Miracle-dz/UniFAR-FTUs huggingface dataset:
IoT-enabled cloud-based additive manufacturing platform to support rapid product development

Additive Manufacturing (AM) with its unique capabilities provides a new way of rapid product development. The emerging Cloud Manufacturing paradigm makes it much easier to access various AM resources with minimum investment. Distributed recourses can also be utilised more efficiently. However, the current cloud platforms mainly focus on providing simple 3D printing services, rather than support the customers throughout the product development process, from design, to process planning, and to printing. Therefore, a new cloud platform is proposed to integrate not only hard resources such as 3D printers and materials, but also soft resources such as the know-how and test data to provide supports on printing as well as design and process planning. Internet of Things provides new capabilities to the cloud platform, enabling customers to remotely control and monitor the printing process. The paper also examined the feasibility of Artificial Neural Networks for surface defect detection. The platform is able to work in dynamic and iterative product development processes and reduce development time and cost. An illustrative platform is developed to demonstrate the functionalities.
NKG2A Expression among CD8 Cells Is Associated with COVID-19 Progression in Hypertensive Patients: Insights from the BRACE CORONA Randomized Trial

Cardiovascular comorbidities and immune-response dysregulation are associated with COVID-19 severity. We aimed to explore the key immune cell profile and understand its association with disease progression in 156 patients with hypertension that were hospitalized due to COVID-19. The primary outcome was progression to severe disease. The probability of progression to severe disease was estimated using a logistic regression model that included clinical variables and immune cell subsets associated with the primary outcome. Obesity; diabetes; oxygen saturation; lung involvement on computed tomography (CT) examination; the C-reactive protein concentration; total lymphocyte count; proportions of CD4+ and CD8+ T cells; CD4/CD8 ratio; CD8+ HLA-DR MFI; and CD8+ NKG2A MFI on admission were all associated with progression to severe COVID-19. This study demonstrated that increased CD8+ NKG2A MFI at hospital admission, in combination with some clinical variables, is associated with a high risk of COVID-19 progression in hypertensive patients. These findings reinforce the hypothesis of the functional exhaustion of T cells with the increased expression of NKG2A in patients with severe COVID-19, elucidating how severe acute respiratory syndrome coronavirus 2 infection may break down the innate antiviral immune response at an early stage of the disease, with future potential therapeutic implications.
Psychometrics of the SDQ-I for Palestinian Adolescent Students

The Self-description Questionnaire–I (SDQ–I) is a multidimensional instrument that measures eight self-concept facets hypothesized in Shavelson’s hierarchical model. This study investigated self-concept in a sample of Palestinian adolescent students using an Arabic version of the SDQ–I. Three-hundred sixty adolescents (163 girls and 197 boys) aged 13 to 16 years (M = 14.3, SD = .87) participated. The 72-item SDQ–I was administered in four Palestinian schools to assess the psychometric properties of the SDQ–I. This included the factor structure and the internal consistency reliability of the SDQ–I subscales and mean score responses of Palestinian self-concept. Factor analysis results, which accounted for the majority of the variance, supported an underlying general self-concept factor structure that demonstrated the eight factors that the SDQ–I is designed to measure. This is consistent with previous studies in similar age groups and the SDQ– I reliabilities were similar to those reported in the literature. Students perceived total self-concept positively (mean = 3.71). Three facets of self-concept (parent relations, reading, and general self-concept) indicated high positive selfconcept. Correlations among the different dimensions were consistent with the hierarchical structure in Shavelson’s model. Overall, the findings provided compelling support for Shavelson’s model, and the structure validity of Western self-concept measure. Interpretations were provided for the discrepancies regarding the Palestinian-Arab culture.
Amplification paramétrique et réduction de bruit quantique dans les microcavités semi-conductrices

Cette these presente des resultats d'optique quantique sur des effets coherents dans des microcavites semi-conductrices, constituee d'un puits quantique place dans une cavite Fabry-Perot resonante. Le confinement des excitons et des photons permet d'atteindre le regime de couplage fort. Sous excitation resonante, on obtient de l'amplification parametrique des polaritons, les modes propres du systeme. Dans la configuration non degeneree, on met en evidence un regime de bistabilite, sous des conditions analogues a celles dans les OPO. Dans la configuration degeneree, le melange a quatre ondes coherent en phase est de type Kerr. Comme pour les atomes froids, on observe de la bistabilite et la reduction du bruit en dessous de la limite quantique standard. En regime de couplage fort, le champ comprime est de nature mixte rayonnement-matiere. On prend en compte des effets transverses qui modifient l'extension spatiale des polaritons, dont on caracterise les proprietes de coherence spatiale.
Toward Exempting from Sentinel Lymph Node Biopsy in T1 Breast Cancer Patients: A Retrospective Study

Background and Objective Sentinel lymph node biopsy (SLNB) is used to assess the status of axillary lymph node (ALN), but it causes many adverse reactions. Considering the low rate of sentinel lymph node (SLN) metastasis in T1 breast cancer, this study aims to identify the characteristics of T1 breast cancer without SLN metastasis and to select T1 breast cancer patients who avoid SLNB through constructing a nomogram. Methods A total of 1,619 T1 breast cancer patients with SLNB in our hospital were enrolled in this study. Through univariate and multivariate logistic regression analysis, we analyzed the tumor anatomical and clinicopathological factors and constructed the Heilongjiang Medical University (HMU) nomogram. We selected the patients exempt from SLNB by using the nomogram. Results In the training cohort of 1,000 cases, the SLN metastasis rate was 23.8%. Tumor volume, swollen axillary lymph nodes, pathological types, and molecular subtypes were found to be independent predictors for SLN metastasis in multivariate regression analysis. Distance from nipple or surface and position of tumor have no effect on SLN metastasis. A regression model based on the results of the multivariate analysis was developed to predict the risk of SLN metastasis, indicating an AUC of 0.798. It showed excellent diagnostic performance (AUC = 0.773) in the validation cohort. Conclusion The HMU nomogram for predicting SLN metastasis incorporates four variables, including tumor volume, swollen axillary lymph nodes, pathological types, and molecular subtypes. The SLN metastasis rates of intraductal carcinoma and HER2 enriched are 2.05% and 6.67%. These patients could be included in trials investigating the SLNB exemption.
Hybrid Approach for Detecting and Classifying Power Quality Disturbances Based on the Variational Mode Decomposition and Deep Stochastic Configuration Network

This paper proposes a novel, two-stage and hybrid approach based on variational mode decomposition (VMD) and the deep stochastic configuration network (DSCN) for power quality (PQ) disturbances detection and classification in power systems. Firstly, a VMD technique is applied to discriminate between stationary and non-stationary PQ events. Secondly, the key parameters of VMD are determined as per different types of disturbance. Three statistical features (mean, variance, and kurtosis) are extracted from the instantaneous amplitude (IA) of the decomposed modes. The DSCN model is then developed to classify PQ disturbances based on these features. The proposed approach is validated by analytical results and actual measurements. Moreover, it is also compared with existing methods including wavelet network, fuzzy and S-transform (ST), adaptive linear neuron (ADALINE) and feedforward neural network (FFNN). Test results have proved that the proposed method is capable of providing necessary and accurate information for PQ disturbances in order to plan PQ remedy actions accordingly.
The complete mitochondrial genome of Megalurothrips usitatus (Bagnall 1913) (Thysanoptera: Thripidae) and its phylogenetic analysis

Abstract Megalurothrips usitatus is a serious pest on Vigna unguiculata. In this study, the complete mitochondrial genome sequence of M. usitatus was characterized and its phylogenetic relationship within the Order Thysanoptera was determined. The mitochondrial genome of M. usitatus was a circular molecule of 15426 bp in length, containing 13 protein-coding genes, 2 rRNA genes, 22 tRNA genes, and the control region. It showed the typical insect mitochondrial genome arrangement. The AT content of the whole genome was 77.69% and the length of the control region was 567 bp with 78.66% AT content. The Maximum likelihood (ML) phylogenetic analysis based on mitochondrial protein-coding genes of 17 insect speciesshowed that M. usitatus is closest to Frankliniella occidentalis.
Selection of Optimal Hyperspectral Wavebands for Detection of Discolored, Diseased Rice Seeds

The inspection of rice grain that may be infected by seedborne disease is important for ensuring uniform plant stands in production fields as well as preventing proliferation of some seedborne diseases. The goal of this study was to use a hyperspectral imaging (HSI) technique to find optimal wavelengths and develop a model for detecting discolored, diseased rice seed infected by bacterial panicle blight (Burkholderia glumae), a seedborne pathogen. For this purpose, the HSI data spanning the visible/near-infrared wavelength region between 400 and 1000 nm were collected for 500 sound and discolored rice seeds. For selecting optimal wavelengths to use for detecting diseased seed, a sequential forward selection (SFS) method combined with various spectral pretreatments was employed. To evaluate performance based on optimal wavelengths, support vector machine (SVM) and linear and quadratic discriminant analysis (LDA and QDA) models were developed for detection of discolored seeds. As a result, the violet and red regions of the visible spectrum were selected as key wavelengths reflecting the characteristics of the discolored rice seeds. When using only two or only three selected wavelengths, all of the classification methods achieved high classification accuracies over 90% for both the calibration and validation sample sets. The results of the study showed that only two to three wavelengths are needed to differentiate between discolored, diseased and sound rice, instead of using the entire HSI wavelength regions. This demonstrates the feasibility of developing a low cost multispectral imaging technology based on these selected wavelengths for non-destructive and high-throughput screening of diseased rice seed.
PKC-Mediated Orai1 Channel Phosphorylation Modulates Ca2+ Signaling in HeLa Cells

The overexpression of the Orai1 channel inhibits SOCE when using the Ca2+ readdition protocol. However, we found that HeLa cells overexpressing the Orai1 channel displayed enhanced Ca2+ entry and a limited ER depletion in response to the combination of ATP and thapsigargin (TG) in the presence of external Ca2+. As these effects require the combination of an agonist and TG, we decided to study whether the phosphorylation of Orai1 S27/S30 residues had any role using two different mutants: Orai1-S27/30A (O1-AA, phosphorylation-resistant) and Orai1-S27/30D (O1-DD, phosphomimetic). Both O1-wt and O1-AA supported enhanced Ca2+ entry, but this was not the case with O1-E106A (dead-pore mutant), O1-DD, and O1-AA-E106A, while O1-wt, O1-E106A, and O1-DD inhibited the ATP and TG-induced reduction of ER [Ca2+], suggesting that the phosphorylation of O1 S27/30 interferes with the IP3R activity. O1-wt and O1-DD displayed an increased interaction with IP3R in response to ATP and TG; however, the O1-AA channel decreased this interaction. The expression of mCherry-O1-AA increased the frequency of ATP-induced sinusoidal [Ca2+]i oscillations, while mCherry-O1-wt and mCherry-O1-DD decreased this frequency. These data suggest that the combination of ATP and TG stimulates Ca2+ entry, and the phosphorylation of Orai1 S27/30 residues by PKC reduces IP3R-mediated Ca2+ release.
The Role and Effectiveness of Photodynamic Therapy on Patients With Actinic Keratosis: A Systematic Review and Meta-Analysis

Actinic keratoses (AKs) are the most common neoplastic lesions and are recognized as a precursor to squamous cell skin cancer. Photodynamic therapy (PDT) is a therapeutic option for multiple AKs in line with field cancerization. The aim of this study was to assess the effectiveness of PDT on patients with AKs using a meta-analysis, in order to evaluate the possible superiority of one treatment over the others. For this purpose, the PubMed, MEDLINE, Scopus, OVID, Science Direct, British Journal of Dermatology, Research Gate, and Embase databases were searched in March 2022. The search terms used were 'photodynamic therapy' and 'actinic keratosis'. We utilized the random-effects meta-analysis model to compare methyl aminolevulinate PDT (MAL-PDT) and the combination of a nanoscale-lipid vesicle formulation with the prodrug 5-aminolevulinic acid (BF-200 ALA) on a complete response (CR) of the lesions. Our meta-analysis indicated that the comparison of BF-200 ALA versus MAL-PDT showed marginally higher CRs than MAL-PDT.
Analysis of the Sustainability of Long-Term Detraining Caused by COVID-19 Lockdown: Impact on the Maximal Aerobic Speed of Under-16 Soccer Players

This retrospective cohort study aimed to analyze the effect of a 9-week detraining caused by COVID-19 lock-down on the maximal aerobic speed (MAS) of youth soccer players. The study included twenty-two under-16 male players competing at the national league level (15.4 ± 0.7 years old) who were analyzed pre and post the detraining period. The MAS was estimated using the Bronco’s test. Moreover, the self-regulated physical exercise performed by the players during the lockdown was monitored using a questionnaire. Considering the training volume per week, the players were grouped into those working more (>180 min/week) and those working less (<180 min/week) during the lockdown. Within-group changes revealed no significant differences (p = 0.122; d = 0.381) in the group that self-trained less than 180 min/week started (pre-lockdown) at 3.97 ± 0.29 m/s and ended (post-lockdown) at 3.85 ± 0.34 m/s, corresponding to a decrease of 3.02%. For those who self-trained more than 180 min/week during the lockdown, they started with 4.33 ± 0.28 m/s and decreased by 1.62% for 4.26 ± 0.28 m/s (p = 0.319; d = 0.250). The team as a whole (pooled data, all players included) decreased 2.27% from 4.15 ± 0.34 to 4.06 ± 0.37 m/s (p = 0.077; d = 0.321). Between group analysis revealed that the group of players that trained more than 180 min/weeks were significantly better than players working below 180 min/week in both pre-lockdown moment (+9.01%; p = 0.007; d = 1.263) and post-lockdown moment (10.6%; p = 0.006; d = 1.323). Home-based training can be a good strategy to mitigate the detraining effects caused by a lockdown.
The Investigation of joint Angle Movement Using Bio-Impedance

Electromyography (EMG) method is widely used in motion detection based on physiological phenomenon. However, EMG technique doesn’t fit to measure the dynamic parameter of motion. For instance, EMG is difficult to measure the joint angle changing. Bio-impedance method is a non-invasive, high performance method. This article evaluates the elbow joint movement using Bio-impedance, the correlation between the elbow joint angle changing and the upper arm bio-impedance changing has been calculated. A one-channel Bio-impedance measurement device with a goniometer has been designed in this study. The bio-impedance device generates high-frequency, low-intensity alternating constant current to human body and measure the bio-impedance signal. 20-kHz, 45-kHz, 50-kHz and 70-kHz has been investigated in the experiment. The one-channel bio-impedance measurement device includes of Wein oscillator, Howland constant current source, high-pass filter, the instrument amplifier INA 128, rectifier, low-pass filter and direct current coupling. Three electrode configurations were applied to compare the influence from each electrode configuration to the correlation calculation. Four male and two female have participated in the experiment of 70-kHz with three electrode configuration. In the experiment of 20-kHz, 45-Khz and 50-kHz, only one subject has participated in these experiments. The motion setting of 45-kHz is different with other frequency condition, it consists of 9 stages. Subject lifted their arms from 0 degrees to 80 degrees and kept their arm at each 10 degrees. The other motion setting consists of 4 stages. Subject lifted their arms from 0 degrees to 90 degrees and kept their arm at each 30 degrees. In multi-frequency with different electrode configurations condition, the result of 45-kHz, 50kHz and 70-kHz contribute high correlation between the elbow joint angle changing and upper arm bio-impedance changing. However, the result of the 20-kHz condition is not stable. In the multi-subject experiment, each subject contributes high correlation result in the 70-kHz condition with three electrode configurations. The last part of Thesis shows the statistical analysis using paired T-test method to observe the influence from different parameter to the correlation between elbow joint motion and bio-impedance changing. The result of paired Ttest method shows different electrode configurations have different influence on the bioimpedance measurement. Keyword: the evaluation of elbow joint motion, statistical analysis, one channel system, three electrode configurations, multi-frequency bio-impedance analysis
Effect of Cyclosporine on the Body Weight of Mice Inoculated with Prostate Cancer Tissues

Cancer is a disease characterized by uncontrolled cell proliferation in the body, leading to impaired functions and high mortality. Different models are used to study cancer in vivo and in vitro. Facilities for many of the studies are not available in developing countries. Genetically modified mice for in vivo model may not be available. Cyclosporine is an immunosuppresant drug that may be used to alter mice immunity necessary for development of implanted xenograft cancer tissues. Mice were randomly separated into four groups of five and subcutaneously administered cyclosporine at different doses (5, 20 and 40 mg/kg including negative control) daily for twentyone days. At seven days of drug administration, cancer tissues from prostate cancer human patients were administered to all mice. Body weights of mice were measured at weekly interval. Tumor-like nodules were observed at the site of cancer inoculation and when present were measured. Gross pathology and histopathology were performed. The results showed significant (p< 0.05) increase in body weight gain in only control group where cyclosporine was not administered. The number of tumor-like growth (first observed at day 14) per group and the magnitude of swelling vary directly (p < 0.05) with cyclosporine dose. Mortality varies inversely with the dose. No lesions were observed from the gross pathology. Histopathology revealed presence of neutrophil, plasma cells and oedema with no cancer cells detected. It was concluded that cyclosporine at the dose of 20 mg/kg in mice followed by administration of prostate cancer tissue caused decrease in body weight gain and allow growth of nodule bulging at the site of cancer tissue administration.
Elliptic diffusions on infinite products.

Product diffusions on infinite products of compact Riemannian manifolds appear naturally s basic objects in different contexts such s statistical mechanics and analysis on groups. This paper studies analytic properties of product heat kernels and their Green functions. In various cases including products of spheres and products of compact semisimple Lie groups we give simple necessary and sufficient conditions for: (a) the product heat diffusion semigroup to have a continuous kernel; (b) the Green function of the product heat diffusion semigroup to have a continuous kernel off the diagonal. At an abstract level, necessary and sufficient conditions for the existence of these kernels are given by theorems of Kakutany (for (a)) and Fukushima (for (b)). The point of this paper is to show how these abstract results apply in practice. The notions of hypercontractivity and time to equilibrium for ergodic Markov semigroups together with eigenvalue and heat kernel estimates due to S. Cheng, P. Li and S. T. Yau will be the keys of our analysis. Notions from representation theory of compact Lie groups and the classification of compact simple Lie groups will be used to treat products of compact semisimple Lie groups. The results presented here were developed to solve a long Standing problem in analysis on groups and to study related potential theoretic questions. Let G be a locally compact, connected, locally connected group. Does there always exist a Symmetrie Gaussian semigroup (μ,Χχ) having a continuous density with respect to Haar measure and such that lim μ((χ) = 0 locally uniformly on xe G\{id}? In a companion paper we will prove that f > 0 such a Gaussian semigroup always exists. Thanks to structure theorems, the case of (infinite) The support of DFG grant 436 RUS 113/51/2 is gratefully acknowledged. 172 Bendikov and Saloff-Coste, Elliptic diffusions on infinite products product of simple Lie groups treated in the present paper is the main building block in the proof of this general result.
Retinal Vessel Segmentation Based on the Anam-Net Model

Accurate segmentation of retinal blood vessels can help ophthalmologists diagnose eye-related diseases such as diabetes and hypertension. The task of segmentation of the vessels comes with a number of challenges. Some of the challenges are due to haemorrhages and microaneurysms in fundus imaging, while others are due to the central vessel reflex and low contrast. Encoder-decoder networks have recently achieved excellent performance in retinal vascular segmentation at the trade-off of increased computational complexity. In this work, we use the Anam-Net model to accurately segment retinal vessels at a low computational cost. The Anam-Net model consists of a lightweight convolutional neural network (CNN) along with bottleneck layers in the encoder and decoder stages. Compared to the standard U-Net model and the R2U-Net model, the Anam-Net model has 6.9 times and 10.9 times fewer parameters. We evaluated the Anam-Net model on three open-access datasets: DRIVE, STARE, and CHASE_DB. The results show that the Anam-Net model achieves better segmentation accuracy compared to several state-of-the-art methods. For the DRIVE, STARE, and CHASE DB datasets, the model achieved {sensitivity and accuracy} of {0.8601, 0.9660}, {0.8697, 0.9728}, and {0.8553, 0.9746}, respectively. On the DRIVE, STARE, and CHASE_DB datasets, we also conduct cross-training experiments. The outcome of this experiment demonstrates the generalizability and robustness of the Anam-Net model.