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PubMedDate not supplied

Modeling multiaquifer wells with MODFLOW.

Multiaquifer wells, i.e., wells that are open across more than one aquifer, can have a profound effect on the hydraulics of a ground water system. These wells change the physical system by establishing direct hydraulic links between otherwise isolated strata. Several methods are available to simulate multiaquifer wells in the context of comprehensive ground water flow simulators. In this paper, we review four methods to represent multiaquifer wells with the widely used code MODFLOW. These methods include a specialized code developed, but never formally released, by the U.S. Geological Survey (USGS), the Multi-Aquifer Well (MAW1) Package. An expanded implementation of the techniques in the MAW1 Package has been incorporated in the Multi-Node Well Package released recently by the USGS (Halford and Hanson 2002). We examine the performance of the methods in the context of a benchmarking study against the analytical solutions of Papadopulos (1966) and Sokol (1963). Our results demonstrate that results obtained with the MAW1 Package closely match exact solutions for pumping and nonpumping conditions, using both coarse and refined grids.

Geological Phenomena↗

PubMed2002

Dosimetric properties of the new 125I BrachySeed model LS-1 source.

The BrachySeed model LS-1 is one of the latest in a series of new brachytherapy 125I seeds that have recently become available commercially for interstitial implants. The dosimetric properties of the seed were investigated analytically, experimentally, and by Monte Carlo simulation. Following the AAPM Task Group 43 formalism, the radial dose function, dose rate constant, and anisotropy parameters were determined. Experimental measurements were made in solid water-equivalent phantoms using GafChromic MD-55-2 films, with correction for the low energy film response. Analyses were carried out from absolute measurements, as well as relative measurements against the Nycomed Amersham OncoSeed Model 6711, which also served to validate our experimental methodology. A small, but systematic difference in the absolute measurements was observed depending on the duration of the irradiation. Monte Carlo simulation was performed using the Integrated Tiger Series CYLTRAN code. We benchmarked the code by comparing the dose parameters of Model 6702 with published values. The radial dose function, g(r), of the Model LS-1 seed was computed at distances from 0.25 to 10 cm by analytical and Monte Carlo calculations with reasonably good agreement. The suggested dose rate constant, A, based on the Monte Carlo simulation is 0.90+/-0.03 cGy h(-1) U(-1). This value is smaller than, but overlaps the experimental determination of 0.98+/-0.06 cGy h(-1) U(-1). The anisotropy function, F(r, theta), and anisotropy factor, phi(an)(r), compared favorably with those of the Model 6711.

Anisotropy↗

PubMed1999

Feature extraction through LOCOCODE.

Low-complexity coding and decoding (LOCOCODE) is a novel approach to sensory coding and unsupervised learning. Unlike previous methods, it explicitly takes into account the information-theoretic complexity of the code generator. It computes lococodes that convey information about the input data and can be computed and decoded by low-complexity mappings. We implement LOCOCODE by training autoassociators with flat minimum search, a recent, general method for discovering low-complexity neural nets. It turns out that this approach can unmix an unknown number of independent data sources by extracting a minimal number of low-complexity features necessary for representing the data. Experiments show that unlike codes obtained with standard autoencoders, lococodes are based on feature detectors, never unstructured, usually sparse, and sometimes factorial or local (depending on statistical properties of the data). Although LOCOCODE is not explicitly designed to enforce sparse or factorial codes, it extracts optimal codes for difficult versions of the "bars" benchmark problem, whereas independent component analysis (ICA) and principal component analysis (PCA) do not. It produces familiar, biologically plausible feature detectors when applied to real-world images and codes with fewer bits per pixel than ICA and PCA. Unlike ICA, it does not need to know the number of independent sources. As a preprocessor for a vowel recognition benchmark problem, it sets the stage for excellent classification performance. Our results reveal an interesting, previously ignored connection between two important fields: regularizer research and ICA-related research. They may represent a first step toward unification of regularization and unsupervised learning.

Algorithms↗

PubMed2005

Prediction of MHC class II binding peptides based on an iterative learning model.

BACKGROUND: Prediction of the binding ability of antigen peptides to major histocompatibility complex (MHC) class II molecules is important in vaccine development. The variable length of each binding peptide complicates this prediction. Motivated by a text mining model designed for building a classifier from labeled and unlabeled examples, we have developed an iterative supervised learning model for the prediction of MHC class II binding peptides. RESULTS: A linear programming (LP) model was employed for the learning task at each iteration, since it is fast and can re-optimize the previous classifier when the training sets are altered. The performance of the new model has been evaluated with benchmark datasets. The outcome demonstrates that the model achieves an accuracy of prediction that is competitive compared to the advanced predictors (the Gibbs sampler and TEPITOPE). The average areas under the ROC curve obtained from one variant of our model are 0.753 and 0.715 for the original and homology reduced benchmark sets, respectively. The corresponding values are respectively 0.744 and 0.673 for the Gibbs sampler and 0.702 and 0.667 for TEPITOPE. CONCLUSION: The iterative learning procedure appears to be effective in prediction of MHC class II binders. It offers an alternative approach to this important prediction problem.

Journal Article↗

PubMed2025

Predicting host tropism in influenza a viruses: insights from multi-segment nucleotide signatures.

BACKGROUND: Influenza A virus (IAV) poses a significant public health threat due to its cross-species transmission and complex host adaptation mechanisms. This study integrated whole-genome data from avian, human, swine, and bovine IAV strains, using machine learning to predict viral host tropism based on nucleotide site features and to identify key sites driving host adaptation along with their synergistic effects. METHODS: A total of 64,000 IAV sequences from avian, human, swine, and bovine hosts were analyzed to build host-prediction models. A four-class classification framework (avian, human, swine, bovine) was constructed using nucleotide site features from all eight genomic segments (PB2, PB1, PA, HA, NP, NA, MP, NS). Eight machine learning algorithms (logistic regression, decision tree, random forest, SVM, KNN, gradient boosting, XGBoost, LightGBM) were benchmarked via 10-fold stratified cross-validation. Model performance was evaluated using accuracy, precision, recall, F1-score, AUPRC, and AUC. SHAP (SHapley Additive exPlanations) analysis prioritized critical nucleotide sites, while bivariate association tests identified synergistic/antagonistic interactions between sites. Nucleotide composition profiles were compared across host groups using hierarchical clustering and heatmap visualization. RESULTS: The XGBoost algorithm demonstrated the best and most stable performance, achieving an AUC value of over 0.95 in distinguishing human-derived sequences from non-human ones. SHAP analysis identified the top 20 critical nucleotide sites for each gene segment, such as sites 46 and 698 in the NS segment. Nucleotide composition analysis revealed high similarity between human and swine sequences in the HA and PB2 segments, and between avian and bovine sequences. The HA segment was particularly challenging in differentiating human from swine strains. Bivariate site association analysis uncovered significant synergistic or antagonistic effects between key sites within gene segments, forming complex networks. For instance, in the NS segment, a positive prediction contribution was observed when sites 371, 698, and 419 were all G. CONCLUSIONS: This study advances our mechanistic understanding of IAV host adaptation, identifies molecular determinants for zoonotic risk stratification, and establishes a scalable machine learning framework for predicting viral host tropism through nucleotide signature analysis, thereby enhancing surveillance strategies and informing preventive measures against emerging viral threats.

Influenza A virus↗

PubMed1994

Clinical Benchmark for Gastric Stapling Procedures.

To help answer the call to cut costs of surgical care, hospitals and physicians have joined to compare methods of care for the more common Diagnosis Related Group (DRG) diagnoses to form a Benchmark. Since many bariatric surgeons are the only ones performing this surgery in their primary hospitals, they do not have two or more surgical routines for comparison. This presentation compares data for the preoperative work-up, operating-room, and methods of postoperative care used by 29 members of the American Society for Bariatric Surgery (ASBS). There was representation of both academic and private surgeons and hospitals. To target areas for possible savings, the hospital bills of 16 patients without complication were compared. The synthesis of this information revealed significant differences in the extent and cost of preoperative work-up, antibiotic coverage, other postoperative care, and length of stay. These differences are examined under the assumption that patient outcome was the same.

Journal Article↗

PubMed2001

New study surveys data on operating room efficiency.

The folks doing knee and hip replacement surgery at Bryn Mawr (PA) Hospital must be doing something right: For the second year in a row, the 330-bed hospital has been named Best Performer for operating room effectiveness and efficiency by OR Benchmarks, a Santa Fe, NM-based benchmarking company. The hospital was one of a dozen studied that provided data to OR Benchmarks on 51 cases of total knee replacements. Thus far, the company has collected data on 880 cases over the past five years. Data collected ranged from cost of supplies to use of clinical pathways.

Arthroplasty, Replacement, Hip↗

PubMed1995

The Benchmarking Effort for Networking Children's Hospitals (BENCHmark).

BACKGROUND: In 1992, 12 large children's hospitals established the Benchmarking Effort for Networking Children's Hospitals (BENCHmark). The goal was for the BENCHmark effort to supplement the hospitals' continuous quality improvement (CQI) programs and to speed adoption of best practices from peer institutions. For three years, the hospitals have been comparing data on cost, quality, and speed indicators. Also, "best practice" groups have met to share information on how processes can be improved. RESULTS: The BENCHmark hospitals have experienced significant process improvement in areas such as emergency department waiting time and admitting process time. EXAMPLE: The BENCHmark hospitals selected admitting as one of the first best practice groups to meet. Interdisciplinary staff from all BENCHmark hospitals met three times over the course of a year to define their indicator and share information on best practices. St Louis Children's Hospital, as a result, instituted a pre-arrival team and cross-trained staff, with the result being a reduction of admitting processing time from 58 minutes to 19 minutes. Same-day surgery patients now bypass the admitting department and go directly to the surgical floor. Patient and surgeon satisfaction has increased greatly. CONCLUSIONS: Hospitals that are planning to benchmark are encouraged to reach consensus on project goals and to focus on indicators that provide a clear business advantage. Physician involvement is key to improving performance and physicians will only be engaged if the hospitals against whom they are benchmarked are considered peers. Being willing to share initial data openly seems to be a key factor in determining successful integration of the BENCHmark process into hospital CQI efforts. The BENCHmark project has been so successful that a second group of 12 comparable pediatric institutions, known as the Network II, has been established.

Efficiency, Organizational↗

PubMed1998

Trials and tribulations of vascular surgical benchmarking.

BACKGROUND: Benchmarking is a new tool to assess the efficiency of different hospitals. Classification of operations using healthcare resource groups (HRGs) is related to parameters including number of cases, length of stay (LOS) and age profile. METHODS: A National Comparative Database was used to compare three hospitals. Analysis was confined to the major HRGs involved with vascular/venous surgery. RESULTS: For high-volume low-complexity varicose vein surgery, all three hospitals had similar numbers of patients and LOS. In contrast, the LOS for routine vascular operations in hospital A was double that in hospital B (16.3 versus 7.4 days). Hospital A had three times as many patients classified as 'other - peripheral vascular disease' as hospital C and six times as many as hospital B (329, 49 and 111 for hospitals A, B and C respectively). LOS following major amputation in hospitals A and C was nearly double that in hospital B (32.4, 18.3 and 33.6 days for hospitals A, B and C respectively). CONCLUSION: There were a number of significant variations between the three hospitals during the 9-month interval. Explanations included the methods of coding, local facilities including availability of rehabilitation beds and difference in the patients' age profiles. Benchmarking in its present format reveals a number of variations which may not necessarily reflect real differences in clinical performance.

Benchmarking↗

PubMed2005

A neural strategy for the inference of SH3 domain-peptide interaction specificity.

BACKGROUND: The SH3 domain family is one of the most representative and widely studied cases of so-called Peptide Recognition Modules (PRM). The polyproline II motif PxxP that generally characterizes its ligands does not reflect the complex interaction spectrum of the over 1500 different SH3 domains, and the requirement of a more refined knowledge of their specificity implies the setting up of appropriate experimental and theoretical strategies. Due to the limitations of the current technology for peptide synthesis, several experimental high-throughput approaches have been devised to elucidate protein-protein interaction mechanisms. Such approaches can rely on and take advantage of computational techniques, such as regular expressions or position specific scoring matrices (PSSMs) to pre-process entire proteomes in the search for putative SH3 targets. In this regard, a reliable inference methodology to be used for reducing the sequence space of putative binding peptides represents a valuable support for molecular and cellular biologists. RESULTS: Using as benchmark the peptide sequences obtained from in vitro binding experiments, we set up a neural network model that performs better than PSSM in the detection of SH3 domain interactors. In particular our model is more precise in its predictions, even if its performance can vary among different SH3 domains and is strongly dependent on the number of binding peptides in the benchmark. CONCLUSION: We show that a neural network can be more effective than standard methods in SH3 domain specificity detection. Neural classifiers identify general SH3 domain binders and domain-specific interactors from a PxxP peptide population, provided that there are a sufficient proportion of true positives in the training sets. This capability can also improve peptide selection for library definition in array experiments. Further advances can be achieved, including properly encoded domain sequences and structural information as input for a global neural network.

Amino Acid Motifs↗

PubMed2005

Empirical analysis of locality, heritability and heuristic bias in evolutionary algorithms: a case study for the multidimensional knapsack problem.

Our main aim is to provide guidelines and practical help for the design of appropriate representations and operators for evolutionary algorithms (EAs). For this purpose, we propose techniques to obtain a better understanding of various effects in the interplay of the representation and the operators. We study six different representations and associated variation operators in the context of a steady-state evolutionary algorithm for the multidimensional knapsack problem. Four of them are indirect decoder-based techniques, and two are direct encodings combined with different initialization, repair, and local improvement strategies. The complex decoders and the local improvement and repair strategies make it practically impossible to completely analyze such EAs in a fully theoretical way. After comparing the general performance of the chosen EA variants for the multidimensional knapsack problem on two benchmark suites, we present a hands-on approach for empirically analyzing important aspects of initialization, mutation, and crossover in an isolated fashion. Static, inexpensive measurements based on randomly created solutions are performed in order to quantify and visualize specific properties with respect to heuristic bias, locality, and heritability. These tests shed light onto the complex behavior of such EAs and point out reasons for good or bad performance. In addition, the proposed measures are also examined during actual EA runs, which gives further insight into dynamic aspects of evolutionary search and verifies the validity of the isolated static measurements. All measurements are described in a general way, allowing for an easy adaption to other representations and problems.

Algorithms↗

PubMed1996

Applying performance measures to long-term care.

BACKGROUND: Nine nursing facilities in Mississippi participated in the American Health Care Association's Quality Indicator Index and Education (QUIIX-Ed) project to apply quantitative performance measurements to continuous quality improvement in long-term care. Begun in May 1994, with the first collection of performance measurement data in March 1995, the project used 15 measures of clinical care based on standardized assessments of resident conditions. METHODOLOGY: QUIIX-Ed assessed the impact of quality indicator information in nursing facilities based on Minimum Data Set resident assessments. Comparison reports allow each facility to profile its performance against that of other providers in the project. The project does not standardize the quality improvement process: the focus is on the incorporation of information into existing nursing care and quality improvement practices. OPERATIONAL ISSUES: Each month the facilities updated their quality indicator scores and exported those scores to a central database that aggregated scores to generate benchmarking statistics for each facility, including project medians, percentiles, and facility performance rankings. EXAMPLES: Two case studies on bedfast residents and restraint use illustrate the process of examining care issues identified by quality indicators, developing appropriate interventions, and evaluating the efficacy of the intervention. DISCUSSION: The limited intervention of introducing quantitative care measurements had a significant impact on resident outcomes and the nursing process. These measurements are readily incorporated into existing nursing practices and facility improvement efforts, regardless of the extent to which the quality improvement process has been developed.

Computer Communication Networks↗

PubMed1999

Monitoring anatomic pathology practice through quality assurance measures.

This article describes the art and science of continuous performance measurement and applications for quality improvement in anatomic pathology. Numerous novel benchmarks derived from multi-institutional data acquired from the College of American Pathologists Q-Probes quality improvement program are illustrated as they relate to specific disciplines in anatomic pathology and aspects of the total testing cycle. Comparative data quantifying performance deficiencies and opportunities for practice improvement are also identified.

Humans↗

PubMedDate not supplied

Benchmarking: a case report.

In mid 1993, administrators and physicians at Bristol Medical Center teams up with HCIA to perform clinical pathway analysis on five diagnosis related groups. The major goal of this project was to establish a partnership between the hospital administration and the medical staff to meet or beat existing benchmarks.

Critical Pathways↗

PubMed2006