Miracle-dz/UniFAR-FTUs huggingface dataset:
Secondary metabolites in Viguiera (Compositae, Heliantheae, Helianthinae) and segregated genera. A review of their biological activities with chemotaxonomic observations

Background: The first monograph of the genus Viguiera was published in 1918 by Blake, including about 141 species. Schilling & Panero based on studies of molecular sequences of nuclear Internal Transcribed Spacer and External Transcribed Spacer, as well as cpDNA, proposed to reclassify the genus, relocating its species in at least other nine genera. Question: Is it possible to identify distinctive patterns between the species of the new classification of Viguiera s. l. and the results of the chemical studies reported? Species considered: Sixty-seven species within the wide Viguiera circumscription with chemical studies and biological activities reported. Results: The species of the genus Viguiera synthesize terpenoids represented mainly by sesquiterpene lactones and diterpenes, with triterpenes, polyacetylenes, volatile terpenoids and flavonoids also present. The main types of secondary metabolites were present in the studied species, although some compounds were more frequent than others in some clades. Conclusion: Germacrolides, heliangolides, furanoheliangolides, tetracyclic diterpenes and flavonoids are the main constituents of Viguiera and segregated genera. Some interesting chemotaxonomic relationships are noted. Nevertheless, nondistinctive clear patterns were observed between clades and chemical groups. These results may be a consequence of the reported chemical studies of the species of Viguiera s. l. , which have not agreed on objetives or methodologies.
Composition, Antioxidant and Anti-inflammatory activities of Hexane and Methanol extracts of Acmella uliginosa from Terai region of Uttarakhand

Acmella uliginosa , an edible herb belonging to Asteraceae family, was collected from the Terai region of Uttarakhand, India. Methanol and hexane extracts of the whole plant were prepared using soxhlet apparatus. The GC-MS analysis of plant extracts identifies 22 and 35 major compounds of methanol and hexane extracts which comprises of 74.21% and 73.20% of the total composition of extracts, respectively. The major compound in hexane was 2, 4-heptadienal (7.99%) whereas trans, trans-9, 12-octadecadienoic acid propyl ester (16.96%) was major compound in methanol extract. The extracts were evaluated for antioxidant and anti-inflammatory properties. Methanol extract showed higher free radical scavenging and reducing power activities with IC 50 value 153.82±1.69 μg/mL and RP 50 value of 152.28±0.41 μg/mL, respectively. The metal chelating activity was higher in hexane extract as compared to methanol extract i.e., 62.08±0.25 μg/mL. The anti-inflammatory activity assessed by its ability to inhibit denaturation was higher in methanol having IB 50 value 87.33±0.15 µg/mL. The total phenolic content (TPC), total flavonoid content (TFC) and ortho-dihydric phenol content (ODP) of methanol and hexane extracts were also evaluated. TPC, TFC and ODP was higher in methanol extract having value of 122.23±0.22, 35.01±0.29 and 8±0.86 mg/mL, respectively. Acmella uliginosa , might be considered as a natural source for antioxidant and anti-inflammatory properties.
The Feasibility and Impact of Practising Online Forest Bathing to Improve Anxiety, Rumination, Social Connection and Long-COVID Symptoms: A Pilot Study

Background: Long-COVID affects over 144 million people globally. In the absence of treatments, there is a need to establish the efficacy of therapies that improve patient outcomes. Forest bathing has been demonstrated to improve physical and mental outcomes but there is no evidence in Long-COVID patients. Accordingly, this pilot study sought to determine the feasibility and effectiveness of online forest bathing in adults with Long-COVID. Methods: Feasibility was assessed by monitoring retention rates and participant feedback. In a waitlist controlled, repeated measures design, 22 Long-COVID patients completed weekly online surveys during a four-week waitlist control period, before engaging in four weekly online forest bathing sessions, completing post-intervention surveys following each session. Results: In terms of retention, 27% did not provide post-intervention data, reasons for non-adherence were: feeling too ill, having medical appointments, or having career responsibilities. Compared with the waitlist control period, there were statistically significant improvements in Anxiety (49% decrease), Rumination (48% decrease), Social Connection (78% increase), and Long-COVID symptoms (22% decrease). Written qualitative comments indicated that participants experienced feelings of calm and joy, felt more connected socially and with nature, and experienced a break from the pain and rumination surrounding their illness. Conclusions: Online Forest bathing resulted in significant improvements in well-being and symptom severity and could be considered an accessible and inexpensive adjunct therapy for Long-COVID patients. Where people have limited access to in-person nature, virtual nature may offer an alternative to improve health and well-being outcomes.
Optimal Lipschitz criteria and local estimates for non-uniformly elliptic problems

We report on new techniques and results in the regularity theory of general non-uniformly elliptic variational integrals. By means of a new potential theoretic approach we reproduce, in the non-uniformly elliptic setting, the optimal criteria for Lipschitz continuity known in the uniformly elliptic one and provide a unified approach between non-uniformly and uniformly elliptic problems.
Quantization maps, algebra representation, and non-commutative Fourier transform for Lie groups

The phase space given by the cotangent bundle of a Lie group appears in the context of several models for physical systems. A representation for the quantum system in terms of non-commutative functions on the (dual) Lie algebra, and a generalized notion of (non-commutative) Fourier transform, different from standard harmonic analysis, has been recently developed, and found several applications, especially in the quantum gravity literature. We show that this algebra representation can be defined on the sole basis of a quantization map of the classical Poisson algebra, and identify the conditions for its existence. In particular, the corresponding non-commutative star-product carried by this representation is obtained directly from the quantization map via deformation quantization. We then clarify under which conditions a unitary intertwiner between such algebra representation and the usual group representation can be constructed giving rise to the non-commutative plane waves and consequently, the non-commutative Fourier transform. The compact groups U(1) and SU(2) are considered for different choices of quantization maps, such as the symmetric and the Duflo map, and we exhibit the corresponding star-products, algebra representations, and non-commutative plane waves.
ERP System Synergizes Company Resources to Achieve Excellence

Synergy between resources consisting of man, money, material machine, method, and market in conducting business activities is very necessary in order to achieve business excellence. One way that can be done is to implement an ERP system. For this reason, the design and implementation of business processes into the Odoo 14 ERP system for SMEs in the retail business of finished or prescription drugs, called the Sehat dan Cantik Pharmacy, is still using the manual method. The system design is carried out using the System Development Life Cycle method, consisting of the investigation stage, analysis stage, design stage, implementation stage, and maintenance stage. Then proceed with measuring the success of the system designed using the D&M IS Success Model framework. The system success value is 17.82 of 20. The ERP system that has been developed has succeeded in creating synergies between the resources owned, so that excellence is obtained in various computerized purchasing, inventory management, and sales business processes. This happens, because the pharmacy business process activities become more organized and efficient with the modification and elimination of old and manual business process activities to new and digitized business processes, as well as minimizing human-error.
Entropy dissipation estimates for inhomogeneous zero-range processes

Introduced by Lu and Yau (CMP, 1993), the martingale decomposition method is a powerful recursive strategy that has produced sharp log-Sobolev inequalities for homogeneous particle systems. However, the intractability of certain covariance terms has so far precluded applications to heterogeneous models. Here we demonstrate that the existence of an appropriate coupling can be exploited to bypass this limitation effortlessly. Our main result is a dimension-free modified log-Sobolev inequality for zero-range processes on the complete graph, under the only requirement that all rate increments lie in a compact subset of $(0,\infty)$. This settles an open problem raised by Caputo and Posta (PTRF, 2007) and reiterated by Caputo, Dai Pra and Posta (AIHP, 2009). We believe that our approach is simple enough to be applicable to many systems.
Dynamical generalization of a solvable family of two-electron model atoms with general interparticle repulsion

Holas, Howard and March (2003 Phys. Lett. A 310 451) have obtained analytic solutions for ground-state properties of a whole family of two-electron spin-compensated harmonically confined model atoms whose different members are characterized by a specific interparticle potential energy u(r12). Here, we make a start on the dynamic generalization of the harmonic external potential, the motivation being the serious criticism levelled recently against the foundations of time-dependent density-functional theory (e.g., Schirmer and Dreuw 2007 Phys. Rev. A 75 022513). In this context, we derive a simplified expression for the time-dependent electron density for arbitrary interparticle interaction, which is fully determined by a one-dimensional non-interacting Hamiltonian. Moreover, a closed solution for the momentum space density in the Moshinsky model is obtained.
A Proximal Diffusion Strategy for Multiagent Optimization With Sparse Affine Constraints

This article develops a proximal primal–dual decentralized strategy for multiagent optimization problems that involve multiple coupled affine constraints, where each constraint may involve only a subset of the agents. The constraints are generally sparse, meaning that only a small subset of the agents are involved in them. This scenario arises in many applications, including decentralized control formulations, resource allocation problems, and smart grids. Traditional decentralized solutions tend to ignore the structure of the constraints and lead to degraded performance. We instead develop a decentralized solution that exploits the sparsity structure. Under constant step-size learning, the asymptotic convergence of the proposed algorithm is established in the presence of nonsmooth terms, and it occurs at a linear rate in the smooth case. We also examine how the performance of the algorithm is influenced by the sparsity of the constraints. Simulations illustrate the superior performance of the proposed strategy.
Effectiveness of Network Centrality for Improving Distribution System Resilience by Hardening

Extreme weather events usually lead to catastrophic damage that renders distribution systems unreliable. The effectiveness of post-event restoration operations can be considerably increased by a well-designed hardening approach. This paper proposed a preventive strategic approach for line hardening to minimize the adverse effects of these events. The approach identifies optimal modeling of distribution line hardening with the least number of vulnerable branches in service and the entire load is provided after obtaining signals for the predicted catastrophe event. A resilience index is shown to evaluate performance of proposed preventive approach in reducing system vulnerability when an event occurs. Numerical results obtained for IEEE 33-bus system validated effectiveness of the proposed hardening solution approach.
Evaluation of the Performance of Methods for Classifying EEG Signal Processing

Over the past few decades the popularity of artificial neural networks has been continuously increasing in the fields of machine learning, data mining and pattern recognition. However, it has been suggested that in many scenarios artificial neural networks do not always deliver the best performance when compared to other data classification methods, like tree-based models. This article evaluates and compares the performance of different classification algorithms and methods employing electroencephalography data. Both artificial neural networks and classic methods are benchmarked and compared.
Assessment Method Based on AIS Data Combining the Velocity Obstacle Method and Pareto Selection for the Collision Risk of Inland Ships

A ship collision risk assessment model is an essential part of ship safety navigation. At present, the open water collision risk assessment model (such as the closest point of approach) is applied, but a ship collision risk model suitable for inland rivers is still in the exploration stage. Compared with open waters, the inland waterway has a larger density of ships, and the land and water environments are complex. The existing risk assessment models lack adaptability under the conditions of inland navigation. Therefore, this paper proposes a real-time collision risk assessment method for ships navigating inland rivers. This method utilizes the information of ships’ size in the automatic identification system (AIS) to construct the velocity obstacle cone between convex polygonal targets using the velocity obstacle method. Then, according to the geometric relationship between the relative velocity of two targets and the velocity obstacle cone, a new collision risk assessment model is defined. This model defines two indicators to evaluate the navigation collision risk: the degree of velocity obstacle intrusion (DVOI) and time of velocity obstacle intrusion (TVOI). These two indicators assess the risk of collision, respectively, from two aspects speed and course. In addition, a method using a trajectory compression algorithm to screen collision avoidance operation points in ship AIS trajectory is proposed to screen collision avoidance scenarios in the Yangtze River waterway. The effectiveness of the proposed collision risk model is verified in course-keeping and collision avoidance scenarios and compared with the traditional closest point of approach (CPA) method. The results indicate that the evaluation model for collision risk assessment is more accurate than the CPA method in all scenarios. Finally, this paper uses the Pareto selection algorithm to combine DVOI and TVOI, which can identify the ship that poses the greatest risk to our ship.
An Improved Lightweight YOLOv5 Network for Defect Detection of Rail Fasteners

The rail fastener is an important infrastructure of railway line system to ensure the safety of railway operation. There is an urgent need for a set of automatic defect inspection scheme for rail fasteners which have high efficiency and accuracy. To this end, this paper proposes a modified lightweight YOLOv5 model considering the application scenario of UAV. We reconstruct the backbone on the basis of ShuffleNetV2 and RepVGG, and switch the detector head to decoupled type from YOLOX. Data augmentation is adopted to address the problem of deficient defect samples. The results show that Yoloxs-lite_s model with ShuffleNetV2 backbone and YOLOX-s head is the most ideal model.
Indirect Immobilised Jagged-1 Enhances Matrisome Proteins Associated with Osteogenic Differentiation of Human Dental Pulp Stem Cells: A Proteomic Study

The indirect immobilisation of Jagged-1 (Jagged-1) promoted osteogenic differentiation of human dental pulp cells (hDPs). Furthermore, the analysis of the Reactome pathway of RNA sequencing data indicates the upregulated genes involved with the extracellular matrix (ECM). Hence, our objective was to investigate the effects of Jagged-1 on proteomic profiles of human dental pulp stem cells (hDPSC). hDPSCs were cultured on the surface coated with human IgG Fc fragment (hFc) and the surface coated with rhJagged1/Fc recombinant protein-coated surface. Cells were differentiated to the osteogenic lineage using an osteogenic differentiation medium (OM) for 14 days, and cells cultured in a growth medium were used as a control. The protein component of the cultured cells was extracted into the cytosol, membrane, nucleus, and cytoskeletal compartment. Subsequently, the proteomic analysis was performed using liquid chromatography–tandem mass spectrometry (LC-MS). Metascape gene list analysis reported that Jagged-1 stimulated the expression of the membrane trafficking protein (DOP1B), which can indirectly improve osteogenic differentiation. hDPSCs cultured on Jagged-1 surface under OM condition expressed COL27A1, MXRA5, COL7A1, and MMP16, which played an important role in osteogenic differentiation. Furthermore, common matrisome proteins of all cellular components were related to osteogenesis/osteogenic differentiation. Additionally, the gene ontology categorised by the biological process of cytosol, membrane, and cytoskeleton compartments was associated with the biomineralisation process. The gene ontology of different culture conditions in each cellular component showed several unique gene ontologies. Remarkably, the Jagged-1_OM culture condition showed the biological process related to odontogenesis in the membrane compartment. In conclusion, the Jagged-1 induces osteogenic differentiation could, mainly through the regulation of protein in the membrane compartment.
Proposal of a Novel Topology of Five-Phase Fractional Slot Concentrated Non-Overlapping Winding with Selective MMF Harmonic Elimination

In this paper, a novel topology of five-phase fractional-slot concentrated winding (FSCW) with selective magnetomotive force (MMF) harmonic elimination is proposed. Compared to traditional FSCW with stator shift technique, not only the parasitic sub- or sup-order harmonics of the MMF can be selectively reduced or eliminated, the non-overlapping characteristic is also kept. Firstly, based on 20-slot/22-pole single-layer (SL) winding topology, a dual five-phase 40-slot/22-pole one of SL winding with 1st harmonic elimination is introduced. Secondly, a new 40-slot/22-pole of double-layer with selective harmonic reduction is presented. Finally, the high performances of the machine with the proposed winding topology are evaluated using finite element analysis (FEA), including air gap flux density, output torque, machines losses, etc.
Spiral structures in the rotor-router walk

We study the rotor-router walk on the infinite square lattice with the outgoing edges at each lattice site ordered clockwise. In the previous paper (Papoyan et al 2015 J. Phys. A: Math. Theor. 48 285203), we considered the loops created by rotors and labeled the sites where the loops become closed. The sequence of labels in the rotor-router walk was conjectured to form a spiral structure asymptotically obeying an Archimedean property. In the present paper, we select a subset of labels called ‘nodes’ and consider the spirals formed by them. The new spirals are directly related to tree-like structures, which represent the evolution of the cluster of vertices visited by the walk. We show that the average number of visits to the origin 〈n0(t)〉 by the moment t≫1 is 〈n0(t)〉=4〈n(t)〉+O(1) where 〈n(t)〉 is the average number of spiral rotations.
Structured Low-Rank and Sparse Method for ISAR Imaging With 2-D Compressive Sampling

With the development of modern advanced radar, there are high demands to perform inverse synthetic aperture radar (ISAR) imaging from sparse frequency band (SFB) and sparse aperture (SA) data, respectively. The compressed sensing (CS)-based methods are commonly applied to deal with the sparse sampling data, nevertheless, suffering from the inherent problem of basis mismatch on the discrete dictionary. Alternatively, the matrix completion (MC) approaches using the low-rank property are also employed to avoid the discrete error by directly reconstructing the missing data, belonging to the group of grid-free technology. However, this class method can hardly provide satisfactory performance on the type of block sparse sampling data. In this article, a novel structured low-rank and sparse (SLR + S) algorithm is proposed for high-resolution ISAR imaging with 2-D compressive sampling, which can effectively deal with various types of sparse sampling patterns. In the scheme, the ISAR signal model with 2-D compressive sampling is established to integrate three commonly used waveforms, including linear frequency modulation (LFM), sparse stepped LFM, and random frequency division modulation. Then, a novel algorithm is proposed for complete sampling data recovery using joint low-rank and sparse constraints. In particular, a structured Hankel formulation is utilized to effectively exploit the latent information of data structure with the enhanced low-rank property. As follows, a fast alternating direction method of multipliers (ADMMs) is applied for high-efficiency and high-precision image reconstruction. Compared with traditional CS and MC methods, the proposed algorithm has the capability of dealing with different patterns of 2-D compressive sampling. Finally, the experiments using both simulated and measured data are performed to confirm the effectiveness of the proposal.
$G_2$-orbifolds from K3 surfaces with ADE-singularities

We construct compact $G_2$-orbifolds with ADE-singularities that carry exactly one parallel spinor. Our examples are related to certain quotients of $\mathbb{C}^2\times T^3$ that have been investigated in arXiv:hep-th/9812205. We shortly discuss the physical applications of our examples.
Gaussian Upper Bounds for Heat Kernels of Continuous Time Simple Random Walks

We consider continuous time simple random walks with arbitrary speed measure $\theta$ on infinite weighted graphs. Write $p_t(x,y)$ for the heat kernel of this process. Given on-diagonal upper bounds for the heat kernel at two points $x_1,x_2$, we obtain a Gaussian upper bound for $p_t(x_1,x_2)$ . The distance function which appears in this estimate is not in general the graph metric, but a new metric which is adapted to the random walk. Long-range non-Gaussian bounds in this new metric are also established. Applications to heat kernel bounds for various models of random walks in random environments are discussed.
Vanishing Pohozaev constant and removability of singularities

Conformal invariance of two-dimensional variational problems is a condition known to enable a blow-up analysis of solutions and to deduce the removability of singularities. In this paper, we identify another condition that is not only sufficient, but also necessary for such a removability of singularities. This is the validity of the Pohozaev identity. In situations where such an identity fails to hold, we introduce a new quantity, called the {\it Pohozaev constant}, which on one hand measures the extent to which the Pohozaev identity fails and on the other hand provides a characterization of the singular behavior of a solution at an isolated singularity. We apply this to the blow-up analysis for super-Liouville type equations on Riemann surfaces with conical singularities, because in the presence of such singularities, conformal invariance no longer holds and a local singularity is in general non-removable unless the Pohozaev constant is vanishing.