Miracle-dz/UniFAR-FTUs huggingface dataset:
Conjectures on world literature

'Nowadays, national literature doesn’t mean much: the age of world literature is beginning, and everybody should contribute to hasten its advent. ’ This was Goethe, of course, talking to Eckermann in 1827; and these are Marx and Engels, twenty years later, in 1848: ‘National one-sidedness and narrow-mindedness become more and more impossible, and from the many national and local literatures, a world literature arises. ’ Weltliteratur: this is what Goethe and Marx have in mind. Not ‘comparative’, but world literature: the Chinese novel that Goethe was reading at the time of that exchange, or the bourgeoisie of the Manifesto, which has ‘given a cosmopolitan character to production and consumption in every country’. Well, let me put it very simply: comparative literature has not lived up to these beginnings. It’s been a much more modest intellectual enterprise, fundamentally limited t o Western Europe, and mostly revolving around the river Rhine (German philologists working on French literature). Not much more.
Performance of a Noninvasive Time-Harmonic Elastography Technique for Liver Fibrosis Evaluation Using Vibration Controlled Transient Elastography as Reference Method

Aim: This study aimed to evaluate the diagnosis performance of time-harmonic elastography (THE) technique in real life in assessing liver fibrosis, considering vibration-controlled transient elastography (VCTE) as a reference method. Material and Method: We prospectively evaluated outpatients from the gastroenterology department. Liver stiffness (LS) was measured by the THE system by dedicated operators, and by VCTE by experienced operators. The diagnostic accuracy of THE in staging liver fibrosis was assessed. We also performed an intra- and interobserver reproducibility sub-analysis on a sub-group of 27 subjects, where liver stiffness measurements (LSM) were performed by a novice, an elastography expert, and an ultrasound expert. Results: Of the 165 patients, using VCTE cut-off values, 49.6% were F0-F1, 15.7% were F2, 6.6% were F3, and 28.1% were F4. A direct, significant and strong correlation (r = 0.82) was observed between LSM assessed by VCTE and THE, p < 0.0001. The cut-off for ruling out liver cirrhosis (LC) by THE on our study group was <1.61 m/s (7.77 kPa)–AUROC = 0.90 [95% CI (0.82–0.93)], Se = 90.7%, Sp = 66.6%, PPV = 55.7%, NPV = 93.9%. The cut-off for ruling in LC by THE was >1.83 m/s (10 kPa)-AUROC = 0.90 [95% CI (0.82–0.93)], p < 0.0001, Se = 65.1%, Sp = 96.7%, PPV = 90.3%, NPV = 85.7%. The overall agreement between examiners was excellent: 0.94 (95% CI: 0.89–0.97); still, the ICCs were higher for the more experienced elastography examiner: 0.92 (95% CI: 0.82–0.96) vs. 0.94 (95% CI: 0.87–0.97) vs. 0.97 (95% CI: 0.95–0.99). Conclusions: THE is a feasible and reproducible elastography technique that can accurately rule in and rule out advanced liver disease.
The feasibility of using the Microsoft KinectTM to measure the degree of movements’ precision for affected upper limbs motion of children with hemiplegia in home-based therapy: Feasibility study

4.9? 3.9? 4.8?
KLS-A: A Full-Life-Time Anomaly Detection Method

Anomaly detection is a significant field in the industry. The anomaly detection system could detect the possible abnormalities of equipment in time, and reduce the human and material resources loss caused by equipment abnormality. It is an effective method to analyze operating status of the equipment by collecting its status data. Anomaly detection usually relies on large amounts of equipment status data. After analyzing a large amount of normal data, a model of normal data is obtained. When abnormal data arrives, the data will be identified by analyzing if the data is different from the existing model. However, a device’s Full-Life-Time must go through the cold-boot stage, when a device is cold-booted, the amount of data is usually small. As the operating time of the equipment increases, data gradually accumulates. So, the efficient anomaly detection research usually focuses on the equipment in smooth-running stage. Some traditional anomaly detection methods can be used when the amount of data is small, but they usually have limited anomaly detection capabilities.This paper is motivated by the problem, we have proposed an anomaly detection method, which could run during cold-boot and also fully explore the ability of large amount of data. We call it KLS-A. "KLS" means the three components of the algorithm: KMeans, LSTM and selector, "A" means adaptive, this means our algorithm can be easily transplanted in different equipment. Through the transformation of KMeans and LSTM, KLS-A has strong adaptability, and it can automatically adjust parameters according to the amount of data. By using a customized selector, KLS-A can freely switch algorithms under different data volumes to meet the anomaly detection at different stages of the equipment. Therefore, it can maintain a good anomaly detection effect under different stages.Meanwhile, we implemented KLS-A on Spark and applied it to the monitoring of SINOPEC's hydrocondensation tower. We monitored twenty-three indicators of the hydrocondensation tower and tested the anomaly detection ability from cold-boot stage to smooth running stage. We also used the same data set to do comparative experiments with traditional anomaly detection algorithms. The results show four abnormalities can be predicted at the earliest time by KLS-A and all stages can guarantee a high accuracy rate.
Locomotor illusions are generated by perceptual body-environment organization

While one is walking, the stimulation by one’s body forms a structure with the stimulation by the environment. This locomotor array of stimulation corresponds to the human-environment relation that one’s body forms with the environment it is moving through. Thus, the perceptual experience of walking may arise from such a locomotor array of stimulation. Humans can also experience walking while they are sitting. In this case, there is no stimulation by one’s walking body. Hence, one can experience walking although a basic component of a locomotor array of stimulation is missing. This may be facilitated by perception organizing the sensory input about one’s body and environment into a perceptual structure that corresponds to a locomotor array of stimulation. We examined whether locomotor illusions are generated by this perceptual formation of a locomotor structure. We exposed sixteen seated individuals to environmental stimuli that elicited either the perceptual formation of a locomotor structure or that of a control structure. The study participants experienced distinct locomotor illusions when they were presented with environmental stimuli that elicited the perceptual formation of a locomotor structure. They did not experience distinct locomotor illusions when the stimuli instead elicited the perceptual formation of the control structure. These findings suggest that locomotor illusions are generated by the perceptual organization of sensory input about one’s body and environment into a locomotor structure. This perceptual body-environment organization elucidates why seated human individuals experience the sensation of walking without any proprioceptive or kinaesthetic stimulation.
Simulation of Fluid Flows based on the Data-driven Evolution of Vortex Particles

Fluid solvers that provide accurate and fast fluid simulations are of great importance in many scientific and engineering disciplines. Conventional numerical solvers based on the Eulerian description of the flow provide highly accurate solutions to the Navier-Stokes equations. However, there is typically a significant amount of computational effort is required to execute such Eulerian simulations. On the other hand, fluid solvers built on the Lagrangian description of the flow are more appealing in terms of its vicinity to the true physics, since it treats the actual fluid particles as the primary computational elements. A particular group of Lagrangian particle methods based on vorticity, instead of velocity, as the primary flow variable, delivers velocity field solutions, which are always divergence-free. These vortex methods have an inherent advantage that the particles need to be present only in the regions where vorticity exists, and therefore fewer fluid particles are required to execute simulations as compared to their counterparts with velocity-based formulations. Recently, deep learning solutions for fluid dynamics problems by the application of artificial neural networks has become more prominent. Neural networks encode the information about the governing laws of fluid dynamics in its parameters using the knowledge extracted from data samples during training. The aim of this work is to use deep learning to learn fluid dynamics with Lagrangian vortex particles as the primary flow representation. Solution strategies to train and evaluate the neural networks for predicting Lagrangian vortex particle dynamics for different flow scenarios are presented throughout this work. Conceptualization and implementation of an approach to model interaction between vortex particles based on the Taylor series expansion of the velocity form the core of this work. We demonstrate that our trained neural networks produce fluid simulations with reasonable accuracy for different flow scenarios while respecting appropriate constraints pertaining to fluid dynamics.
The interactome of porcine epidemic diarrhea virus nucleocapsid protein

Background Many viral proteins specifically interact with cellular proteins to facilitate virus replication. Understanding these interactions can decipher the viral infection mechanism and provide potential targets for antiviral therapy. Porcine epidemic diarrhea virus (PEDV), the agent of PED, causes numerous economic losses for the swine industry each year. Till now, no effective vaccine or drugs are available to contain this disease. As a result, it is critical urgent to elucidate the PEDV interactome. The nucleocapsid (N) of PEDV plays an important role in viral replication. Results In this study, the N gene was cloned into pEGFP-C1 and transfected into 293T cells. The interactome of N was elucidated by label-free mass spectrometry. A total of 125 cellular proteins interacting with PEDV N protein were discovered, of which 4 cellular proteins, DHX9, NCL, KAP1, TCEA1, were confirmed by pull down, immunoprecipitation, and co-localization. Conclusions The interactome of N protein supplied a powerful tool to explore the role of N in PEDV infection and therapeutic targets.
Phase Distinctions in Type Theory

Introduction Type systems were originally introduced in programming languages to provide a degree of static checking, achieved through typechecking. As type systems become more complex and typechecking more sophisticated, the attribute static becomes less appropriate. The situation is better described by thinking that the execution of a program is carried out in two phases: a typechecking phase (compile-time) and an execution phase (run time). 1 Normally one would expect the very notion of type system to enforce this phase distinction. This is true for all simple type systems found in programming languages (e.g. Pascal), which are usually variations on the type system of first-order typed λcalculus. This phase distinction remains when generalizing to second-order typed λcalculus, which can be used to model parametric polymorphism (e.g. in ML [Milner 84]) and abstract types [Mitchell 85]. In all these languages, phases can be distinguished syntactically: there are separate syntactic sorts of type expressions and value expressions. Phase distinction are however lost when moving to languages like Pebble [Burstall 84a] based on dependent types [Martin-Lof 73]. A dependent type is a type which may depend upon the value of some expression. This dependency directly causes phase mixing, unless one is careful to distinguish between compile-time values (e.g. given by constant expressions in Pascal), and run-time values. The loss of phase distinctions manifests itself as the inability to perform compilation, since compilers are based on a syntactic translation phase which strips out
An intact S-layer is advantageous to Clostridioides difficile within the host

Clostridioides difficile is responsible for substantial morbidity and mortality in antibiotically-treated, hospitalised, elderly patients, in which toxin production correlates with diarrhoeal disease. While the function of these toxins has been studied in detail, the contribution of other factors, including the paracrystalline surface layer (S-layer), to disease is less well known. Here, we highlight the essentiality of the S-layer in vivo by reporting the recovery of S-layer revertants, following infection with the S-layer-null strain, FM2.5. Sequencing of the slpA gene revealed either correction of the original point mutation or modification of the sequence upstream of the mutation, which restored the reading frame, and translation of slpA. Selection of these strains was rapid, with up to 90% of isolates identified as revertants 24 h post infection. Two revertant isolates, RvA and RvB, showed modification of 3 and 13 amino acids respectively, compared to wild type sequence. Structural determination of SlpA from RvB revealed a different orientation of its domains, resulting in a reorganisation of the lattice assembly and changes in interacting interfaces which might result in functional differences. These revertants showed differing patterns of disease in vivo; RvA causing equivalent severity to R20291 and RvB an attenuated FM2.5-like phenotype. Comparative RNA sequencing (RNA-Seq) analysis of in vitro grown isolates showed large changes in differentially expressed genes (DEGs) between R20291 and FM2.5 namely in TcdA/TcdB expression, in transcripts associated with sporulation and those linked to cell wall integrity, which may account for attenuation observed in vivo. In comparison, smaller differences were observed between RvA/R20291, and RvB/FM2.5 respectively, which correlated with observed disease severity in vivo. Cumulatively, these data highlight that the S-layer plays a role in C. difficile disease. Author Summary The S-layer of C. difficile is a paracrystalline array that covers the outer surface of the bacterial cell but its contribution to overall disease remains unclear. A previously described, spontaneous slpA-null mutant, FM2.5, with a point mutation in slpA offered an opportunity to study the role of the S-layer in vivo. Here, we confirm that this strain is less virulent in vivo despite effectively colonising the host and producing toxin. We also show in vivo selection for sequence modifications that restore slpA translation and produce an S-layer. While such modifications do not affect the overall 3D structure of individual SlpA (sub)domains, they can lead to altered orientation of the structural domains and subsequent S-layer assembly. Importantly, RNA-Seq analysis in vitro showed large differences in gene expression between FM2.5 and R20291. Detected differences in transcription of genes involved in toxin expression and sporulation suggests that the S-layer provides a selective survival advantage within the host, which contributes to disease severity.
Embedding loose spanning trees in 3-uniform hypergraphs

In 1995, Koml\'os, S\'ark\"ozy and Szemer\'edi showed that every large $n$-vertex graph with minimum degree at least $(1/2 + \gamma)n$ contains all spanning trees of bounded degree. We consider a generalization of this result to loose spanning hypertrees in 3-graphs, that is, linear hypergraphs obtained by successively appending edges sharing a single vertex with a previous edge. We show that for all $\gamma$ and $\Delta$, and $n$ large, every $n$-vertex 3-uniform hypergraph of minimum vertex degree $(5/9 + \gamma)\binom{n}{2}$ contains every loose spanning tree $T$ with maximum vertex degree $\Delta$. This bound is asymptotically tight, since some loose trees contain perfect matchings.
Improving Accuracy and Scalability of Personal Recommendation Based on Bipartite Network Projection

Bipartite network projection method has been recently employed for personal recommendation. It constructs a bipartite network between users and items. Treating user taste for items as resource in the network, we allocate the resource via links between user nodes and item nodes. However, the taste model employed by existing algorithms cannot differentiate “dislike” and “unrated” cases implied by user ratings. Moreover, the distribution of resource is solely based on node degrees, ignoring the different transfer rates of the links. To enhance the performance, this paper devises a negative-aware and rating-integrated algorithm on top of the baseline algorithm. It enriches the current user taste model to encompass “like,” “dislike,” and “unrated” information from users. Furthermore, in the resource distribution stage, we propose to initialize the resource allocation according to user ratings, which also determines the resource transfer rates on links afterward. Additionally, we also present a scalable implementation in the MapReduce framework by parallelizing the algorithm. Extensive experiments conducted on real data validate the effectiveness and efficiency of the proposed algorithms.
DBM-tree: método de acesso métrico sensível à densidade local

A metric space is defined as a set of objects and a metric distance function that is used to measure the similarity between these objects. It allows the development of Metric Access Methods (MAMs) that are able to answer similarity queries in these datasets quickly. Usually these MAMs are materialized through a hierarchical structure called metric trees. These trees are kept balanced because it tends to maintain the height of the tree small, aiming to reduce the number of disk access required to answer queries. However, it is difficult to maintain the tree balanced without overlapping nodes covering a large number of objects, leading to the degradation of query performance. In other words, reducing the overlap among nodes increases the performance of metric trees. A possible solution is to relax the need to keep metric trees balanced. This work presents a new dynamic MAM called DBM-tree (Density-Based Metric tree), which changes the rule that imposes a rigid balancing policy, allowing a small amount of unbalancing in some regions of it. This unbalancing minimizes the degree of overlapping among some high-density nodes and, consequently, increases query answering performance. The amount of relaxation is set by the user and is strongly enforced in the tree. The height of the tree is higher in high-density regions, in order to keep a balance between searching in various subtrees and searching deeply in each subtree. The DBM-tree has an optimization algorithm called DBM-SlimDown that improves the performance in trees through reorganizing the elements among its nodes. The experiments performed over synthetic and real-world datasets showed that the DBM-tree outperforms the traditional MAMs. The DBM-tree is, in average, 50% faster than traditional MAMs and reduces the number of distance calculations and disk accesses up to 50%. After executing the DBM-Slim-Down algorithm, the performance achieves improvements up to 30% for range and k-nearest neighbor queries. Moreover, the DBM-tree is scalable regarding time, number of disk accesses and distance calculations.
A prototype framework for a Bangla question answering system using translation based on transliteration and table look-up as an interface for the medical domain

Question Answering (QA) Systems allow the user to ask questions in a natural language and obtain an exact answer. Through this thesis work, we tried to learn the important issues in the field of Question Answering (QA) systems. We peeked into the internals of many established QA systems. We explored the capabilities of each of them and the reasons that make them good at their task. Then we looked into the details of cross-language QA task. We learned that most of such systems employ some form of machine translation engines. We aimed to have a complete cross-language QA system for Bangla. The language Bangla is among one of the most widely spoken languages of the world but is still in its early stages of research regarding language processing resources and tools. Thus for the cross-language QA task we did not have access to translation engine which was very essential. So we narrowed down our aim and finally proposed an innovative concept of translation based on transliteration and a table look-up approach as an interface for a cross-language QA task where one of the languages involved is at a disadvantage in terms of digital language resources and tools. The proposed concept is implemented in a form of a prototype framework for a very controlled cross-language QA scenario. We do not claim that our proposed approach is a complete approach for a Bangla QA task but we did achieve promising results that can help in Bangla QA task until mature Bangla language processing tools become available.
Version Peer reviewed version Link to publication record in King ' s Research Portal

In the last decade there has been a breakthrough in the construction of theories leading to models for the simulation of atomic scale processes in steel. In this paper the theory is described and developed and used to demonstrate calculations of the di↵usivity and trapping of hydrogen in iron and the structures of carbon vacancy complexes in steel. 1 Historical Introduction In 1947 Geo↵rey Raynor wrote “. if metallurgists of this country do not learn about the electron theories they may discover too late, that the industry in other countries has benefited from knowledge of modern theories and is developing new alloys. ” Hume-Rothery and Raynor had understood perfectly from the work of Mott and Jones before the war that to unravel the complexities of metal phase diagrams required the powerful methods of metal physics that had arisen out of the new quantum mechanics of Schrödinger and Heisenberg of the 1920’s [1]. But some 15 years later, Hume-Rothery writes “The work of the last ten years has emphasised the extreme di culty of producing any really quantitative theory of the electronic structure of metals, except for those of the alkali group. ” The breakthrough came just a few years after that with the appearance of the density functional theory (DFT) of Kohn and co-workers [2, 3] and for which Walter Kohn shared the Nobel Prize in Chemistry (with John Pople) in 1998. It was understood then, and is understood now, that what holds together the atoms in a metal are the valence electrons. These act as the “glue” which is ultimately responsible for the properties that we exploit in metallurgy to produce alloys of prescribed hardness, ductility, fracture resistance, and so on. What Hume-Rothery meant by electronic structure is the stationary state solutions of the Schrödinger equation for the electrons in condensed matter moving in the (so called “external”) potential of the fixed nuclei. At issue in the 1960’s was the awareness that this was fundamentally a many electron problem, requiring the knowledge of a wavefunction (r1, s1, r2, s2 . . . rN , sN ) which depends on the positions and spins of all the N electrons involved. On the other hand, every student learns quantum mechanics in terms of a Schrödinger equation whose solution, (r, s), is the wavefunction of a single particle moving in an electrostatic