Cutoff Strategies Research Articles

Strategic experimentation with asymmetric safe options

We study a two-player game of strategic experimentation with exponential bandits à la (Keller et al., 2005) where the safe-arm payoff is different across players. We show that, as in Das et al. (2020), there exists an equilibrium in cut-off strategies if and only if the difference in safe-arm payoffs is large enough. In the equilibrium in cutoff strategies, the player with the higher safe-arm payoff conducts less experimentation. This feature of the equilibrium offers an explanation for the fact that oftentimes technological innovations are due to startups rather than established market leaders.

Inorganic PM2.5 reduction in Kanto, Japan: The role of ammonia and its emission sources control strategies

Ammonia (NH3) is attracting attention as a carbon-free energy source and a significant precursor to inorganic PM2.5 (hereafter PM2.5), aside from NOx and SOx. Since the emission of NH3 has often been overlooked compared to NOx and SOx, this study aims to reveal the role of NH3 and its emission control on PM2.5 in Kanto, Japan. With the aid of gas ratio (GR) quantitatively defining the stoichiometry between the three precursors to PM2.5, and the aid of atmospheric modeling software ADMER-PRO, coupled with thermodynamics calculations, the spatiotemporal distribution along with PM2.5 reduction under different NH3 emission cutoff strategies in Kanto had been revealed for the first time. The cutoff of NH3 emission could effectively reduce the PM2.5 concentration, with sources originated from agriculture, human/pet activities, and vehicle sources, overall giving a 93.32% PM2.5 reduction. Different cutoff strategies lead to distinct reduction efficiencies of the overall and local PM2.5 concentrations, with GR as a crucial factor. The regions with GR ∼1, are sensitive to the NH3 concentration for forming PM2.5, at which the NH3 reduction strategies should be applied with high priority. On the other hand, installing a new NH3 emission source should be avoided in the region with GR < 1, suppressing the so-yielded PM2.5 pollution. The future PM2.5 pollution control related to the NH3 emission control strategies based on GR, which is stoichiometry-based and applicable to regions other than Kanto, has been discussed.

Cautious stochastic choice, optimal stopping and deliberate randomization

We study cautious stochastic choice (CSC) agents facing optimal timing decisions in a dynamic setting. In an expected utility setting, the optimal strategy is always a threshold strategy—to stop/sell the first time the price process exits an interval. In contrast, we show that in the CSC setting, where the agent has a family of utility functions and is concerned with the worst case certainty equivalent, the optimal strategy may be of non-threshold form and may involve randomization. We provide some carefully constructed examples, including one where we can solve explicitly for the optimal stopping rule and show it is a non-trivial mixture of threshold strategies. Our model is consistent with recent experimental evidence in dynamic setups whereby individuals do not play cut-off or threshold strategies.

A Novel Framework for Fast Feature Selection Based on Multi-Stage Correlation Measures

Datasets with thousands of features represent a challenge for many of the existing learning methods because of the well known curse of dimensionality. Not only that, but the presence of irrelevant and redundant features on any dataset can degrade the performance of any model where training and inference is attempted. In addition, in large datasets, the manual management of features tends to be impractical. Therefore, the increasing interest of developing frameworks for the automatic discovery and removal of useless features through the literature of Machine Learning. This is the reason why, in this paper, we propose a novel framework for selecting relevant features in supervised datasets based on a cascade of methods where speed and precision are in mind. This framework consists of a novel combination of Approximated and Simulate Annealing versions of the Maximal Information Coefficient (MIC) to generalize the simple linear relation between features. This process is performed in a series of steps by applying the MIC algorithms and cutoff strategies to remove irrelevant and redundant features. The framework is also designed to achieve a balance between accuracy and speed. To test the performance of the proposed framework, a series of experiments are conducted on a large battery of datasets from SPECTF Heart to Sonar data. The results show the balance of accuracy and speed that the proposed framework can achieve.

Equilibrium and Welfare Analysis in Second‐Price Auctions with Resale and Costly Entry

This study investigates the effects of resale allowance on entry strategies, seller’s expected revenue, and social welfare in a second‐price auction with two‐dimensional private information on values and participation costs. We characterize the perfect Bayesian equilibrium in cutoff strategies and identify sufficient conditions under which the equilibrium is unique. Our analysis suggests that resale allowance leads the low‐value bidder to become more aggressive on entry, while high‐value bidder has a lower incentive to enter. Furthermore, the allowance of resale can increase the social welfare under a sufficient condition, and its effect on expected revenue is ambiguous.

Hemorrhage During Induction Chemotherapy in Neuroblastoma: Additional Risk Factors in High-Risk Patients.

Background: Neuroblastoma is the most common solid extracranial tumor in children. Patients affected by neuroblastoma are stratified into low, intermediate, and high risk in terms of event-free and overall survival. Some high-risk patients have an additional risk of acute hemorrhagic complications during induction chemotherapy.Aim: To find easily and rapidly assessed parameters that help clinicians identify those patients affected by high-risk neuroblastoma who have an additional risk of hemorrhagic complications.Methods: The clinical notes of patients diagnosed with high-risk neuroblastoma from January 2013 until February 2021 were retrospectively reviewed. Clinical, demographic and laboratory data, biological characteristics of the tumor, and information about treatment and hospital stay were identified.Results: In the examined period, 44 patients were diagnosed with high-risk neuroblastoma. Four of these patients had hemorrhagic complications within 2–7 days after the initiation of induction chemotherapy; two patients had hemothorax, one patient had hemoperitoneum and one patient had hemothorax and hemoperitoneum. The patient with isolated hemoperitoneum was treated with blood components transfusions, clotting factors and colloids infusions; the three patients with hemothorax underwent thoracostomy tube placement and respiratory support. At initial presentation, patients who suffered from hemorrhagic complications had a higher degree of hypertension (stage 2, p = 0.0003), higher levels of LDH (median 3,745 U/L, p = 0.009) and lower levels of hemoglobin (mean 7.6 gr/dl, p = 0.0007) compared to other high-risk patients.Conclusions: A subgroup of “additional” high-risk patients can be identified within the high-risk neuroblastoma patients based on mean arterial pressure, LDH levels and hemoglobin levels at presentation. Further studies to define cut-off values and optimal management strategies for these patients are needed.

Current state of technologies and recognition of anti-SSA/Ro antibodies in China: A multi-center study.

BackgroundPrevious studies have demonstrated that Ro60 and Ro52 have different clinical implications, and anti‐Ro52 antibodies are an independent serum marker of systemic autoimmune diseases, including Sjögren's syndrome. Many different assays have been adopted to detect anti‐Sjögren's syndrome antigen A (SSA)/Ro antibodies, while to date no specific approach has been recommended as optimal for anti‐SSA/Ro antibody testing. Herein, we performed a multi‐center study to explore the current clinical utility of different strategies for anti‐SSA/Ro antibody testing in China.MethodsTwenty‐one tertiary care centers were included in this questionnaire‐based study. The self‐administered questionnaire mainly includes testing methods for anti‐SSA/Ro antibodies, reporting system of results, and interpretation of results by clinicians.ResultsSix different methods were applied to detect anti‐SSA/Ro antibodies in the 21 centers. Line immunoassay (eight different commercial kits) was the most frequently adopted method (21/21, 100%), with different cutoff values and strategies for intensity stratification. There were two reporting systems: One was reported as “anti‐SSA antibodies” and “anti‐Ro52 antibodies” (12/21, 57%), while the other was “anti‐SSA/Ro60 antibodies” and “anti‐SSA/Ro52 antibodies” (9/21, 43%). Notably, six centers (29%) considered either positive anti‐Ro60 or anti‐Ro52 antibodies as positive anti‐SSA antibodies, all of which adopted the latter reporting system.ConclusionSignificant variabilities existed among anti‐SSA/Ro assays. Nearly 30% of centers misinterpreted the definition of positive anti‐SSA antibodies, which may be attributed to the confusing reporting systems of line immunoassay. Therefore, we advocate standardization of the nomenclature of anti‐SSA/Ro antibodies, changing the “anti‐SSA/Ro52” label in favor of the “anti‐Ro52” antibodies for a clear designation.

Electrified Deceleration Cylinder Cutoff Engine Control Benefits and Strategies

&lt;div class="section abstract"&gt;&lt;div class="htmlview paragraph"&gt;Cylinder deactivation is a fuel consumption and CO&lt;sub&gt;2&lt;/sub&gt; reduction technology for internal combustion engines that deactivates cylinders at light to moderate loads, allowing the remaining firing cylinders to operate near optimum efficiency. Dynamic Skip Fire (DSF) uses full-authority cylinder deactivation that allows any cylinder of the engine to be deactivated in sequence. In previous SAE papers, both DSF technology and the synergies between DSF and electrification (eDSF) have been described.&lt;/div&gt;&lt;div class="htmlview paragraph"&gt;Recent engine technology includes deactivation mechanisms that do not effectively incorporate individual cylinder control. Nevertheless, it is still quite possible to improve the efficiency of engines equipped with these ganged-deactivation mechanisms. By grouping all cylinders into a deactivation mode, no air is pumped through the cylinders as it would be during the corresponding conventional operation that deactivates fuel alone. The engine equipped with deactivating cylinders can eliminate pumping work and provide more opportunity to recuperate electrical energy from the vehicle, as well as prevent oxygen saturation of the exhaust aftertreatment system.&lt;/div&gt;&lt;div class="htmlview paragraph"&gt;This paper presents the substantial benefits of this approach, showing both simulated and experimental fuel economy improvements for a C-segment vehicle exceeding 5% in the WLTC class 3 drive cycle. It discusses control strategies for managing transitions in and out of deactivation to achieve customer-pleasing NVH and drivability. Finally, the value proposition is presented for this electrified deceleration cylinder cutoff (eDCCO) system, also known as Hybrid++.&lt;/div&gt;&lt;/div&gt;

Robust sequential search

We study sequential search without priors. Our interest lies in decision rules that are close to being optimal under each prior and after each history. We call these rules robust. The search literature employs optimal rules based on cutoff strategies, and these rules are not robust. We derive robust rules and show that their performance exceeds 1/2 of the optimum against binary independent and identically distributed (i.i.d.) environments and 1/4 of the optimum against all i.i.d. environments. This performance improves substantially with the outside option value; for instance, it exceeds 2/3 of the optimum if the outside option exceeds 1/6 of the highest possible alternative.

ESG controversies and controversial ESG: about silent saints and small sinners

Based on an extensive international dataset containing Thomson Reuters environmental, social and corporate governance (ESG) rating, as well as Thomson Reuters newest controversies and combined score of an average of 2500 companies in the years 2002–2018, this article contributes to the existing discourse of the relationship between corporate social performance and corporate financial performance (CFP) by examining the Fama and French (J Financ Econ 116(1):1–22, 2015) five-factor risk-adjusted performance of positive screened best and worst portfolios, based on a 10% cutoff, respectively, for equally, value- and rank-weighted strategies in the European, US and global market. Furthermore, the controversies score allows us to examine the mid-to-long-term effects of scandals on the CFP without having to rely on the event study methodology. Even though a value-weighted strategy does not show any significant abnormal returns, we examined a significant outperformance for equally weighted worst ESG portfolios and best controversies strategies. These results strongly indicate that this is, on the one hand, driven by low-rated smaller companies (“small sinners”) and clean-coated firms with regard to controversies (“silent saints”) on the other hand. The findings hold for several robustness checks such as adjusting the cutoff rates or splitting the dataset across time.

A Note on Buyers’ Behavior in Auctions with an Outside Option

In this note I show that the equilibrium in cutoff strategies observed in auctions with a buy-it-now price may also arise in markets where objects are sold simultaneously by auctions and posted prices. However, contrary to auctions with a buy-it-now price where buyers need to know only the total number of players in the market, in the latter environment buyers must also observe the number of active bidders in the auction for the equilibrium to exist in cutoff strategies.

Effect of irrigation cut-off strategies on yield, water productivity and gas exchange in a drip-irrigated hazelnut (Corylus avellana L. cv. Tonda di Giffoni) orchard under semiarid conditions

An experiment was conducted to evaluate the effect of irrigation cut-off (ICO) strategies on yield components, water productivity (WP), and gas exchange in drip-irrigated hazelnut (Corylus avellana L., cv. Tonda di Giffoni) trees during two consecutive growing seasons. The experimental design was completely randomized, with four ICO treatments and four replicates per treatment based on threshold values of the midday stem water potential (Ψstem). In the T1 treatment, Ψstem was maintained around –0.7 MPa, while T2, T3, and T4 treatments did not receive irrigation from the beginning of stage III (fruit growth curve) until trees reached approximately the following Ψstem thresholds: –1.0 MPa in T2, –1.3 MPa in T3 and –1.6 MPa in T4. Once reached the specific thresholds, irrigation was restored and maintained according to T1 in all treatments until harvest. Besides, measurements of Ψstem, stomatal conductance (gs), net CO2 assimilation rate (An), transpiration rate (E), yield components, α-tocopherol kernel content, and WP were evaluated in this study. Results indicated that values of Ψstem, An,gs, and E observed in T3 and T4 were between 24–29, 15–37, 15–40, and 11–32 % lower than those found in T1, respectively. T4 significantly decreased yield (kg tree–1), kernel (KW), and fruit (FW) weights, but KW/FW ratio and the α-tocopherol kernel content (μg g–1) were not significantly different among treatments. Also, this study indicated that the T2, T3, and T4 treatments had 10, 17, and 25 days without irrigation, which produced water savings of 19, 24, and 29 % in comparison with T1, respectively. Finally, WP was significantly affected by ICO strategies, with the minimum and maximum values observed in T1 (0.51 kg m–3) and T4 (0.86 kg m–3), respectively.

Information Correlation in a 2 × 2 Game and an Extension of Purification Rationale

In this paper, we study a 2 × 2 Bayesian entry game with correlated private information. The distribution of private information is modelled by a symmetric joint normal distribution. Therefore, the correlation coefficient of the private information distribution reflects the degree of dependence of players' private information. Under such specification, players' private information can be correlated flexibly, which is not confined to the typical additive specification of private payoff shocks or private information by Carlson and van Damme (1993), where the private information is correlated due to the common payoff shock. In our game, if the private information is correlated, we find that given the variances of the private information, there exists a restriction on the degree of correlation of players' private information that allows the game can be solved by cutoff strategies. Specifically, given the variances of the private information, if players' private information in strategic substitutes (strategic complements) Bayesian games are positively (negatively) correlated, the range of correlation coefficient that allows the game can be solved by cutoff strategies is restricted so that if the correlation is out of the range, the game cannot be solved by cutoff strategies. Alternatively, given positive (negative) correlation of private information, the value of variances that allows a strategic substitutes (strategic complements) Bayesian games can be solved by cutoff strategies are restricted within certain range. If the value of variances fall out of the range, the Bayesian game cannot be solved by cutoff strategies. However, given negative (positive) correlation of players' private information in strategic substitutes (strategic complements) Bayesian games, in which the Bayesian games can always be solved by cutoff strategies, we prove that as the variances converge to zero, all pure strategy Bayesian Nash equilibria of the perturbed games converge to the respective Nash equilibria of the corresponding strategic substitutes (strategic complements) complete information games. Based on the result, we conclude that the purification rationale proposed by Harsanyi (1973) can be extended to games with dependent perturbation errors that follow a symmetric joint normal distribution if the correlation coefficient is positive for the strategic complements games or negative for the strategic substitutes games.

Strategic experimentation with asymmetric players

We examine a two-player game with two-armed exponential bandits à la (Keller et al. in Econometrica 73:39–68, 2005), where players operate different technologies for exploring the risky option. We characterise the set of Markov perfect equilibria and show that there always exists an equilibrium in which the player with the inferior technology uses a cut-off strategy. All Markov perfect equilibria imply the same amount of experimentation but differ with respect to the expected speed of the resolution of uncertainty. If and only if the degree of asymmetry between the players is high enough, there exists a Markov perfect equilibrium in which both players use cut-off strategies. Whenever this equilibrium exists, it welfare dominates all other equilibria. This contrasts with the case of symmetric players, where there never exists a Markov perfect equilibrium in cut-off strategies.

Information aggregation with a continuum of types

We study the problem of designing a voting rule which makes voting by cut-off strategies efficient for settings where voters have state-dependent common preferences over and vote on accepting or rejecting an issue but hold private information in the form of continuous types about the true state. We show that such rules only exist under a restrictive condition on the model parameters.

Overcoming the No Free Lunch Theorem in Cut-off Algorithms for Fork-Join programs

Abstract The No Free Lunch Theorem establishes that for any algorithm, any elevated performance over one class of problems is offset by performance over another class. Empirically, this is true for Granularity Control algorithms, particularly in Fork-Join style concurrent programs. Cut-off Algorithms make the decision to either continue forking work (parallelising) or instead computing the remaining execution branches sequentially. These algorithms affect how well a program dynamically adjusts to the parallelism available in the machine. To put things into context, choosing the wrong algorithm can make a program go from 30 s of execution to over a day. Cut-off Algorithms such as Max-Tasks, Max-Level, SurplusTasks and variants do not provide the same performance improvements over the same classes of Fork-Join programs. Thus, programmers have to decide which Cut-off Algorithms to use on different classes of problems. Finding the right Cut-off Algorithm is a time-consuming task, as, most of times, it requires trial-and-error execution of several configurations before determining the right solution. To the best of our knowledge, there is no definitive solution for making this decision automatically. Being able to do so would largely enhance the performance of parallel programs generated by optimising compilers and/or executed by parallelising frameworks. In this work, we address the problem of automatically selecting the right Cut-off Algorithm for highly parallel programs. We evaluate the performance of nowadays most relevant Cut-off Algorithms over different programs. We identify possible correlations between program characteristics and performance improvements observed with different cut-off strategies. Finally, we derive a set classification rules for selection of Cut-off Algorithms that can be integrated into compilers and frameworks that perform automatic parallelisation of programs.

Performance of the UroVysion® FISH assay for the diagnosis of malignant effusions using two cutoff strategies.

The cytological examination of cavity fluids has limited sensitivity in the diagnosis of malignancy. Aneuploidy, which is commonly observed in neoplastic cells, could potentially be used as an ancillary diagnostic tool. To evaluate the detection of aneuploid cells in cavitary effusion samples using the fluorescence in situ hybridization (FISH) assay UroVysion ® with some adaptations and two different cutoff strategies. Seventy samples of pleural or peritoneal fluid with positive (n = 40), negative (n = 15), or suspicious (n = 15) oncotic cytology were subjected to FISH assay with the multitarget UroVysion ® kit, which is composed of probes that hybridize to the centromeric region of chromosomes 3, 7, and 17 and to the locus 9p21. FISH performance was evaluated using two different cutoffs: (1) the manufacturer's cutoff (M‐FISH) and 2) a proposed cutoff (P‐FISH). Using M‐FISH, the diagnostic sensitivity was 57.1%, specificity 87.5%, and accuracy 60.0%; with P‐FISH, the sensitivity was 87.3%, specificity 71.4%, and accuracy 85.7%. When combined with cytology, the sensitivity, specificity, and accuracy were 88.0%, 83.3%, and 87.8%, respectively. Malignant cells presented a predominance of chromosomal gains. The UroVysion ® test using the P‐FISH cutoff was effective in demonstrating aneuploid cells in all malignant effusions, confirming the diagnosis of malignancy even in cases with suspicious cytology.

Olive oil quality response to irrigation cut-off strategies in a super-high density orchard

An increase in olive oil consumption has occurred worldwide in the last decades and has resulted in more land area being dedicated to olive orchards in several southern hemisphere countries. In order to achieve sustainable productivity under the increasing water scarcity, optimal water use is essential. Thus, a field experiment was conducted during four consecutive growing seasons (2010–2011 to 2013–2014) to evaluate olive oil quality in response to irrigation cut-off strategies applied after fruit set using midday stem water potential (Ψstem) thresholds in a super-high density olive orchard (cv. Arbequina) located in the Pencahue Valley, Maule Region, Chile. The experimental design was completely randomized with four treatments and four replicates. In treatment T1 (control), Ψstem was between −1.4 and −2.2 MPa (100% of actual evapotranspiration) throughout the season, while the T2, T3 and T4 treatments did not receive irrigation from fruit set until they reached a Ψstem threshold of approximately −3.5, −5.0, and −6.0 MPa, respectively. Once these thresholds were reached, irrigation was reestablished and maintained as T1 in all treatments until olives were harvested. Fruit oil and water content (%) at harvest were not affected by the different treatments. Free acidity was also not affected, while peroxide and extinction coefficients only showed minor differences between treatments that were within the limits established for commercial extra virgin oil quality. Total polyphenols at harvest were much higher in the water deficit treatments and showed a significant linear relationship each year with the water stress integral. The percentages of the main fatty acids were not affected by the treatments. However, they were significantly different between seasons. Sensory tests indicated that the higher total polyphenol content positively contributed to more pronounced bitter and pungent attributes of olive oil from trees with higher water deficit. Thus, the irrigation cut-off strategies evaluated at our four-year study can be an excellent management tool to both improve the oil quality of cv. Arbequina and reduce water use in super-high density orchard.

Cautious Stochastic Choice, Optimal Stopping and Deliberate Randomization

We study Cautious Stochastic Choice (CSC) agents facing optimal timing decisions in a dynamic setting. In an expected utility setting, the optimal strategy is always a threshold strategy - to stop/sell the first time the price process exits an interval. In contrast, we show that in the CSC setting, where the agent has a family of utility functions and is concerned with the worst case certainty equivalent, the optimal strategy may be of non-threshold form and may involve randomization. We provide some carefully constructed examples, including one where we can solve explicitly for the optimal stopping rule and show it is a non-trivial mixture of threshold strategies. Our model is consistent with recent experimental evidence in dynamic setups whereby individuals do not play cut-off or threshold strategies.

Identification of time and risk preferences in buy price auctions

Buy price auctions merge a posted price option with a standard bidding mechanisms, and have been used by various online auction sites including eBay and General Motors Assistance Corporation. A buyer in a buy price auction can accept the buy price to win with certainty and end the auction early. Intuitively, the buy price option may appeal to bidders who are risk averse or impatient to obtain the good, and a number of authors have examined how such mechanisms can increase the seller's expected revenue over standard auctions. We show that data from buy price auctions can be used to identify bidders' risk aversion and time preferences. We develop a private value model of bidder behavior in a buy price auction with a temporary buy price. Bidders arrive stochastically over time, and the auction proceeds as a second‐price sealed bid auction after the buy price disappears. Upon arrival, a bidder in our model is allowed to act immediately (i.e., accept the buy price if it is still available or place a bid) or wait and act later. Allowing for general forms of risk aversion and impatience, we first characterize equilibria in cutoff strategies and describe conditions under which all symmetric pure‐strategy subgame‐perfect Bayesian Nash equilibria are in cutoff strategies. Given sufficient exogenous variation in auction characteristics such as reserve and buy prices and in auction lengths, we then show that the arrival rate, valuation distribution, utility function, and time‐discounting function in our model are all nonparametrically identified. We also develop extensions of the identification results for cases where the variation in auction characteristics is more limited. Nonparametric identification auctions risk aversion time preferences C14 C57 D44 L81