Miracle-dz/UniFAR-FTUs huggingface dataset:
Integrated weed management using row arrangements and herbicides in pigeonpea (Cajanus cajan) in Australia

In Australia, efforts are under way to revive the pigeonpea (Cajanus cajan (L.) Millsp. ) industry, which has high export potential because of an increased demand in the international market. However, weeds are a major constraint to achieve high yield in pigeonpea. This study was designed to assess the effect of row arrangement and herbicide treatment on weed suppression and pigeonpea grain yield. Row arrangements included row spacing (narrow, 25 cm; wide, 50 cm) and paired rows (rows 25 cm apart within a pair, each pair separated from the next by 75 cm). Herbicide treatments were: untreated control; pre-emergent pendimethalin at 910 g a.i. ha–1; post-emergent imazapic at 84 g a.i. ha–1; and pre-emergent pendimethalin followed by post-emergent imazapic (rates as above). In the first year, Trianthema portulacastrum was the dominant weed, and infestation was 100% in the non-treated control plots. In the second year, other weeds (Setaria viridis, Eragrostis cilianensis and Chloris virgata) comprised 30% of the weed population. Averaged over row arrangements, grain yield varied from 2088 to 2689 kg ha–1 in 2017 and from 835 to 2145 kg ha–1 in 2018, and was lowest in the untreated control and highest in the plots treated with the sequential application of pendimethalin and imazapic. Averaged over years and herbicide treatments, yield was lower in paired rows (1850 kg ha–1) than in narrow (2225 kg ha–1) and wide (2165 kg ha–1) row spacings. In the first year, all herbicide treatments provided >50% control of T. portulacastrum in the narrow and wide row spacings and increased yield by >22% over the untreated control. In the second year, the single application of imazapic proved inferior for controlling weeds, resulting in a 21% reduction in grain yield compared with sequential application of pendimethalin and imazapic. In both years, grain yield was similar for the single application of pendimethalin and sequential application of pendimethalin and imazapic. Despite the complex weed flora in 2018, the single application of imazapic provided acceptable weed control only when the crop was planted at 25 cm row spacing. Our results suggest that the single application of pendimethalin was effective on T. portulacastrum. However, in a complex weed flora situation, the sequential application of pendimethalin and imazapic provided effective weed control and resulted in improved yield.
Witnessing single-photon entanglement with local homodyne measurements: analytical bounds and robustness to losses

Single-photon entanglement is one of the primary resources for quantum networks, including quantum repeater architectures. Such entanglement can be revealed with only local homodyne measurements through the entanglement witness presented in Morin et al (2013 Phys. Rev. Lett. 110 130401). Here, we provide an extended analysis of this witness by introducing analytical bounds and by reporting measurements confirming its great robustness with regard to losses. This study highlights the potential of optical hybrid methods, where discrete entanglement is characterized through continuous-variable measurements.
Joint SCMA and waveform optimisation for WPDM-based logging cable telemetry systems under sampling clock offset

This study introduces sparse code multiple access (SCMA) and wavelet packet division multiplexing (WPDM) to logging cable telemetry systems (LCTSs). The authors study the feasibility of SCMA for LCTSs and provide a WPDM-based system model, as well as the associated optimal waveform design under sampling clock offset (SCO) via a genetic algorithm. The performance advantages of the designed scheme over the conventional WPDM and orthogonal frequency division multiplexing (OFDM) are demonstrated by both analytical and simulation methods. Numerical results show the performance of the SCMA-based mapping method over quadrature amplitude modulation in terms of improved spectral efficiency. Furthermore, the new scheme outperforms conventional WPDM and OFDM in bit error rate performance and transmission rate under SCO. Such advantages with the flexible design of basis functions make SCMA and WPDM a significant candidate for LCTSs.
Virtual element method for semilinear hyperbolic problems on polygonal meshes

ABSTRACT This article deals with the development of the virtual element method for the approximation of semilinear hyperbolic problems. For the space discretization, two different operators are used: the energy projection operator and an internal -projection operator . In order to deal with the time derivative, a Newmark scheme is employed; and the resulted fully discrete scheme is analysed. Moreover, with the help of projection operators, optimal error estimates are derived for both semi- and fully discrete schemes in -norm and -norm. We have conducted numerical experiments on polygonal meshes to illustrate the performance of the proposed scheme and validate the theoretical findings.
Genome-wide characterisation of superoxide dismutase genes in grape and their expression analyses during berry development process

ABSTRACT Previous studies about superoxide dismutase (SOD) genes were mostly with regard to biotic and abiotic stress responses. Some reports have indicated SOD genes may play an important role in plant development. However, little is known about the relationship of SOD genes with grape berry ripening. Thirteen VviSOD genes were identified from grape genome sequences based on the bioinformatic method. Phylogenetic analysis indicated that these VviSODs could be divided into two groups. The genes of VviCu/ZnSOD1a and VviCu/ZnSOD1c were identified as tandem replication genes. The expression analyses based on RNA-Seq and qRT-PCR results in ‘Kyoho’ and its early-ripening bud mutant, ‘Fengzao’, demonstrated that the VviSOD genes involved in the grape berry ripening and VviCu/ZnSOD1c were the main candidate. Sequence analysis of VviCu/ZnSOD1c gene in ‘Fengzao’ showed that the coding sequence was the same as that of ‘Kyoho’. According to the bioinformatic and expression analysis, VviSOD genes probably involved in the grape berry ripening and VviCu/ZnSOD1c was selected as the main candidate to further explore its potential role in the early ripening of ‘Fengzao’.
Clustering Based on Eigenvectors of the Adjacency Matrix

Abstract The paper presents a novel spectral algorithm EVSA (eigenvector structure analysis), which uses eigenvalues and eigenvectors of the adjacency matrix in order to discover clusters. Based on matrix perturbation theory and properties of graph spectra we show that the adjacency matrix can be more suitable for partitioning than other Laplacian matrices. The main problem concerning the use of the adjacency matrix is the selection of the appropriate eigenvectors. We thus propose an approach based on analysis of the adjacency matrix spectrum and eigenvector pairwise correlations. Formulated rules and heuristics allow choosing the right eigenvectors representing clusters, i.e., automatically establishing the number of groups. The algorithm requires only one parameter-the number of nearest neighbors. Unlike many other spectral methods, our solution does not need an additional clustering algorithm for final partitioning. We evaluate the proposed approach using real-world datasets of different sizes. Its performance is competitive to other both standard and new solutions, which require the number of clusters to be given as an input parameter.
A parameter-uniform method for singularly perturbed turning point problems exhibiting interior or twin boundary layers

ABSTRACT A numerical scheme for a class of two-point singularly perturbed boundary value problems with an interior turning point having an interior layer or twin boundary layers is proposed. The solution of this type of problem exhibits a transition region between rapid oscillations and the exponential behaviour. The problem with interior turning point represents a one-dimensional version of stationary convection–diffusion problems with a dominant convective term and a speed field that changes its sign in the catch basin. To solve these problems numerically, we consider a scheme which comprises quintic B-spline collocation method on an appropriate piecewise-uniform mesh, which is dense in the neighbourhood of the interior/boundary layer(s). The method is shown to be parameter-uniform with respect to the singular perturbation parameter ϵ. Some relevant numerical examples are illustrated to verify the theoretical aspects computationally. The results compared with other existing methods show that the proposed method provides more accurate solutions.
SmartDPM: Machine Learning-Based Dynamic Power Management for Multi-Core Microprocessors

To address the power management challenge in multi-core microprocessors, we present a lightweight machine learning based dynamic power management ( SmartDPM ) scheme in which the voltage–frequency levels of the cores are dynamically adjusted along with online learning based workload prediction in an observer-controller loop. To enable scalability, our SmartDPM employs a per-application autonomous power management policy, in which online machine learning principles are employed for predicting the workload and capturing sporadic variations under the constraints of accurate yet lightweight . Further, applications are assigned appropriate voltage–frequency level towards an efﬁcient power management. The learning helps in dynamically reducing prediction error. Compared to the non-DVFS implementation, SmartDPM achieves nearly 35% power saving and nearly 15% higher power savings on average compared to the existing machine learning based power management schemes for a microprocessor with up to 32-cores.
PENGARUH EKSTRAK UBI JALAR UNGU (Ipomoea batatas L.) TERHADAP KADAR Superoksida Dismutase (SOD) TIKUS PUTIH JANTAN (Rattus norvegicus) GALUR WISTAR MODEL ATEROSKLEROSIS

Latar Belakang: Penyakit jantung koroner (PJK) merupakan penyakit jantung yang terutama disebabkan karena penyempitan arteri koronaria akibat proses aterosklerosis. Faktor yang berpengaruh terhadap pembentukan plakaterosklerosis adalah radikal bebas. Ekstrak ubi jalarung umemliki kandungan antosianin, beta glukan dan assamaskorbat sebagai antioksi dan, diharapkan dapat menghambat radikal bebas sehingga plakaterosklerosis tidak terbentuk. Tujuan: Mengetahui Pengaruh pemberian Ekstrak Ubi Jala rUngu (Ipomoea batatasL.) terhadap kadar Superoksida Dismutase SOD tikus jantan putih (Rattusnorvegicus) galurwistar model aterosklerosis. Metode: TrueExperimental, PostTest Only Control Group Designdengan kelompok kontrol negatif, kontrol positif, serta 3 kelompok perlakuan ekstrak Ubi Jalar Ungu yaitu dosis 24mg/hari, 48mg/hari, 96mg/hari Hasil penelitian dan diskusi: Hasil Uji One Way Anova p=0,001 (p<0,05) terdapat perbedaan signifikan. Hasil Uji Post Hoc didapatkan konotasi berbeda antar kelompok. Hasil Uji Korelasi terdapat hubungan yang kuat yaitu p=0,000 (p<0,05). Pada Uji Regresi linier didapatkan R2=0.65. Berdasarkan hasil uji yang dilakukan menunjukkan semakin tinggi dosis ekstrak yang diberikan, semakin tinggi kadar SOD Kesimpulan: Terdapat pengaruh antara pemberian ekstrak ubi jalar ungu (IpoemabatatasL.) terhadap peningkatan kadar Superoksida Dismutase (SOD) tikus jantan putih (Rattusnorvegicus) galurwistar model aterosklerosis.
Arsenic behavior in the autoclave-hydrometallurgical processing of refractory sulfide gold-platinum-bearing products

Among various types of gold-bearing ores a special place belongs to the ores, which contain gold finely-dispersed in sulphide minerals, mostly in arseno-pyrite and pyrite. Autoclave-hydrometallurgical processing technologies for such raw materials seem to be of a particular interest for study. However, autoclave oxidation of sulfide-arsenic material results in significant amounts of technological solutions with high concentrations of arsenic, iron and sulfuric acid. This article represents the studies of how arsenic behaves in autoclave oxidative leaching of a refractory sulphide gold-platinum-bearing concentrate. We studied how the composition of arsenic-bearing solutions in autoclave leaching (acidity, concentration of iron and arsenic) influences the depth of arsenic precipitation when neutralized with calcium-containing reagents, which allows converting the maximum amount of arsenic together with iron in the form of iron arsenate into a stable long-term storable precipitation.
Prediction of the Vase Life of Cut Lily Flowers Using Thermography

This study was conducted in order to predict the vase life of cut lily ‘Woori Tower’ flowers using a non-destructive thermal imaging technique. It was found that the temperature of cut lily flowers was maintained at 20 and was °C slightly lower than the air temperature until they bloomed. On the 11th day, when flowers bloomed, the temperature of leaves and flowers was measured to be 18.75±0.38 and 19.23±0.32 respectively, and their dif °C °C ference with ambient temperature was over 3 . The flower temperature increased slightly when the vase life of cut °C lily flowers ended, and the temperature difference between the air and leaf temperature (1.77 ) and between the °C air and flower temperature (1.39 ) got smaller. No visible aging symptom was observed, but it was found that the °C temperature had risen due to water losses and less functional stomata. The vase life of cut lily flowers can be predicted based on changes in temperature and it will be also possible to predict the potential quality and vase life of cut flowers before harvesting them in greenhouses.
How to Count Multiple Personal-Space Intrusions in Social Robot Navigation

One aspect of social robot navigation is to avoid personal space intrusions. Computationally, this can be achieved by introducing social costs into a robot’s path planner’s objective function. This article tackles the normative question of how robots should aggregate social costs incurred by multiple personal-space intrusions. Of particular interest is the question whether numbers should count, i.e., whether a robot ought to intrude into one person’s personal space in order to avoid intruding into multiple personal spaces. This work proposes four different modes of aggregation of the costs of intrusions into personal space, discusses some of the philosophical arguments, and presents results from a pilot study.
How Trust and Need Satisfaction Motivate Producing User-Generated Content

ABSTRACT The motivation of user-generated content (UGC) is a vital issue for social media providers. This study investigates this issue using the self-determination theory (SDT). The SDT identifies three fundamental human psychological needs, namely the need for competence, autonomy, and relatedness. This study aims to answer the question of how the satisfaction of these needs motivates users to produce UGC and utilizes the multi-study model comparison approach. Two survey studies were conducted in China and the United States. The partial least squares (PLS) analyses confirmed that the SDT indeed explained UGC motivation significantly and that trust beliefs support people’s need for relatedness. Post hoc analyses showed that there were significant differences between Chinese and American culture. Those results make important contributions to theory and practice. For example, practitioners need to motivate users to produce UGC by supporting their psychological needs. Besides, different trust beliefs should be emphasized in different countries.
Protein-protein docking using learned three-dimensional representations

Protein-protein interactions are determined by a number of hard-to-capture features related to shape complementarity, electrostatics, and hydrophobicity. These features may be intrinsic to the protein or induced by the presence of a partner. A conventional approach to protein-protein docking consists in engineering a small number of spatial features for each protein, and in minimizing the sum of their correlations with respect to the spatial arrangement of the two proteins. To generalize this approach, we introduce a deep neural network architecture that transforms the raw atomic densities of each protein into complex three-dimensional representations. Each point in the volume containing the protein is described by 48 learned features, which are correlated and combined with the features of a second protein to produce a score dependent on the relative position and orientation of the two proteins. The architecture is based on multiple layers of SE(3)-equivariant convolutional neural networks, which provide built-in rotational and translational invariance of the score with respect to the structure of the complex. The model is trained end-to-end on a set of decoy conformations generated from 851 nonredundant protein-protein complexes and is tested on data from the Protein-Protein Docking Benchmark Version 4.0.
A versatile endosome acidity-induced sheddable gene delivery system: increased tumor targeting and enhanced transfection efficiency

Background Polycation carriers show great foreground in the developing efficient and safe gene delivery; nevertheless, they are cytotoxic and unstable in vivo because of the excess cationic charge. PEGylation improves the biocompatibility and stability of polycation, whereas PEGylation restrains the endosomal escape to some extent. Materials and methods To address this issue and promote the transfection in vivo, a pH-sensitive conjugate folate-polyethylene glycol-carboxylated chitosan (shorten as FA-PEG-CCTS) was designed and coated on the surface of PEI/NLS/pDNA (PNDs), forming a versatile gene carrier FA-PEG-CCTS/PEI/NLS/pDNA (FPCPNDs). The novel carrier exhibited a few picturesque characteristics, including (i) neutral surface charge to restrain nonspecific interactions; (ii) folate receptors (FR)-mediated endocytosis to augment cellular uptake; (iii) dual proton sponge effect to realize endosome escape, and (iv) nuclear localization sequences (NLS) to enhance the transfection of pDNA. Results FPCPNDs could compress and protect pDNA from degradation. FPCPNDs energetically targeted tumor cells because of their high binding affinity between FA and highly expressed FR on the tumor surface, accordingly enhancing the cellular uptake. In the acidic endosomes, FA-PEG-CCTS segment dissociated from PNDs. Then, PNDs realized endosomal escape through the proton sponge effect of PEI. Furthermore, FPCPNDs showed admirable transfection efficiency with the aid of NLS peptides. What’s more, in vivo studies revealed that FPCPNDs had supreme antitumor activity among the whole preparations. Conclusion In vitro and in vivo assays thus demonstrate that FPCPNDs is a hopeful strategy for gene delivery.
Title Advances in the growth and characterization of magnetic , ferroelectric , and multiferroic oxide thin films

The growth and characterization of functional oxide thin films that are ferroelectric, magnetic, or both at the same time are reviewed. The evolution of synthesis techniques and how advances in in situ characterization have enabled significant acceleration in improvements to these materials are described. Methods for enhancing the properties of functional materials or creating entirely new functionality at interfaces are covered, including strain engineering and layering control at the atomic-layer level. Emerging applications of these functional oxides such as achieving electrical control of ferromagnetism and the future of these complex functional oxides is discussed. 2010 Elsevier B.V. All rights reserved. Abbreviations: AAO, anodized aluminum oxide; AF, antiferromagnet; AFM, atomic force microscopy; BFO, BiFeO3; BMO, BiMnO3; BTO, BaTiO3; c-AFM, conducting atomic force microscopy; CBD, chemical bath deposition; CFO, CoFe2O4; CMR, colossal magnetoresistance; CSD, chemical solution deposition; DSO, DyScO3; EB, exchange bias; ED, electroless deposition; eV, electron volt; FeRAM, ferroelectric random access memory; FM, ferromagnet; GMR, giant magnetoresistance; GSO, GdScO3; H, magnetic field; HRTEM, high-resolution transmission electron microscopy; LSMO, La0.7Ca0. 3MnO3; LPD, liquid phase deposition; LSAT, (LaAlO3)0.29–(Sr0.5Al0.5TaO3)0.71; MBE, molecular beam epitaxy; MOCVD, metal-organic chemical vapor deposition; MRAM, magnetic random access memory; Oe, Oersted; PS, saturation polarization; P–E, polarization–electric field; PCD, photochemical deposition; PEEM, photoemission electron microscopy; PFM, piezoresponse force microscopy; PLD, pulsed laser deposition; PMN-PT, Pb(Mg0.33Nb0.67)O3–PbTiO3; PTO, PbTiO3; PZT, Pb(Zrx,Ti1 x)O3; RF, radio-frequency; RHEED, reflection high-energy electron diffraction; RHEED-TRAXS, reflection highenergy electron diffraction total reflection angle X-ray spectroscopy; SBT, SrBi2Ta2O9; SPES, spin-resolved photoemission spectroscopy; SQUID, superconducting quantum
Error bounds for approximations with deep ReLU neural networks in $W^{s, p}$ norms

We analyze to what extent deep Rectified Linear Unit (ReLU) neural networks can efficiently approximate Sobolev regular functions if the approximation error is measured with respect to weaker Sobolev norms. In this context, we first establish upper approximation bounds by ReLU neural networks for Sobolev regular functions by explicitly constructing the approximate ReLU neural networks. Then, we establish lower approximation bounds for the same type of function classes. A trade-off between the regularity used in the approximation norm and the complexity of the neural network can be observed in upper and lower bounds. Our results extend recent advances in the approximation theory of ReLU networks to the regime that is most relevant for applications in the numerical analysis of partial differential equations.
With Great Speed Come Small Buffers: Space-Bandwidth Tradeoffs for Routing

We consider the Adversarial Queuing Theory (AQT) model, where packet arrivals are subject to a maximum average rate 0 ≤ ρ ≤ 1 and burstiness σ ≤ 0. In this model, we analyze the size of buffers required to avoid overflows in the basic case of a path. Our main results characterize the space required by the average rate and the number of distinct destinations: we show that O(ℓ d1/ℓ + σ) space suffice, where d is the number of distinct destinations and ℓ=⌋1/ρ⌊ and we show that Ω(1 over ℓ d1/ℓ + σ) space is necessary. For directed trees, we describe an algorithm whose buffer space requirement is at most 1 + d' + σ where d' is the maximum number of destinations on any root-leaf path.