Miracle-dz/UniFAR-FTUs huggingface dataset:
Feature preserving multiresolution subdivision and simplification of point clouds: A conformal geometric algebra approach

Due to the huge volume and complex structure, simplification of point clouds is an important technique in practical applications. However, the traditional algorithms often lose geometric information and have no dynamic expanding structure. In this paper, a new simplification algorithm is proposed based on conformal geometric algebra. First of all, a multiresolution subdivision is constructed by the sphere tree, which computes the minimal bounding spheres with the help of k‐means clustering, and then 2 kinds of simplification methods with full advantages of distance computing convenience are applied to carry out self‐adapting simplification. Finally, several comparisons with original data or other algorithms are implemented from visualization to parameter contrast. The results show that the proposed algorithm has good effect not only on the local details but also on the overall error rate.
Raven: Accelerating Execution of Iterative Data Analytics by Reusing Results of Previous Equivalent Versions

Using GUI-based workflows for data analysis is an iterative process. During each iteration, an analyst makes changes to the workflow to improve it, generating a new version each time. The results produced by executing these versions are materialized to help users refer to them in the future. In many cases, a new version of the workflow, when submitted for execution, produces a result equivalent to that of a previous one. Identifying such equivalence can save computational resources and time by reusing the materialized result. One way to optimize the performance of executing a new version is to compare the current version with a previous one and test if they produce the same results using a workflow version equivalence verifier. As the number of versions grows, this testing can become a computational bottleneck. In this paper, we present Raven, an optimization framework to accelerate the execution of a new version request by detecting and reusing the results of previous equivalent versions with the help of a version equivalence verifier. Raven ranks and prunes the set of prior versions to quickly identify those that may produce an equivalent result to the version execution request. Additionally, when the verifier performs computation to verify the equivalence of a version pair, there may be a significant overlap with previously tested version pairs. Raven identifies and avoids such repeated computations by extending the verifier to reuse previous knowledge of equivalence tests. We evaluated the effectiveness of Raven compared to baselines on real workflows and datasets.
Single or Multiple Frames Content Delivery for Robust and Secure Communication in Energy and Spectrum Efficient 5G Networks?

This paper addresses the four enabling technologies, namely multi-user sparse code multiple access (SCMA), content caching, energy harvesting, and physical layer security for proposing an energy and spectral efficient resource allocation algorithm for the access and backhaul links in heterogeneous cellular networks. Although each of the above mentioned issues could be a topic of research, in a real situation, we would face a complicated scenario where they should be considered jointly, and hence, our target is to consider these technologies jointly in a unified framework. Moreover, we propose two novel content delivery scenarios: 1) single frame content delivery, and 2) multiple frames content delivery. In the first scenario, the requested content by each user is served over one frame. However, in the second scenario, the requested content by each user can be delivered over several frames. We formulate the resource allocation for the proposed scenarios as optimization problems where our main aim is to maximize the energy efficiency of access links subject to the transmit power constraints of access and backhaul links, caching and energy harvesting constraints, and SCMA codebook allocation limitations. Due to the practical limitations, we assume that the channel state information values between eavesdroppers and base stations are uncertain and design the network for the worst case scenario. Since the corresponding optimization problems are mixed integer non-linear and nonconvex programming, NP-hard, and intractable, we propose an iterative algorithm based on the well-known alternative and successive convex approximation methods. In addition, the proposed algorithms are studied from the computational complexity, convergence, and performance perspectives.
The impact of public debt on economic growth in Côte d'Ivoire: New evidence from linear and non-linear ARDL approaches

Abstract This study examines the symmetric and asymmetric impact of public debt on economic growth in Côte d'Ivoire using time series data from 1972 to 2021. The analyses were performed using both linear and nonlinear autoregressive distributed lag (ARDL) models. The study also utilised the bounds F-test for cointegration, the Brock-Dechert-Scheinkman (BDS) nonlinearity test, and the Wald test for asymmetries. The findings of the bounds F-test provide support for both linear and nonlinear cointegration. The BDS test results indicate that the series are nonlinear, while Wald test results revealed an asymmetric relationship between public debt and economic growth in Côte d'Ivoire in the short run and symmetric relationship in the long run. Estimation results for the symmetric ARDL regression model provide no evidence of a statistically significant impact of public debt on economic growth, regardless of whether the analysis was conducted in the short run or long run. The NARDL findings indicate that, on average, positive changes to public debt lead to economic decline in the long run, while negative changes cause an economic upturn in the short run. The findings also show that GDP growth responds rapidly and strongly to negative changes in public debt. Therefore, the study encourages the government of Côte d'Ivoire to be cautious about public debt rise because it was established that they have a negative impact on economic growth. Negative changes in the public debt can serve to minimise the uncertainties in the business environment, thus promoting private, public, and foreign direct investments.
Evolution of electro-magnetic field in relativistic heavy ion collisions from the HSD transport approach

Retarded electromagnetic fields – as emerging from the charg e four-currents – have been calculated in the Hadron String Dynamics (HSD) model. The creat ion and evolution of the fields as well as their influence on the quasiparticle propagation w ere studied in detail for non-central Au+Au collisions at the top RHIC energy. It is shown that the c r ated magnetic field is highly inhomogeneous but in the central region of the overlapping n uclei it changes relatively weakly in the transverse direction. We find that at any time the locat i n of the maximum in the distribution of magnetic field strength correlates with that of the en rgy density of the created particles. Our actual calculations show no noticeable influence of the e lectromagnetic fields created in heavy-ion collisions on the effect of the electric charge s eparation with respect to the reaction plane.
of Birmingham Using Discrete Multi-Physics for studying the dynamics of emboli in flexible venous valves

8 Emboli, which are parts of blood clots, can be stuck in the vasculature of various organs (most 9 frequently, lungs) and cause their malfunction or even death. In this work, using mathematical 10 modelling, different types of emboli-like structures are studied in a double venous valve 11 system. The model is implemented with a fully Lagrangian Discrete Multi-Physics technique 12 and the flow is governed by flexible walls. The study shows the effect of different diameters 13 and lengths of a free embolus in the flow surrounding the valve. The presence of an embolus 14 strongly affects the dynamics of both the fluid and the leaflets in venous valves and the 15 permanence of the embolus in the valve chamber is narrowly linked with its length. 16
Behavioural Quotients for Precision and Recall in Process Mining

—The comparison of the languages of software systems, i.e., their behaviours in terms of speciﬁed executions, is a prerequisite for many applications, reaching from system validation through management of a system’s evolution to conformance checking of observed and expected behaviour. If two systems are not language-equivalent, the quantiﬁcation of behavioural differences enables conclusions on the extent of deviation. Such quantiﬁcations are commonly done in a relative manner: A quotient is deﬁned over some measure of two languages, which have potentially been derived via algebraic operations. However, there exists no systematic approach for deﬁning quotients and it is unclear which measures enable meaningful comparisons of systems having inﬁnite behaviours. This paper introduces a framework for deﬁning language quotients. We instantiate the framework with cardinality-based and entropy-based measures to handle ﬁnite and inﬁnite behaviours, and prove important properties of the quotients. We demonstrate application of quotients in the ﬁeld of process mining to capture precision and recall between a log of recorded system executions and a model of expected system executions. An experimental evaluation of the quotients using our open-source implementation demonstrates their feasibility and indicates that the quotients enable a monotonic assessment, unlike state-of-the-art measures in process mining.
Implementation of Elastic Prestack Reverse-Time Migration Using an Efficient Finite-Difference Scheme

Elastic reverse-time migration (RTM) can reflect the underground elastic information more comprehensively than single-component Pwave migration. One of the most important requirements of elastic RTM is to solve wave equations. The imaging accuracy and efficiency of RTM depends heavily on the algorithms used for solving wave equations. In this paper, we propose an efficient staggered-grid finite-difference (SFD) scheme based on a sampling approximation method with adaptive variable difference operator lengths to implement elastic prestack RTM. Numerical dispersion analysis and wavefield extrapolation results show that the sampling approximation SFD scheme has greater accuracy than the conventional Taylor-series expansion SFD scheme. We also test the elastic RTM algorithm on theoretical models and a field data set, respectively. Experiments presented demonstrate that elastic RTM using the proposed SFD scheme can generate better images than that using the Taylor-series expansion SFD scheme, particularly for PS images. FurH. thermore, the application of adaptive variable difference operator lengths can effectively improve the computational efficiency of elastic RTM.
A new generalization of skew-T distribution with volatility models

ABSTRACT In this paper, we propose a new generalized alpha-skew-T (GAST) distribution for generalized autoregressive conditional heteroskedasticity (GARCH) models in modelling daily Value-at-Risk (VaR). Some mathematical properties of the proposed distribution are derived including density function, moments and stochastic representation. The maximum likelihood estimation method is discussed to estimate parameters via a simulation study. Then, the real data application on S&P-500 index is performed to investigate the performance of GARCH models specified under GAST innovation distribution with respect to normal, Student's-t and Skew-T models in terms of the VaR accuracy. Backtesting methodology is used to compare the out-of-sample performance of the VaR models. The results show that GARCH models with GAST innovation distribution outperforms among others and generates the most conservative VaR forecasts for all confidence levels and for both long and short positions.
An improved SVM model with double quantum genetic optimization and its application in fault diagnosis of rolling bearing

Support vector machine (SVM) is a kind of intelligent pattern recognition method which is suitable for small samples, nonlinear, high dimension and other complex problems, But its classification performance and generalization ability are limited by the choice of penalty coefficient and kernel function parameters. To solve this problem, in this paper, a new SVM model optimized by quantum genetic algorithm is proposed. The objective function is the classification accuracy, and the parameters of penalty function and kernel function are optimized to improve the local search ability and parameter optimization of classical genetic algorithm. A new quantum gate algorithm using a dual quantum genetic algorithm improves quantum mutation operations and catastrophic strategies. The experimental results show that the improved SVM model has higher classification accuracy, higher recognition rate and convergence rate than the traditional algorithm, and is of great significance to the development of fault diagnosis of rolling bearing.
Descent Rate Models of the Synchronization of the Quasi-Biennial Oscillation by the Annual Cycle in Tropical Upwelling

The response of the quasi-biennial oscillation (QBO) to an imposed mean upwelling with a periodic modulation is studied, by modeling the dynamics of the zero wind line at the equator using a class of equations known as descent rate models. These are simple mathematical models that capture the essence of QBO synchronization by focusing on the dynamics of the height of the zero wind line. A heuristic descent rate model for the zero wind line is described and is shown to capture many of the synchronization features seen in previous studies of the QBO. It is then demonstrated using a simple transformation that the standard Holton–Lindzen model of the QBO can itself be put into the form of a descent rate model if a quadratic velocity profile is assumed below the zero wind line. The resulting nonautonomous ordinary differential equation captures much of the synchronization behavior observed in the full Holton–Lindzen partial differential equation. The new class of models provides a novel framework within which to understand synchronization of the QBO, and we demonstrate a close relationship between these models and the circle map well known in the mathematics literature. Finally, we analyze reanalysis datasets to validate some of the predictions of our descent rate models and find statistically significant evidence for synchronization of the QBO that is consistent with model behavior.
The Association of Prepregnancy Body Mass Index with Pregnancy Outcomes in Triplet Gestations

The impact of obesity on triplet gestations is poorly understood. In this study, we investigate the association of obesity with birth outcomes in triplets. Triplet births in the state of Missouri from 1989 through 1997 were analyzed. Obesity was deﬁned as maternal prepregnancy body mass index (BMI) (cid:1) 30 kg/m 2 . We assessed the association between obesity and the following outcomes: stillbirth, preeclampsia, very preterm, small for gestational age (SGA), and a composite adverse birth outcome. We employed logistic regression with further correction for intracluster correlation to obtain adjusted estimates. A total of 667 triplet gestations were analyzed. As compared with normal-weight mothers, the likelihood of stillbirth and preeclampsia was higher among obese mothers (odds ratio[OR] ¼ 3.70; 95% conﬁdence interval [CI] ¼ 1.37 to 9.97 and OR ¼ 3.02; 95% CI ¼ 1.69 to 5.40 respectively). Obese mothers were also about twice as likely to experience at least one of the adverse birth outcomes considered. Obese women with triplet gestations have about four-and threefold elevated risks for stillbirth and preeclampsia as compared with their counterparts with normal weight. This observation may be of utility in the preconceptional counseling of women considering the use of assisted reproductive technology.
Network and structural analysis of quail mucins with expression pattern of MUC1 and MUC4 in the intestines of the Iraqi Common Quail (Coturnix Coturnix)

Background Mucins have vital pathophysiological role in gastrointestinal tract (GIT) of avian and other species. However, despite this very little is known about the types of mucins expressed in quail GIT. Hence in this study we examined the expression pattern of mucins (MUC1, and MUC4) in the GIT of the Iraqi Common Quail (Coturnix Coturnix) and performed the network and structural analysis of all reported types of mucins in various breeds of quails. Materials and methods This study protocol was approved by the animal ethics research committee of the College of Veterinary Medicine, University of Al-Qadisiyah, Iraq. Fresh samples of small and large intestines were used for histological and gene expression analysis of MUC1, and MUC4. Network and structural analysis of all reported types of mucins in quails was performed using the STRING Database, Chimera software and PrankWeb-Ligand Binding Site Prediction tool. Results The histological analysis using Alcian blue and PAS stains indicated that most mucins in the intestines of quails were of the acidic mucin type, with minimal prevalence of neutral mucins. The expression of acidic mucins was relatively higher in the duodenum, ileum, caecum, and colon, while the jejunum showed a relatively higher expression of neutral mucins. Gene expression analysis revealed higher expression levels of MUC1 and MUC4 mRNA in the jejunum and colon, with its least expression in the duodenum and ilium. Network analysis indicated predominantly mucin-mucin interactions, with MUC 1, 15, 16 and 24 showing preferential homologous networks while the MUC 2, 4, 5 and 6 showed heterologous networks. Detailed evaluation of intermolecular hydrogen bond formation highlighted the interactions between specific mucin combinations, with certain combinations showing higher affinity, such as MUC5A-MUC6, MUC5A-MUC5B, and MUC5B-MUC6. In contrast, MUC15, MUC16, and MUC24 exhibited limited interactions with other mucin types. Binding site analysis indicated that MUC5B and MUC6 had the most number of binding sites with high probability scores, while MUC2, MUC4, and MUC5A showed lower probability scores despite having more binding sites. In contrast MUC 1, 15, and 16 had very few binding sites (<3 binding sites) all with very low probability scores. Conclusion The findings of this study provide valuable insights into the composition, expression, network interactions, and binding sites of mucins in the quails, contributing to the understanding of mucin-related processes in gastrointestinal physiology and potential implications for gastrointestinal diseases.
De novo progesterone synthesis in plants

The essential roles of progesterone and other C21 steroids in animals are well-documented. Progesterone is an essential hormone for females to maintain a regular menstrual cycle and pregnancy, while also exhibiting anti-inflammatory and antitumor effects. While the biosynthesis pathway of C21 steroids is comprehensively understood in animals, the synthesis mechanisms of progesterone in plants remain unclear. To our best knowledge, this is the first study to elucidate the complete pathway for progesterone biosynthesis in the plant Marsdenia tenacissima, involving the two sterol side chain cleaving cytochrome P450 enzymes (P450scc) Mt108 or Mt150, as well as the Δ5-3β-hydroxysteroid dehydrogenase/Δ5-Δ4 ketosteroid isomerase MtHSD5. This critical discovery paves the way for the sustainable synthesis of steroid hormone drugs using either plants or microbial host cells.
Wild edible yams from Madagascar: New insights into nutritional composition support their use for food security and conservation

Yams (Dioscorea species) are an important food resource in Madagascar, where both cultivated winged yam (D. alata) and wild edible yams are consumed. However, there is limited knowledge on the nutrient composition of wild edible yams in Madagascar, and on how they compare with the cultivated winged yam. Therefore, in this study, nine wild edible yam species, one with two subspecies from Madagascar (D. bako, D. buckleyana, D. irodensis, D. maciba, D. orangeana, D. pteropoda, D. sambiranensis subsp. bardotiae and subsp. sambiranensis, D. seriflora and Dioscorea species Ovy valiha), were analysed for their nutrient composition, compared with cultivated D. alata. They include 6/6 of the most favoured wild edible yam species in Madagascar. We present new nutrient composition data (protein, carbohydrate/starch, energy, lipid, β-carotene, minerals) for these nine wild edible yam species and show that they contain comparable levels of lipids and starch to D. alata, but none are better sources of protein than D. alata. We show that D. irodensis contains a significantly higher β-carotene content when compared to all other edible yams analysed, and that D. buckleyana, D. irodensis and D. sambiranensis subsp. bardotiae have a higher calcium content than cultivated D. alata, while all nine wild edible yam species analysed contain a higher iron content, compared to cultivated D. alata. The nutrient composition data presented could provide new incentives to conserve wild edible yams and inform on strategies to select Disocorea species for sustainable cultivation and use, providing opportunities to enhance future food security in Madagascar.
Weak genetic draft and the Lewontin’s paradox

Neutral theory assumes that in a population of size N, diversity results from an equilibrium between new mutations arising at rate μ and genetic drift that purge them at rate 1/N, predicting an equilibrium value proportional to Nμ. The difference between this expectation and the much lower observed molecular diversity is known as the Lewontin’s paradox of variation. Here, we investigate the effect of genetic draft, a regime of evolution where recurrent sparse selective sweeps entirely drive the diversity of surrounding loci. More specifically, we focus on the neglected distant effect of selective sweeps on remote neutral loci, where the effect of a single sweep is almost negligible. We derived novel mathematical approximations of this underexplored regime and show that under weak genetic draft, diversity at neutral loci is a power law of the population size: , for A < 0.5, where A is the ratio between recombination rate and coefficient of selection (A = c/s). Interestingly the Site Frequency Spectrum at neutral loci is identical to the one produced by genetic drift, as the underlying coalescent tree is an n-Kingman coalescent. In brief, weak genetic draft produces patterns of diversity that look entirely neutral, while being drastically reduced in magnitude. Ultimately, our study points to the need to explore evolutionary models for which diversity looks neutral but does not scale linearly with population size.
rec-1 loss of function is insufficient to homogenize crossover distribution in Caenorhabditis elegans

Meiotic control of crossover (CO) position is critical for proper homologous chromosome segregation and organismal fertility, recombination of parental genotypes, and the generation of novel genetic combinations. We here characterize the recombination rate landscape of a loss of function genetic modifier of CO position in Caernorhabditis elegans. By averaging CO position across hermaphrodite and male meioses and by genotyping 203 single-nucleotide variants covering about 95% of the genome, we find that the characteristic chromosomal arm-center recombination rate domain structure is lost in a loss of function rec-1 mutant. The rec-1 loss of function mutant smooths the recombination rate landscape but is insufficient to eliminate the non-uniform position of CO. We further find that the rec-1 mutant is of little consequence for organismal fertility and embryo hatchability and thus for rates of autosomal non-disjunction. However, it specifically increases X chromosome non-disjunction rates and males’ appearance. Our findings question the maintenance of genetic diversity among C. elegans natural populations, and they further suggest that manipulating genetic modifiers of CO position will help map quantitative trait loci in low-recombining genomic regions.