Relevant Benchmark Research Articles

Utility-Aware Optimal Resource Allocation Protocol for UAV-Assisted Small Cells With Heterogeneous Coverage Demands

In this paper, we consider a UAV-assisted small-cell having heterogeneous users with different data rate and coverage demands. Specifically, we propose a novel utility-aware resource-allocation protocol to maximize the utility of UAV by allowing it to simultaneously serve the highest possible number of heterogeneous users with available energy resources. In this regard, first we derive a closed-form expression for rate-coverage probability of a user considering Rician fading to incorporate the strong line of sight (LoS) component in UAV communication. Next since this UAV utility maximization problem is non-convex and combinatorial, to obtain the global optimal resource allocation policy we propose an iterative feasibility checking method for fixed integers ranging from lower to upper bound on the number of users that can be served by UAV. To further reduce the complexity, we formulate an equivalent problem aimed at minimizing per user energy consumption, where tight analytical relaxation on rate-coverage probability constraint is used along with semi-closed expressions for joint-optimal power and time allocation. Lastly, via detailed numerical investigation, we validate our analytical claims, present insights on the impact of key system parameters, and demonstrate that 60% more users can be served using the proposed scheme as compared to relevant benchmarks.

A Scoping Review of Non-invasive Imaging Modalities in Dermatological Disease: Potential Novel Biomarkers in Hidradenitis Suppurativa.

Background: The development of imaging-based biomarkers has the potential to overcome major challenges in the accurate and reproducible assessment of disease severity and response to novel therapies in Hidradenitis Suppurativa (HS). Understanding the advantages and limitations of existing non-invasive imaging modalities in dermatological disease will aid in the development of hypotheses and inform the design of future studies.Methods: A scoping review was performed using Medline, Embase, Web of Science Databases and evaluation of “gray literature” until June 30, 2019. Citations were examined according to pre-defined inclusion and exclusion criteria. Citations were reviewed by two independent reviewers. Narrative Synthesis was used to summarize data, structured by imaging modality.Results: Non-invasive imaging modalities, such as ultrasound, MRI, RCM, EIS, OCT, and MIT, were identified. Only ultrasound, MRI and MIT have been used in HS. Image modalities vary in image depth, resolution, cost, accessibility and correlation with known aspects of disease activity in HS.Discussion and Conclusion: The benefits and limitations of each imaging modality are products of cost, accessibility, validity and reliability. An additional hurdle to the development of image-based biomarkers in HS is a lack of established analytical benchmarks that can be correlated with existing biological, inflammatory and clinical parameters. This review has identified potential imaging biomarkers, as well as relevant analytical benchmarks that reflect the presence or absence of disease. Further investigation work is needed to analytically and clinically validate these imaging variables in order to identify potential imaging biomarkers in HS.

Evaluation of blood mercury and serum selenium levels in the pregnant population of the Community of Madrid, Spain

BackgroundThe main exposure route to methylmercury (MeHg) is from eating fish and shellfish containing this compound. Since 2004, women of childbearing age in Spain have been urged not to eat some species (eg, tuna, shark, and swordfish), instead choosing low-MeHg seafood as part of a healthy diet. ObjectiveTo describe maternal total blood mercury (THg) and serum selenium (Se) in a cohort of pregnant women living in Spain as it relates to fish intake during the three trimesters and to assess whether or not Spanish women of childbearing age follow the recommendations listed in fish advisories and choose fish species with lower mercury levels. MethodsWe studied 141 female volunteers of childbearing age (16–45 years), interviewing all participants about their overall eating habits and seafood intake. Hg and Se levels were tested using cold-vapor atomic absorption spectrometry (CVAAS) and electrothermal atomic absorption spectrometry (ETAAS), respectively. ResultsAverage THg levels in pregnant women were 2.89 μg/L (standard deviation [SD], 2.75 μg/L, geometric mean [GM], 2.19 μg/L), and THg GM was positively associated with fish intake. Mean Se levels in pregnant women were 73.06 μg/L (SD, 13.38 μg/L), and Se levels were found to increase with tuna intake. In 16 (12%) pregnant women, THg was higher than the level recommended by the U.S. Environmental Protection Agency (EPA) (6.4 μg/L). A positive association was also found between THg and serum Se. ConclusionWomen of childbearing age in Spain had higher THg levels than women in other Western studies. Our study observed that 12% of women had THg levels above the safety limit set by the EPA (6.4 μg/L), and 31% had levels above the relevant benchmark level of 3.5 μg/L suggested by various researchers.

Sustainable Urban Transport Indicators: Case of Mega Cities of India

The modern urban economies, in struggle to keep up with the pace of economic growth are suffering from issues of sustainability in transportation, imposing huge costs on the economy. Major reasons for the unsustainability in transportations can be listed as, a) issue of accessibility, b) lack of efficiency and c) diminishing air quality. This paper tries to evaluate these issues for megacities of India from dimensional principles of sustainability. The paper tried to evaluate the indicators of sustainability by adopting the famous three-dimensional principles to the major mega cities of the country. The findings from this paper are quite interesting to note that, the major mega cities are suffering from unsustainable transport system. To have a deeper look, Bengaluru, emerging mega city of Karnataka, is analysed by bringing new dimension called, institutional sustainability . By evaluating, economic, social, environmental and institutional sustainability with relevant benchmarks, the result showed that, in all respect mega cities of India and more specifically, Bengaluru city is experiencing unsustainable growth of transport sector which needs urgent attention of the policy makers.

Joint Layer Prediction for Improving SHVC Compression Performance and Error Concealment

Scalable high efficiency video coding (SHVC) standard is expected to play a more important role in the heterogeneous landscape of broadcasting, multimedia, networks, and various services applications as it is specified as a layered coding technique in the advanced television systems committee 3.0. However, its block-based structure of temporal and spatial prediction makes it sensitive to information loss and error propagation due to transmission errors. In this context, we propose an improved SHVC with a joint layer prediction (JLP) solution which adaptively combines the decoded information from the base and the enhancement layers to create an additional reference for the SHVC enhancement encoder. To optimize the quality of the joint prediction, the minimum mean square error estimation is executed in computing a combination factor which gives weights to each contribution of the decoded information from the layers. In addition, the proposed JLP is integrated into the SHVC decoder to work as an error concealment solution to mitigate the error propagation happening inevitably in practical video transmission. Experiments have shown that the proposed SHVC framework significantly outperforms its relevant benchmarks, notably by up to 14.8% in bitrate reduction with respect to the standard SHVC codec. The proposed SHVC error concealment strategy also greatly improves the concealed picture quality as well as reducing the problem of error propagation when compared to conventional error concealment approaches.

Vaccination coverage in Qatar: Benchmarking with global figures.

Introduction: Vaccination is considered one of the most successful and cost-effective public health interventions of the 20th century. In 2017, Qatar's Expanded Program of Immunization (EPI) provided vaccination services against a comprehensive list of 15 vaccine-preventable diseases. Objectives: To assess the performance of Qatar's national immunization system, identify possible gaps by determining the national vaccination coverage rates, and benchmark these rates against regional and global figures. Methods: The data utilized herein were retrieved from the vaccination coverage estimates generated by the World Health Organization and United Nations International Children's Emergency Fund. Relevant local, regional, and global vaccination coverage figures were manually extracted and then analyzed for six vaccines (DTP3, Pol3, MCV2, HepB, PCV3, and RotaC) in 2017. Percentages and proportions were compared using the Chi-squared test. Results: Vaccination coverage levels in Qatar have surpassed the optimal level of 90% for all vaccines. Compared with international figures, the national coverage exceeds the relevant benchmarks. For DTP3 and Pol3, Qatar achieved 97% coverage compared with 99% coverage in Jordan and 85% coverage globally. For MCV2, Qatar achieved 93% coverage compared with 99% coverage in Jordan and 67% coverage globally. For RotaC, Qatar achieved 97% coverage compared with 96% coverage in Jordan and 28% coverage globally. For HepB, Qatar achieved 97% coverage compared with 43% coverage globally. Conclusions: Compared with the international benchmarks of major vaccines, the vaccination coverage rates in Qatar are high. However, challenges for maintaining high coverage, such as cultural and language barriers, should be addressed.

A Monte Carlo method for computing the action of a matrix exponential on a vector

A Monte Carlo method for computing the action of a matrix exponential for a certain class of matrices on a vector is proposed. The method is based on generating random paths, which evolve through the indices of the matrix, governed by a given continuous-time Markov chain. The vector solution is computed probabilistically by averaging over a suitable multiplicative functional. This representation extends the existing linear algebra Monte Carlo-based methods, and was used in practice to develop an efficient algorithm capable of computing both, a single entry or the full vector solution. Finally, several relevant benchmarks were executed to assess the performance of the algorithm. A comparison with the results obtained with a Krylov-based method shows the remarkable performance of the algorithm for solving large-scale problems.

A Modified Variable Neighbourhood Search Heuristic for the Multi‐Mode Resource Constrained Project Scheduling Problem with A Case Study

AbstractThis paper provides a fast near‐optimum solution to the Multi‐Mode Resource Constrained Project Scheduling Problem (MRCPSP), for projects with activities that have known deterministic renewable and non‐renewable resource requirements. Multi‐modes allows any activity to execute one of many alternative combinations of resource usages and durations, while each activity needs to pick the most feasible one. This type of setting is more prevalent for real‐life project schedules, which necessitates systematic methodologies and advanced solution approaches in harmony with real‐world implementations. This study proposes a Modified Variable Neighbourhood Search Heuristic (MVNSH) algorithm as an advanced optimization technique for scheduling projects. To validate our approach, exhaustive computational tests were carried out by using relevant benchmark instances. The MVNSH algorithm has been shown to be faster and more accurate than many existing heuristic methods. This research also contributes to developing a practical decision support system for resolving real‐life constraints in multi‐mode resource‐constrained projects.

Abstract 3268: Costimulatory T-cell engagement by PRS-342, a GPC3/4-1BB bispecific molecule, leads to activation of T-cells and tumor growth inhibition in a HCC humanized mouse model

Abstract Background: Increasing evidence shows that 4-1BB is a key costimulatory immunoreceptor and a highly-promising therapeutic target in cancer. Current antibody-based approaches showed immune cell activation not only in tumor tissues, but also in the periphery, which is associated with dose-limiting on-target toxicity. To overcome this limitation, we generated PRS-342, a GPC3/4-1BB bispecific molecule based on the Anticalin technology. This molecule is designed to promote 4-1BB clustering by bridging 4-1BB-positive T cells with GPC3-expressing tumor cells. GPC3 is an oncofetal protein with high tumor selectivity and high expression in not only hepatocellular carcinomas, but also in a variety of other tumors with high medical need. Methods: Anticalin therapeutics are 18 kD proteins derived from human lipocalins. We utilized phage display to generate an Anticalin protein binding to 4-1BB with high affinity and specificity. The PRS-342 bispecific construct was generated by genetic fusion of a 4-1BB-specific Anticalin protein to a humanized high affinity GPC3-targeting monoclonal antibody with an engineered IgG4 backbone. Results: We show that the bispecific molecule PRS-342 retains its ability to bind both targets (4-1BB and GPC3) with similar affinity to the parental building blocks and is capable of binding both targets simultaneously. Biophysical characterization of PRS-342 reflect its good drug-like properties. Using in vitro assays based on mixed culture of human pan-T cells and GPC3-expressing tumor cell lines, PRS-342 induced T-cell costimulation leading to increase production of IL-2 with EC50 in the sub-nanomolar range. In contrast, monospecific binding to GPG3 or 4-1BB by benchmarks or single building blocks was not able to activate T cells in this assay. These data demonstrate the ability of PRS-342 to bind both targets simultaneously, which is necessary for clustering of 4-1BB. PRS-342 was also evaluated for activity in a HepG2 mouse xenograft engrafted with human PBMCs with results supporting its differentiated MoA compared to relevant benchmark controls. Conclusion: PRS-342 was designed to elicit 4-1BB costimulatory effects in a tumor-localized manner. Here we report potent T-cell activation that is strictly dependent on the presence of GPC3-positive tumor cells. Collectively our in vitro and in vivo data support the continued development of PRS-342. Citation Format: Birgit Bossenmaier, Corinna Schlosser, Rachida Siham Bel Aiba, Christian Barthels, Benjamin Weiche, Timo Eichner, Michelle Yegres, Shane A. Olwill. Costimulatory T-cell engagement by PRS-342, a GPC3/4-1BB bispecific molecule, leads to activation of T-cells and tumor growth inhibition in a HCC humanized mouse model [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3268.

A Novel Consistent Quality Driven for JEM Based Distributed Video Coding

Distributed video coding (DVC) is an attractive and promising solution for low complexity constrained video applications, such as wireless sensor networks or wireless surveillance systems. In DVC, visual quality consistency is one of the most important issues to evaluate the performance of a DVC codec. However, it is the fact that the quality of the decoded frames that is achieved in most recent DVC codecs is not consistent and it is varied with high quality fluctuation. In this paper, we propose a novel DVC solution named Joint exploration model based DVC (JEM-DVC) to solve the problem, which can provide not only higher performance as compared to the traditional DVC solutions, but also an effective scheme for the quality consistency control. We first employ several advanced techniques that are provided in the Joint exploration model (JEM) of the future video coding standard (FVC) in the proposed JEM-DVC solution to effectively improve the performance of JEM-DVC codec. Subsequently, for consistent quality control, we propose two novel methods, named key frame quantization (KF-Q) and Wyner-Zip frame quantization (WZF-Q), which determine the optimal values of the quantization parameter (QP) and quantization matrix (QM) applied for the key and WZ frame coding, respectively. The optimal values of QP and QM are adaptively controlled and updated for every key and WZ frames to guarantee the consistent video quality for the proposed codec unlike the conventional approaches. Our proposed JEM-DVC is the first DVC codec in literature that employs the JEM coding technique, and then all of the results that are presented in this paper are new. The experimental results show that the proposed JEM-DVC significantly outperforms the relevant DVC benchmarks, notably the DISCOVER DVC and the recent H.265/HEVC based DVC, in terms of both Peak signal-to-noise ratio (PSNR) performance and consistent visual quality.

Performance evaluation of destriping algorithms: a test procedure based on simulated images

ABSTRACTStriping noise is intrinsic to the process of image acquisition via scanning systems. Although it can be mitigated by radiometric calibration, the residual noise can jeopardize the quantitative analysis of the images and the extraction of physical parameters. This paper presents a new approach for evaluating destriping algorithms by means of a synergic use of: (1) distortion measurements, (2) quality indexes and relevant benchmark values calculated from simulated data, and (3) evaluation of effects on parameters extraction. The proposed procedure is here used to evaluate the performance of three destriping algorithms: Destriping Algorithm based on Statistics and Filtering (DASF), ENVI® algorithm and Wavelet-Fourier Filtering (WFF), on two different scenarios of hyperspectral push-broom data. The study pointed out the need of an approach based on the analysis of several aspects in order to identify the best performing algorithm. In addition, the results showed a good performance of both DASF and WFF that preserved the original radiometry without introducing spectral distortion.

Two-Level Approach for No-Reference Consumer Video Quality Assessment.

Smartphones and other consumer devices capable of capturing video content and sharing it on social media in nearly real time are widely available at a reasonable cost. Thus, there is a growing need for no-reference video quality assessment (NR-VQA) of consumer produced video content, typically characterized by capture impairments that are qualitatively different from those observed in professionally produced video content. To date, most of the NR-VQA models in prior art have been developed for assessing coding and transmission distortions, rather than capture impairments. In addition, the most accurate NR-VQA methods known in prior art are often computationally complex, and therefore impractical for many real life applications. In this paper, we propose a new approach for learning-based video quality assessment, based on the idea of computing features in two levels so that low complexity features are computed for the full sequence first, and then high complexity features are extracted from a subset of representative video frames, selected by using the low complexity features. We have compared the proposed method against several relevant benchmark methods using three recently published annotated public video quality databases, and our results show that the proposed method can predict subjective video quality more accurately than the benchmark methods. The best performing prior method achieves nearly similar accuracy, but at substantially higher computational cost.

Employee profiling via aspect-based sentiment and network for insider threats detection

Historically, the harm caused by insiders has proven to be one of the greatest concerns for any organization. As such, it has received considerable attention from both the industrial and research communities. Existing works mainly focused on modeling the employees’ normal biometric behavior (e.g., human to device interaction pattern) to detect anomalous behavior which corresponds to the insider activity. However, it is unattainable to stop the insider at the final moment when the malicious act is being carried out. In this paper, we propose a novel framework which performs employee profiling based on aspect-based sentiments and social network information and examine its applicability for early detection of potential insider threats. On the contrary to the traditional sentiment analysis, aspect-based sentiment analysis provides more fine-grained information on the employee. Our framework employs a combination of deep learning techniques such as Gated Recurrent Unit (GRU) and skipgram to build temporal sentiment profiles for the employees. It then performs anomaly detection on the profiles and ranks the employees based on their respective anomaly score. Due to the absence of relevant benchmark dataset, we augmented the publicly available real-world Enron email corpus with an insider threat scenario to evaluate our framework. The evaluation results demonstrate that the augmentation is indeed reflected in the augmented employee’s anomaly ranking (i.e., from normal to abnormal) and her close associates are indeed placed closely to her when the profiles are visualized in the 2D space. The profiles obtained from our framework can also be used to complement any existing expert and intelligent systems with additional capabilities in handling textual information such as, integration with profiles obtained from biometric behavior to form a more comprehensive threat detection system.

Estimating Code Biases for Criticality Safety Applications with Few Relevant Benchmarks

Criticality safety analyses rely on the availability of relevant benchmark experiments to determine justifiable margins of subcriticality. When a target application lacks neutronically similar benchmark experiments, validation studies must provide justification to the regulator that the impact of modeling and simulation limitations is well understood for the application and often must provide additional subcritical margin to ensure safe operating conditions. This study estimated the computational bias in the critical eigenvalue for several criticality safety applications supported by only a few relevant benchmark experiments. The accuracy of the following three methods for predicting computational biases was evaluated: the Upper Subcritical Limit STATisticS (USLSTATS) trending analysis method; the Whisper nonparametric method; and TSURFER, which is based on the generalized linear least-squares technique. These methods were also applied to estimate computational biases and recommended upper subcriticality limits for several critical experiments with known biases and for several cases from a blind benchmark study. The methods are evaluated based on both the accuracy of their predicted computation bias and upper subcriticality limit estimates, as well as on the consistency of the methods’ estimates, as the model parameters, covariance data libraries, and set of available benchmark data were varied. Data assimilation methods typically have not been used for criticality safety licensing activities, and this study explores a methodology to address concerns regarding the reliability of such methods in criticality safety bias prediction applications.

Active Space Selection Based on Natural Orbital Occupation Numbers from n-Electron Valence Perturbation Theory.

Efficient and robust approximations to the full configuration interaction (full-CI) method such as the density matrix renormalization group (DMRG) and the full-CI quantum Monte Carlo (FCIQMC) algorithm allow for multiconfigurational self-consistent field (MC-SCF) calculations of molecules with many strongly correlated electrons. This opens up the possibility to treat large and complex systems that were previously untractable, but at the same time it calls for an efficient and reliable active space selection as the choice of how many electrons and orbitals enter the active space is critical for any multireference calculation. In this work we propose an Active Space Selection based on 1st order perturbation theory (ASS1ST) that follows a "bottom-up" strategy and utilizes a set of quasi-natural orbitals together with sensible thresholds for their occupation numbers. The required quasi-natural orbitals are generated by diagonalizing the virtual and internal part of the one-electron reduced density matrix that is obtained from strongly contracted n-electron valence perturbation theory (SC-NEVPT) on top of a minimal active space calculation. Self-consistent results can be obtained when the proposed selection scheme is applied iteratively. Initial applications on four chemically relevant benchmark systems indicate the capabilities of ASS1ST. Eventually, the strengths and limitations are critically discussed.

A Human Rights-Based Approach to Foreign Agricultural Investment in Uganda

The use of human rights approaches in the context of development-related activities appears to be the most appropriate means to observe respect for and the protection of people's rights as states are required to adhere to human rights norms and standards. This article argues for the adoption of a rights-based approach within the framework of foreign agricultural investment activities in Uganda in order to ensure respect for, the protection of and the fulfilment of the fundamental human rights of local communities. It provides an exposition of the procedural and substantive rights which are contained in the relevant international and regional legal instruments and which need to be taken into account in such a rights-based approach. It also distils the relevant benchmarks to be used by the government of Uganda as the standards to be achieved in order to ensure the observance and protection of people's rights, especially with regard to the negotiation and implementation of foreign agricultural investment land deals in Uganda. It then compares the Ugandan legal framework against the distilled benchmarks to ascertain if and to what extent the legal framework conforms to these requirements with regard to regulating foreign agricultural investment activities. Based on the distilled minimum human rights requirements and the obligation they bestow on states, the article concludes that in order for the government of Uganda to properly and effectively respect, protect and fulfil local communities' human rights, it is crucially important that it should consider these requirements and fulfil them during the regulation and implementation of foreign agricultural investment land deals in the country.

859 Evaluation of Kojic Acid and Hydroquinone on Melanoderm™ skin model as controls in screening architecture for skin lightening actives and formulas

MelanoDerm™, supplied by MatTek Corporation, Ashland, MA is a commonly used in vitro model to test a formula or ingredient’s impact on melanin and therefore their ability to even or lighten skin tone. MelanoDerm™ is a 3D constructed, live, manufactured skin culture that is widely used as a screening tool in the cosmetic industry to study melanogenesis and pigmentation. In this study, we evaluated well-known cosmetic compounds i.e. hydroquinone and kojic acid causing effects on melanin and melanogenesis in vivo, as relevant benchmark positive controls for in vitro screening architecture of other actives alone or in combination. Hydroquinone was tested in water solution as a single ingredient or as finished goods formulation at the concentration of 2% and Kojic Acid was investigated in water solutions at two different concentrations (1% and 2%) for their ability to reduce existing and new pigment formation on MelanoDerm™ (MEB-300B) tissues after 14 days of topical application. Cell viability was assessed with MTT assay, color measurements (L*, a*, b* values) with chromameter, and in situ histology of the selected tissues was performed with Hematoxylin and Eosin staining. Hydroquinone evaluation in this model was somewhat challenging due to its known cytotoxicity geared specifically towards melanocytes, while kojic acid was safe at the concentration of 1%. Generated data indicate that both actives may be used as positive controls and thus serve as a validated model in screening architecture of the new perspective skin lightening/brightening actives and represent a translation platform between vitro-to-vivo studies.

Plasma shape control assessment for JT-60SA using the CREATE tools

This paper deals with the plasma shape control problem in JT-60SA. An assessment of the plasma shape control performance is presented, aimed at the definition of an optimal set of gaps to be controlled. Indeed, JT-60SA represents a relevant benchmark to further validate this control approach given the high beta regimes that are envisaged during its operation. Moreover, such regimes represent a challenge from the plasma magnetic control perspective.The control approach considered for the assessment is based on the eXtreme Shape Controller (XSC), since such an approach permits to control, in a least mean square sense, a number of shape descriptors that is larger than the number of poloidal field coils. Considering that the design of the XSC is model-based, the CREATE linear model for the plasma-circuit response has been used for the design.In the presented analysis, the capability of tracking different plasma shapes, as well as the one of rejecting disturbances has been considered. The result of this analysis suggests that a set of about 20 gaps equally spaced along the plasma boundary permits to control the shape with a steady-state root-mean square error of less than 1 cm during the flattop of JT-60SA Scenario 2, in the presence of a set of relevant disturbances.

Overall survival, costs, and healthcare resource use by line of therapy in Medicare patients with newly diagnosed metastatic urothelial carcinoma

Aims: Medicare patients with metastatic or surgically unresectable urothelial carcinoma (mUC) often receive platinum-based chemotherapy as first line of therapy (LOT), but invariably progress, requiring additional LOTs and healthcare resource use (HCRU). To better understand the evolving mUC treatment landscape, the economic burden of chemotherapy-based mUC treatments among US Medicare patients was estimated.Methods: Newly diagnosed Medicare patients with mUC were identified from the Surveillance, Epidemiology, and End Results (SEER)-Medicare database. Patients were followed from diagnosis to death, disenrollment, or end of study to characterize LOTs (first [LOT1], second [LOT2], and third or greater [LOT3+]). Kaplan-Meier methods were used to estimate overall survival (OS) by LOT. HCRU and mean costs were reported over the follow-up period, LOT duration, and maximum LOT received.Results: Among 1,873 eligible patients with mUC (median age = 77 years; median follow-up = 7.5 months), 1,035 (55%) received no chemotherapy. Among chemotherapy-treated patients, 61% had LOT1 only, 25% had LOT1 and LOT2 only, and 14% had LOT3+. Median OS was 8.1 months, range was 4.3 (untreated) to 29.8 (LOT3+) months. HCRU frequency increased with additional LOTs. Mean cumulative per-patient cost was $82,912 for all patients, increasing with additional LOTs (untreated = $57,207; LOT1 = $99,213; LOT2 = $125,190; LOT3+ = $163,884). Mean per patient per month cost was $18,827 for all patients, decreasing with increasing number of LOTs received (untreated = $27,211; LOT1 = $9,601; LOT2 = $7,325; LOT3+ = $6,017).Limitations: Potential for treatment misclassification when using the algorithm defining LOTs and non-generalizability of results to younger patients.Conclusions: Over 50% of Medicare patients with mUC received no chemotherapy. Among chemotherapy-treated patients, most received only one LOT. Additional LOTs led to higher mean costs and HCRU, but as patients were followed longer, monthly costs decreased. As treatments evolve to include immuno-oncology agents, these findings provide a clinically relevant economic benchmark for mUC treatment across different traditional LOTs.

Benchmarking economic infrastructure efficiency: How does the Latin America and Caribbean region compare?

The Latin America and Caribbean (LAC) region has a sizable infrastructure gap. Physical assets, maintenance, and service provision are inadequate and below average for a region at its level of development. The most promising way to close the service gap is to increase efficiency. Relying on data on more than 80 countries for 2000 and 2016, this paper innovates by 1) developing a single economic infrastructure index to compare countries; 2) presenting an efficiency analysis that assesses whether LAC countries have room for improvement in the provision of the quantity and quality of economic infrastructure; 3) proposing a novel peer-identification conceptual framework to identify which countries are the relevant benchmarks for the region; and 4) providing evidence on how sound governance, regulation, rule of law, and the lack of corruption are related to infrastructure efficiency at the country level.