Miracle-dz/UniFAR-FTUs huggingface dataset:
Combining Ability and Heterosis for Grain Yield and its Component Characters in Rice (Oryza Sativa L.)

A full diallel analysis involving nine rice genotypes was used to study the combining ability and heterosis for grain yield and its component characters. The study revealed that ADT 44 was good general combiner for all the six traits studied. The parent CR1009 was also observed to be good combiner for all the traits except harvest index. The cross ADT 44 x CR 1009 exhibited highly significant positive sea effects coupled with highly significant positive heterobeltiosis and standard heterosis for number of filled grains per panicle, biomass per plant and grain yield per plant.
Dairy intake not associated with metabolic syndrome but milk and yogurt intake is inversely associated with prevalence of hypertension in middle‐aged adults

This study examined cross‐sectional associations of dairy intakes and prevalence of metabolic syndrome (MS) and the individual components of MS among 3104 participants in the Framingham Offspring Study. To be consistent with the Dietary Guidelines for Americans, dairy intakes were converted from servings per day to cup equivalents (c). We used logistic regression to calculate odds ratios (OR) between the lowest (< 0.4 c/d) compared to the highest (>3.0 c/d) quintile of diary intakes. After adjustment for age, sex, smoking, total energy and alcohol intakes, dairy intakes (OR= 0.78, (95% CI 0.60, 0.99)), as well as milk and yogurt intakes (OR=0.75 (0.58, 0.97)), were inversely associated with MS. These results were attenuated and no longer significant after adjustment for other aspects of a healthy dietary pattern (whole grain, fruit and vegetable intakes). With respect to the individual components of MS, an inverse association was observed with only milk and yogurt intakes and prevalence of hypertension (OR= 0.76, (0.57, 0.98)). This association remained significant after adjustment for aspects of a healthy dietary pattern and supplemental calcium. Although dairy intakes do not appear to be independently associated with MS, higher milk and yogurt intakes were inversely associated with prevalence of hypertension in middle aged adults. Support from General Mills, USDA (58‐1950‐7‐707), NHLBI (N01‐HC‐25195).
Applying circulating tumor DNA methylation in the diagnosis of lung cancer

Abstract Lung cancer is the leading cause of cancer-related deaths worldwide. Low dose computed tomography (LDCT) is commonly used for disease screening, with identified candidate cancerous regions further diagnosed using tissue biopsy. However, existing techniques are all invasive and unavoidably cause multiple complications. In contrast, liquid biopsy is a noninvasive, ideal surrogate for tissue biopsy that can identify circulating tumor DNA (ctDNA) containing tumorigenic signatures. It has been successfully implemented to assist treatment decisions and disease outcome prediction. ctDNA methylation, a type of lipid biopsy that profiles critical epigenetic alterations occurring during carcinogenesis, has gained increasing attention. Indeed, aberrant ctDNA methylation occurs at early stages in lung malignancy and therefore can be used as an alternative for the early diagnosis of lung cancer. In this review, we give a brief synopsis of the biological basis and detecting techniques of ctDNA methylation. We then summarize the latest progress in use of ctDNA methylation as a diagnosis biomarker. Lastly, we discuss the major issues that limit application of ctDNA methylation in the clinic, and propose possible solutions to enhance its usage.
The Limitations of Federated Learning in Sybil Settings

Federated learning over distributed multi-party data is an emerging paradigm that iteratively aggregates updates from a group of devices to train a globally shared model. Relying on a set of devices, however, opens up the door for sybil attacks: malicious devices may be controlled by a single adversary who directs these devices to attack the system. We consider the susceptibility of federated learning to sybil attacks and propose a taxonomy of sybil objectives and strategies in this setting. We describe a new DoS attack that we term training inflation and present several ways to carry out this attack. We then evaluate recent distributed ML fault tolerance proposals and show that these are insufficient to mitigate several sybil-based attacks. Finally, we introduce a defense against targeted sybil-based poisoning called FoolsGold, which identifies sybils based on the diversity of client updates. We show that FoolsGold exceeds state of the art approaches when countering several types of poisoning attacks. Our work is open source and is available online: https://github.com/DistributedML/FoolsGold
Transfer learning in hierarchical dialogue topic classification with neural networks*

Knowledge transfer between tasks can significantly improve the efficiency of machine learning algorithms. In supervised natural language understanding problems, this sort of improvement is critical since the availability of labelled data is usually scarce. In this paper we address the question of transfer learning between related topic classification tasks. A characteristic of our problem is that the tasks have a hierarchical relationship. Therefore, we introduce and validate how to implement the transfer exploiting this hierarchical structure. Our results for a real-world topic classification task show that the transfer can produce improvements in the behavior of the classifiers for some particular problems.
Resilience in the lives of sexual minority women dealing with twofold peril in India

Abstract Using a model of transactional resilience, this study examined the development of resilience in relation to stressors experienced by sexual minority women throughout the life course. Twenty-five urban women were interviewed about their experiences related to gender and sexuality in Indian society. Thematic analysis was used to analyse the data. Findings showed that women experienced implicit and explicit forms of sexism and heterosexism, making it difficult to survive in a patriarchal and heteronormative society. Several resilience factors were identified reflected in women's efforts to deal with stressors to maintain and create support. Positive characteristics and smart strategies helped participants survive stressful events and maintain healthy relations with others. They also helped them by creating a safe and positive social environment. Findings point to the need to better understand the resilience process among similar populations of women in societies like India, where patriarchy and unequal opportunities affect wellbeing and quality of life.
Electrophysiological priming effects confirm that the extrastriate symmetry network is not gated by luminance polarity

It is known that the extrastriate cortex is activated by visual symmetry. This activation generates an ERP component called the Sustained Posterior Negativity (SPN). SPN amplitude increases (i.e., becomes more negative) with repeated presentations. We exploited this SPN priming effect to test whether the extrastriate symmetry response is gated by element luminance polarity. On each trial, participants observed three stimuli (patterns of dots) in rapid succession (500 ms. with 200 ms. gaps). The patterns were either symmetrical or random. The dot elements were either black or white on a grey background. The triplet sequences either showed repeated luminance (black > black > black, or white > white > white) or changing luminance (black > white > black, or white > black > white). As predicted, SPN priming was comparable in repeated and changing luminance conditions. Therefore, symmetry with black elements is not processed independently from symmetry with white elements. Source waveform analysis confirmed that this priming happened within the extrastriate symmetry network. We conclude that the network pools information across luminance polarity channels.
Effects of spatial autocorrelation on individual tree growth model of Picea likiangensis forest in northwest of Yunnan, China.

We established a permanent plot located at Picea likiangensis forest in Shangri-La county, northwest of Yunnan province, China, from 2008 to 2012, and recorded all stems with the diameter at breast height (DBH) ≥5 cm, mapped the positions of corresponding stem bases. Because Picea likiangensis (Franch.) Pritz. Was a dominant species, it was specifically measured. We used Bayesian statistical approach to quantify a spatially autocorrelated random effects. Meanwhile, the effect of competition on individual growth was also considered . The results showed that symmetrical competition played a very important role in affecting individual growth. When spatially autocorrelated random effects were included, the model accounted for a significant proportion of the variation (R 2 = 0.87; P< 0.001). We also analyzed collected data of other tree species found in the plot, and a high level of correlation relationship was consistently found when spatial autocorrelation was included. The Bayesian approach used in this study, including the intrinsic CAR model, is a powerful technique for exploring important ecological information from forest census data. Our model for the measurement of tree growth rate may be used to simulate forest dynamics and to improve the management practices of natural forests.
Energy Forecasting with Building Characteristics Analysis

With the installation of smart meters, high resolution building-level energy consumption data become increasingly accessible, which not only provides more accurate data for energy forecasting at the aggregated level but also enables data-driven energy forecasting for individual buildings. On the one hand, individual buildings exhibit high randomness, making the forecasting problem at the building-level more challenging. On the other hand, buildings usually have their own characteristics, therefore such valuable information needs to be considered in the forecast models at the aggregation level. In this paper we investigate how unique characteristics of buildings could affect the performance of forecasting models and aim to identify defining patterns of buildings. The usefulness of the proposed approach is demonstrated using data from three real-world buildings.
Impact of a novel phytase derived from Aspergillus nidulans and expressed in transgenic Lemna minor on the performance, mineralization in bone and phosphorous excretion in laying hens.

Received: Revised: Accepted: April 24, 2014 February 11, 2015 February 14, 2015 The undigested phytates excreted through the feces causes the environmental pollution. The phytase enzyme in feed for layers increases the bioavailability of phosphorus, reduces its excretion and is also reported to be a valuable source of pigment for meat or egg. The objective of this study was to assess the effect of supplementation of phytase expressed intransgenic Lemna minor on growth performance, egg quality and mineralization levels of tibia of layers. The experiment was designed with three phytase supplemented groups (B, C and D) and one control group (A) with each 20 replicates of individually caged layers in a completely randomized design. Higher percent increase (P<0.05) in body weights have been recorded in phytase supplemented groups. Results for FCR have shown significant difference (P<0.05) in the phytase supplemented and control group. Increased egg shell thickness has been reported due supplementation of transgenic phytase. An overall significant (P<0.05) increase in egg-production, -weight and the quality of egg-protein has been observed in the layers supplemented with the transgenic phytase. The supplementation of transgenic phytase has significantly (P<0.05) enhanced the deposition of phosphorus and calcium in the bones. An overall significant (P<0.05) decrease in the excretion of phosphorus through feces has been recorded in the treatment groups. The corresponding findings on growth performance, productivity, quality of eggs, bone mineralization and decreased excretion of phosphorus through feces propose phytase derived from A. nidulans and expressed in the transgenic L. minor as an efficacious and cost effective approach. ©2015 PVJ. All rights reserved
Additional File 1 : Inference about Time-dependent Prognostic Accuracy Measures in the Presence of Competing Risks Appendix Proof of Theorem 1

We restrict our attention to a neighborhood around t and cause j i.e. N (j) t (hn) = {tk : |t − tk| < hn, δk = j} with size |N (j) t (hn)| = m (j) t . Other causes can be treated in a similar way. For simplicity, we assume that no subjects are censored. Let Bt denote the number of subjects at the start of the neighborhood i.e. at time t−hn. We assume that no failures other than cause j within neighborhood. We also assume no two subjects fail at the same time. The ordered unique event time for i-th subject is Ti = t(i). The indices of the observed event times due to cause j within the neighborhoodN (j) t (hn) are thenBt+1, Bt+2, . , Bt+m (j) t and that t(Bt+1), t(Bt+2), . , t(Bt+m(j) t ) are the corresponding ordered unique event
GOVERNMENTS FOR BETTER EDUCATION: TAKING PANEL DATA OF STATE LEGITIMACY, DEMOCRACY AND PUBLIC SERVICES

State legitimacy is increases quality of education as in the absence of it the higher education institution will make more profit and gave low quality of education. If the state legitimacy prevails in the country, then the government will be able to regulate these institutions and can bring better policies in the country. Democracy gave right to the students to study whatever they want, to get enrolled in whatever education and can have their own point of view. Democracy empowers students and thus this will contribute to the quality of the education. In any nation the number of public services given to the individuals increase the life standard in the same way if scholarships and funds should be given to the students, electricity would be provided to the educational institution then the quality of the education can be improved. So, state legitimacy, democracy and public services have significant association with the quality of education. The aim of this study was to assess the impact of three dependent variables including state legitimacy, democracy and public services on the independent variables on the quality of the education. The data was collected from ten different Asian countries including are Pakistan, India, Malaysia, Indonesia, China, Afghanistan, Nepal, Bangladesh, Turkey and Saudi Arabia. The timeline of the study is 29 years from 2019 and the data was collected from The Economic Form, The World Bank reports as well as the Transparency International. The analysis was performed by using EViews and various statistical tests were applied including ADF, LLC, cointegration test and ARLD test. The results of ARLD test showed that all three dependent variables were significantly associated with the quality of education. Literacy rate was correlated with the rise in quality of education in both long and short run, but population growth showed rise in quality of education in long run but not in the short run. Only state democracy showed positive association in the long run but showed no association in the short run. The results of our study have social, political and economic implications.
The potential of Portable Near Infrared spectroscopy 1 for assuring quality and authenticity in the food chain , using Iberian hams as 2 an example 3

This communication assesses the use of a portable near infrared (NIR) instrument to 15 measure quantitative (fatty acid profile) properties and qualitative (“Premium” and 16 “Non-premium”) categories of individual Iberian pork carcasses at the 17 slaughterhouse. Acorn-fed Iberian pigs have more unsaturated fats than pigs fed 18 conventional compound feed. Recent advances in miniaturisation have led to a 19 number of handheld NIR devices being developed, allowing processing decisions to 20 be made earlier, significantly reducing time and costs. The most common methods 21 used for assessing quality and authenticity of Iberian hams are analysis of the fatty22 acid composition of subcutaneous fat using gas chromatography (GC) and DNA 23 analysis. In this study, NIR calibrations for fatty acids and classification as premium 24 or non-premium ham, based on carcass fat measured in-situ, were developed using 25 a portable NIR spectrometer. The accuracy of the quantitative equations was 26 evaluated through the standard error of cross validation (SECV) or standard error of 27 prediction (SEP) of 0.84 for palmitic acid (C16:0), 0.94 for stearic acid (C18:0), 1.47 28 for oleic acid (C18:1) and 0.58 for linoleic acid (C18:2). Qualitative calibrations 29 provided acceptable results, with up to 98% of samples (n=234) correctly classified 30 with probabilities >= 0.9. Results indicated a portable NIR instrument has the 31 potential to be used to measure quality and authenticity of Iberian pork carcasses. 32
Mechanisms of Winter Precipitation Variability in the European–Mediterranean Region Associated with the North Atlantic Oscillation

The physical mechanisms whereby the mean and transient circulation anomalies associated with the North Atlantic Oscillation (NAO) drive winter mean precipitation anomalies across the North Atlantic Ocean, Europe, and the Mediterranean Sea region are investigated using the European Centre for Medium-Range Weather Forecasts interim reanalysis. A moisture budget decomposition is used to identify the contribution of the anomalies in evaporation, the mean flow, storm tracks and the role of moisture convergence and advection. Over the eastern North Atlantic, Europe, and the Mediterranean, precipitation anomalies are primarily driven by the mean flow anomalies with, for a positive NAO, anomalous moist advection causing enhanced precipitation in the northern British Isles and Scandinavia and anomalous mean flow moisture divergence causing drying over continental Europe and the Mediterranean region. Transient eddy moisture fluxes work primarily to oppose the anomalies in precipitation minus evaporation generated by the mean flow, but shifts in storm-track location and intensity help to explain regional details of the precipitation anomaly pattern. The extreme seasonal precipitation anomalies that occurred during the two winters with the most positive (1988/89) and negative (2009/10) NAO indices are also explained by NAO-associated mean flow moisture convergence anomalies.
A Simple and Rapid Dual‑fluorescence Viability Assay for Microalgae

A dual-fluorescence method was developed to assay the viability of microalgae and was tested in five strains of cyanobacteria and a green algae, Chlamydomonas reinhardtii. Fluorescence of SYTOX Green, a dye that only penetrates damaged cell membranes, and autofluorescence were observed simultaneously, allowing the discrimination of live and dead cells. We found good correlation in five of six strains between the real percentage of live microalgae in the samples and that measured by the double-fluorescence method. We conclude that our method provides a simple and rapid technique for assessing the viability of microalgae.
Rethinking Modal-oriented Label Correlations for Multi-modal Multi-label Learning

Multi-modal multi-label learning provides a fundamental framework for complex objects, which can be represented with multiple modalities and annotated with multiple labels simultaneously. Different modalities can usually provide complementary information, which may lead to improved performance. What’s more, exploiting label correlations is crucially important to multi-label learning. However, most existing multi-label learning approaches do not sufficiently consider the complementary information among different modalities. In this paper, we propose a novel end-to-end deep learning framework named Rethinking Modal-oriented Label Correlations (RMLC), which sequentially polish the label prediction with each individual modality. In order to explicitly account for the correlated prediction of multiple labels, RMLC leverages an efficient sequential modal-based exploration to rethink label correlations. The final prediction of each label involves the collaboration between modal-specific prediction and the prediction of other labels based on cross-modal interaction. Comprehensive experiments on benchmark datasets validate the effectiveness and competitiveness of the proposed RMLC approach.
Changing Landscape of Global Value Chains: Redefining role of Asian Economies

The paper looks at changing nature and pattern of global value chains (GVCs) integration in Asian economies, mainly East, South-East and South Asian ones. GVCs began as regional chains from Japan and then flourished to other countries, and so the theories explaining GVCs also changed according to the trade and industrial patterns in such economies. Changes in theories have moved from flying geese to fragmentation and agglomeration theory to upgrading in GVCs the pattern of snakes and spiders, which are all now further undergoing transformations in some of their predications due to widespread interplay of digital technologies, fourth industrial revolution (with more adoption of standards in intellectual property and artificial intelligence). The paper studies Asian countries’ changing foreign trade and investment policies as well as industrial strategies to understand how well they are equipped to deal with such changing patterns. There are now movements to promote domestic manufacturing to move up value chains rather than purely relying on imported contents (viz. ‘Made in China 2025’ initiative in China, ‘Make in India’ initiative in India). In fact, since 2013-14, some Asian countries are now experiencing more decline in foreign value content share of gross exports or backward linkages, as compared to some European countries, using TiVA Database. For example, the share has declined for China from 21% in 2012 to 17% in 2016, and for India from 25% to 16% over the same period, suggesting more rise in domestic value added content. The paper estimates changes in Asian GVCs in terms of backward and forward linkages in comparison to European and American economies. Although China-centered GVCs is slowing down, but due to digitalization and use of smart manufacturing and changes in trade policies, many developing countries of Asia mainly China is all set to emerge with different look in GVCs. US and EU value chains have matured much leaving much ground for Asia to take over and build new paradigms even in manufacturing. The paper suggests way of how policies of some Asian countries should be adjusted so that they can place themselves in their most promising sectors in global/regional value chains. Fellow, Indian Council for Research on International Economic Relations (ICRIER), New Delhi, India. Email address: ngupta@icrier.res.in The author would like to thank Ms.Varsha Jain, Research Assistant, ICRIER, for compiling the data and policy documents.