Collective flow and the fluid behavior in p/d/3^3He+Au collisions at sNN=200\sqrt{s_{NN}} = 200 GeV

By varying the intrinsic initial geometry, the p/d/$^3$He+Au collisions at the Relativistic Heavy Ion Collider (RHIC) provide a unique opportunity to understand the collective behavior in the small systems. In this paper, we employ the hybrid model iEBE-VISHNU with TRENTO initial conditions to study the collective flow and the fluid behavior in p/d/$^3$He+Au collisions. With fine-tuned parameters, iEBE-VISHNU can describe the $v_2(p_T)$ and $v_3(p_T)$ data from the PHENIX and STAR collaborations. However, for these parameter sets tuned to fit the STAR data, the hydrodynamic simulations have already beyond their limits with the average Knudsen number $\langle K_n \rangle$ obviously larger than one. Our calculations demonstrate that, for a meaningful evaluation of the fluid behavior in the small systems, model simulations should also pay attention to the validity range of hydrodynamics

Integrated Sensing-Communication-Computation for Over-the-Air Edge AI Inference

Edge-device co-inference refers to deploying well-trained artificial intelligent (AI) models at the network edge under the cooperation of devices and edge servers for providing ambient intelligent services. For enhancing the utilization of limited network resources in edge-device co-inference tasks from a systematic view, we propose a task-oriented scheme of integrated sensing, computation and communication (ISCC) in this work. In this system, all devices sense a target from the same wide view to obtain homogeneous noise-corrupted sensory data, from which the local feature vectors are extracted. All local feature vectors are aggregated at the server using over-the-air computation (AirComp) in a broadband channel with the orthogonal-frequency-division-multiplexing technique for suppressing the sensing and channel noise. The aggregated denoised global feature vector is further input to a server-side AI model for completing the downstream inference task. A novel task-oriented design criterion, called maximum minimum pair-wise discriminant gain, is adopted for classification tasks. It extends the distance of the closest class pair in the feature space, leading to a balanced and enhanced inference accuracy. Under this criterion, a problem of joint sensing power assignment, transmit precoding and receive beamforming is formulated. The challenge lies in three aspects: the coupling between sensing and AirComp, the joint optimization of all feature dimensions' AirComp aggregation over a broadband channel, and the complicated form of the maximum minimum pair-wise discriminant gain. To solve this problem, a task-oriented ISCC scheme with AirComp is proposed. Experiments based on a human motion recognition task are conducted to verify the advantages of the proposed scheme over the existing scheme and a baseline.Comment: This work was accepted by IEEE Transactions on Wireless Communications on Aug. 12, 202

Hybrid light-emitting polymer/SiN_x platform for photonic integration

Organic semiconductors have potentials for a broad range of applications; however, it is difficult to be integrated with traditional inorganic material to meet the need of further application. Based on low-temperature silicon nitride (SiNx) deposition technique, here we demonstrate a hybrid structure fabricated by directly depositing high-quality SiNx on organic polymer film Poly[2-(2',5'-bis(2"-ethylhexyloxy)- phenyl) -1,4-phenylene vinylene] (BEHP-PPV). Stacked BEHP-PPV/SiNx hybrid structures with different periods are obtained and their optical properties are systematically characterized. Moreover, a group of BEHP/PPV embedded SiNx micro-disk is fabricated and amplification of spontaneous emission (ASE) is observed under optical pumping, further confirming that the gain properties of BEHP/PPV are well preserved. Our technique offers a platform to fabricate organic/inorganic hybrid optical devices compatible with integrated components.Comment: 6 pages, 4 figure

Potential genetic therapies based on m6A methylation for skin regeneration: Wound healing and scars/keloids

Skin wound healing is a complex and multistage process, where any abnormalities at any stage can result in the accumulation of non-functional fibrotic tissue, leading to the formation of skin scars. Epigenetic modifications play a crucial role in regulating gene expression, inhibiting cell fate determination, and responding to environmental stimuli. m6A methylation is the most common post-transcriptional modification of eukaryotic mRNAs and long non-coding RNAs. However, it remains unclear how RNA methylation controls cell fate in different physiological environments. This review aims to discuss the current understanding of the regulatory pathways of RNA methylation in skin wound healing and their therapeutic implications with a focus on the specific mechanisms involved

Microfluidic Blood Cell Sorting: Now and Beyond

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/106971/1/smll201302907.pd

Plaintext-Related Dynamic Key Chaotic Image Encryption Algorithm

To address the problems of the high complexity and low security of the existing image encryption algorithms, this paper proposes a dynamic key chaotic image encryption algorithm with low complexity and high security associated with plaintext. Firstly, the RGB components of the color image are read, and the RGB components are normalized to obtain the key that is closely related to the plaintext, and then the Arnold transform is used to stretch and fold the RGB components of the color image to change the position of the pixel points in space, so as to destroy the correlation between the adjacent pixel points of the image. Next, the generated sequences are independently encrypted with the Arnold-transformed RGB matrix. Finally, the three encrypted images are combined to obtain the final encrypted image. Since the key acquisition of this encryption algorithm is related to the plaintext, it is possible to achieve one key per image, so the key acquisition is dynamic. This encryption algorithm introduces chaotic mapping, so that the key space size is 10180. The key acquisition is closely related to the plaintext, which makes the ciphertext more random and resistant to differential attacks, and ensures that the ciphertext is more secure after encryption. The experiments show that the algorithm can encrypt the image effectively and can resist attack on the encrypted image