Toward a Brain-Inspired System: Deep Recurrent Reinforcement Learning for a Simulated Self-Driving Agent

An effective way to achieve intelligence is to simulate various intelligent behaviors in the human brain. In recent years, bio-inspired learning methods have emerged, and they are different from the classical mathematical programming principle. From the perspective of brain inspiration, reinforcement learning has gained additional interest in solving decision-making tasks as increasing neuroscientific research demonstrates that significant links exist between reinforcement learning and specific neural substrates. Because of the tremendous research that focuses on human brains and reinforcement learning, scientists have investigated how robots can autonomously tackle complex tasks in the form of making a self-driving agent control in a human-like way. In this study, we propose an end-to-end architecture using novel deep-Q-network architecture in conjunction with a recurrence to resolve the problem in the field of simulated self-driving. The main contribution of this study is that we trained the driving agent using a brain-inspired trial-and-error technique, which was in line with the real world situation. Besides, there are three innovations in the proposed learning network: raw screen outputs are the only information which the driving agent can rely on, a weighted layer that enhances the differences of the lengthy episode, and a modified replay mechanism that overcomes the problem of sparsity and accelerates learning. The proposed network was trained and tested under a third-party OpenAI Gym environment. After training for several episodes, the resulting driving agent performed advanced behaviors in the given scene. We hope that in the future, the proposed brain-inspired learning system would inspire practicable self-driving control solutions

Effect of Calcium Chloride on Energy Level and Quality of Tan Sheep Meat during Postmortem Aging

Our purpose was to clarify the effect of CaCl2 treatment on the energy level and quality of Tan sheep meat during postmortem aging. Tan sheep hind leg meat was injected with 200 mmol/L CaCl2 solution, and aged at 4 ℃ for 0, 2, 4, 6, and 8 days. The protein expression of phosphofructokinase (PFKM) was detected by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and Western blot to verify whether the glycolysis pathway could be activated by CaCl2. At the same time, the energy level and meat quality indexes were measured during postmortem aging to analyze the mechanism by which the glycolysis pathway affects the metabolic level and quality of Tan sheep meat. The results showed that the protein expression of PFKM decreased during postmortem aging, indicating activation of the glycolytic pathway. CaCl2 treatment accelerated the glycolysis process after slaughter, thereby promoting the decomposition of glycogen, increasing the production of lactic acid, and resulting in a rapid decrease in pH. Water-holding capacity (WHC), myofibril fragmentation index (MFI) and b* value were higher and shear force and a* were lower in the treatment group than in the control and blank groups. Therefore, CaCl2 could affect the color, WHC and tenderness of Tan sheep meat at different aging stages. By accelerating the decrease of pH and the accumulation of energy metabolites, the glycolytic pathway increased the level of energy metabolism during postmortem aging, while inhibiting the production of oxymyoglobin, activating the activity of calpain, changing the structure of myofibrils and shortening the space between muscle protein molecules, which accelerated the process of myofibril fragmentation and the hydrolysis of myofibrillar protein, and led to a deterioration in meat color and an increase in water loss and meat tenderness

Postmortem Degradation of Qinchuan Beef Protein by Proteasome and Its Mediated Ubiquitin-Proteasome Pathway

In this study, the Longissimus dorsi muscle of Qinchuan cattle was injected with the proteasome inhibitor MG-132 immediately postmortem and then stored at 4 ℃. The effect of the ubiquitin-proteasome pathway (UPP) on protein degradation as well as changes in the proteasome activity, ubiquitin content and microstructure of the muscle during postmortem storage was explored in order to provide theoretical support for precise postmortem regulation of beef quality. With the extension of storage time, proteasome activity was lower and the contents of total soluble protein and ubiquitin were higher in the MG-132 group than in the control group. The sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) results showed that the band intensity of total soluble proteins between 40 and 250 kDa was greater in the MG-132 group than in the control group; muscle structure was better preserved in the MG-132 group, and the Z line and the boundary between light and dark bands were clearer than those in the control group. The contents of total soluble protein and ubiquitin showed a significantly positive correlation (P < 0.05). In conclusion, postmortem injection of MG-132 inhibited the proteasome activity and the degradation of ubiquitinated proteins in the UPP in Qinchuan beef, which in turn altered protein degradation and attenuated muscle damage. This suggests that the UPP has a potential role in meat quality formation; the proteasome not only degrades proteins by itself alone to destroy beef myofibrillar structure, but also influences postmortem beef protein degradation through mediating the UPP, ultimately affecting postmortem beef quality

The Efficacy and Safety of Shen Guo Lao Nian Granule for Common Cold of Qi-Deficiency Syndrome: Study Protocol for a Randomized, Double-Blind, Placebo-Controlled, Multicenter, Phase II Clinical Trial

Background. Common cold is one of the most frequently occurring illnesses in primary healthcare services and represents considerable disease burden. Common cold of Qi-deficiency syndrome (CCQDS) is an important but less addressed traditional Chinese medicine (TCM) pattern. We designed a protocol to explore the efficacy, safety, and optimal dose of Shen Guo Lao Nian Granule (SGLNG) for treating CCQDS. Methods/Design. This is a multicenter, randomized, double-blind, placebo-controlled, phase II clinical trial. A total of 240 eligible patients will be recruited from five centers. Patients are randomly assigned to high-dose group, middle-dose group, low-dose group, or control group in a 1 : 1 : 1 : 1 ratio. All drugs are required to be taken 3 times daily for 5 days with a 5-day follow-up period. Primary outcomes are duration of all symptoms, total score reduction on Jackson’s scale, and TCM symptoms scale. Secondary outcomes include every single TCM symptom duration and score reduction, TCM main symptoms disappearance rate, curative effects, and comparison between Jackson’s scale and TCM symptom scale. Ethics and Trial Registration. This study protocol was approved by the Ethics Committee of Clinical Trials and Biomedicine of West China Hospital of Sichuan University (number IRB-2014-12) and registered with the Chinese Clinical Trial Registry (ChiCTR-IPR-15006349)

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

Adaptiv betong 3D-utskrift Baserad på industriell robotik

Additive manufacturing, also known as 3D printing is the construction of a three-dimensional object from 3D CAD model. The process includes that material depositing, joining or solidifying using computer control. It is getting widely used in many fields, such as architecture and civil engineering, industry and even medical fields. Also, the prevalence of 6 axis industrial robot gives researchers and engineers extended possibilities to design and create with the additional degrees of freedom. This project has been conducted at KTH ABE school and ITM school. In recent years, The ABE school explored the possibility of 3D printing with building materials such as concrete which provides a practical basis for the implementation of this project. The ITM school gave guidance and suggestions for this project based on their experience in industrial manufacturing and robot control. The goals were to propose an improvement of current workflow and explore a detection strategy for the defection of concrete 3D printing product. Due to the material limitations of concrete and robot control, the previous printing tasks that should have been automated require human supervision and intervention, which affects work efficiency and completion of finished product. In order to avoid this, an Intel RealSense L515 Lidar camera was applied to capture a point cloud of product to detect the height of product and program can compensate the print layers number and robot trajectory. The industrial robot is controlled by KRL generated from the known trajectory. The implementation of this project consists of background research, design the layout of 3D printing system, algorithm development and case study. A simple clay model is produced during this project to study the feasibility of this method.Additiv tillverkning, även känd som 3D-utskrift, är konstruktionen av ett tredimensionellt objektfrån 3D CAD-modellen. Processen innefattar att material avsätter, sammanfogar eller stelnar under datorstyrningen. Det används allmänt inom många områden, till exempel arkitektur och anläggning, industri och till och med medicinska områden. Också, förekomsten av 6-axligindustrirobot ger forskare och ingenjörer mer möjlighet att designa och skapa på grund av fler frihetsgrader. Detta projekt har genomförts vid KTH ABE-skolan och ITM-skolan. Under de senaste åren har ABE -skolan undersökt möjligheterna till 3D-utskrift med byggmaterial som betong, vilket ger en teoretisk grund för genomförandet av detta projekt. ITM-skolan gav vägledning och förslag för detta projekt baserat på deras erfarenhet av industrielltillverkning och robotstyrning. Målen var att föreslå en förbättring av det nuvarande arbetsflödet och utforska en detekteringsstrategi för osäkerheten i konkret 3D-utskrift. På grund av den materiella begränsningen av betong och felaktighet i robotstyrning kräver de tidigare utskriftsuppgifterna som borde ha automatiserats mänsklig övervakning och intervention. Detta påverkar arbetseffektiviteten och färdigställandet av den färdiga produkten. För att undvika detta tillämpades en Intel RealSense L515 -radarkamera för att fånga produktensmoln för att upptäcka produktens höjd och programmet kan kompensera antalet utskriftslager och robotbanan. Industriroboten styrs av KRL genererad från den kända banan. Genomförandet av detta projekt består av bakgrundsresurser, design av layouten för 3D -utskriftssystem, algoritmutveckling och fallstudier. En enkel lermodell produceras under detta projekt för att studera genomförbarheten av denna metod