Miracle-dz/UniFAR-FTUs huggingface dataset:
Rain Removal From Light Field Images With 4D Convolution and Multi-Scale Gaussian Process

Existing deraining methods focus mainly on a single input image. However, with just a single input image, it is extremely difficult to accurately detect and remove rain streaks, in order to restore a rain-free image. In contrast, a light field image (LFI) embeds abundant 3D structure and texture information of the target scene by recording the direction and position of each incident ray via a plenoptic camera. LFIs are becoming popular in the computer vision and graphics communities. However, making full use of the abundant information available from LFIs, such as 2D array of sub-views and the disparity map of each sub-view, for effective rain removal is still a challenging problem. In this paper, we propose a novel method, 4D-MGP-SRRNet, for rain streak removal from LFIs. Our method takes as input all sub-views of a rainy LFI. To make full use of the LFI, it adopts 4D convolutional layers to simultaneously process all sub-views of the LFI. In the pipeline, the rain detection network, MGPDNet, with a novel Multi-scale Self-guided Gaussian Process (MSGP) module is proposed to detect high-resolution rain streaks from all sub-views of the input LFI at multi-scales. Semi-supervised learning is introduced for MSGP to accurately detect rain streaks by training on both virtual-world rainy LFIs and real-world rainy LFIs at multi-scales via computing pseudo ground truths for real-world rain streaks. We then feed all sub-views subtracting the predicted rain streaks into a 4D convolution-based Depth Estimation Residual Network (DERNet) to estimate the depth maps, which are later converted into fog maps. Finally, all sub-views concatenated with the corresponding rain streaks and fog maps are fed into a powerful rainy LFI restoring model based on the adversarial recurrent neural network to progressively eliminate rain streaks and recover the rain-free LFI. Extensive quantitative and qualitative evaluations conducted on both synthetic LFIs and real-world LFIs demonstrate the effectiveness of our proposed method.
TexPrax: A Messaging Application for Ethical, Real-time Data Collection and Annotation

Collecting and annotating task-oriented dialog data is difficult, especially for highly specific domains that require expert knowledge. At the same time, informal communication channels such as instant messengers are increasingly being used at work. This has led to a lot of work-relevant information that is disseminated through those channels and needs to be post-processed manually by the employees. To alleviate this problem, we present TexPrax, a messaging system to collect and annotate _problems_, _causes_, and _solutions_ that occur in work-related chats. TexPrax uses a chatbot to directly engage the employees to provide lightweight annotations on their conversation and ease their documentation work. To comply with data privacy and security regulations, we use an end-to-end message encryption and give our users full control over their data which has various advantages over conventional annotation tools. We evaluate TexPrax in a user-study with German factory employees who ask their colleagues for solutions on problems that arise during their daily work. Overall, we collect 202 task-oriented German dialogues containing 1,027 sentences with sentence-level expert annotations. Our data analysis also reveals that real-world conversations frequently contain instances with code-switching, varying abbreviations for the same entity, and dialects which NLP systems should be able to handle.
Restricted Phased Space Thermodynamics for Black Holes in Higher Dimensions and Higher Curvature Gravities

The recently proposed restricted phase space thermodynamics is shown to be applicable to a large class of higher dimensional higher curvature gravity models coupled to Maxwell field, which are known as black hole scan models and are labeled by the spacetime dimension d and the highest order k of the Lanczos-Lovelock densities appearing in the action. Three typical example cases with (d,k)=(5,1),(5,2) and (6,2) are chosen as example cases and studied in some detail. These cases are representatives of Einstein-Hilbert, Chern-Simons and Born-Infield like gravity models. Our study indicates that the Einstein-Hilbert and Born-Infield like gravity models have similar thermodynamic behaviors, e.g., the existence of isocharge T−S phase transitions with the same critical exponents, the existence of isovoltage T−S transitions and the Hawking-Page like transitions, and the similar high temperature asymptotic behaviors for the isocharge heat capacities, etc. However, the Chern-Simons like (5,2)-model behaves quite differently. Neither isocharge nor isovoltage T−S transitions could occur and no Hawking-Page like transition is allowed. This seems to indicate that the Einstein-Hilbert and Born-Infield like models belong to the same universality class while the Chern-Simons like models do not.
Efficient Parameterised Compilation for Hybrid Quantum Programming

Near term quantum devices have the potential to outperform classical computing through the use of hybrid classical-quantum algorithms such as Variational Quantum Eigensolvers. These iterative algorithms use a classical optimiser to update a parameterised quantum circuit. Each iteration, the circuit is executed on a physical quantum processor or quantum computing simulator, and the average measurement result is passed back to the classical optimiser. When many iterations are required, the whole quantum program is also recompiled many times. We have implemented explicit parameters that prevent recompilation of the whole program in the quantum programming framework OpenQL, called OpenQLPC. These parameters improve the compilation and therefore total runtime for hybrid quantum-classical algorithms. We compare the time required for compilation and simulation of the MAXCUT algorithm in OpenQLpcto the same algorithm in both PyQuil and Qiskit. We show that efficient handling of parameterised circuits results in up to 70 % reduction in total compilation time for the MAXCUT benchmark, and leads to a reduced total execution time. When using OpenQLPC, compilation of hybrid algorithms is up to two times faster than when using PyQuil or Qiskit.
Time Minimization and Online Synchronization for Multi-agent Systems under Collaborative Temporal Tasks

Multi-agent systems can be extremely efficient when solving a team-wide task in a concurrent manner. However, without proper synchronization, the correctness of the combined behavior is hard to guarantee, such as to follow a specific ordering of sub-tasks or to perform a simultaneous collaboration. This work addresses the minimum-time task planning problem for multi-agent systems under complex global tasks stated as Linear Temporal Logic (LTL) formulas. These tasks include the temporal and spatial requirements on both independent local actions and direct sub-team collaborations. The proposed solution is an anytime algorithm that combines the partial-ordering analysis of the underlying task automaton for task decomposition, and the branch and bound (BnB) search method for task assignment. Analyses of its soundness, completeness and optimality as the minimal completion time are provided. It is also shown that a feasible and near-optimal solution is quickly reached while the search continues within the time budget. Furthermore, to handle fluctuations in task duration and agent failures during online execution, an adaptation algorithm is proposed to synchronize execution status and re-assign unfinished subtasks dynamically to maintain correctness and optimality. Both algorithms are validated rigorously over large-scale systems via numerical simulations and hardware experiments, against several strong baselines.
On the Convergence of Inexact Gradient Descent With Controlled Synchronization Steps

We develop a gradient-like algorithm to minimize a sum of peer objective functions based on coordination through a peer interconnection network. The coordination admits two stages: the first is to constitute a gradient, possibly with errors, for updating locally replicated decision variables at each peer and the second is used for error-free averaging for synchronizing local replicas. Unlike many related algorithms, the errors permitted in our algorithm can cover a wide range of inexactnesses, as long as they are bounded. Moreover, we do not impose any gradient boundedness conditions for the objective functions. Furthermore, the second stage is not conducted in a periodic manner, like many related algorithms. Instead, a locally verifiable criterion is devised to dynamically trigger the peer-to-peer coordination at the second stage, so that expensive communication overhead for error-free averaging can significantly be reduced. Finally, the convergence of the algorithm is established under mild conditions.
A User-Centered Investigation of Personal Music Tours

Streaming services use recommender systems to surface the right music to users. Playlists are a popular way to present music in a list-like fashion, i.e. as a plain list of songs. An alternative are tours, where the songs alternate with segues, which explain the connections between consecutive songs. Tours address the user need of seeking background information about songs, and are found to be superior to playlists, given the right user context. In this work, we provide, for the first time, a user-centered evaluation of two tour-generation algorithms (Greedy and Optimal) using semi-structured interviews. We assess the algorithms, we discuss attributes of the tours that the algorithms produce, we identify which attributes are desirable and which are not, and we enumerate several possible improvements to the algorithms, along with practical suggestions on how to implement the improvements. Our main findings are that Greedy generates more likeable tours than Optimal, and that three important attributes of tours are segue diversity, song arrangement and song familiarity. More generally, we provide insights into how to present music to users, which could inform the design of user-centered recommender systems.
Does Lorentz-symmetric design boost network performance in jet physics?

In the deep learning era, improving the neural network performance in jet physics is a rewarding task as it directly contributes to more accurate physics measurements at the LHC. Recent research has proposed various network designs in consideration of the full Lorentz symmetry, but its benefit is still not systematically asserted, given that there remain many successful networks without taking it into account. We conduct a detailed study on the Lorentz-symmetric design. We propose two generalized approaches for modifying a network - these methods are experimented on Particle Flow Network, ParticleNet, and LorentzNet, and exhibit a general performance gain. We also reveal that the notable improvement attributed to the"pairwise mass"feature in the network is due to its introduction of a structure that fully complies with Lorentz symmetry. We confirm that Lorentz-symmetry preservation serves as a strong inductive bias of jet physics, hence calling for attention to such general recipes in future network designs.
Effect of Seminal Transforming Growth Factorß1 (TGFß1) and Glutathione on Apoptosis in Spermatozoa from Tunisian Infertile Men Andrology-Open Access

We aimed to compare the effect of TGFB1 and glutathione on sperm necrosis in three groups of patients with increased necrospermia. The study included 120 men aged 37.6 ± 4.6 years consulting for sterility of the couple. Patients were subdivided into three groups according to the percentage of necrotic spermatozoa: necrospermia<30%; N=40), moderate necrozoospermia (50-80%, n=45) and severe necrozoospermia (>80%) For each patient, the sperm parameters were evaluated according to WHO standards, TGFB1 and glutathione Oxidized and reduced was carried out by the ELISA technique and by spectrophotometry respectively. We found a significant increase in the levels of TGFβ1 and DFI in moderate and severe necrospermia groups and positive correlations between these two factors and sperm parameters (numeration, mobility and morphology). In addition, a significant decrease in seminal GHSt was observed in the necrozoospermic groups compared to the control group. A strong correlation was observed between the degree of necrozoospermia and the fragmentation of sperm DNA (r=0.878, p=0.001). In addition, a significant positive correlation between TGFβ1 and DFI in the two groups of patients with moderate necrospermia (r=0.43, p<0.05) and severe necrospermia (r=0.52, p<0.05). This confirms that seminal TGFβ1 is a factor in the fragmentation of spermatozoa DNA. These results suggest that decreased glutathione and increased seminal TGFβ1 are important risk factors that can lead to a succession of morphological and functional alterations of spermatozoa resulting in necrozoospermia. Their perturbation in seminal plasma can lead to mediocre results of medically assisted procreation.
Mapping the contours of an emerging phase out science

Phase-out has emerged as a policy approach to confront multiple sustainability crises. From ozone-depleting substances and hazardous chemicals to fossil fuels and transport technologies, phase-out experiences have been documented by diverse scientific communities. To consolidate this dispersed knowledge and inspire more systematic research, we map the evolution of scientific discussions about phase-out through a systematic literature review. Examining 870 papers published since 1970, we trace the evolving nature of phase-out strategies in terms of targets, geographic and industrial contexts, policy instruments and drivers. This provides a multi-faceted overview of an emerging and rapidly growing ‘phase-out science’ rooted across the full spectrum of scientific enquiry. Evolution of this science is marked by broadening engagement with a growing diversity of targets, contexts, and policies. Our analysis also shows how phase-out policies have recently gained momentum as a tool to tackle climate change, with a particular focus on fossil fuels and associated technologies. Results reveal the contours of a rapidly growing ‘phase-out science’ whose character has evolved distinctly over time. Informed by diverse academic disciplines, phase-out science is united by a common interest in the role of this policy approach in tackling various sustainability challenges. Over its 50-year evolution, discussions have broadened to encompass an increasing number and diversity of phase-out targets, geographic and industrial contexts, policy instruments and drivers. The past decade is marked by growing emphasis on using phase-out policies to mitigate climate change, with fossil fuels and associated technologies increasingly targeted.
PRBM_A_312008 1053..1062

*These authors contributed equally to this work Background: Research on the “dark side” of feeling trusted has mainly focused on the workplace, paying much less attention to the non-work domain. Using social exchange theory as a basis, this research explored the effect of feeling trusted on work–family conflict and its underlying mechanisms. Methods: Data were collected in two waves from 375 full-time employees from companies in different industries in China and path analysis was used to test our hypotheses. Results: The results showed that psychological detachment mediated the relationship between feeling trusted and work–family conflict. This mediating effect was moderated by positive reciprocity beliefs, with the effect being stronger for employees with strong (vs weak) positive reciprocity beliefs. Conclusion: This study advances research on the negative effects of feeling trusted, indicating that while it might be important for employees to repay supervisors’ trust, they also need to clearly delineate the boundary between work and family to reduce work–family conflict.
Depletion of Cellular Glutathione Ar,7V'-Bis(fra/f.s-4-Hydroxycycloliexyl)-./V'-nitrosourea as a Determinant of Sensitivity of K562 Human Leukemia Cells to 4-Hydroperoxycyclophosphamide1

A',A"-Bis(frani-4-hydroxycyclohexyl)-/V'-nitrosourea (BHCNU) is a nitrosourea which has carbamoylating but not alkylating activity. It has been shown to carbamoylate and inactivate glutathione reducÃ asethereby reducing the intracellular levels of glutathione (GSH). Since GSH deple tion by buthionine-5,A-sulfoximine potentiates the cytotoxicity of cyclophosphamide, with a corresponding increase in DNA cross-linking, we have investigated the potential interaction between BHCNU and cyclophosphamide. Treatment of K562 human leukemia cells with 15 /IM BHCNU for l h resulted in depletion of glutathione to 40% of control values, without significant reduction of cell viability. Subsequent treat ment with 10 MM4-hydroperoxycyclophosphamide (4-11C'),a self-acti vating derivative of cyclophosphamide, reduced the level of glutathione to less than 20% of control values. BHCNU pretreatment enhanced the cytotoxicity of 4-HC resulting in a dose modification factor of 2.5. Alkaline elution analysis of cellular DNA demonstrated that the level of interstrand cross-linking was 2-fold higher in GSH-depleted cells than in nondepleted cells, and the induction of single strand breaks was markedly increased. These findings demonstrate that BHCNU potentiates the cytotoxicity of 4-HC and suggest that this is due to the increased formation of DNA interstrand cross-links caused by a reduced intracellular conjugation of 4-HC with glutathione which results in an increased binding of 4-HC to DNA targets.
Simulating Spatial Patterns: Dependent Samples from a Multivariate Density

Purpose Suppose we wish to generate samples of m points in d-dimensional space from a joint distribution with density p. Examples occur frequently when studying spatial patterns for which the normalizing constant is not known in closed form. We will assume that the density is symmetric in its arguments, i.e. independent of the ordering of the m random points. If all the marginal densities were known, the obvious way to generate samples from the density would be to add points in turn drawn from the appropriate conditional densities. However, it is often impossible to find even the marginal density of a subset of (m-1) points. Rejection sampling is theoretically feasible whenever the density is bounded, by M say. For a process on [0, 1 ]d generate m independent uniform random vectors x1, . , x and compute X = p(x1, ., xm)/M. Generate an independent uniform variable Y. If X) Y accept (x1, ., xM) otherwise repeat the process. Although this process will terminate (with probability one) it is almost always prohibitively long. The m independent uniform random vectors may be replaced by a sample from any easily simulated density q, provided X is redefined as cp(x)/q(x) with c chosen so that P(Xs< 1) = 1. Useful choices of q for this envelope rejection technique are rare. The method used here exploits the observation that the conditional density p(x1 I x2, .,Xm) is known up to a constant depending only on (x2, ., Xm) and so may be simulated by the rejection technique. The algorithm is mainly to illustrate the technique; the example used is Strauss's density as given by Kelly and Ripley (1976). Define two points to be neighbours if their distance apart is less than R. Then p(x1, ., xm) is proportional to c8 where s is the number
Impact of Population Size, Selection and Multi-Parent Recombination within a Customized NSGA-II and a Landscape Analysis for Biochemical Optimization

—The main task in the drug design process is the prediction of the peptide structure and the bioactivity with the focus on simultaneously optimization of molecular peptide features. The synthesis and laboratory screening are the conventional but cost-intensive steps for optimization. Multi-objective genetic algorithms provide a range of methods for an efﬁcient design of drug peptides. A customized NSGA-II has been especially evolved for biochemical optimization with the focus on producing a great number of very different high quality peptides within a very low number of generations e.g., under 20, termed early convergence. The focus of this work are an insight into the impact of the interdependence between the selection procedure and the population size, the empirical veriﬁcation of the early convergence behavior within a limited range of population size and the inﬂuence of multi-parent recombination on the algorithm performance. These purposes are exemplary investigated on two different dimensional biochemical optimization problems, which are concrete, but as generic as possible. A landscape analysis is performed to gain an insight into the characteristic features and difﬁculties of the multi-objective optimization problems. The performance is assessed on the basis of a convergence indicator especially evolved for our preference of comparing the convergence behavior of populations with different sizes.
cell thickening through enhanced lignification induced by OsMYB30

copyright.  Here, we report the involvement of the OsMYB30 gene in the bsr-d1 -mediated 50 blast resistance. Expression of OsMYB30 is induced during M. oryzae infection or 51 when Bsr-d1 is knocked out or downregulated, as occurs in bsr-d1 plants upon 52 infection. We further find that OsMYB30 binds to and activates the promoters of 53 4-coumarate:coenzyme A ligase genes ( Os4CL3 and Os4CL5 ) resulting in 54 accumulation of lignin subunits G and S. This action leads to obvious thickening 55 of sclerenchyma cells near the epidermis, inhibiting M. oryzae penetration at the 56 early stage of infection. 57  Our study reveals novel components required for bsr-d1 -mediated resistance and 58 penetration-dependent immunity, and advances our understanding of 59 broad-spectrum disease resistance. 60 61
Experimental and Computational Demonstration of a Low-Temperature Waste to By-Product Conversion of U.S. Oil Shale Semi-Coke to a Flue Gas Sorbent

The volatility of crude oil prices incentivizes the use of domestic alternative fossil fuel sources such as oil shale. For ex situ oil shale retorting to be economically and environmentally viable, we must convert the copious amounts of semi-coke waste to an environmentally benign, useable by-product. Using acid and acid + base treatments, we increased the surface area of the semi-coke samples from 15 m2/g (pyrolyzed semi-coke) to upwards of 150 m2/g for hydrochloric acid washed semi-coke. This enhancement in porosity and surface area is accomplished without high temperature treatment, which lowers the overall energy required for such a conversion. XRD analysis confirms that chemical treatments removed the majority of dolomite while retaining other carbonate minerals and maintaining carbon contents of approximately 10%, which is greater than many fly ashes that are commonly used as sorbent materials. SO2 gas adsorption isotherm analysis determined that a double HCl treatment of semi-coke produces sorbents for flue gas treatment with higher SO2 capacities than commonly used fly ash adsorbents. Computational fluid dynamics modeling indicates that the sorbent material could be used in a fixed bed reactor to efficiently remove SO2 from the gas stream.
The existence of trade-offs is a central pillar of evolutionary theory in general and life history

3 Josefa Bleu1,2*, Anne Loison1, Carole Toïgo3 4 5 1 Université de Savoie ; CNRS ; UMR 5553 Laboratoire d’Écologie Alpine, 73376 Le Bourget du 6 Lac, France 7 2Norwegian University of Sciences and Technology, Center for Biodiversity Dynamics, 7034 8 Trondheim, Norway 9 3Office National de la Chasse et de la Faune Sauvage (ONCFS), ZI Mayencin, 38610 Gières, 10 France 11 12 Short title: growth and survival in chamois 13 14