Miracle-dz/UniFAR-FTUs huggingface dataset:
What Is Influencer Marketing and How Does It Target Children? A Review and Direction for Future Research

Children nowadays spend many hours online watching YouTube videos in which their favorite vloggers are playing games, unboxing toys, reviewing products, making jokes or just going about their daily activities. These vloggers regularly post attractive and entertaining content in the hope of building a large follower base. Although many of these vloggers are adults, the number of child vloggers is flourishing. The famous child vlogger Ryan of Ryan’s World, for instance, has more than 19 million viewers and he is (at age seven) a social media influencer. The popularity of these vloggers incited advertisers to include them as a new marketing communication tool, also referred to as influencer marketing, in their marketing strategy. Accordingly, many influential vloggers now receive free products from brands in return for a mention in one of their videos and their other social media (e.g., TikTok or Instagram) and some are even paid to create a sponsored post or video and distribute it to their followers. This sponsored content appears to be highly influential and may affect young children’s brand preferences. Given the limited advertising literacy skills (i.e., knowledge of advertising and skills to critically reflect on this advertising) of children under age 12, they are a vulnerable target group when it comes to persuasion. Therefore, caution is needed when implementing this marketing tactic to target them. However, research on how influencer marketing affects young children (under 12) is scarce and it is unclear how these young children can be empowered to critically cope with this fairly new form of persuasion. This paper therefore aims to shed light on why and how social media influencers have persuasive power over their young followers. The paper starts with providing insights into how and why social media influencers became a new source in advertising. We then discuss the few studies that have been conducted on influencer marketing among young children (under 12), based on a systematic literature review, and take these findings to formulate societal and policy implications and develop a future research agenda.
Free Fatty Acids in Bone Pathophysiology of Rheumatic Diseases

Obesity—in which free fatty acid (FFA) levels are chronically elevated—is a known risk factor for different rheumatic diseases, and obese patients are more likely to develop osteoarthritis (OA) also in non-weight-bearing joints. These findings suggest that FFA may also play a role in inflammation-related joint damage and bone loss in rheumatoid arthritis (RA) and OA. Therefore, the objective of this study was to analyze if and how FFA influence cells of bone metabolism in rheumatic diseases. When stimulated with FFA, osteoblasts from RA and OA patients secreted higher amounts of the proinflammatory cytokine interleukin (IL)-6 and the chemokines IL-8, growth-related oncogene α, and monocyte chemotactic protein 1. Receptor activator of nuclear factor kappa B ligand (RANKL), osteoprotegerin, and osteoblast differentiation markers were not influenced by FFA. Mineralization activity of osteoblasts correlated inversely with the level of FFA-induced IL-6 secretion. Expression of the Wnt signaling molecules, axin-2 and β-catenin, was not changed by palmitic acid (PA) or linoleic acid (LA), suggesting no involvement of the Wnt signaling pathway in FFA signaling for osteoblasts. On the other hand, Toll-like receptor 4 blockade significantly reduced PA-induced IL-8 secretion by osteoblasts, while blocking Toll-like receptor 2 had no effect. In osteoclasts, IL-8 secretion was enhanced by PA and LA particularly at the earliest time point of differentiation. Differences were observed between the responses of RA and OA osteoclasts. FFA might therefore represent a new molecular factor by which adipose tissue contributes to subchondral bone damage in RA and OA. In this context, their mechanisms of action appear to be dependent on inflammation and innate immune system rather than Wnt-RANKL pathways.
Cell-Free Enzymatic Conversion of Spent Coffee Grounds Into the Platform Chemical Lactic Acid

The coffee industry produces over 10 billion kg beans per year and generates high amounts of different waste products. Spent coffee grounds (SCG) are an industrially underutilized waste resource, which is rich in the polysaccharide galactomannan, a polysaccharide consisting of a mannose backbone with galactose side groups. Here, we present a cell-free reaction cascade for the conversion of mannose, the most abundant sugar in SCG, into L-lactic acid. The enzymatic conversion is based on a so far unknown oxidative mannose metabolism from Thermoplasma acidophilum and uses a previously characterized mannonate dehydratase to convert mannose into lactic acid via 4 enzymatic reactions. In comparison to known in vivo metabolisms the bioconversion is free of phosphorylated intermediates and cofactors. Assessment of enzymes, adjustment of enzyme loadings, substrate and cofactor concentrations, and buffer ionic strength allowed the identification of crucial reaction parameters and bottlenecks. Moreover, reactions with isotope labeled mannose enabled the monitoring of pathway intermediates and revealed a reverse flux in the conversion process. Finally, 4.4 ± 0.1 mM lactic acid was produced from 14.57 ± 0.7 mM SCG-derived mannose. While the conversion efficiency of the process can be further improved by enzyme engineering, the reaction demonstrates the first multi-enzyme cascade for the bioconversion of SCG.
Expression QTL (eQTLs) Analyses Reveal Candidate Genes Associated With Fruit Flesh Softening Rate in Peach [Prunus persica (L.) Batsch]

Significant differences in softening rate have been reported between melting flesh in peach and nectarine varieties. This trait seems to be controlled by several genes. We aimed to identify candidate genes involved in fruit softening rate by integrating quantitative trait loci (QTL) and expression QTL (eQTL) analyses, comparing siblings with contrasting softening rates. We used a segregating population derived from nectarine cv. ‘Venus’ selfing, which was phenotyped for softening rate during three seasons. Six siblings with high (HSR) and six with low softening rate (LSR) were sequenced using RNA-Seq. A group of 5,041 differentially expressed genes was identified. Also, we found a QTL with a LOD (logarithm of odds) score of 9.7 on LG4 in all analyzed seasons. Furthermore, we detected 1,062 eQTLs, of which 133 were found co-localizing with the identified QTL. Gene Ontology (GO) analysis showed ‘Response to auxin’ as one the main over-represented categories. Our findings suggest over-expression of auxin biosynthetic related genes in the HSR group, which implies a higher expression and/or accumulation of auxin, thereby triggering fast softening. Conversely, the LSR phenotype might be explained by an altered auxin-homeostasis associated with low auxin levels. This work will contribute to unraveling the genetic mechanisms responsible for the softening rate in peaches and nectarines and lead to the development of molecular markers.
Menopausal Hormone Replacement Therapy and the Risk of Ovarian Cancer: A Meta-Analysis

Background: Findings by epidemiologic studies on menopausal hormone replacement therapy (HRT) and the risk of ovarian cancer are inconsistent. This study aimed to assess the association of menopausal HRT with the risk of ovarian cancer by histological subtype. Methods: A literature search was performed in PubMed, Web of Science, and EmBase for relevant articles published from inception to August 2018. Pooled relative risk ratios (RRs) with 95% confidence intervals (CIs) were determined with a random-effects model. Results: Thirty-six studies involving 4, 229, 061 participants were included in this meta-analysis. The pooled RR of ovarian cancer was 1.29 (95%CI 1.19–1.40, I2 = 57.4%) for menopausal HRT. In subgroup analysis by study design, pooled RRs of ovarian cancer in cohort and case-control studies were 1.35 (95%CI 1.19–1.53) and 1.24 (95%CI 1.11–1.38), respectively. In subgroup analysis by continent, association of menopausal HRT with ovarian cancer was significant for North America (1.41 [1.23–1.61]), Europe (1.22 [1.12–1.34]), and Asia (1.76 [1.09–2.85]), but not Australia (0.96 [0.57–1.61]). Association differed across histological subtypes. Increased risk was only found for two common types, including serous (1.50 [1.35–1.68]) and endometrioid (1.48 [1.13–1.94]) tumors. Conclusion: This meta-analysis suggests that menopausal HRT may increase the risk of ovarian cancer, especially for serous and endometrioid tumors.
MOISTURE SORPTION PROPERTIES AND STORAGE STABILITY CONDITIONS OF A NUTRACEUTICAL SYSTEM MICROENCAPSULATED BY SPRAY DRYING

The adsorption isotherms of a nutraceutical system microencapsulated by spray drying were determined at 20, 35 and 40 °C. Experimental data of the isotherms were fitted using the GAB and Caurie models and the integral thermodynamic functions (enthalpy and entropy) were estimated by the Clausius-Clapeyron equation. The Kelvin and Halsey equations were adequate for calculation of pore radius which varied from 0.67 to 8.15 nm. The point of maximum stability (minimum integral entropy) was found between 3.61 and 3.81 kg H2O/100 kg d.s. (corresponding to water activity, aW , of 0.19-0.37). Enthalpy-entropy compensation for the microcapsules showed two isokinetic temperatures. The first isokinetic temperature was observed at low moisture contents (< 3.81 kg H2O/100 kg d.s.) and was controlled by changes in the entropy of water, whereas the second isokinetic temperature was considered to be enthalpy-driven (3.81-20 kg H2O/100 kg d.s.).
Mechanisms of Long-Term Donor-Specific Allograft Survival Induced by Pretransplant Infusion of Lymphocytes

Pretransplantation donor-specific transfusion (DST) can enhance allograft survival in man and animals. However, due to the lack of a specific marker to identify donor-reactive cells in vivo in man and normal (nontransgenic) animals, the underlying mechanism remains unknown. In this study, we use 2CF1 transgenic mice expressing a transgenic T-cell receptor (TCR) specifically recognizing Ld, a major histocompatibility complex (MHC) class I molecule, to delineate the role of DST in long-term skin allograft survival and its underlying mechanisms. Our main findings include: (1) in the absence of any other immunosuppressive treatment, a single dose pretransplantation infusion of viable splenocytes from an Ld+ donor is sufficient to induce permanent donor-specific skin allograft survival in 2CF1anti-Ld TCR transgenic mice; (2) DST leads to a deletion of the majority (>60%) of donor-reactive T cells in the periphery of the recipient. However, deletion does not necessarily result in tolerance; (3) remaining donor-reactive T cells from DST-treated mice are fully responsive to Ld in vitro, and can suppress the antidonor response of naive T cells in vitro only when exogenous interleukin (IL)-4 is provided; and (4) the sera level of IL-4 in DST-treated tolerant mice is significantly increased. These results suggest that the generation of a subset of T cells with the potential to specifically inhibit antidonor responses, together with promotion of IL-4 production in recipients, may be important mechanisms for the induction and maintenance of antigen-specific tolerance.
Understanding the Disharmony between Weight Normalization Family and Weight Decay: ε-shifted L2 Regularizer

The merits of fast convergence and potentially better performance of the weight normalization family have drawn increasing attention in recent years. These methods use standardization or normalization that changes the weight $\boldsymbol{W}$ to $\boldsymbol{W}'$, which makes $\boldsymbol{W}'$ independent to the magnitude of $\boldsymbol{W}$. Surprisingly, $\boldsymbol{W}$ must be decayed during gradient descent, otherwise we will observe a severe under-fitting problem, which is very counter-intuitive since weight decay is widely known to prevent deep networks from over-fitting. In this paper, we \emph{theoretically} prove that the weight decay term $\frac{1}{2}\lambda||{\boldsymbol{W}}||^2$ merely modulates the effective learning rate for improving objective optimization, and has no influence on generalization when the weight normalization family is compositely employed. Furthermore, we also expose several critical problems when introducing weight decay term to weight normalization family, including the missing of global minimum and training instability. To address these problems, we propose an $\epsilon-$shifted $L_2$ regularizer, which shifts the $L_2$ objective by a positive constant $\epsilon$. Such a simple operation can theoretically guarantee the existence of global minimum, while preventing the network weights from being too small and thus avoiding gradient float overflow. It significantly improves the training stability and can achieve slightly better performance in our practice. The effectiveness of $\epsilon-$shifted $L_2$ regularizer is comprehensively validated on the ImageNet, CIFAR-100, and COCO datasets. Our codes and pretrained models will be released in this https URL.
Denoising convolutional neural network with mask for salt and pepper noise

In this study, the authors propose a new loss function for denoising convolutional neural network (DnCNN) for salt-and-pepper noise (SPN). Based on the motivation of utilising the mask of SPN, firstly from the usual SPN-denoising restoration equation, the authors establish a perfect restoration condition; the restored image is precisely the clean image if this condition holds. Then they design a mask-involved loss function to encourage the network to satisfy this condition in training progress. Experimental results demonstrate that compared with general DnCNN and other state-of-the-art SPN denoising methods, DnCNN equipped with the proposed loss function involving mask (MaskDnCNN) is more effective, robust and efficient.
Adversarial auto-encoder for unsupervised deep domain adaptation

Unsupervised visual domain adaptation aims to train a classifier that works well on a target domain given labelled source samples and unlabelled target samples. The key issue in unsupervised visual domain adaptation is how to do the feature alignment between source and target domains. Inspired by the adversarial learning in generative adversarial networks, this study proposes a novel adversarial auto-encoder for unsupervised deep domain adaptation. This method incorporates the auto-encoder with the adversarial learning so that the domain similarity and reconstruction information from the decoder can be exploited to facilitate the adversarial domain adaptation in the encoder. Extensive experiments on various visual recognition tasks show that the proposed method performs favourably against or better than competitive state-of-the-art methods.
Event-Related Potentials

A and extensive body of research exists discussing the cognitive impairment seen in chronic alcoholics, starting with the classic work of Victor and colleagues (1971), who described changes in the brain and nervous system seen on autopsies of alcohol­ dependent subjects. The changes observed in the brain were correlated with both memory and attentional deficits. The idea that cognitive changes, as reflected in scores on neuropsychological tests given to al­ coholics, were associated with the causes rather than the consequences of alcohol use was conceptually appealing (Goodwin and Hill 1975). P300 has received much attention as a possible neurophysiologi­ cal risk marker for the development of alcoholism. The event relat­ ed potential (ERP) is a series of waves that appear on a scan of the brain’s electrophysiological activity follow­ ing an auditory or visual stimulus. P300, one of the waves that compose the ERP, peaks approximately 3/10ths of a second after an informative event occurs. Alterations in the height of the P 3 0 0 w a v e ( i . e . , i t s a m p l i t u d e ) i n some studies may be a cause or a con­ sequence of drinking (Porjesz et al. 1980). Solving the puzzle of the possi­ ble r ela tio nship b etween P 300 and drinking is especially difficult because a multitude of factors exist that affect the emergent ERP waveform.
Diagnosis of Pancreatic Cystic Lesions by Virtual Slicing: Comparison of Diagnostic Potential of Needle-Based Confocal Laser Endomicroscopy versus Endoscopic Ultrasound-Guided Fine-Needle Aspiration

Background: Pancreatic cystic lesions are often challenging entities for diagnosis and management. EUS-FNA diagnostic accuracy is limited by paucicellularity of cytology specimens and sampling errors. Needle-based confocal laser endomicroscopy (nCLE) provides real-time imaging of the microscopic structure of the cystic lesion and could result in a more accurate diagnosis. Aims and Objectives: To determine the diagnostic utility of in vivo nCLE and EUS-FNA in the diagnosis and histologic characterization of pancreatic cystic lesions (PCL). Materials and Methods: All patients diagnosed with PCL who had undergone nCLE and FNA over a 10-year period within a major urban teaching hospital were included in this study. All gastroenterology reports of the nCLE images and corresponding pathologist findings from the EUS-FNA were collected and compared with, a final diagnosis prospectively collected from clinicopathological and imaging data. Results: A total of n=32 patients were included in this study, which consisted of n=13 serous cystadenoma (SCA), n=7 intraductal papillary mucinous neoplasms (IPMN), n=2 mucinous cystic neoplasms (MCN), n=3 well-differentiated neuroendocrine tumors, n=2 cysts, n=2 benign pancreatic lesions, n=1 adenocarcinoma, n=1 gastrointestinal stromal tumor (GIST) and n=1 lymphangioma. The overall diagnostic rate was higher in nCLE (87.5%) vs. EUS-FNA (71.9%) While the diagnostic accuracy of nCLE and EUS-FNA were comparable in characterization of benign vs. malignant lesions, the nCLE diagnosis demonstrated higher accuracy rate in identifying mucinous cystic neoplasms compared to EUS-FNA. Conclusion: nCLE is a useful companion diagnostic tool for pancreatic cystic lesions and could assist the cytopathologist to better triage the sample for required ancillary testing and treatment planning. The combination of nCLE and EUS-FNA may be especially helpful in reducing the proportion of cases categorized as non-diagnostic.
Evaluating the risk of adverse events with interventional endoscopic retrograde cholangiopancreatography and endoscopic ultrasound procedures in cirrhotic patients

BACKGROUND Hepatic cirrhosis is associated with greater adverse event rates following surgical procedures and is thought to have a higher risk of complications with interventional procedures in general. However, these same patients often require interventional gastrointestinal procedures such as endoscopic retrograde cholangiopancreatography (ERCP) and endoscopic ultrasound (EUS). While studies examining this scenario exist, the overall body of evidence for adverse event rates associated with ERCP/EUS procedures is more limited. We sought add to the literature by examining the incidence of adverse events after ERCP/EUS procedures in our safety-net hospital population with the hypothesis that severity of cirrhosis correlates with higher adverse event rates. AIM To examine whether increasing severity of cirrhosis is associated with greater incidence of adverse events after interventional ERCP/EUS procedures. METHODS We performed a retrospective study of patients diagnosed with hepatic cirrhosis who underwent ERCP and/or EUS-guided fine needle aspirations/fine needle biopsies from January 1, 2016 to March 14, 2019 at our safety net hospital. We recorded Child-Pugh and Model for End-stage Liver Disease (MELD-Na) scores at time of procedure, interventions completed, and 30-day post-procedural adverse events. Statistical analyses were done to assess whether Child-Pugh class and MELD-Na score were associated with greater adverse event rates and whether advanced techniques (single-operator cholangioscopy, electrohydraulic lithotripsy/laser lithotripsy, or needle-knife techniques) were associated with higher complication rates. RESULTS 77 procedures performed on 36 patients were included. The study population consisted primarily of middle-aged Hispanic males. 30-d procedure-related adverse events included gastrointestinal bleeding (7.8%), infection (6.5%), and bile leak (2%). The effect of Child-Pugh class C vs class A and B significantly predicted adverse events (β = 0.55, P < 0.01). MELD-Na scores also significantly predicted adverse events (β = 0.037, P < 0.01). Presence of advanced techniques was not associated with higher adverse events (P > 0.05). When MELD-Na scores were added as predictors with the effect of Child-Pugh class C, logistic regression showed MELD-Na scores were a significant predictor of adverse events (P < 0.01). The findings held after controlling for age, gender, ethnicity and repeat cases. CONCLUSION Increasing cirrhosis severity predicted adverse events while the presence of advanced techniques did not. MELD-Na score may be more useful in predicting adverse events than Child-Pugh class.
High Noise Tolerant R-Peak Detection Method Based on Deep Convolution Neural Network

SUMMARY An R-peak detection method with a high noise tolerance is presented in this paper. This method utilizes a customized deep convolution neural network (DCNN) to extract morphological and temporal features from sliced electrocardiogram (ECG) signals. The proposed network adopts multiple parallel dilated convolution layers to analyze features from diverse ﬁelds of view. A sliding window slices the original ECG signals into segments, and then the network calculates one segment at a time and outputs every point’s probability of belonging to the R-peak regions. After a binarization and a deburring operation, the occurrence time of the R-peaks can be located. Experimental results based on the MIT-BIH database show that the R-peak detection accuracies can be signiﬁcantly improved under high intensity of the electrode motion artifact or muscle artifact noise, which reveals a higher performance than state-of-the-art methods.
The effect of preheating resin composites on surface hardness: a systematic review and meta-analysis

Objectives This paper presents a systematic review and meta-analysis of the effect of preheating on the hardness of nanofilled, nanoceramic, nanohybrid, and microhybrid resin composites. Materials and Methods An electronic search of papers on MEDLINE/PubMed, ScienceDirect, and EBSCOhost was performed. Only in vitro studies were included. Non-English studies, case reports, clinical trials, and review articles were excluded. A meta-analysis of the reviewed studies was conducted to quantify differences in the microhardness of the Z250 microhybrid resin composite using the Comprehensive Meta-Analysis software. Results Only 13 studies met the inclusion criteria for this systematic review. The meta-analysis showed that there were significant differences between the non-preheated and preheated modes for both the top and bottom surfaces of the specimens (p < 0.05). The microhardness of the Z250 resin composite on the top surface in the preheated mode (78.1 ± 2.9) was higher than in the non-preheated mode (67.4 ± 4.0; p < 0.001). Moreover, the microhardness of the Z250 resin composite on the bottom surface in the preheated mode (71.8 ± 3.8) was higher than in the non-preheated mode (57.5 ± 5.7, p < 0.001). Conclusions Although the results reported in the reviewed studies showed great variability, sufficient scientific evidence was found to support the hypothesis that preheating can improve the hardness of resin composites.