Maximum Value Research Articles

Advanced confidence methods in deep learning

The typical aim of classification tasks is to maximize the accuracy of the predicted label for a given input. This accuracy increases with the confidence, which is the maximal value of the output units, and when the accuracy equals confidence, calibration is achieved. Herein, several methods are proposed to enhance the accuracy of inputs with similar confidence, extending significantly beyond calibration. Using the first gap between the maximal and second maximal output values, the accuracy of the inputs with similar confidence is enhanced. The extension of the confidence or confidence gap to their minimal value among a set of augmented inputs further enhances the accuracy of inputs with similar confidence. Enhanced accuracies are demonstrated on EfficientNet-B0 trained on ImageNet and CIFAR-100, and VGG-16 trained on CIFAR-100. The results suggest improved applications for high-accuracy classification tasks that require manual operation for a given fraction of low-accuracy inputs.

Diagnostic value of 18F-fluorodeoxyglucose positron emission tomography/computed tomography imaging in pediatric opsoclonus myoclonus ataxia syndrome presenting with neuroblastoma.

Early precision diagnosis and effective treatment of opsoclonus myoclonus ataxia syndrome (OMAS) patients presenting with neuroblastoma can prevent serious neurological outcomes. To assess the diagnostic value of 18F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) imaging in pediatric OMAS with neuroblastoma. A retrospective evaluation of 45 patients diagnosed with OMAS who underwent 18F-FDG PET/CT was performed. A univariate analysis was performed to compare clinical characteristics between OMAS with and without neuroblastoma. Univariate and multivariate logistic regression analyses were applied to identify independent risk factors for OMAS with neuroblastoma and to develop the clinical model. Finally, independent risk factors and PET/CT were fitted to build the combined model for the diagnosis of OMAS with neuroblastoma and presented as a nomogram. Receiver operating characteristic curve, decision curve, and calibration curveanalyses were conducted to evaluate the performance of the models. Among 45 patients, 27 were PET/CT-positive, 23/27 lesions were neuroblastoma, and four were false positives. One of the false positive patients was confirmed to be adrenal reactive hyperplasia by postoperative pathology, and the symptoms of OMAS disappeared in the remaining three cases during clinical follow-up. The average maximal standardized uptake value of PET/CT-positive lesions was 2.6. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of PET/CT were 100%, 81.8%, 85.2%, 100%, and 91.1%, respectively. Age at diagnosis, lactate dehydrogenase, and neuron-specific enolase showed statistically significant differences between OMAS with and without neuroblastoma. Lactate dehydrogenase was identified as the independent risk factor to develop the clinical model, and the clinical model demonstrated an area under the curve (AUC) of 0.82 for the diagnosis of OMAS with neuroblastoma, with an AUC as high as 0.91 when combined with PET/CT. The decision curve analysis and calibration curve demonstrated that the nomogram had good consistency and clinical usefulness. In patients with OMAS, 18F-FDG PET/CT has a high diagnostic accuracy in detecting tumors of the neuroblastoma, especially when combined with the independent risk factor serum lactate dehydrogenase.

Optimal thermometers with spin networks

The heat capacity C of a given probe is a fundamental quantity that determines, among other properties, the maximum precision in temperature estimation. In turn, C is limited by a quadratic scaling with the number of constituents of the probe, which provides a fundamental limit in quantum thermometry. Achieving this fundamental bound with realistic probes, i.e. experimentally amenable, remains an open problem. In this work, we tackle the problem of engineering optimal thermometers by using networks of spins. Restricting ourselves to two-body interactions, we derive general properties of the optimal configurations and exploit machine-learning techniques to find the optimal couplings. This leads to simple architectures, which we show analytically to approximate the theoretical maximal value of C and maintain the optimal scaling for short- and long-range interactions. Our models can be encoded in currently available quantum annealers, and find application in other tasks requiring Hamiltonian engineering, ranging from quantum heat engines to adiabatic Grover’s search.

Merging Counter-Propagation and Back-Propagation Algorithms: Overcoming the Limitations of Counter-Propagation Neural Network Models.

Artificial neural networks (ANNs) are nowadays applied as the most efficient methods in the majority of machine learning approaches, including data-driven modeling for assessment of the toxicity of chemicals. We developed a combined neural network methodology that can be used in the scope of new approach methodologies (NAMs) assessing chemical or drug toxicity. Here, we present QSAR models for predicting the physical and biochemical properties of molecules of three different datasets: aqueous solubility, acute fish toxicity toward fat head minnow, and bio-concentration factors. A novel neural network modeling method is developed by combining two neural network algorithms, namely, the counter-propagation modeling strategy (CP-ANN) with the back-propagation-of-errors algorithm (BPE-ANN). The advantage is a short training time, robustness, and good interpretability through the initial CP-ANN part, while the extension with BPE-ANN improves the precision of predictions in the range between minimal and maximal property values of the training data, regardless of the number of neurons in both neural networks, either CP-ANN or BPE-ANN.

Efectos de un extracto de hojas de Leucaena leucocephala en la actividad de xantina oxidasa y en los niveles séricos de oxipurinas en ratones

There is a need for novel alternatives to the medical use of allopurinol. In this sense, the present study obtained a leaf extract of L. leucocephala, and its chemical composition, inhibitory action against xanthine oxidase (XO) in vitro, inhibitory interaction between the extract and allopurinol, and the inhibitory action on XO in vivo using mice treated with potassium oxonate and hypoxanthine were determined. Polyphenol and flavonoid compounds were found in the leaf extract. For the leaf extract, the IC50 and maximal values were 334.60 µg/mL and 46.4 % for the inhibition of XO. The 3:1 ratio combination of allopurinol and extract showed IC50 and waDRI values of 1.35 µg/mL, 1.13 (allopurinol) and 1015.72 (extract) to inhibit XO, resulting in a synergistic interaction against XO in vitro. This combination also enhanced the therapeutic success in the mouse model compared with allopurinol administered alone. The present study presents the first evidence for the use of an allopurinol and L. leucocephala extract combination at a 3:1 ratio as a substitute for the administration of allopurinol alone.

Point-of-care β-hydroxybutyrate measurement predicts adequate glucose metabolism suppression in cardiac FDG-PET/CT.

The aims of our study were to evaluate whether point-of-care β-hydroxybutyrate (BHB) measurement can be used to identify patients with adequate cardiac glucose metabolism suppression for cardiac[18F]-fluoro-2-deoxy- d-glucose-positron emission tomography with computerized tomography(FDG-PET/CT) and to develop a pretest probability calculator of myocardial suppression using other metabolic factors attainable before imaging. We recruited 193 patients with any clinical indication for whole body [18F]-FDG-PET/CT. BHB level was measured with a point-of-care device. Maximal myocardial standardized uptake value using lean body mass (SULmax) was measured from eight circular regions of interest with 1 cm circumference and background from left ventricular blood pool. Correlations SULmax and point-of-care measured BHB were analysed. The ability of BHB test to predict adequate suppression was evaluated with receiver operating characteristic analysis. Liver and spleen attenuation in computed tomography weremeasured to assess the presence of fatty liver. BHB level correlated with myocardial uptake and, using a cut-off value of 0.35 mmol/L to predict adequate myocardial suppression, we reached specificity of 90% and sensitivity of 56%. Other variables to predict adequate suppression were diabetes, obesity, ketogenic diet and fatty liver. Using information attainable before imaging, we created a pretest probability calculator of inadequate myocardial glucose metabolism suppression. The area under the curve for BHB test alone was 0.802 and was 0.857 for the pretest calculator (p = 0.319). BHB level measured with a point-of-care device is useful in predicting adequate myocardial glucose metabolism suppression. More detailed assessment of other factors potentially contributing to cardiac metabolism is needed.

Optimal stopping of BSDEs with constrained jumps and related zero-sum games

In this paper, we introduce a non-linear Snell envelope which at each time represents the maximal value that can be achieved by stopping a BSDE with constrained jumps. We establish the existence of the Snell envelope by employing a penalization technique and the primary challenge we encounter is demonstrating the regularity of the limit for the scheme. Additionally, we relate the Snell envelope to a finite horizon, zero-sum stochastic differential game, where one player controls a path-dependent stochastic system by invoking impulses, while the opponent is given the opportunity to stop the game prematurely. Importantly, by developing new techniques within the realm of control randomization, we demonstrate that the value of the game exists and is precisely characterized by our non-linear Snell envelope.

Performance Assessment of Venturi-Assisted Confined Tube Aerators with Varying Diameter

A significant amount of energy in wastewater treatment plants is spent on aeration to treat the organic matter with microorganisms in an oxygen-enriched environment. In this study, a novel and simplistic aeration concept known as Confined Tube Aeration (CTA) is proposed, in which the main elements are a Venturi injector and a coiled tube at its outlet. Two Venturi injector diameters were chosen for evaluation in this study, measuring 1 inch (25.4 mm) and 4 inch (101.6 mm). In this study, a relationship was developed between air suction rate and pressure differential across the injector. Then, a numerical model was developed to analyze hydrodynamic conditions and evaluate system performance. The main findings are that the larger diameter aerator performs 20% better than the smaller injector in terms of standard aeration efficiency (SAE), with a maximal value of 0.74 kgO2/kWh found for the larger diameter system. These results suggest that future SAE improvements may be made for larger diameter systems in full-scale wastewater treatment applications with suitably designed injectors.

Limiting Temperature Rise in Cochlear Implantation Bone Drilling: A Novel Approach.

In the process of cochlear implantation surgery, it is crucial to develop a method to control the temperature during the drilling of the implant channel since high temperatures can result in damage to bone and nerve tissue. This paper simplified the traditional point heat source temperature rise model and proposed a novel extreme peck drilling model to quantitatively calculate the maximum temperature rise value. It is also innovatively introduced a new method for calculating the best peck drilling duty cycle to strictly control the maximum temperature rise value. Besides, the neural network is trained with virtual data to identify two important thermal parameters in the temperature rise model. In the experiment of epoxy resin and temporal bone, the difference between predicted maximum temperature and actual maximum temperature was less than 1.5 °C, and the error rate was less than 10%. And the error source was analyzed by variational mode decomposition, along with discussion of potential solutions. In the temperature control experiment, the model successfully controlled the maximum temperature rise within 10 °C.For cochlear implantation surgery, we also divide the implantation channel into different stages based on the bone density in CT images to identify thermal parameters and calculate drilling strategies. This method provides a new strategy for accurate and effective control of borehole heat generation. These achievements provide new ideas and directions for research in cochlear implantation surgery and related fields, and are expected to have extensive application in medical practice.

Action Candidate Driven Clipped Double Q-Learning for Discrete and Continuous Action Tasks.

Double Q-learning is a popular reinforcement learning algorithm in Markov decision process (MDP) problems. Clipped double Q-learning, as an effective variant of double Q-learning, employs the clipped double estimator to approximate the maximum expected action value. Due to the underestimation bias of the clipped double estimator, the performance of clipped Double Q-learning may be degraded in some stochastic environments. In this article, in order to reduce the underestimation bias, we propose an action candidate-based clipped double estimator (AC-CDE) for Double Q-learning. Specifically, we first select a set of elite action candidates with high action values from one set of estimators. Then, among these candidates, we choose the highest valued action from the other set of estimators. Finally, we use the maximum value in the second set of estimators to clip the action value of the chosen action in the first set of estimators and the clipped value is used for approximating the maximum expected action value. Theoretically, the underestimation bias in our clipped Double Q-learning decays monotonically as the number of action candidates decreases. Moreover, the number of action candidates controls the tradeoff between the overestimation and underestimation biases. In addition, we also extend our clipped Double Q-learning to continuous action tasks via approximating the elite continuous action candidates. We empirically verify that our algorithm can more accurately estimate the maximum expected action value on some toy environments and yield good performance on several benchmark problems. Code is available at https://github.com/Jiang-HB/ac_CDQ.

A Robot Positional Error Compensation Method Based on Improved Kriging Interpolation and Kronecker Products

This paper proposes a stable and high-accuracy model-free calibration method for unopened robotic systems, which can significantly improve the robot positional accuracy. Two improvements are made to the existing kriging-based error compensation method to achieve robustness/practicality enhancement goals: (1) The semi-variogram model is solved using the sequential quadratic programming (SQP) algorithm, and the distance weight coefficients are added to the objective function. The accuracy of semi-variogram modeling is guaranteed, thereby improving the performance and stability of error compensation. (2) The hand-eye (the pose matrix between the robot base and the laser tracker) and the tool center point (TCP) position are calibrated based on Kronecker products without relying on the spatial analyzer (SA) software to construct the robot base coordinate system separately. Thus, the calibration accuracy and efficiency are significantly improved. Experiments have been conducted, and the results reveal that the proposed method can significantly reduce the robot positional error. Furthermore, the proposed approach performs better than the existing kriging-based error compensation method without Kronecker products. The maximum, mean, and root mean square (RMS) values of the absolute positional errors are reduced by 34.48%, 8.09%, and 10.05%, respectively.

Yb3+/Ho3+ doped Ba3Y2B4O12 phosphors: Upconversion luminescence and temperature sensing properties

Optical thermometry achieved by luminescent materials with good stability and high sensitivity has attracted much attention. In this article, Ba3Y2B4O12, a borate with good chemical stability and high laser threshold was chosen to be host material for preparing a series of Ba3Y2-x-yYbxHoyB4O12 (BYBO:xYb3+/yHo3+; 0.01 ≤ x ≤ 0.35, 0.005 ≤ y ≤ 0.035) upconversion phosphors by a facile solid-state method. Under 980 nm excitation, phosphors show strong 551 nm green emission, weak 668 nm red emission, and 755 nm near-infrared emission, while bright greenlight can be observed by naked eye. When x = 0.15, y = 0.01, luminescent intensity obtains the maximum value. At higher doping concentration, the reduction of cell parameters caused by doping can accelerate the decrease of distance between dopants, so that the energy back transfer process is more likely to occur, weakening the green emission. The intensified non-radiative relaxation results in an increased red emission proportion at higher temperature. According to this rule, the temperature sensing properties based on the fluorescence intensity ratio I668/I551 and I688/I755 are studied. The maximum relative sensitivity (SR) reaches 1.53 % K−1 at 478 K, which is higher than most of reported materials. It shows that BYBO:Yb3+/Ho3+ has application potential in temperature sensing.

Computational Approaches Molecular Docking and MD Simulation Establishes the Potential COVID-19 Main Protease Inhibitors from Natural Products

Aim: COVID-19 was classified as a pandemic by the World Health Organization (WHO) on March 11, 2020. No reliable cure, however, was found. To prevent viral replication, complementary therapy with antiviral and antimalarial medications were used. However, due to their synthetic origin, they have a lot of side effects. To overcome this bane natural origin drugs were repositioned. Background: As repositioned drugs do not undergo a pro-long process of pre-clinical trial, hence, they play an excellent role in the spillover of pathogens. The main protease (6LU7) enzyme found in severe acute respiratory syndrome coronavirus-2 (SAR-CoV-2) is essential for viral replication. Thus, it acts as a hotspot in drug discovery. Objective: A molecular docking computational approach was used to determine the ability of the binding contract between the selected 3D-models of COVID-19 protease target and proposed natural compounds pristimerin, amazoquinone, kendomycin, celastrol, 20-epi-isoguesterinol, phenanthrenequinone, taxodione, maytenoquinone, hippeastrine, ammothamnine, 28-hydroxy isoiguesterin, hemanthamine, alisol-B, stigmasterol, β-pinene,and β-sitosterol through Autodock v.1.5.6 software. Method: The present study is designed to perform in-silico studies using molecular docking (Autodock tool v.1.5.6), Discovery Studio 2017 R2 client, Patch dock, SWISS-ADME prediction, and molecular simulation (Desmond simulation package of Schrodinger) between 6LU7 and natural origin compounds. Result: The results of docking study performed between 6LU7 and compounds pristimerin, amazoquinone, kendomycin, celastrol, 20-epi-isoguesterinol, phenanthrenequinone, taxodione, maytenoquinone, hippeastrine, ammothamnine, 28-hydroxy isoiguesterin, hemanthamine, alisol-B, stigmasterol, β-pinene, and β-sitosterol, showed binding energy as -9.68, -7.34, -5.34, -4.63, -4.24, -4.13, -4.08, -3.85, -3.83, -3.7, -3.6, -3.57, -3.54, -3.39, -3.18, and -3.03 Kcal/mol, respectively. It can be shown that the Pristimerin-6LU7 protein complex was maintained throughout the simulation since the ligand RMSDs varied with a maximum value of 4.2Å during the first 10 ns, followed by more stable interactions for the remaining time of the simulation. Conclusion: The goal of the current work was to find inhibitors for both prophylactic and therapeutic usage in COVID-19 patients.

IJCM_413A: A cross sectional study to find out status of post exposure prophylaxis among animal bite cases in Raipur city Chhattisgarh.

Background: Rabies is a viral zoonosis that occurs in more than 100 countries and territories Although a number of carnivores and bat species serve as natural reservoirs, rabies in dogs is the source of 99% human infections and poses a potential threat to more than 3.3 billion people. In humans, rabies is highly fatal once clinical symptoms have developed. According to the World Health Organization, human rabies can be prevented completely by proper post exposure prophylaxis. In India alone, 20,000 deaths (i.e., about 2/100,000 population at risk) and 2 million bites, mostly by dogs, are estimated to occur annually. India has 36% global and 65% Asian rabies burden in terms of cases. Local treatment of wounds is of maximal value when applied immediately after exposure (within minutes if possible). Animal experiments have shown that local wound treatment can reduce the chances of developing rabies by up to 80%. Objectives: To find out the status of post exposure prophylaxis and associated factors among animal bite cases in Raipur city Chhattisgarh. Methodology: Type of study: A community based cross sectional survey Conducted at: Raipur District. Duration of study: Over a period of 3 months (November 2023- January 2024). Study Subjects: General Population. Inclusion criteria: General population, Raipur. Exclusion Criteria: 1) Patients who do not give consent. 2)Unconscious Very ill patients or patients with Mental illness. Results: Total of 1124 participants 41 had animal bite, 63.41% were males and 36.59% were females. Among the biting animals 83% were dogs, while cats were 15% and 2% were monkeys. Out of 41 cases 90.24% had Category II bite while 9.75% had Category III bite. 33 out of 41 i.e. 80.48% victims took Anti Rabies vaccine, while rest 19.52% preferred treatment from traditional healer. Conclusion: Majority of animal bite were of dog bite and were classified under Category II. Improved awareness, forestalling animal rabies, and better access to affordable and potent human rabies vaccines are essential for the elimination of human rabies.

Clustering coefficients for networks with higher order interactions.

We introduce a clustering coefficient for nondirected and directed hypergraphs, which we call the quad clustering coefficient. We determine the average quad clustering coefficient and its distribution in real-world hypergraphs and compare its value with those of random hypergraphs drawn from the configuration model. We find that real-world hypergraphs exhibit a nonnegligible fraction of nodes with a maximal value of the quad clustering coefficient, while we do not find such nodes in random hypergraphs. Interestingly, these highly clustered nodes can have large degrees and can be incident to hyperedges of large cardinality. Moreover, highly clustered nodes are not observed in an analysis based on the pairwise clustering coefficient of the associated projected graph that has binary interactions, and hence higher order interactions are required to identify nodes with a large quad clustering coefficient.

Fluidized bed hydrodynamics under variable air inlet configurations to enhance gasification reactor efficiency: Computational study

This study employs diverse strategies to enhance motion dynamics within the reactor, with a specific focus on the critical geometric parameter of air nozzle configuration. Methodical analysis of various air nozzle angles, 0°, 45o, and 90° relative to the horizontal bottom line is undertaken to discern their influence on these key parameters throughout multiple stages during the recorded flow duration. A CFD model of the physical model is constructed and solved using ANSYS software. Parameters scrutinized include the longitudinal and lateral distribution of particle volume fraction, alongside radial and axial velocities of particles. The results emphasize the significant impact of air-feeding orientation on both radial and axial particle velocities. Notably, 45° air nozzle angle is the best orientation for the fluidized bed reactor displaying maximal values in particle volume fraction fluctuations and bed height. Furthermore, peak values for radial and axial velocity persist consistently throughout the entire flow duration.

Can attentional nudges improve efficiency of bilateral multi-attribute negotiations?

This paper reports the results from a lab experiment to simulate negotiation on innovative therapy commercialization. Using a between-subject design, we analyzed the consequences of two light choice interventions: (1) guiding negotiations towards early wins, and (2) inviting negotiators to share information about their priority goals. In both treatments, the total value created exceeded the control value by approximately 9 % of the maximal value that can be created in this experiment. However, it was essentially the buyer who captured the additional value. We found that, conditional on the success of the negotiation, the total value created increased with the time spent negotiating. Negotiator gender had an impact on the negotiation outcome, with women underperforming compared to men.

Agro-morphological characterization and genotypic diversity of chilli (Capsicum. frutescens) landraces of Bangladesh

Samples of 82 chilli (Capsicum spp.) genotypes grown during the Rabi season of 2016-17 were characterized based on 28 qualitative and 7 quantitative agro-morphological markers. The genotypes were collected and conserved in the Plant Genetic Resources Centre (PGRC) of the Bangladesh Agricultural Research Institute (BARI). The Chi-square (χ 2) tests and the Shannon Diversity Index (H´) were used for the genetic diversity study. All the characters under study were distributed independently except cotyledon leaf shapes and leaf pubescence density. The values of H´ of the genotypes varied widely, the maximum values being observed for the cotyledon leaf shape, leaf density, and anthocyanin leaf spot on the fruit. In contrast, the lowest values were recorded for pigmentation of node and leaf color. The estimated coefficient of variation was the highest while it was the lowest for one thousand seed weights. No variation was observed for calyx annular constriction of fruit. Analytical functions of DIVA-GIS (Geographic Information System) mapping localized the accessions into 10 districts and marked the areas of insufficient collection. Accession AMA-248 belonging to Mymensingh was almost round fruit. Accessions RAI-232 and RAI-80 belonging to Chattogram, AMA-335 belonging to Sherpur, AMA-361 belonging to Jamalpur, RAI-80 belonging to Chattogram, and AHI-01 belonging to Jhenaidah were elongated fruit. Germplasms collected from Chattogram showed the maximum variation in traits of cotyledon leaf color and stem color at the seedling transplanting age. The variation observed in different characters could be important characters in selecting parents for breeding programs.

The accuracy of different calculation methods when identifying handgrip strength asymmetry among middle-aged and older Chinese adults.

At present, there is no uniform standard mean of identifying handgrip strength (HGS) asymmetry based on maximum or average HGS values. Therefore, this study aimed to explore the accuracy of different calculation methods in the evaluation of HGS asymmetry. Using the maximum reading of two trials from both hands (Method A) as the reference standard, the accuracy of the HGS asymmetry identified by the average value of two trials of both hands (Method B) was determined by using various indicators, including specificity, sensitivity, the area under the receiver operating characteristic curve (AUC), positive, and negative predictive values. Overall, 12,163 individuals were included in this study, of whom 47.61% (5791/12,163) were male. The percentages of individuals with HGS asymmetry differed as a function of age and sex when using these two different methods. When employing Method A, 38.52%, 41.57%, and 44.57% of males 45 ≤ age<60, 60 ≤ age<80, and ≥ 80 years of age exhibited HGS asymmetry as compared to 40.78%, 39%, and 39.63% of females. Using Method B, the corresponding proportions were 41.69%, 42.5%, and 40% in males and 42.01%, 41.18%, and 40.55% in females, respectively. When compared to Method A, Method B was found to be effective in identifying HGS asymmetry, with AUC values ranging from 0.844 to 0.877. However, there was only moderate agreement between the two methods in assessing HGS asymmetry. Specifically, the Kappa values for the two Methods were 0.692, 0.694, and 0.766 in males aged 45 to 60, 60 to 80, and 80 years and above, respectively. For females, the Kappa values were 0.674, 0.661, and 0.751, respectively. These results demonstrated that the maximal or average HGS values from two trials using both hands has a significant impact on the consequent identification of HGS asymmetry.

Clearance rates of sand-burrowed and laterally pressed unburrowed Pismo clam Tivela stultorum (Mawe 1823) in a laboratory open-flow system.

Pismo clam extraction is currently banned in Mexico to help the recovery of natural populations. Thus, the primary objective of this study was to gain insight on its basic biology and husbandry protocols. Growth and clearance rate (CR) of sand-burrowed and sediment-free, laterally pressed adult Pismo clams were quantified in the laboratory as a function of burrowing condition, flow, temperature, and microalgal concentration using open-flow chambers. After 40 days, clams remained healthy regardless of burrowing condition and showed a hyperbolic CR response pattern to increased flow, with CR directly proportional to flows lower than 1000 ml min-1. Maximal asymptotic CR values (300 to 400 ml min-1org-1) were observed from 1000 to 2000 ml min-1. No significant CR differences were observed between burrowed and laterally pressed clams, yet microalgal concentration effects were detected, with constant maximal CRs of ∼250 ml min-1 in the range of 50 to 200 cells µl-1 and decline at higher concentrations. Maintenance protocols of laterally pressed organisms were validated in the laboratory with both weight and CR data. To our knowledge, this is the first study providing whole-body physiological data translated into effective husbandry protocols for Pismo clams. This approach represents a fresh perspective to traditional research areas, opening the possibility for continued experimentation under controlled conditions.