Cancellation Factor Research Articles

Atomic Data for Astrophysically Important Spectral Lines of Singly Ionized Nitrogen

Nitrogen lines are widely observed in astrophysical spectra and provide important diagnostics for plasma properties. In this work, we present extended calculations for accurate energy levels, electric dipole radiative transition parameters, and lifetimes for the lowest 102 states of the 2s 22p 2, 2s2p 3, 2s2p 23s, 2s 22p{n 1 l, n 2 d, 4f}(n 1 = 3–5, l = s, p, n 2 = 3, 4), and 2p 4 configurations of N ii within the framework of the fully relativistic multiconfiguration Dirac–Hartree–Fock and relativistic configuration interaction methods. These data are useful for modeling astrophysical spectra, for example, for nitrogen abundance determinations in early B-type stars, and for studying the compositions and plasma properties of H ii regions and planetary nebulae. Our computed transition parameters are compared with available experimental and theoretical data. The accuracy of the calculations is also assessed via a statistical analysis of the differences between the transition rates in the Babushkin and Coulomb gauges and by consideration of cancellation factors. In this way, 201 of the 1656 transitions computed in this work are estimated to be from accurate to better than 3%, corresponding to an accuracy class of A.

Association of Neighborhood Opportunity, Race, and Ethnicity with Pediatric Day-of-surgery Cancellations: A Cohort Study.

Day-of-surgery cancellations impede healthcare access and contribute to inequities in pediatric healthcare. Socially disadvantaged families have many risk factors for surgical cancellation, including low health literacy, transportation barriers, and childcare constraints. These social determinants of health are captured by the Child Opportunity Index 2.0, a national quantification of neighborhood-level characteristics that contribute to a child's vulnerability to adversity. This study examined the association of neighborhood opportunity with pediatric day-of-surgery cancellations. A retrospective cohort study of children younger than 18 yr of age scheduled for ambulatory surgery at a tertiary pediatric hospital between 2017 and 2022 was conducted. Primary addresses were geocoded to determine Child Opportunity Index 2.0 neighborhood opportunity. Log-binomial regression was used to estimate the relative risk of day-of-surgery cancellation comparing different levels of neighborhood opportunity. This study also estimated the relative risk of cancellations associated with race and ethnicity, by neighborhood opportunity. Overall, the incidence of day-of-surgery cancellation was 3.8%. The incidence of cancellation was lowest in children residing in very-high-opportunity neighborhoods and highest in children residing in very-low-opportunity neighborhoods (2.4% vs. 5.7%, P < 0.001). The adjusted relative risk of day-of-surgery cancellation in very-low-opportunity neighborhoods compared to very-high-opportunity neighborhoods was 2.24 (95% CI, 2.05 to 2.44; P < 0.001). The results showed statistical evidence of an interaction of Children's Opportunity Index with race and ethnicity. In very-low-opportunity neighborhoods, Black children had 1.48 times greater risk of day-of-surgery cancellation than White children (95% CI, 1.35 to 1.63; P < 0.001). Likewise, in very-high-opportunity neighborhoods, Black children had 2.17 times greater risk of cancellation (95% CI, 1.75 to 2.69; P < 0.001). This study found a strong relationship between pediatric day-of-surgery cancellation and neighborhood opportunity. Black children at every level of opportunity had the highest risk of cancellation, suggesting that there are additional factors that render them more vulnerable to neighborhood disadvantage.

High Rates of Eye Surgery Cancellation in Veterans Related to Mental Health.

Approximately 9 million veterans receive health care at the Veterans Health Administration, many of whom have psychiatric illnesses. The military continues to have higher rates of psychiatric illness compared to the civilian population. Having a diagnosis such as posttraumatic stress disorder or depression may create challenges in using health care services, such as surgery. The aim of this study was to evaluate eye surgery cancellation, risk factors for cancellation, and areas for intervention within the VA. This was a single-center retrospective cohort study. The Veteran Health Information Systems and Technology Architecture were queried to identify all surgical requests at the West Los Angeles VA in 2019. Data collection included sociodemographic information and comorbid medical conditions, including psychiatric illness. Exploratory analyses using univariate logistic regression were used to evaluate factors associated with surgery cancellation. A total of 1,115 surgical requests were identified with a cancellation rate of 23.7% (n = 270). Sociodemographic factors were similar between those with completed and cancelled surgery. However, having a psychiatric diagnosis correlated with surgery cancellation. For all subspecialties, patients with schizophrenia were more likely to have cancellation (odds ratio [OR], 2.53, P = .04). For retina surgery, patients with posttraumatic stress disorder were more likely to have cancellation (OR, 4.23, P = .01). Glaucoma patients with anxiety (OR, 5.78, P = .05) and depression (OR, 4.05, P = .04) were more likely to have cancellation. There was a significant amount of eye surgery cancellations in veterans with variation by subspecialty and comorbid conditions. Having a psychiatric illness was correlated with increased rates of surgery cancellation amongst veterans. Areas to improve surgical utilization include risk stratification and increased support of vulnerable patients before surgery.

Cancellation of the more complicated ophthalmic inpatient surgeries in a tertiary general hospital: a 10-year retrospective study.

Although ophthalmic ambulatory surgeries are less costly and may enhance the more efficient utilization of hospital resources, inpatient surgeries were preferable alternatives for patients with complicated eye diseases or poor general health. However, the incidence, causes, and related factors of ophthalmic inpatient surgery cancellation remained largely unknown. The electronic medical records of ophthalmic inpatient surgeries between January 2012 and December 2022 was retrospectively reviewed. Cancellation-related factors were explored using multivariate logistic regression analysis and the reasons of cancellation were also evaluated. In total, 820 cancelled surgeries and 42,073 performed surgeries were included, with a cancellation rate of 1.9%. Any other ocular comorbidities were risk factors for cancellation (odds ratio (OR) 1.872, 95% confidence intervals (CI) 1.504-2.331; p < 0.001), while older age (OR 0.990, 95% CI 0.986-0.995; p < 0.001), local residence (OR 0.809, 95% CI 0.692-0.947; p = 0.008), any systemic comorbidities (OR 0.740, 95% CI 0.616-0.889; p = 0.001), and previous history of surgeries (OR 0.403, 95% CI 0.341-0.476; p < 0.001) were negatively associated with surgery cancellation. The top two categorical cancellation reasons were medical factors (508, 62.0%) and patient-related factors (285, 34.8%). "Patient/family refused surgery" (127, 15.5%), "acute conjunctivitis or uveitis relapse" (103, 12.6%), and "ocular condition improved and procedure no longer indicated" (71, 8.7%) were the three most common single cancellation reasons. Any other ocular comorbidities, younger age, no systemic comorbidities, non-local residence, and no past surgical history were related factors for ophthalmic inpatient surgery cancellation. The majority of cancellations were due to patient-related or medical factors. Great importance should be attached to the cancellation of the more complicated inpatient surgeries and further efforts are warranted to explore how to reduce cancellation.

Joint Design of Antenna Selection and Resource Allocation in Massive MIMO‐Based Ultra Dense Heterogeneous Networks

Fifth generation (5G) communication network is anticipated to satisfy the need for higher data rates, less latency, ubiquitous connectivity with minimum consumption of energy and acceptable quality of Service (QoS). The massive MIMO and heterogeneous network (HetNet) has evolved as a promising technology to address the aforementioned challenges. In the proposed framework, the massive MIMO technology at the macro base station and full duplex (FD) technology enabled at the small cell base station in HetNet are investigated. An optimal antenna selection strategy, user association (UA), and power allocation (PA) in a massive MIMO‐based HetNet with FD‐enabled small cells are proposed to optimize system sum rate. Initially, the objective function of the optimization problem is nonconvex and a mixed integer nonlinear programming problem. Then, the solution is obtained by transforming the problem into convex problem utilizing Lagrangian decomposition. Simulation results manifest the effect of the number of base station antennas, number of small cell base stations, self‐interference cancellation factor, and channel state information on system sum rate. Moreover, it is evident that the propounded algorithm is effective in terms of optimizing the system sum rate when compared to the conventional maximum signal‐ to ‐ interference ‐ plus ‐noise ‐ ratio (SINR) algorithm.

Power Allocation for NOMA With Cache-Aided D2D Communication

Communication networks are becoming increasingly content-centric, and reusable content like viral information and video on demand are often requested by multiple users. Caching at the user equipment enables device-to-device (D2D) communications to be used to deliver requested contents which will help reduce data traffic at base stations and also enhance the achievable data rates. In this paper, we propose a system whereby users are able to exchange valuable cached content with each other via a D2D link which underlays the reception of a downlink non-orthogonal multiple access (NOMA) signal. We formulated a sum rate maximization problem that is subject to minimum rate constraints and derived optimal solutions depending on which user is the D2D transmitter. Additionally, sub-optimal solutions based on a negligible self-interference assumption are also proposed. Simulation results demonstrate the significant performance gains of underlaid D2D communications as compared with optimal downlink cellular NOMA. Furthermore, results on the self-interference (SI) cancellation factor highlight that the sub-optimal power allocation solution offers sum rate performance close to the optimal case. The performance gains are further enhanced when SI cancellation is high.

Predictors of same day cancellation of elective surgery.

Same day cancellations of surgery have adverse effects on both patients and health care systems. To date, the majority of research has evaluated reasons for same day cancellation, and relatively little is known about risk factors for cancellation. The aim of this study is to develop and evaluate the accuracy of a model for preoperatively predicting which patients are at risk for experiencing same day cancellation. While accurately predicting which patients are likely to experience same day cancellation remains challenging, predictive models may aid in the early identification of patients at risk for cancellation. Future studies are required to assess whether the use of predictive analytics leads to reduced cancellation rates in practice.

Extended atomic data for oxygen abundance analyses

As the most abundant element in the universe after hydrogen and helium, oxygen plays a key role in planetary, stellar, and galactic astrophysics. Its abundance is especially influential in terms of stellar structure and evolution, and as the dominant opacity contributor at the base of the Sun’s convection zone, it is central to the discussion on the solar modelling problem. However, abundance analyses require complete and reliable sets of atomic data. We present extensive atomic data for O I by using the multiconfiguration Dirac–Hartree–Fock and relativistic configuration interaction methods. We provide the lifetimes and transition probabilities for radiative electric dipole transitions and we compare them with results from previous calculations and available measurements. The accuracy of the computed transition rates is evaluated by the differences between the transition rates in Babushkin and Coulomb gauges, as well as via a cancellation factor analysis. Out of the 989 computed transitions in this work, 205 are assigned to the accuracy classes AA-B, that is, with uncertainties smaller than 10%, following the criteria defined by the Atomic Spectra Database from the National Institute of Standards and Technology. We discuss the influence of the new log(gf) values on the solar oxygen abundance, ultimately advocating for log єO = 8.70 ± 0.04.

Revised and Extended Analysis of Ar vi

This paper analyzes the emission spectrum of Ar vi and adds new information about this ion. We use a capillary light source to study the Ar vi spectrum, presenting 39 line classifications for the first time, including one line in the ultraviolet region. A total of nine possible Ar vi lines in the ultraviolet between 3288 and 3440 Å are analyzed. We revised the wavelengths of the lines at 1284.01 and 1307.42 Å previously used to identify Ar vi in astronomical objects. The lifetimes, weighted transition rates (gA) and their estimated uncertainties, and cancellation factors are obtained using a Hartree–Fock calculation with energy parameters adjusted to fit the values of the experimental levels and modified to include core polarization effects. We analyze all the experimentally known transitions of the Ar vi spectrum, with particular attention to conflicting information. Isoelectronic sequences of energy levels and transitions, for which the trend is not a smooth curve, are analyzed. We revise previous studies where the information needed to support line classifications and level designations is incomplete.

High-accuracy determination of Paul-trap stability parameters for electric-quadrupole-shift prediction

The motion of an ion in a radiofrequency (rf) Paul trap is described by the Mathieu equation and the associated stability parameters that are proportional to the rf and dc electric field gradients. Here, a higher-order, iterative method to accurately solve the stability parameters from measured secular frequencies is presented. It is then used to characterize an endcap trap by showing that the trap’s radial asymmetry is dominated by the dc field gradients and by measuring the relation between the applied voltages and the gradients. The results are shown to be in good agreement with an electrostatic finite-element-method simulation of the trap. Furthermore, a method to determine the direction of the radial trap axes using a “tickler” voltage is presented, and the temperature dependence of the rf voltage is discussed. As an application for optical ion clocks, the method is used to predict and minimize the electric quadrupole shift (EQS) using the applied dc voltages. Finally, a lower limit of 1070 for the cancellation factor of the Zeeman-averaging EQS cancellation method is determined in an interleaved low-/high-EQS clock measurement. This reduces the EQS uncertainty of our 88Sr+ optical clock to ≲1×10−19 in fractional frequency units.

Phased-Array Transmission for Secure Multiuser mmWave Communication via Kronecker Decomposition

This paper proposes a multiuser physical layer secure transmission scheme for millimeter-wave communication. We use Kronecker decomposition to design the common transmit vector to synthesize the desired symbols for multiple legitimate receivers in the proposed scheme. Specifically, the algorithm converts the design of common transmit weight for multiuser into the design of sub-weight vectors having the Vandermonde structure. By using Kronecker decomposition, the sub-weight vectors are decomposed into Kronecker factors and designed. To eliminate the message sending towards the undesired directions while guaranteeing the quality of transmission in the target directions, we separate the Kronecker factors into two parts by using the property of the Kronecker product. The first part (the interference cancellation factor) cancels the interference between legitimate users; the second part (the signal enhancement factor) achieves signal enhancement. For a given information symbol, multiple solutions of transmit weight are obtained. By utilizing this time-varying transmit weight, we realize the secure transmission for multiuser. In addition, the proposed algorithm has no restrictions on modulation, and it also has analytical solutions with low computational complexities. Simulations are presented to verify the effectiveness of the algorithm under various situations.

Incidence and Risk Factors for Patient-related Short-term Cancellation of Elective Arthroscopic Surgery: A Case-matched Study.

Introduction:Short-term cancellation of elective ambulatory orthopaedic surgery can result in disruption to the process flow of the operating room, with resultant negative financial implications for the health system. The risk factors for patient-related short-term cancellations within 24 hours of the surgical date have not been well defined.Methods:A retrospective review of a single orthopaedic surgery electronic internal database was done to identify all cancellations from January 1, 2016, through December 31, 2019, which were made within 24 hours of the surgical date. Inclusion criteria included elective arthroscopic procedures canceled solely for patient-related issues. Any cancellation for surgeon-related or ambulatory center–related reasons was excluded. Demographic patient and surgical data, including insurance type, employment status, previous history of cancellation for the same surgery, socioeconomic status based on the Area Deprivation Index, and surgery type, were tabulated. Each cancellation was matched 1:2 with noncanceled cases based on the anatomic site of the arthroscopy scheduled. Multivariable logistic regression was used to examine associations of patient demographic and medical characteristics with surgical cancellation.Results:There were 4,715 total arthroscopic procedures done during the study period, of which 126 (2.7%) were canceled within 24 hours of the surgery date. The mean age of the canceled cases was 44.9 ± 16.1 years (range, 14 to 77 years), with 46 females (43%) included. The presence of MRI of the involved joint within 6 months of surgery (adjusted odds ratio [aOR], 0.39, 95% confidence interval [CI], 0.17 to 0.91) and current employment (aOR, 0.56, 95% CI, 0.33-0.94) were independently predictive of noncancellation. Current smokers were more likely to cancel within 24 hours of surgery (aOR, 2.63, 95% CI, 1.4-4.9). Finally, having previously canceled the same surgery was significantly associated with a current surgical cancellation (P = 0.004).Discussion:Identification of the factors associated with short-term patient-related cancellation of elective arthroscopy may serve as the basis for preoperative interventions aimed specifically at those more likely to cancel. In turn, these interventions can minimize preventable cancellations.

SINR percolation for Cox point processes with random powers

AbstractSignal-to-interference-plus-noise ratio (SINR) percolation is an infinite-range dependent variant of continuum percolation modeling connections in a telecommunication network. Unlike in earlier works, in the present paper the transmitted signal powers of the devices of the network are assumed random, independent and identically distributed, and possibly unbounded. Additionally, we assume that the devices form a stationary Cox point process, i.e., a Poisson point process with stationary random intensity measure, in two or more dimensions. We present the following main results. First, under suitable moment conditions on the signal powers and the intensity measure, there is percolation in the SINR graph given that the device density is high and interferences are sufficiently reduced, but not vanishing. Second, if the interference cancellation factor $\gamma$ and the SINR threshold $\tau$ satisfy $\gamma \geq 1/(2\tau)$ , then there is no percolation for any intensity parameter. Third, in the case of a Poisson point process with constant powers, for any intensity parameter that is supercritical for the underlying Gilbert graph, the SINR graph also percolates with some small but positive interference cancellation factor.

Factors for Postponement or Cancellation of Operating Programs Set in the Orthopedics-Traumatology Department of Yalgado Ou&amp;#233;draogo University Teaching Hospital in Ouagadougou (Burkina Faso)

Objective: The purpose of this work was to study the factors of cancellations or postponement of regulated operating programs of the Orthopedic-Traumatology unit of Yalgado Ouédraogo University Teaching Hospital. Materials and Methods: This was a prospective descriptive study over a period of six months. All interventions postponed or canceled during the study period were included. Patients who died or were lost to follow-up before surgery were not included. Results and Comments: the postponement/ cancellation rate was 24.5%. Out of 83 operations cancelled, 72.3% of patients were under 50 years old [extreme 15 and 88 years old]. ASA classes I and II were dominant with 57% and 37% of patients canceled, respectively. There were more postponed interventions (67.5%) than definitive cancellations (32.5%). The causes found were avoidable in 68.7% of cases. The most common was the unavailability of labile blood products (57%), the lack of financial means (36%) and the absence of the patient (28%). The results of our study show that 53% of the causes of cancellations were related to the organization of the hospital. Conclusion: the cancellation rate of orthopedic surgeries remains high at Yalgado Ouédraogo University Teaching Hospital. Most of the causes of cancellations are potentially preventable and the vast majority of them are related to the organization of the hospital. Financial accessibility to care plays an important role in cancellations.

Mathematical justification on the origin of the sigmoid in logistic regression

Logistic regression is a commonly used classification algorithm in machine learning. It allows categorizing data into discrete classes by learning the relationship from a given set of labeled data. It learns a linear relationship from the given data set and then introduces nonlinearity through an activation function to determine a hyperplane that separates the learning points into two subclasses. In the case of logistic regression, the sigmoid is the most used activation function to perform binary classification. The choice of sigmoid for binary classifications is justified by its ability to transform any real number into a probability between 0 and 1. This study provides, through two different approaches, a rigorous mathematical answer to the crucial question that torments us, namely where does this logistic function on which most neural network algorithms are based come from? References Stoltzfus, "Logistic regression: A brief primer," Academic Emergency Medicine, vol. 18, no. 10, pp. 1099-1104, 2011. Peng et al, "An introduction to logistic regression analysis and reporting," The Journal of Educational Research, vol. 96, no. 1, pp. . Costa et al, "A logistic regression model for consumer default risk," Journal of Applied Statistics, vol. 47, no. 13-15, pp. 2879-2894, 2020. Gatzert and M. Schubert, "Cyber risk management in the us banking and insurance industry: A textual and empirical analysis of determinants and value," Journal of Risk and Insurance, vol. 89, no. 3, pp. 725-763, 2022. Premsmith and H. Ketmaneechairat, "A predictive model for heart disease detection using data mining techniques," Journal of Advances in Information Technology, vol. 12, pp. 14-20, 2021. Almotiri et al, "Using api with logistic regression model to predict hotel reservation cancellation by detecting the cancellation factors," International Journal of Advanced Computer Science and Applications, vol. 12 , no. 6 , pp. . Kudupudi et al, "Spam message detection using logistic regression," International Journal of Advanced Computer Science and Applications, vol. 9, no. 9, pp. 815-818, 2021. Keren and . Cuiwei, "Housing price analysis using linear regression and logistic regression: A comprehensive explanation using melbourne real estate data," in 2021 IEEE International Conference on Computing (ICOCO), 2021, pp. 241-246. Dheeru and G. Casey, "UCI machine learning repository," 2017. [Online]. Available: http://archive.ics. uci.edu/ml Goldbloom, "Kaggle dataset," 2010. [Online]. Available: https: //www.kaggle.com/ Febrianti et al, "The parameter estimation of logistic regression with maximum likelihood method and score function modification," Journal of Physics: Conference Series, vol. 1725, no. 1, p. 012014, 2021. Lucena, "Loss functions for classification using structured entropy," 2022. [Online]. Available: https://arxiv.org/abs/2206.07122 Hikmat and A. Abdulazeez, "Comparison of optimization techniques based on gradient descent algorithm: a review," PalArch?s Journal of Archaeology of Egypt/Egyptology, vol. 18, no. 4, pp. 2715-2743, 2021.E. Norton et al, “Odds ratios-current best practice and use,” Journal of the American Medical Association, vol. 320, no. 1, pp. 84–85, 2018 Tong, Fundamental Properties and Sampling Distributions of the Multivariate Normal Distribution. Springer New York, 1990, pp. 23– 61.

Generalized Receiver with Parallel Interference Cancellation for Multiuser Detection

Parallel interference cancellation is considered as a simple yet effective multiuser detector for direct -sequence code-division multiple-access (DS-CDMA) systems. However, system performance be deteriorated due to unreliable interference cancellation in the early stages. Thus, a detector with the partial parallel interfere-nce cancellation in which the partial cancellation factors are introduced to control the interference cancellation level has been developed as a remedy. Although the partial cancellation factors are crucial, complete solutions for their optimal values are not available. In this paper, we consider a two-stage decoupled generalized receiver with the partial parallel interference cancellation. Using the minimum bit error rate (BER) criterion, we derive a complete set of optimal partial cancellation factors. This includes the optimal partial cancellation factors for pe-riodic and aperiodic spreading codes in channels with the additive white Gaussian noise and multipath chann-els. Simulation results demonstrate that the considered theoretical optimal partial cancellation factors agree clo-sely with empirical ones. The proposed two-stage generalized receiver with the partial parallel interference can-cellation using the derived optimal partial cancellation factors outperforms not only a two-stage, but also a three-stage conventional generalized receiver with the full parallel interference cancellation.

Factors Contributing to Late Cancellation and No-Show for Otolaryngologic Surgery: A Prospective Study.

Late cancellations and no-shows for surgery place a burden on patients, healthcare providers, and the health system. We aim to identify risk factors contributing to this phenomenon. Patients who did not arrive for, or canceled within 24 hours of, their surgical appointment between January 2019 and 2020 were identified. Controls were matched by date, procedure, and gender. Demographic information was obtained by phone interview and chart review. Chi-square and Student t-test analyses were used to predict risk factors for cancellation. Thirty-one patients were identified, of whom 21 completed phone interviews. Age, gender, race, language, marital status, and smoking status were not significantly different. Study patients reported more transportation challenges (33.3% vs. 4.8%, p = .01) yet lived closer to the hospital (4.53 miles vs. 14.05 miles, p = .01). Study patients lived in lower income zip codes ($48,145 vs. $63,406, p = .02) and more commonly had Medicaid as their primary insurance (70.9% vs. 38.7%, p = .04). Most commonly, no reason was given for cancellation (22.6%) followed by personal reasons (16.1%) and surgery reconsideration (16.1%). Transportation trouble and lower income are significant risk factors for surgery late cancellation. Prior no-show must also be considered. A targeted pilot program may help prevent late cancellations.

Pilot-Assisted SIMO-NOMA Signal Detection With Learnable Successive Interference Cancellation

In this letter, we propose a pilot-assisted receiver scheme based on learnable successive interference cancellation (PA-LSIC) for uplink single-input multiple-output (SIMO) non-orthogonal multiple access (NOMA) systems. The PA-LSIC combines the successive interference cancellation (SIC) structure with the model-driven deep learning network. Considering the noise impact of channel estimation and the incomplete detection and cancellation in SIC process, we introduce some new parameters, such as noise cancellation factor and interference cancellation factor, which are optimized by using the back-propagation algorithm and random gradient descent algorithm. Numerical results show that the PA-LSIC has superior bit error rate (BER) performance and lower complexity during training and implementation.

Energy Efficiency Optimization for Massive MIMO Backhaul Networks with Imperfect CSI and Full Duplex Small Cells

In this paper, a massive MIMO enabled backhaul model for two-tier heterogeneous networks with in-band full-duplex transmission and imperfect CSI is provided. Because of a massive number of antennas at the macro base station and densification of small cells, circuit power consumption increases in the system. It is requisite to study energy efficiency of such backhaul networks. This paper aims at maximizing EE for optimal user association, spectrum allocation, and power allocation while accounting for QoS and backhaul constraints. A joint optimization problem is formulated as a non-convex mixed integer non-linear problem which provides an un-affordable computational complexity. To crack the problem efficiently, it is progressively divided into sub-problems until each one is convex and is solved separately to obtain the optimal solution. Furthermore, complexity of the proposed algorithm is evaluated and Jain’s fairness index is measured. Simulation results of the proposed distributive algorithm are shown and compared with that of the existing algorithm (Max SINR) to manifest the strength of the proposed algorithm. The impact of self-interference cancellation factor and channel estimation error on EE is clearly reflected by the numerical results. In addition, it is observed that using the proposed algorithm results in better EE than increasing the number of antennas.

Risk factors for cancellation after dispatch of rapid response cars for prehospital emergency care: a single-center, case-control study.

AimThe objective of this study is to identify the risk factors for cancellation after dispatch of rapid response cars (RRC) for prehospital emergency care.MethodsWe retrospectively extracted data from all RRC cases dispatched from our hospital between April 2017 and March 2019. A total of 1,440 cases were included in our study and divided into either the “cancelled” group (n = 723) or the “treated” group (n = 717), based on the occurrence of cancellation. The variables obtained from the request calls for RRC included patient characteristics, distance from the hospital to the scene, and reasons for RRC request. The variables were compared between the two groups and logistic regression analysis was carried out to identify the risk factors for RRC cancellation.ResultsMultivariable analysis showed that distance from the hospital to the scene (odds ratio [OR] 1.25; 95% confidence interval (CI), 1.21–1.28), suspicion of cardiopulmonary arrest with no witness information (OR 7.61; 95% CI, 4.13–14.00), dyspnea (OR 2.22; 95% CI, 1.19–4.11), and suicide by hanging (OR 3.49; 95% CI, 1.37–8.89) were independent risk factors for cancellation.ConclusionsIn our study, a greater distance from the hospital to the scene, suspicion of cardiopulmonary arrest with no witness information, dyspnea, and suicide by hanging were identified as independent risk factors for cancellation after dispatch of RRC. Evaluating the risk factors for cancellation at individual facilities could help hospitals adjust their dispatch criteria to allocate limited medical resources more effectively.