Flow characteristics and heat transfer performance in a Y-Fractal mini/microchannel heat sink

This article presents a combined experimental and computational study to investigate the flow and heat transfer in a Y-fractal microchannel. Experimental apparatus was newly built to investigate the effect of three different control factors, i.e., fluid flow rate, inlet temperature and heat flux, on the heat transfer characteristics of the microchannel. A standard k-Ɛ turbulence computational fluid dynamics (CFD) model was developed, validated and further employed to simulate the flow and heat transfer microchannel. A comparison between simulated results and the obtained experimental data was presented and discussed. Results showed that good agreement was achieved between the current simulated results and experimental data. Furthermore, an improved new design was suggested to further increase the heat transfer performance and create uniformity of temperature distribution.Peer reviewe

First attempt to build realistic driving scenes using video-to-video synthesis in OpenDS framework

Existing programmable simulators enable researchers to customize different driving scenarios to conduct in-lab automotive driver simulations. However, software-based simulators for cognitive research generate and maintain their scenes with the support of 3D engines, which may affect users' experiences to a certain degree since they are not sufficiently realistic. Now, a critical issue is the question of how to build scenes into real-world ones. In this paper, we introduce the first step in utilizing video-to-video synthesis, which is a deep learning approach, in OpenDS framework, which is an open-source driving simulator software, to present simulated scenes as realistically as possible. Off-line evaluations demonstrated promising results from our study, and our future work will focus on how to merge them appropriately to build a close-to-reality, real-time driving simulator

miRAS: a data processing system for miRNA expression profiling study

<p>Abstract</p> <p>Background</p> <p>The study of microRNAs (miRNAs) is attracting great considerations. Recent studies revealed that miRNAs play as important regulators of gene expression and some even as cancer players or inhibitors. Many studies try to discover new miRNAs and reveal the miRNA expression profile in cancer using a SAGE-based total RNA clone method. However, the data processing of this method is labor-intensive with several different biological databases and more than ten data processing steps involved.</p> <p>Results</p> <p>With miRAS, miRNAs and possible miRNA candidates contained in the submitted sequencing data were obtained together with their expression profile. The functions of known and predicted miRNAs were then analyzed by miRNA target prediction followed by target gene annotations. Finally, to extract the biological significance of the miRNAs in the samples, further annotations of the known miRNA and target genes were performed by collecting the public expression datasets of miRNA and target genes in normal and cancer tissues.</p> <p>Conclusion</p> <p>We introduce a web-based analysis platform called miRNA Analysis System (miRAS), for processing and analyzing of the sequence data obtained from the total RNA clone method. The system was built on generalizing the study of a liver cancer cell line total RNA sequencing project. miRAS is freely available on the web.</p

Face2Multi-modal: in-vehicle multi-modal predictors via facial expressions

Towards intelligent Human-Vehicle Interaction systems and innovative Human-Vehicle Interaction designs, in-vehicle drivers' physiological data has been explored as an essential data source. However, equipping multiple biosensors is considered the limited extent of user-friendliness and impractical during the driving procedure. The lack of a proper approach to access physiological data has hindered wider applications of advanced biosignal-driven designs in practice (e.g. monitoring systems and etc.). Hence, the demand for a user-friendly approach to measuring drivers' body statuses has become more intense. In this Work-In-Progress, we present Face2Multi-modal, an In-vehicle multi-modal Data Streams Predictors through facial expressions only. More specifically, we have explored the estimations of Heart Rate, Skin Conductance, and Vehicle Speed of the drivers. We believe Face2Multi-modal provides a user-friendly alternative to acquiring drivers' physiological status and vehicle status, which could serve as the building block for many current or future personalized Human-Vehicle Interaction designs. More details and updates about the project Face2Multi-modal is online at https://github.com/unnc-ucc/Face2Multimodal/

Spin: An Efficient Secure Computation Framework with GPU Acceleration

Accuracy and efficiency remain challenges for multi-party computation (MPC) frameworks. Spin is a GPU-accelerated MPC framework that supports multiple computation parties and a dishonest majority adversarial setup. We propose optimized protocols for non-linear functions that are critical for machine learning, as well as several novel optimizations specific to attention that is the fundamental unit of Transformer models, allowing Spin to perform non-trivial CNNs training and Transformer inference without sacrificing security. At the backend level, Spin leverages GPU, CPU, and RDMA-enabled smart network cards for acceleration. Comprehensive evaluations demonstrate that Spin can be up to $2\times$ faster than the state-of-the-art for deep neural network training. For inference on a Transformer model with 18.9 million parameters, our attention-specific optimizations enable Spin to achieve better efficiency, less communication, and better accuracy

Composite vertical structures and spatiotemporal characteristics of abnormal eddies in the Japan/East Sea: a synergistic investigation using satellite altimetry and Argo profiles

Mesoscale eddies are omnipresent and play an important role in regulating Earth’s climate and ocean circulation in the global ocean. Here using the combination of satellite altimetry products and Argo float profile data, two types of abnormal eddies are investigated: WCEs(warm cyclonic eddies) and CAEs(cold anticyclonic eddies) with different cores than conventional eddies in the Japan/East Sea. By applying a classification method based on the calculation of the heat content anomalies in the upper ocean, it was found that 10% of the eddies that captured the Argo float profiles exhibited obvious abnormal features. Subsequently, their spatiotemporal distributions and characteristics were analyzed statistically. Three-dimensional structures of abnormal eddies were obtained via the composite analysis method, showing that the warm/cold and light/dense core of the composite WCE/CAE is confined to the upper 100 m of the ocean with a maximum temperature anomaly of approximately +1.0(-1.1)°C. The composite WCE had a double-core salinity structure with a salty core above 50 m and an inferior fresh core. Meanwhile composite CAE had a fresh single-core with a maximum magnitude of -0.05 psu. Abnormal eddies are pervasive in the Japan/East sea, a revaluation of the role of these eddies in ocean circulation and climate systems, such as heat and salt transport, air and sea interaction, and variability in mixed layer depth, is of great importance

Large-scale association analysis identifies new lung cancer susceptibility loci and heterogeneity in genetic susceptibility across histological subtypes.

Although several lung cancer susceptibility loci have been identified, much of the heritability for lung cancer remains unexplained. Here 14,803 cases and 12,262 controls of European descent were genotyped on the OncoArray and combined with existing data for an aggregated genome-wide association study (GWAS) analysis of lung cancer in 29,266 cases and 56,450 controls. We identified 18 susceptibility loci achieving genome-wide significance, including 10 new loci. The new loci highlight the striking heterogeneity in genetic susceptibility across the histological subtypes of lung cancer, with four loci associated with lung cancer overall and six loci associated with lung adenocarcinoma. Gene expression quantitative trait locus (eQTL) analysis in 1,425 normal lung tissue samples highlights RNASET2, SECISBP2L and NRG1 as candidate genes. Other loci include genes such as a cholinergic nicotinic receptor, CHRNA2, and the telomere-related genes OFBC1 and RTEL1. Further exploration of the target genes will continue to provide new insights into the etiology of lung cancer

Rapid detection of porcine circovirus type 4 via multienzyme isothermal rapid amplification

Porcine circovirus type 4 (PCV4) is a newly emerging pathogen that was first detected in 2019 and is associated with diverse clinical signs, including respiratory and gastrointestinal distress, dermatitis and various systemic inflammations. It was necessary to develop a sensitive and specific diagnostic method to detect PCV4 in clinical samples, so in this study, a multienzyme isothermal rapid amplification (MIRA) assay was developed for the rapid detection of PCV4 and evaluated for sensitivity, specificity and applicability. It was used to detect the conserved Cap gene of PCV4, operated at 41°C and completed in 20 min. With the screening of MIRA primer-probe combination, it could detect as low as 101 copies of PCV4 DNA per reaction and was highly specific, with no cross-reaction with other pathogens. Further assessment with clinical samples showed that the developed MIRA assay had good correlation with real-time polymerase chain reaction assay for the detection of PCV4. The developed MIRA assay will be a valuable tool for the detection of the novel PCV4 in clinical samples due to its high sensitivity and specificity, simplicity of operation and short testing time

Safety, Immunogenicity, and Mechanism of a Rotavirus mRNA-LNP Vaccine in Mice

Rotaviruses (RVs) are a major cause of diarrhea in young children worldwide. The currently available and licensed vaccines contain live attenuated RVs. Optimization of live attenuated RV vaccines or developing non-replicating RV (e.g., mRNA) vaccines is crucial for reducing the morbidity and mortality from RV infections. Herein, a nucleoside-modified mRNA vaccine encapsulated in lipid nanoparticles (LNP) and encoding the VP7 protein from the G1 type of RV was developed. The 5\u27 untranslated region of an isolated human RV was utilized for the mRNA vaccine. After undergoing quality inspection, the VP7-mRNA vaccine was injected by subcutaneous or intramuscular routes into mice. Mice received three injections in 21 d intervals. IgG antibodies, neutralizing antibodies, cellular immunity, and gene expression from peripheral blood mononuclear cells were evaluated. Significant differences in levels of IgG antibodies were not observed in groups with adjuvant but were observed in groups without adjuvant. The vaccine without adjuvant induced the highest antibody titers after intramuscular injection. The vaccine elicited a potent antiviral immune response characterized by antiviral clusters of differentiation CD