Miracle-dz/UniFAR-FTUs huggingface dataset:
Cerberus: Minimalistic Multi-shard Byzantine-resilient Transaction Processing

To enable high-performance and scalable blockchains, we need to step away from traditional consensus-based fully-replicated designs. One direction is to explore the usage of sharding in which we partition the managed dataset over many shards that independently operate as blockchains. Sharding requires an efficient fault-tolerant primitive for the ordering and execution of multi-shard transactions, however. In this work, we seek to design such a primitive suitable for distributed ledger networks with high transaction throughput. To do so, we propose Cerberus, a set of minimalistic primitives for processing single-shard and multi-shard UTXO-like transactions. Cerberus aims at maximizing parallel processing at shards while minimizing coordination within and between shards. First, we propose Core-Cerberus, that uses strict environmental requirements to enable simple yet powerful multi-shard transaction processing. In our intended UTXO-environment, Core-Cerberus will operate perfectly with respect to all transactions proposed and approved by well-behaved clients, but does not provide any guarantees for other transactions. To also support more general-purpose environments, we propose two generalizations of Core-Cerberus: we propose Optimistic-Cerberus, a protocol that does not require any additional coordination phases in the well-behaved optimistic case, while requiring intricate coordination when recovering from attacks; and we propose Pessimistic-Cerberus, a protocol that adds sufficient coordination to the well-behaved case of Core-Cerberus, allowing it to operate in a general-purpose fault-tolerant environments without significant costs to recover from attacks. Finally, we compare the three protocols, showing their potential scalability and high transaction throughput in practical environments.
Frictional Wear and Corrosion Behavior of AlCoCrFeNi High-Entropy Alloy Coatings Synthesized by Atmospheric Plasma Spraying

High-entropy alloy coatings (HEAC) exhibit good frictional wear and corrosion resistances, which are of importance for structure materials. In this study, the microstructure, surface morphology, hardness, frictional wear and corrosion resistance of an AlCoCrFeNi high-entropy alloy coating synthesized by atmospheric plasma spraying (APS) were investigated. The frictional wear and corrosion resistance of the coating are simultaneously improved with an increase of the power of APS. The influence of the APS process on the microstructure and mechanical behavior is elucidated. The mechanisms of frictional wear and corrosion behavior of the AlCoCrFeNi HEAC are discussed in detail.
13 Root Development in Arabidopsis

The Arabidopsis plant, like most angiosperms, produces an extensive root system designed to function in the anchorage of the plant and absorption of water and mineral ions. The development of the plant root system is relatively easy to study, despite the fact that roots are generally subterranean organs. Several properties of roots make them amenable to developmental studies: (1) The root apical meristem is accessible and not enclosed by developing organs or primordia; (2) the root is free of pigments and therefore essentially transparent; (3) there are relatively few differentiated cell types in roots; (4) root morphogenesis in many plants occurs in a continuous and relatively uniform fashion without significant developmental transitions; and (5) cell files are easy to observe in longitudinal sections and their origin can be traced back to the apical meristem. Our understanding of root morphology and development in Arabidopsis has come largely from studies of the seedling root system. The small size of the Arabidopsis seedling and its ability to be grown aseptically under defined conditions facilitates morphological, physiological, and genetic analyses. The genetic studies of root development in Arabidopsis have been particularly illuminating and have led to the isolation of many root developmental mutants. In this chapter, we review our current understanding of root development in Arabidopsis by describing research on roots of Arabidopsis as well as roots of other plants, where appropriate. For readers interested in a detailed discussion of physiological or functional aspects of roots, reviews can be found in Torrey and Clarkson.
A Decoupling Method for Antennas With Different Frequencies in 5G Massive MIMO Application

A method to weaken the interference of antennas working in different frequencies is proposed in this paper. It uses a Frequency Selective Surface (FSS) placed between two different antennas. For one antenna, the FSS acts as an electromagnetically transparent structure, so the electromagnetic wave will penetrate the FSS and radiates into the free space. For the other one, the FSS acts as an artificial magnetic conductor, reflecting the incoming energy. With this design, two adjacent antennas could keep their individual performance especially radiation patterns normal. It is worth noting that although the FSS has been used in many aspects, such as reducing antenna’s radar cross section or reducing the coupling between the identical antennas, its application in the field of ‘different antennas decoupling’ is the first time. An embodiment is displayed in this paper for verification. Two antennas worked at different bands of 5G are placed very close with an FSS structure inserted. It turns out that the whole antenna has good electrical and radiation properties over the working band. This decoupling strategy can be very useful in 5G Massive MIMO application.
Exploring Trapping Problem on Weighted Heterogeneous Networks Induced by Extended Corona Product

Since many dynamical processes can be analyzed in the framework of trapping problem, it is great important to explore trapping problem on diverse complex systems or networks. However, addressing trapping problem on networks generated by graph products is still less touched. In this paper, by taking type of random walks and number of traps into account and compiling four different scenarios, trapping problem is touched more completely on resultant weighted heterogeneous networks of extended corona product and weight reinforcement mechanism. In more detail, we study standard random walk and delayed random walk on the network with a deep trap fixed at one initial node in the first and second scenarios respectively. This two types of random walks are further investigated on the network with three traps placed at initial three nodes in more challenging third and fourth scenarios. In all this four scenarios, the solutions of average trapping time(<inline-formula> <tex-math notation="LaTeX">$ATT$ </tex-math></inline-formula>) are deduced analytically to measure trapping efficiency, which agree well with their corresponding numerical counterparts and show that <inline-formula> <tex-math notation="LaTeX">$ATT$ </tex-math></inline-formula> grows sub-linearly with network size. Besides, expressions of <inline-formula> <tex-math notation="LaTeX">$ATT$ </tex-math></inline-formula> obtained in the second and fourth scenarios indicate that the parameter <inline-formula> <tex-math notation="LaTeX">$p$ </tex-math></inline-formula> governing delayed random walk alters the pre-factor of <inline-formula> <tex-math notation="LaTeX">$ATT$ </tex-math></inline-formula> but has no effect on the leading scaling of <inline-formula> <tex-math notation="LaTeX">$ATT$ </tex-math></inline-formula>. Furthermore, the comparisons between expression of <inline-formula> <tex-math notation="LaTeX">$ATT$ </tex-math></inline-formula> in first and third scenarios, expression of <inline-formula> <tex-math notation="LaTeX">$ATT$ </tex-math></inline-formula> in second and fourth scenarios imply that <inline-formula> <tex-math notation="LaTeX">$ATT$ </tex-math></inline-formula> can be lowered and trapping efficiency can be improved accordingly by introducing more traps. In summary, this work may enrich the clues for understanding trapping issue and modulating trapping process on more general heterogeneous weighted networks.
An Economic Incentive for D2D Assisted Offloading Using Stackelberg Game

The explosive growth of traffic demand challenges the current cellular network. Device-to-Device assisted offloading is a promising solution for alleviating traffic overloading burdens. However, a content transmitter (CT) unwillingly participates in cellular offloading due to the selfish nature and non-cooperation. To this end, an incentive mechanism initiated by mobile users (MUs) is proposed to motivate the CT’s participation for maximizing the CT’s profit and mobile users’ utilities. In particular, we consider the utility of a mobile user by jointly combining effects of social awareness and network congestion. The MUs and content providers offer proper economic payments to compensate the CT’s energy consumption cost. The interactions among participants formulate a two-stage Stackelberg game. The main aim of this game is to reach Nash equilibrium (NE) that neither the CT nor MUs have incentives to deviate unilaterally. We theoretically prove the existence and uniqueness of NE. Furthermore, iterative algorithms are designed to calculate NE for obtaining the best strategies of the CT and MUs. Numerical results demonstrate the robustness and feasibility of our proposed model.
Network Inference from a Mixture of Diffusion Models for Fake News Mitigation

The dissemination of fake news intended to deceive people, influence public opinion and manipulate social outcomes, has become a pressing problem on social media. Moreover, information sharing on social media facilitates diffusion of viral information cascades. In this work, we focus on understanding and leveraging diffusion dynamics of false and legitimate contents in order to facilitate network interventions for fake news mitigation. We analyze real-world Twitter datasets comprising fake and true news cascades, to understand differences in diffusion dynamics and user behaviours with regards to fake and true contents. Based on the analysis, we model the diffusion as a mixture of Independent Cascade models (MIC) with parameters \theta_T , \theta_F over the social network graph; and derive unsupervised inference techniques for parameter estimation of the diffusion mixture model from observed, unlabeled cascades. Users influential in the propagation of true and fake contents are identified using the inferred diffusion dynamics. Characteristics of the identified influential users reveal positive correlation between influential users identified for fake news and their relative appearance in fake news cascades. Identified influential users tend to be related to topics of more viral information cascades than less viral ones; and identified fake news influential users have relatively fewer counts of direct followers, compared to the true news influential users. Intervention analysis on nodes and edges demonstrates capacity of the inferred diffusion dynamics in supporting network interventions for mitigation.
A Measurement Model of Mutual Influence for Information Dissemination

The recent development of the mobile Internet and the rise of social media have significantly enriched the way people access information. Accurate modeling of the probability of information propagation between users is essential for studying information dissemination issues in social networks. As the dissemination of information is inseparable from the interactions between users, the probability of propagation can be characterized by such interactions. In general, there are differences in the dissemination modes of information that carry different topics in a real social network. Using these factors, we propose a method (TMIVM) to measure the mutual influence between users at the topic level. The method associates two vectorization parameters for each user—an influence vector and a susceptibility vector—where the dimensions of the vector represent different topic categories. The magnitude of the mutual influence between users on different topics can be obtained by the product of the corresponding elements of the vectors. Specifically, in this article, we fit a social network historical information cascade data through Survival Analysis to learn the parameters of the influence and susceptibility vectors. The experimental results on a synthetic data set and a real Microblog data set show that this method better measures the propagation probability and information cascade predictions compared to other methods.
Enhanced Video Analytics for Sentiment Analysis Based on Fusing Textual, Auditory and Visual Information

With the widespread of online videos and digital transformation, video informatics and analytics have recently gained substantially increasing importance with an impressive success in a variety of tasks such as digital marketing, video surveillance and security systems, healthcare systems, talk show analysis, analysis of influencing groups in social media, and target tracking. This paper evaluates the potential contribution of various video modalities and how they are correlated to video analytics for sentiment analysis in the morphologically-rich Arabic language. Moreover, an enhanced approach is presented for video analytics to predict the speaker’s sentiment of multi-dialect Arabic through the integration of textual, auditory and visual modalities. Different features are extracted to represent each modality including prosodic and spectral acoustic features to represent audio, neural word embedding to represent audio text transcript, and dense optical-flow descriptors to represent visual modality. The extracted features are used individually to train two machine learning classifiers to provide a baseline. Then, the effectiveness of various combinations of modalities is verified using multi-level fusion (feature, score and decision). The experimental results demonstrate that the proposed approach of combining different modalities can lead to more accurate prediction of speaker’s sentiment with above 94% accuracy.
Cervical Cancer Screening with DNA-HPV Testing and Precancerous Lesions Detection: A Brazilian Population-based Demonstration Study

Abstract Objective To evaluate the rates of precancerous lesions, colposcopy referral, and positive predictive value (PPV) by age groups of a population-based screening with DNA-HPV testing. Methods The present demonstration study compared 16,384 HPV tests performed in the first 30 months of the program with 19,992 women tested in the cytology screening. The colposcopy referral rate and PPV for CIN2+ and CIN3+ by age group and screening program were compared. The statistical analysis used the chi-squared test and odds ratio (OR) with 95% confidence interval (95%CI). Results The HPV tests were 3.26% positive for HPV16-HPV18 and 9.92% positive for 12 other HPVs with a 3.7 times higher colposcopy referral rate than the cytology program, which had 1.68% abnormalities. Human Papillomavirus testing detected 103 CIN2, 89 CIN3, and one AIS, compared with 24 CIN2 and 54 CIN3 detected by cytology ( p < 0.0001). The age group between 25 and 29 years old screened by HPV testing had 2.4 to 3.0 times more positivity, 13.0% colposcopy referral, twice more than women aged 30 to 39 years old (7.7%; p < 0.0001), and detected 20 CIN3 and 3 early-stage cancer versus 9 CIN3 and no cancer by cytology screening (CIN3 OR= 2.10; 95%CI: 0.91–5.25; p = 0.043). The PPV of colposcopy for CIN2+ ranged from 29.5 to 41.0% in the HPV testing program. Conclusion There was a significant increase in detections of cervix precancerous lesions in a short period of screening with HPV testing. In women < 30 years old, the HPV testing exhibited more positivity, high colposcopy referral rate, similar colposcopy PPV to older women, and more detection of HSIL and early-stage cervical cancer.
How I treat venous thromboembolism in pregnancy.

Of 1,000 pregnant women, one to two will experience venous thromboembolism (VTE) during pregnancy or the postpartum period. Pulmonary embolism (PE) is a leading cause of maternal mortality and deep vein thrombosis (DVT) leads to maternal morbidity and may diminish quality of life due to post-thrombotic syndrome during the rest of a woman's life. Despite this important burden, the evidence base for the management of pregnancy-related VTE is weak. Recommendations from evidence-based guidelines are often extrapolated from the non-pregnant population and thus weak or conditional. As a consequence, there is wide variation of practice. In women with a suspicion of PE, the pregnancy-adapted YEARS algorithm is safe and efficient, with 39% of women not needing computed tomographic pulmonary angiography (CTPA) to rule out PE. Low-molecular-weight heparin (LMWH) in therapeutic doses is the treatment of choice during pregnancy, and anticoagulation (LMWH or vitamin K antagonists [VKA] postpartum) should be continued until 6 weeks after delivery with a minimum total duration of 3 months. Use of LMWH or vitamin K antagonists does not preclude breastfeeding. Postpartum, direct oral anticoagulants (DOACs) are an option if women do not breastfeed and long-term use is intended. Management of delivery, including the type of analgesia, requires a multidisciplinary approach and depends on local preferences and patient-specific conditions. Several options are possible and include waiting for spontaneous delivery with temporary interruption of LMWH. Prophylaxis for the prevention of recurrent VTE in subsequent pregnancies is indicated in most women with a history of VTE.
Insights into the Potential of Hardwood Kraft Lignin to Be a Green Platform Material for Emergence of the Biorefinery

Lignin is an abundant, renewable, and relatively cheap biobased feedstock that has potential in energy, chemicals, and materials. Kraft lignin, more specifically, has been used for more than 100 years as a self-sustaining energy feedstock for industry after which it has finally reached more widespread commercial appeal. Unfortunately, hardwood kraft lignin (HWKL) has been neglected over these years when compared to softwood kraft lignin (SWKL). Therefore, the present work summarizes and critically reviews the research and development (R&D) dealing specifically with HWKL. It will also cover methods for HWKL extraction from black liquor, as well as its structure, properties, fractionation, and modification. Finally, it will reveal several interesting opportunities for HWKL that include dispersants, adsorbents, antioxidants, aromatic compounds (chemicals), and additives in briquettes, pellets, hydrogels, carbon fibers and polymer blends and composites. HWKL shows great potential for all these applications, however more R&D is needed to make its utilization economically feasible and reach the levels in the commercial lignin market commensurate with SWKL. The motivation for this critical review is to galvanize further studies, especially increased understandings in the field of HWKL, and hence amplify much greater utilization.
The Geometry of Noise in Color and Spectral Image Sensors

Digital images are always affected by noise and the reduction of its impact is an active field of research. Noise due to random photon fall onto the sensor is unavoidable but could be amplified by the camera image processing such as in the color correction step. Color correction is expressed as the combination of a spectral estimation and a computation of color coordinates in a display color space. Then we use geometry to depict raw, spectral and color signals and noise. Geometry is calibrated on the physics of image acquisition and spectral characteristics of the sensor to study the impact of the sensor space metric on noise amplification. Since spectral channels are non-orthogonal, we introduce the contravariant signal to noise ratio for noise evaluation at spectral reconstruction level. Having definitions of signal to noise ratio for each steps of spectral or color reconstruction, we compare performances of different types of sensors (RGB, RGBW, RGBWir, CMY, RYB, RGBC).
Influence of acquisition settings and radiation exposure on CT lung densitometry—An anthropomorphic ex vivo phantom study

Objectives To systematically evaluate the influence of acquisition settings in conjunction with raw-data based iterative image reconstruction (IR) on lung densitometry based on multi-row detector computed tomography (CT) in an anthropomorphic chest phantom. Materials and methods Ten porcine heart-lung explants were mounted in an ex vivo chest phantom shell, six with highly and four with low attenuating chest wall. CT (Somatom Definition Flash, Siemens Healthineers) was performed at 120kVp and 80kVp, each combined with current-time products of 120, 60, 30, and 12mAs, and was reconstructed with filtered back projection (FBP) and IR (Safire, Siemens Healthineers). Mean lung density (LD), air density (AD) and noise were measured by semi-automated region-of interest (ROI) analysis, with 120kVp/120 mAs serving as the standard of reference. Results Using IR, noise in lung parenchyma was reduced by ~ 31% at high attenuating chest wall and by ~ 22% at low attenuating chest wall compared to FBP, respectively (p<0.05). IR induced changes in the order of ±1 HU to mean absolute LD and AD compared to corresponding FBP reconstructions which were statistically significant (p<0.05). Conclusions Densitometry is influenced by acquisition parameters and reconstruction algorithms to a degree that may be clinically negligible. However, in longitudinal studies and clinical research identical protocols and potentially other measures for calibration may be required.
Thiolation of Biopolymers for Developing Drug Delivery Systems with Enhanced Mechanical and Mucoadhesive Properties: A Review

Biopolymers are extensively used for developing drug delivery systems as they are easily available, economical, readily modified, nontoxic, biodegradable and biocompatible. Thiolation is a well reported approach for enhancing mucoadhesive and mechanical properties of polymers. In the present review article, for the modification of biopolymers different thiolation methods and evaluation/characterization techniques have been discussed in detail. Reported literature on thiolated biopolymers with enhanced mechanical and mucoadhesive properties has been presented conspicuously in text as well as in tabular form. Patents filed by researchers on thiolated polymers have also been presented. In conclusion, thiolation is an easily reproducible and efficient method for customization of mucoadhesive and mechanical properties of biopolymers for drug delivery applications.
Risk Stratification for Naloxone Rescue Kit Interventions at a Veterans Affairs Teaching Hospital.

Because of its analgesic effect, duloxetine is also used to treat chronic pain or neuropathic pain such as fibromyalgia and painful diabetic neuropathy. Especially, duloxetine is one of only few drugs approved by the US Food and Drug Administration for the treatment of fibromyalgia; it showed a significant improvement in fibromyalgia-associatedpain. Relevant to facial pain, chronic nonorganic orofacial pain (burning mouth syndrome and atypical odontalgia) was significantly relieved by 12-week treatment with 20 to 40mg/d of duloxetine. Although the facial parts that exhibited pain were different from those reported in the previous study, our patient responded to a 20-mg/d dose of duloxetine, and her facial pain was relieved after 4 weeks of treatment. Also, our patient did not show depressive symptoms before duloxetine treatment, suggesting that the analgesic effect of duloxetine is independent of its antidepressant action in this case. We could not completely rule out placebo effect. However, the treatment time course showed that duloxetine relieved the patient's facial pain in a sustained manner,