Miracle-dz/UniFAR-FTUs huggingface dataset:
Long distance transport of potassium in cereals during grain filling in intact plants

Translocation of labeled potassium (K+) from the root to the ear and its distribution within the culm during 4, 8 and 12 h of uptake was studied in intact wheat plants (Triticum aestivum L. cv. Kolibri) 3 and 5 weeks after anthesis at 0.5 and 5.0 mM K+ concentration in the uptake solution. Uptake of labeled K+ into the shoot was proportional to the K+ concentration applied. After 4 h of uptake about 2% and after 12 h about 7% of labeled K+ applied to the roots were taken up into the shoot at both K+ concentrations. After 12 h of uptake only 6% of the total label in the culm had reached the ear, while about 40% of the label was found in the upper three internodes. In spite of an increasing concentration of labeled K+ during 12 h in the uppermost internode (peduncle), translocation of K+ into the rachis was low. The low and uniform K+ content found generally in grain dry weight seems therefore to be due to a controlled K+ supply to the ear.
Producing biofuels from urban organic waste

This study explored the possibility to biologically produce hydrogen and methane through the thermophilic single and two stages anaerobic codigestion of waste activated sludge and the organic fraction of municipal solid waste. Specific gas productions in single and double-stage processes working with an hydraulic retention time of 20 days were 493 L/kgTVS and 572 L/kgTVS, respectively. In the two stage process hydrogen and methane productions reached values of 24 LH2/kgTVS and 272 LCH4/kgTVS, respectively. Obtained biohythane, after upgrading, is particularly valuable for the automotive sector.
DIGESTION SURVIVAL OF ALGAE: SOME ECOLOGICAL COMPARISIONS BETWEEN FREE SPORES AND PROPAGULES IN FECAL PELLETS 1

Benthic algae survive passage through the digestive tract of different types of grazers, either regenerating new tissues or releasing protoplasts and swarmers which act as accessory means of reproduction to generate new individuals. The ecological importance of this phenomenon is evaluated here by studying spores and fecal pellets. Alga fragments egested alive inside fecal pellets have some ecological advantages over free propagules. In intertidal habitats, the sticky nature of the pellets permits attachment to the substratum while protecting the contained algae from desiccation. In subtidal habitats, the pellets sink 8–22 times faster than the fastest sinking algal propagule. Quantification of swarmers and protoplasts released from algal fragments in the fecal pellets indicates densities of about 217 germlings·cm−2 and values of 300–700 propagules per pellet. Extrapolation of these results to field conditions based on number of grazers and pellets suggest production figures varying from 0.5–3.5 × 105to 1.3–1.5 × 106 propagules·m−2·12 h−1. These values are within known density ranges of settling spores in the field. The ecological significance of the phenomenon may be especially important at seasons when the density of grazers increases and the normal reproductive activity of the algae being consumed decreases.
Selective chemical control of doublegee (Emex australis) in legume pasture

Seven chemicals were evaluated for selective control of doublegee (Emex australis) in legume pasture in 14 field trials conducted at several sites in Western Australia over three years. The effect of removing doublegee on pasture growth was studied in four field trials over the same period. Three hundred and fifty to 700 g a.i. methabenzthiazuron ha-1 gave good selective control of this weed except at Chapman and Wongan Hills in 1974 where the beginning of the growing season was poorly defined. The selectivity of bromoxynil and WL 6361 1 in one year of trials was similar to methabenzthiazuron but that of asulam and metoxuron was too restricted for practical use when doublegees were sprayed at the 2-4 leaf growth stage, 2,4-DB showed selectivity on doublegees with 12 leaves, and no herbicides were satisfactory on doublegees with more than 12 leaves at the time of spraying. Pasture growth and clover seed production was not substantially increased by controlling doublegee.
Territorial and non-territorial spawning behaviour in the bream

The spawning behaviour of bream Abramis brama was studied in 1993, in a harbour on the River Meuse, Belgium. Fish spawned from 22 to 27 April and from 11 to 14 May, when the water temperature rose to 14.5) C. The reproductive behaviour of the bream was studied within a 15 m long part of the harbour using a video camera. Territorial males with tubercles (33–43 cm total length; >5 years old) defended bank areas of diameter 80–150 cm which included spawning substratum, i.e. roots of alder and willow trees and aquatic plants. Water depth ranged from 25 to 50 cm. Non-territorial males without tubercles (24–33 cm; 3–4 years old), remained 2–4 m away from the bank. Aggressive behaviour between males was frequent and, occasionally, males with tubercles were unable to defend a territory. Mature females (25–43 cm; >3 years old), coming from the deeper water of the surrounding area, were followed by non-territorial males before spawning in territories near the bank.
On The Relational Width of First-Order Expansions of Finitely Bounded Homogeneous Binary Cores with Bounded Strict Width

The relational width of a finite structure, if bounded, is always (1, 1) or (2, 3). In this paper we study the relational width of first-order expansions of finitely bounded homogeneous binary cores where binary cores are structures with equality and some anti-reflexive binary relations such that for any two different elements a, b in the domain there is exactly one binary relation R with (a, b) ϵ R. Our main result is that first-order expansions of liberal finitely bounded homogeneous binary cores with bounded strict width have relational width (2, MaxBound) where MaxBound is the size of the largest forbidden substructure, but is not less than 3, and liberal stands for structures that do not forbid certain finite structures of small size. This result is built on a new approach and concerns a broad class of structures including reducts of homogeneous digraphs for which the CSP complexity classification has not yet been obtained.
Controlled quantum imprisonment of wave packet and flat bands in a fractal geometry.

The explicit construction of non-dispersive flat band modes and the tunability of has been reported for a hierarchical 3-simplex fractal geometry. A single band tight binding Hamiltonian defined for the deterministic self-similar non-translationally invariant network can give rise to a countably infinity of such self localized eigenstates for which the wave packet gets trapped inside a characteristic cluster of atomic sites. An analytical prescription to detect those dispersionless states has been demonstrated elaborately. The states are localized over clusters of increasing sizes, displaying the existence of a multitude of localization areas. The onset of localization can, in principle, be delayed in space by an appropriate choice of the energy of the electron. The response of the system with the modulation of the anisotropy parameter is also studied. Supportive calculation of spectral landscape and demonstration of band dispersion plot are presented to solidify the analytical results. Variation of effective mass tensor cites re-entrant behavior with respect to the modulation of off-diagonal anisotropy. The tunability of those states leads to the controlled decay of wave function envelope. The impact of uniform magnetic perturbation on the bound states has also been discussed. Continuous variation of flux modulates the position of the flat band modes. The macroscopic degeneracy associated with the modes is retained with respect to the application of perturbation.
Thresholdless excitation of edge plasmons by transverse current

We theoretically demonstrate that dc electron flow across the junction of two-dimensional electron systems leads to excitation of edge magnetoplasmons. The threshold current for such plasmon excitation does not depend on contact effects and approaches zero for ballistic electron systems, which makes a strong distinction from the well-known Dyakonov-Shur and Cerenkov-type instabilities. We estimate the competing plasmon energy gain from dc current and loss due to electron scattering. We show that plasmon self excitation is feasible in GaAs-based heterostructures at $T\lesssim 200$ K and magnetic fields $B \lesssim 10$ T.
Towards Conversational Recommendation over Multi-Type Dialogs

We focus on the study of conversational recommendation in the context of multi-type dialogs, where the bots can proactively and naturally lead a conversation from a non-recommendation dialog (e.g., QA) to a recommendation dialog, taking into account user’s interests and feedback. To facilitate the study of this task, we create a human-to-human Chinese dialog dataset DuRecDial (about 10k dialogs, 156k utterances), where there are multiple sequential dialogs for a pair of a recommendation seeker (user) and a recommender (bot). In each dialog, the recommender proactively leads a multi-type dialog to approach recommendation targets and then makes multiple recommendations with rich interaction behavior. This dataset allows us to systematically investigate different parts of the overall problem, e.g., how to naturally lead a dialog, how to interact with users for recommendation. Finally we establish baseline results on DuRecDial for future studies.
STUDIES OF THE RELEASE OF DISSOLVED FREE AMINO ACIDS BY MARINE ZOOPLANKTON1

ABSTRACI’ Rates of release of clissolved free amino acids by marinc net zooplankton are a positive function of water temperature and can bc cstimatcd by the equation R = T 6.0, where R= release rate in mg a-amino N g-l day-‘, 2’ = temperature ( “C), and 6.0 is a constant. Most of the common protein amino acids are prcscnt in rclcase products. Glycine, taurinc, and alaninc usually predominate. It is cstimatcd that in an “average” water column net zooplankton release an amount of total dissolved amino acids equal to the amount in solution in about one month.
Can bars erode cuspy halos?

Abstract One of the major and widely known small scale problem with the Lambda CDM model of cosmology is the “core-cusp” problem. In this study we investigate whether this problem can be resolved using bar instabilities. We see that all the initial bars are thin (b/a < 0.3) in our simulations and the bar becomes thick ( b /a > 0.3) faster in the high resolution simulations. By increasing the resolution, we mean a larger number of disk particles. The thicker bars in the high resolution simulations transfer less angular momentum to the halo. Hence, we find that in the high resolution simulations it takes around 7 Gyr for the bar to remove inner dark matter cusp which is too long to be meaningful in galaxy evolution timescales. Physically, the reason is that as the resolution increases, the bar buckles faster and becomes thicker much earlier on.
Reproduction and development of the Arabian Leopard, Panthera pardus nimr, in captivity

Abstract The reproduction and development of the Arabian Leopard, Panthera pardus nimr, as determined in captivity, is similar to other subspecies although not previously documented and important from a captive breeding perspective. The following reproductive data was determined: inter-oestrus period 32.2 days; oestrus period 6.9 days; gestation period 97.5 days; mean number of cubs 1.25; cubs eyes open after 7.5 days.
GRAVITATIONAL WAVES, 100 YEARS LATER

We present a short communication on the recent direct measurements of gravitational waves, made possible by the joint efforts of the LIGO and the Virgo projects. These notes are devoted to a broad audience. In the first part we will present the basic ideas of the theory of relativity, leading to the prediction of the existence of gravitational waves. The second part is devoted to present the main results and consequences of the discovery.
Minority Class Oversampling for Tabular Data with Deep Generative Models

In practice, machine learning experts are often confronted with imbalanced data. Without accounting for the imbalance, common classifiers perform poorly and standard evaluation metrics mislead the practitioners on the model's performance. A common method to treat imbalanced datasets is under- and oversampling. In this process, samples are either removed from the majority class or synthetic samples are added to the minority class. In this paper, we follow up on recent developments in deep learning. We take proposals of deep generative models, including our own, and study the ability of these approaches to provide realistic samples that improve performance on imbalanced classification tasks via oversampling. Across 160K+ experiments, we show that all of the new methods tend to perform better than simple baseline methods such as SMOTE, but require different under- and oversampling ratios to do so. Our experiments show that the way the method of sampling does not affect quality, but runtime varies widely. We also observe that the improvements in terms of performance metric, while shown to be significant when ranking the methods, often are minor in absolute terms, especially compared to the required effort. Furthermore, we notice that a large part of the improvement is due to undersampling, not oversampling. We make our code and testing framework available.
Abundance and Diversity of Sulfur-Oxidizing Bacteria along a Salinity Gradient in Four Qinghai-Tibetan Lakes, China

Sulfur-oxidizing bacteria (SOB) play important roles in the sulfur cycle and are widespread in a number of environments, but their occurrence and relationship to geochemical conditions in (hyper)saline lakes are still poorly understood. In this study, the abundance and diversity of SOB populations were investigated in four Qinghai-Tibetan lakes (Erhai Lake, Gahai Lake 1, Gahai Lake 2 and Xiaochaidan Lake) by using quantitative polymerase chain reaction (qPCR) and soxB gene- (encoding sulfate thiohydrolase) based phylogenectic analyses. qPCR analyses showed that in the studied lakes, the total bacterial 16S rRNA and soxB gene abundances in the sediments were distinctly higher than in the overlying waters. The 16S rRNA gene abundance in the waters ranged 5.27 × 106–6.09 × 108 copies per mL and 7.39 × 1010–2.9 × 1011 copies per gram sediment. The soxB gene abundance in the waters ranged from 1.88 × 104 to 5.21 × 105 per mL and 4.73 × 106–2.65 × 107 copies per gram sediment. The soxB gene in the waters of the two hypersaline lakes (Gahai Lake 2 and Xiaochaidan Lake) was more abundant (2.97 × 105 and 5.21 × 105 copies per mL) than that in the two low-salinity lakes (1.88 × 104 and 3.36 × 104 copies per mL). Phylogenetic analysis showed that Alpha- and Betaproteobacteria were dominant SOB in the investigated lakes, and the composition of proteobacterial subgroups varied with salinity: in freshwater Erhai Lake and low-salinity Gahai Lake 1, the SOB populations were dominated by the Betaproteobacteria, whereas in hypersaline Lake Gahai 2 and Xiaochaidan Lake, the SOB populations were dominated by Alphaproteobacteria. Overall, salinity played a key role in controlling the diversity and distribution of SOB populations in the investigated Qinghai-Tibetan lakes.
Efficient Betweenness Based Content Caching and Delivery Strategy in Wireless Networks

In this letter, we propose a content caching and delivery strategy to maximize throughput capacity in cache-enabled wireless networks. To this end, efficient betweenness (EB), which indicates the ratio of content delivery paths passing through a node, is first defined to capture the impact of content caching and delivery on network traffic load distribution. Aided by EB, throughput capacity is shown to be upper bounded by the minimal ratio of successful delivery probability (SDP) to EB among all nodes. Through effectively matching nodes’ EB with their SDP, the proposed strategy improves throughput capacity with low computation complexity. Simulation results show that the gap between the proposed strategy and the optimal one (obtained through exhausted search) is kept smaller than 6%.
Multi-Task Network for Noise-Robust Keyword Spotting and Speaker Verification using CTC-based Soft VAD and Global Query Attention

Keyword spotting (KWS) and speaker verification (SV) have been studied independently although it is known that acoustic and speaker domains are complementary. In this paper, we propose a multi-task network that performs KWS and SV simultaneously to fully utilize the interrelated domain information. The multi-task network tightly combines sub-networks aiming at performance improvement in challenging conditions such as noisy environments, open-vocabulary KWS, and short-duration SV, by introducing novel techniques of connectionist temporal classification (CTC)-based soft voice activity detection (VAD) and global query attention. Frame-level acoustic and speaker information is integrated with phonetically originated weights so that forms a word-level global representation. Then it is used for the aggregation of feature vectors to generate discriminative embeddings. Our proposed approach shows 4.06% and 26.71% relative improvements in equal error rate (EER) compared to the baselines for both tasks. We also present a visualization example and results of ablation experiments.
The role of environment on quenching, star formation and AGN activity

Abstract Galaxies undergoing ram pressure stripping in clusters are an excellent opportunity to study the effects of environment on both the AGN and the star formation activity. We report here on the most recent results from the GASP survey. We discuss the AGN-ram pressure stripping connection and some evidence for AGN feedback in stripped galaxies. We then focus on the star formation activity, both in the disks and the tails of these galaxies, and conclude drawing a picture of the relation between multi-phase gas and star formation.
Where Am I Looking At? Joint Location and Orientation Estimation by Cross-View Matching

Cross-view geo-localization is the problem of estimating the position and orientation (latitude, longitude and azimuth angle) of a camera at ground level given a large-scale database of geo-tagged aerial (eg., satellite) images. Existing approaches treat the task as a pure location estimation problem by learning discriminative feature descriptors, but neglect orientation alignment. It is well-recognized that knowing the orientation between ground and aerial images can significantly reduce matching ambiguity between these two views, especially when the ground-level images have a limited Field of View (FoV) instead of a full field-of-view panorama. Therefore, we design a Dynamic Similarity Matching network to estimate cross-view orientation alignment during localization. In particular, we address the cross-view domain gap by applying a polar transform to the aerial images to approximately align the images up to an unknown azimuth angle. Then, a two-stream convolutional network is used to learn deep features from the ground and polar-transformed aerial images. Finally, we obtain the orientation by computing the correlation between cross-view features, which also provides a more accurate measure of feature similarity, improving location recall. Experiments on standard datasets demonstrate that our method significantly improves state-of-the-art performance. Remarkably, we improve the top-1 location recall rate on the CVUSA dataset by a factor of 1.5x for panoramas with known orientation, by a factor of 3.3x for panoramas with unknown orientation, and by a factor of 6x for 180-degree FoV images with unknown orientation.
A brief note on the second fundamental form of the variation of Hodge structure of a smooth projective hypersurface

We determine the second fundamental form of a variation of Hodge Structure of a smooth projective hypersurface using the classical identification of the Hodge structure and the action of the infinitesimal variation of Hodge structure with pieces of the Jacobian Ideal of the hypersurface. This simple algebraic description also implies that, in this case, the variation of Hodge structure satisfies a new set of second order partial differential equations.Comments are welcome!
Ball possession dynamics in the game of Football: From data analysis to modeling

Collective dynamics studies of team sports such as football is a hard task involving large amounts of data and analysis. In this contribution we aim to address a particular subject of this broad field such as the dynamics of the ball possession intervals. To this end we have analyzed a novel football database comprising one season of the five major leagues of Europe. First we obtained the key elements of ball possession dynamics from a statistical analysis of the database. Using this input we developed a simple stochastic model based on three agents, two teammates, and one defender. This model includes four parameters and can capture the main emergent statistical observables of the ball possession intervals in the database: the distribution of (i) possession time, (ii) the number of passes performed, and (iii) the ball distance traveled on passes. In the last part, we show that the dynamics of the model, can be mapped into a Wiener process with a drift and an absorbing barrier.
Choose Your Own Question: Encouraging Self-Personalization in Learning Path Construction

Learning Path Recommendation is the heart of adaptive learning, the educational paradigm of an Interactive Educational System (IES) providing a personalized learning experience based on the student's history of learning activities. In typical existing IESs, the student must fully consume a recommended learning item to be provided a new recommendation. This workflow comes with several limitations. For example, there is no opportunity for the student to give feedback on the choice of learning items made by the IES. Furthermore, the mechanism by which the choice is made is opaque to the student, limiting the student's ability to track their learning. To this end, we introduce Rocket, a Tinder-like User Interface for a general class of IESs. Rocket provides a visual representation of Artificial Intelligence (AI)-extracted features of learning materials, allowing the student to quickly decide whether the material meets their needs. The student can choose between engaging with the material and receiving a new recommendation by swiping or tapping. Rocket offers the following potential improvements for IES User Interfaces: First, Rocket enhances the explainability of IES recommendations by showing students a visual summary of the meaningful AI-extracted features used in the decision-making process. Second, Rocket enables self-personalization of the learning experience by leveraging the students' knowledge of their own abilities and needs. Finally, Rocket provides students with fine-grained information on their learning path, giving them an avenue to assess their own skills and track their learning progress. We present the source code of Rocket, in which we emphasize the independence and extensibility of each component, and make it publicly available for all purposes.
High-Dimensional Inference Based on the Leave-One-Covariate-Out LASSO Path.

We propose a new measure of variable importance in high-dimensional regression based on the change in the LASSO solution path when one covariate is left out. The proposed procedure provides a novel way to calculate variable importance and conduct variable screening. In addition, our procedure allows for the construction of P-values for testing whether each coefficient is equal to zero as well as for testing hypotheses involving multiple regression coefficients simultaneously; bootstrap techniques are used to construct the null distribution. For low-dimensional linear models, our method can achieve higher power than the $t$-test. Extensive simulations are provided to show the effectiveness of our method. In the high-dimensional setting, our proposed solution path based test achieves greater power than some other recently developed high-dimensional inference methods.