Miracle-dz/UniFAR-FTUs huggingface dataset:
Distributed Stochastic Non-Convex Optimization: Momentum-Based Variance Reduction

In this work, we propose a distributed algorithm for stochastic non-convex optimization. We consider a worker-server architecture where a set of $K$ worker nodes (WNs) in collaboration with a server node (SN) jointly aim to minimize a global, potentially non-convex objective function. The objective function is assumed to be the sum of local objective functions available at each WN, with each node having access to only the stochastic samples of its local objective function. In contrast to the existing approaches, we employ a momentum based "single loop" distributed algorithm which eliminates the need of computing large batch size gradients to achieve variance reduction. We propose two algorithms one with "adaptive" and the other with "non-adaptive" learning rates. We show that the proposed algorithms achieve the optimal computational complexity while attaining linear speedup with the number of WNs. Specifically, the algorithms reach an $\epsilon$-stationary point $x_a$ with $\mathbb{E}\| \nabla f(x_a) \| \leq \tilde{O}(K^{-1/3}T^{-1/2} + K^{-1/3}T^{-1/3})$ in $T$ iterations, thereby requiring $\tilde{O}(K^{-1} \epsilon^{-3})$ gradient computations at each WN. Moreover, our approach does not assume identical data distributions across WNs making the approach general enough for federated learning applications.
Effects of Enzymatic Treatments of Marigold Flowers on Lutein Isomeric Profiles

Reversed-phase C30 HPLC was applied to study the identity of lutein isomers and to monitor the effects of solids content and elimination of water-soluble substances on the isomeric carotenoid profiles of marigold (Tagetes erecta) samples treated with enzymes. The tentative identity of four lutein isomers present in saponified marigold extracts was confirmed. Enzymatic treatment on a 5% solids slurry produced the marigold meal with the highest all-trans-lutein content [25.1 g/kg dry weight (dw)]. We did not observe variations in the distribution in percentage of lutein isomers due to enzymatic treatment; the elimination of water solubles had a significant but small effect on such variations. The solids content was the principal factor that affected the carotenoid profiles. An analysis of the distribution showed that 15% solids gave the highest all-trans-lutein percentage in treated meals. Interestingly, with 20% solids both the degradation of lutein and the percentage of all-trans-zeaxanthin were the highe.
Epitaxial engineering of flat silver fluoride cuprate analogs

As-grown AgF2 has a remarkably similar electronic structure as insulating cuprates, but it is extremely electronegative, which makes it hard to handle and dope. Furthermore, buckling of layers reduces magnetic interactions and enhances unwanted self-trapping lattice effects. We argue that epitaxial engineering can solve all these problems. By using a high throughput approach and first principle computations, we find a set of candidate substrates which can sustain the chemical aggressiveness of AgF2 and at the same time have good lattice parameter matching for heteroepitaxy, enhancing AgF2 magnetic and transport properties and opening the possibility of field-effect carrier injection to achieve a new generation of high-Tc superconductors. Assuming a magnetic mechanism and extrapolating from cuprates we predict that the superconducting critical temperature of a single layer can reach 195 K.
Levitating Rigid Objects with Hidden Support Structures

We propose a novel algorithm to efficiently generate hidden structures to support arrangements of floating rigid objects. Our optimization finds a small set of rods and wires between objects and each other or a supporting surface (e.g., wall or ceiling) that hold all objects in force and torque equilibrium. Our objective function includes a sparsity inducing total volume term and a linear visibility term based on efficiently pre-computed Monte-Carlo integration, to encourage solutions that are as-hidden-as-possible. The resulting optimization is convex and the global optimum can be efficiently recovered via a linear program. Our representation allows for a user-controllable mixture of tension-, compression-, and bending-resistant rods or tension-only wires. We explore applications to theatre set design, museum exhibit curation, and other artistic endeavours.
Efecto de dietas con diferentes proporciones de proteínas y lípidos sobre la respuesta productiva y características de la canal del salmón del Pacífico (Oncorhynchus kisutch)

Los objetivos del presente trabajo fueron evaluar la respuesta productiva, las caracteristicas de la canal y costo alimentario de cada kilo de peso ganado por salmones coho alimentados con diferentes proporciones de proteina/lipidos en sus dietas durante su etapa de engorda final. Se emplearon 3.300 salmones coho asignados al azar a tres tratamientos con dos repeticiones cada uno. Los peces del tratamiento 1 (control) recibieron una dieta con 45% de proteina y 22% de lipidos (P/L 2.04); los del tratamiento 2, una dieta que contenia 43% de proteina y 26% de lipidos (P/L 1.65), y los del tratamiento 3, una dieta con 40% proteina y 30% lipidos (P/L 1.33). La respuesta productiva fue evaluada considerando peso promedio, consumo de alimento, ganancia de peso, eficiencia de conversion alimenticia y tasa de crecimiento especifico. Las caracteristicas de la canal fueron evaluadas por el peso al sacrificio, longitud de cuerpo, rendimiento, peso de visceras, peso de higado, peso de gonadas, grasa perivisceral y espesor de pared ventral. Los resultados de la respuesta productiva de los peces fueron similares entre los tratamientos excepto el peso final: dieta 1: 3911g; dieta 2: 4179g, y dieta 3: 4078g, que fue superior (p<0.05) en los tratamientos 2 y 3, con las proporciones de P/L mas estrechas, como tambien los machos (4237g) fueron mas pesados (p<0.05) que las hembras (3840g). En general, en los peces alimentados con la dieta 2 los machos tuvieron mejores resultados que las hembras. Las dietas con mayor contenido graso originaron un mayor deposito de grasa perivisceral, sin embargo, el rendimiento de la canal no fue afectado. El tratamiento 2 resulto ser el mas caro ($ 675), por concepto del gasto en alimento por kilo ganado de salmon, que el tratamiento 1 ($ 627) y 3 ($ 625), respectivamente. La decision final del empleo de dietas con mayores contenidos de lipidos debe basarse en mejorar la eficiencia de conversion de la dieta y que el costo del reemplazo de un insumo como la harina de pescado por otro origine dietas de un precio menor, que no fue el caso del presente trabajo.
Self-Supervised Knowledge Triplet Learning for Zero-shot Question Answering

The aim of all Question Answering (QA) systems is to be able to generalize to unseen questions. Current supervised methods are reliant on expensive data annotation. Moreover, such annotations can introduce unintended annotator bias which makes systems focus more on the bias than the actual task. In this work, we propose Knowledge Triplet Learning (KTL), a self-supervised task over knowledge graphs. We propose heuristics to create synthetic graphs for commonsense and scientific knowledge. We propose methods of how to use KTL to perform zero-shot QA and our experiments show considerable improvements over large pre-trained transformer models.
Euclid: The importance of galaxy clustering and weak lensing cross-correlations within the photometric Euclid survey

Context. The data from the Euclid mission will enable the measurement of the angular positions and weak lensing shapes of over a billion galaxies, with their photometric redshifts obtained together with ground-based observations. This large dataset, with well-controlled systematic effects, will allow for cosmological analyses using the angular clustering of galaxies (GCph) and cosmic shear (WL). For Euclid, these two cosmological probes will not be independent because they will probe the same volume of the Universe. The cross-correlation (XC) between these probes can tighten constraints and is therefore important to quantify their impact for Euclid. Aims. In this study, we therefore extend the recently published Euclid forecasts by carefully quantifying the impact of XC not only on the final parameter constraints for different cosmological models, but also on the nuisance parameters. In particular, we aim to decipher the amount of additional information that XC can provide for parameters encoding systematic effects, such as galaxy bias, intrinsic alignments (IAs), and knowledge of the redshift distributions. Methods. We follow the Fisher matrix formalism and make use of previously validated codes. We also investigate a different galaxy bias model, which was obtained from the Flagship simulation, and additional photometric-redshift uncertainties; we also elucidate the impact of including the XC terms on constraining these latter. Results. Starting with a baseline model, we show that the XC terms reduce the uncertainties on galaxy bias by ∼17% and the uncertainties on IA by a factor of about four. The XC terms also help in constraining the γ parameter for minimal modified gravity models. Concerning galaxy bias, we observe that the role of the XC terms on the final parameter constraints is qualitatively the same irrespective of the specific galaxy-bias model used. For IA, we show that the XC terms can help in distinguishing between different models, and that if IA terms are neglected then this can lead to significant biases on the cosmological parameters. Finally, we show that the XC terms can lead to a better determination of the mean of the photometric galaxy distributions. Conclusions. We find that the XC between GCph and WL within the Euclid survey is necessary to extract the full information content from the data in future analyses. These terms help in better constraining the cosmological model, and also lead to a better understanding of the systematic effects that contaminate these probes. Furthermore, we find that XC significantly helps in constraining the mean of the photometric-redshift distributions, but, at the same time, it requires more precise knowledge of this mean with respect to single probes in order not to degrade the final “figure of merit”.
AI4Bharat-IndicNLP Corpus: Monolingual Corpora and Word Embeddings for Indic Languages

We present the IndicNLP corpus, a large-scale, general-domain corpus containing 2.7 billion words for 10 Indian languages from two language families. We share pre-trained word embeddings trained on these corpora. We create news article category classification datasets for 9 languages to evaluate the embeddings. We show that the IndicNLP embeddings significantly outperform publicly available pre-trained embedding on multiple evaluation tasks. We hope that the availability of the corpus will accelerate Indic NLP research. The resources are available at this https URL.
Maize BIG GRAIN1 homolog overexpression increases maize grain yield

Summary The Zea Mays BIG GRAIN 1 HOMOLOG 1 (ZM‐BG1H1) was ectopically expressed in maize. Elite commercial hybrid germplasm was yield tested in diverse field environment locations representing commercial models. Yield was measured in 101 tests across all 4 events, 26 locations over 2 years, for an average yield gain of 355 kg/ha (5.65 bu/ac) above control, with 83% tests broadly showing yield gains (range +2272 kg/ha to −1240 kg/ha), with seven tests gaining more than one metric ton per hectare. Plant and ear height were slightly elevated, and ear and tassel flowering time were delayed one day, but ASI was unchanged, and these traits did not correlate to yield gain. ZM‐BG1H1 overexpression is associated with increased ear kernel row number and total ear kernel number and mass, but individual kernels trended slightly smaller and less dense. The ZM‐BG1H1 protein is detected in the plasma membrane like rice OS‐BG1. Five predominant native ZM‐BG1H1 alleles exhibit little structural and expression variation compared to the large increased expression conferred by these ectopic alleles.
Generative Adversarial Data Programming

The paucity of large curated hand-labeled training data forms a major bottleneck in the deployment of machine learning models in computer vision and other fields. Recent work (Data Programming) has shown how distant supervision signals in the form of labeling functions can be used to obtain labels for given data in near-constant time. In this work, we present Adversarial Data Programming (ADP), which presents an adversarial methodology to generate data as well as a curated aggregated label, given a set of weak labeling functions. More interestingly, such labeling functions are often easily generalizable, thus allowing our framework to be extended to different setups, including self-supervised labeled image generation, zero-shot text to labeled image generation, transfer learning, and multi-task learning.
Evaluation of Elephant-based Algorithms for Flow Table Reduction under Realistic Traffic Distributions

The majority of Internet traffic is caused by a relatively small number of flows (so-called elephant flows). This phenomenon can be exploited to facilitate traffic engineering: resource-costly individual flow forwarding entries can be created only for elephants, while serving mice over shortest paths. Although this idea already appeared as a part of proposed TE systems, it was not examined by itself. It remains unknown what extent of flow table occupancy and operations number reduction can be achieved, how to select thresholds or sampling rates to cover the desired fraction of traffic or how to detect elephants with low computational and memory overhead. In this paper, we use reproducible traffic models obtained from 30-day-long campus/residential trace covering 4 billion flows to answer these questions. The most important finding is that simple packet sampling performs surprisingly well on realistic traffic, reducing the number of flow entries by a factor up to 400 with the aim to cover 80% of the traffic. Its superb performance and negligible overhead questions the need for more sophisticated algorithms. We also provide an open-source software package allowing the replication of our experiments or the performing of similar evaluations for other algorithms or flow distributions.
A Taxonomy of Approaches for Integrating Attack Awareness in Applications

Software applications are subject to an increasing number of attacks, resulting in data breaches and financial damage. Many solutions have been considered to help mitigate these attacks, such as the integration of attack-awareness techniques. In this paper, we propose a taxonomy illustrating how existing attack awareness techniques can be integrated into applications. This work provides a guide for security researchers and developers, aiding them when choosing the approach which best fits the needs of their application.
Transforming growth factor‐β isoforms regulate the surface expression on membrane cofactor protein (CD46) and CD59 on human keratinocytes

We studied the regulation of the expression of complement regulatory proteins, membrane cofactor protein (MCP), decay accelerating factor (DAF) and CD59, on human keratinocytes by supernatant of activated mononuclear cells and by some individual cytokines present therein. Cultured keratinocytes expressed MCP, DAF and CD59. Supernatant of activated mononuclear cells and recombinant forms of transforming growth factor (TGF)‐β variants (β1, β2 and β3) up‐regulated MCP and CD59 but not DAF. Recombinant IL‐1α, IL‐2, IL‐6, TNF‐α and IFN‐γ had no influence. TGF‐β present in the supernatant was likely responsible for up‐regulation of MCP and CD59. A monoclonal anti‐TGF‐β antibody, which neutralized TGF‐β1, ‐β2 and ‐β3, did not inhibit the up‐regulation of MCP and CD59 by the supernatant. These results indicated that TGF‐β and an additional factor(s) present in the supernatant may be responsible for up‐regulating the expression of MCP and CD59 on keratinocytes; both may be acting non‐synergistically.
Information-Collection in Robotic Process Monitoring: An Active Perception Approach

Active perception systems maximizing information gain to support both monitoring and decision making have seen considerable application in recent work. In this paper, we propose and demonstrate a method of acquiring and extrapolating information in an active sensory system through use of a Bayesian Filter. Our approach is motivated by manufacturing processes, where automated visual tracking of system states may aid in fault diagnosis, certification of parts and safety; in extreme cases, our approach may enable novel manufacturing processes relying on monitoring solutions beyond passive perception. We demonstrate how using a Bayesian Filter in active perception scenarios permits reasoning about future actions based on measured as well as unmeasured but propagated state elements, thereby increasing substantially the quality of information available to decision making algorithms used in control of overarching processes. We demonstrate use of our active perception system in physical experiments, where we use a time-varying Kalman Filter to resolve uncertainty for a representative system capturing in additive manufacturing.
Succinct dynamic variation graphs

Motivation Pangenomics is a growing field within computational genomics. Many pangenomic analyses use bidirected sequence graphs as their core data model. However, implementing and correctly using this data model can be difficult, and the scale of pangenomic data sets can be challenging to work at. These challenges have impeded progress in this field. Results Here we present a stack of two C++ libraries, libbdsg and libhandlegraph, which use a simple, field-proven interface, designed to expose elementary features of these graphs while preventing common graph manipulation mistakes. The libraries also provide a Python binding. Using a diverse collection of pangenome graphs, we demonstrate that these tools allow for efficient construction and manipulation of large genome graphs with dense variation. For instance, the speed and memory usage is up to an order of magnitude better than the prior graph implementation in the vg toolkit, which has now transitioned to using libbdsg’s implementations. Availability libhandlegraph and libbdsg are available under an MIT License from https://github.com/vgteam/libhandlegraph and https://github.com/vgteam/libbdsg. Contact erik.garrison@ucsc.edu
Multilingual Embeddings Jointly Induced from Contexts and Concepts: Simple, Strong and Scalable

Word embeddings induced from local context are prevalent in NLP. A simple and effective context-based multilingual embedding learner is Levy et al. (2017)'s S-ID (sentence ID) method. Another line of work induces high-performing multilingual embeddings from concepts (Dufter et al., 2018). In this paper, we propose Co+Co, a simple and scalable method that combines context-based and concept-based learning. From a sentence aligned corpus, concepts are extracted via sampling; words are then associated with their concept ID and sentence ID in embedding learning. This is the first work that successfully combines context-based and concept-based embedding learning. We show that Co+Co performs well for two different application scenarios: the Parallel Bible Corpus (1000+ languages, low-resource) and EuroParl (12 languages, high-resource). Among methods applicable to both corpora, Co+Co performs best in our evaluation setup of six tasks.
A threat to loyalty: Fear of missing out (FOMO) leads to reluctance to repeat current experiences

We investigate a popular but underresearched concept, the fear of missing out (FOMO), on desirable experiences of which an individual is aware, but in which they do not partake. Through laboratory and field studies, we establish FOMO’s pervasiveness as a psychological phenomenon, present real-life contexts wherein FOMO may be experienced, and explore its behavioral consequences. Specifically, we show that FOMO poses a threat to loyalty by decreasing one’s intentions to repeat a current experience and may decrease the valuation of the current experience.
Localization of the membrane-bound hydrogenase in Alcaligenes eutrophus by electron microscopic immunocytochemistry

The membrane-bound hydrogenase was localized in cells of Alcaligenes eutrophus by electron microscopic immunocytochemistry. Post-embedding labeling performed on ultrathin sections revealed that the enzyme was located predominantly (80%) at the cell periphery in autotrophically and heterotrophically grown bacteria harvested from the exponential phase of growth. In the stationary growth phase, however, only 50% of the enzyme was found at the cell periphery; the remaining 50% was distributed over the cytoplasm. The relative amount of electron microscopic label per cell as seen by application of the protein A—gold technique was higher in cells grown autotrophically as compared to cells grown heterotrophically on fructose. Derepression of the enzyme was followed electron microscopically in a substrate-shift experiment (growth on fructose, followed by a shift to glycerol). Major amounts of the enzyme appeared to undergo a reattachment to the cytoplasmic membrane under these conditions, starting with a reduced location of the enzyme in the cytoplasm and an accumulation in cell areas close to the cytoplasmic membrane. These findings indicate that the ‘membrane-bound’ hydrogenase (i.e., that material enriched as membrane-bound enzyme according to the appropriate activity test) is not, in fact, membrane bound or membrane integrated but membrane associated. It may or may not interact with the cytoplasmic face of the cytoplasmic membrane, depending on the growth phase and conditions.
Testing different forms of regulation of yolk thyroid hormone transfer in pied flycatchers

Hormones transferred from mothers to their offspring are considered a maternal tool to prepare progeny for expected environmental conditions, increasing maternal fitness. To flexibly influence offspring, mothers should be able to transmit the hormonal signals independent of their own hormonal status. However, the ability to regulate hormone transfer to the next generation is under debate. We studied the transfer of thyroid hormones (THs) to eggs in a bird model. We elevated thyroxine (T4, the prohormone for the biological active triiodothyronine, T3) during egg-laying using T4 implants on females of a wild population of pied flycatchers (Ficedula hypoleuca), and measured plasma and yolk T4 and T3 as a response. To our knowledge, studies that manipulated a prohormone and measured the change in its active metabolites have rarely been conducted. We found an increase in plasma and yolk T4 and no change in T3 concentrations leading to a similar decrease in yolk T3/T4 ratio in response to the T4 treatment in plasma and yolk. This suggests that mothers are able to regulate the conversion of T4 in T3 to avoid potential costs of elevated exposure to the active hormone to herself and to her progeny. Finally, contrary to our predictions, we found no evidence of regulatory mechanisms at the follicle level, which is essential for independent regulation of yolk hormone transfer. Summary statement Thyroid hormones have been overlooked in the context of hormone-mediated maternal effects. We found that mothers may regulate yolk thyroid hormone transfer by regulating the conversion of the active form of the hormone.