Miracle-dz/UniFAR-FTUs huggingface dataset:
Empirical modeling and analysis of local search algorithms for the job-shop scheduling problem

Local search algorithms are among the most effective approaches for locating high-quality solutions to a wide range of combinatorial optimization problems. However, our theoretical understanding of these algorithms is very limited, leading to significant problems for both researchers and practitioners. Specifically, the lack of a theory of local search impedes the development of more effective algorithms, prevents practitioners from identifying the algorithm most appropriate for a given problem, and allows widespread conjecture and misinformation regarding the benefits and/or drawbacks of particular algorithms. This thesis represents a significant step toward a theory of local search. Using empirical methods, we develop theoretical models of the behavior of four well-known local search algorithms: a random walk, tabu search, iterated local search, and simulated annealing. The analysis proceeds in the context of the well-known job-shop scheduling problem, one of the most difficult NP-hard problems encountered in practice. The large volume of prior research on the job-shop scheduling problem provides a diverse range of available algorithms and problem instances, in addition to numerous empirical observations regarding local search algorithm behavior; the latter are used to validate our behavioral models. We show that all four local search algorithms can be modeled with high fidelity using straightforward variations of a generalized one-dimensional Markov chain. The states in these models represent sets of solutions a given fixed distance from the nearest optimal solution. The transition probabilities in all of the models are remarkably similar, in that search is consistently biased toward solutions that are roughly equidistant from the nearest optimal solution and solutions that are maximally distant from the nearest optimal solution. Surprisingly, the qualitative form of the transition probabilities is simply due to the structure of the representation used to encode solutions: the binary hypercube. The models account for between 96% and 99% of the variability in the cost required to locate both optimal and sub-optimal solutions to a wide range of problem instances, and provide explanations for numerous phenomena related to problem difficulty for local search in the job-shop scheduling problem. In the course of our analysis, we also disprove many conjectures regarding the behavior and benefits of particular algorithms. (Abstract shortened by UMI.)
Strategies for High Efficiency, High Energy, Multi-cycle THz-wave Generation

— Electromagnetic waves with frequencies in the THz range have been of technolog-ical relevance for decades for a number of applications ranging from imaging to spectroscopy. Most of these applications place modest requirements on energy and control of the millimeter wave electromagnetic ﬁeld and therefore progress toward the generation of high energy, multi-cycle THz-frequency pulses have shown only modest advances. Over the past few years however, the potential of high energy, ﬁeld controlled THz-frequency waves for the acceleration of charged particles has been recognized, oﬀering promising outlooks towards tabletop X-ray sources. Suc-cessful electron acceleration has been experimentally demonstrated using modest — microjoule level — THz-frequency wave sources [1]. The standing challenge hampering the generation of high energy THz-frequency pulses originates from two limitations. On the one hand, the conversion eﬃciency of the THz generation process is capped by the fundamental Manley-Rowe limit to hardly 0.1% for multi-cycle wave generation in the hundreds of GHz frequency range. On the other hand, the ﬁnite energy of state-of-the-art near-IR driving lasers places an upper bound on the achievable THz energy that can be
The Research and Implementation of Clothing Style Transfer Algorithm Based on CycleGAN

The rapid development of artificial intelligence has brought about changes in many industries, and the application of deep learning technology in apparel design has become a current research hotspot. Since human subjective consciousness plays a dominant role in design style during the design process, artificial intelligence methods can effectively avoid the problem. In this paper, we focus on the application of Cycle Generative Adversarial Network (CycleGAN) in clothing style migration by giving an overview of CycleGAN. To address the problems exhibited by traditional generative adversarial networks in clothing style migration, this paper adds a filtering link before model training, which makes the generative adversarial network more focused and the edges more clear in the process of style migration. Through the comparison of experimental results, it is verified that the method works better in clothing style migration.
Animaton: Scriptable Finite Automaton for Animation Design in Unity3D Game Engine

In this paper, we propose a novel technical approach for animation design in the Unity3D game engine using the scriptable finite automaton called Animaton that specifies the transitions between positions, rotations, and animation clips for each animated virtual character. In our animation design interface, the animation designer can write easy-to-use C-like scripts to define the animation logic, drag and drop each state label in the virtual scene, and then can use different input strings to simulate different animation sequences. We conduct a series of numerical experiments to demonstrate how is our proposed approach applied to the animation design process and how potentially it can improve the animation design efficiency.
End-user engineering of ontology-based knowledge bases

ABSTRACT Knowledge bases store information on certain topics. Applying a well-structured and machine-readable format for a knowledge base is a prerequisite for any AI-based processing or reasoning. Semantic technologies (e.g. RDF) offer such a format and have the advantages that they make it possible to define the semantics of the information and support advanced querying. However, the disadvantage is that using such technologies is challenging for people not trained in IT, such as subject matter experts. This means that they need to rely on semantic technology experts to create, maintain, and query their knowledge bases. However, these experts are, in turn, not trained in the subject matter, while domain knowledge is essential for the construction of high-quality knowledge bases. In this paper, we present an end-user engineering approach for ontology-based knowledge bases. The goal is to allow subject matter experts to develop, maintain, and exploit the knowledge base themselves. We also present the supporting tools developed so far. The tools for the construction and the manual filling of the knowledge base are using the jigsaw metaphor to hide technicalities and guide the users. We also developed tools to automatically import data from spreadsheets into the knowledge base and to perform some type of quality control on the data. The end-user approach and the tools are demonstrated and evaluated for building a knowledge base in the toxicology domain.
Urban co-creation taxonomy

ABSTRACT Participation processes first emerged in the twentieth century and are becoming more common in democratic urban planning processes. In resilient, inclusive urban regeneration, the inhabitants are involved in transforming cities. Today, these processes are evolving and new creative tools are emerging. The aim of this research is to understand facets of what is known as urban co-creation by analysing experiments and classifying into a taxonomy their tools, the type of urban space involved, the duration, and the purposes. The use of the taxonomy in case studies shows how participation can be synthesized using a relatively simple code of pattern combinations.
On regular solutions to compressible radiation hydrodynamic equations with far field vacuum

Abstract The Cauchy problem for three-dimensional (3D) isentropic compressible radiation hydrodynamic equations is considered. When both shear and bulk viscosity coefficients depend on the mass density ρ \rho in a power law ρ δ {\rho }^{\delta } (with 0 < δ < 1 0\lt \delta \lt 1 ), based on some elaborate analysis of this system’s intrinsic singular structures, we establish the local-in-time well-posedness of regular solution with arbitrarily large initial data and far field vacuum in some inhomogeneous Sobolev spaces by introducing some new variables and initial compatibility conditions. Note that due to the appearance of the vacuum, the momentum equations are degenerate both in the time evolution and viscous stress tensor, which, along with the strong coupling between the fluid and the radiation field, make the study on corresponding well-posedness challenging. For proving the existence, we first introduce an enlarged reformulated structure by considering some new variables, which can transfer the degeneracies of the radiation hydrodynamic equations to the possible singularities of some special source terms, and then carry out some singularly weighted energy estimates carefully designed for this reformulated system.
An Innovative Multi-Sensor Fusion Algorithm to Enhance Positioning Accuracy of an Instrumented Bicycle

Cycling is an increasingly popular mode of travel in cities, but its poor safety record currently acts as a hurdle to its wider adoption as a real alternative to the private car. A particular source of hazard appears to originate from the interaction of cyclists with motorized traffic at low speeds in urban areas. But while technological advances in recent years have resulted in numerous attempts at systems for preventing cyclist-vehicle collisions, these have generally encountered the challenge of accurate cyclist localization. This paper addresses this challenge by introducing an innovative bicycle localization algorithm, which is derived from the geometrical relationships and kinematics of bicycles. The algorithm relies on the measurement of a set of kinematic variables (such as yaw, roll, and steering angles) through low-cost on-board sensors. It then employs a set of Kalman filters to predict-correct the direction and position of the bicycle and fuse the measurements in order to improve positioning accuracy. The capabilities of the algorithm are then demonstrated through a real-world field experiment using an instrumented bicycle, called “iBike”, in an urban environment. The results show that the proposed fusion achieves considerably lower positioning errors than that would be achieved based on dead-reckoning alone, which makes the algorithm a credible basis for the development of future collision warning and avoidance systems.
Cardiovascular Comorbidities Are the Main Predictors of Cardiac Reverse Remodeling following Kidney Transplantation

Background: End-stage renal disease is associated with cardiac remodeling, which is partly reversible after kidney transplantation (KT). We aimed to determine the association of cardiovascular comorbidities or kidney-related factors with cardiac reverse remodeling after KT. Methods: We performed echocardiography in 56 patients (aged 48 ± 15 years, mean ± SD) before and 24 months after undergoing their first KT. Echocardiograms were reviewed using a standardized process with blinding for the patient characteristics and evaluation timing. Multivariable linear regression analysis was used to evaluate the association between comorbidities and changes in cardiac structure and systolic/diastolic function. Results: Left ventricular mass index (LVMI) and diastolic parameters did not change significantly, while left ventricular ejection fraction (LVEF) increased from 63.9 to 69.6% (p = 0.046). Multivariable analysis revealed associations of histories of valvular heart disease with a smaller reduction in LVMI (β = –27.3, p = 0.04), of coronary artery disease or heart failure with a smaller increase in LVEF (β = 7.17, p = 0.02), and of diabetes mellitus with less improvement in E wave (β = –0.19, p = 0.05), e’ (β = 4.15, p = 0.046), and E/e’ (β = –5.00, p < 0.01). Conclusion: Cardiovascular comorbidities were associated with less improvement in cardiac structure and function following KT. Our findings suggest that patients with CV comorbidities may experience limited “favorable” reverse cardiac remodeling following KT.
Multimodal assessment of non-alcoholic fatty liver disease with transmission-reflection optoacoustic ultrasound

Non-alcoholic fatty liver disease (NAFLD) is an umbrella term referring to a group of conditions associated to fat deposition and damage of liver tissue. Early detection of fat accumulation is essential to avoid progression of NAFLD to serious pathological stages such as liver cirrhosis and hepatocellular carcinoma. We exploited the unique capabilities of transmission-reflection optoacoustic ultrasound (TROPUS), which combines the advantages of optical and acoustic contrasts, for an early-stage multi-parametric assessment of NAFLD in mice. The multispectral optoacoustic imaging allowed for spectroscopic differentiation of lipid content, as well as the bio-distributions of oxygenated and deoxygenated hemoglobin in liver tissues in vivo. The pulse-echo (reflection) ultrasound (US) imaging further provided a valuable anatomical reference whilst transmission US facilitated the mapping of speed of sound changes in lipid-rich regions, which was consistent with the presence of macrovesicular hepatic steatosis in the NAFLD livers examined with ex vivo histological staining. The proposed multimodal approach facilitates quantification of liver abnormalities at early stages using a variety of optical and acoustic contrasts, laying the ground for translating the TROPUS approach toward diagnosis and monitoring NAFLD in patients.
ATG9 vesicles comprise the seed membrane of mammalian autophagosomes

During autophagosome biogenesis, the incorporation of transmembrane proteins into the expanding phagophore is not readily observed. In addition, the membrane surface area of the organelle expands rapidly, while the volume of the autophagosome is kept low. Several recent studies have suggested a model of membrane expansion that explains how these attributes are maintained. The autophagosome expands predominantly through the direct protein-mediated transfer of lipids through the lipid transfer protein ATG2. As these lipids are only introduced into the cytoplasmic-facing leaflet of the expanding phagophore, full membrane growth also requires lipid scramblase activity. ATG9 has been demonstrated to harbor scramblase activity and is essential to autophagosome formation, however if and when it is integrated into mammalian autophagosomes remains unclear. Here we show that in the absence of lipid transport, ATG9 vesicles are already fully competent to collect proteins normally found on mature autophagosomes, including LC3-II. Further, through the novel use of styrene-maleic acid lipid particles as a nanoscale interrogation of protein organization on intact membranes, we show that ATG9 is fully integrated in the same membranes as LC3-II, even on maturing autophagosomes. The ratios of these two proteins at different stages of maturation demonstrate that ATG9 proteins are not continuously integrated, but rather are present on the seed vesicles only and become diluted in the rapidly expanding autophagosome membrane. Thus, ATG9 vesicles are the seed membrane from which mammalian autophagosomes form.
A microbiota-derived metabolite instructs peripheral efferocytosis

The phagocytic clearance of dying cells, termed efferocytosis, is essential for both tissue homeostasis and tissue health during cell death-inducing treatments. Failure to efficiently clear dying cells augments the risk of pathological inflammation and has been linked to a myriad of autoimmune and inflammatory diseases. Although past studies have elucidated local molecular signals that regulate efferocytosis in a tissue, whether signals arising distally also regulate efferocytosis remains elusive. Interestingly, clinical evidence suggests that prolonged use of antibiotics is associated with an increased risk of autoimmune or inflammatory disease development. We therefore hypothesized that intestinal microbes produce molecular signals that regulate efferocytotic ability in peripheral tissue phagocytes. Here, we find that macrophages, the body’s professional phagocyte, display impaired efferocytosis in peripheral tissues in both antibiotic-treated and germ-free mice in vivo, which could be rescued by fecal microbiota transplantation. Mechanistically, the microbiota-derived short-chain fatty acid butyrate directly boosted efferocytosis efficiency and capacity in mouse and human macrophages, with both intestinal and local delivery of butyrate capable of rescuing antibiotic-induced peripheral efferocytosis defects. Bulk mRNA sequencing of primary macrophages treated with butyrate in vitro and single cell mRNA sequencing of macrophages isolated from antibiotic-treated and butyrate-rescued mice revealed specific regulation of phagocytosis-associated transcriptional programs, in particular the induction of programs involved in or supportive of efferocytosis. Surprisingly, the effect of butyrate on efferocytosis was not mediated through G protein-coupled receptor signaling, but instead acted by inhibition of histone deacetylase 3. Strikingly, peripheral efferocytosis was impaired well-beyond withdrawal of antibiotics and, importantly, antibiotic-treated mice exhibited a poorer response to a sterile efferocytosis-dependent inflammation model. Collectively, our results demonstrate that a process essential for tissue homeostasis, efferocytosis, relies on distal molecular signals, and suggest that a defect in peripheral efferocytosis may contribute to the clinically-observed link between broad-spectrum antibiotics use and inflammatory disease.
A Neural Index Reflecting the Amount of Cognitive Resources Available during Memory Encoding: A Model-based Approach

Humans have a limited amount of cognitive resources to process various cognitive operations at a given moment. The Source of Activation Confusion (SAC) model of episodic memory proposes that resources are consumed during each processing and once depleted they need time to recover gradually. This has been supported by a series of behavioral findings in the past. However, the neural substrate of the resources is not known. In the present study, over an existing EEG dataset of a free recall task (Kahana et al., 2022), we provided a neural index reflecting the amount of cognitive resources available for forming new memory traces. Unique to our approach, we obtained the neural index not through correlating neural patterns with behavior outcomes or experimental conditions, but by demonstrating its alignment with a latent quantity of cognitive resources inferred from the SAC model. In addition, we showed that the identified neural index can be used to propose novel hypothesis regarding other long-term memory phenomena. Specifically, we found that according to the neural index, neural encoding patterns for subsequently recalled items correspond to greater available cognitive resources compared with that for subsequently unrecalled items. This provides a mechanistic account for the long-established subsequent memory effects (SMEs, i.e. differential neural encoding patterns between subsequently recalled versus subsequently unrecalled items), which has been previously associated with attention, fatigue and properties of the stimuli.
Dual role of Pectin Methyl Esterase activity in the regulation of plant cell wall biophysical properties

Acid-growth theory has been postulated in the 70s to explain the rapid elongation of cells in response to plant hormone auxin. More recently, it has been demonstrated that activation of the proton ATPs pump (H+-ATPs) promoting acidification of the apoplast is the principal mechanism through which hormones like auxin as well as brassinosteroids (BR) induce cell elongation. However, the impact of this acidification on the mechanical properties of the cell wall remained largely unexplored. Here, we use Atomic Force Microscopy (AFM) to demonstrate that acidification of apoplast is necessary and sufficient to induce cell elongation through cell wall relaxation. Moreover, we demonstrate that Pectin Methyl Esterase (PME) can induce both cell wall softening or stiffening in extracellular calcium dependent-manner and that tight control of PME activity is required for hypocotyl elongation.
PPAR-γ regulates the effector function of human TH9 cells by promoting glycolysis

T helper 9 cells (TH9) are key drivers of allergic tissue inflammation. They are characterized by the expression of type 2 cytokines, such as IL-9 and IL-13, and the peroxisome proliferator-activated receptor gamma (PPAR-γ) transcription factor. However, the functional role of PPAR-γ in human TH9 cells remains unknown. Here, we demonstrate that PPAR-γ drives activation-induced glycolysis, which, in turn, specifically promotes the expression of IL-9, but not IL-13, in an mTORC1-dependent manner. In vitro and ex vivo experiments on skin samples of allergic contact dermatitis showed that the PPAR-γ-mTORC1-IL-9 pathway was active in TH9 cells in human skin inflammation. Additionally, we found that tissue glucose levels were dynamically regulated in acute allergic skin inflammation, suggesting that in situ glucose availability is linked to distinct immunological signals in vivo. Furthermore, paracrine IL-9 induced the lactate transporter MCT1 in IL-9R+ TH cells, where it increased aerobic glycolysis and proliferative capacity. Taken together, our findings delineate a hitherto unknown relationship between PPAR-γ-dependent glucose metabolism and the pathogenic effector function of human TH9 cells. Graphical abstract
The RSK-RPS6 Axis Controls the Preconditioning Effect and Induces Spinal Cord Regeneration

Unlike immature neurons and neurons from the peripheral nervous system (PNS), mature neurons from the central nervous system (CNS) cannot regenerate after injury. In the past 15 years, huge progress has been made to identify molecules and pathways necessary for neuroprotection and/or regeneration after CNS injury. In most regenerative models, phosphorylated ribosomal protein S6 (p-RPS6) is upregulated in neurons, which is often associated with an activation of the mTOR pathway. However, the exact contribution of post-translational modifications of this ribosomal protein in CNS regeneration remains elusive. In this study, we demonstrate that RPS6 phosphorylation is essential for PNS and CNS regeneration. We show that this phosphorylation is induced during the preconditioning effect in dorsal root ganglion (DRG) neurons, and that it is controlled by the p90S6 kinase RSK2. Our results reveal that RSK2 controls the preconditioning effect and that the RSK2-RPS6 axis is key for this process, as well as for PNS regeneration. Finally, we demonstrate that RSK2 promotes CNS regeneration in the dorsal column and allows functional recovery. Our data establish the critical role of RPS6 phosphorylation controlled by RSK2 in CNS regeneration and give new insights into the mechanism related to axon growth and circuit formation after traumatic lesion.