Time Threshold Research Articles

Three billion new trees in the EU’s biodiversity strategy: low ambition, but better environmental outcomes?

The EU Biodiversity strategy aims to plant 3 billion trees by 2030, in order to improve ecosystem restoration and biodiversity. Here, we compute the land area that would be required to support this number of newly planted trees by taking account of different tree species and planting regimes across the EU member states. We find that 3 billion trees would require a total land area of between 0.81 and 1.37 Mha (avg. 1.02 Mha). The historic forest expansion in the EU since 2010 was 2.44 Mha, meaning that despite 3 billion trees sounding like a large number this target is considerably lower than historic afforestation rates within the EU, i.e. only 40% of the past trend. Abandoned agricultural land is often proposed as providing capacity for afforestation. We estimate agricultural abandoned land areas from the HIstoric Land Dynamics Assessment+ database using two time thresholds (abandonment since 2009 or 2014) to identify potential areas for tree planting. The area of agricultural abandoned land was 2.6 Mha (potentially accommodating 7.2 billion trees) since 2009 and 0.2 Mha (potentially accommodating 741 million trees) since 2014. Our study highlights that sufficient space could be available to meet the 3 billion tree planting target from abandoned land. However, large-scale afforestation beyond abandoned land could have displacement effects elsewhere in the world because of the embodied deforestation in the import of agricultural crops and livestock. This would negate the expected benefits of EU afforestation. Hence, the EU’s relatively low ambition on tree planting may actually be better in terms of avoiding such displacement effects. We suggest that tree planting targets should be set at a level that considers physical ecosystem dynamics as well as socio-economic conditions.

An RSU Deployment Scheme for Vehicle-Infrastructure Cooperated Autonomous Driving

For autonomous driving vehicles, there are currently some issues, such as limited environmental awareness and locally optimal decision-making. To increase the capacity of autonomous cars’ environmental awareness, computation, decision-making, control, and execution, intelligent roads must be constructed, and vehicle–infrastructure cooperative technology must be used. The Roadside unit (RSU) deployment, a critical component of vehicle–infrastructure cooperative autonomous driving, has a direct impact on network performance, operation effects, and control accuracy. The current RSU deployment mostly uses the large-spacing and low-density concept because of the expensive installation and maintenance costs, which can accomplish the macroscopic and long-term communication functions but fall short of precision vehicle control. Given these challenges, this paper begins with the specific requirements to control intelligent vehicles in the cooperative vehicle–infrastructure environment. An RSU deployment scheme, based on the improved multi-objective quantum-behaved particle swarm optimization (MOQPSO) algorithm, is proposed. This RSU deployment scheme was based on the maximum coverage with time threshold problem (MCTTP), with the goal of minimizing the number of RSUs and maximizing vehicle coverage of communication and control services. Finally, utilizing the independently created open simulation platform (OSP) simulation system, the model and algorithm’s viability and effectiveness were assessed on the Nguyen–Dupuis road network. The findings demonstrate that the suggested RSU deployment scheme can enhance network performance and control the precision of vehicle–infrastructure coordination, and can serve as a general guide for the deployment of RSUs in the same application situation.

Construct Trip Graphs by Using Taxi Trajectory Data

The trip graph, which can model the residents’ taxi demands, consists of vertices used to indicate trips and edges used to indicate the follow-up relationships between trips. A trip v_j is a tight follow-up trip of another trip v_i, if a taxi can arrive at the departure location of v_j within a time threshold delta after it finishes v_i. However, for big cities, there are a large amount of trips every day and it is time consuming to construct a trip graph. In this paper, we propose efficient algorithms to construct trip graphs for big cities. When constructing a trip graph, the most expensive step is to connect the vertices if the tight follow-up relationships exist. To find out the tight follow-up trips fast, we design an index considering both spatial and temporal constraints. To designate appropriate search areas, we propose efficient methods to determine the distance-based search areas and the traffic-based search areas. We conduct experiments on real datasets, i.e., the taxi trajectories of Shanghai in 2015. The experimental results show that our algorithm can construct the trip graph about 40 times faster than the straightforward method. We also demonstrate the usages of the trip graph in green transportation applications, i.e., the minimum fleet analysis and the minimum total “idle” mileage analysis.

Perioperative Interventions to Prevent Gastroesophageal Reflux Disease and Marginal Ulcers After Bariatric Surgery - an International Experts' Survey.

This study aimed to survey international experts in metabolic and bariatric surgery (MBS) to improve and consolidate perioperative interventions to prevent gastroesophageal reflux disease (GERD) and marginal ulcers (MU) after MBS. Very important long-term complications after MBS include GERD, Barrett's esophagus, and MU. Prevention might be fundamental to reduce the incidence, severe complications, and the increasing number of revisional bariatric surgeries. An international scientific team designed an online confidential questionnaire with 45 multiple-choice questions. The survey was sent to 110 invited experts and 96 of them (from 41 different countries) participated from 21 July 2022 to 4 September 2022. Most experts (≥ 90%) prescribe postoperative acid suppression agents after MBS. Life-long proton pump inhibitors prophylaxis in smokers with avoidance of non-steroidal anti-inflammatory drugs are recommended by most of the experts (66%, 73%) after any type of gastric bypass. Two-thirds of experts (69%) perform Helicobacter pylori eradication prior to MBS. Two-thirds of experts (68%) routinely perform EGD and biopsy before MBS. Follow-up esophagogastroduodenoscopy (EGD) and timing threshold for revisional and conversional MBS were variable among experts. This expert survey underlines important perioperative interventions that reached a two-thirds consensus among MBS international experts. Variability in follow-up EGD, approach to complication management, and thresholds for revisional and conversional MBS emphasize the need for further researches and consensus guidelines.

UAV-assisted multi-tier computing framework for IoT networks

Next-generation wireless networks are expected to support a massive amount of Internet of Things (IoT) devices in delivering a wide range of novel resource-intensive applications. IoT devices, despite their enhanced capabilities, fall short of meeting the computational requirements of these applications within a strict deadline. This paper leverages a hierarchical computational model where IoT devices offload their computational tasks to a number of unmanned aerial vehicles (UAVs) that can be deployed in a way to establish strong line-of-sight links. Being equipped with computational resources, UAVs process part of the tasks within the set time threshold while the other tasks are transferred to edge and cloud servers for potential processing. This work aims at optimizing the number and position of deployed UAVs, IoT-to-UAV association, resource allocation, and task offloading to UAVs, edge servers, and the cloud, while ensuring various system constraints. The problem is formulated as a mixed integer programming problem and solved using successive convex approximation. An efficient solution is then proposed to decompose the main problem into two subproblems that are solved iteratively. The first subproblem minimizes the number of IoT clusters and positions a UAV to serve each cluster while the second subproblem maximizes the percentage of admitted tasks using the resulting number of UAVs determined by the first subproblem. As long as not all devices are fully served, an additional UAV is introduced and the two subproblems are solved repeatedly. The proposed decomposition solution has been evaluated as a function of various system parameters and application use cases to show optimized performance and high scalability.

Does a time threshold exist for bladder repair after which outcomes worsen? A Trauma Quality Improvement Program study

BackgroundThe appropriate timing of surgical intervention for bladder injuries is not well-defined. The effect of time to surgery on the outcomes of patients with a bladder injury was assessed using data from the Trauma Quality Improvement Program. MethodsPatients with dominant or isolated bladder injuries who underwent surgical repair from 2017 to 2019 were studied. Mortality, infection (surgical site infection or sepsis), acute kidney injury, overall length of stay, and length of stay after surgery were compared between patients who underwent bladder repair within and after 24 hours of arrival at the emergency department. The role of time to surgical repair in the outcomes of patients with a bladder injury was evaluated. ResultsA total of 1,507 patients with a mean time to bladder repair of 14.0 hours were studied. In total, 233 (15.5%) patients with a bladder injury underwent bladder repair more than 1 day after emergency department arrival. These patients had significantly more infections (5.6% vs 2.5%, P = .011), more acute kidney injuries (7.8% vs 1.8%, P < .001), and a longer length of stay after surgery (16.0 vs 12.3 days, P = .001) than patients who underwent bladder repair within 1 day. A time to bladder repair longer than 24 hours after emergency department arrival did not significantly affect mortality (P = .075) but significantly increased the risk of infection/acute kidney injury (odds = 1.823, P = .040). However, the infection/acute kidney injury risk did not increase with increasing time to surgery in patients who underwent bladder repair within 24 hours (P = .120). ConclusionPatients with dominant or isolated bladder injuries may have a poor outcome (ie, increased infection rate, acute kidney injury, longer overall length of stay, and longer length of stay after bladder repair) if they undergo surgical repair more than 24 hours after arrival at the emergency department.

Rapid Guessing in Low-Stakes Assessments: Finding the Optimal Response Time Threshold with Random Search and Genetic Algorithm

Rapid guessing is an aberrant response behavior that commonly occurs in low-stakes assessments with little to no formal consequences for students. Recently, the availability of response time (RT) information in computer-based assessments has motivated researchers to develop various methods to detect rapidly guessed responses systematically. These methods often require researchers to identify an RT threshold subjectively for each item that could distinguish rapid guessing behavior from solution behavior. In this study, we propose a data-driven approach based on random search and genetic algorithm to search for the optimal RT threshold within a predefined search space. We used response data from a low-stakes math assessment administered to over 5000 students in 658 schools across the United States. As we demonstrated how to use our data-driven approach, we also compared its performance with those of the existing threshold-setting methods. The results show that the proposed method could produce viable RT thresholds for detecting rapid guessing in low-stakes assessments. Moreover, compared with the other threshold-setting methods, the proposed method yielded more liberal RT thresholds, flagging a larger number of responses. Implications for practice and directions for future research were discussed.

Exploring the Nonlinearity of Commute-Time Utility Considering Individual Ideal Preferences and Tolerance ThresholdsC: ase Study in Kunming

Exploring the nonlinearity of commute-time utility is useful in predicting urban travel demand. However, existing studies assume that commute utility decreases linearly with commute time. This ignores the influence of commuters’ ideal preferences and tolerance thresholds on commute utility. To reveal the nonlinear variation of commute utility with commute time and its influence on the choice of commute mode, the ideal commute time (ICT) and the tolerance threshold for commute time (TTCT) were introduced. Three-piecewise linear utility models (Models 2, 3, 4) were constructed and compared with the linear utility multinomial logit model (Model 1). The results of empirical study showed that: (a) the goodness of fit of these three modified models is higher than that of Model 1, indicating that the fitting effect of the commute-time utility model can be improved with either or both the ICT and TTCT; (b) there is a nonlinear relationship between the commute utility and the commute time. The commute-time utility decreases slowly before ICT, declines steadily between the ICT and the TTCT, and falls significantly after TTCT; and (c) when the commute time exceeds the TTCT, the perceived utility of commuters traveling by walking or cycling decreases significantly, and there are few changes in the perceived utility of commuters by car, which increases the probability that commuters who use active modes will transfer to commuting by car. The research results have implications for improving the prediction capacity of commute mode choice model and could guide commuters to switch to more sustainable commute modes.

Sea-Surface Small Target Detection Based on Four Features Extracted by FAST Algorithm

On account of current algorithm and parameter design difficulties and low detection accuracy in feature extractions of small target detections in sea clutter environment, this paper proposes a correspondingly improved four feature extraction method by FAST. After the short-time Fourier transform is applied, a time–frequency distribution spectrogram of original data is generated. Candidate feature points (CFP) are first extracted by FAST algorithm, and then a four-feature extraction is implemented with FAST and DBSCAN combined. The feature distinction is enhanced through a feature optimization. Upon the construction of the four-dimensional feature vectors, XGBoost classifier algorithm classifies and detects these feature vectors. The genetic algorithm optimizes the hyperparameters in XGBoost and updates the decision threshold in real time to control the detection method’s false alarm rate. The IPIX dataset is employed for experimental verification. Verification results confirm that this proposed detection method has better performance than several other currently used detection methods. The detection performance is improved by 7% and 13.8% when observation time is set at 0.512 s and 1.024 s, respectively.

Diverse effects of gaze direction on heading perception in humans.

Gaze change can misalign spatial reference frames encoding visual and vestibular signals in cortex, which may affect the heading discrimination. Here, by systematically manipulating the eye-in-head and head-on-body positions to change the gaze direction of subjects, the performance of heading discrimination was tested with visual, vestibular, and combined stimuli in a reaction-time task in which the reaction time is under the control of subjects. We found the gaze change induced substantial biases in perceived heading, increased the threshold of discrimination and reaction time of subjects in all stimulus conditions. For the visual stimulus, the gaze effects were induced by changing the eye-in-world position, and the perceived heading was biased in the opposite direction of gaze. In contrast, the vestibular gaze effects were induced by changing the eye-in-head position, and the perceived heading was biased in the same direction of gaze. Although the bias was reduced when the visual and vestibular stimuli were combined, integration of the 2 signals substantially deviated from predictions of an extended diffusion model that accumulates evidence optimally over time and across sensory modalities. These findings reveal diverse gaze effects on the heading discrimination and emphasize that the transformation of spatial reference frames may underlie the effects.

Scale-Dependent Verification of the OU MAP Convection Allowing Ensemble Initialized with Multi-Scale and Large-Scale Perturbations during the 2019 NOAA Hazardous Weather Testbed Spring Forecasting Experiment

Given the large range of resolvable space and time scales in large-domain convection-allowing for ensemble forecasts, there is a need to better understand optimal initial-condition perturbation strategies to sample the forecast uncertainty across these space and time scales. This study investigates two initial-condition perturbation strategies for CONUS-domain ensemble forecasts that extend into the two-day forecast lead time using traditional and object-based verification methods. Initial conditions are perturbed either by downscaling perturbations from a coarser resolution ensemble (i.e., LARGE) or by adopting the analysis perturbations from a convective-scale, EnKF system (i.e., MULTI). It was found that MULTI had more ensemble spread than LARGE across all scales initially, while LARGE’s perturbation energy surpassed that of MULTI after 3 h and continued to maintain a surplus over MULTI for the rest of the 36h forecast period. Impacts on forecast bias were mixed, depending on the forecast lead time and forecast threshold. However, MULTI was found to be significantly more skillful than LARGE at early forecast hours for the meso-gamma and meso-beta scales (1–9h), which is a result of a larger and better-sampled ensemble spread at these scales. Despite having a smaller ensemble spread, MULTI was also significantly more skillful than LARGE on the meso-alpha scale during the 20–24h period due to a better spread-skill relation. MULTI’s performance on the meso-alpha scale was slightly worse than LARGE’s performance during the 6–12h period, as LARGE’s ensemble spread surpassed that of MULTI. The advantages of each method for different forecast aspects suggest that the optimal perturbation strategy may require a combination of both the MULTI and LARGE techniques for perturbing initial conditions in a large-domain, convection-allowing ensemble.

Warranty Cost Analysis for Multi-State Products Protected by Lemon Laws

The implementation of lemon laws in America has played an important role in improving the quality of after-sales service. Nowadays, many countries, such as China, Canada, Europe, Australia, Singapore, and South Korea, have adopted lemon laws in various industries to protect the interest of consumers. From the perspective of manufacturers, accurate estimation of the cost of the warranty service is of great importance in guiding product pricing, quality control, and design of warranty policies. According to the terms of different lemon laws, two warranty models considering the repair time and numbers for failures are proposed in this paper. Products under these models are multi-state, and Markov processes are used to model the degradation processes of products. In the first model, a product will be replaced by a new one if the time for a repair or the number of failures exceeds their respective thresholds over the warranty period. Under the second model, both catastrophic and minor failures are considered. A product will be replaced if one of the following three conditions is met over the warranty period: the time of one repair action (regardless of failure type) is longer than a time threshold; the number of minor failures is larger than a preset threshold; a catastrophic failure occurs. The expected warranty cost rates under the two proposed warranty models are derived under the assumption of renewable warranty terms. Numerical examples are given to illustrate the results obtained.

GaVe: A Webcam-Based Gaze Vending Interface Using One-Point Calibration.

Gaze input, i.e., information input via eye of users, represents a promising method for contact- free interaction in human-machine systems. In this paper, we present the GazeVending interface (GaVe), which lets users control actions on a display with their eyes. The interface works on a regular webcam, available on most of today's laptops, and only requires a short one-point calibration before use. GaVe is designed in a hierarchical structure, presenting broad item cluster to users first and subsequently guiding them through another selection round, which allows the presentation of a large number of items. Cluster/item selection in GaVe is based on the dwell time, i.e., the time duration that users look at a given Cluster/ item. A user study (N=22) was conducted to test optimal dwell time thresholds and comfortable human-to-display distances. Users' perception of the system, as well as error rates and task completion time were registered. We found that all participants were able to quickly understand and know how to interact with the interface, and showed good performance, selecting a target item within a group of 12 items in 6.76 seconds on average. We provide design guidelines for GaVe and discuss the potentials of the system.

Accessibility in a multiple transport mode urban park based on the “D-D” model: A case study in Park City, Chengdu

Park City is a new concept for sustainable urban development. Urban Parks are the core of Park City, where park accessibility is the central index of park services. Previous studies have been conducted primarily from residents' perspective, based on the “O-D” (origin to destination) model to access the park accessibility. However, urban parks should be considered a place supporting the coexistence of tourists and residents. Moreover, tourists' movement patterns differ from those of residents, which are expressed as “no turning back” and traverse circular or nodal routes. Consequently, this paper proposes that the traditional “O-D” model be expanded to be consistent with the movement patterns of tourists.This paper employs Park City Chengdu as an exemplar and proposes a “D-D” (destination to destination) model to facilitate further park accessibility. The calculation process was based on a multiple transportation mode measure with multiple time thresholds, entrances, and exits, supported by Web API. The results reveal the key time nodes and park accessibility rankings for four transportation modes. In particular, the park accessibility presents a “dual-core, several sub-centers and cluster-types” circle structure. Furthermore, the park accessibility in Chengdu was generally balanced, except within 25 min, as well as walking and public transport. This paper provides new hypothetical perspectives and practical experiences for studying urban park accessibility, and novel ideas for parks' sites and distribution while serving as a model for cities worldwide for sustainable urban development.

Spatial rehabilitation using virtual auditory space training paradigm in individuals with sensorineural hearing impairment.

The present study aimed to quantify the effects of spatial training using virtual sources on a battery of spatial acuity measures in listeners with sensorineural hearing impairment (SNHI). An intervention-based time-series comparison design involving 82 participants divided into three groups was adopted. Group I (n = 27, SNHI-spatially trained) and group II (n = 25, SNHI-untrained) consisted of SNHI listeners, while group III (n = 30) had listeners with normal hearing (NH). The study was conducted in three phases. In the pre-training phase, all the participants underwent a comprehensive assessment of their spatial processing abilities using a battery of tests including spatial acuity in free-field and closed-field scenarios, tests for binaural processing abilities (interaural time threshold [ITD] and level difference threshold [ILD]), and subjective ratings. While spatial acuity in the free field was assessed using a loudspeaker-based localization test, the closed-field source identification test was performed using virtual stimuli delivered through headphones. The ITD and ILD thresholds were obtained using a MATLAB psychoacoustic toolbox, while the participant ratings on the spatial subsection of speech, spatial, and qualities questionnaire in Kannada were used for the subjective ratings. Group I listeners underwent virtual auditory spatial training (VAST), following pre-evaluation assessments. All tests were re-administered on the group I listeners halfway through training (mid-training evaluation phase) and after training completion (post-training evaluation phase), whereas group II underwent these tests without any training at the same time intervals. Statistical analysis showed the main effect of groups in all tests at the pre-training evaluation phase, with post hoc comparisons that revealed group equivalency in spatial performance of both SNHI groups (groups I and II). The effect of VAST in group I was evident on all the tests, with the localization test showing the highest predictive power for capturing VAST-related changes on Fischer discriminant analysis (FDA). In contrast, group II demonstrated no changes in spatial acuity across timelines of measurements. FDA revealed increased errors in the categorization of NH as SNHI-trained at post-training evaluation compared to pre-training evaluation, as the spatial performance of the latter improved with VAST in the post-training phase. The study demonstrated positive outcomes of spatial training using VAST in listeners with SNHI. The utility of this training program can be extended to other clinical population with spatial auditory processing deficits such as auditory neuropathy spectrum disorder, cochlear implants, central auditory processing disorders etc.

Resolving the accessibility dilemma: Comparing cumulative and gravity-based measures of accessibility in eight Canadian cities

There is a lack of agreement regarding the theoretical framework that practitioners should use for accessibility assessment – a measure of transport and land-use systems performance. Cumulative measures are simple and easy to interpret, while gravity-based measures are more sophisticated, resourceful, and less intuitive approaches. As such, this study aims to investigate whether the estimates of a simple cumulative opportunity measure are significantly different from those made using advanced gravity-based measures to understand if the former can be a substitute for the latter in practice and if a certain threshold of travel time can be recommended for different regions. We estimated cumulative and gravity-based accessibility using decay-probability density functions, decay-cumulative density functions, Gaussian, and a Log-Logistic decay-cumulative density functions using census commuting flows, car congested travel time and public transit schedules from eight metropolitan regions across Canada – Toronto, Montreal, Vancouver, Edmonton, Quebec City, Winnipeg, London, and Halifax. These measures of accessibility were tested for correlation, and we found that a coefficient of approximately 0.90 is reached when the threshold to calculate cumulative opportunities accessibility is set to the average commute time for both low- and non-low-wage jobs accessibility analyses by transit and motor vehicles. The paper provides evidence to support the reliability of cumulative accessibility, facilitates its broader adoption for evaluation of transport and land use interactions in North American cities, as well as opens opportunities to advance the equitable distribution of transport system benefits.

Adapting a deep convolutional RNN model with imbalanced regression loss for improved spatio-temporal forecasting of extreme wind speed events in the short to medium range

Abstract. The number of wind farms and amount of wind power production in Europe, both on- and offshore, have increased rapidly in the past years. To ensure grid stability and on-time (re)scheduling of maintenance tasks and to mitigate fees in energy trading, accurate predictions of wind speed and wind power are needed. Particularly, accurate predictions of extreme wind speed events are of high importance to wind farm operators as timely knowledge of these can both prevent damages and offer economic preparedness. This work explores the possibility of adapting a deep convolutional recurrent neural network (RNN)-based regression model to the spatio-temporal prediction of extreme wind speed events in the short to medium range (12 h lead time in 1 h intervals) through the manipulation of the loss function. To this end, a multi-layered convolutional long short-term memory (ConvLSTM) network is adapted with a variety of imbalanced regression loss functions that have been proposed in the literature: inversely weighted, linearly weighted and squared error-relevance area (SERA) loss. Forecast performance is investigated for various intensity thresholds of extreme events, and a comparison is made with the commonly used mean squared error (MSE) and mean absolute error (MAE) loss. The results indicate the inverse weighting method to most effectively shift the forecast distribution towards the extreme tail, thereby increasing the number of forecasted events in the extreme ranges, considerably boosting the hit rate and reducing the root-mean-squared error (RMSE) in those ranges. The results also show, however, that such improvements are invariably accompanied by a pay-off in terms of increased overcasting and false alarm ratio, which increase both with lead time and intensity threshold. The inverse weighting method most effectively balances this trade-off, with the weighted MAE loss scoring slightly better than the weighted MSE loss. It is concluded that the inversely weighted loss provides an effective way to adapt deep learning to the task of imbalanced spatio-temporal regression and its application to the forecasting of extreme wind speed events in the short to medium range.

Measuring pedestrian flows in public spaces: Inferring walking for transport and recreation using Wi-Fi probes

Differentiating transport and recreational walking in public spaces could promote the precise design of walkable public spaces for different walking demands to encourage more walking behaviors. However, previous studies mainly relied on field observations and self-reports, failing to quantitatively distinguish and depict the spatial-level usage of transport and recreational walking of all pedestrians passing by. This study proposed an approach based on the traffic counts and the number of pedestrians to infer transport and recreation walking in public spaces. A comparative experiment using Wi-Fi probes to collect pedestrian data in a gated residential community and a creative center in Beijing, China, was conducted to verify the applicability of this method. The results demonstrated that the transport walking index (the number of pedestrians) could portray the volume of transport walking, and the recreational walking index (average traffic counts of each pedestrian) could depict the proportion of recreational walking in public spaces. Two tests using different time threshold parameters and field observations verified the robustness of the results. Given the low-cost and long-duration observation, this method can potentially support the process of Post Occupancy Evaluation and Environment and Behavior research in more public spaces to make them more walkable.

Elastic and inelastic low-energy electron scattering from pyridine.

A comprehensive investigation of elastic and inelastic electron scattering from molecular pyridine is reported using the ab initio R-matrix method with the static exchange plus polarization and close-coupling approximations for incident energies up to 10eV. The two well-known low-lying 1 2B1 and 1 2A2 shape resonances as well as a 2 2B1 mixed-character resonance compare well with the theoretical and experimental results. We also detect five core-excited resonances (1 2A1, 1 2B2, 3 2B1, 2 2A2, and 4 2B1), which lie above the first electronic excitation threshold. The total elastic cross sections and momentum transfer cross sections agree reasonably with previous reference data. Comparisons of the differential elastic cross sections of pyridine with those measured for benzene, pyrazine, and pyrimidine show remarkable agreement at scattering angles above 40° but behave differently for forward scattering below 40° below 6eV, due to the dominant effect of the permanent dipole moment on the differential cross section in the low energy region with narrow scattering angles. Inelastic electronic excitation cross sections are presented, showing the influence of core-excited resonances below the ionization threshold for the first time.

Identification of an Operative Time Threshold for Substantially Increased Postoperative Complications Among Elderly Spine Surgery Patients.

Retrospective cohort study. To identify whether thresholds exist beyond which operative duration or age increases risks for complications among patients ≥65years undergoing elective spine surgery. Elective inpatient spine procedures unrelated to infection/trauma/tumor diagnoses in patients <65years recorded in the 2006-2019 American College of Surgeons National Surgical Quality Improvement database were identified. Univariate analyses was used to compare 30day complication rates among 5 operative duration and age-stratified groups. To quantify the risk of prolonged operative duration on complications, multivariate analyses were performed controlling for confounders. A generalized linear model was used to assess the individual and combined effect strength of age and operative duration on complication rates. Among 87,705 patients stratified by operative duration, 30day complication rates rose nonlinearly as operative duration increased, with a sharp rise after 4.0-4.9 hours (28.3% at 4.0-4.9hours, 51.7% at ≥5hours, P < .001). Multivariate analysis found operative duration was independently associated with increased risk of overall complications (odds ratio 1.10→1.69, P < .001) and medical complications (odds ratio 1.19→1.98, P < .001). Although complication rates rose by age (all P < .001), age was not independently predictive of overall complications within any operative duration group on multivariate analysis. Operative duration had a greater effect (η2P = .067) than age (η2P = .003) on overall complication rates. Increased operative duration was strongly associated with 30day complication rates, particularly beyond a threshold of 5hours. Furthermore, operative duration had a notably larger effect on overall complication rates than age.