Miracle-dz/UniFAR-FTUs huggingface dataset:
Publication de données individuelles respectueuse de la vie privée: une démarche fondée sur le co-clustering. (Privacy-preserving microdata publishing : an approach based on co-clustering)

There is a strong economic and civic demand for the opening of individual data. However, the publication of such data poses a risk to the individuals represented in it. This thesis focuses on the problem of anonymizing multidimensional data tables containing individual data for publishing purposes. In particular, two data anonymization approaches families will be focused on: the first aims to merge each individual into a group of individuals, the second is based on the addition of disruptive noise to the original data. Two new approaches are developed in the context of group anonymization. They aggregate the data using a co-clustering technique and then use the produced model, to generate synthetic records, in the case of the first solution. While the second proposal seeks to achieve the formalism of k-anonymity. Finally, we present a new anonymization algorithm “DPCocGen” that ensures differential privacy. First, a data-independent partitioning on the domains is used to generate a perturbed multidimensional histogram, a multidimensional co-clustering is then performed on the noisy histogram resulting in a partitioning scheme. Finally, the resulting schema is used to partition the original data in a differentially private way. Synthetic individuals can then be drawn from the partitions.
Enzymatic Urea Sensor Based on Graphene Oxide/Titanium Dioxide Films Modified by Urease-Magnetic Beads

In this paper, we proposed an enzymatic urea sensor using urease-magnetic beads (MBs) modified graphene oxide (GO)/titanium dioxide (TiO2) composite layers. The urea sensor was prepared by screen-printing technology and radio frequency sputtering. TiO2 sensing film was deposited onto polyethylene terephthalate substrate, which serves as an efficient matrix for immobilization of urease. Preparation of GO/TiO2 films was completed after GO being deposited onto the TiO2 film. Moreover, the characterization and sensing properties of the urea sensor were performed by energy dispersive spectrometer, scanning electron microscope, atomic force microscopy, electrochemical impedance spectroscopy, and voltage-time measurement system. The results indicated that the GO/TiO2 urea sensor enhances its performance of average sensitivity, response time, and drift rate after modifying the sensing membrane though MBs.
PyTorch Implementation and Assessment of Pre-Trained Convolutional Neural Networks for Tomato Leaf Disease Classification

Plant diseases detection and management practices are a major concern in the agriculture sector. Automating the process of plant disease detection with acceptable accuracy and speed using computer-aided systems could help develop an early diagnosis while substantially reducing economic losses. Recent advancements in deep neural networks have allowed researchers to drastically improve the accuracy of image classification and recognition systems. This paper presents a comprehensive assessment of the deep-learning approaches based on the pre-trained convolutional neural network models and the PyTorch framework to classify disease infections in tomato plants. Models such as EfficientNet-B0, ResNext-50_32x4d and MobileNet-V2, which relatively exhibit improved performance under different trade-offs, were tested using images captured with the natural background. Key performance indices were evaluated with varying hyperparameters during training and validation on a GPU-based system. The results show that ResNext-50_32x4d delivers the best accuracy of 90.14% (0.001 LR; 8 Batch Size), with the right hyperparameter optimization, and MobileNet-V2 delivers the lowest loss of 0.356 (0.001 LR; 16 Batch Size) during model validation for the given dataset and system constraints. ResNext-50_32x4d also performs better in inference than the other two models tested. The assessment performed in this paper will help researchers and developers decide on selecting an appropriate model for precision agriculture and smart farming deployments.
Snowband Characteristics Associated With Lake‐Effect Misovortices During the OWLeS Project

Vortices of diameters 100 m to 10 km have been observed during lake‐effect snowstorms. Lines of misovortices (diameters = 40–4,000 m) have recently been documented forming over Lake Ontario during long lake‐axis‐parallel (LLAP)‐type lake‐effect storms. Using National Weather Service Weather Surveillance Radar—1988 Doppler (WSR‐88D) and Doppler on Wheels radar data from the Ontario Winter Lake‐effect Systems (OWLeS) project, lines of misovortices (also referred to as “misovortex lines” in this study) were investigated for intensive observation period (IOP)7 (7 January 2014) and IOP9 (9 January 2014). Results revealed that the misovortex lines formed on the southern or northern side of the west‐to‐east‐oriented LLAP band, whichever was closest to a low‐level boundary nearest the corresponding south or north shoreline (northern part in IOP7, southern part in IOP9). Examination of these two IOPs in the context of a total of 23 OWLeS IOPs, 11 of which had predominantly LLAP band morphology, showed that, in 4 of the 11 LLAP IOPs, horizontal shear zones/reflectivity bands formed in preferred regions over Lake Ontario and nearby land areas where low‐level boundaries (e.g., land breeze fronts) have been noted to develop near shoreline irregularities. Horizontal shear zones were predominant in approximately half of the OWLeS LLAP IOPs and were associated with storms having a well‐organized, solid banded reflectivity structure. Misovortices occurred when horizontal shear zones were prevalent, supporting the idea that horizontal shearing instability was important to their formation.
Deep learning method for agriculture monitoring under adaptive environment using UAV-based aerial images

Deep learning-based traditional crop classification has become an integral part of smart agriculture now-a-days. However, the performance of these models sufferers a lot due to the distribution discrepancy (in terms of growth, types, and cultivated region of crops) between the training (source region) and testing (target region) data. To resolve this, a heterogeneous domain adaptation-based classification strategy has been investigated by considering the two different types of aerial image datasets collected over two different regions. Here, initially, a deep convolution neural network under multi-filter and multi-scale framework (MFMS-DCNN) was trained on the source-region data. Following that, an active learning approach is incorporated by employing the annotated source images to retrieve the set of ‘most-informative’ target images. This set includes the necessary common and extra class images from the target domain and eliminates the unnecessary missing class samples from the source domain. Finally, the common source and ‘most-informative’ target images are combined to fine-tune the trained MFMS-DCNN model which is then used to identify the crop classes of all the target samples under a heterogeneous framework. Experimental outcomes on the two datasets have established the proficiency of the proposed scheme to handle the heterogeneous DA problem for the agricultural region.
Products of Functions in ${\mathop\mathrm{BMO}}({\mathcal X})$ and $H^1_{\rm at}({\mathcal X})$ via Wavelets over Spaces of Homogeneous Type

Let $({\mathcal X},d,\mu)$ be a metric measure space of homogeneous type in the sense of R. R. Coifman and G. Weiss and $H^1_{\rm at}({\mathcal X})$ be the atomic Hardy space. Via orthonormal bases of regular wavelets and spline functions recently constructed by P. Auscher and T. Hyt\"onen, the authors prove that the product $f\times g$ of $f\in H^1_{\rm at}({\mathcal X})$ and $g\in\mathop\mathrm{BMO}({\mathcal X})$, viewed as a distribution, can be written into a sum of two bounded bilinear operators, respectively, from $H^1_{\rm at}({\mathcal X})\times\mathop\mathrm{BMO}({\mathcal X})$ into $L^1({\mathcal X})$ and from $H^1_{\rm at}({\mathcal X})\times\mathop\mathrm{BMO}({\mathcal X})$ into $H^{\log}({\mathcal X})$, which affirmatively confirms the conjecture suggested by A. Bonami and F. Bernicot (This conjecture was presented by L. D. Ky in [J. Math. Anal. Appl. 425 (2015), 807-817]).
CTPS cytoophidia formation affects cell cycle progression and promotes TSN-induced apoptosis of MKN45 cells

Cytidine triphosphate synthase (CTPS) forms filamentous structures termed cytoophidia in numerous types of cell. Toosendanin (TSN) is a tetracyclic triterpenoid and induces CTPS to form cytoophidia in MKN45 cells. However, the effects of CTPS cytoophidia on the proliferation and apoptosis of human gastric cancer cells remain poorly understood. In the present study, CTPS-overexpression and R294D-CTPS mutant vectors were generated to assess the effect of CTPS cytoophidia on the proliferation and apoptosis of gastric cancer MKN45 cells. Formation of CTPS cytoophidia significantly inhibited MKN45 cell proliferation (evaluated using EdU incorporation assay), significantly blocked the cell cycle in G1 phase (assessed using flow cytometry) and significantly decreased mRNA and protein expression levels of cyclin D1 (assessed by reverse transcription-quantitative PCR and western blotting, respectively). Furthermore, the number of apoptotic bodies and apoptosis rate were markedly elevated and mitochondrial membrane potential was markedly decreased. Moreover, mRNA and protein expression levels of Bax increased and Bcl-2 decreased markedly in MKN45 cells following transfection with the CTPS-overexpression vector. The proliferation rate increased, percentage of G1/G0-phase cells decreased and apoptosis was attenuated in cells transfected with the R294D-CTPS mutant vector and this mutation did not lead to formation of cytoophidia. The results of the present study suggested that formation of CTPS cytoophidia inhibited proliferation and promoted apoptosis in MKN45 cells. These results may provide insights into the role of CTPS cytoophidia in cancer cell proliferation and apoptosis.
FACTORS AFFECTING ECOTOURISM LOYALTY WITH THE MODERATING ROLE OF SOCIAL INFLUENCE - EMPIRICAL EVIDENCE IN VIETNAM

Today, ecotourism has become more common and attractive for tourists who love to explore nature and experience the cultural heritage. In the 4.0 age of technology, social networking not only helps visitors find suitable destinations to visit easily but also provides visitors with a place to leave comments or reviews after the trips. This study aims to qualify the relationships between electronic-worth-of-mouth (eWOM), social influence (SI), destination image (DI), tourist satisfaction (SAT), and ecotourism loyalty (EL). The study applied the PLS-SEM model to estimate 499 observations at ecotourism sites in Vietnam as empirical evidence. The research results show that all the factors in the research model have positive and significant effects on EL. In particular, DI and SAT, directly and indirectly, affect EL; while eWOM and SI only have direct effects on EL. Additionally, it was found that the effect of eWOM on EL increased with the moderating role of SI.
Association of Drain Use in Ankle Arthrodesis With Increased Blood Transfusion Risk: A National Observational Study

Background: Closed wound drainage has been extensively studied in the hip and knee arthroplasty literature with equivocal results on its clinical benefits. Although also used in orthopaedic surgeries like ankle arthrodesis and ankle arthroplasty, large-scale data are currently lacking on utilization patterns and real-world effectiveness. We, therefore, aimed to address this research gap in this distinct surgical cohort using national claims data. Methods: Using the Premier Healthcare claims database from 2006 to 2016, ankle arthrodesis (n=10,085) and ankle arthroplasty (n=4,977) procedures were included. The main effect was drain use, defined by detailed billing descriptions. Outcomes included blood transfusion, 90-day readmission, and length and cost of hospitalization. Mixed-effects models measured associations between drain use and outcomes. Odds ratios (OR, or % change), 95% CIs, and P values are reported. Results: Overall, drains were used in 11% (n=1,074) and 15% (n=755) of ankle arthrodesis and ankle arthroplasty procedures, respectively. Drain use dramatically decreased over the years in both surgery types: from 14% to 6% and 24% to 7% between 2006 and 2016, for arthrodesis and ankle arthroplasty procedures, respectively. After adjustment for relevant covariates, drain use was associated with increased odds of blood transfusion in ankle arthrodesis surgery (OR 1.4, CI 1.1-1.8, P = .0168), whereas differences that were statistically but not clinically significant were seen in cost and length of stay. In total ankle arthroplasty, no statistically significant associations were observed between drain use and the selected outcomes. Conclusion: This is the first national study on drain use in ankle surgery. We found a decrease in use over time. Drain use was associated with higher odds of blood transfusion in ankle arthrodesis patients. Although this negative effect may be mitigated by the rapidly decreasing use of drains, future studies are needed to discern drivers of drain use in this distinct surgical population. Level of Evidence: Level III, retrospective cohort study
A Case of Meningitis in an Infant Due to Hypervirulent Klebsiella pneumoniae Transmission Within a Family

Abstract Hypervirulent Klebsiella pneumoniae (hvKP), an emerging pathotype derived from K. pneumoniae, frequently causes invasive infections of multiple organs and is associated with both high disability and fatality rates. In this study, a case of meningitis in a young infant caused by hvKP is presented. Cytological and biochemical examinations of the cerebrospinal fluid (CSF) revealed purulent meningitis, a diagnosis that was confirmed by a positive CSF culture result. The pathogen was identified as hvKP through analysis of positive virulence-associated genes. Meanwhile, hvKP was also isolated from stool samples of both the infant and her father. Antimicrobial susceptibility, capsular typing, and multilocus sequence typing (MLST) of three isolates from the infant’s CSF and stool and her father’s stool samples were analyzed. The three K. pneumoniae isolates were susceptible to all antibiotics except ampicillin and were identified as capsular serotype K2 and sequence type 86. These genetic relatedness analyses indicated that the strain isolated from the infant’s CSF might have originated from her father’s stool via familial transmission. This case is the first report of meningitis in an infant due to hvKP transmitted within a family.
Does exercise impact gut microbiota composition in men receiving androgen deprivation therapy for prostate cancer? A single-blinded, two-armed, randomised controlled trial

Introduction A potential link exists between prostate cancer (PCa) disease and treatment and increased inflammatory levels from gut dysbiosis. This study aims to examine if exercise favourably alters gut microbiota in men receiving androgen deprivation therapy (ADT) for PCa. Specifically, this study will explore whether: (1) exercise improves the composition of gut microbiota and increases the abundance of bacteria associated with health promotion and (2) whether gut health correlates with favourable inflammatory status, bowel function, continence and nausea among patients participating in the exercise intervention. Methods and analysis A single-blinded, two-armed, randomised controlled trial will explore the influence of a 3-month exercise programme (3 days/week) for men with high-risk localised PCa receiving ADT. Sixty patients will be randomly assigned to either exercise intervention or usual care. The primary endpoint (gut health and function assessed via feacal samples) and secondary endpoints (self-reported quality of life via standardised questionnaires, blood biomarkers, body composition and physical fitness) will be measured at baseline and following the intervention. A variety of statistical methods will be used to understand the covariance between microbial diversity and metabolomics profile across time and intervention. An intention-to-treat approach will be utilised for the analyses with multiple imputations followed by a secondary sensitivity analysis to ensure data robustness using a complete cases approach. Ethics and dissemination Ethics approval was obtained from the Human Research Ethics Committee of Edith Cowan University (ID: 19827 NEWTON). Findings will be reported in peer-reviewed publications and scientific conferences in addition to working with national support groups to translate findings for the broader community. If exercise is shown to result in favourable changes in gut microbial diversity, composition and metabolic profile, and reduce gastrointestinal complications in PCa patients receiving ADT, this study will form the basis of a future phase III trial. Trial registration number ANZCTR12618000280202.
The Effects of Secondary Growth of Spartina alterniflora after Treatment on Sediment Microorganisms in the Yellow River Delta

As a typical invasive species, Spartina alterniflora is widely recognized as one of the primary threats to biodiversity in various habitats, including wetlands. Although the invasion by S. alterniflora has been managed in multiple ways, it may reappear after treatment. How S. alterniflora affects the soil microbial community in coastal wetlands during its regeneration process has not yet been clarified. Here, rhizosphere soil samples (RSPs) and bulk soil samples (SSPs) were collected in the S. alterniflora community and a high-throughput sequencing method was conducted to analyze the composition and diversity of soil microorganisms. Meanwhile, we also obtain the soil physicochemical properties. In the present study, there was no significant difference in the alpha diversity of both bacterial and fungal communities in the SSP and RSP groups. The PCoA (principal coordinate analysis) also showed that the microbial community structure did not differ significantly between the SSP and RSP groups. The results showed that except for pH, the total sulfur (TS) content, total nitrogen (TN) content, and electrical conductivity (EC) did not differ significantly (p > 0.05) between the SSP and RSP groups. The composition of the bacterial and fungal community in the rhizosphere of S. alterniflora was similar to that found in the surrounding soils. The top two dominant bacterial phyla were Proteobacteria and Desulfobacterota in the present study. Venn diagram results also support this view; most OTUs belong to the common OTUs of the two groups, and the proportion of unique OTUs is relatively small. The LEfSe (LDA effect size) analysis showed that Campylobacterota (at the phylum level) and Sulfurimonas (at the genus level) significantly increased in the RSP group, implying that the increased Sulfurimonas might play an essential role in the invasion by S. alterniflora during the under-water period. Overall, these results suggest that the bacterial and fungal communities were not significantly affected by the S. alterniflora invasion due to the short invasion time.
Regulation of alternative splicing by p300-mediated acetylation of splicing factors

Splicing of precursor mRNA (pre-mRNA) is an important regulatory step in gene expression. Recent evidence points to a regulatory role of chromatin-related proteins in alternative splicing regulation. Using an unbiased approach, we have identified the acetyltransferase p300 as a key chromatin-related regulator of alternative splicing. p300 promotes genome-wide exon inclusion in both a transcription-dependent and -independent manner. Using CD44 as a paradigm, we found that p300 regulates alternative splicing by modulating the binding of splicing factors to pre-mRNA. Using a tethering strategy, we found that binding of p300 to the CD44 promoter region promotes CD44v exon inclusion independently of RNAPII transcriptional elongation rate. Promoter-bound p300 regulates alternative splicing by acetylating splicing factors, leading to exclusion of hnRNP M from CD44 pre-mRNA and activation of Sam68. p300-mediated CD44 alternative splicing reduces cell motility and promotes epithelial features. Our findings reveal a chromatin-related mechanism of alternative splicing regulation and demonstrate its impact on cellular function.
α-Cyperone Protects Cardiomyocytes against Oxygen-Glucose Deprivation-Induced Inflammation and Oxidative Stress by Akt/FOXO3a/NF-κB Pathway

Objective This study is aimed at investigating the mechanism of α-cyperone in oxygen and glucose deprivation- (OGD-) induced myocardial injury. Methods Cardiomyocytes were exposed to OGD and then treated with α-cyperone. The cell counting kit-8 (CCK-8) assay and flow cytometry were performed to determine cell proliferation and apoptosis, respectively. The expression of inflammatory factors was monitored by quantitative reverse transcription-polymerase chain reaction (qRT-PCR). The profiles of apoptosis-related proteins, inflammatory proteins, and the Akt/FOXO3a/NF-κB pathway were determined by western blot. The phosphorylation of Akt, FOXO3a, and NF-κB was determined by immunofluorescence assay. The superoxide dismutase (SOD) activity and the malondialdehyde (MDA) content were gauged by the colorimetric method, and the reactive oxygen species (ROS) content was measured. Results α-Cyperone hindered OGD-induced inflammation, oxidative stress, and apoptosis in cardiomyocytes. OGD activated the FOXO3a/NF-κB pathway and hampered the Akt phosphorylation. α-cyperone reversed OGD-mediated FOXO3a/NF-κB pathway activation. Treatment with MK-2206 abated the protective effect of α-cyperone against OGD-induced myocardial injury. The addition of α-cyperone to cardiomyocytes following Bay11-7082 treatment had no conspicuous effect on the viability and apoptosis. Conclusions α-Cyperone protected cardiomyocytes against OGD-induced inflammation and oxidative stress via the Akt/FOXO3a/NF-κB axis.
Demagnetization Fault Diagnosis of the Permanent Magnet Motor for Electric Vehicles Based on Temperature Characteristic Quantity

Permanent magnet motors are widely used in the driving system of electric vehicles because of their high power density and small size. However, the permanent magnet motor is prone to demagnetization due to the complex operating environment of electric vehicles and characteristics of permanent magnet motors. To ensure the normal operation of vehicles, the demagnetization fault diagnosis of permanent magnets should develop. In this study, the thermal behavior of a permanent magnet motor under local demagnetization fault is discussed. Results show that the demagnetization of permanent magnets has a significant effect on the temperature of the motor; thus, the temperature is added into input signals of the permanent magnet demagnetization fault diagnosis. The healthy state of the permanent magnet is predicted by the back propagation (BP) neural network to realize the demagnetization fault diagnosis. First, the demagnetization test platform is built to test the performance of the motor, and the current, torque, and temperature of the motor are measured according to different demagnetization degrees. Second, the demagnetization simulation model of the motor is established by the finite-element method, and the air gap magnetic field, loss, and temperature of the motor are analyzed. Lastly, the temperature, current, speed, and torque signals are selected as input signals of the neural network model, and the demagnetization rate of the rotor is taking as the output signal. The neural network prediction model is established and trained, and the good generalization ability is obtained.