Search for spin-dependent gravitational interactions at the Earth range

Among the four fundamental forces, only gravity does not couple to particle spins according to the general theory of relativity. We test this principle by searching for an anomalous scalar coupling between the neutron spin and the Earth gravity on the ground. We develop an atomic gas comagnetometer to measure the ratio of nuclear spin-precession frequencies between $^{129}$Xe and $^{131}$Xe, and search for a change of this ratio to the precision of 10$^{-9}$ as the sensor is flipped in the Earth gravitational field. The null results of this search set an upper limit on the coupling energy between the neutron spin and the gravity on the ground at 5.3$\times$10$^{-22}$~eV (95\% confidence level), resulting in a 17-fold improvement over the previous limit. The results can also be used to constrain several other anomalous interactions. In particular, the limit on the coupling strength of axion-mediated monopole-dipole interactions at the range of the Earth radius is improved by a factor of 17.Comment: Accepted by Physical Review Letter

Status and Prospects of the PandaX-III Experiment

The PandaX-III experiment searches the neutrinoless double beta decay of $^{136}$Xe with a high-pressure xenon gaseous time projection chamber~(TPC). Thermal-bonding Micromegas modules are used for charge collection. Benefitting from the excellent energy resolution and imaging capability, the background rate can be significantly suppressed through the topological information of events. The technology is successfully demonstrated by a prototype detector. The final detector has been constructed. In this paper, we will report the status of the PandaX-III experiment, including the construction and commissioning of the final detector, and the Micromegas-based TPC performance test in the prototype detector

The progress of research on the application of redox nanomaterials in disease therapy

Redox imbalance can trigger cell dysfunction and damage and plays a vital role in the origin and progression of many diseases. Maintaining the balance between oxidants and antioxidants in vivo is a complicated and arduous task, leading to ongoing research into the construction of redox nanomaterials. Nanodrug platforms with redox characteristics can not only reduce the adverse effects of oxidative stress on tissues by removing excess oxidants from the body but also have multienzyme-like activity, which can play a cytotoxic role in tumor tissues through the catalytic oxidation of their substrates to produce harmful reactive oxygen species such as hydroxyl radicals. In this review, various redox nanomaterials currently used in disease therapy are discussed, emphasizing the treatment methods and their applications in tumors and other human tissues. Finally, the limitations of the current clinical application of redox nanomaterials are considered

Intelligent Ship Collision Avoidance Algorithm Based on DDQN with Prioritized Experience Replay under COLREGs

Ship collisions often result in huge losses of life, cargo and ships, as well as serious pollution of the water environment. Meanwhile, it is estimated that between 75% and 86% of maritime accidents are related to human factors. Thus, it is necessary to enhance the intelligence of ships to partially or fully replace the traditional piloting mode and eventually achieve autonomous collision avoidance to reduce the influence of human factors. In this paper, we propose a multi-ship automatic collision avoidance method based on a double deep Q network (DDQN) with prioritized experience replay. Firstly, we vectorize the predicted hazardous areas as the observation states of the agent so that similar ship encounter scenarios can be clustered and the input dimension of the neural network can be fixed. The reward function is designed based on the International Regulations for Preventing Collision at Sea (COLREGs) and human experience. Different from the architecture of previous collision avoidance methods based on deep reinforcement learning (DRL), in this paper, the interaction between the agent and the environment occurs only in the collision avoidance decision-making phase, which greatly reduces the number of state transitions in the Markov decision process (MDP). The prioritized experience replay method is also used to make the model converge more quickly. Finally, 19 single-vessel collision avoidance scenarios were constructed based on the encounter situations classified by the COLREGs, which were arranged and combined as the training set for the agent. The effectiveness of the proposed method in close-quarters situation was verified using the Imazu problem. The simulation results show that the method can achieve multi-ship collision avoidance in crowded waters, and the decisions generated by this method conform to the COLREGs and are close to the level of human ship handling

Intelligent Ship Collision Avoidance Algorithm Based on DDQN with Prioritized Experience Replay under COLREGs

Ship collisions often result in huge losses of life, cargo and ships, as well as serious pollution of the water environment. Meanwhile, it is estimated that between 75% and 86% of maritime accidents are related to human factors. Thus, it is necessary to enhance the intelligence of ships to partially or fully replace the traditional piloting mode and eventually achieve autonomous collision avoidance to reduce the influence of human factors. In this paper, we propose a multi-ship automatic collision avoidance method based on a double deep Q network (DDQN) with prioritized experience replay. Firstly, we vectorize the predicted hazardous areas as the observation states of the agent so that similar ship encounter scenarios can be clustered and the input dimension of the neural network can be fixed. The reward function is designed based on the International Regulations for Preventing Collision at Sea (COLREGs) and human experience. Different from the architecture of previous collision avoidance methods based on deep reinforcement learning (DRL), in this paper, the interaction between the agent and the environment occurs only in the collision avoidance decision-making phase, which greatly reduces the number of state transitions in the Markov decision process (MDP). The prioritized experience replay method is also used to make the model converge more quickly. Finally, 19 single-vessel collision avoidance scenarios were constructed based on the encounter situations classified by the COLREGs, which were arranged and combined as the training set for the agent. The effectiveness of the proposed method in close-quarters situation was verified using the Imazu problem. The simulation results show that the method can achieve multi-ship collision avoidance in crowded waters, and the decisions generated by this method conform to the COLREGs and are close to the level of human ship handling

Morphology and thermoelectric properties of graphene nanosheets enwrapped with polypyrrole

With the help of sodium dodecyl sulfate (SDS), uniform polypyrrole (PPy) coatings were conveniently grown on both sides of reduced graphene oxide (rGO) nanosheet surfaces via a template-directed in situ polymerization. The rGO/PPy composites exhibited greatly enhanced thermoelectric performance with a power factor at room temperature of up to 3.01 mu W m(-1) K-2, which is 84 times greater than that of the pure PPy

Impacts of Modification of Alloying Method on Inclusion Evolution in RH Refining of Silicon Steel

This study explores the effect of introducing additional alloy elements not only in a different order but also at different stages of the Ruhrstahl-Heraeus (RH) process of low-carbon silicon steel production. A more economical method, described as “pre-alloying”, has been introduced. The evolution of MnO-FeO inclusions produced by pre-alloying was investigated. Results show that spherical 3FeO·MnO inclusions form first, then shelled FeO·zMnO (z = 0.7–4) inclusions nucleate on the surface of pre-existing 3FeO·MnO. Spherical FeO·zMnO (z = 3–5) is further evolved from shelled 3FeO·MnO by diffusion. Because these MnO-FeO inclusions float up into the slag before degassing, the pre-alloying process does not affect the quality of the melt in the end. Both carbon content and inclusion size conform to industry standards

Physical, mechanical, and biological properties of collagen membranes for guided bone regeneration: a comparative in vitro study

Abstract Background To provide a reference for clinical selection of collagen membranes by analyzing the properties of three kinds of collagen membranes widely used in clinics: Bio-Gide membrane from porcine dermis (PD), Heal-All membrane from bovine dermis (BD), and Lyoplant membrane from bovine pericardium (BP). Methods The barrier function of three kinds of collagen membranes were evaluated by testing the surface morphology, mechanical properties, hydrophilicity, and degradation rate of collagen membranes in collagenase and artificial saliva. In addition, the bioactivity of each collagen membrane as well as the proliferation and osteogenesis of MC3T3-E1 cells were evaluated. Mass spectrometry was also used to analyze the degradation products. Results The BP membrane had the highest tensile strength and Young’s modulus as well as the largest water contact angle. The PD membrane exhibited the highest elongation at break, the smallest water contact angle, and the lowest degradation weight loss. The BD membrane had the highest degradation weight loss, the highest number of proteins in its degradation product, the strongest effect on the proliferation of MC3T3-E1 cells, and the highest expression level of osteogenic genes. Conclusions The PD membrane is the best choice for shaping and maintenance time, while the BD membrane is good for osteogenesis, and the BP membrane is suitable for spatial maintenance. To meet the clinical requirements of guided bone regeneration, using two different kinds of collagen membranes concurrently to exert their respective advantages is an option worth considering

The Role of HIF-1α in Bone Regeneration: A New Direction and Challenge in Bone Tissue Engineering

The process of repairing significant bone defects requires the recruitment of a considerable number of cells for osteogenesis-related activities, which implies the consumption of a substantial amount of oxygen and nutrients. Therefore, the limited supply of nutrients and oxygen at the defect site is a vital constraint that affects the regenerative effect, which is closely related to the degree of a well-established vascular network. Hypoxia-inducible factor (HIF-1α), which is an essential transcription factor activated in hypoxic environments, plays a vital role in vascular network construction. HIF-1α, which plays a central role in regulating cartilage and bone formation, induces vascular invasion and differentiation of osteoprogenitor cells to promote and maintain extracellular matrix production by mediating the adaptive response of cells to changes in oxygen levels. However, the application of HIF-1α in bone tissue engineering is still controversial. As such, clarifying the function of HIF-1α in regulating the bone regeneration process is one of the urgent issues that need to be addressed. This review provides insight into the mechanisms of HIF-1α action in bone regeneration and related recent advances. It also describes current strategies for applying hypoxia induction and hypoxia mimicry in bone tissue engineering, providing theoretical support for the use of HIF-1α in establishing a novel and feasible bone repair strategy in clinical settings

Plasma cell-free DNA 5-hydroxymethylcytosine and whole-genome sequencing signatures for early detection of esophageal cancer

Abstract Esophageal cancer is a highly incidence and deadly disease with a poor prognosis, especially in developing countries. Owing to the lack of specific symptoms and early diagnostic biomarkers, most patients are diagnosed with advanced disease, leading to a 5-year survival rate of less than 15%. Early (n = 50) and middle-advanced (n = 50) esophageal squamous cell carcinoma (ESCC) patients, as well as 71 healthy individuals, underwent 5-hydroxymethylcytosine (5hmC) sequencing on their plasma cell-free DNA (cfDNA). A Northern Chinese cohort of cfDNA 5hmC dataset of 150 ESCC patients and 183 healthy individuals were downloaded for validation. A diagnostic model was developed using cfDNA 5hmC signatures and then improved by low-pass whole genome sequencing (WGS) features of cfDNA. Conserved cfDNA 5hmC modification motifs were observed in the two independent ESCC cohorts. The diagnostic model with 5hmC features achieved an AUC of 0.810 and 0.862 in the Southern and Northern cohorts, respectively, with sensitivities of 69.3–74.3% and specificities of 82.4–90.7%. The performance was well maintained in Stage I to Stage IV, with accuracy of 70–100%, but low in Stage 0, 33.3%. Low-pass WGS of cfDNA improved the AUC to 0.934 with a sensitivity of 82.4%, a specificity of 88.2%, and an accuracy of 84.3%, particularly significantly in Stage 0, with an accuracy up to 80%. 5hmC and WGS could efficiently differentiate very early ESCC from healthy individuals. These findings imply a non-invasive and convenient method for ESCC detection when clinical treatments are available and may eventually prolong survival