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We determine the global emission distribution of the potent greenhouse gas sulfur hexafluoride (SF6) for the period 2005–2021 using inverse modelling. The inversion is based on 50 d backward simulations with the Lagrangian particle dispersion model (LPDM) FLEXPART and on a comprehensive observation data set of SF6 mole fractions in which we combine continuous with flask measurements sampled at fixed surface locations and observations from aircraft and ship campaigns. We use a global-distribution-based (GDB) approach to determine baseline mole fractions directly from global SF6 mole fraction fields at the termination points of the backward trajectories. We compute these fields by performing an atmospheric SF6 re-analysis, assimilating global SF6 observations into modelled global three-dimensional mole fraction fields. Our inversion results are in excellent agreement with several regional inversion studies in the USA, Europe, and China. We find that (1) annual US SF6 emissions strongly decreased from 1.25 Gg in 2005 to 0.48 Gg in 2021; however, they were on average twice as high as the reported emissions to the United Nations. (2) SF6 emissions from EU countries show an average decreasing trend of −0.006 Gg yr−1 during the period 2005 to 2021, including a substantial drop in 2018. This drop is likely a direct result of the EU's F-gas regulation 517/2014, which bans the use of SF6 for recycling magnesium die-casting alloys as of 2018 and requires leak detection systems for electrical switch gear. (3) Chinese annual emissions grew from 1.28 Gg in 2005 to 5.16 Gg in 2021, with a trend of 0.21 Gg yr−1, which is even higher than the average global total emission trend of 0.20 Gg yr−1. (4) National reports for the USA, Europe, and China all underestimated their SF6 emissions. (5) Our results indicate increasing emissions in poorly monitored areas (e.g. India, Africa, and South America); however, these results are uncertain due to weak observational constraints, highlighting the need for enhanced monitoring in these areas. (6) Global total SF6 emissions are comparable to estimates in previous studies but are sensitive to a priori estimates due to the low network sensitivity in poorly monitored regions. (7) Monthly inversions indicate that SF6 emissions in the Northern Hemisphere were on average higher in summer than in winter throughout the study period.

A new method is developed to derive the bulk density and bulk water fraction of a population of particles from collocated measurements from the Micro-Rain Radar (MRR) and Particle Size and Velocity disdrometer (Parsivel). A rigorous particle-scattering simulation, namely the T-matrix method, is applied to Parsivel's particle size distribution data to calculate the reflectivity (ZHH). The possible combinations of the particle's ice, air, and water are derived to compare them with the MRR-measured ZHH. The combination of the minimum water fraction and maximum ice fraction subsequently determines the bulk density (ρbulk). The proposed method is applied to the data collected from the International Collaborative Experiments for Pyeongchang 2018 Olympic and Paralympic winter games (ICE-POP 2018) projects and its pre-campaign. The estimated ρbulk was examined independently by a comparison of the liquid-equivalent snowfall rate (SR) of collocated Pluvio devices. The bias values are adequately low (SR: −0.25–0.06 mm h−1). The retrieved bulk density also shows good consistency with collocated Precipitation Imaging Package (PIP) retrievals. The results indicate the capability of the proposed algorithm to derive reliable ρbulk, leveraging the compact and easily deployable designs of MRR and Parsivel. The derived bulk density of the two warm–low cases (28 February and 7 March 2018) shares a similar transition as the systems were decaying. The higher bulk density and bulk water fraction were found in the coastal sites (BKC and GWU have a median value of ρbulk and are 0.05 to 0.12 g cm−3), typically accompanied by higher liquid-water constituents (mean values of the top 5 % bulk water fraction are 0.07 to 0.45) than the inland sites (YPO and MHS have a median value of ρbulk and are 0.06 to 0.10, and mean values of the top 5 % bulk water fraction are 0.001 to 0.008) during such synoptic conditions.

The Weather Research and Forecasting (WRF) double-moment 6-class (WDM6) scheme was modified by incorporating predicted graupel density. Explicitly predicted graupel density, in turn, modifies graupel characteristics such as the fall velocity–diameter and mass–diameter relationships of graupel. The modified WDM6 has been evaluated based on a two-dimensional (2D) idealized squall line simulation and winter snowfall events that occurred during the International Collaborative Experiment for Pyeongchang Olympics and Paralympics (ICE-POP 2018) field campaign over the Korean Peninsula. From the 2D simulation, we confirmed that the modified WDM6 can simulate varying graupel densities, ranging from low values in an anvil cloud region to high values in the convective region at the mature stage of a squall line. Simulations with the modified WDM6 increased graupel amounts at the surface and decreased graupel aloft because of the faster sedimentation of graupel for two winter snowfall cases during the ICE-POP 2018 campaign, as simulated in the 2D idealized model. The altered graupel sedimentation in the modified WDM6 influenced the magnitude of the major microphysical processes of graupel and snow, subsequently reducing the surface snow amount and precipitation over the mountainous region. The reduced surface precipitation over the mountainous region mitigates the surface precipitation bias observed in the original WDM6, resulting in better statistical skill scores for the root mean square errors. Notably, the modified WDM6 reasonably captures the relationship between graupel density and its fall velocity, as retrieved from 2D video disdrometer measurements, thus emphasizing the necessity of including predicted graupel density to realistically represent the microphysical properties of graupel in models.

Aims: Relapse is a common characteristic of compulsive behaviors like addiction, where individuals tend to return to drug use or overeating after a period of abstinence. PFC (prefrontal cortex) neuronal ensembles are required for drug and food-seeking behaviors and are partially regulated by Norepinephrine (NE). However, the contributions of neuromodulators, such as the adrenergic system, in food-seeking behavior are not fully understood. Main methods: To investigate this, we trained male and female rats to press a lever in an operant chamber to obtain banana-flavored food pellets for ten days. We then administered DSP-4 (N-(2-chloroethyl)-N-ethyl-2-bromobenzylamine hydrochloride), a neurotoxin that diminishes norepinephrine levels in the brain. The rats were kept in their home cages for ten more days before being returned to the operant chambers to measure food-seeking behavior. Key findings: Despite receiving DSP-4, the PFC neuronal ensembles measured by Fos and food-seeking behavior did not differ between groups, but rather sex. Significance: Although both NE and Fos expressing neurons are implicated in food-seeking, they do not seem to be involved in a cue-contextual induced re-exposure response.

Introduction An “escape room” is a game requiring teamwork and problem-solving during which a series of puzzles are solved to escape a locked room. Various escape room activities have been designed for healthcare professionals, including internal medicine residents and nursing students (Anderson et al. Simulation & Gaming 2021; 52(1) 7-17; Rodríguez-Ferrer et al. BMC Med Educ 2022; 22:901; Khanna et al. Cureus 2021; 13 (9) e18314). Escape rooms provide an opportunity for social activity, an important component of resident wellness (Mari et al. BMC Med Educ 2019; 19(1):437). This abstract describes an escape room challenge designed and implemented at our psychiatry residency program quarterly wellness afternoon event, which is an afternoon session dedicated to resident wellness. Objectives The objective of this project was to design and implement an escape room challenge containing multiple game mechanics, including hidden roles, information asymmetry, acting, logical deduction, and spying. This activity was conducted to enhance bonding among residents while reinforcing knowledge in psychiatry. Methods We designed and implemented an escape room for 22 residents. Residents were divided into four teams each tasked with completing a sequence of puzzles to open the final lockbox. Two novel mechanics were added to the activity. Each team had a “clue holder” with clues to help solve all the puzzles. This team member had to conceal their identity because, if any of the other teams identified this person, the original winning team would have to give up the prize to the team that guessed the identity of this person. One member of each team was assigned a “spy” role whose mission was to make it hard for the clue holder to reveal all the clues. An anonymous post-activity survey was completed using Google Forms. Results The script was set in a fictional, abandoned psychiatric emergency room. The first task was a visual puzzle of a historic figure in psychiatry. The second activity involved residents guessing the psychotropic medication being acted out by another resident in the style of charades. The third activity required residents to apply developmental milestones to decode a combination lock. The fourth puzzle involved residents solving riddles by using information gathered from resident profiles on the residency program website. Eleven (50%) residents completed the post-game survey. All residents answered true or very true that they enjoyed the game and that participation helped them better connect with their peers. Eight (73%) residents answered true or very true that they learned something from the activity. Conclusions An adapted escape room challenge is a novel wellness activity that enhance resident collegiality, teamwork, and bonding. All residents who completed the post-activity survey indicated that they enjoyed the activity and felt more connected to their peers afterwards. Disclosure of Interest None Declared

Nitrous acid (HONO) plays an important role in the formation of ozone and fine aerosols in the urban atmosphere. In this study, a new simulation approach is presented to calculate the HONO mixing ratios using a deep neural technique based on measured variables. The Reactive Nitrogen Species using a Deep Neural Network (RND) simulation is implemented in Python. The first version of RND (RNDv1.0) is trained, validated, and tested with HONO measurement data obtained in Seoul, South Korea, from 2016 to 2021. RNDv1.0 is constructed using k-fold cross validation and evaluated with index of agreement, correlation coefficient, root mean squared error, and mean absolute error. The results show that RNDv1.0 adequately represents the main characteristics of the measured HONO, and it is thus proposed as a supplementary model for calculating the HONO mixing ratio in a polluted urban environment.

The WISSDOM (Wind Synthesis System using Doppler Measurements) synthesis scheme was developed to derive high-resolution 3-dimensional (3D) winds under clear-air conditions. From this variational-based scheme, detailed wind information was obtained from scanning Doppler lidars, automatic weather stations (AWSs), sounding observations, and local reanalysis datasets (LDAPS, Local Data Assimilation and Prediction System), which were utilized as constraints to minimize the cost function. The objective of this study is to evaluate the performance and accuracy of derived 3D winds from this modified scheme. A strong wind event was selected to demonstrate its performance over complex terrain in Pyeongchang, South Korea. The size of the test domain is 12×12 km2 extended up to 3 km a.m.s.l. (above mean sea level) height with a remarkably high horizontal and vertical resolution of 50 m. The derived winds reveal that reasonable patterns were explored from a control run, as they have significant similarity with the sounding observations. The results of intercomparisons show that the correlation coefficients between derived horizontal winds and sounding observations are 0.97 and 0.87 for u- and v-component winds, respectively, and the averaged bias (root mean square deviation, RMSD) of horizontal winds is between −0.78 and 0.09 (1.77 and 1.65) m s−1. The correlation coefficients between WISSDOM-derived winds and lidar QVP (quasi-vertical profile) are 0.84 and 0.35 for u- and v-component winds, respectively, and the averaged bias (RMSD) of horizontal winds is between 2.83 and 2.26 (3.69 and 2.92) m s−1. The statistical errors also reveal a satisfying performance of the retrieved 3D winds; the median values of wind directions are −5 to 5 (0 to 2.5)∘, the wind speed is approximately −1 to 3 m s−1 (−1 to 0.5 m s−1), and the vertical velocity is −0.2 to 0.6 m s−1 compared with the lidar QVP (sounding observations). A series of sensitivity tests with different weighting coefficients, radius of influence (RI) in interpolation, and various combination of different datasets were also performed. The results indicate that the present setting of the control run is the optimal reference to WISSDOM synthesis in this event and will help verify the impacts against various scenarios and observational references in this area.

As a component of the National Aeronautics and Space Administration's (NASA's) Weather Focus Area and Global Precipitation Measurement (GPM) Ground Validation participation in the International Collaborative Experiments for the PyeongChang 2018 Olympic and Paralympic Winter Games' (ICE-POP 2018) field research and forecast demonstration programs, hourly ocean surface meteorology properties were retrieved from the GPM microwave observations for January–March 2018. In this study, the retrieved ocean surface meteorological products – 2 m temperature, 2 m specific humidity, and 10 m wind speed – were assimilated into a regional numerical weather prediction (NWP) framework. This explored the application of these observations for two heavy snowfall events during the ICE-POP 2018, on 27–28 February and 7–8 March 2018. The Weather Research and Forecasting (WRF) model and the community Gridpoint Statistical Interpolation (GSI) were used to conduct high-resolution simulations and data assimilation experiments. The results indicate that the data assimilation has a large influence on surface thermodynamic and wind fields in the model initial condition for both events. With cycled data assimilation, a significantly positive influence of the retrieved surface observation was found for the March case, with improved quantitative precipitation forecasts and reduced errors in temperature forecasts. A slightly smaller yet positive impact was also found in the forecast for the February case.

In blue-ice areas (BIAs), deep ice is directly exposed at the surface, allowing for the cost-effective collection of large-sized old-ice samples. However, chronostratigraphic studies on blue-ice areas are challenging owing to fold and fault structures. Here, we report on a surface transect of ice with an undisturbed horizontal stratigraphy from the Larsen BIA, northern Victoria Land, East Antarctica. Ice layers defined by dust bands and ground-penetrating radar (GPR) surveys indicate a monotonic increase in age along the ice flow direction on the downstream side, while the upstream ice exhibits a potential repetition of ages on scales of tens of meters, which result from a complicated fold structure. Stable water isotopes (δ18Oice and δ2Hice) and components of the occluded air (i.e., CO2, N2O, CH4, δ15N–N2, δ18Oatm (=δ18O-O2), δO2/N2, δAr/N2​​​​​​​, 81Kr, and 85Kr) are analyzed for surface ice and shallow ice core samples. Correlating δ18Oice, δ18Oatm, and CH4 records from the Larsen BIA with ice from previously drilled ice cores indicates that the gas age at various shallow vertical coring sites ranges between 9.2–23.4 kyr BP, while the ice age sampled from the surface ranges from 5.6 to 24.7 kyr BP. Absolute radiometric 81Kr dating for the two vertical cores confirms ages within acceptable levels of analytical uncertainty. A tentative climate reconstruction suggests a large deglacial warming of 15 ± 5 ∘C (1σ) and an increase in snow accumulation by a factor of 1.7–4.6 (from 24.3 to 10.6 kyr BP). Our study demonstrates that BIAs in northern Victoria Land may help to obtain high-quality records for paleoclimate and atmospheric greenhouse gas compositions through the last deglaciation, although in general climatic interpretation is complicated by the need for upstream flow corrections, evidence for strong surface sublimation during the last glacial period, and potential errors in the estimated gas age–ice age difference.

This study evaluates the performance of four bulk-type microphysics schemes, Weather Research and Forecasting (WRF) double-moment 6-class (WDM6), WRF double-moment 7-class (WDM7), Thompson, and Morrison, focusing on hydrometeors and microphysics budgets in the WRF model version 4.1.3. Eight snowstorm cases, which can be sub-categorized as cold-low, warm-low, and air–sea interaction cases are selected, depending on the synoptic environment during the International Collaborative Experiment for Pyeongchang Olympics and Paralympics (ICE-POP 2018) field campaign. All simulations present a positive bias in the simulated surface precipitation for cold-low and warm-low cases. Furthermore, the simulations for the warm-low cases show a higher probability of detection score than simulations for the cold-low and air–sea interaction cases even though the simulations fail to capture the accurate transition layer for wind direction. WDM6 and WDM7 simulate abundant cloud ice for the cold-low and warm-low cases, and thus snow is mainly generated by aggregation. Meanwhile, Thompson and Morrison schemes simulate insignificant cloud ice amounts, especially over the lower atmosphere, where cloud water is simulated instead. Snow in the Thompson and Morrison schemes is mainly formed by the accretion between snow and cloud water and deposition. The melting process is analyzed as a key process to generate rain in all schemes. The discovered positive precipitation bias for the warm-low and cold-low cases can be mitigated by reducing the melting efficiency in all schemes. The contribution of melting to rain production is reduced for the air–sea interaction case with decreased solid-phase hydrometeors and increased cloud water in all simulations.

Powder bed 3D printing is an additive manufacturing process that combines powder particles by selectively depositing a liquid activator on a powder bed. Sand molds for high-resolution casting can be realized as a high-quality green body via powder bed 3D printing. In this study, we investigated the effect of vertical penetration of aqueous droplets on the quality of the green body formed from a cement-mixed sand powder. The cement was hydrated by aqueous droplets and acted as a binder between the sand particles. The penetration ratio of the prepared powders was calculated from the penetration depth and spread diameter. Evidently, the penetration ratio and penetration resolution determined the strength and surface resolution of the green body. The results showed that an increase in the silica sand grain size led to a desirable penetration resolution with a relatively high green body strength at the same cement content. Additionally, the green body made from the sand with a particle size of 70 μm showed a relatively high green body strength and an excellent green body surface resolution even at 5% cement content, and it was determined that the green body strength and resolution depend on the penetration pattern.

As fossil fuel depletion and environmental pollution problems are becoming increasingly more serious, interest in the efficient use of natural resources and alternative energy is rapidly growing. In particular, interest in fuels stored as high-pressure gases such as natural gas and hydrogen is also rising. Ultrasonic waves show various received signals according to characteristics such as density of the medium and acoustic impedance. An experimental study on the detection of the micro-leakage of fuel stored as high-pressure gas was conducted based on the characteristics of ultrasonic waves. First, an ultrasonic sensor was manufactured by selecting the matching layer with consideration of the acoustic impedance. In the experiment, a mass flow controller (MFC) was attached to a perforated hole in the fabricated chamber to generate micro-leakage, and the signal from the receiving ultrasonic sensor was then collected. The envelope signal of the received ultrasonic sensor signal was analyzed through the Gaussian distribution method. The temperature inside the chamber and the received voltage decreased according to a similar trend and showed a nonlinear result. However, the phase of the received ultrasonic sensor signal showed a relatively linear result according to the internal pressure change. Micro-leakage could not be detected with only the received voltage seen by the ultrasonic sensor. Therefore, the phase shift of the receiving ultrasonic sensor can be used to detect micro-leakage in a high-pressure gas tank.

Snowfall in the northeastern part of South Korea is the result of complex snowfall mechanisms due to a highly contrasting terrain combined with nearby warm waters and three synoptic pressure patterns. All these factors together create unique combinations, whose disentangling can provide new insights into the microphysics of snow on the planet. This study focuses on the impact of wind flow and topography on the microphysics drawing of 20 snowfall events during the ICE-POP 2018 (International Collaborative Experiment for PyeongChang 2018 Olympic and Paralympic winter games) field campaign in the Gangwon region. The vertical structure of precipitation and size distribution characteristics are investigated with collocated MRR (micro rain radar) and PARSIVEL (particle size velocity) disdrometers installed across the mountain range. The results indicate that wind shear and embedded turbulence were the cause of the riming process dominating the mountainous region. As the strength of these processes weakens from the mountainous region to the coastal region, riming became less significant and gave way to aggregation. This study specifically analyzes the microphysical characteristics under three major synoptic patterns: air–sea interaction, cold low, and warm low. Air–sea interaction pattern is characterized by more frequent snowfall and vertically deeper precipitation systems on the windward side, resulting in significant aggregation in the coastal region, with riming featuring as a primary growth mechanism in both mountainous and coastal regions. The cold-low pattern is characterized by a higher snowfall rate and vertically deep systems in the mountainous region, with the precipitation system becoming shallower in the coastal region and strong turbulence being found in the layer below 2 km in the mountainous upstream region (linked with dominant aggregation). The warm-low pattern features the deepest system: precipitation here is enhanced by the seeder–feeder mechanism with two different precipitation systems divided by the transition zone (easterly below and westerly above). Overall, it is found that strong shear and turbulence in the transition zone is a likely reason for the dominant riming process in the mountainous region, with aggregation being important in both mountainous and coastal regions.

Abstract Predictions for the Higgs masses are a distinctive feature of supersymmetric extensions of the Standard Model, where they play a crucial role in constraining the parameter space. The discovery of a Higgs boson and the remarkably precise measurement of its mass at the LHC have spurred new efforts aimed at improving the accuracy of the theoretical predictions for the Higgs masses in supersymmetric models. The “Precision SUSY Higgs Mass Calculation Initiative” (KUTS) was launched in 2014 to provide a forum for discussions between the different groups involved in these efforts. This report aims to present a comprehensive overview of the current status of Higgs-mass calculations in supersymmetric models, to document the many advances that were achieved in recent years and were discussed during the KUTS meetings, and to outline the prospects for future improvements in these calculations.

This article describes a 4-month dataset of precipitation and cloud measurements collected during the International Collaborative Experiments for PyeongChang 2018 Olympic and Paralympic winter games (ICE-POP 2018). This paper aims to describe the data collected by the Environmental Remote Sensing Laboratory of the École Polytechnique Fédérale de Lausanne. The dataset includes observations from an X-band dual-polarisation Doppler radar, a W-band Doppler cloud profiler, a multi-angle snowflake camera and a two-dimensional video disdrometer (https://doi.org/10.1594/PANGAEA.918315, Gehring et al., 2020a). Classifications of hydrometeor types derived from dual-polarisation measurements and snowflake photographs are presented. The dataset covers the period from 15 November 2017 to 18 March 2018 and features nine precipitation events with a total accumulation of 195 mm of equivalent liquid precipitation. This represents 85 % of the climatological accumulation over this period. To illustrate the available data, measurements corresponding to the four precipitation events with the largest accumulation are presented. The synoptic situations of these events were contrasted and influenced the precipitation type and accumulation. The hydrometeor classifications reveal that aggregate snowflakes were dominant and that some events featured significant riming. The combination of dual-polarisation variables and high-resolution Doppler spectra with ground-level snowflake images makes this dataset particularly suited to study snowfall microphysics in a region where such measurements were not available before.

Ground-based radar and radiometer data observed during the 2017–2018 winter season over the Pyeongchang area on the east coast of the Korean Peninsula were used to simultaneously estimate both the cloud liquid water path and snowfall rate for three types of snow clouds: near-surface, shallow, and deep. Surveying all the observed data, it is found that near-surface clouds are the most frequently observed cloud type with an area fraction of over 60 %, while deep clouds contribute the most in snowfall volume with about 50 % of the total. The probability distributions of snowfall rates are clearly different among the three types of clouds, with the vast majority hardly reaching 0.3 mm h−1 (liquid water equivalent snowfall rate) for near-surface, 0.5 mm h−1 for shallow, and 1 mm h−1 for deep clouds. However, the liquid water paths in the three types of clouds all have the substantial probability to reach 500 g m−2. There is no clear correlation found between snowfall rate and the liquid water path for any of the cloud types. Based on all observed snow profiles, brightness temperatures at Global Precipitation Measurement Microwave Imager (GPM/GMI) channels are simulated, and the ability of a Bayesian algorithm to retrieve snowfall rate is examined using half the profiles as observations and the other half as an a priori database. Under an idealized scenario, i.e., without considering the uncertainties caused by surface emissivity, ice particle size distribution, and particle shape, the study found that the correlation as expressed by R2 between the “retrieved” and “observed” snowfall rates is about 0.32, 0.41, and 0.62, respectively, for near-surface, shallow, and deep snow clouds over land surfaces; these numbers basically indicate the upper limits capped by cloud natural variability, to which the retrieval skill of a Bayesian retrieval algorithm can reach. A hypothetical retrieval for the same clouds but over ocean is also studied, and a major improvement in skills is found for near-surface clouds with R2 increasing from 0.32 to 0.52, while a smaller improvement is found for shallow and deep clouds. This study provides a general picture of the microphysical characteristics of the different types of snow clouds and points out the associated challenges in retrieving their snowfall rate from passive microwave observations.

LIDAR is being widely used for mapping and modelling because it accurately scans and acquires 3D geometric information of the surrounding environment. In order to improve the accuracy of the LIDAR measurement, it is necessary to precisely estimate the intrinsic parameters as well as extrinsic parameters and eliminate the systematic errors. Many studies are conducted to eliminate these errors caused by the intrinsic parameters of LIDAR. However, when the result of intrinsic calibration is verified using actual LIDAR data, there is a problem that other error factors cannot be excluded. Therefore, in this study, the LIDAR intrinsic calibration is verified by using a LIDAR simulator that simulates the mechanism of the actual LIDAR. When constructing a LIDAR simulator, the systematic error is inserted according to the intrinsic parameter model of LIDAR. And according to the method of scanning with LIDAR, it is divided into upright scanning and tilted scanning, and the error included LIDAR simulation data is generated. After that, the intrinsic parameters are estimated by applying the plane-based intrinsic calibration. Since values of the intrinsic parameters are known, they are compared with the estimated parameters, and the results of estimate are analyzed according to the scanning method.

This paper focus on traffic light distance measurement using stereo camera which is a very important and challenging task in image processing domain, where it is used in several systems such as Driving Safety Support Systems (DSSS), autonomous driving and traffic mobility. In this paper, we propose an integrated traffic light distance measurement system for self-driving based on stereo image processing. Therefore, an algorithm to spatially locate the detected traffic light is required in order to make these detections useful. In this paper, an algorithm to detect, classify the traffic light colours and spatially locate traffic light are integrated. Detection and colours classification are made simultaneously via YOLOv3, using RGB images. 3D traffic light localization is achieved by estimating the distance from the vehicle to the traffic light, by looking at detector 2D bounding boxes and the disparity map generated by stereo camera. Moreover, Gaussian YOLOv3 weights based on KITTI and Berkeley datasets has been replaced with the COCO dataset. Therefore, a detection algorithm that can cope with mislocalizations is required in autonomous driving applications. This paper proposes an integrated method for improving the detection accuracy and traffic lights colours classification while supporting a real-time operation by modelling the bounding box (bbox) of YOLOv3. The obtained results show fair results within 20 meters away from the sensor, while misdetection and classification appeared in further distance.

This study aimed to develop a risk-based approach for determining control areas to manage non-point source pollution, developing a framework to prioritize catchments by considering the characteristics of polluted runoff from non-point sources. The best management, decision-making, and scientific approaches, such as the technique for order of preference by similarity to ideal solution (TOPSIS) and the Delphi technique, are required for the designation of control areas and the application of the best management practices to the control areas. Multi-criteria decision-making (MCDM) methods can handle the diversity and complexity of non-point source pollution. The Delphi technique was employed for selecting the assessment criteria/sub-criteria and determining their weights. Sub-criteria for each catchment unit were scored with either a quantitative or qualitative scale. All non-point pollution sources in mainland Republic of Korea were included, with the exception of a few islands, with catchment prioritization and pollution vulnerability evaluations shown as thematic maps. This study contributes to the field by developing a new risk-based approach for ranking and prioritizing catchments; this provides valuable information for the Ministry of Environment to use to identify control areas and manage non-point source pollution.

Throughout prolonged tasks, visual attention fluctuates temporally in response to the present stimuli, task demands, and changes in available attentional resources. This temporal fluctuation has downstream effects on memory for stimuli presented during the task. Researchers have established that detection of a target (e.g., a square of a color to which participants are instructed to respond with a button press) within a rapid serial visual presentation (RSVP) stream leads to better memory for concurrently presented stimuli than for stimuli presented along with an RSVP distractor (e.g., a square of a color to which participants are instructed to withhold response). Although debates have arisen regarding whether this memory difference, termed the attentional boost effect, results from target-induced enhancement, distractor-induced impairment, or a combination of the two, researchers have largely come to focus on explanations that consider only target-induced memory enhancement. In the present study, we show across three large-sampled experiments a consistent appearance of both target-induced memory enhancement and distractor-induced memory impairment relative to a baseline. In each experiment, participants responded with a spacebar press to squares of one color in an RSVP stream while withholding response to squares of another color and trials with no square (baseline trials). They simultaneously memorized concurrently presented objects. The presence of both enhancement and impairment in these experiments invites the development of new dual-task research that considers distractor-induced memory impairment and the control of temporal selection across tasks.

Increasing evidence has shown that implicit learning shapes visuospatial attention, yet how such learning interacts with top-down, goal-driven attention remains unclear. This study investigated the relationship between task goals and selection history using a location probability learning (LPL) paradigm. We tested whether a top-down spatial cue facilitates or interferes with the acquisition of implicit LPL. In a visual search task, participants were asked to give precedence to one of four, spatially cued, quadrants of the screen. Unbeknownst to them, there was an underlying uneven spatial probability in which the target appeared disproportionately often in the cued quadrant (37.5%) and a second, uncued quadrant (37.5%). To assess what participants had learned, neutral, uncued testing trials with an equal target location probability (25%) were used. Results revealed faster search times in the cued and the uncued high-probability quadrants compared to the two low-probability quadrants and these fast search times remained prevalent in the neutral testing blocks. Importantly, LPL was comparable between the cued and uncued locations in the testing blocks, suggesting that the spatial cue neither facilitated nor interfered with LPL. These results support the dual-system view of attention, revealing parallel systems supporting both goal-driven and experience-guided attention.

quantitative precipitation estimation (QPE) of snowfall has generally been expressed in power-law form between equivalent radar reflectivity factor (Ze) and liquid equivalent snow rate (SR). It is known that there is large variability in the prefactor of the power law due to changes in particle size distribution (PSD), density, and fall velocity, whereas the variability of the exponent is considerably smaller. The dual-wavelength radar reflectivity ratio (DWR) technique can improve SR accuracy by estimating one of the PSD parameters (characteristic diameter), thus reducing the variability due to the prefactor. The two frequencies commonly used in dual-wavelength techniques are Ku- and Ka-bands. The basic idea of DWR is that the snow particle size-to-wavelength ratio is falls in the Rayleigh region at Ku-band but in the Mie region at Ka-band. We propose a method for snow rate estimation by using NASA D3R radar DWR and Ka-band reflectivity observations collected during a long-duration synoptic snow event on 30–31 January 2012 during the GCPEx (GPM Cold-season Precipitation Experiment). Since the particle mass can be estimated using 2-D video disdrometer (2DVD) fall speed data and hydrodynamic theory, we simulate the DWR and compare it directly with D3R radar measurements. We also use the 2DVD-based mass to compute the 2DVD-based SR. Using three different mass estimation methods, we arrive at three respective sets of Z–SR and SR(Zh, DWR) relationships. We then use these relationships with D3R measurements to compute radar-based SR. Finally, we validate our method by comparing the D3R radar-retrieved SR with accumulated SR directly measured by a well-shielded Pluvio gauge for the entire synoptic event.

Abstract The relic abundance of heavy stable particles charged under a confining gauge group can be depleted by a second stage of annihilations near the deconfinement temperature. This proceeds via the formation of quarkonia-like states, in which the heavy pair subsequently annihilates. The size of the quarkonium formation cross section was the subject of some debate. We estimate this cross section in a simple toy model. The dominant process can be viewed as a rearrangement of the heavy and light quarks, leading to a geometric cross section of hadronic size. In contrast, processes in which only the heavy constituents are involved lead to mass-suppressed cross sections. These results apply to any scenario with bound states of sizes much larger than their inverse mass, such as U(1) models with charged particles of different masses, and can be used to construct ultra-heavy dark-matter models with masses above the naïve unitarity bound. They are also relevant for the cosmology of any stable colored relic.

Abstract We propose a new variable, the charm fraction, for collider searches for new physics. We analyze this variable in the context of searches for simplified supersymmetry models with squarks, the gluino, and the bino, assuming that only the lightest massdegenerate squarks can be produced at the high-luminosity LHC. The charm fraction complements event counting and kinematic information, increasing the sensitivity of the searches for models with heavy gluinos, for which squark production is flavor-blind. If squarks are discovered at the LHC, this variable can help discriminate between different underlying models. In particular, with improved charm tagging, the charm fraction can provide information on the gluino mass, and in some scenarios, on whether this mass is within the reach of a future 100 TeV hadron collider.

We measured peroxyacetyl nitrate (PAN) and other reactive species such as O3, NO2, CO, and SO2 with aerosols including mass, organic carbon (OC), and elemental carbon (EC) in PM2. 5 and K+ in PM1. 0 at Gosan Climate Observatory in Korea (33.17° N, 126.10° E) during 19 October–6 November 2010. PAN was determined through fast gas chromatography with luminol chemiluminescence detection at 425 nm every 2 min. The PAN mixing ratios ranged from 0.1 (detection limit) to 2.4 ppbv with a mean of 0.6 ppbv. For all measurements, PAN was unusually better correlated with PM2. 5 (Pearson correlation coefficient, γ = 0.79) than with O3 (γ = 0.67). In particular, the O3 level was highly elevated with SO2 at midnight, along with a typical midday peak when air was transported rapidly from the Beijing areas. The PAN enhancement was most noticeable during the occurrence of haze under stagnant conditions. In Chinese outflows slowly transported over the Yellow Sea, PAN gradually increased up to 2.4 ppbv at night, in excellent correlation with a concentration increase in PM2. 5 OC and EC, PM2. 5 mass, and PM1. 0 K+. The high K+ concentration and OC ∕ EC ratio indicated that the air mass was impacted by biomass combustion. This study highlights PAN decoupling with O3 in Chinese outflows and suggests PAN as a useful indicator for diagnosing continental outflows and assessing their perturbation of regional air quality in northeast Asia.

Although precipitation has been measured for many centuries, precipitation measurements are still beset with significant inaccuracies. Solid precipitation is particularly difficult to measure accurately, and wintertime precipitation measurement biases between different observing networks or different regions can exceed 100 %. Using precipitation gauge results from the World Meteorological Organization Solid Precipitation Intercomparison Experiment (WMO-SPICE), errors in precipitation measurement caused by gauge uncertainty, spatial variability in precipitation, hydrometeor type, crystal habit, and wind were quantified. The methods used to calculate gauge catch efficiency and correct known biases are described. Adjustments, in the form of transfer functions that describe catch efficiency as a function of air temperature and wind speed, were derived using measurements from eight separate WMO-SPICE sites for both unshielded and single-Alter-shielded precipitation-weighing gauges. For the unshielded gauges, the average undercatch for all eight sites was 0.50 mm h−1 (34 %), and for the single-Alter-shielded gauges it was 0.35 mm h−1 (24 %). After adjustment, the mean bias for both the unshielded and single-Alter measurements was within 0.03 mm h−1 (2 %) of zero. The use of multiple sites to derive such adjustments makes these results unique and more broadly applicable to other sites with various climatic conditions. In addition, errors associated with the use of a single transfer function to correct gauge undercatch at multiple sites were estimated.

Autonomous underwater gliders offer the capability of measuring oceanic parameters continuously at high resolution in both vertical and horizontal planes, with timescales that can extend to many months. An experimental ion-sensitive field-effect transistor (ISFET) sensor measuring pH on the total scale was attached to a glider during the REP14-MED experiment in June 2014 in the Sardinian Sea in the northwestern Mediterranean. During the deployment, pH was sampled at depths of up to 1000 m along an 80 km transect over a period of 12 days. Water samples were collected from a nearby ship and analysed for dissolved inorganic carbon concentration and total alkalinity to derive the pH for validating the ISFET sensor measurements. The vertical resolution of the pH sensor was good (1 to 2 m), but stability was poor and the sensor drifted in a non-monotonous fashion. In order to remove the sensor drift, a depth-constant time-varying offset was applied throughout the water column for each dive, reducing the spread of the data by approximately two-thirds. Furthermore, the ISFET sensor required temperature- and pressure-based corrections, which were achieved using linear regression. Correcting for this decreased the apparent sensor pH variability by a further 13 to 31 %. Sunlight caused an apparent sensor pH decrease of up to 0.1 in surface waters around local noon, highlighting the importance of shielding the sensor from light in future deployments. The corrected pH from the ISFET sensor is presented along with potential temperature, salinity, potential density anomalies (σθ), and dissolved oxygen concentrations (c(O2)) measured by the glider, providing insights into the physical and biogeochemical variability in the Sardinian Sea. The pH maxima were identified close to the depth of the summer chlorophyll maximum, where high c(O2) values were also found. Longitudinal pH variations at depth (σθ > 28. 8 kg m−3) highlighted the variability of water masses in the Sardinian Sea. Higher pH was observed where salinity was > 38. 65, and lower pH was found where salinity ranged between 38.3 and 38.65. The higher pH was associated with saltier Levantine Intermediate Water, and it is possible that the lower pH was related to the remineralisation of organic matter. Furthermore, shoaling isopycnals closer to shore coinciding with low pH and c(O2), high salinity, alkalinity, dissolved inorganic carbon concentrations, and chlorophyll fluorescence waters may be indicative of upwelling.

We report on the first detailed study of intruder configurations in the ground state of 30Ne by means of the 12C(30Ne, 29Ne+γ)X one-neutron knockout reaction at 228 MeV/nucleon. Using a combined analysis of individual parallel momentum distributions and partial cross sections we find: (a) comparable p- and d-wave removal strength to 29Ne final states with excitation energies below 200 keV, and (b) significant p-wave removal strength to the 620 keV state of 29Ne, and (c) no evidence for f-wave intruder strength leading to bound 29Ne final states. The SDPF-U-MIX shell model calculation in the sd–pf model space provides a better overall agreement with the measured energy levels of 29Ne and the fp-intruder amplitudes in 30Ne than the SDPF-M prediction, suggesting that the refinement of the sd–pf cross shell interaction and extension of the model space to include the 2p1/2 and 1f5/2 levels are important for understanding the island of inversion.

Ieodo Ocean Research Station (IORS), a research tower (~ 40 m a.s.l.) for atmospheric and oceanographic observations, is located in the East China Sea (32.07° N, 125.10° E). The IORS is almost equidistant from South Korea, China, and Japan and, therefore, it is an ideal place to observe Asian outflows without local emission effects. The seasonal variation of ozone was distinct, with a minimum in August (37 ppbv) and two peaks in April and October (62 ppbv), and was largely affected by the seasonal wind pattern over east Asia. At IORS, six types of air masses were distinguished with different levels of O3 concentrations by the cluster analysis of backward trajectories. Marine air masses from the Pacific Ocean represent a relatively clean background air with a lowest ozone level of 32 ppbv, which was most frequently observed in summer (July–August). In spring (March–April) and winter (December–February), the influence of Chinese outflows was dominant with higher ozone concentrations of 62 and 49 ppbv, respectively. This study confirms that the influence of Chinese outflows was the main factor determining O3 levels at IORS and its extent was dependent on meteorological state, particularly at a long-term scale.

This study proposes an improved group decision making (GDM) framework that combines the VIKOR method with data fuzzification to quantify the spatial flood vulnerability including multiple criteria. In general, GDM method is an effective tool for formulating a compromise solution that involves various decision makers since various stakeholders may have different perspectives on their flood risk/vulnerability management responses. The GDM approach is designed to achieve consensus building that reflects the viewpoints of each participant. The fuzzy VIKOR method was developed to solve multi-criteria decision making (MCDM) problems with conflicting and noncommensurable criteria. This comprising method can be used to obtain a nearly ideal solution according to all established criteria. This approach effectively can propose some compromising decisions by combining the GDM method and fuzzy VIKOR method. The spatial flood vulnerability of the southern Han River using the GDM approach combined with the fuzzy VIKOR method was compared with the spatial flood vulnerability using general MCDM methods, such as the fuzzy TOPSIS and classical GDM methods (i.e., Borda, Condorcet, and Copeland). As a result, the proposed fuzzy GDM approach can reduce the uncertainty in the data confidence and weight derivation techniques. Thus, the combination of the GDM approach with the fuzzy VIKOR method can provide robust prioritization because it actively reflects the opinions of various groups and considers uncertainty in the input data.

Carbonaceous and soluble ionic species of PM1.0 and PM10 were measured along with the absorption and scattering properties and aerosol number size distributions at Gosan Climate Observatory (GCO) from January to September 2008. The daily averaged equivalent black carbon (EBC) measured as aerosol absorption exhibited two types of spectral dependence with a distinct maximum (peak) at either 370 nm or 880 nm, by which two subsets were extracted and classified into the respective groups (370 and 880 nm). The 370 nm group was distinguished by high organic carbon (OC) concentrations relative to elemental carbon (EC) and sulfate, but sulfate was predominant for the 880 nm group. The PM1.0 OC of the 370 nm group was mainly composed of refractory and pyrolized components that correlated well with PM1.0 EC1, referred to as char EC, which suggests biofuel and biomass combustion as the source of these OC fractions, particularly during winter. The scanning electron microscope (SEM) images and the number size distributions implied that aerosols of the 370 nm group were externally mixed upon transport in fast-moving air masses that passed through the Beijing area in about one day. In contrast, the aerosols of the 880 nm group were characterized by high sulfate concentrations, and seemed to be internally mixed during slow transport over the Yellow Sea region over approximately 2 to 4 days. The absorption and scattering coefficients of the 880 nm group were noticeably higher compared to those of the 370 nm group. The average absorption ångström exponent (AAE) was estimated to be 1.29 and 1.0 for the 370 and 880 nm groups, respectively, in the range 370–950 nm. These results demonstrated that the optical properties of aerosols were intimately linked to chemical composition and mixing state, characteristics determined both by source and atmospheric aging processes. In OC dominant aerosols, absorption was enhanced in the UV region, which was possibly due to refractory and pyrolized OC compounds. Under sulfate dominant conditions, the sulfate coating on BC particles likely contributed to the absorption of the longer visible light. Consequently, single scattering albedo (SSA) was higher for the 880 nm group than for the 370 nm group, emphasizing that the relative abundances of absorbing and scattering constituents are also important in estimating the climate effect of aerosols.

This study aims to develop a new procedure that combines multi-criteria spatial vulnerability analysis with the traditional linear probabilistic risk approach. This approach is named integrated fuzzy flood vulnerability assessment because it combines the watershed-based vulnerability framework with stream-based risk analysis. The Delphi technique and pressure-state-impact-response framework are introduced to objectively select evaluation criteria, and the fuzzy TOPSIS technique is proposed to address the uncertainty of weights to all criteria and crisp input data of all spatial units. ArcGIS is used to represent the spatial results to all criteria. This framework is applied to the south Han River basin in South Korea. As a result, the flood vulnerability ranking was derived and vulnerability characteristics of all spatial units were compared. This framework can be used to conduct a prefeasibility study for flood mitigation projects when various stakeholders should be included.

This study was conducted to determine how the isolation method of the porcine preantral follicles influenced the following follicular growth in vitro. Mechanical and enzymatical isolations were used for retrieving the follicles from prepubertal porcine ovaries, and in vitro-growth of the follicles and the expression of folliculogenesis-related genes were subsequently monitored. The enzymatic retrieval with collagenase treatment returned more follicles than the mechanical retrieval, while the percentage of morphologically normal follicles was higher with mechanical retrieval than with enzymatic retrieval. After 4 days of culture, mechanically retrieved, preantral follicles yielded more follicles with normal morphology than enzymatically retrieved follicles, which resulted in improved follicular growth. The mRNA expression of FSHR, LHR Cx43, DNMT1 and FGFR2 genes was significantly higher after culture of the follicles retrieved mechanically. These results suggest that mechanical isolation is a better method of isolating porcine preantral follicles that will develop into competent oocytes in in vitro culture.

PM1.0, PM2.5, and PM10 were sampled at Gosan ABC Superstation on Jeju Island from August 2007 to September 2008. The carbonaceous aerosols were quantified with the thermal/optical reflectance (TOR) method, which produced five organic carbon (OC) fractions, OC1, OC2, OC3, OC4, and pyrolyzed organic carbon (OP), and three elemental carbon (EC) fractions, EC1, EC2, and EC3. The mean mass concentrations of PM1.0, PM2.5, and PM10 were 13.7 μg m−3, 17.2 μg m−3, and 28.4 μg m−3, respectively. The averaged mass fractions of OC and EC were 23.0% and 10.4% for PM1.0, 22.9% and 9.8% for PM2.5, and 16.4% and 6.0% for PM10. Among the OC and EC sub-components, OC2 and EC2+3 were enriched in the fine mode, but OC3 and OC4 in the coarse mode. The filter-based PM1.0 EC agreed well with black carbon (BC) measured by an Aethalometer, and PM10 EC was higher than BC, implying less light absorption by larger particles. EC was well correlated with sulfate, resulting in good relationships of sulfate with both aerosol scattering coefficient measured by Nephelometer and BC concentration. Our measurements of EC confirmed the definition of EC1 as char-EC emitted from smoldering combustion and EC2+3 as soot-EC generated from higher-temperature combustion such as motor vehicle exhaust and coal combustion (Han et al., 2010). In particular, EC1 was strongly correlated with potassium, a traditional biomass burning indicator, except during the summer, when the ratio of EC1 to EC2+3 was the lowest. We also found the ratios of major chemical species to be a useful tool to constrain the main sources of aerosols, by which the five air masses were well distinguished: Siberia, Beijing, Shanghai, Yellow Sea, and East Sea types. Except Siberian air, the continental background of the study region, Beijing plumes showed the highest EC1 (and OP) to sulfate ratio, which implies that this air mass had the highest net warming by aerosols of the four air masses. Shanghai-type air, which was heavily influenced by southern China, showed the highest sulfate enhancement. The highest EC2+3/EC1 ratio was found in aged East Sea air, demonstrating a significant influence of motor vehicle emissions from South Korea and Japan and less influence from industrial regions of China. The high ratio results from the longer residence time and less sensitivity to wet scavenging of EC2+3 compared to EC1, indicating that soot-EC could have greater consequence in regional-scale warming.

Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system that leads to substantial disability through deficits of sensation and of motor, autonomic, and neuro-cognitive function. Many clinical and pathological features of experimental autoimmune encephalomyelitis (EAE) show close similarity to MS. Bee venom (BV) has been used in the practice of oriental medicine and evidence from the literature indicates that BV plays an anti-inflammatory or anti-nociceptive role against inflammatory reactions associated with arthritis and other inflammatory diseases. The purpose of the present study was to determine whether BV could suppress immune cell differentiation and infiltration into spinal cord on EAE mice commonly used as a model for MS. BV treatment increased the population of CD4 + CD25 + Foxp3 + T cells and inhibited CD4 + T-cell proliferation in vitro. In vivo , BV treatment increased the population of CD4 + CD25 + Foxp3 + T cells. Furthermore, BV administration reduced the severity of EAE while concurrently decreasing INF-γ producing CD4 + T cells, IL-17A producing CD4 + T cells and inflammatory cytokine production including INF-γ, IL-17A, TNF and IL-6. BV-treated animals exhibited less infiltration and preserved morphology compared to saline-treated animals. Interestingly, the therapeutic effects of BV on EAE disappeared when CD4 + CD25 + Foxp3 + T cells were depleted by using anti-CD25 antibody. Our research suggests that BV could be a potential therapeutic agent for antiinflammatory effects in an animal model of EAE.