Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards a Crypto Asset Taxonomy: A Text Classification-based Approach

There are over 1900 cryptocurrencies trading in the market as of September 2020 and the number is rapidly growing. In the current crypto scene, cryptocurrencies are seen as investment vehicles by many, yet every crypto asset is designed to operate in a specific sector within a pre-defined business model. In addition to sector, there are various characteristics and factors that differentiate one crypto asset from another. Crypto investors can leverage these factors and characteristics and use these indicators to create different trading strategies. In our work, in order to guide the decision-making process for investors and to help them analyse crypto assets in a holistic manner, we classify the crypto assets under various characteristics, aiming towards a crypto asset taxonomy. In this paper, we focus on automated annotation of the cryptocurrencies in terms of sector, transaction anonymity and asset type through the public information. Though the information we utilise is public, it is scattered around quite a vast number of sources in different formats. Therefore, we generated an annotated dataset by collecting information from various sources. We utilised several supervised learning algorithms, including both traditional ones and more recent neural models, and analyzed the classification performance for the three aspects.
Unbiased warped-area sampling for differentiable rendering

Differentiable rendering computes derivatives of the light transport equation with respect to arbitrary 3D scene parameters, and enables various applications in inverse rendering and machine learning. We present an unbiased and efficient differentiable rendering algorithm that does not require explicit boundary sampling. We apply the divergence theorem to the derivative of the rendering integral to convert the boundary integral into an area integral. We rewrite the converted area integral to a form that is suitable for Monte Carlo rendering. We then develop an efficient Monte Carlo sampling algorithm for solving the area integral. Our method can be easily plugged into a traditional path tracer and does not require dedicated data structures for sampling boundaries. We analyze the convergence properties through bias-variance metrics, and demonstrate our estimator's advantages over existing methods for some synthetic inverse rendering examples.
Monolith

We propose Monolith, a monolithic pressure-viscosity-contact solver for more accurately, robustly, and efficiently simulating non-trivial two-way interactions of rigid bodies with inviscid, viscous, or non-Newtonian liquids. Our solver simultaneously handles incompressibility and (optionally) implicit viscosity integration for liquids, contact resolution for rigid bodies, and mutual interactions between liquids and rigid bodies by carefully formulating these as a single unified minimization problem. This monolithic approach reduces or eliminates an array of problematic artifacts, including liquid volume loss, solid interpenetrations, simulation instabilities, artificial "melting" of viscous liquid, and incorrect slip at liquid-solid interfaces. In the absence of solid-solid friction, our minimization problem is a Quadratic Program (QP) with a symmetric positive definite (SPD) matrix and can be treated with a single Linear Complementarity Problem (LCP) solve. When friction is present, we decouple the unified minimization problem into two subproblems so that it can be effectively handled via staggered projections with alternating LCP solves. We also propose a complementary approach for non-Newtonian fluids which can be seamlessly integrated and addressed during the staggered projections. We demonstrate the critical importance of a contact-aware, unified treatment of fluid-solid coupling and the effectiveness of our proposed Monolith solver in a wide range of practical scenarios.
Selection of Information Streams in Social Sensing: an Interdependence- and Cost-aware Ranking Method

In this work we address the problem of critical source selection in social sensing. We propose an approach to the ranking of information streams, which is aware of the interdependence among streams (redundancy and synergies), of the cost of individual streams, and of the cost related to the integration of multiple streams. The method is based on the use of the Coalitional Game Theory concept of Power Index, and relies on the polynomial-time estimate of the stream sets characteristics. With respect to other works using a power index, the method takes into account that the problem has a non-trivial cost structure.
A practical ply-based appearance model of woven fabrics

Simulating the appearance of woven fabrics is challenging due to the complex interplay of lighting between the constituent yarns and fibers. Conventional surface-based models lack the fidelity and details for producing realistic close-up renderings. Micro-appearance models, on the other hand, can produce highly detailed renderings by depicting fabrics fiber-by-fiber, but become expensive when handling large pieces of clothing. Further, neither surface-based nor micro-appearance model has not been shown in practice to match measurements of complex anisotropic reflection and transmission simultaneously. In this paper, we introduce a practical appearance model for woven fabrics. We model the structure of a fabric at the ply level and simulate the local appearance of fibers making up each ply. Our model accounts for both reflection and transmission of light and is capable of matching physical measurements better than prior methods including fiber based techniques. Compared to existing micro-appearance models, our model is light-weight and scales to large pieces of clothing.
Purification and characterisation of amylolytic enzymes from Lipomyces starkeyi

A purification scheme has been developed for the extracellular carbohydrases; a­glucosidase and a-amylase, secreted by the ascosporogenous soil yeast Lipomyces starkeyi NCYC 1436. Growth and optimum enzyme yield conditions were determined with cultures of L. starkeyi grown at 30°C on a medium containing 2% soluble starch, 1 % yeast extract and 1 % Bactopeptone, appropriate enzyme assay procedures having been devised. Both enzymes were initially precipitated from the cell free supernatant by an 85%(w/v) ammonium sulphate precipitation. Many different chromatographic media were then assessed, but the choice of a hydrophobic (Phenyl Sepharose CL-4B) column had the advantage of utilizing the ammonium sulphate precipitate with minimum sample preparation. The pellet was adjusted to lM salt and adsorbed to the hydrophobic column. Elution of the two activities was carried out by a series of decreasing salt washes. Although fractionation of the two enzymes was not complete, the column was effective in eliminating a substantial quantity of inactive material, whilst maintaining good recoveries of approximately 59% for a-glucosidase and 72% for a-amylase. Both enzymes were substantially purified using ion exchange chromatography ( Q­Sepharose fast flow medium), with a-glucosidase being apparently close to electrophoretic homogeneity; elution of the two enzyme activities was carried out at 4°C, using a linear gradient with sodium acetate buffer, pH 5.0. Individual HIC fractions purified by ion exchange showed between a 0.3 to 24.6-fold increase in purity for a-glucosidase, and between a 2.8 to 7.6 increase in purity for a­amylase. However, by selecting the most active a-glucosidase fraction isolated after running the 0.01M HIC fraction on ion exchange, the purification factor rose to 83.4. Several properties of the purified a-:glucosidase enzyme were investigated. The molecular weight of the a-glucosidase was determined by electrophoresis under denaturing and non-denaturing conditions, after ion exchange chromatography. A single major band was detected by SDS-PAGE with an estimated molecular weight of 93,000 + 5,000 Daltons, and under native conditions, the molecular weight was estimated at 162,000 Daltons. Specific enzyme activity staining of the native gel confirmed that the single band was an a-glucosidase. However, isoelectric focusing of the purified Lipomyces starkeyi a-glucosidase, detected three bands - within the pl range of 4.6-5.0. Further characterisation studies revealed the pH and temperature optimum of the purified L. starkeyi a-glucosidase at 4.5 and 55°C respectively. Km and Vmax measurements using a range of substrates suggested that the a­glucosidase had a broad substrate specificity but showed a marked preference for substrates with a-1,4 linkages such as soluble starch, PNPG, and a-1,3 linkages, such as n1gerose. SDS and native gel electrophoresis ( combined with specific activity staining) revealed 3 distinct a-amylase activities, and the molecular weights were determined as 82,000, 68,000 and 48,500 Daltons.
An Evaluation of the Doctor-Interpretability of Generalized Additive Models with Interactions

Applying machine learning in healthcare can be problematic because predictions might be biased, can lack robustness, and are prone to overly rely on correlations. Interpretable machine learning can mitigate these issues by visualizing gaps in problem formalization and putting the responsibility to meet additional desiderata of machine learning systems on human practitioners. Generalized additive models with interactions are transparent, with modular one-and two-dimensional risk functions that can be reviewed and, if necessary, removed. The key objective of this study is to determine whether these models can be interpreted by doctors to safely deploy them in a clinical setting. To this end, we simulated the review process of eight risk functions trained on a clinical task with twelve clinicians and collected information about objective and subjective factors of interpretability. The ratio of correct answers for dichotomous statements covering important properties of risk functions was 0 . 83 ± 0 . 02 ( n = 360) and the median of the participants’ certainty to correctly understand them was Certain ( n = 96) on a seven-level Likert scale (one = Very Uncertain to seven = Very Certain ). These results suggest that doctors can correctly interpret risk functions of generalized additive models with interactions and also feel conﬁdent to do so. However, the evaluation also identiﬁed several interpretability issues and it showed that interpretability of generalized additive models depends on the complexity of risk functions.
Match

We present MATch, a method to automatically convert photographs of material samples into production-grade procedural material models. At the core of MATch is a new library DiffMat that provides differentiable building blocks for constructing procedural materials, and automatic translation of large-scale procedural models, with hundreds to thousands of node parameters, into differentiable node graphs. Combining these translated node graphs with a rendering layer yields an end-to-end differentiable pipeline that maps node graph parameters to rendered images. This facilitates the use of gradient-based optimization to estimate the parameters such that the resulting material, when rendered, matches the target image appearance, as quantified by a style transfer loss. In addition, we propose a deep neural feature-based graph selection and parameter initialization method that efficiently scales to a large number of procedural graphs. We evaluate our method on both rendered synthetic materials and real materials captured as flash photographs. We demonstrate that MATch can reconstruct more accurate, general, and complex procedural materials compared to the state-of-the-art. Moreover, by producing a procedural output, we unlock capabilities such as constructing arbitrary-resolution material maps and parametrically editing the material appearance.
Severity of Ongoing Post-Concussive Symptoms as a Predictor of Cognitive Performance Following a Pediatric Mild Traumatic Brain Injury

Abstract Objective: This study aimed to examine the predictors of cognitive performance in patients with pediatric mild traumatic brain injury (pmTBI) and to determine whether group differences in cognitive performance on a computerized test battery could be observed between pmTBI patients and healthy controls (HC) in the sub-acute (SA) and the early chronic (EC) phases of injury. Method: 203 pmTBI patients recruited from emergency settings and 159 age- and sex-matched HC aged 8–18 rated their ongoing post-concussive symptoms (PCS) on the Post-Concussion Symptom Inventory and completed the Cogstate brief battery in the SA (1–11 days) phase of injury. A subset (156 pmTBI patients; 144 HC) completed testing in the EC (~4 months) phase. Results: Within the SA phase, a group difference was only observed for the visual learning task (One-Card Learning), with pmTBI patients being less accurate relative to HC. Follow-up analyses indicated higher ongoing PCS and higher 5P clinical risk scores were significant predictors of lower One-Card Learning accuracy within SA phase, while premorbid variables (estimates of intellectual functioning, parental education, and presence of learning disabilities or attention-deficit/hyperactivity disorder) were not. Conclusions: The absence of group differences at EC phase is supportive of cognitive recovery by 4 months post-injury. While the severity of ongoing PCS and the 5P score were better overall predictors of cognitive performance on the Cogstate at SA relative to premorbid variables, the full regression model explained only 4.1% of the variance, highlighting the need for future work on predictors of cognitive outcomes.
A plethora of carbapenem resistance in Acinetobacter baumannii: no end to a long insidious genetic journey

Acinetobacter baumannii, notorious for causing nosocomial infections especially in patients admitted to intensive care unit (ICU) and burn units, is best at displaying resistance to all existing antibiotic classes. Consequences of high potential for antibiotic resistance has resulted in extensive drug or even pan drug resistant A. baumannii. Carbapenems, mainly imipenem and meropenem, the last resort for the treatment of A. baumannii infections have fallen short due to the emergence of carbapenem resistant A. baumannii (CRAB). Though enzymatic degradation by production of class D β-lactamases (Oxacillinases) and class B β-lactamases (Metallo β-lactamases) is the core mechanism of carbapenem resistance in A. baumannii; however over-expression of efflux pumps such as resistance-nodulation cell division (RND) family and variant form of porin proteins such as CarO have been implicated for CRAB inception. Transduction and outer membrane vesicles-mediated transfer play a role in carbapenemase determinants spread. Colistin, considered as the most promising antibacterial agent, nevertheless faces adverse effects flaws. Cefiderocol, eravacycline, new β-lactam antibiotics, non-β-lactam-β-lactamase inhibitors, polymyxin B-derived molecules and bacteriophages are some other new treatment options streamlined.
‘The Primacy of ‘Home’: An exploration of how older adults’ transition to life in a care home towards the end of the first year

Abstract This grounded theory study sought to explore how older adults’ experience the transition from living at home to a care home with a specific focus on the latter part of the first year of the move. The study was carried out within a large Health Trust in the UK between August 2017 and May 2019. Purposive sampling was used in the initial stages of data collection. Thereafter and consistent with grounded theory methodology, theoretical sampling was employed to undertake semi‐structured interviews with 17 individuals from eight care homes between 5 and 12 months after the move. This paper reports five key categories which were: (a) The lasting effect of first Impressions ‘They helped me make my mind up’ (b) On a Journey ‘I just take it one day at a time’, (c) Staying connected and feeling ‘at home’ ‘You get something good out of it you know…you get hope’. (d) Managing loss and grief ‘It was important for me to say cheerio to the house’ and (e) Caring relationships ‘I didn't realise that I was lonely until I had company’. Together these five categories formed the basis of the core category ‘The Primacy of ‘Home’ which participants identified as a place they would like to feel valued, nurtured and have a sense of belonging. This study identifies that it is important for individual preferences and expectations to be managed from the outset of the move. Individuals and families need to be supported to have honest and caring conversations to promote acceptance and adaptation to living in a care home while continuing to embrace the heart of ‘home’. Key recommendations from this study include the need to raise awareness of the significance of the ongoing psychological and emotional well‐being needs of older people which should be considered in policy directives and clinical practice.
Food irradiation : principles and applications

Preface. Introduction (R. Molins). Radiation Inactivation of Microorganisms (J. Dickson). Food Irradiation Chemistry (E. Stewart). Disinfestation of Stored Grains, Pulses, Dried Fruits and Nuts, and Other Dried Foods (M. Ahmed). Irradiation as a Quarantine Treatment (G. Hallman). Irradiation of Meats and Poultry (R. Molins). Irradiation Processing of Fish and Shellfish Products (M. Kilgen). Irradiation of Fruits and Vegetables (P. Thomas). Irradiation of Tuber and Bulb Crops (P. Thomas). Irradiation of Minimally Processed Foods (J. Farkas). Radiation Decontamination of Spices, Herbs, Condiments, and Other Dried Food Ingredients (J. Farkas). Combination Treatments Involving Food Irradiation (M. Patterson). Development of Irradiated Shelf- Stable Meat and Poultry Products (D. Thayer). Detection Methods for Irradiated Foods (E. Stewart). Process Control and Dosimetry in Food Irradiation (D. Ehlermann). Economic and Technical Considerations in Food Irradiation (P. Kunstadt). Global Status of Food Irradiation in 2000 (R. Molins). Index.
Red algae natural products for prevention of lipopolysaccharides (LPS)-induced liver and kidney inflammation and injuries

Abstract Background: The liver and kidney inflammation due to bacterial infection is one of the most common pathological problems leading to tissue damage or disease. In many liver and kidney disorders, which represent serious global health burden with a high economic cost, oxidative stress-related inflammation and apoptosis are important pathogenic components, finally resulting in acute liver and/or kidney failure. Erythropoietin and its analogues are well known to influence the interaction between apoptosis and inflammation in liver and kidney. Objective: The aim of the present study is to investigate and clarify the effect of Galaxaura oblongata (G. oblongata) red algae on lipopolysaccharides (LPS)-induced acute liver and kidney injury of mice with endotoxemia and associated molecular mechanism from inflammation, apoptosis and oxidative stress levels. Results: The current study cleared out that treatment of rats with the G. oblongata extract prior to LPS injection significantly lowered serum cytokines, including NF-κB, MPO and LPO, and improved liver apoptosis through suppressing protein tyrosine kinase signaling pathway, and that may be due to antibacterial activity as well antioxidant capacity of G. oblongata extract. Conclusion: The present study was cleared out the possibility of administration of G. oblongata red algae as a multi products source for biotechnological, medical, nutraceutical and pharmaceutical applications due to highly antioxidant and anti-inflammatory capacities even although more investigations are required for separating, purifying and characterizing these bioactive compounds.
What, Where, When and How of Visual Word Recognition: A Bibliometrics Review

The neural/mental operations involved in the process of visual word recognition (VWR) are fundamental for the efficient comprehension of written/printed words during reading. The present study used CiteSpace, a visual analysis software, to identify the intellectual landscape where VWR has been reviewed in the past decade. Thus, synthesized co-citation networks were analyzed to explore and discuss the main questions raised in the VWR literature: the research fronts and the emerging trends of research on this topic. Our results showed that the main questions addressed in VWR studies during the last decade have been focused on four main aspects related to “what,” “where,” “when,” and “how” of VWR; to be specific, the different types of representations assessed during VWR (“what”), the locations and the timing of the brain activity involved in VWR (“where” and “when”), and the interactivity among different representations during processing (“how”). Among the revised studies, letter position coding was found to be the main topic of interest, possibly reflecting the critical role of this process. Furthermore, the evidence found in these studies consistently supported that VWR implies access to phonological, semantic, and morphological representations, which interact and modulate the processing of written words, particularly during early stages. Altogether, our findings showed the evolution in VWR literature regarding the different cognitive and neural operations involved in this process, highlighting the growing interest over the last decade toward the top-down way that mental representations interact.
Visceral adiposity index is closely associated with urinary albumin‐creatinine ratio in the Chinese population with prediabetes

Visceral obesity is a major health issue and is a risk factor for an atherogenic state. Visceral obesity has been reported to be a crucial link between albuminuria and cardiovascular diseases (CVD). This study attempted to explore the association between visceral obesity and albuminuria in prediabetic individuals.
Increasing heart vascularisation after myocardial infarction using brain natriuretic peptide stimulation of endothelial and WT1+ epicardial cells

Brain natriuretic peptide (BNP) treatment increases heart function and decreases heart dilation after myocardial infarction (MI). Here, we investigated whether part of the cardioprotective effect of BNP in infarcted hearts related to improved neovascularisation. Infarcted mice were treated with saline or BNP for 10 days. BNP treatment increased vascularisation and the number of endothelial cells in all areas of infarcted hearts. Endothelial cell lineage tracing showed that BNP directly stimulated the proliferation of resident endothelial cells via NPR-A binding and p38 MAP kinase activation. BNP also stimulated the proliferation of WT1+ epicardium-derived cells but only in the hypoxic area of infarcted hearts. Our results demonstrated that these immature cells have a natural capacity to differentiate into endothelial cells in infarcted hearts. BNP treatment increased their proliferation but not their differentiation capacity. We identified new roles for BNP that hold potential for new therapeutic strategies to improve recovery and clinical outcome after MI.