Miracle-dz/UniFAR-FTUs huggingface dataset:
Limits to the spread of an obligate social cheater in the social amoeba Dictyostelium discoideum

Cooperation is widespread across life, but its existence can be threatened by exploitation. Social cheaters can be obligate, incapable of contributing to a necessary function, so that spread of the cheater leads to loss of the function. In the social amoeba Dictyostelium discoideum, obligate social cheaters cannot become dead stalk cells that lift spores up for dispersal, but instead depend on forming chimeras with fully functional altruistic individuals for forming a stalk. Obligate cheaters in D. discoideum are known to pay the cost of being unable to form fruiting bodies on their own. In this study we discovered that there are two additional costs that can apply to obligate cheaters. Even when there are wild-type cells to parasitize, the chimeric fruiting bodies that result have shorter stalks that are disadvantaged in spore dispersal. Furthermore, we found that obligate cheaters were overrepresented among spore cells in chimeras only when they were at low frequencies. Failure to develop into viable fruiting bodies on their own, negative frequency-dependent cheating, and shorter fruiting bodies represent three limits on obligate social cheating so it is not surprising that obligate cheaters have not been found in nature.
Estimation of Basic Reproduction Number of the COVID-19 Epidemic in Denmark using a Two-Step Model.

Objective: To conduct an early estimation of the Basic Reproduction Number (BRN) induced by government interference, and to project resulting day to day number of in-patients, ICU-patients and cumulative number of deaths in a Danish setting. Method: We used the Kermack and McKendrick model with varying basic reproduction number to estimate number infected and age stratified percentages to estimate number of in-patients, ICU-patients and cumulative number of deaths. Changes in basic reproduction number was estimated based on current in-patient numbers. Results: The basic reproductive number in the time period of February 27th to March 18th was found to be 2.65, however, this number was reduced to 1.99 after March 18th. Keywords: COVID-19, basic reproduction number, Danish population
Genetic and Phenotypic Associations among Maturity, Yield and Quality Parameters in Popcorn

The study was conducted to measure both genetic and phenotypic associations among all studied characters of popcorn. Six basic generations viz. two parents, F , F , BC and BC , of single cross popcorn were 1 2 1 2 used in this study. These generations were developed after selection of desired parents. The parental inbredlines, PS-1 and BD-1 were selected on their maturity and grain yield potential. The resultant F (PS-1 × BD-1) was selfed to obtained F and crossed with its male and female parents as well in the same 1 2 season to obtained BC and BC generations. Maturity characters including days to anthesis, silking and 1 2 maturity were positively and significantly correlated with each other at both genetic and phenotypic level. Maturity traits were negatively associated with yield contributing traits. Phenotypic correlation of days to silking and maturity with percent unpopped grains was positive and significantly. Quality parameter, expansion volume was negatively but significant correlated with all yield contributing traits including, fresh ear weight, ear diameter, ear length, kernel row per ear, grains per row, grain per ear, grain yield, biological yield and harvest index both at genetic and phenotypic level. Phenotypic association of expansion volume was negative and significant with percent unpopped grains. Both genetic and phenotypic correlation of yield contributing traits was positive and significant with each other. Positive correlation between yield related traits indicted that grain yield could be improved by making selection on any of these studied yield characters.
TLDR: Token Loss Dynamic Reweighting for Reducing Repetitive Utterance Generation

Natural Language Generation (NLG) models are prone to generating repetitive utterances. In this work, we study the repetition problem for encoder-decoder models, using both recurrent neural network (RNN) and transformer architectures. To this end, we consider the chit-chat task, where the problem is more prominent than in other tasks that need encoder-decoder architectures. We first study the influence of model architectures. By using pre-attention and highway connections for RNNs, we manage to achieve lower repetition rates. However, this method does not generalize to other models such as transformers. We hypothesize that the deeper reason is that in the training corpora, there are hard tokens that are more difficult for a generative model to learn than others and, once learning has finished, hard tokens are still under-learned, so that repetitive generations are more likely to happen. Based on this hypothesis, we propose token loss dynamic reweighting (TLDR) that applies differentiable weights to individual token losses. By using higher weights for hard tokens and lower weights for easy tokens, NLG models are able to learn individual tokens at different paces. Experiments on chit-chat benchmark datasets show that TLDR is more effective in repetition reduction for both RNN and transformer architectures than baselines using different weighting functions.
The Planetary Luminosity Problem: “Missing Planets” and the Observational Consequences of Episodic Accretion

The high occurrence rates of spiral arms and large central clearings in protoplanetary disks, if interpreted as signposts of giant planets, indicate that gas giants commonly form as companions to young stars (<few Myr) at orbital separations of 10–300 au. However, attempts to directly image this giant planet population as companions to more mature stars (>10 Myr) have yielded few successes. This discrepancy could be explained if most giant planets form by “cold start,” i.e., by radiating away much of their formation energy as they assemble their mass, rendering them faint enough to elude detection at later times. In that case, giant planets should be bright at early times, during their accretion phase, and yet forming planets are detected only rarely through direct imaging techniques. Here we explore the possibility that the low detection rate of accreting planets is the result of episodic accretion through a circumplanetary disk. We also explore the possibility that the companion orbiting the Herbig Ae star HD 142527 may be a giant planet undergoing such an accretion outburst.
Linearly Self-Equivalent APN Permutations in Small Dimension

All almost perfect nonlinear (APN) permutations that we know to date admit a special kind of linear self-equivalence, i.e., there exists a permutation <inline-formula> <tex-math notation="LaTeX">$G$ </tex-math></inline-formula> in their CCZ-equivalence class and two linear permutations <inline-formula> <tex-math notation="LaTeX">$A$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$B$ </tex-math></inline-formula>, such that <inline-formula> <tex-math notation="LaTeX">$G \circ A = B \circ G$ </tex-math></inline-formula>. After providing a survey on the known APN functions with a focus on the existence of self-equivalences, we search for APN permutations in dimension 6, 7, and 8 that admit such a linear self-equivalence. In dimension six, we were able to conduct an <italic>exhaustive search</italic> and obtain that there is only one such APN permutation up to CCZ-equivalence. In dimensions 7 and 8, we performed an exhaustive search for all but a few classes of linear self-equivalences and we did not find any new APN permutation. As one interesting result in dimension 7, we obtain that all APN permutation polynomials with coefficients in <inline-formula> <tex-math notation="LaTeX">$\mathbb {F}_{2}$ </tex-math></inline-formula> must be (up to CCZ-equivalence) monomial functions.
The Semantic Evolution of Observation Data: Visualizing spatiotemporal water data

Résumé. The Coordinated Online Information Network (COIN) incorporates semantic web technology that integrates, publishes and visualizes time series water data allowing users to access a multitude of datasets in order to compare the data and draw conclusions. It employs an efficient and systematic data storage and retrieval system and can convert the data to a standard format for visualization. COIN utilizes a number of standards from OGC (Open Geospatial Consortium) and W3C (RDF, OWL, SPARQL and GeoSPARL) and benefits from generic ontologies transforming semantics to data, enriching data sets and making it available and interoperable via WFS and WMS standards. These principles facilitate publication and exchange of data across the web, increasing transparency and interpretability. Through modernized data submission and retrieval we hope to break down the silos of data, allowing users to visualize time series water quality and hydrometric data from multiple sources to increase knowledge in relationship to impacts on Yukon water.
The use of mHealth for maternal health care in Ethiopia

En el capitulo 1 describimos el contexto, la hipotesis y objetivos desarrollados en esta Tesis Doctoral. En esta Tesis se han planteado tres objetivos principales: primero, un analisis de la funcion de los ? Health Extension Workers? (HEWs) en la atencion maternal en los servicios primarios de salud rurales de Etiopia; segundo, una evaluacion detallada de los conocimientos y competencias de los HEWs en salud maternal y los desafios, barreras y oportunidades que presentan; Tercero, el desarrollo y la aplicabilidad de innovadoras aplicaciones de salud movil (m? salud) y como estas pueden contribuir en la mejora de los procesos de salud maternal. El capitulo 2 se basa en el articulo publicado en BMC Health Services Research, ? The role of health extension workers in improving utilization of maternal health services in rural areas in Ethiopia: a cross sectional study? Desde el ano 2003, el gobierno etiope ha realizado un gran esfuerzo para desarrollar un sistema basico de salud de atencion primaria. Para ello, ha formado y desplegado mas de treinta mil trabajadores comunitarios de salud (HEWs) en las zonas rurales del pais. Los HEWs tienen una formacion basica en salud publica y medicina preventiva y conforman la primera linea de atencion sanitaria en las areas rurales. En este sentido, es necesario una evaluacion del impacto y efectividad de la cartera de servicios de salud maternal que los HEWs pueden ofrecer a la poblacion. En este primer estudio seleccionamos de forma aleatoria 725 mujeres con ninos menores de cinco anos en tres distritos del norte de Etiopia y evaluamos, entre otras variables, la utilizacion de metodos de planificacion familiar, la atencion prenatal y postnatal, y la utilizacion de sales iodadas, comparandolos con los resultados obtenidos en un estudio previo a nivel nacional (DHS, 2005). Mediante un analisis estadistico de regresion logistica, investigamos las posibles asociaciones de multiples variables epidemiologicas con la utilizacion de los servicios de salud maternal. Nuestros resultados indican que los HEWs han contribuido de forma relevante en la mejoria de la utilizacion de los servicios de planificacion familiar, la atencion prenatal y el diagnostico del la infeccion por HIV. Sin embargo, no ha sido especialmente significativa su impacto en la mejora de la atencion postnatal y la atencion durante el parto. Asimismo, observamos que las mujeres que tenian estudios (OR, 1.85), escuchaban la radio (OR, 1.45), o tenian algun ingreso economico propio (OR, 1.43), demostraban una mayor utilizacion de los servicios de salud maternal. En este sentido, es recomendable mejorar la coordinacion de los HEWs con las matronas y enfermeras de los hospitales comarcales y el apoyo que se ofrece a los 184 HEWs para priorizar los casos de alto riesgo y la peparacion al parto y su coordinacion con los centros de salud.
Inferring the topology of a non-linear sparse gene regulatory network using fully Bayesian spline regression

We propose a semi-parametric Bayesian model, based on penalised splines, for the recovery of the topology of an interaction network from longitudinal data. Our motivation is inference of gene regulatory networks from low resolution microarray time series ( 10 (cid:0) 50 time points). Parenthood relations are mapped by augmenting the model with kinship indicators and providing these with either an overall or gene-wise hierarchical structure. Appropriate speciﬁcation of the prior is crucial to control the ﬂexibility of the splines, especially under circumstances of scarce data; thus we provide an informative, proper prior and analyse sensitivity. The posterior is analytically intractable and numerical methods are needed. A Metropolis-within-Gibbs sampler is proposed, with a novel Metropolis-Hastings step for sampling the topology and the spline coefﬁcients simultaneously. We also construct a linear model for comparison purposes. Model ﬁt is illustrated using synthetic data drawn from ODE models and and gene expression from an experimental data set of the Arabidopsis thaliana circadian rhythm.
ILLUMINA® SEQUENCING OF GREEN STINK BUG NYMPH AND ADULT cDNA TO IDENTIFY POTENTIAL RNAi GENE TARGETS

Whole-body transcriptomes for nymphs and adults of the green stink bug, Acrosternum hilare (Say), were sequenced on an Illumina® Genome Analyzer IIx sequencer. The insects were collected from sites in North Carolina and Virginia, USA. The cDNA library for each sample was sequenced on one lane of an eight-lane flow cell. Total read count was 25,211,411 and 23,601,951 for the nymph and adult libraries, respectively. Mean read length was 124 bps (base pairs) for nymph and 125 bps for adult. Total sequencing data were 3,127,036,121 bps for nymph cDNA and 2,956,794,438 bps for adult. Trinity® software was used to assemble the nymph and adult reads into 79,062 and 74,271 contigs (contiguous sequences), respectively. Blast2GO® software was used to align, map, and annotate the contigs. For the alignment step, the contigs were translated to peptides and compared to the GenBank nr (non-redundant) protein database using the BLASTx (Basic Local Alignment Search Tool) algorithm with E-value cut-off set at E-3 (10). The average length of BLASTx translated sequences was 1248 (range = 201 – 7968) amino acids for the nymph and 1320 (range = 201 – 7957) for the adult. Several nymph and adult sequences showed high homology (E-value ≤ 1.5 E-13) with database hormones, neuropeptides, neurotransmitters and/or their receptors. Seventeen nymph and adult sequences were identical (E-value = 0) to A. pisum, T. castaneum, B. germaninca, and P. humanus corporis hormones. After alignment of green stink bug contigs with GenBank nr database sequences, all BLAST hits (E-value ≤ E-3) were mapped and annotated with GO (Gene Ontology) terms that assigned the translated sequences to categories of putative protein function. Mapping and annotation steps yielded 13,226 nymph and 14,725 adult sequences assigned to 13 GO functional categories: Catalysis, binding, transport, signal transduction, structural molecule activity, enzyme regulation, electron carrier activity, antioxidant activity, metallochaperone, channel regulation, protein tag, translation regulation and nutrient reservoir. The goal of sequencing and of on-going bioinformatic analysis of these transcriptomes is to identify candidate RNAi gene targets with potential to be developed as insecticidal transgenes for control of stink bugs and other hemipteran pests of cotton. The resulting data can also be applied to other protein function and genetics studies.
Investigating the Crushing Behavior of Weathered Phyllite Fills Under Compaction

Weathered phyllite fill is crushable and will be further broken during the compaction process. In this paper, standard ASTM compaction tests were performed on weathered phyllite fills with 45%, 55% and 65% rock content, to investigate the crushing behavior of weathered phyllite fill under compaction. The particle size distributions before and after compaction were observed and then the particle breakage of weathered phyllite fills were analyzed by fractal dimension. Furthermore, relative fractal dimension was proposed in this paper and was adopted to evaluate the effect of initial rock content and initial gradation on the particle breakage. It was found that fractal dimension well characterized the crushing behavior of weathered phyllite fills. The weathered phyllite fills became finer with the increased number of times it was compacted. Under the first compaction, the degree of crushing was greatly affected by the initial rock content and increased with greater rock contents. However, under the second compaction, the degree of crushing rate was dominated by initial particle gradation, and the better the initial particle gradation, the lower the rate of crushing. The findings in this paper may provide guidance for the construction of weathered phyllite subgrade fills.
Time series and machine learning to forecast the water quality from satellite data

Managing the quality of water for present and future generations of coastal regions should be a central concern of both citizens and public officials. Remote sensing can contribute to the management and monitoring of coastal water and pollutants. Algal blooms are a coastal pollutant that is a cause of concern. Many satellite data, such as MODIS, have been used to generate water-quality products to detect the blooms such as chlorophyll a (Chl-a), a photosynthesis index called fluorescence line height (FLH), and sea surface temperature (SST). It is important to characterize the spatial and temporal variations of these water quality products by using the mathematical models of these products. However, for monitoring, pollution control boards will need nowcasts and forecasts of any pollution. Therefore, we aim to predict the future values of the MODIS Chl-a, FLH, and SST of the water. This will not be limited to one type of water but, rather, will cover different types of water varying in depth and turbidity. This is very significant because the temporal trend of Chl-a, FLH, and SST is dependent on the geospatial and water properties. For this purpose, we will decompose the time series of each pixel into several components: trend, intra-annual variations, seasonal cycle, and stochastic stationary. We explore three such time series machine learning models that can characterize the non-stationary time series data and predict future values, including the Seasonal ARIMA (Auto Regressive Integrated Moving Average) (SARIMA), regression, and neural network. The results indicate that all these methods are effective at modelling Chl-a, FLH, and SST time series and predicting the values reasonably well. However, regression and neural network are found to be the best at predicting Chl-a in all types of water (turbid and shallow). Meanwhile, the SARIMA model provides the best prediction of FLH and SST.
Pipelined Backpropagation at Scale: Training Large Models without Batches

New hardware can substantially increase the speed and efficiency of deep neural network training. To guide the development of future hardware architectures, it is pertinent to explore the hardware and machine learning properties of alternative training algorithms. In this work we evaluate the use of small batch, fine-grained Pipelined Backpropagation, an asynchronous pipeline parallel training algorithm that has significant hardware advantages. We introduce two methods, Spike Compensation and Linear Weight Prediction, that effectively mitigate the downsides caused by the asynchronicity of Pipelined Backpropagation and outperform existing techniques in our setting. We show that appropriate normalization and small batch sizes can also aid training. With our methods, fine-grained Pipelined Backpropagation using a batch size of one can match the accuracy of SGD for multiple networks trained on CIFAR-10 and ImageNet. Simple scaling rules allow the use of existing hyperparamaters for traditional training without additional tuning.
Repeated Games with Asymmetric Information Last Round Convergence and No-Instant Regret in Repeated Games with Asymmetric Information

This paper considers repeated games in which one player has more information about the game than the other players. In particular, we investigate repeated two-player zero-sum games where only the column player knows the payoff matrix A of the game. Suppose that while repeatedly playing this game, the row player chooses her strategy at each round by using a no-regret algorithm to minimize her (pseudo) regret. We develop a no-instantregret algorithm for the column player to exhibit last round convergence to a minimax equilibrium. We show that our algorithm is efficient against a large set of popular noregret algorithms of the row player, including the multiplicative weight update algorithm, the online mirror descent method/follow-the-regularized-leader, the linear multiplicative weight update algorithm, and the optimistic multiplicative weight update.
Energy Efficiency Maximization in Millimeter Wave Hybrid MIMO Systems for 5G and Beyond

At millimeter wave (mmWave) frequencies, the higher cost and power consumption of hardware components in multiple-input multiple output (MIMO) systems do not allow beamforming entirely at the baseband with a separate radio frequency (RF) chain for each antenna. In such scenarios, to enable spatial multiplexing, hybrid beamforming, which uses phase shifters to connect a fewer number of RF chains to a large number of antennas is a cost effective and energy-saving alternative. This paper describes our research on fully adaptive transceivers that adapt their behaviour on a frame-by-frame basis, so that a mmWave hybrid MIMO system always operates in the most energy efficient manner. Exhaustive search based brute force approach is computationally intensive, so we study fractional programming as a low-cost alternative to solve the problem which maximizes energy efficiency. The performance results indicate that the resulting mmWave hybrid MIMO transceiver achieves significantly improved energy efficiency results compared to the baseline cases involving analogue-only or digital-only signal processing solutions, and shows performance trade-offs with the brute force approach.
Screening of Phytochemicals and In silico Approach through Drug Design of Centella asiatica

Centellaasiatica is a valuable medicinal herbaceous aromatic creeper which has been valued for centuries in ayurvedic medicine. Phytochemical analysis of Centellaasiatica plant extracts revealed the presence of various biochemical compounds such as alkaloids, flavonoids, glycosides, triterpenoids and saponins etc. Since triterpenoids and flavonoids have remarkable anti-inflammatory activity also Phyto compound possess a wide range of activities, which may help in protection against tuberculosis diseases. In this study, the molecular docking was applied to explore the binding mechanism and to correlate its docking score with the activity of plant derived compounds and also identified targets were validated through some other databases to select the better ones and design the drug. This study reveals that NOD2 is a better potential drug target for tuberculosis and Quercetin is the best ligand to inhibit NOD2 and might be prevent the disease Tuberculosis. Our result can be useful for the design and development of novel compounds having better inhibitory activity against several type of Tuberculosis. This potential agent will be a promising candidate can further be validated in research for its proper function. This work would help to design a potent lead molecule against any other disease.