Trade-off Research Articles

Energy-efficient instruction compression with programmable dictionaries

AbstractTo improve the energy efficiency of computation, accelerators trade off performance and energy consumption for flexibility. Fixed-function accelerators reach high energy efficiency, but are inflexible. Adding programmability via an instruction set architecture (ISA) incurs an energy consumption overhead, as instructions are fetched and decoded. To reduce it, hardware-controlled instruction caches and software-controlled components, such as loop buffers and (programmable) dictionaries improve the energy efficiency of instruction streams in embedded processors. Reducing the instruction overhead with code compression is well established and dictionary compression has been an effective approach due to its simplicity. Compared to static dictionaries, adding programmability improves the effectiveness. However, run-time-programmable dictionary compression and its effect on energy consumption has not been thoroughly studied. We describe a scheme to target energy efficiency by using fine-grained programmable dictionaries in embedded compute devices. Guided by compile-time analysis, the dictionary contents are changed during execution. On CHStone and Embench suites, our method reduces energy consumption on average by 11.4% and 3.8% with negligible run-time overhead. The addition of a loop buffer further reduces the energy consumption by 19.8% and 4.5% in the two suites. Our results indicate that programmable dictionary compression allows further energy reductions over an already highly tuned instruction stream.

A Predictive Model for Digital Currencies Prices using Geometric Brownian Motion Stochastic Differential Equation: A Case Study of the Bitcoin

In this research work, we developed a predictive model for digital currency prices, involving daily closing price as a function of time. We used the Geometric Brownian motion stochastic differential equation which was solved using inbuild functions in Microsoft Excel. While we used the Bitcoin as our case study, our model was able to predict the daily closing prices of Bitcoin to a reasonable degree of accuracy. We equally observe that the time dependent Geometric Brownian motion stochastic differential equation cannot give digital currency traders and investors a clue on when to trade off their digital assets. Thus, it become very risky using our model to make well informed trading decisions. We therefore, recommend that for minimum risk, trades and investors in digital currencies should consider a combination of other signal tools to take more informed and less risky trading decisions.

Enhancing financial risk prediction with symbolic classifiers: addressing class imbalance and the accuracy–interpretability trade–off

Enhancing financial risk prediction with symbolic classifiers: addressing class imbalance and the accuracy–interpretability trade–off

Trade-Off Between Growth Regimes in Chlorella vulgaris: Impact on Carotenoid Production

With the increasing awareness of socio-environmental issues, a global trend has emerged emphasizing the valorization of natural ingredients that promote health and well-being within sustainable production systems, such as microalgae-based carotenoids. Currently, little is understood about the correlation between biomass productivity and carotenoid content, which is a fundamental parameter for facilitating the immediate expansion of microalgae bioprocesses and ensuring the availability and industrial viability of these compounds. In this context, this study aims to investigate the carotenoid profile of Chlorella vulgaris through growth curve experiments conducted under photoautotrophic and heterotrophic regimes. Additionally, a trade-off analysis was performed for the production of carotenoids from microalgae. Carotenoids were quantified using high-performance liquid chromatography coupled with diode array and mass spectrometry detectors (HPLC-PDA-MS/MS). The performance of kinetic phases and energy demands across growth regimes was assessed to provide insights into production trade-offs. The results indicated that a total of 22 different carotenoids were identified in all the extracts. The all-trans-lutein and all-trans-β-carotene were the majority compounds. The total carotenoid content of Chlorella vulgaris revealed significant differences in the kinetic phases of carotenoid production, indicating that carotenoid volumetric production is only viable if the cultures are conducted until the log and stationary phases, based on the function of the biomass volumetric production (weight.volume−1). Therefore, the best trade-off for the process was to provide photoautotrophic growth until the exponential phase (log). Under this condition, the maximum carotenoid and lutein content was 2921.70 µg.L−1, reaching a maximum cell biomass of 1.46 g.L−1. From an environmental/economic point of view, the energy demand was 7.74 kWh.L−1. Finally, the scientific advances achieved in this study provide a holistic view of the influence of the main cultivation methods on the production of microalgae carotenoids, suggesting a viable initial direction for different industrial applications.

Weighting for progressivity? An analysis of implicit tradeoffs associated with weighted student funding in Tennessee

We study the progressivity of school district funding under Tennessee's weighted student funding formula. We propose a simple definition of progressivity based on the difference in exposure to district per-pupil funding between poor and non-poor students. The realized progressivity of district funding in Tennessee is much smaller—only about 17 percent as large—as the formula weights imply directly. The attenuation is driven by the mixing of poor and non-poor students within districts. We further show the components of the Tennessee formula not explicitly tied to student poverty are only modestly progressive.

Preferences for pre-exposure prophylaxis delivery among HIV-negative pregnant and breastfeeding women in Zambia: evidence from a discrete choice experiment.

Pregnant and breastfeeding women at substantial risk for HIV infection in sub-Saharan Africa can benefit from biomedical interventions such as pre-exposure prophylaxis (PrEP). We estimated the benefit that pregnant and breastfeeding women may derive from PrEP service delivery in order to guide PrEP roll-out in the target population in Zambia. Between September and December 2021, we conducted a discrete choice experiment (DCE) among a convenient sample of 389 pregnant and breastfeeding women not living with HIV in Lusaka, Zambia. Women aged 18 years or older, with a documented negative HIV result in their antenatal card responded to a structured questionnaire containing 12 choice sets on service delivery attributes of PrEP: waiting time at the facility, travel time to the facility dispensing PrEP, location for PrEP pick-up, health care provider attitude and PrEP supply at each refill. Mixed logit regression analysis was used to determine the participant's willingness to trade off one attribute of PrEP for the other at a 5% significance level. Willingness to wait (WTW) was used to determine the relative utility derived from each attribute against waiting time. Waiting time at the facility, travel time to the facility, health care provider attitude and amount of PrEP supply at each refill were important attributes of PrEP service delivery (all p < 0.01). Participants preferred less waiting time at the facility (β = -0.27, p < 0.01). Women demonstrated a strong preference for a 3-months' supply of PrEP (β = 1.69, p < 0.01). They were willing to wait for 5 h at the facility, walk for more than an hour to a facility dispensing PrEP, encounter a health care provider with a negative attitude in order to receive PrEP enough for 3 months. Patient-centered approaches can help to inform the design and implementation of PrEP services among pregnant and breastfeeding women. In this study, we found that a reduction in clinic visits-including through multi-month dispensing of PrEP-could improve uptake of services in antenatal and postnatal settings.

Pengaruh Working Capital Management terhadap Profitabilitas Perusahaan Manufaktur Indeks LQ-45

Every organization that is profit-oriented or non-profit, regardless of the size and nature of its business, requires a number of working capital. Working capital is the most important factor for maintaining liquidity, survival, solvency and profitability of the business. Working capital management is one of the most important areas when making comparisons between a company's liquidity and profitability, which involves a decision on the number of current assets and asset financing. The efficiency of working capital management is very important especially for manufacturing companies, where most of its assets consist of current assets. This directly affects the profitability and liquidity of the company. The trade off between liquidity and profitability is important because if working capital management is not given, companies tend to fail and face bankruptcy. The importance of efficient working capital management is undoubted. Because working capital provides strength for each economic and management unit which is considered to be one of the most important functions of corporate management. Therefore, given the importance of working capital management management this research was focused on evaluating the effect of working capital on profitability, in the LQ45 index manufacturing company for the 2003-2007 period. Key Words: working capital management, profitability, manufacturing LQ45Y index

Greenhouse gases emission trade-offs for benefits gain - An analysis from paddy rice and upland crops cultivation in Hau Giang province, Viet Nam

Agriculture activities require energy for operation and emit greenhouse gases (GHGs) into the atmosphere. However, agriculture provides essential nutrients with carbon sources through its main and by-products. This study used the life cycle assessment methodology to evaluate the carbon balance in agricultural systems of paddy rice (PR), corn, mung bean (MB), and black sesame (BS) in the summer-autumn growing season in the Vietnamese Mekong Delta. The results showed that PR and upland crops produced a net carbon source of 1,280.9–18,915 kg-C ha–1. Corn cultivation achieved the best value in carbon index analyses. To have one calorie from grain, selected crops must trade off 115.19–501.81 mg-CO2e. This study concluded that four selected crop cultivations achieved carbon analysis benefits. However, corn is a suitable recommendation for adapting to the agricultural conversion from PR farming to better upland crop cultivation.

Melatonin Mediates Trade–Off in Antioxidant Responses and Nitrogen Metabolism and Benefits the Growth of Fragrant Rice Seedlings Under Light–Nitrogen Levels

Melatonin Mediates Trade–Off in Antioxidant Responses and Nitrogen Metabolism and Benefits the Growth of Fragrant Rice Seedlings Under Light–Nitrogen Levels

Housing choice in an evolving remote work landscape

We estimate a joint model of housing choice along several dimensions to account for changing valuations of housing outcomes due to the COVID-19 pandemic. We consider housing outcomes including housing type, tenure type, the presence of a patio or yard, the number of bedrooms, neighborhood population density, median housing cost, accessibility of amenities, school quality, crime rate, and commute distance. Data used for this analysis were collected in October and November of 2021 from 24 metropolitan areas across the United States. A Generalized Heterogeneous Data Model (GHDM) is used to estimate these housing outcomes as a function of exogenous household sociodemographic characteristics and latent lifestyle propensities. The GHDM also captures jointness caused by unobserved factors, allowing for the estimation of accurate causal effects between outcomes. The results reveal that lifestyle preferences have significant impacts on housing outcomes. Specifically, individuals with a preference for teleworking are more likely to reside in single-family homes in highly populated areas, experience longer commute distances, and exhibit a higher sensitivity to the presence of amenities in their neighborhoods. Additionally, the analysis of tradeoffs between housing outcomes reveals the relative valuations of various housing outcomes. An increased commute distance is found to lead to an increase in single-family homes, reductions in density, and an increased crime rate. Choosing an apartment in a high-density neighborhood is found to lead to reductions in school quality and significant increases in crime rates. Implications of the results for land-use planning, travel demand analysis, and equity considerations are identified and discussed.

Sustainability assessment of additive manufacturing end-of-life material management

Additive manufacturing (AM) methods enable complex, customized, and on-demand production of many products from different material types across various industries. The growing demand for flexible and more sustainable manufacturing solutions places AM in the mix of processes considered for non-commodities. However, AM processes also present unintentional environmental releases in end-of-life (EoL) material management, compromising overall sustainability. Data availability to assess the sustainability of individual EoL material management from individual AM processes is limited. Even so, EoL materials generated across AM practices frequently overlap, supporting high-level assessment as an alternative approach. Therefore, a holistic AM EoL material management sustainability analysis was completed using a customized list of efficiency, environmental, energy, and economic indicators from the Gauging Reaction Effectiveness for the Environmental Sustainability of Chemistries with a multi-Objective Process Evaluator (GREENSCOPE) methodology. Subsequently, this assessment identified low material recycling rates and high energy costs in some EoL material management processes, such as incineration and recovery. Subsequently, a trade-off analysis was performed to determine process modification opportunities, including implementing recycling to reduce the amount of hazardous waste at the expense of additional energy and cost investment. The AM EoL-specific sustainability analysis serves as a resource to offer insights and empower policymakers and stakeholders to enhance pollution prevention strategies and optimize the existing EoL material management processes.

New Linked Employee-Employer Data Show Workforce Composition Is Associated With Health Insurance Offers Among Small Employers.

Decades of research shows that small firms are much less likely to offer health insurance than large firms, but less is known about differences among small employers. We examine this issue using the Medical Expenditure Panel Survey-Insurance Component with Administrative Records (MEPS-ICAR), a unique employer-employee linked data set that is constructed by matching the Medical Expenditure Panel Survey-Insurance Component (MEPS-IC) to Internal Revenue Service administrative records and the Decennial Census. Multivariate analyses show that among firms with fewer than 50 workers, the probability that workers receive an insurance offer is positively associated with higher median workforce incomes, and conditional offers of dependent coverage increase when the majority of workers are married or from a family with at least three members. This first application of the MEPS-ICAR highlights the significance of workforce characteristics in shaping small employer insurance benefits and the data's usefulness for expanding analyses of policy changes, wage-benefit tradeoffs, and health insurance benefits.

Constitutional design preferences: An experimental approach

Abstract A rich literature links the survival of national constitutions to their legitimacy among citizens. However, most studies examine constitutions as a bundle of rights and institutions, and few test the micro-foundations of constitutional preferences explicitly. This article examines how individuals evaluate both the content and flexibility of discrete constitutional elements using a conjoint experiment in Japan. Respondents were asked to rate twenty-six hypothetical constitutions that varied randomly in their enumeration of twelve rights and institutions. We find that citizens generally prefer constitutions that enumerate more provisions, with greater weight placed on human rights than political institutions. This result largely confirms theoretical expectations from earlier work on comparative constitutional design. In addition, political factors, such as partisanship, moderate preferences on issues that have long divided progressives and conservatives in Japan, such as constraints on the military and establishing national emergency provisions. By contrast, socioeconomic characteristics such as income, age, and education do not, suggesting broad demographic consensus on the merits of distinct provisions. Importantly, we further demonstrate that citizens do not trade off constitutional detail and flexibility, as suggested by existing research. Respondents who prefer the enumeration of more provisions do not necessarily want a lower amendment hurdle to facilitate adaptation to new circumstances. Preferences about constitutional flexibility appear to be based on strategic imperatives, notably the desire to cement preferred provisions and prevent changes by future majorities.

Trade-off Analysis in Strengthening the Criteria for Master Teacher Promotion

Effective master teachers constitute a valuable human resource playing a significant role not only as instructional leaders but also as educational researchers. However, the pressing demands of quality education alongside changing policies call for the need to ensure that these leaders meet competitive standards. Using the developmental-evaluative design, this study which is anchored on Criterion Theory, aims to enhance the existing criteria of the Department of Education (DepEd) in screening, selecting, and hiring Master Teacher applicants. Delphi technique and trade-offs analysis with ten expert respondents derived nine new and consensually evaluated measures (research training, research conference, publication, INSET/LAC, completed researches, best practices/innovations, qualifying examination, master's degree &amp; awards) comprising the "Enhanced Criteria for Master Teacher Promotion" at 70-point cut-off qualification. The discriminant function model constituted data from 60 Master Teachers in the Maasin City Division and confirmed discriminatory success at 91.78% variability during model validation of 15 Master Teachers. Thus, the new criteria demonstrate the potential to assure the DepEd of competent and quality instructional leaders that the country needs today. This study recommends the adoption of the enhanced criteria as a policy. However, further evaluation is necessary to strengthen its validity before its full implementation.

To be or not to be, when synthetic data meet clinical pharmacology: A focused study on pharmacogenetics.

The use of synthetic data in pharmacology research has gained significant attention due to its potential to address privacy concerns and promote open science. In this study, we implemented and compared three synthetic data generation methods, CT-GAN, TVAE, and a simplified implementation of Avatar, for a previously published pharmacogenetic dataset of 253 patients with one measurement per patient (non-longitudinal). The aim of this study was to evaluate the performance of these methods in terms of data utility and privacy trade off. Our results showed that CT-GAN and Avatar used with k = 10 (number of patients used to create the local model of generation) had the best overall performance in terms of data utility and privacy preservation. However, the TVAE method showed a relatively lower level of performance in these aspects. In terms of Hazard ratio estimation, Avatar with k = 10 produced HR estimates closest to the original data, whereas CT-GAN slightly underestimated the HR and TVAE showed the most significant deviation from the original HR. We also investigated the effect of applying the algorithms multiple times to improve results stability in terms of HR estimation. Our findings suggested that this approach could be beneficial, especially in the case of small datasets, to achieve more reliable and robust results. In conclusion, our study provides valuable insights into the performance of CT-GAN, TVAE, and Avatar methods for synthetic data generation in pharmacogenetic research. The application to other type of data and analyses (data driven) used in pharmacology should be further investigated.

Tackling nonlinear price impact with linear strategies

AbstractEmpirical studies in various contexts find that the price impact of large trades approximately follows a power law with exponent between 0.4 and 0.7. Yet, tractable formulas for the portfolios that trade off predictive trading signals, risk, and trading costs in an optimal manner are only available for quadratic costs corresponding to linear price impact. In this paper, we show that the resulting linear strategies allow to achieve virtually optimal performance also for realistic nonlinear price impact, if the “effective” quadratic cost parameter is chosen appropriately. To wit, for a wide range of risk levels, this leads to performance losses below 2% compared to a numerical algorithm proposed by Kolm and Ritter, run at very high accuracy. The effective quadratic cost depends on the portfolio risk and concavity of the impact function, but can be computed without any sophisticated numerics by simply maximizing an explicit scalar function.

Effect of Coupled Microstructural Characteristics of Catalyst Layer on High Temperature: Proton Exchange Membrane Fuel Cell Performance

Abstract The widespread adoption of High Temperature-Proton Exchange Membrane Fuel Cells (HT-PEMFC) in commercial applications is limited by their performance and durability compared to conventional energy sources. A key factor affecting these cells is the sluggish oxygen reduction reaction (ORR) at the cathode catalyst layer (CL). Optimizing the structural parameters of the cathode CL can enhance cell performance and longevity. Current research on these parameters is mostly descriptive, lacking numerical evidence to quantify their impact. This study develops a three-dimensional, non-isothermal HT-PEMFC numerical model to investigate the sensitivities of coupled structural parameters of the cathode CL, including Pt loading, CL thickness, and Pt particle diameter, at three levels. The orthogonal/Taguchi approach quantitatively assesses the impact of these parameters. The study reveals that Pt loading significantly affects cell voltage and cathode overpotential, while Pt diameter influences the homogeneity of overpotential distribution. The dominant impact of a single parameter decreases at higher current densities, necessitating careful analysis of trade-offs between different structural characteristics to maximize performance. These findings offer valuable insights for future experimental studies to enhance cell performance through adjustments to cathode catalyst characteristics.

On Trade-Off Relationship between Static and Dynamic Lateral Stabilities of Articulated Heavy Vehicles

Articulated heavy vehicles exhibit poor lateral stability, which may lead to unstable motion modes, e.g., trailer-sway and jackknifing, causing severe accidents. Varying relevant vehicle parameters improves the static stability but degrades the dynamic stability. The past studies focused either on the static or dynamic stability alone. However, little attention has been paid to exploring the trade-off between the static and dynamic stabilities. To gain design insights for active safety systems for AHVs, this article studies this trade-off systematically. To this end, a systematic method is proposed to conduct the linear stability and trade-off analysis. To implement and demonstrate the proposed method, a linear three-degrees-of-freedom yaw-plane model is generated to represent a tractor/semi-trailer. A trade-off analysis is conducted considering two tractor rear-axle configurations and three trailer payload arrangements. In each case, simulation is performed in both steady-state and transient testing maneuvers. To validate the linear stability analysis based on the linear yaw-plane model, two nonlinear TruckSim models are introduced, and the corresponding simulation is conducted. Insightful understanding of the trade-off is gained through analyzing the simulation results, and the linear stability analysis will provide valuable guidelines for the design and development of active safety systems for AHVs.

The Gains and Losses of Cultivated Land Requisition–Compensation Balance: Analysis of the Spatiotemporal Trade-Offs and Synergies in Ecosystem Services Using Hubei Province as a Case Study

The cultivated land requisition–compensation balance (CLRCB) policy is an important policy implemented by China to address the reduction in cultivated land and ensure food security. Although this policy has alleviated the loss of cultivated land quantity, it has had complex and diverse impacts on ecosystem services. Taking Hubei Province as the study area, this research explores the impact of the implementation of the CLRCB on ecosystem services and simulates the changes in ecosystem services in the study area in 2030 and the impact of CLRCB on the interactions among various services. The results show the following: (1) from 2000 to 2020, Hubei Province achieved a balance in the quantity of cultivated land through excessive compensation but failed to reach the goals of balancing cultivated land yield and productivity. (2) During the requisition–compensation process, habitat quality decreased by 501,862, and carbon storage lost 1.3 × 107 t, indicating negative ecological impacts; soil conservation services increased by 184.2 × 106 t, and water production increased by 21.29.3 × 108 m3. Within the cultivated land requisition–compensation area, habitat quality and carbon storage, as well as soil conservation and water production, exhibited synergistic relationships, while the remaining pairs of ecosystem services showed trade-off relationships. (3) The simulation of ecosystem services in 2030 indicates that soil conservation and water production are highest under the natural development scenario, while habitat quality and carbon storage are highest under the ecological protection scenario, both of which are superior to the urban development scenario. Under the natural development scenario, the trade-off and synergistic relationships among various ecosystem services in the cultivated land requisition–compensation area remain unchanged, while these relationships change significantly under the other two scenarios. This study emphasizes that future CLRCB should not only focus on maintaining the quantity of cultivated land but also consider the comprehensive benefits of ecosystem services, in order to achieve sustainable land-use management and ecological conservation.

Learning to match patients to clinical trials using large language models

Objective:This study investigates the use of Large Language Models (LLMs) for matching patients to clinical trials (CTs) within an information retrieval pipeline. Our objective is to enhance the process of patient-trial matching by leveraging the semantic processing capabilities of LLMs, thereby improving the effectiveness of patient recruitment for clinical trials. Methods:We employed a multi-stage retrieval pipeline integrating various methodologies, including BM25 and Transformer-based rankers, along with LLM-based methods. Our primary datasets were the TREC Clinical Trials 2021–23 track collections. We compared LLM-based approaches, focusing on methods that leverage LLMs in query formulation, filtering, relevance ranking, and re-ranking of CTs. Results:Our results indicate that LLM-based systems, particularly those involving re-ranking with a fine-tuned LLM, outperform traditional methods in terms of nDCG and Precision measures. The study demonstrates that fine-tuning LLMs enhances their ability to find eligible trials. Moreover, our LLM-based approach is competitive with state-of-the-art systems in the TREC challenges.The study shows the effectiveness of LLMs in CT matching, highlighting their potential in handling complex semantic analysis and improving patient-trial matching. However, the use of LLMs increases the computational cost and reduces efficiency. We provide a detailed analysis of effectiveness-efficiency trade-offs. Conclusion:This research demonstrates the promising role of LLMs in enhancing the patient-to-clinical trial matching process, offering a significant advancement in the automation of patient recruitment. Future work should explore optimising the balance between computational cost and retrieval effectiveness in practical applications.