Cost-efficient Strategy Research Articles

Enzymatic formulation strategies unlock highly-efficient saccharification of distinct pretreated corncobs

Optimization of the composition of enzyme cocktail is an effective way to improve the hydrolytic efficiency and reduce the cost during enzymatic hydrolysis of lignocellulose. Herein, the optimal enzymes ratios of enzyme cocktails for efficient hydrolysis of corncobs with distinct pretreatments were quantitatively formulated. As the importance of pretreatment type on xylan extraction, the optimized cellulase/hemicellulase ratios for NaClO2, H2SO4 and steam explosion treated corncob were 1:1.5, 1:0.15 and 1:0.75, respectively. Meanwhile, different requirements for types of cellulases are also determined: endoglucanase and cellobiohydrolase were key enzymes in the hydrolysis of NaClO2 and H2SO4 treated corncobs, respectively, while the synergy of three kinds of cellulases was preferred for steam-exploded corncob. Furthermore, based on the optimized cellulase/hemicellulase ratios, cellulases proportions for hydrolyzing the corncobs pretreated with distinctive methods were determined. Notably, by the enzymatic formulation strategy, 100% yields of glucose and xylose were obtained simultaneously from NaClO2 treated corncob, which was up to 70.1% and 80.1% at high solid loading (20%), respectively. Without detoxification of hydrolysate, high isopropanol yield of 0.45 g/g (of dry matter) was achieved. Hence, this study demonstrated a low cost and high efficient conversion strategy for prospective high-value utilization of lignocellulose.

Essential Medicines for Dental Caries: Cost-Effectiveness of ART and SDF

Abstract Background Untreated tooth decay (caries) is the most common global health condition and one of the largest preventable disease burdens for society. It concerns both children and adults, particularly in low resource settings whereout of pocket expenditures for oral care often cause catastrophic health expenditures. The 2021 WHO Oral Health Resolution emphasized the relevance of developing so-called “Best Buys” for oral health. The purpose of this study was to identify the cost-effectiveness of Atraumatic Restorative Treatment (ART) and Silver Diamine Fluoride (SDF) as potential treatments to reduce the caries burden worldwide. Methods Leaning on WHO CHOICE methodology, evidence scoping and an expert consensus were facilitated to extract model input parameters which were then fed into cost-effectiveness-analyses (CEA) for ART and SDF. The cost-effectiveness of the interventions was expressed as Cost per DALY averted. Results The evidence scoping revealed relevant, information on the effectiveness and costs of ART and SDF. The CEA identified both ART and SDF to be potentially cost-efficient treatment strategies in settings with limited resources. SDF was found to provide a cost-efficient treatment alternative in settings where the comparably larger (human) resource requirements for ART cannot be met. Conclusions The findings suggest that ART and SDF represent potentially cost-efficient strategies to reduce the caries burden in settings with limited resources. While ART has previously been proposed as part of WHO’s essential package of oral care, SDF could provide a comparably inexpensive treatment alternative. Key messages • Untreated tooth decay (caries) is the most common global health condition and one of the largest preventable disease burdens for society. • The CEA identified both ART and SDF to be potentially cost-efficient treatment strategies in settings with limited resources.

Towards Better Oral Health Prevention: the Value for Money of Fluoride Toothpaste

Abstract Background Although largely preventable, tooth decay (dental caries) is among the most common health conditions worldwide and contributes to substantial dental treatment expenditures. While Fluoride Toothpaste (FT) is considered an essential strategy for oral health prevention, its market price has been shown to vary substantially across various settings. Against this background, the present study aimed to develop a decision analytical model to evaluate the cost-effectiveness of FT in various settings. Methods Leaning on WHO CHOICE methodology, evidence scoping and an expert consensus were facilitated to extract model input parameters which were then fed into cost-effectiveness-analyses (CEA) for FT. The cost-effectiveness of the interventions was expressed as cost per Disability-Adjusted Life Year (DALY) averted. Results The CEA identified a high likelihood for FT to be a cost-efficient treatment strategy in settings with comparably low market prices for FT. FT was less likely to be a cost-efficient treatment strategy in settings with comparably high market prices for FT. Conclusions The developed decision analytical model is suitable to inform policymakers about the extent to which FT represents good value-for-money under different market prices. Key messages • Fluoride toothpaste can provide high value for money as an oral health preventive strategy. • Policymakers need to ensure the affordability of fluoride toothpaste in order to harvest relevant efficiency gains.

Evaluating new evacuation systems related to human behaviour using a situational awareness approach – A study of the implementation of evacuation elevators in an underground facility

Elevator evacuation is associated with several safety benefits and can be a cost-efficient evacuation strategy in many buildings or facilities. Despite the advantages, elevator evacuation is not yet a common strategy in the built environment. In this paper, a design strategy that allows the designer to consider information needs of evacuees when designing the information and guidance measures for evacuation elevators is presented. The strategy is based on human behaviour theories and the Theory of Affordance. The use of the design strategy is also illustrated for a case study, i.e., an underground metro station with evacuation elevators. This case study identifies several important measures, which accommodate the information needs of the evacuees, e.g., (1) voice alarm containing information that elevators can be used for evacuation, and (2) a system in the elevator lobby indicating that the elevators are operational. The paper also highlights future research areas where the current level of knowledge related to elevator evacuation needs to increase.

A Dynamic Game Framework for Rational and Persistent Robot Deception With an Application to Deceptive Pursuit-Evasion

This article studies rational and persistent deception among intelligent robots to enhance security and operational efficiency. We present an <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$N$ </tex-math></inline-formula> -player <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula> -stage game with an asymmetric information structure where each robot’s private information is modeled as a random variable or its type. The deception is persistent as each robot’s private type remains unknown to other robots for all stages. The deception is rational as robots aim to achieve their deception goals at minimum cost. Each robot forms a dynamic belief of others’ types based on intrinsic or extrinsic information. Perfect Bayesian Nash equilibrium (PBNE) is a natural solution concept for dynamic games of incomplete information. Due to its requirements of sequential rationality and belief consistency, PBNE provides a reliable prediction of players’ actions, beliefs, and expected cumulative costs over the entire <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula> stages. The contribution of this work is fourfold. First, we identify the PBNE computation as a nonlinear stochastic control problem and characterize the structures of players’ actions and costs under PBNE. We further derive a set of extended Riccati equations with cognitive coupling under the linear-quadratic (LQ) setting and extrinsic belief dynamics. Second, we develop a receding-horizon algorithm with low temporal and spatial complexity to compute PBNE under intrinsic belief dynamics. Third, we investigate a deceptive pursuit-evasion game as a case study and use numerical experiments to corroborate the results. Finally, we propose metrics, such as deceivability, reachability, and the price of deception (PoD), to evaluate the strategy design and the system performance under deception. Note to Practitioners—Recent advances in automation and adaptive control in multi-agent systems enable robots to use deception to accomplish their objectives. Deception involves intentional information hiding to compromise the security and operational efficiency of the robotic systems. This work proposes a dynamic game framework to quantify the impact of deception, understand the robots’ behaviors and intentions, and design cost-efficient strategies under the deception that persists over stages. Existing research studies on robot deception have relied on experiments while this work aims to lay a theoretical foundation of deception with quantitative metrics, such as deceivability and the PoD. The proposed model has wide applications, including cooperative robots, pursuit and evasion, and human–robot teaming. The pursuit-evasion games are used as case studies to show how the deceiver can amplify the deception by belief manipulation and how the deceived robots can reduce the negative impact of deception by enhanced maneuverability and Bayesian learning. The future work would focus on designing cooperative deception among swarm robotics and robotic systems that are robust to or further benefit from the deception.

A comprehensive computational approach for the identification of structure-based potential pharmacological candidates as selective AKR1B1 and AKR1B10 inhibitors: repurposing of purine alkaloids for the treatment of cancer

Significant metabolic pathways have been linked to AKR1B1 and AKR1B10. These enzymes are crucial biological targets in the therapy of colon cancer. In the past several decades, drug repurposing has gained appeal as a time and cost-efficient strategy for providing new indications for existing drugs. The structural properties of the plant-based alkaloidal drugs theobromine and theophylline were examined using density functional theory (DFT) computations, where the B3LYP/SVP method was used to quantify the dipole moment, polarizability, and optimization energy. Optimized structures obtained through DFT studies were docked inside the active pocket of target proteins to evaluate their inhibitory potential. Moreover, molecular dynamic simulation provides significant insight into a dynamic view of molecular interactions. The findings of current revealed theobromine and theophylline as strong AKR1B1 and AKR1B10 inhibitors, respectively. In addition, the anti-cancer potential of theophylline and theobromine was validated by targeting various tumor proteins, i.e. NF-κB, cellular tumor antigen P53 and caspase-3 using a molecular docking approach. Theobromine was found to be strongly interacted with NF-κB and caspase-3, whereas theophylline potentially inhibited cellular tumor antigen P53. In addition, the ADMET characteristics of theobromine and theophylline were identified, confirming their drug-like capabilities. These results should open the way for further experimental validation and structure-based drug design/repurposing of AKR1B1/AKR1B10 inhibitors for the treatment of colon cancer and associated malignancies. Communicated by Ramaswamy H. Sarma

Integrated freight car routing and train scheduling

Rail freight transportation is involved with highly complex logistical processes and requires a lot of resources such as locomotives or wagons. Thus, cost-efficient strategies for routing freight cars in a cargo network are of great interest for railway companies. When it comes to single wagon load traffic, trains are usually formed by collecting individual freight cars into batches at shunting yards, in order to transport them jointly to their destinations. The problem of finding optimal routes and schedules for single freight cars is typically solved in two steps: (i) determining routes for the freight cars in the railway network by solving the Single-freight car routing problem (SCRP), and (ii) deciding on time schedules for trains by solving the freight train scheduling problem (FTSP). Since train departure and arrival times, as well as freight car routes are highly interdependent, one aims to solve the SCRP and the FTSP simultaneously. For smooth and convenient operational processes many railway companies apply the concept of a routing matrix. This matrix defines unique routes between all shunting yards that are used for all shipments. In this work, we present an integrated mathematical model based on time discretization, that jointly solves the SCRP and FTSP and enforces the routing matrix concept. To the best of our knowledge, this is the first work that combines all three aspects. The approach is tailored for Rail Cargo Austria’s (RCA) needs, incorporating train capacities, yard capacities, and restrictions regarding travel times. We perform an extensive computational study based on real-world data provided by RCA. Besides the performance we analyze the utilization of trains, waiting times of freight cars, and the number of shunting processes.

In situ synthesis of highly dispersed VO2(M) nanoparticles on glass surface for energy efficient smart windows

Thermochromic VO2-based smart windows are considered as a highly promising building envelope to reduce building energy consumption. However, the inherent unsatisfactory optical performance hindered its practical applications and nanocomposite films are testified to be the most promising strategy addressing this issue, while uniformly dispersing nanoparticles is often a challenge. Herein, a facile in situ method was proposed to directly fabricate highly dispersed VO2 nanoparticles (HD-VN) on a glass surface from the VOC2O4·xH2O aqueous solution to achieve the high-optical performance VO2 film (HD-VN film). The forming mechanism of HD-VN was fully elucidated and HD-VN was generated via the sintering process from the irregular VO2 particles derived from the decomposition of polyvinyl pyrrolidone (PVP). The HD-VN film showed excellent luminous transmittance (Tlum) of 72.5% and solar energy modulation efficiency (ΔTsol) of 10.1%, the former was attributed to the reduced refractive index which led to a reduced reflectance of HD-VN film, and the latter was ascribed to the localized surface plasmon resonance (LSPR) behavior of the HD-VN. The simple and cost-efficient synthesis strategy would promote the application of VO2 film in energy-efficient glazing, and also shed light on the structures’ design applied to the field of optics, catalysts, and sensors.

Tailored defect-rich cerium metal organic frameworks for efficient fluoride removal from wastewater

The excess fluoride in water is a fatal threat towards ecological security and human health. Herein, a novel strategy for efficient removal of fluoride is proposed based on defective cerium-based metal organic frameworks (CeMOFs), which are prepared through a simple and cost-efficient water-compensation strategy at room temperature. By virtue of the tailored ligand exchange between the OH–/H2O coordinated at Ce defect sites and dissociative fluoride ions, CeMOFs exhibit superior affinity towards fluoride ion over other anions under wide pH range, as well as ultrahigh halotolerancy (5 mol L-1 of nitrate). Intriguingly, rich defects on CeMOFs give rise to a maximum adsorption capacity of up to 202.8 mg g−1 for fluoride and excellent reusability is also substantiated. Satisfactory fluoride removal results are reached when treating an assortment of actual environmental water samples, demonstrating the practical applicability of CeMOFs especially for complex high-fluoride matrixes. This work offers a reliable approach to fabricating functional materials with fine-tuned structures and surface properties for environmental application.

Cost-Efficient Workflow Scheduling Algorithm for Applications With Deadline Constraint on Heterogeneous Clouds

In recent years, more and more large-scale data processing and computing workflow applications run on heterogeneous clouds. Such cloud applications with precedence-constrained tasks are usually deadline-constrained and their scheduling is an essential problem faced by cloud providers. Moreover, minimizing the workflow execution cost based on cloud billing periods is also a complex and challenging problem for clouds. In realizing this, we first model the workflow applications as I/O Data-aware Directed Acyclic Graph (DDAG), according to clouds with global storage systems. Then, we mathematically state this deadline-constrained workflow scheduling problem with the goal of minimum execution financial cost. We also prove that the time complexity of this problem is NP-hard by deducing from a multidimensional multiple-choice knapsack problem. Third, we propose a heuristic cost-efficient task scheduling strategy called CETSS, which includes workflow DDAG model building, task subdeadline initialization, greedy workflow scheduling algorithm, and task adjusting method. The greedy workflow scheduling algorithm mainly consists of dynamical task renting billing period sharing method and unscheduled task subdeadline relax technique. We perform rigorous simulations on some synthetic randomly generated applications and real-world applications, such as Epigenomics, CyberShake, and LIGO. The experimental results clearly demonstrate that our proposed heuristic CETSS outperforms the existing algorithms and can effective save the total workflow execution cost. In particular, CETSS is very suitable for large workflow applications.

Shadow prices and abatement cost of soil erosion in Shaanxi Province, China: Convex expectile regression approach

Since 1999, the Sloping Land Conversion Program (SLCP) in China, regarded as one of the largest payments for ecosystem services (PES) programs worldwide, was carried out for the alleviation of soil erosion. The high economic cost of the SLCP has attracted considerable attention to its ecological and economic effects during the past decades. However, reliable evidence about abatement alternatives and abatement costs of soil erosion remains scant. Using panel data of 83 counties observed in Shaanxi Province from 2000 to 2015, the marginal abatement cost (MAC) of soil erosion is accurately evaluated by a directional distance function with convex expectile regression. Besides, we explore how external variables affect shadow prices and the choice of abatement solutions. Our main findings are the following: First, this novel data-driven approach could alleviate the bias from the interference of noise and inefficiency; second, incorporating the investment of the SLCP into the production process allows to find the most cost-efficient abatement solution from both the input side (i.e., increasing the SLCP investment) and the output side (i.e., downscaling the primary industry or downscaling the non-primary industries); third, the temporal-spatial distribution of abatement costs shows that the abatement potential from the SLCP has shrunk gradually, which implies that there might be cost-inefficiency in some counties if the SLCP continues; finally, we recognize that natural conditions, like wind speed and vegetation quality, could influence the input-side abatement cost and output-side abatement cost differently. These results have profound policy implications, asking for more cost-efficient abatement strategies in the future.

Genomic selection for improvement of growth traits in triangle sail mussel (Hyriopsis cumingii)

The triangle sail mussel, Hyriopsis cumingii, is the most important aquaculture species for freshwater pearl production in China. However, one major problem of freshwater pearl mussel industry is the low profit despite high pearl yield, and the focus of current research has now switched from yield to the improvement of pearl quality. It is essential to enhance the quality of pearls by improving the growth performance of mussels and, to this end, genomic selection (GS) has been proved as a useful method for selective breeding. In the present study, 764 mussels (496 for reference population, 268 for selection candidates) were genotyped by sequencing (GBS) and a total of 97,090 single nucleotide polymorphisms (SNPs) were identified. Based on genome-wide SNPs, the heritability was estimated to be moderate to high for the following five growth traits: shell length, shell height, shell width, shell weight, and body weight (0.36 ± 0.11 to 0.51 ± 0.10). Then, the effects of five GS models (i.e., GBLUP, BayesA, BayesB, BayesCπ, and BayesLASSO) and different SNP numbers (selected using three SNP screening strategies) on the predictive ability (PA) of the genomic estimated breeding values (GEBVs) were compared. The GBLUP model containing 10,000 SNPs selected by GWAS strategy was established and was used to calculate GEBVs in selection candidates. The individuals with high GEBVs were then selected as broodstock for the fast-growth strain (FS), and the rest for control strains (CS). At last, encouraging results were detected that the FS performed significantly better than CS in terms of growth, with different traits increasing by 5.74–28.77% and 11.93%–54.58% at the WY and CM sites, respectively. These results may assist in the future large-scale commercial application of GS in H. cumingii and provide a cost-efficient GS strategy for other aquaculture species as well.

Nonlinear optimal control of a mean-field model of neural population dynamics.

We apply the framework of nonlinear optimal control to a biophysically realistic neural mass model, which consists of two mutually coupled populations of deterministic excitatory and inhibitory neurons. External control signals are realized by time-dependent inputs to both populations. Optimality is defined by two alternative cost functions that trade the deviation of the controlled variable from its target value against the “strength” of the control, which is quantified by the integrated 1- and 2-norms of the control signal. We focus on a bistable region in state space where one low- (“down state”) and one high-activity (“up state”) stable fixed points coexist. With methods of nonlinear optimal control, we search for the most cost-efficient control function to switch between both activity states. For a broad range of parameters, we find that cost-efficient control strategies consist of a pulse of finite duration to push the state variables only minimally into the basin of attraction of the target state. This strategy only breaks down once we impose time constraints that force the system to switch on a time scale comparable to the duration of the control pulse. Penalizing control strength via the integrated 1-norm (2-norm) yields control inputs targeting one or both populations. However, whether control inputs to the excitatory or the inhibitory population dominate, depends on the location in state space relative to the bifurcation lines. Our study highlights the applicability of nonlinear optimal control to understand neuronal processing under constraints better.

Hierarchical architecture: A novel, facile and cost-efficient strategy to boost electrochemical performance of Li-O2 battery cathodes

The sluggish performance of cathodes, which is eagerly awaiting optimal design, is a major impediment to the practical implementation of lithium-oxygen batteries (LOBs). We present the meticulous design and synthesis of hierarchical porous graphene foam (HPGF) cathodes with various pore size architectures. A novel and facile method was proposed to prepare highly porous Ni foam from which graphene foam with a surface area increase of more than ten times was derived. To enable the transportation of Li+ and O2 species through graphene sheet thickness, Ni(NO3)2 was used as an ignition source to generate adjustable holes in graphene layers, resulting in a tri-continuous passage of electrons, ions, and oxygen. As a result, superior electrochemical performances such as high capacity, good rate capability, and cycling stability (5 percent degradation in 2500 h) were achieved. A pouch-type battery demonstrated good flexibility and a broad application perspective by operating directly in ambient air.

A Combination of MALDI-TOF MS Proteomics and Species-Unique Biomarkers' Discovery for Rapid Screening of Brucellosis.

Brucellosis is considered to be a zoonotic infection with a predominant incidence in most parts of Iran that may even simply involve diagnostic laboratory personnel. In the present study, we apply matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry (MALDI-TOF MS) for rapid and reliable discrimination of Brucella abortus and Brucella melitensis, based on proteomic mass patterns from chemically treated whole-cell analyses. Biomarkers of the low molecular weight proteome in the MALDI-TOF MS spectra were assigned to conserved ribosomal and structural protein families that were found in genome assemblies of B. abortus and B. melitensis in the NCBI database. Significant protein mass signals successfully mapped to ribosomal proteins and structural proteins, such as integration host factor subunit alpha, cold-shock proteins, HU family DNA-binding protein, ATP synthase subunit C, and GNAT family N-acetyltransferase, with specific biomarker peaks that have been identified for each virulent and vaccine strain. Web-accessible bioinformatics algorithms, with a robust data analysis workflow, followed by ribosomal and structural protein mapping, significantly enhanced the reliable assignment of key proteins and accurate identification of Brucella species. Furthermore, clinical samples were analyzed to confirm the most dominant protein biomarker candidates and their relevance for the identifications of B. melitensis and B. abortus. With proper optimization, we envision that the presented MALDI-TOF MS proteomics analyses, coupled with special usage of bioinformatics, could be used as a cost-efficient strategy for the diagnostics of brucellosis and introduce a reliable identification protocol for species of dangerous bacteria.

Assessing the impact of free-roaming dog population management through systems modelling

Free-roaming dogs can present significant challenges to public health, wildlife conservation, and livestock production. Free-roaming dogs may also experience poor health and welfare. Dog population management is widely conducted to mitigate these issues. To ensure efficient use of resources, it is critical that effective, cost-efficient, and high-welfare strategies are identified. The dog population comprises distinct subpopulations characterised by their restriction status and level of ownership, but the assessment of dog population management often fails to consider the impact of the interaction between subpopulations on management success. We present a system dynamics model that incorporates an interactive and dynamic system of dog subpopulations. Methods incorporating both fertility control and responsible ownership interventions (leading to a reduction in abandonment and roaming of owned dogs, and an increase in shelter adoptions) have the greatest potential to reduce free-roaming dog population sizes over longer periods of time, whilst being cost-effective and improving overall welfare. We suggest that future management should be applied at high levels of coverage and should target all sources of population increase, such as abandonment, births, and owners of free-roaming dogs, to ensure effective and cost-efficient reduction in free-roaming dog numbers.

The costs and benefits of emergent surgical workflow for acute appendicitis in children

BackgroundControversy exists regarding how operative timing affects patient safety and resource utilization for acute appendicitis. Over 3 years, our institution trialed efforts to optimize appendectomy workflow. Our aim is to describe the ramifications of expediting appendectomy and implementing standardized protocols relative to historic controls. MethodsPatient records at a freestanding children's hospital were reviewed from synchronized 6-month periods from 2019 to 2021. During Year 1 (historic), no standardized workflows existed. In Year 2 (expedited), appendicitis management was protocoled using a clinical quality improvement bundle, which included performing appendectomies within two hours of diagnosis. In Year 3 (QI), operative timing was relaxed to the same calendar day while all prior QI initiatives continued. Descriptive statistics were performed, using hospital length of stay (LOS) as the primary outcome. Results298 patients underwent appendectomy for acute appendicitis. The median expedited workflow LOS was 15.3 hours shorter (p = 0.003) than historic controls; however, this was sustained despite relaxation of surgical urgency in the QI workflow. No differences in perforation rates were observed. During the expedited workflow, OR overtime staffing expense increased by $90,000 with no significant change in hospital costs. In multivariate regression, perforation was the only variable associated with LOS. ConclusionHospital LOS can be shortened by expediting appendectomy. However, in our institution this did not decrease hospital costs and was furthermore balanced by higher personnel expenses. A sustained decrease in LOS after relaxing operative urgency standards implies that concurrent QI initiatives represent a more effective and cost-efficient strategy to decrease hospital resource utilization. Level of evidenceLevel III

Effect of pooling family oral fluids on the probability of PRRSV RNA detection by RT-rtPCR

Family oral fluids (FOFs) are an aggregate sample type shown to be a cost-efficient and convenient option for determining the porcine reproductive and respiratory syndrome virus (PRRSV) status of weaning age pigs. This study investigates the effect of pooling PRRSV-positive FOF samples with PRRSV-negative FOF samples at different levels (1/3, 1/5, 1/10, 1/20) on the probability of PRRSV RNA detection by reverse-transcription real-time polymerase chain reaction (RT-rtPCR). Mathematical models were built to assess how much the probability of RT-rtPCR PRRSV detection changed with increasing proportion of PRRSV-positive samples present within pools and how partially sampling a farrowing room influenced the probability of RT-rtPCR detection of PRRSV RNA in pooled samples at different prevalence scenarios. A general example of a guideline for FOF-based sampling under different prevalence scenarios to detect PRRSV RNA by RT-rtPCR with at least 95 % certainty is presented. At the sample level, the probability of detecting PRRSV RNA by RT-rtPCR decreased from 100 % to 87 %, 68 %, and 26 % when diluting up to 1/20 for PRRSV positive FOF having an initial Cycle threshold (Ct) below 34, between 34 and 36, or above 36, respectively. When PRRSV prevalence is near-zero (1 or 2 litters positive out of 56), the most cost-efficient farrowing room sampling strategy to detect PRRSV RNA with at least 95 % certainty was pooling FOF samples up to 1/10; at higher prevalence (≥ 3 of 56 litters positive), the most cost-efficient strategy was submitting samples in pools of 20. Subsampling a farrowing room for FOF pools was also demonstrated to be a valuable cost-saving strategy. Overall, based on the conditions of this study, pooling FOFs up to 1/20 is a valid option in situations of cost constraint and regardless of pooling level chosen, capturing as many litters as possible improves the probability of PRRSV detection.

The value of recycling for low-carbon energy systems - A case study of Germany's energy transition

To achieve climate neutrality, synergies between circular economy and reduction of greenhouse gas emissions must be strengthened. Previously unused emission reduction potentials of resource efficiency are to be exploited. Since all potentially possible emission reduction measures are linked by interactions, the evaluation of a single measure in terms of cost efficiency, effectiveness, and compliance with climate protection targets is very complex and requires a model-based analysis that takes the entire energy system into account.This work advances an energy system model for Germany so that through comprehensive modeling of industrial processes and implementation of recycling options, the impact of recycling measures in the context of national greenhouse gas mitigation strategies can be analyzed.The scenario evaluation shows that different recycling strategies have large effects on the German energy system. Without recycling energy demand in 2050 will increase by more than 300 TWh and cost of transformation will rise by 85% compared to a reference scenario, with today's recycling rates. On the other hand, if maximum recycling rates can be achieved, costs of transformation can be reduced by 26% until 2050. Recycling is an essential and cost-efficient greenhouse gas reduction strategy for future low-carbon energy system designs.

Economic Analysis of Exclusionary EGFR Test Versus Up-Front NGS for Lung Adenocarcinoma in High EGFR Mutation Prevalence Areas.

This study sought to determine whether exclusionary EGFR mutation testing followed by next-generation sequencing (NGS) is a cost-efficient and timely strategy in areas with high prevalence rates of EGFR mutation. We developed a decision tree model to compare exclusionary EGFR testing followed by NGS and up-front NGS. Patients entered the model upon diagnosis of metastatic lung adenocarcinoma. Gene alterations with FDA-approved targeted therapies included EGFR, ALK, ROS1, BRAF, RET, MET, NTRK, and KRAS. Model outcomes were testing-related costs; time-to-test results; monetary loss, taking both costs and time into consideration; and percentage of patients who could be treated by FDA-approved therapies. Stacked 1-way and 3-way sensitivity analyses were performed. Exclusionary EGFR testing incurred testing-related costs of US $1,387 per patient, a savings of US $1,091 compared with the costs of up-front NGS. The time-to-test results for exclusionary EGFR testing and up-front NGS were 13.0 and 13.6 days, respectively. Exclusionary EGFR testing resulted in a savings of US $1,116 in terms of net monetary loss, without a reduction of patients identified with FDA-approved therapies. The EGFR mutation rate and NGS cost had the greatest impact on minimizing monetary loss. Given that the tissue-based NGS turnaround time was shortened to 7 days, up-front NGS testing would become the best strategy if its price could be reduced to US $568 in Taiwan. In areas with high prevalence rates of EGFR mutation, exclusionary EGFR testing followed by NGS, rather than up-front NGS, is currently a cost-efficient strategy for metastatic lung adenocarcinoma.