Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Learning Long- and Short-Term User Literal-Preference with Multimodal Hierarchical Transformer Network for Personalized Image Caption

Personalized image caption, a natural extension of the standard image caption task, requires to generate brief image descriptions tailored for users' writing style and traits, and is more practical to meet users' real demands. Only a few recent studies shed light on this crucial task and learn static user representations to capture their long-term literal-preference. However, it is insufficient to achieve satisfactory performance due to the intrinsic existence of not only long-term user literal-preference, but also short-term literal-preference which is associated with users' recent states. To bridge this gap, we develop a novel multimodal hierarchical transformer network (MHTN) for personalized image caption in this paper. It learns short-term user literal-preference based on users' recent captions through a short-term user encoder at the low level. And at the high level, the multimodal encoder integrates target image representations with short-term literal-preference, as well as long-term literal-preference learned from user IDs. These two encoders enjoy the advantages of the powerful transformer networks. Extensive experiments on two real datasets show the effectiveness of considering two types of user literal-preference simultaneously and better performance over the state-of-the-art models

Information Design in Multi-Agent Reinforcement Learning

Reinforcement learning (RL) mimics how humans and animals interact with the environment. The setting is somewhat idealized because, in actual tasks, other agents in the environment have their own goals and behave adaptively to the ego agent. To thrive in those environments, the agent needs to influence other agents so their actions become more helpful and less harmful. Research in computational economics distills two ways to influence others directly: by providing tangible goods (mechanism design) and by providing information (information design). This work investigates information design problems for a group of RL agents. The main challenges are two-fold. One is the information provided will immediately affect the transition of the agent trajectories, which introduces additional non-stationarity. The other is the information can be ignored, so the sender must provide information that the receivers are willing to respect. We formulate the Markov signaling game, and develop the notions of signaling gradient and the extended obedience constraints that address these challenges. Our algorithm is efficient on various mixed-motive tasks and provides further insights into computational economics. Our code is available at https://github.com/YueLin301/InformationDesignMARL

Nutritional modulation of health, egg quality and environmental pollution of the layers

World egg production and consumption have been increasing for the past decades. Traditional strategies in poultry nutrition have made vital contributions to this great growth in quantity. However, current global issues should be considered in modern egg production such as growing populations and food security, food safety and quality, limited resources and environmental problems. The development of knowledge of poultry nutrition and modern biotechnology provides novel nutritional approaches to closely fit the requirement of pullets and laying hens, which will consequently decrease the nutrition emissions and maintain the lower cost of feed. Nutrition has also been widely accepted as a strategy to influence health and diseases of laying hens. The maintenance of good health is an important prerequisite for improving productivity and egg quality. In addition, there are many measures and strategies for minimizing the incidence of egg defects and providing a choice of lifestyle to enhance human health. This paper reviews current research progress on developing innovative technologies and strategies to maximize animal health and performance, improve the quality of egg products and minimize pollution caused by poultry production

Day-Ahead PM2.5 Concentration Forecasting Using WT-VMD Based Decomposition Method and Back Propagation Neural Network Improved by Differential Evolution

Accurate PM2.5 concentration forecasting is crucial for protecting public health and atmospheric environment. However, the intermittent and unstable nature of PM2.5 concentration series makes its forecasting become a very difficult task. In order to improve the forecast accuracy of PM2.5 concentration, this paper proposes a hybrid model based on wavelet transform (WT), variational mode decomposition (VMD) and back propagation (BP) neural network optimized by differential evolution (DE) algorithm. Firstly, WT is employed to disassemble the PM2.5 concentration series into a number of subsets with different frequencies. Secondly, VMD is applied to decompose each subset into a set of variational modes (VMs). Thirdly, DE-BP model is utilized to forecast all the VMs. Fourthly, the forecast value of each subset is obtained through aggregating the forecast results of all the VMs obtained from VMD decomposition of this subset. Finally, the final forecast series of PM2.5 concentration is obtained by adding up the forecast values of all subsets. Two PM2.5 concentration series collected from Wuhan and Tianjin, respectively, located in China are used to test the effectiveness of the proposed model. The results demonstrate that the proposed model outperforms all the other considered models in this paper

Effect of dietary protein sources and storage temperatures on egg internal quality of stored shell eggs

This study was conducted to evaluate the effects of various protein sources (soybean meal, SBM; cottonseed protein, CSP; double-zero rapeseed meal, DRM) on the internal quality (Haugh unit, yolk index, albumen pH, yolk hardness and yolk springiness) of eggs when stored at either 4 or 28°C for 28 d. A total of 288 laying hens (32 wk of age) were randomly allotted to 6 treatment groups (4 replicates per treatment) and fed diets containing SBM, CSP, or DRM individually or in combination with equal crude protein content (SBM-CSP, SBM-DRM, and CSP-DRM) as the protein ingredient(s). A 6 × 2 factorial arrangement was employed with dietary types and storage temperatures (4 and 28°C) as the main effects. After 12 wk of diet feeding, a total of 216 eggs was collected for egg internal quality determination. The results showed as follows: 1) lower egg quality was observed in the DRM group compared with the other groups when stored at 4 and 28°C for 28 d (P < 0.05), while there was no difference in egg internal quality among the other groups. 2) The CSP diet resulted in higher yolk hardness compared with the other diets when eggs were stored at 4°C for 28 d (P < 0.05). Lower Haugh unit was observed in the DRM and SBM-DRM groups compared with the other groups when eggs were stored for 28 d at 4°C (P < 0.05). 3) Yolk breakage occurred in the DRM group and eggs could not be analyzed for egg internal quality when stored at 28°C for 28 d. The overall results indicated that CSP or DRM as the sole dietary protein source for laying hens may adversely affect the internal quality of stored eggs as compared with the SBM diet, and half replacement of CSP combined with SBM may maintain similar egg quality to SBM diet alone for eggs stored under refrigerated conditions

Macular choroidal thickness in highly myopic women during pregnancy and postpartum: a longitudinal study

Abstract Background High myopia, a cause of serious visual impairment, is a significant global public health concern. We investigate longitudinal changes in macular choroidal thickness (CT) during pregnancy and 6-months postpartum in women with high myopia (HM). Methods A prospective longitudinal study was conducted in HM-pregnant women during the course of pregnancy (n = 42 eyes, 42 patients) and 6 months postpartum (n = 40 eyes, 40 patients, two cases lost).Macular CT was measured via enhanced-depth imaging (EDI)-optical coherence tomography (OCT) (EDI-OCT). Intraocular pressure (IOP), axial length (AL), refractive error, mean arterial pressure (MAP), mean ocular perfusion pressure (MOPP), and body mass index (BMI) were also measured. Results Macular CTs of HM pregnant women (214.3 ± 52.3 μm) had increased significantly during the third trimester of pregnancy compared with postpartum women (192.7 ± 51.9 μm, p = 0.014). No significant differences in AL, refractive error, or MAP were found between pregnant and postpartum groups (p > 0.05 for all parameters).During pregnancy, macular CT was negatively correlated with AL (first trimester: p = 0.010; second trimester: p = 0.013; and third trimester: p = 0.008) and positively correlated with refractive error (first trimester: p = 0.038; second trimester: p = 0.024; and third trimester: p = 0.010). No correlations between macular CT and age, IOP, MOPP, MAP, or BMI were found. Conclusions Our study revealed the presence of a significantly thicker choroid during the third trimester of pregnancy compared with 6-mo postpartum in HM women. Macular CT positively correlated with refractive error and negatively correlated with AL during pregnancy, but did not correlate with gestational age, MOPP, IOP, MAP, or BMI