A Spatial Autoregressive Quantile Regression to Examine Quantile Effects of Regional Factors on Crash Rates

Spatial autocorrelation and skewed distribution are the most frequent issues in crash rate modelling analysis. Previous studies commonly focus on the spatial autocorrelation between adjacent regions or the relationships between crash rate and potentially risky factors across different quantiles of crash rate distribution, but rarely both. To overcome the research gap, this study utilizes the spatial autoregressive quantile (SARQ) model to estimate how contributing factors influence the total and fatal-plus-injury crash rates and how modelling relationships change across the distribution of crash rates considering the effects of spatial autocorrelation. Three types of explanatory variables, i.e., demographic, traffic networks and volumes, and land-use patterns, were considered. Using data collected in New York City from 2017 to 2019, the results show that: (1) the SARQ model outperforms the traditional quantile regression model in prediction and fitting performance; (2) the effects of variables vary with the quantiles, mainly classifying three types: increasing, unchanged, and U-shaped; (3) at the high tail of crash rate distribution, the effects commonly have sudden increases/decrease. The findings are expected to provide strategies for reducing the crash rate and improving road traffic safety.

Flow and Thermal Resistance Network Modeling of Finned Heat Sinks With Bypass Mounted in Rectangular Enclosure

This study describes a thermal design method of forced convection cooling in high-density packaging electronic equipment for upstream design processes by flow and thermal resistance network analysis. Forced convection cooling by combining fans and heat sinks is the most standard strategy for dissipating heat from electronic equipment. In recent years, the thermal design of electronic equipment becomes more critical, and fast thermal design is required due to the rapid development of final products. We have been developing the flow and thermal resistance network analysis as the quick thermal design method for electronic equipment. However, an accurate prediction of forced convection cooling performance by finned heat sinks mounted in high-density packaging electronic equipment is generally tricky. Some bypasses, which are clearances between the heat sinks and enclosure walls or other components, exist around the heat sinks. Therefore, a flow rate distribution between the heat sink fins and the bypasses should be predicted. Many researchers have investigated hydrodynamic characteristics and heat transfer characteristics of finned heat sinks. However, many previous studies have been conducted on the finned heat sink performance when there are no bypasses. In order to achieve an optimum design of the finned heat sinks in the upstream configuration regardless of the heat sink dimensions, a systematic database of hydrodynamic characteristics and heat transfer characteristics of the finned heat sinks with bypasses should be investigated. This paper discusses the development of function models of pressure drop, flow rate distribution, and heat transfer of the finned heat sinks with the bypasses for the resistance network analysis through experiments and CFD analysis. Several types of finned heat sinks with 40 mm in width and 80 mm in length were prepared, and these were mounted in a rectangular enclosure with 45 mm in width and height. First, the pressure drop characteristic around the heat sink was investigated. In addition, the flow rate distribution between the heat sink and the bypass was evaluated separately. A flow branching coefficient was developed to predict the flow rate distribution around the heat sink combined with the pressure drop coefficient. Using the developed flow branching coefficient, the flow and thermal resistance network model around the finned heat sink was developed. The results from the proposed resistance network model showed good agreement with those from the experiment.

Stretching and squeezing of neuronal log firing rate distribution by psychedelic and intrinsic brain state transitions

How psychedelic drugs change the activity of cortical neuronal populations and whether such changes are specific to transition into the psychedelic brain state or shared with other brain state transitions is not well understood. Here, we used Neuropixels probes to record from large populations of neurons in prefrontal cortex of mice given the psychedelic drug TCB-2. Drug ingestion significantly stretched the distribution of log firing rates of the population of recorded neurons. This phenomenon was previously observed across transitions between sleep and wakefulness, which suggested that stretching of the log-rate distribution can be triggered by different kinds of brain state transitions and prompted us to examine it in more detail. We found that modulation of the width of the log-rate distribution of a neuronal population occurred in multiple areas of the cortex and in the hippocampus even in awake drug-free mice, driven by intrinsic fluctuations in their arousal level. Arousal, however, did not explain the stretching of the log-rate distribution by TCB-2. In both psychedelic and naturally occurring brain state transitions, the stretching or squeezing of the log-rate distribution of an entire neuronal population reflected concomitant changes in two subpopulations, with one subpopulation undergoing a downregulation and often also stretching of its neurons’ log-rate distribution, while the other subpopulation undergoes upregulation and often also a squeeze of its log-rate distribution. In both subpopulations, the stretching and squeezing were a signature of a greater relative impact of the brain state transition on the rates of the slow-firing neurons. These findings reveal a generic pattern of reorganisation of neuronal firing rates by different kinds of brain state transitions.

A Method of Quantifying Refrigerant Distribution in a Two-Pass Micro-Channel Evaporator

Background: The flow rate distribution in the flat tubes of a micro-channel evaporator is essential for its heat transfer performance. Due to a large number of flat tubes in a micro-channel evaporator, the flow rate distribution is often difficult to determine. Objective: An evaporator test rig was constructed to study the quantification of the refrigerant mass flow rate distribution in a two-pass evaporator without de-stroying its structure. Methods: A heat transfer performance test rig for a two-pass evaporator was es-tablished. Subcooled refrigerant R134a was pumped into the inlet header, and infrared thermography was used to obtain the cloud map of the wall tempera-ture distribution on the surface of the evaporator. The flow rate distribution in each flat tube was calculated based on an analysis that combines the heat bal-ance between the airside and the refrigerant side with the effectiveness-Number of Transfer Units (ε-NTU) method. Results: The flow rate distribution was found to be in good agreement with the evaporator wall temperature distribution. The difference between the calculated and measured total mass flow rates was less than 15.9%, which proves that the method is simple and effective. The unevenness of flowrate distribution in the 1st and 2nd pass is 0.13 and 0.32, respectively. Conclusion: This method is simple and effective and does not destroy the structure of the micro-channel evaporator. However, it is only suitable for cases in which subcooled zone exists in a pass and is not applicable to a pass in which the refrigerant is only in a single-phase or a two-phase state.