Miracle-dz/UniFAR-FTUs huggingface dataset:
Searching in semantically rich linked data: a case study in cultural heritage

Traditionally the relations between concepts from a controlled vocabulary, such as the hierarchical and associative relations in a thesaurus, have been used to support users in their search process. In the context of the Semantic Web, multiple interlinked vocabularies are becoming available, providing a large number of different relations between concepts. However, for a specific search task, only a small fraction of these will be meaningful to the user, and currently we have little understanding of which methods can be used to determine this. In this paper, we describe a case study in the cultural heritage domain that investigates support for the specific task of finding artworks in a data set of multiple linked art collections and vocabularies. In a first experiment a number of use cases from domain experts are collected and the paths in the data graph by which artworks can be found are analysed. A number of different types of paths are identified and their usefulness is qualitatively evaluated. In a second experiment we explore how the different path types can be used in a semantic search algorithm to support the intended search behavior indicated by the experts. We conclude that effective end-user support requires a highly interactive application in which the user can explore multiple search strategies. Based on our findings we discuss the implications on the design of such an interactive search application.
A mathematical model of bipolar radiofrequency-induced thermofusion

Bipolar radiofrequency-induced thermofusion has become a widely accepted method successfully used in open and particularly in minimally-invasive surgery for the sealing of blood vessels and tissue of up to several millimeters diameter. Despite its wide-spread application, the thermofusion process itself is not well understood on a quantitative and dynamic level, and manufacturers largely rely on trial-and-error methods to improve existing instruments. To predict the effect of alternative generator control strategies and to allow for a more systematic approach to improve thermofusion instruments, a mathematical model of the thermofusion process is developed. The system equations describe the spatial and temporal evolution of the tissue temperature due to Joule heating and heat transfer, and the loss of tissue water due to vaporization. The resulting effects on the tissue properties, most importantly the electrical resistivity, heat capacity and thermal conductivity, are considered as well. Experimental results indicate that the extent of the lateral thermal damage is directly affected by Joule heating of the lateral tissue. The experimental findings are supported by simulation results using the proposed mathematical model of thermofusion.
Object-Based Selective Materialization for Efficient Implementation of Spatial Data Cubes

With a huge amount of data stored in spatial databases and the introduction of spatial components to many relational or object-relational databases, it is important to study the methods for spatial data warehousing and OLAP of spatial data. In this paper, we study methods for spatial OLAP, by integrating nonspatial OLAP methods with spatial database implementation techniques. A spatial data warehouse model, which consists of both spatial and nonspatial dimensions and measures, is proposed. Methods for the computation of spatial data cubes and analytical processing on such spatial data cubes are studied, with several strategies being proposed, including approximation and selective materialization of the spatial objects resulting from spatial OLAP operations. The focus of our study is on a method for spatial cube construction, called object-based selective materialization, which is different from cuboid-based selective materialization (proposed in previous studies of nonspatial data cube construction). Rather than using a cuboid as an atomic structure during the selective materialization, we explore granularity on a much finer level: that of a single cell of a cuboid. Several algorithms are proposed for object-based selective materialization of spatial data cubes, and a performance study has demonstrated the effectiveness of these techniques.
Functional and biophysical characterization of an HLA-A*6801-restricted HIV-specific T cell receptor

HLA‐A*6801 exhibits several unusual features. First, it is known to bind weakly to CD8 due to the presence of an A245V substitution in the α3 domain. Second, it is able to accommodate unusually long peptides as a result of peptide ‘kinking’ in the binding groove. Third, CD8+ cytotoxic T lymphocytes that recognise HLA‐A*6801‐restricted antigens can tolerate substantial changes in the peptide sequence without apparent loss of recognition. In addition, it has been suggested that HLA‐A68‐restricted TCR might bind with higher affinity than other TCR due to their selection in the presence of a decreased contribution from CD8. Here we (1) examine monoclonal T cell recognition of an HLA‐A*6801‐restricted HIV‐1 Tat‐derived 11‐amino acid peptide (ITKGLGISYGR) and natural variant sequences thereof; (2) measure the affinity and kinetics of a TCR/pHLA‐A68 interaction biophysically for the first time, showing that equilibrium binding occurs within the range previously determined for non‐HLA‐A68‐restricted TCR (KD approx. 7 μM); and (3) show that “normalization” of the non‐canonical HLA‐A*6801 CD8‐binding domain enhances recognition of agonist peptides without inducing non‐specific activation. This latter effect may provide a fundamental new mechanism with which to enhance T cell immunity to specific antigens.
A practitioner's view of system engineering

Tradeoff studies are the core technology of the system engineer during the early design effort. The system engineer creates tools to analyze performance, reliability, human interfaces, and cost. The entire life of the system is fixed by the system engineers' imagination during the initial design. After drawings are released, the principal activities of the system engineer are the resolution of intersubsystem conflicts and the documentation of delivered products. This paper describes planed and unplanned growth in large-scale systems and offers examples. (Various kinds of performance analysis tools are described, that are used for electrical and mechanical systems.) Perfect optimization of cost requires the owner to issue bonds to pay for higher quality products from savings in maintenance and operations. There is a dose relation between project management, system engineering, proposal preparation, and cost estimating, The design process has been bureaucratized, especially on projects paid for by large noncompetitive organizations. The result has been a trend to rote project management by technically illiterate lawyers and MBAs. This paper concludes with a projection of the future of system engineering in information processing, biological systems, infrastructure, and macroeconomics.
Intelligent Scheduling Technology of Swarm Intelligence Algorithm for Drone Path Planning

Different kinds of swarm intelligence algorithm obtain superior performances in solving complex optimization problems and have been widely used in path planning of drones. Due to their own characteristics, the optimization results may vary greatly in different dynamic environments. In this paper, a scheduling technology for swarm intelligence algorithms based on deep Q-learning is proposed to intelligently select algorithms to realize 3D path planning. It builds a unique path point database and two basic principles are proposed to guide model training. Path planning and network learning are separated by the proposed separation principle and the optimal selection principle ensures convergence of the model. Aiming at the problem of reward sparsity, the comprehensive cost of each path point in the whole track sequence is regarded as a dynamic reward. Through the investigation of dynamic environment conditions such as different distances and threats, the effectiveness of the proposed method is validated.
In Vitro and in Vivo Anti-Inflammatory Effect of a Biotechnologically Modified Borage Seed Extract: Evidence for Lipid Pro-Resolving Mediators’ Implication in the Enhancement of Psoriatic and Atopic Dermatitis Lesions

Aim: Resolvins, maresins and lipoxins are lipid mediators issued from essential polyunsaturated fatty acids which are the first anti-inflammatory and pro-resolving signals identified during the resolution phase of inflammation. As borage oil and/or borage seed extracts have shown beneficial action in treatment of atopic dermatitis or eczema in human and canine, we have modified a borage oil component by using biotechnology in order to get a compound structurally related to a polyunsaturated fatty acid, and we have studied its ability to reduce inflammation mediators production through the generation of resolvins, maresins and/or lipoxins. Additionally, we have demonstrated the potent anti-inflammatory effect of this new compound which consists in borage seed oil aminopropanediol amides, through an in vivo study concerning subjects suffering from psoriasis or atopic dermatitis. Study Design/Methods: For the in vitro study, inflammation was induced in co-cultures of human dendritic cells and normal keratinocytes by the addition of PMA and the calcium ionophore A23187. Ability of our borage seed oil aminopropanediol amides to increase resolvin D2, maresin 1 and lipoxins A4 and B4 synthesis was then measured. Pro-inflammatory cytokines (IL-1β, IL-6, IL-8) and PGE2 productions were also quantified. For the in vivo study, 36 subjects suffering from psoriasis or atopic dermatitis have used twice a day during 30 days, a formulation containing borage seed oil aminopropanediol amides. Before the beginning of the study and after 30 days’ treatment, the severity of psoriasis and of atopic dermatitis was evaluated by using the PGA and the SCORAD scoring scales, respectively. Results: Borage seed oil aminopropanediol amides were able to significantly increase the resolvin D2, maresin 1 and lipoxins A4 and B4 synthesis. Concomitantly, they were also able to significantly inhibit the production of IL-1β, IL-6, IL-8 and PGE2 induced by the PMA and the calcium ionophore A23187 in the in vitro co-culture model used. Introduced in formulation, borage seed oil aminopropanediol amides significantly reduced the clinical manifestations of psoriasis and atopic dermatitis. Conclusion: Our in vitro and in vivo study clearly showed the anti-inflammatory activity of borage seed oil aminopropanediol amides and emphasized the putative role of pro-resolving lipid mediators in the treatment of atopic dermatitis, psoriasis or other inflammation-induced skin diseases.
Fully-Automated Instance Decomposition and Subplan Synthesis for Parallel Execution

Subplans with limited interactions can be executed in a parallel and flexible manner. Given the success of SAT planning in the international planning competitions in 2004 and 2006 and advances in SAT solving, it is worth investigating how SAT planning can be used to generate plans for execution by multiple agents. We report on SAT encodings that have a model if and only if there are n subplans, each with up to k steps, such that they together achieve the goal and also satisfy the encoded criteria about permitted and prohibited interactions among them. These n subplans can be executed by different agents. Our SAT-based approach decomposes a planning instance fully automatically in an entirely unfamiliar domain with no knowledge from humans, if a decomposition exists. Desired properties of decomposition and solution are encoded as SAT. The key ideas in our encodings are an allocation of actions and subgoals to various agents and explanatory frame axioms for multiple agents. No domain-specific knowledge is used. We report on an empirical evaluation of the encodings. Our approach is domain-independent and fully automated. We discuss variants of our encodings.
Realising the future: forecasting with high frequency based volatility (HEAVY) models

This paper studies in some detail a class of high frequency based volatility (HEAVY) models. These models are direct models of daily asset return volatility based on realized measures constructed from high frequency data. Our analysis identifies that the models have momentum and mean reversion effects, and that they adjust quickly to structural breaks in the level of the volatility process. We study how to estimate the models and how they perform through the credit crunch, comparing their fit to more traditional GARCH models. We analyse a model based bootstrap which allow us to estimate the entire predictive distribution of returns. We also provide an analysis of missing data in the context of these models.
Shared Experience, Outcome, and Forgetting: An Empirical Study

Shared experience (i.e., experience working together in prior projects) among project team members is known to affect the project team’s performance. However, little is known of whether this effect is moderated by other factors. In this study, we examine the two attributes of shared experience as moderators: the outcome of shared experience and the time lapse of shared experience. We find that the effect of shared experience on project performance shows an inverse U-shaped curve with respect to the degree of failure (or success) of shared experience, suggesting that the effect of shared experience on project performance becomes strongest under intermediate degrees of failure (or success) of shared experience but comparatively weaker when the degree of failure (or success) is high or low. Moreover, we find that the inverse U-shaped curve becomes more flattened as the lapse of shared experience increases. This study makes a theoretical contribution by finding nonlinear moderating effects of shared experience. It also provides practical implications to software project management.
Fixed-k Asymptotic Inference About Tail Properties

ABSTRACT We consider inference about tail properties of a distribution from an iid sample, based on extreme value theory. All of the numerous previous suggestions rely on asymptotics where eventually, an infinite number of observations from the tail behave as predicted by extreme value theory, enabling the consistent estimation of the key tail index, and the construction of confidence intervals using the delta method or other classic approaches. In small samples, however, extreme value theory might well provide good approximations for only a relatively small number of tail observations. To accommodate this concern, we develop asymptotically valid confidence intervals for high quantile and tail conditional expectations that only require extreme value theory to hold for the largest k observations, for a given and fixed k. Small-sample simulations show that these “fixed-k” intervals have excellent small-sample coverage properties, and we illustrate their use with mainland U.S. hurricane data. In addition, we provide an analytical result about the additional asymptotic robustness of the fixed-k approach compared to kn → ∞ inference.
Impact of Silver Nanoparticles on Germinated Fenugreek Seed

Effects of silver nanoparticles on plant growth parameters such as Root length, fresh weight, Dry weight, Speed of germination and % Germination contents of economic important pulses, Fenugreek (Trigonella foenum-graecum); was probed in the present research. The study was carried out in a randomized block design with three replications. Five levels of silver nanoparticles (0, 10, 20, 30 and 40 μg mL -1 ) were used. After germination, daily supply with 15 ml from each concentration was carried out for 12 days during plant growth. Seed germination results indicate that AgNPs at their lower concentrations promoted seed germination and early seedling growth in Fenugreek, however at higher concentration showed slight adverse effects. Additionally, the lowest amount of these parameters was found with control plants, but the enhancing level of silver nanoparticles resulting in the reduction of these compounds. A significant positive influence on root length, root fresh weight and root dry weight root elongation was observed for all seeds in compared to those of unexposed control germination. The results showed that the effect of AgNPs was significant on germination percentage in P ≤ 0.05. The results of this experiment showed that the use of AgNPs increased the germination in Fenugreek. Key-words: Nanotechnology; silver nanoparticles; Fenugreek; Seed germination
Genomic and phenotypic evidence for an incomplete domestication of South American grain amaranth (Amaranthus caudatus)

The process of domestication leads to major morphological and genetic changes, which in combination are known as domestication syndrome that differentiates crops from their wild ancestors. We characterized the genomic and phenotypic diversity of the South American grain amaranth Amaranthus caudatus, which has been cultivated for thousands of years and is one of the three native grain amaranths of South and Central America. Previously, several models of domestication were proposed including a domestication from the close relatives and putative ancestors A. hybridus or A. quitensis. To investigate the evolutionary relationship of A. caudatus and its two close relatives, we genotyped 119 amaranth accessions of the three species from the Andean region using genotyping-by-sequencing (GBS) and compared phenotypic variation in two domestication-related traits, seed size and seed color. The analysis of 9,485 SNPs revealed a strong genetic differentiation of cultivated A. caudatus from the relatives A. hybridus and A. quitensis. The two relatives did not cluster according to the species assigment but formed mixed groups according to their geographic origin in Ecuador and Peru, respectively. A. caudatus had a higher genetic diversity than its close relatives and shared a high proportion of polymorphisms with their wild relatives consistent with the absence of a strong bottleneck or a high level of recent gene flow. Genome sizes and seed sizes were not significantly different between A. caudatus and its relatives, although a genetically distinct group of A. caudatus from Bolivia had significantly larger seeds. We conclude that despite a long history of human cultivation and selection for white grain color, A. caudatus shows a weak genomic and phenotypic domestication syndrome and is an incompletely domesticated species because of weak selection or high levels of gene flow from its sympatric close undomesticated relatives that counteracted the fixation of key domestication traits.
Calcium dependence of the activation and inactivation kinetics of the light-activated phosphodiesterase of retinal rods

The Ca2+ dependence of the kinetics and light sensitivity of light- activated phosphodiesterase was studied with a pH assay in toad and bovine rod disk membranes (RDM), and in a reconstituted system containing GTP-binding protein, phosphodiesterase and rhodopsin kinase. Three statistics, peak hydrolytic velocity, turnoff time, and time to peak velocity, were measured. ATP decreased phosphodiesterase light sensitivity nearly 10-fold and accelerated the dim-flash kinetics of cGMP hydrolysis when compared to those with GTP alone. CA2+ reversed all of the effects of ATP, Ca2+ increased peak velocity, turnoff time, and time to peak velocity, to the values obtained with GTP alone. The Ca2+ dependence of peak velocity and turnoff time can be characterized as hyperbolic saturation functions with a K0.5 for Ca2+ of 1.0-1.5 mM in toad RDM. In bovine RDM the Ca2+ dependence of peak velocity and turnoff time has a K0.5 of 0.1 mM Ca2+. The Ca2+ dependence in the reconstituted system is similar to that in bovine RDM for peak velocity (K0.5 = 0.1 mM Ca2+) but differs for turnoff time (K0.5 = 2.5 mM Ca2+). We tested the hypothesis that a soluble modulator, normally required to confer submicromolar Ca2+ sensitivity, was too dilute in our assay by comparing data obtained at one RDM concentration with those obtained at 10-fold higher RDM, and therefore a constituent protein, concentration. We observe no difference and present a formal analysis of these data that excludes the hypothesis that the soluble modulator binds its target protein with Kd less than 5 microM. The lack of submicromolar Ca2+ dependence of any of the steps in the cGMP cascade that underlie cGMP phosphodiesterase activation and inactivation in vitro argues against Ca2+ regulation of these steps having a significant role in the light adaptation of the intact rod.
Chord Diagrams and Coxeter Links

The paper presents a construction of fibered links (K, Σ) out of chord diagrams L. Let Γ be the incidence graph of L. Under certain conditions on L the symmetrized Seifert matrix of (K, Σ) equals the bilinear form of the simply‐laced Coxeter system (W, S) associated to Γ and the monodromy of (K, Σ) equals minus the Coxeter element of (W, S). Lehmer's problem is solved for the monodromy of these Coxeter links.
Fifteen‐year statistical analysis of cloud characteristics over China using Terra and Aqua Moderate Resolution Imaging Spectroradiometer observations

Using 15‐year observations obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS) on board both NASA Terra and Aqua from March 2003 to February 2018, this study investigated the spatio‐temporal variations of both macro‐ and micro‐physical cloud properties over China, including cloud fraction (CF), cloud top pressure (CTP), cloud top temperature (CTT), cloud optical thickness (COT), and effective radius (r e) of both liquid water and ice clouds. Multi‐year averaged CF is around 61% over whole China region. However, CF varies with both regions and seasons. The CFs are about 6–8% larger in summer and winter (~64–65%) than in spring and autumn (~58%). By classifying China into five regimes, which are northwestern China (NW), northeastern China (NE), Tibetan Plateau (TP), northern China (N), and southern China (S), there is a clear CF regional distribution pattern. In general, there are large amount of clouds in S and southeast of TP, and small amount in NE, N, NW and most TP. Moreover, there are generally more clouds over ocean than over land, and much more clouds over S than over N. The CFs are larger (smaller) in the afternoon than in the morning over most land (ocean) regions. Furthermore, the largest CF differences between afternoon and morning occur over the TP region in China. COT demonstrates almost the same regional distribution pattern as the CF for all four seasons. Specifically, COT is higher in S than in N, which is most likely associated with the type of clouds and the availability of water vapour. Cloud r e shows larger values in NW and TP than in eastern China regions in all seasons except for summer, which could be related to the heavy aerosol pollution in eastern China regions. Accompanying with the cold cloud tops over TP, a low CTP centre is often located there.
Pre-Training and Fine-Tuning for Satellite Image-to-Image Translation

Geospatial technologies are increasingly important for various applications worldwide, including vegetation monitoring. Collecting ground truth data for specific geospatial tasks are challenging and time-consuming. Recently, the foundation model research have been explored, then pre-training on large-scale data and fine-tuning for specific tasks are important components of this technique. Although this approach can enhance the performance in downstream tasks such as satellite image translation, directly fine-tuning models pre-trained on natural images like ImageNet is suboptimal for geospatial data due to the inherent domain differences. In this paper, we pro-pose a novel image translation approach with pre-training on geospatial-specific data and data augmentation. We present a case study where our method achieved outstanding results in a competition for inferring normalized difference vegetation index images from synthetic aperture radar data of cabbage farms. Our approach outperformed other methods with a 31% higher score than the second-ranked team and a 44% higher score than the average of the top five teams.