Adaptive Environment Modeling Based Reinforcement Learning for Collision Avoidance in Complex Scenes

The major challenges of collision avoidance for robot navigation in crowded scenes lie in accurate environment modeling, fast perceptions, and trustworthy motion planning policies. This paper presents a novel adaptive environment model based collision avoidance reinforcement learning (i.e., AEMCARL) framework for an unmanned robot to achieve collision-free motions in challenging navigation scenarios. The novelty of this work is threefold: (1) developing a hierarchical network of gated-recurrent-unit (GRU) for environment modeling; (2) developing an adaptive perception mechanism with an attention module; (3) developing an adaptive reward function for the reinforcement learning (RL) framework to jointly train the environment model, perception function and motion planning policy. The proposed method is tested with the Gym-Gazebo simulator and a group of robots (Husky and Turtlebot) under various crowded scenes. Both simulation and experimental results have demonstrated the superior performance of the proposed method over baseline methods.Comment: accepted by IROS202

Edge Accelerated Robot Navigation with Hierarchical Motion Planning

Low-cost autonomous robots suffer from limited onboard computing power, resulting in excessive computation time when navigating in cluttered environments. This paper presents Edge Accelerated Robot Navigation, or EARN for short, to achieve real-time collision avoidance by adopting hierarchical motion planning (HMP). In contrast to existing local or edge motion planning solutions that ignore the interdependency between low-level motion planning and high-level resource allocation, EARN adopts model predictive switching (MPS) that maximizes the expected switching gain w.r.t. robot states and actions under computation and communication resource constraints. As such, each robot can dynamically switch between a point-mass motion planner executed locally to guarantee safety (e.g., path-following) and a full-shape motion planner executed non-locally to guarantee efficiency (e.g., overtaking). The crux to EARN is a two-time scale integrated decision-planning algorithm based on bilevel mixed-integer optimization, and a fast conditional collision avoidance algorithm based on penalty dual decomposition. We validate the performance of EARN in indoor simulation, outdoor simulation, and real-world environments. Experiments show that EARN achieves significantly smaller navigation time and collision ratios than state-of-the-art navigation approaches.Comment: 12 pages, 14 figures, 1 table, submitted to IEEE for possible publicatio

Towards artificial general intelligence via a multimodal foundation model

The fundamental goal of artificial intelligence (AI) is to mimic the core cognitive activities of human. Despite tremendous success in the AI research, most of existing methods have only single-cognitive ability. To overcome this limitation and take a solid step towards artificial general intelligence (AGI), we develop a foundation model pre-trained with huge multimodal data, which can be quickly adapted for various downstream cognitive tasks. To achieve this goal, we propose to pre-train our foundation model by self-supervised learning with weak semantic correlation data crawled from the Internet and show that promising results can be obtained on a wide range of downstream tasks. Particularly, with the developed model-interpretability tools, we demonstrate that strong imagination ability is now possessed by our foundation model. We believe that our work makes a transformative stride towards AGI, from our common practice of "weak or narrow AI" to that of "strong or generalized AI".Comment: Published by Nature Communications, see https://www.nature.com/articles/s41467-022-30761-

Advances in omics research on peanut response to biotic stresses

Peanut growth, development, and eventual production are constrained by biotic and abiotic stresses resulting in serious economic losses. To understand the response and tolerance mechanism of peanut to biotic and abiotic stresses, high-throughput Omics approaches have been applied in peanut research. Integrated Omics approaches are essential for elucidating the temporal and spatial changes that occur in peanut facing different stresses. The integration of functional genomics with other Omics highlights the relationships between peanut genomes and phenotypes under specific stress conditions. In this review, we focus on research on peanut biotic stresses. Here we review the primary types of biotic stresses that threaten sustainable peanut production, the multi-Omics technologies for peanut research and breeding, and the recent advances in various peanut Omics under biotic stresses, including genomics, transcriptomics, proteomics, metabolomics, miRNAomics, epigenomics and phenomics, for identification of biotic stress-related genes, proteins, metabolites and their networks as well as the development of potential traits. We also discuss the challenges, opportunities, and future directions for peanut Omics under biotic stresses, aiming sustainable food production. The Omics knowledge is instrumental for improving peanut tolerance to cope with various biotic stresses and for meeting the food demands of the exponentially growing global population

Ukuran Organ Sistem Reproduksi Itik Jantan Yang Disuplementasi Probiotik Mep+ Berbagai Dosis Selama 30 Hari

Probiotics MEP+ can increase fowl weight and weft efficiency, therefore it is important to know probiotics MEP+ effect at different dosage toward reproduction aspect. This research aimed to examine duck reproduction organ size suplemented with probiotics MEP+ with different dosage within 30 days. This research used Completely Randomized Design (CRD) with 4 treatments with different dosages within 30 days which was without probiotic\u27s application or control (K), 0,75 ml/kg wefts (P1) dose, 1,5 ml/kg wefts (P2) dose, a n d 3 ml/kg wefts (P3) dose. Each treatment repeated 8 times. Total 40 ducks raised in floor dry cage system. At 31st day of treatment duck reproduction system organ was measured. Whole results show increase average data (±SD) for weight of both right and left testis, and liver weight with highly probiotics dosage it, however the analysis result statistic not significant (P>0,05) except weight of right left testis with duck weight or gonadosomatic indeks (GSI) were very significant (P<0,01) among all treatment at different dosages was compared control. The results is confirmed that probiotic\u27s MEP+ treatment with different dosages within 30 days gave no effect towards duck reproduction system organ size except to gonadosomatic indeks (GSI) male duck

Profil dan Learning Outcomes Lulusan Pendidikan Akuntansi sebagai Referensi Lptk dalam Menyiapkan Guru Akuntansi Bermutu

The objective of this research is to stipulate the profile and learning outcome of the graduates of the Study Program of Accounting Education, the Faculty of Teacher Training and Education, Sebelas Maret University. It is intended to help the Indonesian government to prepare the qualified teacher of Accounting subject matter according to the perceptions of alumni, lecturers, stakeholders, profession associations, and decision makers.The data sources of research were 96 students, 248 alumni, 15 lecturers, 15 stakeholders, Association of Accounting Educator Profession of Indonesia, and Chief of the Study Program of Accounting Education, Sebelas Maret University. The data of research were collected through observation, documentation, and FGD. They were analyzed by using the qualitative approach.The results of research show that (1) the profile of the graduates of the Study Program of Accounting Education includes the prospective teachers of Accounting subject matter for Vocational High Schools and Senior Secondary Schools who major in Introduction to Accounting and Finance, Number Processing/Spreadsheet, Banking, Accounting of Service and Trading Company, Financial Accounting, Accounting Computer, Accounting of Manufacturing Company, and Tax Administration; prospective Accounting instructors at non-formal education programs;; edupreneurs in the field of accounting and finance; junior researchers in the field of accounting and finance; and assistant accountants, and (2) the learning outcome expected includes attitude, knowledge, general and special skills, characters, and transferable soft skills which are relevant with the demands of the general public

Y-Single Nucleotide Polymorphisms Diversity in Chinese Indigenous Horse

In contrast to high genetic diversity of mitochondrial DNA (mtDNA), equine Y chromosome shows extremely low variability, implying limited patrilines in the domesticated horse. In this study, we applied direct sequencing and restriction fragment length polymorphism (RFLP) methods to investigate the polymorphisms of 33 Y chromosome specific loci in 304 Chinese indigenous horses from 13 breeds. Consequently, two Y-single nucleotide polymorphisms (SNPs) (Y-45701/997 and Y-50869) and one Y-indel (Y-45288) were identified. Of those, the Y-50869 (T>A) revealed the highest variation frequency (24.67%), whereas it was only 3.29% and 1.97% in Y-45288 (T/-) and Y-45701/997 (G>T) locus, respectively. These three mutations accounted for 27.96% of the total samples and identified five Y-SNP haplotypes, demonstrating genetic diversity of Y chromosome in Chinese horses. In addition, all the five Y-SNP haplotypes were shared by different breeds. Among 13 horse breeds analyzed, Balikun horse displayed the highest nucleotide diversity (π = 5.6×10−4) and haplotype diversity (h = 0.527), while Ningqiang horse showed the lowest nucleotide diversity (π = 0.00000) and haplotype diversity (h = 0.000). The results also revealed that Chinese horses had a different polymorphic pattern of Y chromosome from European and American horses. In conclusion, Chinese horses revealed genetic diversity of Y chromosome, however more efforts should be made to better understand the domestication and paternal origin of Chinese indigenous horses

A Chinese SCA36 pedigree analysis of NOP56 expansion region based on long-read sequencing

Introduction: Spinocerebellar ataxias 36 (SCA36) is the neurodegenerative disease caused by the GGCCTG Hexanucleotide repeat expansions in NOP56, which is too long to sequence using short-read sequencing. Single molecule real time (SMRT) sequencing can sequence across disease-causing repeat expansion. We report the first long-read sequencing data across the expansion region in SCA36.Methods: We collected and described the clinical manifestations and imaging features of Han Chinese pedigree with three generations of SCA36. Also, we focused on structural variation analysis for intron 1 of the NOP56 gene by SMRT sequencing in the assembled genome.Results: The main clinical features of this pedigree are late-onset ataxia symptoms, with a presymptomatic presence of affective and sleep disorders. In addition, the results of SMRT sequencing showed the specific repeat expansion region and demonstrated that the region was not composed of single GGCCTG hexanucleotides and there were random interruptions.Discussion: We extended the phenotypic spectrum of SCA36. We applied SMRT sequencing to reveal the correlation between genotype and phenotype of SCA36. Our findings indicated that long-read sequencing is well suited to characterize known repeat expansion