Miracle-dz/UniFAR-FTUs huggingface dataset:
New Perspectives to Study the Biomass Allocation and its Relationship with the Functioning of Plants in Neotropical Ecosystems

RESUMEN Como responden las plantas a la variabilidad en la disponibilidad de los recursosabioticos, es un tema central en estudios de fisiologia ecologica. Varios modelos departicion optima han sugerido un balance funcional en la biomasa asignada al vas-tago y la raiz con la siguienteprediccion: “las plantas cambiarian su asignacion debiomasa hacia el vastago si la ganancia de carbono de la parte aerea de la planta esafectada por un nivel bajo de r ecursos sobre el suelo, tal como luz o CO 2 . Igualmente,las plantas cambiarian su asignacion hacia la raiz si el nivel de los recursos del sueloes bajo, tal como nutrientes y agua”. Estos cambios en la asignacion pueden ser con-siderados como adaptativos, ya que permiten a la planta capturar mas de aquel re-curso que limitafuertemente su crecimiento. En este trabajo, discutimos algunosesquemas metodologicos que a traves de la descripcion y analisis de la asignacion debiomasa pretenden probar dicha prediccion. Enfatizamos que la conclusion extraidaen contra o a favor de la prediccion se fundamenta en la interpretacion del terminoplasticidad, conllevando recientemente al uso de metodologias que sugieren que laprediccion no se cumple en respuesta a la disponibilidad de algunos recursos. Propo-nemos la utilizacion de un protocolo de investigacion para estudiar los patrones deasignacion de biomasa y sugerimos una metodologia para cuantificar la plasticidadde diferentes genotipos desde un punto de vista discreto.
Faster algorithms for sampling connected induced subgraphs

We consider the problem of sampling connected induced $k$-node subgraphs ($k$-graphlets) uniformly at random from a given graph $G=(V,E)$. The best algorithms known achieve $\epsilon$-uniformity and are based on random walks or color coding. The random walk approach has a worst-case running time of $\Delta^{\! \Theta(k)}\log\frac{n}{\epsilon}$ where $n=|V|$ and $\Delta$ is the maximum degree of $G$, while color coding requires a preprocessing that takes time and space $2^{\Theta(k)}O(m \log\frac{1}{\epsilon})$ where $m=|E|$. Our main result is an algorithm for $\epsilon$-uniform sampling with the following guarantees. The preprocessing runs in time $k^{O(k)}O\big(\frac{1}{\epsilon}\, n \log n \big)$ and space $O(n)$. After, the algorithm yields independent $\epsilon$-uniform $k$-graphlets in $k^{{O}(k)}{O}\big((\frac{1}{\epsilon})^{10}\log \frac{1}{\epsilon} \big)$ expected time per sample. The preprocessing phase computes in one pass an approximate ordering of $G$ that makes rejection sampling efficient in the sampling phase, and the $\epsilon$-uniformity is based on estimating cuts and coupling arguments. In fact, the algorithm derives from a much simpler algorithm which has ${O}(m \log \Delta)$ preprocessing time and returns perfectly uniform $k$-graphlets from $G$ in $k^{{O}(k)}{O}(\log \Delta)$ expected time per sample. In addition, we give an almost-tight bound for the random walk technique. More precisely, we show that the most commonly used random walk has mixing time $k^{{O}(k)} {O}(t(G)(\frac{\Delta}{\delta})^{k-1}\! \log n)$ where $t(G)$ is the mixing time of $G$ and $\delta$ is its minimum degree. This improves on recent results and is tight up to a factor $k^{{O}(k)} \delta \log n$.
Hayvan Hakları ve Hayvan Refahı: Felsefi Bakış - Nesnel Arayışlar

The effort of human to systemize his view for animal has a long history. Domestication as a meaning of commitment to survive is one of the most crucial milestones in this period. On the other hand, it is not difficult to predict that the description of mananimal relation with the perception that animals share this planet with humans can lead to a complex philosophical argument. In this regard, it can be put forward that the questioning of the sensibility to animal welfare is an argument at philosophical level, whereas the provision and control of animal welfare conditions is a pursuit at scientific level. The argument and the application areas largely support each other. Many factors play important roles in the perception of constitutional regulations on animal welfare as a public agreement document. Social and cultural achievements, ethical values and welfare level are the main factors. This study aimed at analyzing the different responses to the question of “What is animal welfare? ” in the light of historical development of efforts on systemizing man-animal relation. Possible impacts of man-animal relation in an industrial period on animal welfare approaches and scientific efforts towards objective description and determination of animal welfare were also dealt with in the present study.
Hierarchical Prediction Based on Network-Representation-Learning-Enhanced Clustering for Bike-Sharing System in Smart City

The sharing bike system is emerging as a new type of transportation with the advance of the smart city in recent years. More and more people will choose to ride a sharing bicycle for short-distance travel. While sharing bikes provide convenient services to customers, there are also many unfavorable factors in the sharing bike system, which have a certain impact on the riding experience of customers. One of the obvious disadvantages is the imbalance of usage because of the abnormal distribution of sharing bike stations in different areas. Despite some prediction work have been done, most of them merely consider the geographical factors between station whereas the user preferences and global network information are not fully considered. In this work, we propose a hierarchical model for sharing bike prediction, which can predict the number of rents/returns of each sharing bike station in the future to achieve resource redistribution. The proposed model is composed of two steps, including the sharing bike station clustering via network representation learning by considering the migration trends and geographic location information of bike-sharing between station. In the hierarchical prediction step, the total number of all bike-sharing station is predicted with an inference model based on multiple similarities. Finally, the number of rents/returns at each station can be derived. Our method is evaluated based on two publicly available sharing data sets by comparison with several baseline methods. Extensive experimental results on two open sharing bike data sets demonstrate that our proposed hierarchical can achieve the best prediction results. Our proposed method has a 17.34% improvement in root-mean-squared logarithmic error and a 10.4% improvement in return prediction.
Feeding and Oviposition Behaviour of Trioza erytreae (Hemiptera: Triozidae) on Different Citrus Rootstock Material Available in Europe

Simple Summary The Mediterranean Basin is the second largest citrus-producing region in the world. Huanglongbing (HLB) is the most important and devastating citrus disease worldwide, the causal agents of which are three bacteria species that belong to the genus Candidatus Liberibacter. The main transmission of these three bacteria is by two psyllid vectors, Diaphorina citri and Trioza erytreae. Trioza erytreae is a specific pest of plants from the Rutaceae family, which includes cultivated citrus. This insect has recently been detected in Mediterranean Basin countries, such as Spain and Portugal, but none of the causal agents of HLB have been described as infecting citrus plants in this region. The potential risk of HLB emergence has increased concern in the Spanish and Portuguese citrus industries, which require novel methods for controlling/eradicating populations of T. erytreae that are environmentally sound under new pesticide restrictions from European Union authorities. Hence, psyllid rootstock feeding preferences could play an important role in pest management. Thus, different citrus rootstocks have been tested for feeding, oviposition, and survival of T. erytreae. This study reports that the most commonly used citrus rootstocks (Carrizo citrange and Citrus macrophylla) are the favorite choices for the development of T. erytreae, and by contrast Poncirus trifoliata is the least suitable for this insect vector. Abstract Trioza erytreae (Del Guercio, 1918) (Hemiptera: Triozidae) is a vector of Candidatus Liberibacter spp. , the causal agent of Huanglongbing disease (HLB). This study evaluates the preference of T. erytreae in different citrus seedlings. Thus, six different non-grafted citrus rootstocks were used for these experiments: (a) Carrizo citrange; (b) Citrus macrophylla; (c) ‘Cleopatra’ mandarin; (d) Forner-Alcaide No. 5; (e) Forner-Alcaide No. 517, and (f) Poncirus trifoliata (‘Flying Dragon’). The behaviour and survival of this psyllid was evaluated through the feeding preference of T. erytreae adults for different rootstocks (in a choice trial under greenhouse conditions) and oviposition and survival of T. erytreae adults on the different citrus material (in a no-choice trial under laboratory conditions). Trioza erytreae showed a clear preference for hosting and feeding on C. macrophylla, and Carrizo citrange was the most suitable rootstock for insect reproduction and survival followed by C. macrophylla. Conversely, Poncirus trifoliata was the least attractive rootstock to T. erytreae adults in the greenhouse trial and led to significantly lower T. erytreae survival. Our results suggest that conventional citrus rootstocks, such as Carrizo citrange and C. macrophylla, could increase T. erytreae populations.
The lizard (Reptilia, Squamata) assemblage from the Paleocene of Montchenot (Paris Basin, MP6)

ABSTRACT Here we describe the lizard fauna from the locality of Montchenot (Paris Basin, late Paleocene, MP6). This material can be allocated to five major clades: Scincoidea, Lacertoidea (? Lacertidae), Amphisbaenia, Anguimorpha (? Anguidae and Shinisauridae). The assemblage from Monchenot is dominated by small lizard specimens and appears as highly sorted. Predation could produce such biased assemblages. The composition of the lizard fauna from Monchenot is rather similar to those of Cernay-lès-Reims and Rivecourt, two coeval localities (MP6) in the Paris Basin. However, these faunas sharply contrast (in diversity and composition) with the lizard fauna found in the early Eocene of the same area (Paris Basin and Belgian Basin). These differences highlight the impact of the Paleocene/Eocene transition on the lizard fauna of Europe.
The development of new materials such MOFs for CO2 capture and alkylation of aromatic compounds.

This thesis is a European project TOPCOMBI of 22 partners. More specifically, this work is the result ofcollaboration between ENI (Italy), ITQ (Spain), Repsol (Spain) and IRCELYON (France). This work consists of 2 different themes which improvements can be obtained by finding new materials tailoredto the needs.The global energy demands are and will be constantly rising in the coming years. In order to meet this need,new resources must be found and further optimized. Fossil fuels are among the most used resources in the world. Amongthis 3, natural gas appears to be the most promising point of view of energy efficiency and ecological impact. However,many gas fields cannot be treated because there are too small or too contaminated to be economically viable. One way tomake them attractive is to lower the cost of purification using novel separation techniques such as the PSA system.However, there is no currently effective adsorbent to allow a viable economic cleansing.Today, the alkylation reactions represent a very important economic interest. Industrial processes are typicallycarried out by homogeneous acid reactions or not. Seeing the new environmental restrictions, some homogeneouscatalytic processes must be replaced by heterogeneous catalytic reactions with the same yields. To do this, new materialsto acid characters were used: the zeolites. However the small size of pores of these compounds prevents selectivealkylation reactions of molecules too large compounds such as poly-aromatic.For twenty years, new microporous crystalline compounds have emerged. The MOFs, Metal OrganicFrameworks. These compounds have the characteristic to be obtained with different metal cations and organic ligands.These combinations give a wide variety of these compounds at the level of reactivity, pore volume and pore size. In thiswork, we tried to get different materials with specific characteristics in order to use them in methods for purification ofmethane in acid catalysis. To do this, we have established a protocol for the synthesis of MOFs with high speed and acharacterization protocol suited to our needs. The different compounds fulfilling the various criteria being tested in theappropriate responses.
Efficient Asymmetric photothermal source: Designing a heating Janus-Nanojet

Janus particles have flourished as subject of intensive research due to their synergetic properties and their promising use in different fields, especially in biomedicine. The combination of materials with radically different physical properties in the same nanostructure gives rise to the so-called Janus effects, allowing phenomena of a contrasting nature to occur in the same architecture. In particular, interesting advantages can be taken from a thermal Janus effect for photoinduced hyperthermia cancer therapies. Such therapies still have limitations associated to the heating control in terms of temperature stability and energy management. While previous studies have shown that some plasmonic single-material nanoparticles are somehow effective at killing cancer cells, it is necessary to investigate alternative plasmonic Janus nanoheaters to improve the heating efficiency and thermal control, mainly because the widespread single-material nanoheaters are highly homogeneous sources of heat, which implies that the surrounding biological medium is isotropically heated, equally affecting cancerous and healthy cells. A detailed thermoplasmonic study of the thermal Janus effect is still missing. Here we perform such study and demonstrate that doughnut-based Janus nanoparticles exhibit an outstanding photothermal control under practical illumination conditions, i.e., unpolarized light. Furthermore, we present novel and effective Janus nanoparticle designs that possess superior photothermal conversion features and unique directional heating capacity, being able to channel up to 91% of the total thermal energy onto a target. We discuss the implications of these innovative nanoparticles with regards to thermoplasmonics hyperthermia cancer therapy.
Naturalistic Decision Making in the Air Traffic Control Tower: Combining Approaches to Support Changes in Procedures

ABSTRACT Changes in air traffic control systems and procedures can result in a variety of changes in how controllers coordinate their activities, communicate, and perform their tasks. It is important to anticipate the effects of these changes before they are made, but no single method is adequate to assess all human performance issues. In this paper, we present a trio of complimentary methods to assess a variety of human performance issues and discuss the analytical merits of each. The methods include Cognitive Analysis and Modeling, Critical Incident Analysis, and Controller Coordination Analysis. For each method, we highlight its purpose and outline the product, with specific examples drawn from the domain of air traffic control in the tower environment. Keywords Air Traffic Control, Cognitive Task Analysis, Cognitive Modeling, Coordination Analysis, Critical Incident Analysis, GOMS INTRODUCTION In an effort to alleviate congestion, many airports are seeking means to increase capacity. Such means typically include procedural revisions, the construction or reconfiguration of taxiways, and the construction or reconfiguration of runways. Reconfigurations that entail the construction of new runways and taxiways will almost always require procedural revisions, and they may also entail additional changes, such as the construction of satellite control towers or the reconfiguration of an existing control tower. While such improvements may increase capacity, they may also significantly change air traffic controller decision making and communication. So before such procedural changes are made, it is necessary to predict the effects they will have on air traffic controller performance. Ideally, the new procedures would be evaluated in an interactive air traffic control tower simulator to predict how they will impact performance. However, such simulations are costly and time-consuming to construct and perform. Thus, our goal was to develop a Naturalistic Decision Making methodology that would identify key issues to guide the construction of scenarios for focused evaluation during simulation exercises. To gain a comprehensive understanding of controller decision-making and performance, we present a trio of complimentary approaches, including: the construction of controller cognitive models, an analysis of airport critical incidents, and an analysis of controller coordination. Our selection of methods was guided by the fact that a comprehensive review of air traffic control procedures would require analysis of both routine and non-routine operations (e.g., occasions where errors occurred) and events. Since we identified workload and task completion time as important aspects of controller performance, we determined that cognitive modeling would be a suitable approach. But while cognitive modeling excels at predicting change for routine events, we determined that it would not adequately predict the effects of change in controller performance under non-
Evidence of a Phonon Hall Effect in the Kitaev Spin Liquid Candidate $\alpha$-RuCl$_3$

The material $\alpha$-RuCl$_3$ has been the subject of intense scrutiny as a potential Kitaev quantum spin liquid, predicted to display Majorana fermions as low energy excitations. In practice, $\alpha$-RuCl$_3$ undergoes a transition to a state with antiferromagnetic order below a temperature $T_{\rm N}$ $\approx$ 7 K, but this order can be suppressed by applying an external in-plane magnetic field of $H_\parallel$ = 7 T. Whether a quantum spin liquid phase exists just above that field is still an open question, but the reported observation of a quantized thermal Hall conductivity at $H_\parallel$ $>$ 7 T by Kasahara and co-workers $\big[$Kasahara ${\it et \ al}$. , Nature ${\bf 559}$, 227 (2018)$\big]$ has been interpreted as evidence of itinerant Majorana fermions in the Kitaev quantum spin liquid state. In this study, we re-examine the origin of the thermal Hall conductivity $\kappa_{\rm xy}$ in $\alpha$-RuCl$_3$. Our measurements of $\kappa_{\rm xy}$($T$) on several different crystals yield a temperature dependence very similar to that of the phonon-dominated longitudinal thermal conductivity $\kappa_{\rm xx}$($T$), for which the natural explanation is that $\kappa_{\rm xy}$ is also mostly carried by phonons. Upon cooling, $\kappa_{\rm xx}$ peaks at $T \simeq$ 20 K, then drops until $T_{\rm N}$, whereupon it suddenly increases again. The abrupt increase below $T_{\rm N}$ is attributed to a sudden reduction in the scattering of phonons by low-energy spin fluctuations as these become partially gapped when the system orders. The fact that $\kappa_{\rm xy}$ also increases suddenly below $T_{\rm N}$ is strong evidence that the thermal Hall effect in $\alpha$-RuCl$_3$ is also carried predominantly by phonons. This implies that any quantized signal from Majorana edge modes would have to come on top of a sizable -- and sample-dependent -- phonon background.
DIRECT: Direct and Indirect Responses in Conversational Text Corpus

We create a large-scale dialogue corpus that provides pragmatic paraphrases to advance technology for understanding the underlying intentions of users. While neural conversation models acquire the ability to generate ﬂuent responses through training on a dialogue corpus, previous corpora have mainly focused on the literal meanings of utterances. However, in reality, people do not always present their intentions directly. For example, if a person said to the operator of a reservation service ‘I don’t have enough budget. ’, they, in fact, mean ‘please ﬁnd a cheaper option for me. ’ Our corpus provides a total of 71 , 498 indirect–direct utterance pairs accompanied by a multi-turn dialogue history extracted from the MultiWoZ dataset. In addition, we propose three tasks to benchmark the ability of models to recognize and generate indirect and direct utterances. We also investigated the performance of state-of-the-art pre-trained models as baselines.
Evaluation of Different Feedback Conditions on Worker's Performance in an Augmented Reality-based Support System for Carbon Fiber Reinforced Plastic Manufacturing

Carbon fiber reinforced polymers (CFRP) are materials with excellent mechanical properties. However, slight variations in the manufacturing process lead to substantially decreasing mechanical stability and additional production costs for assuring the product’s quality. For large lot sizes a high process quality can be achieved through automation. However, for small lot sizes manual processes are required, which introduce variances in process quality. To support workers in the manual production however, there is little support to guide them and to reduce the variance in product quality. Augmented Reality (AR) applications are successfully used to offer guidance in other manufacturing processes. Yet, no empirical studies of the applicability of AR to support CFRP processing have been carried out. Therefore we present an AR based prototypic worker support system for CFRP manufacturing. Empirically, the impact of different feedback modalities (none, auditory, visual, auditory+visual) as well as individual factors on effectivity, efficiency and user satisfaction was investigated. Key findings show that combined feedback worked best for accuracy, however no feedback was fastest. Regarding user preferences, auditory followed by auditory+visual feedback was rated best. Taking user preferences and performance into account will provide useful guidelines for the development of a support system.
Few-Shot Image Denoising with Meta-Learning Project Proposal

Image denoising is a topic that has been explored from many different angles, two of the most prominent being learning-based methods and non-learning based methods. Most learning-based methods, like the DnCNN [10] result in de-noised images of much higher quality than non-learning based approaches like non-local means [1] and BM3D [4]. However, most of these learning-based approaches require training on a large number of clean and real noisy image pairs [10], which can be difficult to obtain for certain applications. Many applications may only have access to a few clean and real noisy image pairs, which could lead to overfitting in learning-based approaches. This challenge is usually addressed by constructing large training datasets with clean and noisy image pairs where the noisy image is synthetically generated from the clean image. Specifically, to generate our noisy images, we draw samples from a chosen noise distribution and apply this noise to a clean image [9]. However, training with synthetically generated noisy images does not generalize well in practice due to a lack of fine-tuning during test-time [3, 8]. Furthermore, many of these learning-based models are also trained to denoise for a specific type of noise and fixed amount of noise variance, not making them very generalizable, especially for smaller-sized training sets. For our project, we want to address the above challenges by re-implementing parts of the paper “Few-Shot Meta-Denoising” [3] which applies meta-learning algorithms to learn few-shot image denoising with various noise distributions. We believe the combination of meta-learning and few-shot learning is a good model for the image denoising challenges described above because the model will quickly learn how to denoise images from a few synthetically generated noisy images (using various noise distributions) and use fine-tuning to efficiently adapt to denoising of a small set of real noisy images.