The Relationship Between Human Behavior Pattern and Urban Street Space

As the most important and largest public space in urban built-up areas, street space is the most exciting and exciting part for people in the city, which is closely related to people's behavior patterns.Streets are full of vitality because of people's participation, and successful street Spaces can effectively promote the public life of urban residents.Therefore, it is of great significance to study the relationship between human behavior pattern and urban street space.After studying the common behavior patterns of people in street space, this paper analyzes the mutual influence between them, and finally puts forward the existing problems and improvement suggestions of urban street space under the current background

Shock Study in Fully Relativistic Isothermal Flows. II

The isothermal shocks and their stabilities in fully relativistic accretion wedge flows onto black holes are studied. The jump condition across the shock is modified by the relativistic effects when the sound speed is comparable to the speed of light. With a new kind of instability analysis, it is found that only one of the two possible shocks is stable. The results are applied to the QPO behavior in galactic black hole candidates such as Cygnus X-1

Transonic Inviscid Disc Flows in the Schwarzschild Metric – I

The coupled hydrodynamic equations governing equatorial flows applicable to inviscid disc accretion in the Schwarzschild metric are solved analytically and numerically. Here, we concentrate on the transonic solutions, that represent physically allowed accretion on to black holes. A polytropic equation linking gas pressure and density is assumed, and solutions are obtained for different conditions, such as isothermal and adiabatic gas flows. The dependence of those solutions on the angular momentum is explored. Under certain conditions, when there exist multiple possible sonic points, the numerical simulation automatically zeros in to the unique transonic solution passing through one of the sonic points

The Centennial Variation of El Niño Impact on Atlantic Tropical Cyclones

Predicting tropical cyclone (TC) activity becomes more important every year while the understanding of what factors impact them continues to be complicated. El Niño–Southern Oscillation (ENSO) is one of the primary factors impacting the activities in both the Pacific and the Atlantic, but an extensive examination of the fluctuation in this system has yet to be studied in its entirety. This article analyzes the ENSO impacts on the Atlantic tropical cyclone activity during the assessed warm and cold years to show the dominant centennial-scale variation impact. This study looks to plausibly link this variation to the Southern Ocean centennial variability, which is rarely mentioned in any factors affecting the Atlantic tropical cyclone activity. This centennial variability could be used to enhance future work related to predicting tropical cyclones

Improved Associated Conditions in Rapid Intensifications of Tropical Cyclones

Rapid intensification (RI) of tropical cyclones (TC) is a major error source in TC intensity forecasting. In order to improve the estimates of RI probability, association rules are used to facilitate the process of mining for candidate sets of conditions. Compared to the relation analysis method, the technique of association rules can simply explore associations among multiple conditions. Our mining results identified a reduced predictor set with fewer factors identified in previous studies but improved RI probabilities. That is, the RI probability with three conditions satisfied: low vertical shear, high humidity, and the TC being in an intensification phase is higher than that with five satisfied conditions including high sea surface temperature and an intensity far away from the maximum potential intensity in addition to the above three

Robust Power Allocation for UAV-aided ISAC Systems with Uncertain Location Sensing Errors

Unmanned aerial vehicle (UAV) holds immense potential in integrated sensing and communication (ISAC) systems for the Internet of Things (IoT). In this paper, we propose a UAV-aided ISAC framework and investigate three robust power allocation schemes. First, we derive an explicit expression of the Cram\'er-Rao bound (CRB) based on time-of-arrival (ToA) estimation, which serves as the performance metric for location sensing. Then, we analyze the impact of the location sensing error (LSE) on communications, revealing the inherent coupling relationship between communication and sensing. Moreover, we formulate three robust communication and sensing power allocation problems by respectively characterizing the LSE as an ellipsoidal distributed model, a Gaussian distributed model, and an arbitrary distributed model. Notably, the optimization problems seek to minimize the CRB, subject to data rate and total power constraints. However, these problems are non-convex and intractable. To address the challenges related to the three aforementioned LSE models, we respectively propose to use the ${\cal{S}}$-Procedure and alternating optimization (${\cal{S}}$-AO) method, Bernstein-type inequality and successive convex approximation (BI-SCA) method, and conditional value-at-risk (CVaR) and AO (CVaR-AO) method to solve these problems. Finally, simulation results demonstrate the robustness of our proposed UAV-aided ISAC system against the LSE by comparing with the non-robust design, and evaluate the trade-off between communication and sensing in the ISAC system

Numerical Simulation on Heat Transfer Performance of Silicon Carbide/ Nitrate Composite for Solar Power Generation

KNO3 was used as the phase change material (PCM), but its thermal conductivity is too low to transfer heat between the PCM and conduction oil efficiently. In this thesis, on the basis of the previous studies (Yong Li, 2015), the solar power generation efficiency is enhanced with high temperature interval (280℃—400℃), and the new composite which are composed by the SiC honeycomb (SCH) frame and infiltrated KNO3 is simulated by using Fluent software. The results show that the new composite of the KNO3 +30%SCH suit for the requirement of the charging time and capacity in the design of the thermal energy storage units (TESU); The comparable simulation for the long and short pipe models supplies the evidences that the long pipe simulation can be substituted by the short pipe simulation relatively, which reduces the 3-D simulation time enormously; The comparable simulation of the radial dimensions supplies some theory foundations for the design of the module thermal energy storage tank (MTEST) . These simulation results have important guidance on the design of the thermal energy storage unit and the module thermal energy storage tank

Numerical Simulations of the Impacts of the Saharan Air Layer on Atlantic Tropical Cyclone Development

In this study, the role of the Saharan air layer (SAL) is investigated in the development and intensification of tropical cyclones (TCs) via modifying environmental stability and moisture, using multisensor satellite data, long-term TC track and intensity records, dust data, and numerical simulations with a state-of-the-art Weather Research and Forecasting model (WRF). The long-term relationship between dust and Atlantic TC activity shows that dust aerosols are negatively associated with hurricane activity in the Atlantic basin, especially with the major hurricanes in the western Atlantic region. Numerical simulations with the WRF for specific cases during the NASA African Monsoon Multidisciplinary Analyses (NAMMA) experiment show that, when vertical temperature and humidity profiles from the Atmospheric Infrared Sounder (AIRS) were assimilated into the model, detailed features of the warm and dry SAL, including the entrainment of dry air wrapping around the developing vortex, are well simulated. Active tropical disturbances are found along the southern edge of the SAL. The simulations show an example where the dry and warm air of the SAL intruded into the core of a developing cyclone, suppressing convection and causing a spin down of the vortical circulation. The cyclone eventually weakened. To separate the contributions from the warm temperature and dry air associated with the SAL, two additional simulations were performed, one assimilating only AIRS temperature information (AIRST) and one assimilating only AIRS humidity information (AIRSH) while keeping all other conditions the same. The AIRST experiments show almost the same simulations as the full AIRS assimilation experiments, whereas the AIRSH is close to the non-AIRS simulation. This is likely due to the thermal structure of the SAL leading to low-level temperature inversion and increased stability and vertical wind shear. These analyses suggest that dry air entrainment and the enhanced vertical wind shear may play the direct roles in leading to the TC suppression. On the other hand, the warm SAL temperature may play the indirect effects by enhancing vertical wind shear; increasing evaporative cooling; and initiating mesoscale downdrafts, which bring dry air from the upper troposphere to the lower levels

Role of Anomalous Warm Gulf Waters in the Intensification of Hurricane Katrina

The year 2005 experienced several strong hurricanes intensifying in the Gulf of Mexico before making landfall that severely damaged the Gulf States, especially Hurricane Katrina. Remarkable similarities between sea surface temperature anomaly (SSTA) and major hurricane (categories 3 and higher) activity over the Gulf are identified. However, the intensification of individual hurricanes may not necessarily be temporally and spatially coincident with the distribution of warm waters or high sea surface temperature (SST). High SST values are found in advance of significant intensification of Hurricane Katrina. We emphasize that high SSTA which occurred at the right time and right place was conducive to the hurricane intensification. In particular, high SSTA in the northeastern quadrant of the storm track induced significant increases in surface latent heat fluxes (LHF) contributing to the rapid intensification of Katrina. We also compared and verified model simulations with buoy observations

Training Socially Aligned Language Models on Simulated Social Interactions

Social alignment in AI systems aims to ensure that these models behave according to established societal values. However, unlike humans, who derive consensus on value judgments through social interaction, current language models (LMs) are trained to rigidly replicate their training corpus in isolation, leading to subpar generalization in unfamiliar scenarios and vulnerability to adversarial attacks. This work presents a novel training paradigm that permits LMs to learn from simulated social interactions. In comparison to existing methodologies, our approach is considerably more scalable and efficient, demonstrating superior performance in alignment benchmarks and human evaluations. This paradigm shift in the training of LMs brings us a step closer to developing AI systems that can robustly and accurately reflect societal norms and values.Comment: Code, data, and models can be downloaded via https://github.com/agi-templar/Stable-Alignmen