is a useful technique for the identification, conservation, and diversity estimation at the species level in plants. The current research work was carried out to characterize selected Fragaria species from northern Pakistan using DNA barcode markers. Methodology. Initially, the efficacy of eight DNA barcode markers was analyzed based on the amplification and sequencing of the genome of selected Fragaria species. The resultant sequences were analyzed using BLAST, MEGA 7.0, and Bio Edit software. The phylogenetic tree was constructed by using Fragaria current species sequences and reference sequences through the neighbor-joining method or maximum likelihood method. Results Among eight DNA barcode markers, only two (ITS2 and rbclC) were amplified, and sequences were obtained. ITS2 sequence was BLAST in NCBI for related reference species which ranged from 89.79% to 90.05% along with Fragaria vesca (AF163517.1) which have 99.05% identity. Similarly, the rbclC sequence of Fragaria species was ranged from 96% to 99.58% along with Fragaria × ananassa (KY358226.1) which had 99.58% identity. Conclusion It is recommended that DNA barcode markers are a useful tool to identify the genetic diversity of a species. Moreover, this study could be helpful for the identification of the Fragaria species cultivated in other regions of the world.