Miracle-dz/UniFAR-FTUs huggingface dataset:
Long Optimal or Small-Defect LRC Codes with Unbounded Minimum Distances

A code over a finite field is called locally recoverable code (LRC) if every coordinate symbol can be determined by a small number (at most r, this parameter is called locality) of other coordinate symbols. For a linear code with length n, dimension k and locality r, its minimum distance d satisfies a Singleton-like bound. A code attaining this bound is called optimal. Many families of optimal locally recoverable codes have been constructed by using different techniques in finite fields or algebraic curves. However no optimal LRC code over a general finite field of q elements with the length n around the square of q, the locality r larger than or equal to 24 and the minimum distance d larger than or equal to 9 has been constructed. In this paper for any given finite field of q elements, any given r between 1 and q-1 and given d in certain range, we give an optimal LRC code with length n around the square of q, locality r and minimum distance d. This is the only known family of optimal LRC codes with lengths n around the square of q and unbounded localities and minimum distances d larger than or equal to 9. We also gives an asymptotic bound for q-ary r locality LRC codes better than the previously konwn bound. Many long r-locality LRC codes with small defects are also constructed.
Competing endogenous RNA crosstalk at system level

microRNAs (miRNAs) regulate gene expression at post-transcriptional level by repressing target RNA molecules. Competition to bind miRNAs tends in turn to correlate their targets, establishing effective RNA-RNA interactions that can influence expression levels, buffer fluctuations and promote signal propagation. Such a potential has been characterized mathematically for small motifs both at steady state and away from stationarity. Experimental evidence, on the other hand, suggests that competing endogenous RNA (ceRNA) crosstalk is rather weak. Extended miRNA-RNA networks could however favour the integration of many crosstalk interactions, leading to significant large-scale effects in spite of the weakness of individual links. To clarify the extent to which crosstalk is sustained by the miRNA interactome, we have studied its emergent systemic features in silico in large-scale miRNA-RNA network reconstructions. We show that, although generically weak, system-level crosstalk patterns (i) are enhanced by transcriptional heterogeneities, (ii) can achieve high-intensity even for RNAs that are not co-regulated, (iii) are robust to variability in transcription rates, and (iv) are significantly non-local, i.e. correlate weakly with miRNA-RNA interaction parameters. Furthermore, RNA levels are generically more stable when crosstalk is strongest. As some of these features appear to be encoded in the network’s topology, crosstalk may functionally be favoured by natural selection. These results suggest that, besides their repressive role, miRNAs mediate a weak but resilient and context-independent network of cross-regulatory interactions that interconnect the transcriptome, stabilize expression levels and support system-level responses.
Direct imaging of irregular satellite discs in scattered light

Direct imaging surveys have found that long-period super-Jupiters are rare. By contrast, recent modelling of the widespread gaps in protoplanetary discs revealed by Atacama Large Millimetre Array suggests an abundant population of smaller Neptune to Jupiter-mass planets at large separations. The thermal emission from such lower-mass planets is negligible at optical and near-infrared wavelengths, leaving only their weak signals in reflected light. Planets do not scatter enough light at these large orbital distances, but there is a natural way to enhance their reflecting area. Each of the four giant planets in our Solar system hosts swarms of dozens of irregular satellites, gravitationally captured planetesimals that fill their host planets’ spheres of gravitational influence. What we see of them today are the leftovers of an intense collisional evolution. At early times, they would have generated bright circumplanetary debris discs. We investigate the properties and detectability of such irregular satellite discs (ISDs) following models for their collisional evolution from Kennedy & Wyatt (2011). We find that the scattered light signals from such ISDs would peak in the 10–100 au semimajor axis range implied by ALMA, and can render planets detectable over a wide range of parameters with upcoming high-contrast instrumentation. We argue that future instruments with wide fields of view could simultaneously characterize the atmospheres of known close-in planets, and reveal the population of long-period Neptune–Jupiter mass exoplanets inaccessible to other detection methods. This provides a complementary and compelling science case that would elucidate the early lives of planetary systems.
The TCGA Meta-Dataset Clinical Benchmark

Machine learning is bringing a paradigm shift to healthcare by changing the process of disease diagnosis and prognosis in clinics and hospitals. This development equips doctors and medical staff with tools to evaluate their hypotheses and hence make more precise decisions. Although most current research in the literature seeks to develop techniques and methods for predicting one particular clinical outcome, this approach is far from the reality of clinical decision making in which you have to consider several factors simultaneously. In addition, it is difficult to follow the recent progress concretely as there is a lack of consistency in benchmark datasets and task definitions in the field of Genomics. To address the aforementioned issues, we provide a clinical Meta-Dataset derived from the publicly available data hub called The Cancer Genome Atlas Program (TCGA) that contains 174 tasks. We believe those tasks could be good proxy tasks to develop methods which can work on a few samples of gene expression data. Also, learning to predict multiple clinical variables using gene-expression data is an important task due to the variety of phenotypes in clinical problems and lack of samples for some of the rare variables. The defined tasks cover a wide range of clinical problems including predicting tumor tissue site, white cell count, histological type, family history of cancer, gender, and many others which we explain later in the paper. Each task represents an independent dataset. We use regression and neural network baselines for all the tasks using only 150 samples and compare their performance.
Dealing with Sparse Rewards in Reinforcement Learning

Successfully navigating a complex environment to obtain a desired outcome is a difficult task, that up to recently was believed to be capable only by humans. This perception has been broken down over time, especially with the introduction of deep reinforcement learning, which has greatly increased the difficulty of tasks that can be automated. However, for traditional reinforcement learning agents this requires an environment to be able to provide frequent extrinsic rewards, which are not known or accessible for many real-world environments. This project aims to explore and contrast existing reinforcement learning solutions that circumnavigate the difficulties of an environment that provide sparse rewards. Different reinforcement solutions will be implemented over a several video game environments with varying difficulty and varying frequency of rewards, as to properly investigate the applicability of these solutions. This project introduces a novel reinforcement learning solution by combining aspects of two existing state of the art sparse reward solutions, curiosity driven exploration and unsupervised auxiliary tasks.
Reanalysis of the binary neutron star merger GW170817 using numerical-relativity calibrated waveform models

We reanalyze gravitational waves from a binary-neutron-star merger GW170817 using a numerical-relativity (NR) calibrated waveform model, the TF2+_KyotoTidal model. By imposing a uniform prior on the binary tidal deformability $\tilde{\Lambda}$ the symmetric $90\%$ credible interval of $\tilde{\Lambda}$ is estimated to be $481^{+436}_{-359}$ ($402^{+465}_{-279}$) for the case of $f_\mathrm{max}=1000~\mathrm{Hz}$ ($2048~\mathrm{Hz}$), where $f_\mathrm{max}$ is the maximum frequency in the analysis. We also reanalyze the event with other waveform models: two post-Newtonian waveform models (TF2$\_$PNTidal and TF2+$\_$PNTidal), the TF2+$\_$NRTidal model that is another NR calibrated waveform model, and its upgrade, the TF2+$\_$NRTidalv2 model. While estimates of parameters other than $\tilde{\Lambda}$ are broadly consistent among different waveform models, our results indicate that there is a difference in estimates of $\tilde{\Lambda}$ among three NR calibrated waveform models. The difference in the peak values of posterior probability density functions of $\tilde{\Lambda}$ between the NR calibrated waveform models (the TF2+$\_$KyotoTidal and TF2+$\_$NRTidalv2 models) for $f_\mathrm{max}=1000~\mathrm{Hz}$ is about 40 and is much smaller than the width of $90\%$ credible interval, which is about 700. The systematic error for the NR calibrated waveform models will be significant to measure $\tilde{\Lambda}$ in the case of GW170817-like signal for the planned third generation detectors's sensitivities.
Keyphrase Extraction from Scholarly Articles as Sequence Labeling using Contextualized Embeddings

In this paper, we formulate keyphrase extraction from scholarly articles as a sequence labeling task solved using a BiLSTM-CRF, where the words in the input text are represented using deep contextualized embeddings. We evaluate the proposed architecture using both contextualized and fixed word embedding models on three different benchmark datasets (Inspec, SemEval 2010, SemEval 2017) and compare with existing popular unsupervised and supervised techniques. Our results quantify the benefits of (a) using contextualized embeddings (e.g. BERT) over fixed word embeddings (e.g. Glove); (b) using a BiLSTM-CRF architecture with contextualized word embeddings over fine-tuning the contextualized word embedding model directly, and (c) using genre-specific contextualized embeddings (SciBERT). Through error analysis, we also provide some insights into why particular models work better than others. Lastly, we present a case study where we analyze different self-attention layers of the two best models (BERT and SciBERT) to better understand the predictions made by each for the task of keyphrase extraction.
Evaluation of role of noradrenergic system in the antidepressant activity of tramadol using forced swim test in Albino mice

Several studies have suggested that tramadol could play a role in mood improvement. The present study was undertaken to evaluate the role of noradrenergic system in the antidepressant activity of tramadol in a test predictive of antidepressant activity in mice. Animals were divided into five groups, and each group comprised of six mice. Group 1 (control group) was pretreated with normal saline (0.1 ml/10 g). Groups 2, 3 and 4 were pretreated with three different doses (10, 20, and 40 mg/kg) of tramadol. Group 5 was pretreated with imipramine at the dose of 10 mg/kg. All the drugs were given intraperitonially (0.1 ml/10 g). After 15 minutes of drug administration, mice were placed individually in the 5 L glass beakers, filled to a height of 15 cm with water (room temperature) and the duration of immobility is recorded during the last 4 minutes of a 6 minutes test. In the next stage of the study, procedure was repeated with six different groups of animalse, each group comprising of six mice. The groups of animals here included animals pretreated with 40 mg/kg of tramadol, propranolol 5mg/kg, tramadol 40mg/kg + propranolol 5mg/kg, phentolamine 10mg/kg, and phentolamine 10mg/kg + tramadol 40mg/kg. Tramadol at 40mg/kg dose on acute as well as chronic administration for 10 days significantly decreased immobility period as compared to control mice. There was no significant difference in the antidepressant activity in animals administered with tramadol 40 mg/kg and imipramine 10mg/kg. Phentolamine effectively blocked the reduction in immobility duration by tramadol where as propranolol did not have significant effect on the antidepressant like action of tramadol in forced swim test in mice.
Removal of COD , BOD and Color from Municipal Solid Waste Leachate using Silica and Iron nano particles-A Comparative Study

Application of nano particle in the treatment of municipal solid waste leachate is of recent interest. In this paper, the effectiveness of silica nano particles synthesized from blast furnace slag and iron nano particle synthesized from chemicals was studied for the removal of organic pollutants and color. The synthesized nano particles were characterized using SEM, TEM, EDX and FTIR analysis. Batch experiments were conducted to remove the BOD, COD and color from Aged landfill leachate (ALL) and leachate from the composting yard (CYL). Influencing parameters like pH, contact time, nano particle dosage and Hydrogen peroxide concentration were studied. The maximum removal was achieved at the pH of 6 for both the nano particle, contact time 90 minutes for silica nano particle and 120 minutes for iron nano particle, silica nano particle dose as 0.4g/50 ml, iron nano particle dose as 0.3g/50ml and hydrogen peroxide concentration was found to be 3M and 4M for silica and iron nano particles respectively. The removal efficiency in CYL and ALL using silica nano particle was obtained as 87.15%, 72.72%, 83.15% and 82.5%, 62.5%, 77.34% for color, BOD and COD respectively. Similarly for iron nano particle, the removal efficiency was found to be 60.3%, 65%, 67.43% and 57.06%, 57.27%, 67% for the removal of color, BOD and COD in CYL and ALL, respectively.
Forecasting Volatility in Stock Markets : a Volume Filtered GARCH Model ∗

In GARCH-type models, no distinction is made between informative and noninformative price variations in the dynamic of variance. This paper develops a Volume Filtered GARCH model incorporating unexpected volume and its impact on stock volatility. This framework allows to isolate non-informed market noise into one component, and simultaneously to capture a filtered variance estimate. The asymmetric and leptokurtic distribution of return depends on the correlation between unexpected volumes and innovations in returns, more likely to be negative. Empirically, the model is selected for all S&P 100 stocks according to standard selection criteria. The model implies more stable variance estimates with no costs in terms of risk management. ∗The author would like to thank Mireille Bossy and Georges Hübner for valuable comments and ideas. †INRIA, France and Research engineer at Koris International. Email: maxime.bonelli@inria.fr, Address: Koris International, Parc Technologique de Sophia-Antipolis, 200 avenue de Roumanille, Immeuble Néri, 06410 Biot France, and Phone: + 33 (0)4 88 72 88 32.
The audit expectation gap in Eritrea

The public's expectations of auditors are usually not met by the actual performance of auditors. This is presumed to be caused by the difference in perception between what the public expects and the auditors deliver. This is termed the "expectation gap in auditing". Due to the widespread concern raised by the public, a number of researchers have studied the problem in various countries, among others: USA, Britain, South Africa, Finland, Spain, Singapore, New Zealand and Australia. All the studies undertaken indicate the existence of an expectation gap in these countries. Although many researchers and professional bodies have suggested how to close or narrow the gap, the problem is likely to remain unresolved due to spectacular corporate collapses such as Enron. The aim of this research study is to investigate the existence and the nature of the audit expectation gap in Eritrea, to analyze its constituent parts and to identify the factors which contribute to the gap, to compare the findings to the research findings of similar studies and, finally, to recommend possible solutions to narrow the expectation gap in Eritrea. A survey was conducted via structured interviews (through questionnaire) and unstructured interviews to examine the perceptions of auditors, directors, managers, accountants, internal auditors, shareholders, bank loan officers and tax inspectors of the Inland Revenue Department. Overall, the findings of this research suggest that there is a wide audit expectation gap on issues concerning the auditor's responsibility for fraud detection and the reporting of fraud and other illegal acts to authorities, going concern problems, and for examining the efficiency and effectiveness of the company's management. Auditors independence was also an important point of concern. Moreover, inadequate regulations by the regulatory body with regard to audit quality was also found to be a factor which contributed to the gap. Abstract Un ive r i ty of Ca pe To wnUn ive r i ty of Ca pe To wn The Audit expectation gap The most dissatisfied group, of all the interest groups, were users. This can be due partly to the dissatisfaction of the tax auditors with respect to the audit of small and medium sized companies. Moreover, there seems also to exist a lack of knowledge among users and management about the nature and limitations of the audit function. With respect to auditors, lack of knowledge also exists with regard to auditors' legal responsibilities. Moreover, auditors considered many of the suggested duties as the existing duty of an auditor. Hence the "knowledge gap" also exists among auditors. Overall, this research report indicates evidence of the existence of the audit expectation gap, and also provides a comprehensive approach to narrow the gap in Eritrea. If the recommendations are implemented, this may give the public confidence and trust in [mancial reporting in Eritrea. The directions that future research may take are also discussed.
1 1 Se p 20 19 AVEC ’ 18 Eco-driving with Learning Model Predictive Control

We present a predictive cruise controller which iteratively improves the fuel economy of a vehicle traveling along the same route every day. Our approach uses historical data from previous trip iterations to improve vehicle performance while guaranteeing a desired arrival time. The proposed predictive cruise controller is based on the recently developed Learning Model Predictive Control (LMPC) framework, which is extended in this paper to include time constraints. Moreover, we reformulate the modified LMPC with time constraint into a computationally tractable form. Our method is presented in detail, applied to the predictive cruise control problem, and validated through simulations.
A review of the impact of Fairtrade over the last ten years

Over the last decade, Fairtrade sales have increased dramatically, reaching €2.89bn globally by the end of 2008. In line with this growth there is increasing demand to measure and demonstrate the difference that engagement with Fairtrade is having for participating producers and workers and their families – in other words the impact that Fairtrade is having at the local level. This paper summarises a review of the published literature on Fairtrade’s impact, commissioned by the Fairtrade Foundation and conducted by NRI in 2009.
Philosophiae Doctor Title : Incomplete Financial Markets : Volatility and Transaction Costs

This paper studies the set of competitive equilibria in financial economies with intermediation costs. We consider an arbitrary dividend structure, which includes options and equity with limited liabilities. We show a general existence result and upper-hemi continuity of the equilibrium correspondence. Finally, we prove that when intermediation costs approach zero, unbounded volume of asset trades is a necessary and sufficient condition, provided that, there is no financial equilibrium without intermediation costs. JEL classification:. D41; D52; D53;
MORPHOLOGICAL VARIABILITY AMONG NIGERIAN EGGPLANTS ( Solanum L . ) AND THEIR WILD RELATIVES

Solanum L. , is the largest genus of the family Solanaceae with over 2,000 species. Considering their worldwide distribution, a remarkably high level of morphological diversity has manifested at the species, the cultivar and the generic levels. This coupled with the crossability affinities between S. melongena and other distantly related Solanum species producing fertile F1 hybrids makes classification much more complicated. This extreme diversity of the species of Solanum has been attributed to its great antiquity, as well as its extraordinary rate of speciation. This study explored and determined the levels of both inter and intra genetic relationships as well as variability among vegetable Solanum and wild related species collected from Southern Nigeria. Forty nine samples representing 12 different species of vegetable Solanum and related species were randomly collected and studied. Data obtained from measurement of thirty seven quantitative and qualitative phenotypic characters were analyzed. Analysis of these traits showed samples occurring in 11 major clusters while 2 samples remained ungrouped at a truncated line of 51%. The correlation coefficient 0.75 for the highest similarity between genotypes and the least 0.34 displayed a good separation from a conserved region of the genome. Principal Component Analysis (PCA) also revealed that fruit characters were important agronomic marker traits with a cumulative total variation of 67.96%. These characters most effectively discriminated among samples and hence are useful in establishing a simple but effective vegetable Solanum classification system in Nigeria.
A New Instrument (Scale) for Measuring the Socioeconomic Status of a Family: Preliminary Study

Research questions: Can a new scale be developed for more accurate assessment of socioeconomic status of families in India? Hypothesis: The new instrument (scale) is useful for accurate assessment of socioeconomic status of families in India. Objectives: To devsie and test a new instrument to measure socioeconomic status of families in India. Design: Cross sectional community based study. Setting: Urban rural resettlement colony slum and mobile groups. Participants: Families residing in the above areas. Study tool: Filling up of information about socioeconomic status using the newly developed scale. Results: By a process of random sampling 2095 families in the National Capital Territory of Delhi were studied to find out their SES by using this scale. It was found that 31 families (1.5%) belonged to Upper high SES 221 (10.5%) to High 291 (14.2%) to Upper middle 507 (24.2%) to Lower Middle 745 (35.6%) to Poor and 294 (14.0%) belonged to Very Poor socioeconomic category. Conclusion: The instrument serves the purpose of categorizing the families in different socio-economic strata. However it needs to be tested in other areas to determine its validity reliability and utility. (authors)
THE PREFRONTAL CORTEX AND COGNITIVE CONTROL

One of the enduring mysteries of brain function concerns the process of cognitive control. How does complex and seemingly wilful behaviour emerge from interactions between millions of neurons? This has long been suspected to depend on the prefrontal cortex — the neocortex at the anterior end of the brain — but now we are beginning to uncover its neural basis. Nearly all intended behaviour is learned and so depends on a cognitive system that can acquire and implement the ‘rules of the game’ needed to achieve a given goal in a given situation. Studies indicate that the prefrontal cortex is central in this process. It provides an infrastructure for synthesizing a diverse range of information that lays the foundation for the complex forms of behaviour observed in primates.