Miracle-dz/UniFAR-FTUs huggingface dataset:
Genome-wide analysis of basic helix-loop-helix superfamily members in peach

The basic helix-loop-helix (bHLH) transcription factor family is a superfamily found in all eukaryotes that plays important roles in regulating growth and development. Over the past several decades, many bHLH superfamily genes have been identified and characterized in herbaceous and woody plants. However, the genes belonging to the bHLH superfamily in peach (Prunus persica) have not yet been comprehensively identified and characterized. Here, we identified 95 members of the bHLH superfamily in the peach genome, and these genes were classified into 19 subfamilies based on a phylogenetic comparison with bHLH proteins from Arabidopsis. The members within each subfamily were highly conserved according to the analysis of motif compositions and exon/intron organizations. The 95 bHLH genes were unevenly distributed on chromosomes 1 to 8 of the peach genome. We identified 57 pairs of bHLH members that were orthologous between peach and Arabidopsis. Additionally, 48 pairs of paralogous bHLH genes were identified on the eight chromosomes of the peach genome. Coupled with relative expression analysis of bHLH genes in red-fleshed peach fruit at five developmental stages, we identified several bHLH genes that might be involved in fruit development and anthocyanin biosynthesis. This study provides insight into the molecular mechanisms through which these genes are involved in the regulation of biological and biochemical processes in peach and lays the foundation for further studies on these genes.
A prospective study of prepregnancy dietary fat intake and risk of gestational diabetes.

BACKGROUND Fatty acids play a vital role in glucose homeostasis; however, studies on habitual dietary fat intakes and gestational diabetes mellitus (GDM) risk are limited and provide conflicting findings. OBJECTIVE We determined whether the total amount and the type and source of prepregnancy dietary fats are related to risk of GDM. DESIGN A prospective study was conducted in 13,475 women who reported a singleton pregnancy between 1991 and 2001 in the Nurses' Health Study II. In these women, 860 incident GDM cases were reported. The adjusted RR of GDM was estimated for quintiles of total fat, specific fat, and the source of fat intakes by pooled logistic regression. RESULTS Higher animal fat and cholesterol intakes were significantly associated with increased GDM risk. Across increasing quintiles of animal fat, RRs (95% CIs) for GDM were 1.00 (reference), 1.55 (1.20, 1.98), 1.43 (1.09, 1.88), 1.40 (1.04, 1.89), and 1.88 (1.36, 2.60) (P-trend = 0.05). Corresponding RRs (95% CIs) for dietary cholesterol were 1.00 (reference), 1.08 (0.84, 1.32), 1.02 (0.78, 1.29), 1.20 (0.93, 1.55), and 1.45 (1.11, 1.89) (P-trend = 0.04). The substitution of 5% of energy from animal fat for an equal percentage of energy from carbohydrates was associated with significantly increased risk of GDM [RR (95% CI): 1.13 (1.08, 1.18); P < 0.0001]. No significant associations were observed between dietary polyunsaturated fat, monounsaturated fat, or trans fat intakes and GDM risk. CONCLUSION Higher prepregnancy intakes of animal fat and cholesterol were associated with elevated GDM risk.
Mining Graphlet Counts in Online Social Networks

Counting subgraphs is a fundamental analysis task for online social networks (OSNs). Given the sheer size and restricted access of online social network data, efficient computation of subgraph counts is highly challenging. Although a number of algorithms have been proposed to estimate the relative counts of subgraphs in OSNs with restricted access, there are only few works which try to solve a more general problem, i.e., counting subgraph frequencies. In this paper, we propose an efficient random walk-based framework to estimate the subgraph counts. Our framework generates samples by leveraging consecutive steps of the random walk as well as by observing neighbors of visited nodes. Using the importance sampling technique, we derive unbiased estimators of the subgraph counts. To make better use of the degree information of visited nodes, we also design an improved estimator, which increases the efficiency of the estimate at no additional cost. We conduct extensive experimental evaluation on real-world OSNs to confirm our theoretical claims. The experiment results show that our estimators are unbiased, accurate, efficient and better than the state-of-the-art algorithm. For the Weibo graph with more than 58 million nodes, our method produces estimate of triangle count with an error less than 5% using only 20 thousands sampled nodes. Detailed comparison with the state-of-the-art method demonstrates that our algorithm is 4 to 5 times more accurate.
Predict what app to use next time only consider time and latest used app context

With the increasing number of mobile applications and the increase of the capacity of mobile phone, people use more and more mobile applications. A variety of applications enrich our lives, and makes us manage our screens and folders become difficult at the same time. If we can predict that the user will use the application, which will help to improve the user experience. In this paper, we only use the latest used app and time context information, in the case of fine-grained time, and propose improved Bayesian network model and linear model. We use the MDC dataset for this research. The evaluation results show that the hit rate of this model under the same dataset can increase the accuracy rate of about 9% compared to the baseline model.
Correlation between shift-work-related sleep problems and heavy drinking in Japanese male factory workers.

AIMS To investigate the effects of shift work on increased alcohol intake associated with poor sleep quality. METHODS This cross-sectional survey evaluated the correlation between work schedule, poor sleep quality and heavy drinking among 909 factory workers aged 35-54 years in Japan. Subjects included 530 day workers, 72 shift workers who did not work at night and 290 shift workers who engaged in night work. Heavy drinking was defined as a mean volume of alcohol consumption exceeding 60 g/day. RESULTS Compared with other workers, night-shift workers who suffered poor sleep quality exhibited the highest frequency of heavy drinking (17.6%). Multiple logistic regression analysis demonstrated that compared with day workers with good sleep, night-shift workers who experienced poor sleep had more than twice the odds of heavy alcohol consumption (odds ratio 2.17 [95% confidence interval (CI), 1.20-3.93]). Shift workers who did not work at night and day workers with poor sleep were not at increased odds of heavy drinking. CONCLUSION Shift workers who engage in night work may try to modify their health behavior to cope with sleep problems. Such modification may be a risk factor for heavy drinking.
Novel Digital Features Discriminate Between Drought Resistant and Drought Sensitive Rice Under Controlled and Field Conditions

Dynamic quantification of drought response is a key issue both for variety selection and for functional genetic study of rice drought resistance. Traditional assessment of drought resistance traits, such as stay-green and leaf-rolling, has utilized manual measurements, that are often subjective, error-prone, poorly quantified and time consuming. To relieve this phenotyping bottleneck, we demonstrate a feasible, robust and non-destructive method that dynamically quantifies response to drought, under both controlled and field conditions. Firstly, RGB images of individual rice plants at different growth points were analyzed to derive 4 features that were influenced by imposition of drought. These include a feature related to the ability to stay green, which we termed greenness plant area ratio (GPAR) and 3 shape descriptors [total plant area/bounding rectangle area ratio (TBR), perimeter area ratio (PAR) and total plant area/convex hull area ratio (TCR)]. Experiments showed that these 4 features were capable of discriminating reliably between drought resistant and drought sensitive accessions, and dynamically quantifying the drought response under controlled conditions across time (at either daily or half hourly time intervals). We compared the 3 shape descriptors and concluded that PAR was more robust and sensitive to leaf-rolling than the other shape descriptors. In addition, PAR and GPAR proved to be effective in quantification of drought response in the field. Moreover, the values obtained in field experiments using the collection of rice varieties were correlated with those derived from pot-based experiments. The general applicability of the algorithms is demonstrated by their ability to probe archival Miscanthus data previously collected on an independent platform. In conclusion, this image-based technology is robust providing a platform-independent tool for quantifying drought response that should be of general utility for breeding and functional genomics in future.
Stereo disparity estimation using discrete orthogonal moments

In the article we present various theoretical and experimental approaches to the problem of stereo matching and disparity estimation. We propose to calculate stereo disparity in the moments space, but we also present correlation based method. In order to calculate disparity vector we decided to use discrete orthogonal moments of Tchebichef, Zernike and Legendre. In our research of stereo disparity estimation all of these moments were tested and compared. In the article we also propose the original method of determining the global displacement vector between the stereopair images in order to find the common part of these images (adequate for matching) and the margins of these stereo images. Experimental results confirm effectiveness of the presented methods of determining stereo disparity and stereo matching for robotics and machine vision applications.
Optimizing color transfer using color similarity measurement

Color transfer algorithms alter the color appearance in the source image by borrowing colors from the target image. In this paper, we present a simple yet effective generalized color transfer algorithm, taking into consideration the influences contributed from both the source and target images. We introduce the Gaussian membership function as our first color similarity measurement. This function aims at balancing the degree of similarity of color distributions between source and resultant images and that between target and resultant images, respectively. With regard to the second color similarity measurement, we combine color histogram with the statistic concept of the correlation. Referring to different weights, the histogram correlation method derives correlations at each color channel between source and resultant images and those between target and resultant images. Color transfer is optimized by automatically stabilizing correlations before producing the final color transfer resultant image. Experimental results demonstrate that our proposed algorithm automatically takes into consideration the source and target images producing a visually plausible result. The statics comparison shows that our scheme outperforms current state-of-the-art methods.
A Boosting Framework of Factorization Machine

Recently, Factorization Machines (FM) has become more and more popular for recommendation systems, due to its effectiveness in finding informative interactions between features. Usually, the weights for the interactions is learnt as a low rank weight matrix, which is formulated as an inner product of two low rank matrices. This low rank can help improve the generalization ability of Factorization Machines. However, to choose the rank properly, it usually needs to run the algorithm for many times using different ranks, which clearly is inefficient for some large-scale datasets. To alleviate this issue, we propose an Adaptive Boosting framework of Factorization Machines (AdaFM), which can adaptively search for proper ranks for different datasets without re-training. Instead of using a fixed rank for FM, the proposed algorithm will adaptively gradually increases its rank according to its performance until the performance does not grow, using boosting strategy. To verify the performance of our proposed framework, we conduct an extensive set of experiments on many real-world datasets. Encouraging empirical results shows that the proposed algorithms are generally more effective than state-of-the-art other Factorization Machines.
Dietary patterns and all-cause, cancer, and cardiovascular disease mortality in Japanese men and women: The Japan public health center-based prospective study

Objective A meta-analysis showed an inverse association of a prudent/healthy dietary pattern with all-cause mortality and no association of a western/unhealthy dietary pattern. However, the association of distinctive dietary patterns of Japanese population with mortality remains unclear. We prospectively investigated the association between dietary patterns and all-cause, cancer, and cardiovascular disease mortality among Japanese adults. Methods Participants were 36,737 men and 44,983 women aged 45–74 years who participated in the second survey of the Japan Public Health Center-based Prospective Study (1995–1998) and who had no history of serious disease. Dietary patterns were derived from principal component analysis of the consumption of 134 food and beverage items ascertained by a food frequency questionnaire. Hazard ratios of death from the second survey to December 2012 were estimated using cox proportional hazard regression analysis. Results A prudent dietary pattern, which was characterized by high intake of vegetables, fruit, soy products, potatoes, seaweed, mushrooms, and fish, was significantly associated with decreased risk of all-cause and cardiovascular disease mortality. The multivariable-adjusted hazard ratios (95% confidence intervals) of all-cause and cardiovascular disease mortality for the highest versus lowest quartile of the prudent dietary pattern score were 0.82 (0.77 to 0.86) and 0.72 (0.64 to 0.79), respectively (P for trend <0.001 in both). A Westernized dietary pattern, characterized by high intake of meat, processed meat, bread, and dairy products, was also inversely associated with risk of all-cause, cancer, and cardiovascular disease mortality. A traditional Japanese dietary pattern was not associated with these risks. Conclusions The prudent and Westernized dietary patterns were associated with a decreased risk of all-cause and cardiovascular disease mortality in Japanese adults.
Robust multi-robot cooperation through dynamic task allocation and precaution routines

In this paper, we present the design and implementation of a multi-robot cooperation framework to collectively execute inter-dependent tasks of an overall complex mission requiring diverse capabilities. Given a heterogeneous team of robots and task dependencies, the proposed framework provides a distributed mechanism for assigning tasks to robots in an order that efficiently completes the mission. The approach is robust to unreliable communication and robot failures. It is a distributed auction-based approach, and therefore scalable. In order to obtain optimal allocations, effective bid evaluations are needed. Additionally to maintain optimality in noisy environments, dynamic re-allocations of tasks are needed as implemented in dynamic task selection and coalition maintenance scheme that we propose. Real-time contingencies are handled by recovery routines, called Plan B precautions in our framework. Here, in this paper, we present performance results of our framework for robustness in simulations that include variable message loss rates and robot failures. Experiments illustrate robustness of our approach against several contingencies.
Fipronil recognition by the FA1 site of human serum albumin

Fipronil is a broad‐spectrum pesticide widely used in agriculture, horticulture, and forestry. Because fipronil can cause a variety of toxic effects in animals and humans, its use is authorized as a pesticide in veterinary medicinal products for pets, but not for the treatment of livestock animals whose products are intended for consumption. Recently, however, the presence of fipronil residues has been detected in the eggs and meat of layer hens from farms located in different European countries. Given the relevance of fipronil toxicity for human health, it is important to gain information concerning its fate in the human body, including its binding mode to human serum albumin (HSA), the most abundant protein in plasma. Here, the inhibition of heme‐Fe(III) binding to the fatty acid site 1 (FA1) of HSA by fipronil is reported. Docking simulations support functional data, indicating that the FA1 site is the preferential cleft for fipronil recognition by HSA. The affinity of fipronil for HSA (Kf = 1.9 × 10−6 M, at pH 7.3, and 20.0°C) may be relevant in vivo. Indeed, HSA could play a pivotal role in fipronil transport and scavenging, thus reducing the pesticide‐free plasmatic levels, with consequent reduced systemic toxicity. In turn, fipronil binding to the FA1 site of HSA could impair the recognition of endogenous and exogenous molecules.
Can mutation‐mediated effects occurring early in development cause long‐term seizure susceptibility in genetic generalized epilepsies?

Epilepsy has a strong genetic component, with an ever‐increasing number of disease‐causing genes being discovered. Most epilepsy‐causing mutations are germ line and thus present from conception. These mutations are therefore well positioned to have a deleterious impact during early development. Here we review studies that investigate the role of genetic lesions within the early developmental window, specifically focusing on genetic generalized epilepsy (GGE). Literature on the potential pathogenic role of sub‐mesoscopic structural changes in GGE is also reviewed. Evidence from rodent models of genetic epilepsy support the idea that functional and structural changes can occur in early development, leading to altered seizure susceptibility into adulthood. Both animal and human studies suggest that sub‐mesoscopic structural changes occur in GGE. The existence of sub‐mesoscopic structural changes prior to seizure onset may act as biomarkers of excitability in genetic epilepsies. We also propose that presymptomatic treatment may be essential for limiting the long‐term consequences of disease‐causing mutations in genetic epilepsies.
Habitat specialization through germination cueing: a comparative study of herbs from forests and open habitats.

BACKGROUND AND AIMS This study examined the adaptive association between seed germination ecology and specialization to either forest or open habitats across a range of evolutionary lineages of seed plants, in order to test the hypotheses that (1) species' specialization to open vs. shaded habitats is consistently accompanied by specialization in their regeneration niche; and (2) species are thereby adapted to utilize different windows of opportunity in time (season) and space (habitat). METHODS Seed germination response to temperature, light and stratification was tested for 17 congeneric pairs, each consisting of one forest species and one open-habitat species. A factorial design was used with temperature levels and diurnal temperature variation (10 °C constant, 15-5 °C fluctuating, 20 °C constant, 25-15 °C fluctuating), and two light levels (light and darkness) and a cold stratification treatment. The congeneric species pair design took phylogenetic dependence into account. KEY RESULTS Species from open habitats germinated better at high temperatures, whereas forest species performed equally well at low and high temperatures. Forest species tended to germinate only after a period of cold stratification that could break dormancy, while species from open habitats generally germinated without cold stratification. The empirically derived germination strategies correspond quite well with establishment opportunities for forest and open-habitat plant species in nature. CONCLUSIONS Annual changes in temperature and light regime in temperate forest delimit windows of opportunity for germination and establishment. Germination strategies of forest plants are adaptations to utilize such narrow windows in time. Conversely, lack of fit between germination ecology and environment may explain why species of open habitats generally fail to establish in forests. Germination strategy should be considered an important mechanism for habitat specialization in temperate herbs to forest habitats. The findings strongly suggest that phases in the plant life cycle other than the established phase should be considered important in adaptive specialization.
Autophagic Marker MAP1LC3B Expression Levels Are Associated with Carotid Atherosclerosis Symptomatology

Objectives The mechanism by which atheroma plaque becomes unstable is not completely understood to date but analysis of differentially expressed genes in stable versus unstable plaques may provide clues. This will be crucial toward disclosing the mechanistic basis of plaque instability, and may help to identify prognostic biomarkers for ischaemic events. The objective of our study was to identify differences in expression levels of 59 selected genes between symptomatic patients (unstable plaques) and asymptomatic patients (stable plaques). Methods 80 carotid plaques obtained by carotid endarterectomy and classified as symptomatic (>70% stenosis) or asymptomatic (>80% stenosis) were used in this study. The expression levels of 59 genes were quantified by qPCR on RNA extracted from the carotid plaques obtained by endarterectomy and analyzed by means of various bioinformatic tools. Results Several genes associated with autophagy pathways displayed differential expression levels between asymptomatic and symptomatic (i.e. MAP1LC3B, RAB24, EVA1A). In particular, mRNA levels of MAP1LC3B, an autophagic marker, showed a 5−fold decrease in symptomatic samples, which was confirmed in protein blots. Immune system−related factors and endoplasmic reticulum-associated markers (i.e. ERP27, ITPR1, ERO1LB, TIMP1, IL12B) emerged as differently expressed genes between asymptomatic and symptomatic patients. Conclusions Carotid atherosclerotic plaques in which MAP1LC3B is underexpressed would not be able to benefit from MAP1LC3B−associated autophagy. This may lead to accumulation of dead cells at lesion site with subsequent plaque destabilization leading to cerebrovascular events. Identified biomarkers and network interactions may represent novel targets for development of treatments against plaque destabilization and thus for the prevention of cerebrovascular events.