Miracle-dz/UniFAR-FTUs huggingface dataset:
Some results following from the properties of Weyl families of transformed boundary pairs

We study characteristics, as well as some implications caused by them, of Weyl families corresponding to the transformed isometric/(essentially) unitary boundary pairs $(\mathfrak{L},\Gamma)$. A linear relation $\Gamma$ is assumed to be transformed according to $\Gamma\to\Gamma V$ or $\Gamma\to V\Gamma$ with an isometric/unitary linear relation $V$ between Krein spaces.
Is SGD a Bayesian sampler? Well, almost

Overparameterised deep neural networks (DNNs) are highly expressive and so can, in principle, generate almost any function that fits a training dataset with zero error. The vast majority of these functions will perform poorly on unseen data, and yet in practice DNNs often generalise remarkably well. This success suggests that a trained DNN must have a strong inductive bias towards functions with low generalisation error. Here we empirically investigate this inductive bias by calculating, for a range of architectures and datasets, the probability $P_{SGD}(f\mid S)$ that an overparameterised DNN, trained with stochastic gradient descent (SGD) or one of its variants, converges on a function $f$ consistent with a training set $S$. We also use Gaussian processes to estimate the Bayesian posterior probability $P_B(f\mid S)$ that the DNN expresses $f$ upon random sampling of its parameters, conditioned on $S$. Our main findings are that $P_{SGD}(f\mid S)$ correlates remarkably well with $P_B(f\mid S)$ and that $P_B(f\mid S)$ is strongly biased towards low-error and low complexity functions. These results imply that strong inductive bias in the parameter-function map (which determines $P_B(f\mid S)$), rather than a special property of SGD, is the primary explanation for why DNNs generalise so well in the overparameterised regime. While our results suggest that the Bayesian posterior $P_B(f\mid S)$ is the first order determinant of $P_{SGD}(f\mid S)$, there remain second order differences that are sensitive to hyperparameter tuning. A function probability picture, based on $P_{SGD}(f\mid S)$ and/or $P_B(f\mid S)$, can shed new light on the way that variations in architecture or hyperparameter settings such as batch size, learning rate, and optimiser choice, affect DNN performance.
THE WATER RELATIONS AND IRRIGATION REQUIREMENTS OF OLIVE (Olea europaea L.): A REVIEW

SUMMARY The results of research on the water relations and irrigation needs of olive are collated and summarised in an attempt to link fundamental studies on crop physiology to irrigation practices. Background information on the ecology of the olive (it is native to the coastal areas of the eastern Mediterranean) and on crop development processes are presented, followed by reviews of the influence of water stress on gas exchange (stomatal conductance, photosynthesis and transpiration), crop water requirements, water productivities and irrigation systems. The olive has many attributes that help to protect it against drought, including the morphology of the leaf, and the capacity to conserve water under conditions of high evaporative demand through stomatal closure, osmotic regulation and resistance to cavitation. The concept of ‘deficit irrigation’ has been the subject of much research. Although vegetative growth is restricted, there is no convincing evidence that ‘sustained deficit irrigation’ or ‘regulated deficit irrigation’ or ‘partial root zone drying’ offer any advantages over conventional practices. Water productivities are very variable and difficult to reconcile due, in part, to biennial bearing, tree-to-tree variability and differences in tree population densities. Similarly, no clear consensus has emerged on how best to exploit the sensitivity of trunk expansion to water availability in irrigation scheduling. As production methods for this historical crop are intensified (high-density hedgerows, irrigated and mechanized orchards), so will the need to understand the role that water plays in the production processes become ever more critical.
Clinical profile of patients of fungal keratitis presenting to the tertiary health care centre

Purpose To study the clinical profile of patients of fungal keratitis presenting to the tertiary health care centre. MethodsThis was a prospective observational study that involved 100 eyes of 50 patients with fungal keratitis complaining of foreign body sensation ,pain ,blurring of vision ,redness , itching ,watering ,photophobia. Diagnostic tests were done in all the patients. Results-There were 34 males and 16 females and the age group taken was 30 to 75 years. 14 patients belonged to the age group of 30 to 45 years, out of which 10 were males and 4 were females. 28 patients belonged to age group of 46 to 60 years, out of which 22 were males and 6 were females. 8 patients belonged to the age group of 61 to 75 years , out of which 6 were males and 2 were females. Most common presentation in fungal keratitis patients is foreign body sensation in 72% patients followed by blurring of vision in 66% patients , pain in 55% patients , redness in 48% patients ,itching in 44% patients , watering in 38% patients and photophobia in 32% patients. Majority of patients belong to low socioeconomic class . Most of the patients presented in monsoon season from july to September. The most common risk factor was trauma with vegetative matter followed by ocular surgery , contact lens users , topical steroid users and immunocompromised states like diabetes mellitus . Predominant fungal isolate was Aspergillus spp. followed by Fusarium, candida, and curvullaria spp. Conclusion Fungal keratitis is a common form of ocular disease and tends to occur more commonly in males of 46 to 60 years age group that is males working in farms. Most common presentation of fungal keratitis is foreign body sensation and blurring of vision followed by pain, redness, itching, watering and photophobia and signs include dry feathery corneal ulcer ,hypopyon, satellite lesions, sloughing ulcer and in some cases impending perforation. Most common organism isolated was Aspegillus followed by fusarium and candida.
Optical and near-infrared observations of the SPT2349-56 proto-cluster core at z = 4.3

We present Gemini-S and Spitzer-IRAC optical-through-near-IR observations in the field of the SPT2349-56 proto-cluster at z = 4.3. We detect optical/IR counterparts for only 9 of the 14 submillimetre galaxies (SMGs) previously identified by ALMA in the core of SPT2349-56. In addition, we detect four z ∼ 4 Lyman-break galaxies (LBGs) in the 30 arcsec-diameter region surrounding this proto-cluster core. Three of the four LBGs are new systems, while one appears to be a counterpart of one of the nine observed SMGs. We identify a candidate brightest cluster galaxy (BCG) with a stellar mass of $(3.2^{+2.3}_{-1.4})\times 10^{11}$ M⊙. The stellar masses of the eight other SMGs place them on, above, and below the main sequence of star formation at z ≈ 4.5. The cumulative stellar mass for the SPT2349-56 core is at least (12.2 ± 2.8) × 1011 M⊙, a sizeable fraction of the stellar mass in local BCGs, and close to the universal baryon fraction (0.19) relative to the virial mass of the core (1013 M⊙). As all 14 of these SMGs are destined to quickly merge, we conclude that the proto-cluster core has already developed a significant stellar mass at this early stage, comparable to z = 1 BCGs. Importantly, we also find that the SPT2349-56 core structure would be difficult to uncover in optical surveys, with none of the ALMA sources being easily identifiable or constrained through g, r, and i colour selection in deep optical surveys and only a modest overdensity of LBGs over the more extended structure. SPT2349-56 therefore represents a truly dust-obscured phase of a massive cluster core under formation.
Blast-wave description of 
Υ
 elliptic flow at energies available at the CERN Large Hadron Collider

A simultaneous blast-wave fit to particle yields and elliptic flow ($v_{2}$) measured as a function of transverse momentum in Pb-Pb collisions at LHC energies is presented. A compact formula for the calculation of $v_2(p_T)$ for an elliptic freeze-out surface is used which follows from the Cooper-Frye ansatz without further assumptions. Over the full available $p_T$ range, the $\Upsilon$ elliptic flow data is described by the prediction based on the fit to lighter particles. This prediction shows that, due to the large $\Upsilon$ mass, a sizable elliptic flow is only expected at transverse momenta above 10 GeV/$c$.
Object Files and Schemata: Factorizing Declarative and Procedural Knowledge in Dynamical Systems

Modeling a structured, dynamic environment like a video game requires keeping track of the objects and their states (\emph{declarative} knowledge) as well as predicting how objects behave (\emph{procedural} knowledge). Black-box models with a monolithic hidden state often lack \emph{systematicity}: they fail to apply procedural knowledge consistently and uniformly. For example, in a video game, correct prediction of one enemy's trajectory does not ensure correct prediction of another's. We address this issue via an architecture that factorizes declarative and procedural knowledge and that imposes modularity within each form of knowledge. The architecture consists of active modules called \emph{object files} that maintain the state of a single object and invoke passive external knowledge sources called \emph{schemata} that prescribe state updates. To use a video game as an illustration, two enemies of the same type will share schemata but will each have their own object file to encode their distinct state (e.g., health, position). We propose to use attention to control the determination of which object files to update, the selection of schemata, and the propagation of information between object files. The resulting architecture is a drop-in replacement conforming to the same input-output interface as normal recurrent networks (e.g., LSTM, GRU) yet achieves substantially better generalization on environments that have factorized declarative and procedural knowledge, including a challenging intuitive physics benchmark.
Reaction Rate Sensitivity of the Production of γ-Ray Emitting Isotopes in Core-collapse Supernovae

Radioactive isotopes produced in core-collapse supernovae (CCSNe) provide useful insights into the underlying processes driving the collapse mechanism and the origins of elemental abundances. Their study generates a confluence of major physics research, including experimental measurements of nuclear reaction rates, astrophysical modeling, and γ-ray observations. Here we identify the key nuclear reaction rates to the nucleosynthesis of observable radioactive isotopes in explosive silicon burning during CCSNe. Using the nuclear reaction network calculator SkyNet and current REACLIB reaction rates, we evolve temperature–density–time profiles of the innermost 0.45 M ⊙ ejecta from the core collapse and explosion of a 12 M ⊙ star. Individually varying 3403 reaction rates by factors of 100, we identify 141 reactions that cause significant differences in the isotopes of interest, namely, 43K, 47Ca, 44,47Sc, 44Ti, 48,51Cr, 48,49V, 52,53Mn, 55,59Fe, 56,57Co, and 56,57,59Ni. For each of these reactions, we present a novel method to extract the temperature range pertinent to the nucleosynthesis of the relevant isotope; the resulting temperatures lie within the range T = 0.47–6.15 GK. Limiting the variations to within 1σ of STARLIB reaction rate uncertainties further reduces the identified reactions to 48 key rates, which can be used to guide future experimental research. Complete results are presented in tabular form.
Multiband GPI Imaging of the HR 4796A Debris Disk

We have obtained Gemini Planet Imager (GPI) J-, H-, K1-, and K2-Spec observations of the iconic debris ring around the young, main-sequence star HR 4796A. We applied several point-spread function (PSF) subtraction techniques to the observations (Mask-and-Interpolate, RDI-NMF, RDI-KLIP, and ADI-KLIP) to measure the geometric parameters and the scattering phase function for the disk. To understand the systematic errors associated with PSF subtraction, we also forward-modeled the observations using a Markov Chain Monte Carlo framework and a simple model for the disk. We found that measurements of the disk geometric parameters were robust, with all of our analyses yielding consistent results; however, measurements of the scattering phase function were challenging to reconstruct from PSF-subtracted images, despite extensive testing. As a result, we estimated the scattering phase function using disk modeling. We searched for a dependence of the scattering phase function with respect to the GPI filters but found none. We compared the H-band scattering phase function with that measured by Hubble Space Telescope STIS at visual wavelengths and discovered a blue color at small scattering angles and a red color at large scattering angles, consistent with predictions and laboratory measurements of large grains. Finally, we successfully modeled the SPHERE H2 HR 4796A scattered phase function using a distribution of hollow spheres composed of silicates, carbon, and metallic iron.
Video Representation Learning with Visual Tempo Consistency

Visual tempo, which describes how fast an action goes, has shown its potential in supervised action recognition. In this work, we demonstrate that visual tempo can also serve as a self-supervision signal for video representation learning. We propose to maximize the mutual information between representations of slow and fast videos via hierarchical contrastive learning (VTHCL). Specifically, by sampling the same instance at slow and fast frame rates respectively, we can obtain slow and fast video frames which share the same semantics but contain different visual tempos. Video representations learned from VTHCL achieve the competitive performances under the self-supervision evaluation protocol for action recognition on UCF-101 (82.1\%) and HMDB-51 (49.2\%). Moreover, comprehensive experiments suggest that the learned representations are generalized well to other downstream tasks including action detection on AVA and action anticipation on Epic-Kitchen. Finally, we propose Instance Correspondence Map (ICM) to visualize the shared semantics captured by contrastive learning.
New Species and Redescriptions in the Central-Western Pacific Subgenus Inseliellum (Diptera: Simuliidae)

Abstract Complete redescriptions of S. trukense Stone and S. guamense Stone (subgenus Inseliellum Rubtsov) are made based on new material from Micronesia. Holotypes of S. arlecchinum Craig and S. admixtum Craig have been reexamined and new morphological details provided as they are for some other species. Seven new species are described: S. caesariatum, S. fararae, S. hispidum, S. hirticranium, S. joyae, S. pallidicranium, and S. pseudocorium. A new hirticranium subgroup within the castaneum-group, which includes S. pallidicranium, S. hirticranium, S. hispidum, and S. caesariatum, is defined on the basis of numerous elongate cephalic setae and smooth abdominal cuticle in the larvae. Simulium fararae and S. joyae are placed in the castaneum-group and S. pseudocorium in the tahitiense-group. A total of 48 species is now recognized for Inseliellum. Brief comments are made concerning larval habitats, biology, relationships within Inseliellum, and problems with homoplasy.
Role of isolation and habitat quality in shaping species abundance: a test with badgers (Meles meles L.) in a gradient of forest fragmentation

This paper describes badger (Meles meles L. 1758) abundance in remnant forests of the two Iberian plateaux. The relative role of factors related to habitat quality and to isolation were tested in order to explain variations in badger abundance according to forest‐scrubland cover at the landscape scale. It was predicted that isolation would be more important where there is less forest cover (greater fragmentation), while habitat quality would predominate in areas where forest cover is greater (less fragmentation).
Cutting Edge: TCR δ Gene Is Frequently Rearranged in Adult B Lymphocytes 1

TCR gene rearrangement generates diversity of T lymphocytes by V(D)J recombination. Ig genes are rearranged in B cells using the same enzyme machinery. Physiologically, TCR gene is postulated to rearrange exclusively in T lineage, but malignant B precursor lymphoblasts contain rearranged TCR genes in most patients. Several mechanisms by which malignant cells break the regulation of V(D)J recombination have been proposed. In this study we show that incomplete TCR δ rearrangements V2-D3 and D2-D3 occur each in up to 16% alleles in B lymphocytes of all healthy donors studied, but complete VDJ rearrangement was negative at the sensitivity limit of 1%. Data are based on real-time quantitative PCR validated by PAGE and sequencing of the cloned products. Therefore, TCR genes rearrange not exclusively in T lineage. This study opens up further questions regarding the exact extent of the “cross-lineage” TCR or Ig rearrangements in normal lymphocytes, specific subsets in which the cross-lineage rearrangements occur, and the physiological importance of these rearrangements.
Parameter-free renormalization group theory of the order-disorder phase transition in $\beta$-brass

A self-consistent (SC) renormalization group approach analogous to the coherent potential approximation (CPA) in the band structure theory of disordered alloys has been developed. With the use of generalized CPA techniques a renormalization group equation in the local potential approximation (LPA) derived previously for spatially homogeneous systems has been extended to the lattice case and supplemented with a CPA-like self-consistency condition. To validate the approach it has been applied to the simple cubic Ising model and good agreement of the spontaneous magnetization calculated with the use of the SC-LPA equation with the available exact Monte Carlo simulations data has been established. Then the approach has been applied to the bcc Ising model corresponding to $\beta$-brass. With the use of the effective pair interaction values from available {\em ab initio} calculations the critical temperature, the correlation length and the long range order parameter in the vicinity of the critical point have been calculated in excellent agreement with experimental data. Quantitative arguments have been given in support of the suggestion that the experimentally observed large decrease of the effective critical exponent of the order parameter in comparison with its universal value is enhanced by the positive value of the second neighbour pair interaction found in the {\em ab initio} calculations.
Compositional Video Synthesis with Action Graphs

Videos of actions are complex spatio-temporal signals, containing rich compositional structures. Current generative models are limited in their ability to generate examples of object configurations outside the range they were trained on. Towards this end, we introduce a generative model (AG2Vid) based on Action Graphs, a natural and convenient structure that represents the dynamics of actions between objects over time. Our AG2Vid model disentangles appearance and position features, allowing for more accurate generation. AG2Vid is evaluated on the CATER and Something-Something datasets and outperforms other baselines. Finally, we show how Action Graphs can be used for generating novel compositions of unseen actions.
Community Structure aware Embedding of Nodes in a Network

Detecting communities or the modular structure of real-life networks (e.g. a social network or a product purchase network) is an important task because the way a network functions is often determined by its communities. Traditional approaches to community detection involve modularity-based algorithms, which generally speaking, construct partitions based on heuristics that seek to maximize the ratio of the edges within the partitions to those between them. On the other hand, node embedding approaches represent each node in a graph as a real-valued vector and is thereby able to transform the problem of community detection in a graph to that of clustering a set of vectors. Existing node embedding approaches are primarily based on, first, initiating random walks from each node to construct a context of a node, and then make the vector representation of a node close to its context. However, standard node embedding approaches do not directly take into account the community structure of a network while constructing the context around each node. To alleviate this, we explore two different threads of work. First, we investigate the use of maximum entropy-based random walks to obtain more centrality preserving embedding of nodes, which may lead to more effective clusters in the embedded space. Second, we propose a community structure-aware node embedding approach, where we incorporate modularity-based partitioning heuristics into the objective function of node embedding. We demonstrate that our proposed combination of the combinatorial and the embedding approaches for community detection outperforms a number of modularity-based baselines and K-means clustering on a standard node-embedded (node2vec) vector space on a wide range of real-life and synthetic networks of different sizes and densities.
Maternal effects in Daphnia: what mothers are telling their offspring and do they listen?

Maternal effects can significantly impact offspring performance. Provisioning of offspring with energy stores can quantitatively alter their growth rates, survivorship, and future fecundity, and influence population regulatory mechanisms. In this paper, we show that maternal effects can also qualitatively affect offspring reproduction (i.e. their mode of reproduction). The freshwater herbivore Daphnia pulex can change the amount of energy allocated between asexual and ephippial egg production. Our experiments on individuals, experiencing “step-up” or “step-down” food manipulations, reveal that offspring qualitatively shift their energy allocation away from asexual reproduction to ephippial egg production when there is a simple mismatch between maternal and offspring food environments. We show that the response is asymmetric with respect to changes in food level, ephippial egg production is higher with a greater mismatch between environments, and that the effect can be observed in dynamic experimental populations. These results point to a “generational memory” that could challenge our interpretation of field patterns and mechanisms influencing population dynamics in Daphnia–algal systems.
Spotlight counts, site fidelity and migration of European rabbits (Oryctolagus cuniculus)

Regardless of their sex and age, the persistence of 76 rabbits (Oryctolagus cuniculus) translocated onto 5 different sites with relatively low rabbit densities was identical to that of resident rabbits. Emigration and exploratory movements by rabbits from 12 discrete populations were positively correlated with rabbit density and mainly undertaken by adult rabbits. Adult males moved significantly more often and further than adult females. Two peaks in immigration were observed; a large peak (usually in January) immediately following the breeding season, and a second but smaller peak in March which preceded the start of the next breeding season. Again, significantly more adult males than females immigrated. The proportion of rabbits seen in spotlight counts was positively correlated with rabbit density, which suggests that biases in population estimates could result in some situations. No clear patterns on the effects of a variety of weather variables on spotlight counts could be established, but increasing rainfall, wind speed and moonlight may have reduced rabbit activity.
Vocalizaciones del nandu comun rhea americana ( aves : rheidae ) en argentina

Las especies, altamente sociales poseen un sistema complejo de comunicacion vocal (Martella y Bucher 1990). Las vocalizaciones de los nandues muy pocas veces han sido citadas . en la literatura; se sabe, que son semejantes a mugidos de ganado vacuno, que coinciden o preceden a la formacion de harenes y que pueden ser escuchadas a gran distancia