MDE and LLM Synergy for Network Experimentation: Case Analysis of Wireless System Performance in Beaulieu-Xie Fading and κ-µ Co-Channel Interference Environment with Diversity Combining.

Channel modeling is a first step towards the successful projecting of any wireless communication system. Hence, in this paper, we analyze the performance at the output of a multi-branch selection combining (SC) diversity receiver in a wireless environment that has been distracted by fading and co-channel interference (CCI), whereby the fading is modelled by newer Beaulieu-Xie (BX) distribution, and the CCI is modelled by the κ-µ distribution. The BX distribution provides the ability to include in consideration any number of line-of-sight (LOS) useful signal components and non-LOS (NLOS) useful signal components. This distribution contains characteristics of some other fading models thanks to its flexible fading parameters, which also applies to the κ-µ distribution. We derived here the expressions for the probability density function (PDF) and cumulative distribution function (CDF) for the output signal-to-co-channel interference ratio (SIR). After that, other performances are obtained, namely: outage probability (Pout), channel capacity (CC), moment-generating function (MGF), average bit error probability (ABEP), level crossing rate (LCR), and average fade duration (AFD). Numerical results are presented in several graphs versus the SIR for different values of fading and CCI parameters, as well as the number of input branches in the SC receiver. Then, the impact of parameters on all performance is checked. From our numerical results, it is possible to directly obtain the performance for all derived and displayed quantities for cases of previously known distributions of fading and CCI by inserting the appropriate parameter values. In the second part of the paper, a workflow for automated network experimentation relying on the synergy of Large Language Models (LLMs) and model-driven engineering (MDE) is presented, while the previously derived expressions are used for evaluation. Due to the aforementioned, the biggest value of the obtained results is the applicability to the cases of a large number of other distributions for fading and CCI by replacing the corresponding parameters in the formulas for the respective performances.

On the Effect of Imperfect Reference Signal Phase Recovery on Performance of PSK System Influenced by TWDP Fading.

We examine the effects of imperfect phase estimation of a reference signal on the bit error rate and mutual information over a communication channel influenced by fading and thermal noise. The Two-Wave Diffuse-Power (TWDP) model is utilized for statistical characterization of propagation environment where there are two dominant line-of-sight components together with diffuse ones. We derive novel analytical expression of the Fourier series for probability density function arising from the composite received signal phase. Further, the expression for the bit error rate is presented and numerically evaluated. We develop efficient analytical, numerical and simulation methods for estimating the value of the error floor and identifying the range of acceptable signal-to-noise ratio (SNR) values in cases when the floor is present during the detection of multilevel phase-shift keying (PSK) signals. In addition, we use Monte Carlo simulations in order to evaluate the mutual information for modulation orders two, four and eight, and identify its dependence on receiver hardware imperfections under the given channel conditions. Our results expose direct correspondence between bit error rate and mutual information value on one side, and the parameters of TWDP channel, SNR and phase noise standard deviation on the other side. The results illustrate that the error floor values are strongly influenced by the phase noise when signals propagate over a TWDP channel. In addition, the phase noise considerably affects the mutual information.

Ten-Year Trends in Sales of Alzheimer Disease Drugs in France Compared With Sales in Germany, Spain, and the UK.

This cross-sectional study analyzes 10-year trends in sales of Alzheimer disease drugs in France compared with trends in the UK, Spain, and Germany.

Pediatric Prescriptions of Proton Pump Inhibitors in France (2009-2019): A Time-Series Analysis of Trends and Practice Guidelines Impact.

OBJECTIVE: To describe the ambulatory proton pump inhibitor (PPI) prescription in French children, its trends, and the impact of French (2014) and international (2018) clinical guidelines. STUDY DESIGN: We described PPI prescription rates based on national dispensation data in French children (IQVIA's Xponent database, 2009-2019). Using a segmented linear regression, we assessed the impact of clinical guidelines on PPI prescription rates. Analyses were performed for the overall pediatric population and by age subgroups (infants <2 years old, children 2-11 years old, adolescents 12-17 years old). RESULTS: During the study period, 8 060 288 pediatric PPI prescriptions were filled, with a mean PPI prescription rate of 52.5 per 1000 inhabitants per year. Between 2009 and 2019, the PPI prescription rate increased by 41% in the overall pediatric population (+110% in infants). The PPI prescription rate showed seasonal patterns with peaks in winter. After the release of French guidelines, significant decreases in trends of prescription rates occurred overall (change in trend -0.28, 95% CI -0.34;-0.23) and across all age groups. In infants, this change in trend was not sufficient to reverse the PPI prescription rate that was still increasing over time. In children, the PPI prescription rate slightly decreased and in adolescents, it was stable. After the release of international guidelines, a significant decrease in trend occurred in adolescents only (change in trend -0.26, 95% CI -0.47; -0.04). CONCLUSIONS: The pediatric PPI prescription rate in France was high, displayed a major increase over the last decade, mainly among infants, and was modestly affected by clinical guidelines.

Monitoring outpatient antibiotic utilization using reimbursement and retail sales data: a population-based comparison in France, 2012-17.

OBJECTIVES: To assess whether a retail sales database could be used to monitor antibiotic utilization in the outpatient setting at the national level. METHODS: We extracted 2012-17 outpatient antibiotic extrapolated retail sales (IQVIA's Xponent) and reimbursement data from the National Health Insurance (SNDS) in metropolitan France. We compared estimates of antibiotic use and consumption [number of antibiotic drug deliveries (DrID) and defined daily doses (DID) per 1000 inhabitants per day]. We relied on relative differences, Pearson's r statistics and time series using autoregressive integrated moving average (ARIMA) modelling to study: (i) differences in point estimates, (ii) correlation, and (iii) consistency in time trends between Xponent and SNDS. The analysis was conducted overall and in subgroups (age groups, therapeutic classes, major antimicrobial agents and regions). RESULTS: We analysed approximately 377 million antibiotic drug deliveries, comprising nearly 3.4 billion DDDs. Overall, Xponent slightly overestimated SNDS point estimates with yearly relative differences of +3.5% for DrID and +3.3% for DID. Peaks in relative differences were observed for July and August months. Relative differences were <5% in most subgroups, except for fosfomycin and three French regions. Overall and across most subgroups, the correlation between Xponent and SNDS monthly aggregated estimates was almost perfect (r ≥ 0.992 for all subgroups, except for one region). ARIMA modelling showed high consistency between Xponent's and SDNS's DrID time series, but detected timepoints where the series significantly diverged. CONCLUSIONS: IQVIA's Xponent and SNDS data were highly consistent. Xponent database seems suitable for monitoring outpatient antibiotic utilization in France.

Community antibiotic prescribing for children in France from 2015 to 2017: a cross-sectional national study.

OBJECTIVES: To assess recent community antibiotic prescribing for French children and identify areas of potential improvement. METHODS: We analysed 221 768 paediatric (<15 years) visits in a national sample of 680 French GPs and 70 community paediatricians (IQVIA's EPPM database), from March 2015 to February 2017, excluding well-child visits. We calculated antibiotic prescription rates per 100 visits, separately for GPs and paediatricians. For respiratory tract infections (RTIs), we described broad-spectrum antibiotic use and duration of treatment. We used Poisson regression to identify factors associated with antibiotic prescribing. RESULTS: GPs prescribed more antibiotics than paediatricians [prescription rate 26.1 (95% CI 25.9-26.3) versus 21.6 (95% CI 21.0-22.2) per 100 visits, respectively; P < 0.0001]. RTIs accounted for more than 80% of antibiotic prescriptions, with presumed viral RTIs being responsible for 40.8% and 23.6% of all antibiotic prescriptions by GPs and paediatricians, respectively. For RTIs, antibiotic prescription rates per 100 visits were: otitis, 68.1 and 79.8; pharyngitis, 67.3 and 53.3; sinusitis, 67.9 and 77.3; pneumonia, 80.0 and 99.2; bronchitis, 65.2 and 47.3; common cold, 21.7 and 11.6; bronchiolitis 31.6 and 20.1; and other presumed viral RTIs, 24.1 and 11.0, for GPs and paediatricians, respectively. For RTIs, GPs prescribed more broad-spectrum antibiotics [49.8% (95% CI 49.3-50.3) versus 35.6% (95% CI 34.1-37.1), P < 0.0001] and antibiotic courses of similar duration (P = 0.21). After adjustment for diagnosis, antibiotic prescription rates were not associated with season and patient age, but were significantly higher among GPs aged ≥50 years. CONCLUSIONS: Future antibiotic stewardship campaigns should target presumed viral RTIs, broad-spectrum antibiotic use and GPs aged ≥50 years.

Discrepancies in national time trends of outpatient antibiotic utilization using different measures: a population-based study in France.

Objectives: To assess time trends of outpatient antibiotic utilization using different measures and explore their discrepancies. Methods: Based on French sales data from the IQVIA SDM database, 2009-16, we assessed time trends in outpatient antibiotic utilization using PrID, DID, PID and SID (defined as the number of prescriptions, DDDs, packages and standard units per 1000 inhabitants per day, respectively). We explored discrepancies between trends in PrID and DID by modelling the number of DDDs per prescription. Results: Outpatient antibiotic utilization (n = 538.2 million projected prescriptions) decreased in terms of PrID, PID and SID (-10%, -8% and -8%, respectively; negative regression slopes; P < 0.01), but remained stable according to DID (+2%; slope 0.009; P = 0.4). The number of DDDs per prescription increased over time (+14%; slope 0.019; P < 0.001). The proportions of amoxicillin and amoxicillin/clavulanate were positively associated with the number of DDDs per prescription (adjusted coefficients 0.10 and 0.15, respectively; both P < 0.05), as well as the proportion of adult and hospital prescriptions (adjusted coefficients 0.07 and 0.05, respectively; both P < 0.05). The discrepancy between DID and PrID disappeared when the DDD of amoxicillin was increased to values higher than the current DDD. Conclusions: Time trends in outpatient antibiotic utilization expressed as PrID, DID, PID and SID provided conflicting results. We caution against using DID alone when monitoring antibiotic utilization. Instead, we recommend monitoring both DID and PrID as they provide different types of relevant information, especially when studying trends at a national level.