Comparison Of Simulated Research Articles

Evaluating the relative treatment efficacy of CD40 agonist mitazalimab in combination with mFOLFIRINOX in patients with metastatic pancreatic ductal adenocarcinoma (mPDAC) using unanchored indirect treatment comparisons (ITCs).

723 Background: Mitazalimab, a human CD40 agonistic IgG1antibody has demonstrated encouraging results in combination with mFOLFIRINOX (mFFX) in the phase 2 single arm trial OPTIMIZE-1 in patients with mPDAC. We conducted unanchored ITCs to assess the relative efficacy of mitazalimab + mFFX vs FOLFIRINOX (FFX) / mFFX and NALIRIFOX (NFX), the most effective therapies to date. Methods: Using data from OPTIMIZE-1 and published data from five RCTs identified via a literature review, matching-adjusted indirect comparisons (MAIC) and simulated treatment comparisons (STC), two commonly used ITC methods for health technology assessment (1) were conducted to balance effect modifiers and prognostic factors between trials. Analysis outcomes were overall survival (OS), objective response rate (ORR), and progression free survival (PFS). Reconstructed survival data from FFX, mFFX, and NFX studies were pooled together for the comparison with FFX/mFFX (Pool #1) and FFX/mFFX/NFX (Pool #2) pooled studies. Results: In the STC analysis mitazalimab + mFFX showed a significantly higher OS versus Pool #1 [hazard ratio (HR): 0.64; 95% CI: 0.46 – 0.87] and #2 [HR: 0.65; 95% CI: 0.47 – 0.87], corresponding to an improvement in median OS by 3.4 and 3.3 months respectively. The OS HRs of study-level pairwise comparisons ranged from 0.57 (95% CI: 0.39 – 0.80) to 0.85 (95% CI: 0.53 – 1.39) with only one non-significant comparison. MAICs showed similar trends, although the comparison with Pool #1 was close to statistical significance (HR: 0.68; 95% CI: 0.45 – 1.02). Results of the PFS and ORR comparisons are shown in the table below. Conclusions: Literature based ITCs show a significantly better efficacy of mitazalimab + mFFX versus the current available therapies in patients with mPDAC. These trends will have to be confirmed in a randomized Phase 3 study. 1. Phillippo DM et al, 2019. Clinical trial information: NCT02829099 . ITC results – HR (for OS and PFS) and odds ratios (for ORR) and their 95% CIs. STC MAIC Comparator study OS PFS ORR OS PFS ORR PRODIGE 4 (FFX) 0.57 (0.39 – 0.80) 0.63 (0.44 – 0.88) 1.62(0.87 – 2.99) 0.60 (0.40 – 0.89) 0.56 (0.37 – 0.82) 1.55(0.84 – 2.87) PANOPTIMOX (FFX) 0.58 (0.39 – 0.84) 0.68 (0.47 – 0.98) 1.17(0.59 – 2.30) 0.60 (0.38 – 0.94) 0.67(0.44 – 1.02) 1.04(0.52 – 2.05) AVENGER500 (FFX) 0.71 (0.50 – 0.98) 1.15(0.82 – 1.60) 1.35(0.75 – 2.42) 0.69(0.46 – 1.03) 1.11(0.76 – 1.62) 1.30(0.72 – 2.34) SWOGS1313 (mFFX) 0.85(0.53 – 1.39) 0.89(0.57 – 1.36) 0.90(0.43 – 1.89) 0.91(0.55 – 1.50) 0.86(0.55 – 1.33) 0.88(0.42 – 1.86) Pool #1 0.64 (0.46 – 0.87) 0.81(0.59 – 1.10) 1.33(0.77 – 2.32) 0.68(0.45 – 1.02) 0.81(0.56 – 1.18) 1.20(0.69 – 2.09) NAPOLI-3 (NFX) 0.68 (0.49 – 0.93) 0.85(0.61 – 1.17) 0.97(0.55 – 1.71) 0.67 (0.46 - 0.97) 0.83(0.58 – 1.20) 0.92(0.52 – 1.62) Pool #2 0.65 (0.47 – 0.87) 0.82(0.60 – 1.11) 1.17(0.68 – 2.02) 0.68 (0.47 – 0.99) 0.84(0.59 – 1.19) 1.11(0.64 – 1.91)

Comparative Efficacy of Lebrikizumab, Dupilumab, and Tralokinumab in Maintaining Treatment Response in Atopic Dermatitis at Varying Treatment Continuance Rates

Introduction: Atopic dermatitis (AD) is a chronic inflammatory skin disease with significant impacts on quality of life. Despite the effectiveness of biologics for moderate to severe AD, long-term treatment adherence can be challenging in clinical practice. This study introduces the “durability index” as a novel estimate of the maintenance of therapeutic effect under varying treatment continuance rates. Methods: A population-adjusted indirect comparison of placebo-controlled phase 3 trials of dupilumab 300 mg QW/Q2W (SOLO 1, SOLO 2, and SOLO CONTINUE), tralokinumab 300 mg Q2W (ECZTRA1 and ECZTRA 2), and lebrikizumab 250 mg Q4W (ADvocate1 and ADvocate2) was conducted. In these trials, patients who responded at week 16 (IGA 0/1 or EASI 75) were re-randomized to either continue treatment or switch to treatment withdrawal (placebo) until week 52. The durability index was developed to estimate drug performance at varying treatment continuance rates between 100% to 0% on-treatment. Unanchored simulated treatment comparison (STC) was used to estimate odds ratios (OR) adjusting for baseline covariates. Results: For IGA 0/1, patients receiving lebrikizumab had statistically significantly better odds of maintaining response at week 52 than those on dupilumab for all treatment continuance rates, ranging from 1.730 (p = 0.044) at 100% to 4.690 (p < 0.001) at 0%. ORs comparing lebrikizumab to tralokinumab ranged from 1.787 at 100% continuance to 1.516 at 0%, with significant results favoring continuance rates between 39.5% and 96.9%. For EASI 75, week-52 durability at 100% continuance was non-significantly different between lebrikizumab and dupilumab (OR 0.687, p = 0.183); however, ORs increased in favor of lebrikizumab at lower treatment continuance rates, reaching significance from 64.2% (OR 1.454, p = 0.05) to 0% (OR 3.235, p < 0.001) continuance. ORs comparing lebrikizumab to tralokinumab ranged from 2.132 at 100% to 3.891 at 0% continuance, with significant results favoring lebrikizumab for all treatment continuance rates. ORs comparing dupilumab and tralokinumab showed varying results: tralokinumab was favored for IGA 0/1 at lower continuance rates, while dupilumab was favored for EASI 75 at higher continuance rates. Conclusions: In this indirect comparative analysis, lebrikizumab had treatment response rates that were comparable to or better than dupilumab and tralokinumab, regardless of treatment continuance rates. This finding suggests that lebrikizumab may offer a more effective long-term management option for AD. This analysis was funded by Eli Lilly and Company.

DUVET: sub-kiloparsec resolved star formation driven outflows in a sample of local starbursting disc galaxies

ABSTRACT We measure resolved (kiloparsec-scale) outflow properties in a sample of 10 starburst galaxies from the Deep near-UV observations of Entrained gas in Turbulent (DUVET) galaxies sample, using Keck/KCWI observations of H $\beta$ and [O iii] $\lambda$5007. We measure $\sim 460$ lines of sight that contain outflows, and use these to study scaling relationships of outflow velocity ($v_{\rm out}$), mass-loading factor ($\eta$; mass outflow rate per star formation rate) and mass flux ($\dot{\Sigma }_{\rm out}$; mass outflow rate per area) with co-located star formation rate surface density ($\Sigma _{\rm SFR}$) and stellar mass surface density ($\Sigma _{\ast }$). We find strong, positive correlations of $\dot{\Sigma }_{\rm out} \propto \Sigma _{\rm SFR}^{1.2}$ and $\dot{\Sigma }_{\rm out} \propto \Sigma _{\ast }^{1.5}$. We also find shallow correlations between $v_{\rm out}$ and both $\Sigma _{\rm SFR}$ and $\Sigma _{\ast }$. Our resolved observations do not suggest a threshold in outflows with $\Sigma _{\rm SFR}$, but rather we find that the local specific star formation rate ($\Sigma _{\rm SFR}/\Sigma _\ast$) is a better predictor of where outflows are detected. We find that outflows are very common above $\Sigma _{\rm SFR}/\Sigma _\ast \gtrsim 0.1$ Gyr$^{-1}$ and rare below this value. We argue that our results are consistent with a picture in which outflows are driven by supernovae, and require more significant injected energy in higher mass surface density environments to overcome local gravity. The correlations we present here provide a statistically robust, direct comparison for simulations and higher redshift results from JWST.

Enhancing low-illumination imagery using a Deep Convolutional Generative Adversarial Network with weight regularization (DCGAN-WR) and Zero-Reference Deep Curve Estimation (DCE)

Improving low-light images to enhance prediction in various applications has a greater advantage. A two-pronged approach that employs Deep Convolutional Generative Adversarial Networks with weight regularization (DCGAN-WR) and Zero-Reference Deep Curve Estimation (DCE) was used. The model was trained using the LOL dataset, and the results showed significant improvements in image quality. The DCGAN is fine-tuned with Group Lasso regularization to enhance the performance. The DCGAN-WR model is shown to enhance images realistically, demonstrating its capacity to learn characteristics and texture representations from low-light input. Empirical and simulated image comparisons demonstrate remarkable performance under demanding low-light settings. Moreover, the DCE model employs a novel approach that considers color constancy loss, light smoothness, and spatial consistency. Information about the learning dynamics and curve parameter changing capabilities of the model can be visualized by loss function graphs, which aim to maximize picture quality. Compared to the original images, Images generated by the DCE models maintain color accuracy, increase exposure levels, and preserve spatial coherence. A solution for low-illumination image enhancement is achieved through the proposed model DCGAN-WR and DCE. Genuine details are recorded by the GAN model, while the DCE adjusts the exposure levels and color balance to produce improved, aesthetically pleasing, and contextually accurate images. The proposed approach not only outperforms the other methods on the LOL dataset but also exhibits potential for practical use in computer vision tasks, which require higher image quality for precise analysis and interpretation.

An Efficient Acoustic Camera Simulator for Robotic Applications: Design, Implementation, and Validation.

As forward-looking imaging sonar, also called an acoustic camera, has emerged as an important sensor for marine robotics applications, its simulators have attracted considerable research attention within the field. This paper presents an acoustic camera simulator that efficiently generates acoustic images using only the depth information of the scene. The simulator approximates the acoustic beam of a real acoustic camera as a set of acoustic rays originating from the center of the acoustic camera. A simplified active sonar model and error models for the acoustic rays are incorporated to account for the environmental factors which can affect the rays. The simulator is implemented in the Gazebo simulator, a robotic simulator, and does not rely on any other components except depth rendering. To evaluate the performance of the developed simulator, qualitative and quantitative comparisons were conducted between simulated images and actual acoustic images obtained in a test tank.

Using cluster-based permutation tests to estimate MEG/EEG onsets: How bad is it?

Localising effects in space, time and other dimensions is a fundamental goal of magneto- and electroencephalography (EEG) research. A popular exploratory approach applies mass-univariate statistics followed by cluster-sum inferences, an effective way to correct for multiple comparisons while preserving high statistical power by pooling together neighbouring effects. Yet, these cluster-based methods have an important limitation: each cluster is associated with a unique p-value, such that there is no error control at individual timepoints, and one must be cautious about interpreting when and where effects start and end. Sassenhagen and Draschkow (2019) provided an important reminder of this limitation. They also reported results from a simulation, suggesting that onsets estimated from EEG data are both positively biased and very variable. However, the simulation lacked comparisons to other methods. Here, I report such comparisons in a new simulation, replicating the positive bias of the cluster-sum method, but also demonstrating that it performs relatively well, in terms of bias and variability, compared to other methods that provide pointwise p-values: two methods that control the false discovery rate and two methods that control the familywise error rate (cluster-depth and maximum statistic methods). I also present several strategies to reduce estimation bias, including group calibration, group comparison and using binary segmentation, a simple change point detection algorithm that outperformed mass-univariate methods in simulations. Finally, I demonstrate how to generate onset hierarchical bootstrap confidence intervals that integrate variability over trials and participants, a substantial improvement over standard group approaches that ignore measurement uncertainty.

Comparison of NeedleTrainer™ and ultrasound tissue simulator in a simulated environment among novice regional anaesthesia practitioners

BackgroundUtilising ultrasound technology has resulted in higher success and lower complication rates during regional anaesthesia (RA) procedures. Proper training is necessary to accurately identify structures, optimise images, and improve hand–eye coordination. Simulation training using immersive virtual environments and simulation models has enabled this competency training to be conducted safely before performing on patients. We conducted a study to compare the simulator performance and users’ feedback on a Blue Phantom Regional Anaesthesia Ultrasound Training Block and NeedleTrainer™.MethodsForty-seven participants were recruited via convenient sampling during a RA workshop for novice practitioners. They were divided into the N or B group and then crossover to experience using both Blue Phantom and NeedleTrainer model. Time-to-reach-target, first-pass success rate, and complication rate were assessed, while the learning and confidence scores were rated using six-item and three-item questionnaires, respectively, via a 5-point Likert scale.ResultsBlue Phantom model has a longer time-to-target as compared to the NeedleTrainer model (16 ± 8 vs 8 ± 3 s, p < 0.001), higher first- pass success rate (100% vs 80.9%), and lower complication rate (0% vs 19.1%). Higher overall learning satisfaction scores (28 ± 4 vs 25 ± 4, p = 0.003) and confidence scores after training (13 ± 2 vs 12 ± 2, p < 0.001) were recorded for the Blue Phantom model.ConclusionsWe postulated that the artificial intelligence structure recognition software enables NeedleTrainer users to attain shorter time-to-target. That being said, Blue Phantom provides better operator learning satisfaction, improved confidence, higher success and lower complication rates among novice RA practitioners, possibly due to greater tactile feedback during the simulated training.

Force field comparison for molecular dynamics simulations of liquid membranes

To accelerate the development of liquid ion-selective barriers based on ethers, we compare the all-atom force fields GAFF, OPLS-AA with charge correction 1.14*CM1A (OPLS-AA/CM1A), CHARMM version 36 (CHARMM36), and COMPASS for diisopropyl ether (DIPE) to determine the most appropriate model for further simulations of liquid membranes. Utilizing the selected force fields, we calculate the density and shear viscosity of DIPE across a temperature range of 243–333 K. Furthermore, we use CHARMM36 with mTIP3P water model and COMPASS with its own water model to evaluate the mutual solubility and interfacial tension between DIPE and water, estimate the partition coefficients of ethanol in DIPE + Ethanol + Water systems. Based on our comparative study, we conclude that CHARMM36 is the most suitable force field for modeling ether-based liquid membranes.

A taxometric analysis of panic disorder

ABSTRACT Panic disorder is costly, and while evidence-based interventions for panic disorder are effective, obtaining a diagnosis often precludes access to such treatments. This is problematic because the categorical diagnosis of panic disorder (i.e. “you have it, or you don’t”) supported by modern diagnostic manuals contradicts empirically supported dimensional models of panic disorder. Taxometric analyses, which test the dimensional or categorical latent structure of constructs, have consistently revealed dimensional latent structures when applied to other anxiety disorders and panic-related processes, but taxometric analyses have never been applied to panic disorder. To address this gap in the literature, three nonredundant taxometric procedures were applied to seven theoretically-relevant indicators of panic disorder derived from Panic Disorder Severity Scale data collected from 663 participants recruited via Amazon Mechanical Turk. Simulated comparison plots and objective fit indices were also evaluated. The collective results provided consistent empirical support for a dimensional model of panic disorder, with an overall mean CCFI score of .39. The implications of the present findings for the measurement, assessment, diagnosis, and treatment of panic disorder are discussed.

Optimized trajectory tracking control with disturbance resistance for wheeled mobile robot

When unavoidable disturbances exist in practical applications, the unicycle wheeled mobile robot (WMR) with non-holonomic constraint is challenging to be accurately controlled in finite time. An optimized dual closed-loop strategy is proposed in this paper to solve the trajectory tracking control problem of the unicycle WMR. The control strategy with fast time convergence and anti-disturbance properties consists of kinematic and dynamics controllers and an optimization algorithm. The kinematic controller is designed with an improved backstepping method to eliminate the non-holonomic constraints. The robust sliding mode control (SMC) method with fixed-time convergence is used to construct the dynamics controller. The optimization algorithm enhances the performance of the strategy and achieves accurate control. The global convergence and robustness of the strategy are theoretically demonstrated. The effectiveness of the strategy is verified by comparison in simulations.

Detecting Indoor Tiny Autonomous Malicious Drones within Critical Infrastructures: An Innovative Algorithm based on Harmonic Radar-Equipped Mini-Drones

Critical infrastructures play a central role in the welfare of contemporary societies and they should properly function 24/7. Since their role is so important, they regularly become targets of malicious parties, terrorists, industrial spies, and even hostile governments. In this paper, the scenario of cyber or physical attacks to CIs from tiny autonomous malicious drones is analyzed. In particular, this work focuses on indoor spaces, protected by mini-drones. The mini-drones are equipped with harmonic radar and run a novel algorithm, which guides them to scan the whole area. Assuming that the malicious drones behave as non-linear systems, the mini-drones transmit signals and analyze the received signals, creating a non-linear system 3D location map for the whole space. In the consecutive scans, any changes on the 3D location map indicate that the malicious drone has changed location. Simulated results and comparisons to state-of-the-art approaches exhibit the cost-effectiveness and time efficiency of the proposed scheme as well as its limitations.

Comparison of Web-Based and On-Site Lung Simulators for Education in Mechanical Ventilation.

Training in mechanical ventilation is a key goal in critical care fellowship education. Web-based simulators offer a cost-effective and readily available alternative to traditional on-site simulators. However, it is unclear how effective they are as teaching tools. In this study, we evaluated the test scores of fellows who underwent mechanical ventilation training by using a web-based simulator compared with fellows who used an on-site simulator during a mechanical ventilation course. This was a nonrandomized controlled trial conducted as part of a mechanical ventilation course that involved 70 first-year critical care fellows. The course was identical except for the simulation technology used. One group of instructors used a traditional on-site simulator, the ASL 5000 Lung Solution (n = 39). The second group was instructed in using a web-based simulator, VentSim (n = 31). Each fellow completed a pre-course test and a post-course test by using a validated, case-based ventilator waveform examination that consisted of 5 questions with a total possible score of 100. The primary outcome was a comparison of the mean scores on the posttest between the 2 groups. The study was designed as a non-inferiority trial with a predetermined margin of 10 points. There was no significant difference in the mean ± SD pretest scores between the web-based and the on-site groups (21.1 ± 12.6 and 26.9 ± 13.6 respectively; P = .11). The mean ± SD posttest scores were 45.6 ± 25.0 for the web-based simulator and 43.4 ± 16.5 for on-site simulator (mean difference 2.2; one-sided 95% CI -7.0 to ∞; P non-inferiority = .02 [non-inferiority confirmed]). Changes in mean ± SD scores (posttest - pretest) were 25.9 ± 20.9 for the web-based simulator and 16.5 ± 15.9 for the on-site simulator (mean difference 9.4, one-sided 95% CI 0.9 to ∞; P non-inferiority < .001 [non-inferiority confirmed]). In the education of first-year critical care fellows on mechanical ventilation waveform analysis, a web-based mechanical ventilation simulator was non-inferior to a traditional on-site mechanical ventilation simulator.

Comparative Analysis and Optimal Selection of Calibration Functions in Pure Rotational Raman Lidar Technique

The pure rotational Raman (PRR) lidar technique relies on calibration functions (CFs) to extract temperature information from raw detection data. The choice of CF significantly impacts the accuracy of the retrieved temperature. In this study, we propose a method that combines multiple Monte Carlo simulation experiments with a statistical analysis, and we first conduct simulated comparisons of the calibration effects of different CFs while considering the impact of noise. We categorized ten common CFs into four groups based on their functional form and the number of calibration coefficients. Based on functional form, specifically, we defined 1/T = f(lnQ) as a forward calibration function (FCF) and lnQ = g(1/T) as a backward calibration function (BCF). Here, T denotes temperature, and Q denotes the signal intensity ratio. Their performance within and outside the calibration interval is compared across different integration times, smoothing methods, and reference temperature ranges. The results indicate that CFs of the same category exhibit similar calibration effects, while those of different categories exhibit notable differences. Within the calibration interval, the FCF performs better, especially with more coefficients. However, outside the calibration interval, the linear calibration function (which can be considered a two-coefficient FCF) has an obvious advantage. Conclusions based on the simulation results are validated with actual data, and the factors influencing calibration errors are discussed. Utilizing these findings to guide CF selection can enhance the accuracy and stability of PRR lidar detection.

Delivery Route Scheduling of Heterogeneous Robotic System with Customers Satisfaction by Using Multi-Objective Artificial Bee Colony Algorithm

This study addresses the route scheduling problem for the heterogeneous robotic delivery system (HRDS) that perform delivery tasks in an urban environment. The HRDS comprises two distinct types of vehicles: an unmanned ground vehicle (UGV), which is constrained by road networks, and an unmanned aerial vehicle (UAV), which is capable of traversing terrain but has limitations in terms of energy and payload. The problem is formulated as an optimal route scheduling problem in a road network, where the goal is to find the route with minimum delivery cost and maximum customer satisfaction (CS) enabling the UAV to deliver packages to customers. We propose a new method of route scheduling based on an improved artificial bee colony algorithm (ABC) and the non-dominated sorting genetic algorithm II (NSGA-II) that provides the optimal delivery route. The effectiveness and superiority of the method we proposed are demonstrated by comparison in simulations. Moreover, the physical experiments further validate the practicality of the model and method.

1417P Comparative efficacy and safety of tislelizumab versus anti-PD-1 treatments in second-line esophageal squamous cell carcinoma: Simulated treatment comparisons

1417P Comparative efficacy and safety of tislelizumab versus anti-PD-1 treatments in second-line esophageal squamous cell carcinoma: Simulated treatment comparisons

A rotating machinery feature enhancement method based on improved symplectic geometry mode component sparsity

Gears and bearings are vital parts of rotating equipment. Weak fault feature enhancement is crucial to fault diagnosis. Therefore, a feature enhancement method based on the improved symplectic geometry mode component sparsity (ISGMCS) is proposed. Firstly, the improved symplectic geometry mode decomposition (ISGMD) method is proposed to reduce redundancy. ISGMD parameter optimization is based on Particle Swarm Optimization (PSO) and Kurtosis-to-Eigenvalue (KE). The max-kurtosis redundancy reduction component of ISGMD with less redundancy is used for sparse analysis. Subsequently, the sparse feature mining method is proposed to enhance the fault features of the redundancy reduction component. A sparse model optimization solution based on Forward-Backward Splitting (FBS) and the Mean Amplitude Ratio (MAR) metric is implemented. Finally, the effectiveness and superiority of ISGMCS are verified by simulated experiments, fault experiments, and comparison experiments. Meanwhile, the Mean Value of Amplitude (MVA) metric is designed to evaluate the effect of ISGMCS.

A hyperbolic–elliptic PDE model and conservative numerical method for gravity-dominated variably-saturated groundwater flow

Richards equation is often used to represent two-phase fluid flow in an unsaturated porous medium when one phase is much heavier and more viscous than the other. However, it cannot describe the fully saturated flow for some capillary functions without specialized treatment due to degeneracy in the capillary pressure term. Mathematically, gravity-dominated variably saturated flows are interesting because their governing partial differential equation switches from hyperbolic in the unsaturated region to elliptic in the saturated region. Moreover, the presence of wetting fronts introduces strong spatial gradients often leading to numerical instability. In this work, we develop a robust, multidimensional mathematical model and implement a well-known efficient and conservative numerical method for such variably saturated flow in the limit of negligible capillary forces. The elliptic problem in saturated regions is integrated efficiently into our framework by solving a reduced system corresponding only to the saturated cells using fixed head boundary conditions in the unsaturated cells. In summary, this coupled hyperbolic–elliptic PDE framework provides an efficient, physics-based extension of the hyperbolic Richards equation to simulate fully saturated regions. Finally, we provide a suite of easy-to-implement yet challenging benchmark test problems involving saturated flows in one and two dimensions. These simple problems, accompanied by their corresponding analytical solutions, can prove to be pivotal for the code verification, model validation (V&V) and performance comparison of simulators for variably saturated flow. Our numerical solutions show an excellent comparison with the analytical results for the proposed problems. The last test problem on two-dimensional infiltration in a stratified, heterogeneous soil shows the formation and evolution of multiple disconnected saturated regions.

Robust optimal dispatching of power grid with the participation of virtual power plants

Abstract One of the key technologies for creating intelligent distribution networks is energy management systems, which allow virtual power plants (VPPs) to combine distributed flexible resources and accomplish unified scheduling and coordination. This paper presents a solid optimization model that compromises safety and economics for distribution networks involving virtual power plants. First, a power flow model for the distribution network is created to minimize voltage variation, operating cycle cost, and the safety operation of several AM (active management) methods as constraints. Second, a strong optimization model for the distribution network was built with the participation of virtual power plants, accounting for the unpredictability of the load and fresh energy. Finally, the problem was solved using the relaxation evolution technique, and the precision and potency of the suggested model were shown by doing a simulated comparison study on the upgraded IEEE33 node testing system.

A novel framework to intercept GPS-denied, bomb-carrying, non-military, kamikaze drones: Towards protecting critical infrastructures

Protection of urban critical infrastructures (CIs) from GPS-denied, bomb-carrying kamikaze drones (G-B-KDs) is very challenging. Previous approaches based on drone jamming, spoofing, communication interruption and hijacking cannot be applied in the case under examination, since G-B-KDs are uncontrolled. On the other hand, drone capturing schemes and electromagnetic pulse (EMP) weapons seem to be effective. However, again, existing approaches present various limitations, while most of them do not examine the case of G-B-KDs. This paper, focuses on the aforementioned under-researched field, where the G-B-KD is confronted by two defensive drones. The first neutralizes and captures the kamikaze drone, while the second captures the bomb. Both defensive drones are equipped with a net-gun and an innovative algorithm, which, among others, estimates the locations of interception, using a real-world trajectory model. Additionally, one of the defensive drones is also equipped with an EMP weapon to damage the electronics equipment of the kamikaze drone and reduce the capturing time and the overall risk. Extensive simulated experiments and comparisons to state-of-art methods, reveal the advantages and limitations of the proposed approach. More specifically, compared to state-of-art, the proposed approach improves: (a) time to neutralize the target by at least 6.89%, (b) maximum number of missions by at least 1.27% and (c) total cost by at least 5.15%.

Methods for Indirect Treatment Comparison: Results from a Systematic Literature Review.

Health technology assessment (HTA) agencies express a clear preference for randomized controlled trials when assessing the comparative efficacy of two or more treatments. However, an indirect treatment comparison (ITC) is often necessary where a direct comparison is unavailable or, in some cases, not possible. Numerous ITC techniques are described in the literature. A systematic literature review (SLR) was conducted to identify all the relevant literature on existing ITC techniques, provide a comprehensive description of each technique and evaluate their strengths and limitations from an HTA perspective in order to develop guidance on the most appropriate method to use in different scenarios. Electronic database searches of Embase and PubMed, as well as grey literature searches, were conducted on 15 November 2021. Eligible articles were peer-reviewed papers that specifically described the methods used for different ITC techniques and were written in English. The review was performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A total of 73 articles were included in the SLR, reporting on seven different ITC techniques. All reported techniques were forms of adjusted ITC. Network meta-analysis (NMA) was the most frequently described technique (in 79.5% of the included articles), followed by matching-adjusted indirect comparison (MAIC) (30.1%), network meta-regression (24.7%), the Bucher method (23.3%), simulated treatment comparison (STC) (21.9%), propensity score matching (4.1%) and inverse probability of treatment weighting (4.1%). The appropriate choice of ITC technique is critical and should be based on the feasibility of a connected network, the evidence of heterogeneity between and within studies, the overall number of relevant studies and the availability of individual patient-level data (IPD). MAIC and STC were found to be common techniques in the case of single-arm studies, which are increasingly being conducted in oncology and rare diseases, whilst the Bucher method and NMA provide suitable options where no IPD is available. ITCs can provide alternative evidence where direct comparative evidence may be missing. ITCs are currently considered by HTA agencies on a case-by-case basis; however, their acceptability remains low. Clearer international consensus and guidance on the methods to use for different ITC techniques is needed to improve the quality of ITCs submitted to HTA agencies. ITC techniques continue to evolve quickly, and more efficient techniques may become available in the future.