Single Assignment Research Articles

Effects of step-by-step line balancing in apparel assembly line

The mixed work assignment technique was applied to the modular production concept to solve the apparel assembly line balancing problem. Specifically, an algorithm was implemented to generate workstations by first classifying tasks into modules through an analysis of the manufacturing process and assigning grouped tasks in the single task–multiple workers and multiple tasks–single worker assignment methods. Then, worker assignment was sequentially performed considering the skill level of the worker. A simulation of producing 100 men’s shirts was performed. Owing to line balancing, the total production time was considerably lower than that reported in previous studies. The enhanced performance was attributable to the fact that unlike previous studies that limited the apparel assembly line balancing problem to worker assignment, line balancing was performed through both task and worker assignment in this study. The results demonstrated that task assignment must be considered in the design stage in the apparel assembly line balancing problem.

Classification of user queries according to a hierarchical medical procedure encoding system using an ensemble classifier.

The Swiss classification of surgical interventions (CHOP) has to be used in daily practice by physicians to classify clinical procedures. Its purpose is to encode the delivered healthcare services for the sake of quality assurance and billing. For encoding a procedure, a code of a maximal of 6-digits has to be selected from the classification system, which is currently realized by a rule-based system composed of encoding experts and a manual search in the CHOP catalog. In this paper, we will investigate the possibility of automatic CHOP code generation based on a short query to enable automatic support of manual classification. The wide and deep hierarchy of CHOP and the differences between text used in queries and catalog descriptions are two apparent obstacles for training and deploying a learning-based algorithm. Because of these challenges, there is a need for an appropriate classification approach. We evaluate different strategies (multi-class non-terminal and per-node classifications) with different configurations so that a flexible modular solution with high accuracy and efficiency can be provided. The results clearly show that the per-node binary classification outperforms the non-terminal multi-class classification with an F1-micro measure between 92.6 and 94%. The hierarchical prediction based on per-node binary classifiers achieved a high exact match by the single code assignment on the 5-fold cross-validation. In conclusion, the hierarchical context from the CHOP encoding can be employed by both classifier training and representation learning. The hierarchical features have all shown improvement in the classification performances under different configurations, respectively: the stacked autoencoder and training examples aggregation using true path rules as well as the unified vocabulary space have largely increased the utility of hierarchical features. Additionally, the threshold adaption through Bayesian aggregation has largely increased the vertical reachability of the per node classification. All the trainable nodes can be triggered after the threshold adaption, while the F1 measures at code levels 3-6 have been increased from 6 to 89% after the threshold adaption.

Evaluation of Students Performance during Distance form of Education

Abstract During the COVID-19 pandemic, it was necessary to convert teaching to a distance method. The distance form of education had the advantage of student´s choice of place and time for study. However, students had to study using self-access. This could have a negative impact on study results. On the other hand, they could retain their academic results due to the extension of the time needed to grasp the subject matter. This article deals with the analysis of the performance of students regarding the study grades and the time required to complete a single assignment in the course of Mechanical Testing and Defectoscopy of Materials.

Optimization of Platoon Formation Center Location for Truck Platooning in Turkey

In Road Transportation, truck transportation is commonly being categorized into Less Than Truckload (LTL), Partial Truckload and Full Truckload (TL). The standard LTL transportation is carried out by means of consolidated freight at optimized depots of designation, in the form of single or multiple assignment. Nowadays, freight transportation industry is now facing a serious problem of scarce labor force and environmental concerns. One solution for that is truck platooning. Truck Platooning is a grouping of freight vehicles into connected vehicle convoys using electronic coupling as an application in automated driving technology with the aim of saving fuel, reducing travel costs, and improving infrastructure efficiency. Platoon planning is required to obtain the best results of platooning. Therefore, the objective of this study is to find the optimal locations of PFC in Turkey for (de)formation truck platoons by using discrete mathematical optimization.

A Comprehensive Evaluation Method for the Service Status of Groins in Waterways Based on an AHP-Improved CRITIC Combination Weighting Optimization Model

A comprehensive evaluation model that combines an analytical hierarchy process (AHP) method and the improved version of the Criteria Importance Through Inter-criteria Correlation (CRITIC) method is proposed to solve integrated assessment problems related to the service status of groins in waterways. In view of the influencing factors and functional characteristics of damaged groins for waterway regulation, a waterway groin service status (WGSS) evaluation index system with a hierarchical structure was constructed using target-criteria elements. Additionally, based on the multi-attribute characteristics of the indicators, standards for rating and assigning values to elemental indicators were developed. Considering that traditional empowerment methods are rather one-sided and limited, an AHP-improved CRITIC method combination assigning optimization model was established based on the least squares principle, and the optimal combination weights were solved by the Lagrange multiplier method. The reliability and applicability of the model were tested by successfully applying the evaluation model to the comprehensive evaluation of the service status of spur dikes in the upper reaches of the Yangtze River. The results showed that the combined weights that were calculated by the AHP and the improved CRITIC optimization model were able to reflect both subjective and objective information, which makes up for the shortcomings of a single assignment method, and the weights assigned to the service status evaluation indexes for groins were reasonable. The comprehensive evaluation method to determine the service status of groins proposed in this paper was more accurate than the traditional evaluation method with subjective assignment and provided a scientific basis for decision making to maintain the sustainability of groin function.

Sea lion attacking‐based deer hunting optimization algorithm for dynamic nurse scheduling in health care sector contribution of hybrid algorithm in cloud

SummaryThe main intent of this article is to frame the dynamic NSP in the cloud using a multi‐objective optimization strategy. The benefit of the dynamic scheduling over static scheduling is that the scheduling will be done week by week based on the available number of nurses. For solving this problem, several constraints like single assignment per day, under‐staffing, shift type successions, consecutive assignments, consecutive resting days, and complete week‐end are considered. With reference to these constraints, a minimized objective function is used based on the nurse demand in week by week. Each constraint is having some conditions for solving this problem. These schedules are stored in cloud for efficient decision making regarding NSP and it helps in assisting the future scheduling purposes. It also offers secure storage when compared to the other storage devices. As a novelty, this article tries to employ the hybrid meta‐heuristic algorithm called sea lion attacking‐based deer hunting optimization algorithm. Hybrid optimization algorithms have been reported to be promising for certain search problems with a higher convergence rate. Hence, the developed hybrid optimization algorithm hardly helps to generate a feasible and near‐optimal schedule at the end of the horizon.

The effect of batched patient-physician assignment on patient length of stay in the emergency department.

ObjectivesQueuing theory suggests that signing up for multiple patients at once (batching) can negatively affect patients’ length of stay (LOS). At academic centers, resident assignment adds a second layer to this effect. In this study, we measured the rate of batched patient assignment by resident physicians, examined the effect on patient in‐room LOS, and surveyed residents on underlying drivers and perceptions of batching.MethodsThis was a retrospective study of discharged patients from August 1, 2020 to October 27, 2020, supplemented with survey data conducted at a large, urban, academic hospital with an emergency medicine training program in which residents self‐assign to patients. Time stamps were extracted from the electronic health record and a definition of batching was set based on findings of a published time and motion study.ResultsA total of 3794 patients were seen by 28 residents and ultimately discharged during the study period. Overall, residents batched 23.7% of patients, with a greater rate of batching associated with increasing resident seniority and during the first hour of resident shifts. In‐room LOS for batched assignment patients was 15.9 minutes longer than single assignment patients (P value < 0.01). Residents’ predictions of their rates of batching closely approximated actual rates; however, they underestimated the effect of batching on LOS.ConclusionsEmergency residents often batch patients during signup with negative consequences to LOS. Moreover, residents significantly underestimate this negative effect.

Clinical trials of stem cell-based therapies for pediatric diseases: a comprehensive analysis of trials registered on ClinicalTrials.gov and the ICTRP portal site

BackgroundResearch on clinical trials that employ stem cells to treat children’s diseases is limited. The clinical trial registry database provides a unique window to us to get known about clinical trial researches with different statuses. However, few studies aimed to perform a comprehensive and thorough analysis of those registered trials in the aforementioned field based on ClinicalTrials.gov and the ICTRP portal site.MethodsOur study covered the clinical researches about stem cell therapy enrolling subjects aged under 18 years old registered on ClinicalTrials.gov and WHO ICTRP before May 18, 2021. A cross-sectional study was implemented to comprehensively describe and analyze the included trials that met the criteria. Results were available on ClinicalTrials.gov, and publications related to the included trials were identified. All analyses were performed utilizing the SPSS 25.0 software.ResultsEventually, 202 clinical trials were included and evaluated. The participant number of trials tended to be small; 71.3% were enrolled < 50. And 93.5% of the subjects were without gender restrictions. Till May 2020, 112 trials had been preliminary completed, of which only 39 trials had published papers or uploaded results. Most (73.6%) of 186 interventional trials were in phase 1 and phase 2, where 131 (70.4%) trials were conducted without masking, and 26.3% trials were randomized; 55.4% trials were performed single group assignment. Of 16 observational trials, case-only/series took up 37.5%. Hematopoietic stem cells (37.1%) and mesenchymal stem cells (36.1%) were mostly employed, while umbilical cord blood (UCB)-derived cells (24.3%) and bone marrow (BM)-derived cells (20.8%) were the major sources.ConclusionsThis study provided an overall picture of utilizing stem cells for treatment and management of childhood diseases. Since clinical trials in this area are insufficient in quantity and quality, there is an urgent need of larger, better-designed trials. Increased investment in clinical research of stem cell treatment products should be carried out to achieve the transformation of results as soon as possible. Moreover, it is important to optimize the management of the registration platform and shorten the time it takes for research results to be published.

QIRO: A Static Single Assignment-based Quantum Program Representation for Optimization

We propose an IR for quantum computing that directly exposes quantum and classical data dependencies for the purpose of optimization. The Quantum Intermediate Representation for Optimization (QIRO) consists of two dialects, one input dialect and one that is specifically tailored to enable quantum-classical co-optimization. While the first employs a perhaps more intuitive memory-semantics (quantum operations act on qubits via side-effects), the latter uses value-semantics (operations consume and produce states) to integrate quantum dataflow in the IR’s Static Single Assignment (SSA) graph. Crucially, this allows for a host of optimizations that leverage dataflow analysis. We discuss how to map existing quantum programming languages to the input dialect and how to lower the resulting IR to the optimization dialect. We present a prototype implementation based on MLIR that includes several quantum-specific optimization passes. Our benchmarks show that significant improvements in resource requirements are possible even through static optimization. In contrast to circuit optimization at run time, this is achieved while incurring only a small constant overhead in compilation time, making this a compelling approach for quantum program optimization at application scale.

Ex ante budget impact analysis (BIA) of PD-1 inhibitor toripalimab plus gemcitabine-cisplatin (T+GC) versus a simulated pembrolizumab regimen in first line (1L) treatment of recurrent or metastatic nasopharyngeal cancer (rmNPC).

e18024 Background: Interim results of the JUPITER-02 randomized double-blind phase 3 trial demonstrated a PFS benefit for T+GC (11.7 m) vs placebo+GC (8m) in 1L treatment of rmNPC. The KEYNOTE-028 nonrandomized (single group assignment) phase 1b trial showed the potential benefit of pembrolizumab in previously treated NPC. The trials were not comparable in population and design, precluding a direct comparison. We performed an ex ante BIA comparing T+GC to a simulated pembrolizumab+GC (sP+GC) regimen under an assumed equivalence in efficacy and safety. Methods: An ex ante budget impact model (budget holder perspective; accrual approach) compared a treatment mix “without” T+GC (only sP+GC) to one “with” T+GC in an annual incident US population of 1200 patients (year 1), a 5y time horizon, and a fixed 50/50 market share split. Population adjustments were for discontinuation, death, and progression with corresponding medication adjustments to estimate fully treated patient equivalents. Cost inputs included: drugs (average sales price), drug administration, and grade 3/4 adverse event (AE) management. Three scenarios were modeled: toripalimab priced at 70%, 80% and 90% of pembrolizumab. Results: In the “without” scenario, the 5y costs of sP+GC treatment totaled $2,062,509,042 and the 5y cost of managing AEs $210,382,926, for a total of $2,272,891,967. In the “with” scenario at 50% market share, the corresponding 5y costs for sP+GC declined to $1,031,254,521 for treatment and $105,191,463 in AE costs, for a total of $1,136,445,984. The corresponding costs for T+GC priced at 70%, 80%, 90% of pembrolizumab were $746,834,887, $841,641,432 and $936,447,976 (treatment) and $105,191,463 (AE management), for 5y gross budget impacts of $852,026,350, $946,832,895 and $1,041,639,439. Net savings “with” T+GC were $49,331,430, $32,887,620 and $16,443,810 in 2022 rising to $64,974,264, $43,316,176 and $21,658,088 by 2026. The total 5y net budget impact of adding T+GC to the treatment mix totaled $284,419,634, $189,613,089 and $94,806,545 in savings. Conclusions: Citing the findings from the JUPITER-02 trial of T+GC, regimens including a PD-1 inhibitor, gemcitabine and cisplatin are now a NCCN category 2A recommendation for 1L treatment of rmNPC. This ex ante BIA demonstrates the substantial savings potential of toripalimab (at a discounted cost compared to pembrolizumab) in rmNPC. With forthcoming final JUPITER-02 data showing a PFS benefit of 21.4m, the value of an available, lower-priced and efficacious anti-PD1 agent is highly significant to patients, providers and payers in terms of both clinical efficacy and cost efficiency. Emerging data suggest that toripalimab may be effective in more frequently occurring tumor types and the savings from such expanded access are likely to be multifold.

Effects of Resonance Tube Voice Therapy on Parkinson's Disease: Clinical Trial

To verify the effect of resonance tube voice therapy on the vocal aspects of patients with Parkinson's Disease (PD). Intra-subject comparative controlled clinical trial with a single group assignment. Fourteen individuals with PD (10 men, mean age 66.1 years; four women, mean age 73.75 years) received eight 45-minute sessions of voice therapy, twice a week for 4 weeks. The therapy consisted of semi-occluded vocal tract exercises - phonation method in a resonance tube (glass, 27 cm x 9 mm) in water. Tube depth in water ranged from 2 cm to 9 cm, as the difficulty in carrying out the exercises increased (usual pitch, high pitch, low pitch, ascending/descending glissandos), followed by sentence production. The assessments were made three times: at baseline (Time0), after 30 days without intervention (Time1), and 1 day after eight intervention sessions (Time2). The following aspects were assessed: vocal intensity; acoustic parameters (Smoothed Cepstral Peak Prominence - CPPs, alpha ratio, and L1-L0 difference); auditory-perceptual analysis of the overall degree of vocal quality deviation; voice symptoms (Voice Symptom Scale protocol - VoiSS) and voice-related quality of life (Voice-Related Quality of Life Protocol - V-RQOL). The results were compared at the three times of assessment Time0/Time1/Time2 using one-way repeated measures ANOVA test and Tukey test (5% significance). intervention significantly increased: vocal intensity, L1-L0 value of vowel /a/ and counting, CPP value in counting, and decreased: the overall degree of vocal quality deviation in 78% of participants, the total score of VoiSS protocol, the limitation, and emotional subscales. In addition, the intervention increased the score of all the domains of V-RQOL protocol - physical, socio-emotional, and total. Resonance tube phonation in voice therapy was effective in increasing vocal intensity and long-term acoustic parameters, the improved overall degree of vocal quality, reducing voice symptoms, and increasing voice-related quality of life in individuals with PD.

Imperative or Functional Control Flow Handling

Modern data analysis tasks often involve control flow statements, such as the iterations in PageRank and K-means. To achieve scalability, developers usually implement these tasks in distributed dataflow systems, such as Spark and Flink. Designers of such systems have to choose between providing imperative or functional control flow constructs to users. Imperative constructs are easier to use, but functional constructs are easier to compile to an efficient dataflow job. We propose Mitos, a system where control flow is both easy to use and efficient. Mitos relies on an intermediate representation based on the static single assignment form. This allows us to abstract away from specific control flow constructs and treat any imperative control flow uniformly both when building the dataflow job and when coordinating the distributed execution.

Risk Assessment of Building Foundation Pit Construction Based on Fuzzy Hierarchical Comprehensive Evaluation Method

The safety of foundation pit construction is gaining widespread attention. In order to reduce the risks of foundation pit construction and avoid the safety problems brought by the pits, it is necessary to study the risks of foundation pit construction. This paper takes the actual construction of a building as the background. Firstly, the possible main risks of foundation pit construction were identified and summarized, and then, the evaluation index system was formed. Secondly, the risk levels of various types of foundation pit risks were derived through analytic hierarchy process (AHP). In the expert scoring session of the Delphi method, the influences of both the degree of risk consequences and the probability of occurrence are combined. The risk value of the risk event is obtained in combination, which overcomes the bias problem of the traditional single assignment. Finally, an affiliation matrix was established to judge the affiliation of risk indicators to the risk level. The comprehensive risk evaluation level of this foundation pit project construction was assessed as level II. It is the degree of general risk.

An approach for evaluating the effects of dietary fiber polysaccharides on the human gut microbiome and plasma proteome

Increases in snack consumption associated with Westernized lifestyles provide an opportunity to introduce nutritious foods into poor diets. We describe two 10-wk-long open label, single group assignment human studies that measured the effects of two snack prototypes containing fiber preparations from two sustainable and scalable sources; the byproducts remaining after isolation of protein from the endosperm of peas and the vesicular pulp remaining after processing oranges for the manufacture of juices. The normal diets of study participants were supplemented with either a pea- or orange fiber-containing snack. We focused our analysis on quantifying the abundances of genes encoding carbohydrate-active enzymes (CAZymes) (glycoside hydrolases and polysaccharide lyases) in the fecal microbiome, mass spectrometric measurements of glycan structures (glycosidic linkages) in feces, plus aptamer-based assessment of levels of 1,300 plasma proteins reflecting a broad range of physiological functions. Computational methods for feature selection identified treatment-discriminatory changes in CAZyme genes that correlated with alterations in levels of fiber-associated glycosidic linkages; these changes in turn correlated with levels of plasma proteins representing diverse biological functions, including transforming growth factor type β/bone morphogenetic protein-mediated fibrosis, vascular endothelial growth factor-related angiogenesis, P38/MAPK-associated immune cell signaling, and obesity-associated hormonal regulators. The approach used represents a way to connect changes in consumer microbiomes produced by specific fiber types with host responses in the context of varying background diets.

Providing effective feedback with soaring class sizes: It’s still possible

“Do more with less”, is a message that many of us are likely used to hearing, whether explicitly, or implicitly. We consolidate resources, streamline processes etc, in the name of economy. Sometimes streamlining grading and feedback means grading with minimal or no feedback, and/or eliminating intensive writing assignments that take a lot of time to grade. However, in upper‐level, discipline‐specific classes, automated grading and feedback do not always do what we need it to do for formative assessment. Writing assignments are a critical component of students demonstrating learning outcomes, and thoughtful, specific feedback accompanying the grading, is just as important. But how we do this in a class of 20 students just isn’t scalable. Does that mean the feedback component is lost? Not necessarily. My hypothesis is that the feedback that students require on higher Bloom’s level assignments can be consolidated by topic/question, and effectively delivered to large classes via video feedback.ResultsIn studying the errors made in different types of questions/topics of a particular assignment over multiple semesters, it appeared that between 3‐5 specific errors accounted for more than 95% of the errors in each question on the assignment. When the protocol was implemented, grading was completed expeditiously, without any direct written feedback other than number grades. Subsequently, a feedback video was released to the class discussing the assignment and going through each question/topic. Common errors, and how to avoid them, were covered in the video feedback. In a class of 68 students, 186 video plays were recorded for a single remediation assignment. And although some of the engagement durations were highly variable, that is the engagement model that was suggested to students by encouraging them to only watch those parts of the video feedback they felt was necessary.ConclusionsIn concert with other types of feedback including peer feedback, and immediate in‐class feedback, video feedback for common misconceptions/errors provides an efficient way to engage students in formative learning. Despite this, it is clear that alternative (or traditional) access to feedback must be provided for those students who fall outside these so‐called normal thresholds. However, streamlining the feedback process for &gt;90% of students will allow more time to be spent with non‐typical learners, or other students who require alternate resources. In this way, it is hoped that learners from marginalized communities and neuroatypical learners, who may benefit from increased guidance, can still get what they need, while the greater majority have opportunities to refine and tailor the feedback they most need.

Clinical Trials of Liposomes in Children's Anticancer Therapy: A Comprehensive Analysis of Trials Registered on ClinicalTrials.gov.

ObjectiveClinical trials have become essential for driving the development of medicine. However, little is known about the current status of clinical trials on liposomes in children’s anticancer therapy (LCAT). This study aimed to synthesize current finding from clinical trials of LCAT in ClinicalTrials.gov.MethodsA cross-sectional descriptive study of clinical trials on LCAT was conducted, using studies registered on ClinicalTrials.gov through December 30, 2021.ResultsA total of 74 eligible trials were identified, accounting for 4.8% (74/1552) of all trials on liposomes for cancer therapy. Among these trials, 70 (94.6%) were interventional trials, and the remaining 4 (5.4%) were observational trials. Of the 70 interventional trials, 63 (90.0%) were for treatment, 48.6% were involving unlabeled allocations, 30.0% were randomized, 52.9% were single group assignment, 71.4% were without masking, 28.6% were Phase 3 trials, 30.0% were Phase 1 trials, and 24.3% were Phase 2 trials. Furthermore, 17 liposomal drugs for 123 types of cancer were investigated in the interventional trials, and these were mainly focused on organic chemicals (43/70, 61.4%). Of these cancers, the highest proportion was leukemia (15.4%), followed by lymphoma (9.8%) and ovarian cancer (8.9%).ConclusionHigh quality, adequately powered, masked, appropriately sized, and randomized clinical trials represent the critical priorities for conducting a high-quality clinical trial. However, most of these trials for LCAT were non-randomized, single group assignment, and non-blinded interventional trials of small scale, with various eligibility criteria and outcome measures. Our analysis highlights the need for improvement in the completeness of study designs curated on clinicalTrials.gov. We urge for decision-makers to avoid adopting entrenched positions about the study design of cancer clinical trials to avoid this problem. As such, tackling the problematic challenges related to cancer and designing efficient trials for cancer requires developing and applying new approaches and multiple strategies.

Audit as You Go: A Smart Contract-Based Outsourced Data Integrity Auditing Scheme for Multiauditor Scenarios with One Person, One Vote

The data outsourcing services provided by cloud storage have greatly reduced the headache of data management for users, but the issue of remote data integrity poses further security concerns and computing burdens. The introduction of a third-party auditor (TPA) frees data owners from the auditing burden and alleviates disputes over the audit results between data owners and cloud storage providers. However, malicious cloud servers may collude with TPAs to deceive users for financial profits. Hiring multiple auditors in a single audit assignment appears to be a method to address the above problem, but the ensuing voting issues need to be further explored. In this paper, we proposed a smart contract-based outsourced data integrity auditing scheme for multiauditor scenarios. Unlike some existing schemes using reputation like factors as their voting weights, auditors in our scheme vote equally and audit as they go, without any maintenance. This mechanism not only frees auditors from trivia not related to the auditing but also avoids the drawbacks of centralization associated with over-high voting weights. The challenge used to check the integrity of the outsourced data is jointly generated by each involved auditor. Any collusion would be detected as long as there exists more than one honest auditor in the audit. We implement and deploy the scheme as Ethereum smart contracts. With the help of blockchain, the entire auditing process is public and transparent. Both the generated data and the obtained results are persisted with immutability, which ensures the traceability of all historical audits. The comprehensive theoretical and experimental analyses demonstrate that our scheme meets the claimed targets with high efficiency and low gas costs.

Weaving Synchronous Reactions into the Fabric of SSA-form Compilers

We investigate the programming of reactive systems combining closed-loop control with performance-intensive components such as Machine Learning (ML). Reactive control systems are often safety-critical and associated with real-time execution requirements, a domain of predilection for synchronous programming languages. Extending the high levels of assurance found in reactive control systems to computationally intensive code remains an open issue. We tackle it by unifying concepts and algorithms from synchronous languages with abstractions commonly found in general-purpose and ML compilers. This unification across embedded and high-performance computing enables a high degree of reuse of compiler abstractions and code. We first recall commonalities between dataflow synchronous languages and the static single assignment (SSA) form of general-purpose/ML compilers. We highlight the key mechanisms of synchronous languages that SSA does not cover—denotational concepts such as synchronizing computations with an external time base, cyclic and reactive I/O, as well as the operational notions of relaxing control flow dominance and the modeling of absent values. We discover that initialization-related static analyses and code generation aspects can be fully decoupled from other aspects of synchronous semantics such as memory management and causality analysis, the latter being covered by existing dominance-based algorithms of SSA-form compilers. We show how the SSA form can be seamlessly extended to enable all SSA-based transformations and optimizations on reactive programs with synchronous concurrency. We derive a compilation flow suitable for both high-performance and reactive aspects of a control application, by embedding the Lustre dataflow synchronous language into the SSA-based MLIR/LLVM compiler infrastructure. This allows the modeling of signal processing and deep neural network inference in the (closed) loop of feedback-directed control systems. With only minor efforts leveraging the MLIR infrastructure, the generated code matches or outperforms state-of-the-art synchronous language compilers on computationally intensive ML applications.

Dynamic Multiagent Assignment Via Discrete Optimal Transport

We propose an optimal solution to a dynamic assignment problem to assign a group of moving agents to another group of moving targets. Our approach leverages connections to the theory of discrete optimal transport to convert the problem into a tractable linear program. We simultaneously solve for the optimal assignment and the control of the individual agents. As a result, we can account for dynamics and capabilities of a heterogeneous set of agents and targets. In contrast to existing assignment schemes, this approach considers cost metrics informed by the underlying agent dynamics and capabilities rather than just distance. We show that the minimizer of the dynamic assignment problem is equivalent to the minimizer of the associated Monge problem from optimal transport. We prove that the resulting approach only requires a single assignment computation over the operating lifetime, rather than periodic reassignment. Furthermore, we demonstrate cost benefits that increase as the network size increases, achieving almost 50&#x0025; cost reduction compared with distance-based metrics. We demonstrate our approach through simulation on several multiagent and multitarget tracking problems.

Growth kinetics and progression rates of cystic renal masses on active surveillance.

298 Background: The Bosniak classification is used to risk stratify the probability of cancer among cystic renal masses using CT or MRI and assigns a class ranging from I-IV. Bosniak III and IV masses have the highest probabilities of cancer and are treated similarly to solid renal masses per 2021 American Urological Association (AUA) Guidelines. The purpose of this study was to determine the growth kinetics and progression rates of unresected Bosniak III and IV masses defined by Bosniak Classification, version 2019 (v2019). Methods: In this retrospective and IRB-approved study, CT and MRI images of 107 cystic renal masses from 100 patients (34 women, 66 men; range 28-92 years) with unresected Bosniak III and IV masses from 2005-2021 were reviewed. Cystic renal masses on baseline imaging were assigned a category based on v2019 by two abdominal radiologists, with discrepancies resolved by a third, such that each mass had a single Bosniak class assignment. Mass dimensions over serial imaging were measured using orthogonal planes by a radiologist with 3D laboratory training. Linear growth rate (mm/year) and volumetric growth rate (mL/year) were calculated. “Progression” off of active surveillance was defined as any of the following: linear growth rate &gt; 5 mm a year, volume doubling rate ≤ 1 year, or increased stage based on TNM. Results: 107 cystic renal masses were categorized as 51 Bosniak III and 56 Bosniak IV masses on baseline exam. Median follow-up time was 406 days. Linear growth rate for Bosniak III masses was 0.4 ± 4.3 mm/year while linear growth rate for Bosniak IV masses was 2.3 ± 4.9 mm/year (p = 0.036; Student’s t-test). 12/51 (24%) Bosniak III masses progressed based on above definitions while 26/56 (46%) Bosniak IV masses progressed (p = 0.016; Fisher’s exact test). 13 masses upgraded from a Bosniak III to IV during surveillance, but category upgrades were not associated with progression (p = 0.131; Fisher’s exact test). 2 patients developed lung metastases; both masses were Bosniak IV and were biopsy proven papillary and clear cell renal cell carcinomas. Conclusions: Although currently treated similarly by AUA Guidelines, unresected Bosniak IV masses grow faster than Bosniak III masses and are more likely to progress off of active surveillance.