Miracle-dz/UniFAR-FTUs huggingface dataset:
42A. NONEQUILIBRIUM PLASMA LAYER EVOLUTION IN A PURE NOBLE GAS FLOW IN THE MHD-GENERATOR CHANNEL

In works [1,2] the numerical simulation of evolution of nonequilibrium plasma layers in the channel of MHD generator under the influence of ionization-recombination processes and diffusion had been conducted. Considering the ionizationrecombination processes such factors were taken into account, as nonequilibrium distribution of atoms by excited states and free electrons by energy, and also an effective two-body process of dissociative recombination with a participation of a molecule ion. It had been shown that a regime close to the regime of "frozen ionization" was realized, when the gas in a nonequilibrium T-layer had a temperature about 2000–3000K, which exceeds the temperature of gas flow considerably, but is much less than the electron temperature. High temperature and low density of gas lead to the decrease of speed of the atomic ion conversion to the molecule ones and correspondingly, to the decrease of speed of dissociative recombination. As a result, the process of MHD conversion is going with the electron temperature below 1–1.5 10K, at which the ionization speed is insignificant. In this way, the regime is realized in which depending the electron temperature, the ionization ratio alters slowly and ionization-overheating instability doesn't develop. Among the problems which are to be studied now, we separate two questions, that can be considered within the framework of one-dimension model. The first, when considering the MHD interaction in the gas flow with plasma layer there was not considered the process of initial creation of plasma layer. At the inlet of MHD channel it was set periodically the region with an ionization ratio ~10 combined with an isobaric disturbance in which the gas temperature exceeded the temperature in non-perturbed gas by 1000–2000K. In connection with that the problem is set to carry out the numerical simulation of process of plasma layer creation, using the existing model of nonequilibrium plasma kinetics. As a result of numerical simulation the parameters of regime in that an uniformly ionized plasma layer with high ionization ratio and increased gas temperature would be created. The second, when simulating the MHD energy conversion the gas flow was considered in the MHD channel only. At the outlet of MHD channel the gas flow is supersonic and has an alternating velocity, density and temperature. To define the adiabatic efficiency of energy conversion correctly it is necessary to consider the transition of flow to the subsonic regime. For that purpose the MHD channel must be supplied by a diffuser at the outlet of that the constant value of pressure in the flow is set.
Multi-omics analyses show disease, diet, and transcriptome interactions with the virome.

BACKGROUND AND AIMS The gut virome includes eukaryotic viruses and bacteriophages that can shape the gut bacterial community and elicit host responses. The virome may be implicated in diseases such as irritable bowel syndrome (IBS), where gut bacteria play an important role in pathogenesis. Herein we provide a comprehensive and longitudinal characterization of the virome including DNA and RNA viruses and paired multi-omics data in a cohort of healthy subjects and patients with IBS. METHODS We selected two consecutive stool samples per subject from a longitudinal study cohort and performed metagenomic sequencing on DNA and RNA viruses after enriching for viral-like particles. Viral sequence abundance was evaluated over time as well as in the context of diet, bacterial composition and function, metabolite levels, colonic gene expression, host genetics, and IBS subsets. RESULTS We found that the gut virome was temporally stable and correlated with the colonic transcriptome. We identified IBS-subset specific changes in phage populations- Microviridae, Myoviridae, and Podoviridae species were elevated in IBS-D, and other Microviridae and Myoviridae species were elevated in IBS-C compared to healthy controls. We identified correlations between subsets of the virome and bacterial composition (unclassifiable "dark matter" and phages) and diet (eukaryotic viruses). CONCLUSIONS We found that the gut virome is stable over time but varies among subsets of IBS patients. It can be affected by diet and potentially influences host function via interactions with gut bacteria and/or altering host gene expression.
Structural brain abnormalities associated with cognitive impairments in bipolar disorder

Cognitive impairment has been highlighted as a core feature of bipolar disorder (BD) that often persists during remission. The specific brain correlates of cognitive impairment in BD remain unclear which impedes efficient therapeutic approaches. In a large sample of remitted BD patients, we investigated whether morphological brain abnormalities within dorsal prefrontal cortex (PFC) and hippocampus were related to cognitive deficits.
Sustained anti-obesity effects of life-style change and anti-inflammatory interventions after conditional inactivation of the activin receptor ALK7

Life-style change and anti-inflammatory interventions have only transient effects in obesity. It is not clear how benefits obtained by these treatments can be maintained longer term, specially during sustained high caloric intake. Constitutive ablation of the activin receptor ALK7 in adipose tissue enhances catecholamine signaling and lipolysis in adipocytes, and protects mice from diet-induced obesity. Here, we investigated the consequences of conditional ALK7 ablation in adipocytes of adult mice with pre-existing obesity. Although ALK7 deletion had little effect on its own, it synergized strongly with a transient switch to low-fat diet (life-style change) or anti-inflammatory treatment (Na-salicylate), resulting in enhanced lipolysis, increased energy expenditure, and reduced adipose tissue mass and body weight gain, even under sustained high caloric intake. By themselves, diet-switch and salicylate had only a temporary effect on weight gain. Mechanistically, combination of ALK7 ablation with either treatment strongly enhanced the levels of β3-AR, the main adrenergic receptor for catecholamine stimulation of lipolysis, and C/EBPα, an upstream regulator of β3-AR expression. These results suggest that inhibition of ALK7 can be combined with simple interventions to produce longer-lasting benefits in obesity.
Multiple CTCF sites cooperate with each other to maintain a TAD for enhancer–promoter interaction in the β‐globin locus

Insulators are cis‐regulatory elements that block enhancer activity and prevent heterochromatin spreading. The binding of CCCTC‐binding factor (CTCF) protein is essential for insulators to play the roles in a chromatin context. The β‐globin locus, consisting of multiple genes and enhancers, is flanked by two insulators 3′HS1 and HS5. However, it has been reported that the absence of these insulators did not affect the β‐globin transcription. To explain the unexpected finding, we have deleted a CTCF motif at 3′HS1 or HS5 in the human β‐globin locus and analyzed chromatin interactions around the locus. It was found that a topologically associating domain (TAD) containing the β‐globin locus is maintained by neighboring CTCF sites in the CTCF motif‐deleted loci. The additional deletions of neighboring CTCF motifs disrupted the β‐globin TAD, resulting in decrease of the β‐globin transcription. Chromatin interactions of the β‐globin enhancers with gene promoter were weakened in the multiple CTCF motifs‐deleted loci, even though the enhancers have still active chromatin features such as histone H3K27ac and histone H3 depletion. Genome‐wide analysis using public CTCF ChIA‐PET and ChIP‐seq data showed that chromatin domains possessing multiple CTCF binding sites tend to contain super‐enhancers like the β‐globin enhancers. Taken together, our results show that multiple CTCF sites surrounding the β‐globin locus cooperate with each other to maintain a TAD. The β‐globin TAD appears to provide a compact spatial environment that enables enhancers to interact with promoter.
DBU-Mediated cleavage of aryl- and heteroaryl disulfides

The capacity of the nitrogen nucleophile, 1,8-diazabicyclo(5.4.0)undec-7-ene (DBU) to reduce aryl- and heteroaryl disulfides to the corresponding mercaptans is demonstrated. While dicarboxylated disulfide analogues afford the mono-DBU disulfide salts, as confirmed by X-ray crystallography, the corresponding methyl esters are cleaved normally .
Nickel-Catalyzed Hydrosilylation of CO2 in the Presence of Et3B for the Synthesis of Formic Acid and Related Formates

The reaction of CO2 with Et3SiH catalyzed by the nickel complex [(dippe)Ni(μ-H)]2 (1) afforded the reduction products Et3SiOCH2OSiEt3 (12%), Et3SiOCH3 (3%), and CO, which were characterized by standard spectroscopic methods. Part of the generated CO was found as the complex [(dippe)Ni(CO)]2 (2), which was characterized by single-crystal X-ray diffraction. When the same reaction was carried out in the presence of a Lewis acid, such as Et3B, the hydrosilylation of CO2 efficiently proceeded to give the silyl formate (Et3SiOC(O)H) in high yields (85–89%), at 80 °C for 1 h. Further reactivity of the silyl formate to yield formic acid, formamides, and alkyl formates was also investigated.
Valence-Mending Passivation of Si(100) Surface: Principle, Practice and Application

Surface states have hindered and degraded many semiconductor devices since the Bardeen era. Surface states originate from dangling bonds on the surface. This paper discusses a generic solution to surface states, i.e. valence-mending passivation. For the Si (100) surface, a single atomic layer of valence-mending sulfur, selenium or tellurium can terminate ~99% of the dangling bonds, while group VII fluorine or chlorine can terminate the remaining 1%. Valence-mending passivation of Si (100) has been demonstrated using CVD, MBE and solution passivation. The keys to valence-mending passivation include an atomically-clean Si (100) surface for passivation and precisely one monolayer of valence-mending atoms on the surface. The passivated surface exhibits unprecedented properties. Electronically the Schottky barrier height between various metals and valence-mended Si (100) now follows more closely the Mott-Schottky theory. With metals of extreme workfunctions, new records for low and high Schottky barriers are created on Si (100). The highest barrier so far is 1.14 eV, i.e. a larger-than-bandgap barrier, and the lowest barrier is below 0.08 eV and potentially negative. Chemically silicidation between metal and valence-mended Si (100) is suppressed up to 500 °C, and the thermally-stable record Schottky barriers enable their applications in nanoelectronic, optoelectronic and photovoltaic devices. Another application is transition metal dichalcogenides. Valence-mended Si (100) is an ideal starting surface for growth of dichalcogenides, as it provides only van der Waals bonding to the dichalcogenide.
Unsupervised motion capture data segmentation based on topic model

In this paper, we propose an unsupervised motion segmentation method based on topical model borrowed from Natural Language Processing. We apply hierarchical clustering on motion dataset to obtain a list of representative poses to constitute motion 'vocabulary'. By doing so, motion capture data can be viewed as text which comprises a sequence of motion words. We use sliding window to generate a sequence of motion documents (with overlap between consecutive motion documents). Then we use Sparse Topical Coding (STC) model to extract sparse topical codes of motion documents and conduct spectral clustering to get motion segmentations. Silhouette coefficient is used to determine the value of K (number of motion types). The results of experiments show that our method can segment motions with a very high accuracy. Our method has a strong generalization ability that also performs well on motion data which is captured by different subjects, with various motion types, even though they are from different motion dataset (HDM05 in our experiment).
Interactive multi‐character motion retargeting

A motion retargeting process is necessary as the body size and proportion of the actors are generally different from those of the target characters. However, the original spatial relationship between the multiple characters and the environment is easily broken when using previous motion retargeting methods, which are generally performed for each character independently. Therefore, time‐consuming manual adjustments by animators are usually required to obtain satisfactory results. To address these issues, we present a novel multicharacter motion retargeting method that preserves various types of spatial relationships between characters and environments. We establish a unified deformation‐based framework for the motion retargeting of multiple characters (more than two) or nonhuman characters with complex interactions. Also, an interactive motion editing interface with immediate feedback to the user is provided. We experimentally show that our method achieves a speedup when compared with previous motion retargeting methods.
Encoding, Analysing and Modeling I-Folk: A New Database of Iberian Folk Music

Folk music is a fundamental immaterial heritage that promotes cultural identity. However, it lacks a substantial body of open access materials, and its promotion has been disconnected from the education curriculum. In this context, facilitated access to annotated high-quality folk music content can promote better educational tools and enhance cultural heritage literacy. Based on this, we advance and detail three main contributions: 1) a standardized model to musically annotate Iberian folk music; 2) a new database, named I-Folk, with annotated files following the proposed model; and 3) tools for navigating and retrieving folk music contents from the database. A particular emphasis is given to the educational application of the proposed model, contents, and tools in education. Ultimately, we strive for the promotion of Iberian folk music to the educators’ community.
Render‐based factorization for additive light field display

Augmented Reality (AR) and Virtual Reality (VR) applications enable viewers to experience 3D graphics immersively. However, current hardware either fails to provide multiple viewpoints like projectors or cause conflicts between vergence and accommodation like consumable headsets. Prior researchers have designed multi‐view displays to solve the problem by enabling view‐dependent images and focus cues. Nevertheless, it requires minutes to calculate one frame, which is critical for real‐time AR/VR applications. In this paper, we propose a new render‐based factorization for additive light field display and further improve the performance by optimizing the initialization of layers. We next compare our work with the state of the art and the results show that our solution has competitive results while the calculation takes less than 20 ms for each frame.
One Chatbot Per Person: Creating Personalized Chatbots based on Implicit User Profiles

Personalized chatbots focus on endowing chatbots with a consistent personality to behave like real users, give more informative responses, and further act as personal assistants. Existing personalized approaches tried to incorporate several text descriptions as explicit user profiles. However, the acquisition of such explicit profiles is expensive and time-consuming, thus being impractical for large-scale real-world applications. Moreover, the restricted predefined profile neglects the language behavior of a real user and cannot be automatically updated together with the change of user interests. In this paper, we propose to learn implicit user profiles automatically from large-scale user dialogue history for building personalized chatbots. Specifically, leveraging the benefits of Transformer on language understanding, we train a personalized language model to construct a general user profile from the user's historical responses. To highlight the relevant historical responses to the input post, we further establish a key-value memory network of historical post-response pairs, and build a dynamic post-aware user profile. The dynamic profile mainly describes what and how the user has responded to similar posts in history. To explicitly utilize users' frequently used words, we design a personalized decoder to fuse two decoding strategies, including generating a word from the generic vocabulary and copying one word from the user's personalized vocabulary. Experiments on two real-world datasets show the significant improvement of our model compared with existing methods.
The e-ACSL perspective on runtime assertion checking

Runtime Assertion Checking (RAC) is the discipline of verifying program assertions at runtime, i.e. when executing the code. Nowadays, RAC usually relies on Behavioral Interface Specification Languages (BISL) à la Eiffel for writing powerful code specifications. Since now more than 20 years, several works have studied RAC. Most of them have focused on BISL. Some others have also considered combinations of RAC with others techniques, e.g. deductive verification (DV). Very few tackle RAC as a verification technique that soundly generates efficient code from formal annotations. Here, we revisit these three RAC's research areas by emphasizing the works done in E-Acsl, which is both a BISL and a RAC tool for C code. We also compare it to others languages and tools.
Privacy-Aware Remote Information Retrieval User Experiments Logging Tool

User behaviors and experiences are the fundamental parts of information retrieval systems, but are often difficult to collect, bringing challenges to both applications and research. Recently, researchers have been exploring more fine-grained user behavior than simple clicks, such as time patterns, mouse/scroll patterns, etc., with their own specific laboratory experimental platforms. However, the lack of public available toolkits for logging user behaviors and experiences leads to difficulties on field study of remote user experiments in real scenarios. In this work, we propose a Privacy-Aware Remote User Logging Tool for remotely collecting user behaviors and explicit experience feedback, with a special care for user privacy. With this tool, participants can conduct the user experiments remotely without time and location constraints, giving researchers the possibility to observe users' more natural behaviors and experiences.
Propensity-scored Probabilistic Label Trees

Extreme multi-label classification (XMLC) refers to the task of tagging instances with small subsets of relevant labels coming from an extremely large set of all possible labels. Recently, XMLC has been widely applied to diverse web applications such as automatic content labeling, online advertising, or recommendation systems. In such environments, label distribution is often highly imbalanced, consisting mostly of very rare tail labels, and relevant labels can be missing. As a remedy to these problems, the propensity model has been introduced and applied within several XMLC algorithms. In this work, we focus on the problem of optimal predictions under this model for probabilistic label trees, a popular approach for XMLC problems. We introduce an inference procedure, based on the A*-search algorithm, that efficiently finds the optimal solution, assuming that all probabilities and propensities are known. We demonstrate the attractiveness of this approach in a wide empirical study on popular XMLC benchmark datasets.
Circumstances enhanced Criminal Court View Generation

Criminal Court View Generation is an essential task in legal intelligence, which aims to automatically generate sentences interpreting judgment results. The court view could be seen as the summary of crime circumstances in a case, including ADjudging Circumstance (ADC) and SEntencing Circumstance (SEC). However, different circumstances vary widely, and adopting them to generate court views directly may limit the generation performance. Therefore, it is necessary to identify the ADC and SEC related sentences in case facts and enhance them into the court view generation, respectively. To this end, in this paper, we propose a novel Circumstances enhanced Criminal Court View Generation (C3VG) method, consisting of the extraction and generation stage. Specifically, in the extraction stage, we design a Circumstances Selector to select ADC and SEC related sentences. After that, we apply them to two generators to generate the circumstances enhanced court views, respectively. After merging the two types of court views, we could obtain the final court views. We evaluate C3VG by conducting extensive experiments on a real-world dataset and experimental results clearly validate the effectiveness of our proposed model.
HemodynamicVR - Adapting the User’s Field Of View during Virtual Reality Locomotion Tasks to Reduce Cybersickness using Wearable Functional Near-Infrared Spectroscopy

We present HemodynamicVR, a virtual reality headset combined with functional near-infrared spectroscopy (fNIRS). We believe that sensing brain activity will enable novel interactions in virtual reality. In this paper, we assess a user’s cybersickness based on the change of their total hemoglobin concentration measured via an fNIRS device, and we try to mitigate that by changing the field of view (FOV) in real-time. In this experiment, participants experienced VR locomotion with an added variable FOV controlled by velocity changes and by fNIRS. The results suggest that fNIRS can detect cybersickness as registered by the qualitative SSQ test.
The Information Retrieval Anthology

We present the IR Anthology, a corpus of information retrieval publications accessible via a metadata browser and a full-text search engine. Following the example of the well-known ACL Anthology, the IR Anthology serves as a hub for researchers interested in information retrieval. Our search engine ChatNoir indexes the publications' full texts, enabling a focused search and linking users to the respective publisher's site for personal access. Listing more than 40,000 publications at the time of writing, the IR Anthology can be freely accessed at https://IR.webis. de.
Reinforcement Learning for Information Retrieval

There is strong interest in leveraging reinforcement learning (RL) for information retrieval (IR) applications including search, recommendation, and advertising. Just in 2020, the term "reinforcement learning" was mentioned in more than 60 different papers published by ACM SIGIR. It has also been reported that Internet companies like Google and Alibaba have started to gain competitive advantages from their RL-based search and recommendation engines. This full-day tutorial gives IR researchers and practitioners who have no or little experience with RL the opportunity to learn about the fundamentals of modern RL in a practical hands-on setting. Furthermore, some representative applications of RL in IR systems will be introduced and discussed. By attending this tutorial, the participants will acquire a good knowledge of modern RL concepts and standard algorithms such as REINFORCE and DQN. This knowledge will help them better understand some of the latest IR publications involving RL, as well as prepare them to tackle their own practical IR problems using RL techniques and tools. Please refer to the tutorial website (https://rl-starterpack.github.io/) for more information.