Miracle-dz/UniFAR-FTUs huggingface dataset:
Tissular Distribution and Metabolism of trans-ε-Viniferin after Intraperitoneal Injection in Rat

Background: Recent studies showed that trans-ε-viniferin (ε-viniferin), a trans-resveratrol dehydrodimer, has anti-inflammatory and anti-obesity effects in rodents. The main purpose of this work was to assess the tissue distribution study of ε-viniferin and its metabolites after intraperitoneal (IP) administration in rat. Methods: After IP injection of 50 mg/kg, ε-viniferin and its metabolites were identified and quantified in plasma, liver, kidneys, adipose tissues, urine, and faeces by Liquid Chromatography-High Resolution Mass Spectrometry (LC-HRMS). Results: ε-Viniferin underwent a rapid hepatic metabolism mostly to glucuronides but also to a lesser extent to sulphate derivatives. The highest glucuronide concentrations were found in liver followed by plasma and kidneys whereas only traces amounts were found in adipose tissues. In contrast the highest ε-viniferin areas under concentration (AUC) and mean residence times (MRT) values were found in white adipose tissues. Finally, much lower levels of ε-viniferin or its metabolites were found in urine than in faeces, suggesting that biliary excretion is the main elimination pathway. Conclusion: A rapid and large metabolism of ε-viniferin and a high bioaccumulation in white adipose tissues were observed. Thus, these tissues could be a reservoir of the native form of ε-viniferin that could allow its slow release and a sustained presence within the organism.
Investigation of Tandem-x Penetration Depth Over the Greenland Ice Sheet

Ongoing global warming causes dramatic changes globally, especially with respect to Polar Regions. In this context, digital elevation data is of high importance for most glaciological applications. In this paper, we investigate TanDEM-X penetration depth over snow and ice on the Greenland ice sheet. In particular, the relation of backscatter intensity and interferometric coherence to penetration depth of the X-band InSAR signal is explored in order to improve the reliability of TanDEM-X elevation data. The analyses showed a distinct relationship of backscatter intensity, coherence and penetration depth. In addition, the influence of the height of ambiguity of the interferometric TanDEM-X data is presented. On an experimental test site in Northern Greenland, we demonstrated the estimation of TanDEM-X penetration depth based on backscatter intensity and interferometric coherence utilizing a linear regression model.
Linguistic Signals under Misinformation and Fact-Checking

Misinformation and fact-checking are opposite forces in the news environment: the former creates inaccuracies to mislead people, while the latter provides evidence to rebut the former. These news articles are often posted on social media and attract user engagement in the form of comments. In this paper, we investigate linguistic (especially emotional and topical) signals expressed in user comments in the presence of misinformation and fact-checking. We collect and analyze a dataset of 5,303 social media posts with 2,614,374 user comments from Facebook, Twitter, and YouTube, and associate these posts to fact-check articles from Snopes and PolitiFact for veracity rulings (i.e., from true to false). We find that linguistic signals in user comments vary significantly with the veracity of posts, e.g., we observe more misinformation-awareness signals and extensive emoji and swear word usage with falser posts. We further show that these signals can help to detect misinformation. In addition, we find that while there are signals indicating positive effects after fact-checking, there are also signals indicating potential "backfire" effects.
QoE-Assured 4K HTTP Live Streaming via Transient Segment Holding at Mobile Edge

HTTP-based live streaming has become increasingly popular in recent years, and more users have started generating 4K live streams from their devices (e.g., mobile phones) through social-media service providers like Facebook or YouTube. If the audience is located far from a live stream source across the global Internet, TCP throughput becomes substantially suboptimal due to slow start and congestion control mechanisms. This is especially the case when the end-to-end content delivery path involves radio access network at the last mile. As a result, the data rate perceived by a mobile receiver may not meet the high requirement of 4K video streams, which causes deteriorated quality-of-experience (QoE). In this paper, we propose a scheme named edge-based transient holding of live segment (ETHLE), which addresses the abovementioned issue by performing context-aware transient holding of video segments at the mobile edge with virtualized content caching capability. Through holding the minimum number of live video segments at the mobile edge cache in a context-aware manner, the ETHLE scheme is able to achieve seamless 4K live streaming experiences across the global Internet by eliminating buffering and substantially reducing initial startup delay and live stream latency. It has been deployed as a virtual network function at an LTE-A network, and its performance has been evaluated using real live stream sources that are distributed around the world. The significance of this paper is that by leveraging virtualized caching resources at the mobile edge, we address the conventional transport-layer bottleneck and enable QoE-assured Internet-wide live streaming services with high data rate requirements.
Y^2Seq2Seq: Cross-Modal Representation Learning for 3D Shape and Text by Joint Reconstruction and Prediction of View and Word Sequences

Jointly learning representations of 3D shapes and text is crucial to support tasks such as cross-modal retrieval or shape captioning. A recent method employs 3D voxels to represent 3D shapes, but this limits the approach to low resolutions due to the computational cost caused by the cubic complexity of 3D voxels. Hence the method suffers from a lack of detailed geometry. To resolve this issue, we propose Y2Seq2Seq, a view-based model, to learn cross-modal representations by joint reconstruction and prediction of view and word sequences. Specifically, the network architecture of Y2Seq2Seq bridges the semantic meaning embedded in the two modalities by two coupled “Y” like sequence-tosequence (Seq2Seq) structures. In addition, our novel hierarchical constraints further increase the discriminability of the cross-modal representations by employing more detailed discriminative information. Experimental results on cross-modal retrieval and 3D shape captioning show that Y2Seq2Seq outperforms the state-of-the-art methods.
First Evaluation of Land Surface Emissivity Spectra Simulated with the Sail-Thermique Model

The SAIL-Thermique model was developed to simulate land surface emissivity. It is adapted from the original SAIL model. A specific experiment was set-up over a soybean canopy for evaluating spectral emissivity simulations. Multispectral data were obtained thanks to a CIMEL CE 312-2 radiometer and emissivities calculated using the TES method. Comparison of multispectral emissivity simulations and measurements at various leaf area index levels were comparable in terms of emissivity values and spectral behavior.
AIS Electronic Library (AISeL)

Automobile purchase intentions of customers relate to car dealers’ costs and affect the car dealers’ marketing strategy and manufacturing process in the long term. Automobile purchase intention classification has become critically important for car dealers. In our paper, we innovatively constructed a hobby based network and a working based network of customers, and used customers’ profile of same group as inputs to the deep learning model to predict customers’ purchase intention based on community detection by social network analysis. Based on the real-world dataset, our experimental results verify that the framework with both hobby-based network and working-based network using deep learning method has best performance, which is 14% better than the baseline model. And the hobby-based network outperforms working-based network. Because of the advantage of consumer’s personality, hobbies can be used for better predicting the purchase intention. Therefore, our proposed framework is a potential tool for automobile purchase intention classification.
Rotated Region Based Fully Convolutional Network for Ship Detection

Ship detection from high-resolution optical remote sensing images has been a prevalent domain in recent years. Unlike objects in natural images, ships of interest can be anywhere in optical remote sensing images with multi-scale and multi-oriented which makes it more different to be detected. In this paper, we propose a novel method based on the fully convolutional network to detect ships. Our method has three important components: 1) we design a network merging different levels of feature map to fuse multi-scale information. Determining the existence of large ship require features from deep layers in the network, while predicting rotated bounding box enclosing small ships need shallow layers information; 2) The network can be trained end-to-end to generate score maps which indicates the confidence score for the ship region of interest in pixel-wise level through all locations and scaled of an image; 3) We design a rotated bounding box regression model to localize the ships. The experimental results on our dataset collected from Google Earth has demonstrated our proposed method achieves promising performance on ship detection in terms of both efficiency and accuracy in high-resolution optical remote sensing images.
Multiple-Domain Sentiment Classification for Cantonese Using a Combined Approach

In this study, we proposed a combined approach, which amalgamates machine learning and lexicon-based approaches for multiple-domain sentiment classification that supports Cantonese-based social media analysis. Our study contributes to the existing literature not only by investigating the effectiveness of the proposed combined approach for supporting social media analysis in the Cantonese context but also by verifying that the proposed method outperforms the baseline approaches, which are commonly used in the literature. We demonstrated that social media network-based classifiers can be general classifiers that support multiple-domain sentiment classification.
Neuronal phase consistency tracks dynamic changes in acoustic spectral regularity

The brain parses the auditory environment into distinct sounds by identifying those acoustic features in the environment that have common relationships (e.g., spectral regularities) with one another and then grouping together the neuronal representations of these features. Although there is a large literature that tests how the brain tracks spectral regularities that are predictable, it is not known how the auditory system tracks spectral regularities that are not predictable and that change dynamically over time. Furthermore, the contribution of brain regions downstream of the auditory cortex to the coding of spectral regularity is unknown. Here, we addressed these two issues by recording electrocorticographic activity, while human patients listened to tone‐burst sequences with dynamically varying spectral regularities, and identified potential neuronal mechanisms of the analysis of spectral regularities throughout the brain. We found that the degree of oscillatory stimulus phase consistency (PC) in multiple neuronal‐frequency bands tracked spectral regularity. In particular, PC in the delta‐frequency band seemed to be the best indicator of spectral regularity. We also found that these regularity representations existed in multiple regions throughout cortex. This widespread reliable modulation in PC – both in neuronal‐frequency space and in cortical space – suggests that phase‐based modulations may be a general mechanism for tracking regularity in the auditory system specifically and other sensory systems more generally. Our findings also support a general role for the delta‐frequency band in processing the regularity of auditory stimuli.
A Background Calibration Technique to Control the Bandwidth of Digital PLLs

This paper presents a technique to regulate the bandwidth of digital phase-locked loops (PLLs), where a fully digital automatic control circuit, running in background, is used to desensitize loop gain from analog parameters. The method that is based on an adaptive least-mean-squares algorithm requires no injection of a training sequence, potentially degrading phase noise performance, and is suitable in particular for bang-bang PLLs, where the bandwidth depends on the input noise. The operating principle is first introduced and discussed with the help of an intuitive time-domain model, and the algorithm extension addressing the practical implementation issues associated with loop latency is then presented. The calibration circuit is embedded in a 65-nm CMOS digital PLL that achieves 400-fs integrated rms jitter with a power consumption of 4.5 mW. The algorithm enables digital programmability of loop bandwidth from 100 kHz to 2 MHz with an error below 1 dB between the theoretical and measured PLL noise transfer functions.
How Aesthetic Engagement with IT is Shaping Digital Society: An Ethnographic Example

In this paper, we discuss an empirical example of the everyday aesthetics of engagement with information systems work practices. Drawing on an ethnographic study, we suggest that the information systems phenomena can be seen as a form of artwork in the practices of a new generation of IT professionals. Using the aesthetic ontology of art, an artwork is conceptualised as something that manifests, articulates, and reconfigures the human practices in a digital society. This paper is intended as an empirical contribution towards advancing the discussion of the aesthetics of engagement in the information systems literature.
Effects of loss of consciousness on maxillofacial fractures in simple falls

BACKGROUND/AIMS Loss of consciousness while falling is reported to increase the risk of more severe injury. However, few studies of maxillofacial injuries have been reported. The aim of this study was to investigate the effects of loss of consciousness on maxillofacial fractures in falls on a level surface (simple falls). MATERIAL AND METHODS Patients with maxillofacial fractures caused by simple falls were subdivided into two categories: patients who fell without loss of consciousness and patients who fell with loss of consciousness, according to the Guidelines for the Diagnosis and Management of Syncope (version 2009). The severity of the injuries was compared between these two groups. RESULTS In 413 patients with maxillofacial fractures, 58 cases were falls without loss of consciousness, and 44 cases were falls with loss of consciousness. In falls with loss of consciousness, 54.5% were reflex syncope, followed by syncope due to orthostatic hypotension (15.9%), epilepsy (15.9%), and cardiac syncope (9.1%). The average number of fracture lines in the mandible was significantly lower in falls without loss of consciousness (1.53 ± 0.7) than in falls with loss of consciousness (2.00 ± 1.00) (P = 0.045). The average Facial Injury Severity Scale score was lower in falls without loss of consciousness (2.24 ± 1.20) than in falls with loss of consciousness (2.68 ± 1.39). Fractures of other parts of the body were significantly more common in falls without loss of consciousness (22.2%) than in falls with loss of consciousness (9.1%) (P = 0.0135). CONCLUSIONS Patients with loss of consciousness and maxillofacial fractures due to simple falls showed a tendency to sustain more severe maxillofacial injuries than those without loss of consciousness.
Anti-Adenoviral Activity of 2-(3-Chlorotetrahydrofuran-2-yl)-4-Tosyl-5-(Perfluoropropyl)-1,2,3-Triazole

Background and objectives: A considerable increase in the levels of adenoviral diseases among both adults and children necessitate the development of effective methods for its prevention and treatment. The synthesis of the new fluorinated 1,2,3-triazoles, and the study of the mechanisms of their action, are promising for the development of efficient antiviral drugs of our time. Materials and Methods: Antiviral activity and cell cytotoxic effect of 2-(3-chlorotetrahydrofuran-2-yl)-4-tosyl-5-(perfluoropropyl)-1,2,3-triazole (G29) were determined by MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide) assay. The influence of the compound on the infectivity of human adenovirus type 5 (HAdV-5) was carried out via the cytomorphology method. The influence of the compound on the cell cycle under a condition of adenovirus infection was studied using flow cytometric analysis of propidium iodide-stained cells. Results: It was found that G29 suppressed HAdV-5 reproduction by 50% in concentrations of 37 μg/mL. Furthermore, the compound reduced the titer of virus obtained de novo, and inhibited HAdV-5 inclusion bodies formation by 84–90%. The use of fluorinated compounds under the conditions of adenovirus infection decreased the number of apoptotic cells by 11% and the number of cells in S phase by 21–42% compared to the profile of infected cells. Conclusions: The fluorinated compound G29 showed moderate activity against HAdV-5 based on several mechanisms. It led to the normalization of the life cycle of cells infected with adenovirus to the level of non-infected cells and caused the obstruction of HAdV-5 reproduction, inducing the formation of non-infectious virus progeny.
Changes in Lean Muscle Mass Associated with Neoadjuvant Platinum-Based Chemotherapy in Patients with Muscle Invasive Bladder Cancer

Background: Baseline sarcopenia or severe lean muscle deficiency is independently associated with increased mortality after cystectomy for muscle-invasive urothelial carcinoma of the bladder (MIUC). The impact of chemotherapy on muscle mass in MIUC patients remains undefined Objectives: To describe preoperative changes in body composition in MIUC patients receiving platinum-based neoadjuvant chemotherapy (NC). Methods: Patients with cT2-4 N0-1 M0 UC of the bladder who received NC were identified. Lumbar skeletal muscle index (SMI, cm2/m2), visceral adipose index (VAI, cm2/m2), and the subcutaneous and intramuscular adipose index (SAI, cm2/m2) were calculated using validated methodology (cross sectional area of skeletal muscle/height2 at L3) from measurement of soft tissue areas on pre- (pre-NC) and post-NC (post-NC) computed tomography. Patients were classified as sarcopenic according to consensus definitions: Male: SMI <55 cm2/m2, Female: SMI <38.5 cm2/m2. Pre-NC and post-NC median body mass index (BMI kg/m2), SMI, and adipose indices were compared. Results: The study cohort consisted of 26 patients, with a median age 70 years, including 7 females (27%). Chemotherapy regimens included dose-dense methotrexate, vinblastine, doxorubicin and cisplatin (31%), gemcitabine/cisplatin (62%) and gemcitabine/carboplatin (3.8%) with a median of 3.5 (range 2–6) cycles. Median pre- and post-NC BMI were 27.1 kg/m2 and 27.2 kg/m2 (p = 0.36). Median pre- and post-NC SMI were 49.1 cm2/m2 and 44.5 (p < 0.001) respectively. Median percent change in SMI was –6.4% (range –30% to 10%). Pre-NC, 18 (69%) patients were sarcopenic vs. 21 (81%, p = 0.002) post-NC. Median time between initiation of chemotherapy and cystectomy was 110 days. Conclusions: We observed a significant decrease in lean muscle mass among MIUC patients treated with platinum-based NC prior to cystectomy, with an associated increase in the prevalence of sarcopenia. Patients undergoing NC may benefit from pre-habilitative interventions to mitigate lean muscle loss prior to cystectomy.
Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge

Gliomas are the most common primary brain malignancies, with different degrees of aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, i.e., peritumoral edematous/invaded tissue, necrotic core, active and non-enhancing core. This intrinsic heterogeneity is also portrayed in their radio-phenotype, as their sub-regions are depicted by varying intensity profiles disseminated across multi-parametric magnetic resonance imaging (mpMRI) scans, reflecting varying biological properties. Their heterogeneous shape, extent, and location are some of the factors that make these tumors difficult to resect, and in some cases inoperable. The amount of resected tumoris a factor also considered in longitudinal scans, when evaluating the apparent tumor for potential diagnosis of progression. Furthermore, there is mounting evidence that accurate segmentation of the various tumor sub-regions can offer the basis for quantitative image analysis towards prediction of patient overall survival. This study assesses thestate-of-the-art machine learning (ML) methods used for brain tumor image analysis in mpMRI scans, during the last seven instances of the International Brain Tumor Segmentation (BraTS) challenge, i.e., 2012-2018. Specifically, we focus on i) evaluating segmentations of the various glioma sub-regions in pre-operative mpMRI scans, ii) assessing potential tumor progression by virtue of longitudinal growth of tumor sub-regions, beyond use of the RECIST/RANO criteria, and iii) predicting the overall survival from pre-operative mpMRI scans of patients that underwent gross tota lresection. Finally, we investigate the challenge of identifying the best ML algorithms for each of these tasks, considering that apart from being diverse on each instance of the challenge, the multi-institutional mpMRI BraTS dataset has also been a continuously evolving/growing dataset.
Outcomes for popliteal artery injury repair after discharge: A large-scale population-based analysis

BACKGROUND Although short-term outcomes for popliteal artery injury after endovascular versus open repair appear similar, studies on outcomes after discharge are limited. We evaluated popliteal artery injury repair in a population-based data set. We hypothesized that postdischarge outcomes for open repair are superior to endovascular repair. METHODS Patients with popliteal artery injury were identified in the California Office of Statewide Health Planning and Development 2007–2014 discharge database. Popliteal artery injury and other lower-extremity injuries were identified using International Classification of Diseases, Ninth Revision, Clinical Modification diagnosis codes. Procedure codes were evaluated to identify open repair, endovascular repair, fasciotomy, and amputation. Primary outcomes were mortality or amputation. The association between repair method and each outcome was evaluated with logistic regression. Postdischarge amputation and all-cause mortality were evaluated using survival analysis. RESULTS Among 769 patients with popliteal artery injury, open repair occurred in 456 (59.3%), endovascular repair in 37 (4.3%), combined endovascular and open in 18 (2.3%), and nonoperative management in 258 (33.6%). Fasciotomy was performed more frequently in open than endovascular repair (p = 0.001) during index admission. Amputation rate was also increased in open repair, but this was not significant (p = 0.196). Arterial thromboembolus during index admission was more likely after endovascular or combined endovascular and open compared with open (24.3%, 55.6%, 16.7%, respectively, p < 0.001). Patients requiring both endovascular and open were more likely to undergo amputation postdischarge (hazard ratio, 4.11; 95% confidence interval, 1.16–14.53). Patients undergoing endovascular repair were more likely to die postdischarge (hazard ratio, 4.43; 95% confidence interval, 1.06–18.56) compared with patients who had open repair (median, 98.5 days postdischarge). CONCLUSIONS In a large cohort with popliteal artery injury, open repair was associated with lower rates of index admission arterial thromboembolus as well as postdischarge amputation and all-cause mortality. We recommend conducting a prospective multicenter study to examine the appropriate use of endovascular repair for this injury. LEVEL OF EVIDENCE Therapeutic, level IV.