Comparison of Full-Reference Image Quality Models for Optimization of Image Processing Systems

The performance of objective image quality assessment (IQA) models has been evaluated primarily by comparing model predictions to human quality judgments. Perceptual datasets gathered for this purpose have provided useful benchmarks for improving IQA methods, but their heavy use creates a risk of overfitting. Here, we perform a large-scale comparison of IQA models in terms of their use as objectives for the optimization of image processing algorithms. Specifically, we use eleven full-reference IQA models to train deep neural networks for four low-level vision tasks: denoising, deblurring, super-resolution, and compression. Subjective testing on the optimized images allows us to rank the competing models in terms of their perceptual performance, elucidate their relative advantages and disadvantages in these tasks, and propose a set of desirable properties for incorporation into future IQA models.

Development and characterization of an all-in-one gamma probe with auto-peak detection for sentinel lymph node biopsy based on NEMA NU3-2004 standard

Background

A gamma probe is a handheld device used for intraoperative interventions following interstitial injection of a radiotracer to locate regional lymph nodes through the external detection of radiation. This work reports on the design and performance evaluation of a novel fully integrated gamma probe (GammaPen), recently developed by our group.

Materials and methods

GammaPen is an all-in-one pocket gamma probe with low weight and adequate dimensions, consisting of a detector, a control unit and output all together. The detector module consists of a cylindrical Thallium-activated Cesium Iodide [CsI (Tl)] crystal optically coupled to a Silicon photomultiplier (SiPM), shielded using Tungsten housing on side and back faces. The electronics of the probe consists of two small boards to handle signal processing and analog peak detection tasks. A number of parameters, including probe sensitivity in air/water, spatial resolution in air/water, angular resolution in air/water, and side and back shielding effectiveness, were measured to evaluate the performance of the probe based on NEMA NU3-2004 standards.

Results

The sensitivity of the probe in air at distances of 10, 30, and 50 mm is 18784, 3500, and 1575 cps/MBq. The sensitivity in scattering medium was also measured at distances of 10, 30, and 50 mm as 17,680, 3050, and 1104 cps/MBq. The spatial and angular resolutions in scattering medium were 47 mm and 87 degree at 30 mm distance from the probe, while they were 40 mm and 77 degree in air. The detector shielding effectiveness and leakage sensitivity are 99.91% and 0.09%, respectively.

Conclusion

The performance characterization showed that GammaPen can be used effectively for sentinel lymph node localization. The probe was successfully used in several surgical interventions by an experienced surgeon confirming its suitability in a clinical setting.

NEMA NU2-2012 performance measurements of the United Imaging uPMR790: an integrated PET/MR system

PURPOSE

In this paper, we aimed to evaluate the positron emission tomography (PET) performance of, to the best of our knowledge, the third commercially available whole-body integrated PET/magnetic resonance (MR) system.

METHODS

The PET system performance was measured following the NEMA standards with and without simultaneous MR operation. PET spatial resolution, sensitivity, scatter fraction, count-rate performance, accuracy of count losses and random corrections, image quality, and time-of-flight (TOF) resolution were quantitatively evaluated. Clinical scans were acquired at the PET/MR system and compared with images acquired at a PET/CT with the same digital detector technology.

RESULTS

Measurement results of essential PET performance were reported in the form of MR idle (MR pulsing). The axial, radial, and tangential spatial resolutions were measured as 2.72 mm (2.73 mm), 2.86 mm (2.85 mm), and 2.81 mm (2.82 mm) FWHM, respectively, at 1 cm radial offset. The NECR peak was measured as 129.2 kcps (129.5 kcps) at 14.7 kBq mL^-1 (14.2 kBq mL^-1). The scatter fraction at NECR peak was 37.9% (36.5%), and the maximum slice error below NECR was 4.1% (4.5%). Contrast recovery coefficients ranged from 51.8% (52.3%) for 10 mm hot sphere to 87.3% (87.2%) for 37 mm cold sphere. TOF resolution at 5.3 kBq mL^-1 was measured at 535 ps (540 ps). With point source, TOF was measured to be 474 ps (485 ps). Clinical scans revealed similar image quality from the PET/MR and the comparative PET/CT system.

CONCLUSION

The PET performance of the newly introduced integrated PET/MR system is not significantly affected by the simultaneous operation of an MR sequence (2-point DIXON sequence). Measurement results demonstrate comparable performance with other state-of-the-art PET/MR systems. The clinical benefits of high spatial resolution and long axial coverage remain to be further evaluated in specific clinical imaging applications.

Development of composite mechanical peeler cum juice extractor for kinnow and sweet orange

A mechanical peeler cum juice extractor was designed and developed for simultaneous peeling and juice extraction of kinnow and sweet orange fruits. Based on the designed components and prior optimization of operational parameters for peeling of both the fruits, a functional machine was developed. Major components of the machine include spur gear assembly (Φ 102 mm and Φ 76 mm), two fruit holders (Φ 30 mm), revolving shaft with length 570 mm, clearance of the tool for peeling 25 mm and cutting knife with length 80 mm, respectively. This peeler was operated using a motor, gear assembly and the combination of pulleys. The juice extractor was also fitted with a conical hopper having a flattened base to facilitate the juice extraction of peeled fruits. For performance evaluation, fruit rotation speed was considered as independent parameter and was varied at 220, 260, 280, 300, 360 rpm, whereas peeling time (s), peeling efficiency (%), peel remained on fruit (%) and juice loss (%) were taken as dependent parameters. The machine resulted in best performance at fruit rotational speed of 220 rpm (kinnow) and 260 rpm (sweet orange) with higher peeling efficiency and minimum juice loss. The capacity for peeling and juicing operation was 60-90 kg/h (kinnow) and 50-60 kg/h (sweet orange), respectively. This composite peeling cum juice extractor machine can find its applicability in cottage citrus fruit juice processing industries as well as for the domestic juice sellers.

Measuring research in the big data era: The evolution of performance measurement systems in the Italian teaching hospitals

BACKGROUND

In the healthcare system, Teaching Hospitals(THs) not only provide care, but also train healthcare professionals and carry out research activities. Research is a fundamental pillar of THs' mission and relevant for the healthcare system monitored by Performance Evaluation Systems. Research activities can be measured using citation index services and this paper highlights differences between two services based on bibliometrics, describes opportunities and risks when performance indicators rely on data collected, controlled and validated by external services and discusses the possible impact on health policy at a system and provider level.

METHODS

A bibliometric analysis was done on data between 2014-2016 from ISI Web of Science and Scopus of 18.255 physicians working in 26 Italian THs. Quantity was defined as the number of publications and quality as Impact Factor or Field-Weighted Citation Impact.

RESULTS

Overall, 41.233 and 66.409 documents were extracted from respectively ISI Web of Science and Scopus. While benchmarking results, significant differences in ranked position both in metrics emerged.

DISCUSSION

Utilizing secondary data sources to measure research activities of THs allows benchmarking at an (inter)national level and overcoming self-referment. To utilize indicators for multiple governance purposes at the system and provider level, indicators need to be profoundly understood, require formalizations in data validation, internal analysis and a sharing process among health professionals, management and policymakers.

Does professors' gender impact how students evaluate their teaching and the recommendations for the best professor?

This study examined the impact of the professors' gender according to a student evaluation of teaching (SET) in a private university. The study took place in a private university (n = 103,833) on six different campuses in the north region of Mexico. The distribution of the professors’ gender was analyzed according to semesters, campuses, and schools. Our findings suggested that when undergraduates evaluated their professors on specific criteria concerning teaching performance, they expressed their opinion regardless of the professors' gender. However, when being asked for a single overall evaluation, as whether they would recommend the professor as one of their best professors, the students tended to favor male professors over their female peers by a slight margin. While such perceptions might not be representative of the actual teaching quality, it would be interesting in the future to delve deeper into the causes of possible biases.

Impact of DRGs-based inpatient service management on the performance of regional inpatient services in Shanghai, China: an interrupted time series study, 2013-2019

Background

The asymmetry of information brings difficulty for government to manage public hospitals. Therefore, Jiading District of Shanghai has been establishing DRGs-based inpatient service management system (ISMS) to effectively compare the output of different hospitals through DRGs, reward desired hospital performance and enhance inpatient service capacity. However, the impact of the implementation of DRGs-based inpatient service management (ISM) policy in Jiading district is still unknow. We therefore conducted this study to evaluate the impact of DRGs-based ISM policy on the performance of inpatient service since its implementation in Jiading District, Shanghai, China in 2017.

Methods

Using an interrupted time series design, we analyzed quarterly data of seven DRGs-based performance measures from the ISMS which covered all five public hospitals in Jiading District from 2013 to 2019. We utilized the segmented linear regression model to assess the change of level and trend of performance indicators before and after ISM policy. Dickey–Fuller test was used to examine the stationary of the data. Durbin-Watson test was performed to check the series autocorrelation of indicators.

Results

Significant changes in the following indicators were observed since the implementation of ISM policy. The case-mix index (CMI) level decreased by 0.103 (P < 0.05), the trend increased by 0.008 (P < 0.05). The total weight level decreased by 3719.05 (P < 0.05), and the trend increased by 250.13 (P < 0.05). The time efficiency index (TEI) level increased by 0.12 (P < 0.05), and the trend decreased by 0.01 (P < 0.05). The cost efficiency index (CEI) level increased by 0.31 (P < 0.05), and the trend decreased by 0.02 (P < 0.05). No significant difference was found in the change of DRGs number, inpatient mortality of low-risk group cases (IMLRG) and inpatient mortality of medium-to-low risk group cases (IMMLRG).

Conclusions

Findings highlight the role of ISM policy in improving the capacity and efficiency of regional inpatient service. Three prerequisites, including a good information system, high-quality EMR data, and a management team, are needed for other countries to implement their own ISM policy to help government manage public hospitals and improve the performance of regional inpatient service.

Generalized criteria for evaluating hotspot identification methods

Hotspot identification (HSID) is one of the most important components in the highway safety management process. Previous research has found that hazardous sites identified with different methods are not consistent. It is therefore necessary to evaluate the performance of various HSID methods. The existing evaluation criteria are limited to two consecutive periods, and do not consider the temporal instability of crashes. In addition, one existing criterion does not precisely evaluate HSID method under given circumstances. This paper proposed three generalized criteria to evaluate the performance of HSID methods: (1) High Crashes Consistency Test (HCCT) is proposed to evaluate HSID methods in terms of their reliabilities of identifying sites with high crash counts; (2) Common Sites Consistency Test (CSCT) is proposed to gauge HSID methods in consistently identifying a set of common sites as hazardous sites; and, (3) Absolute Rank Differences Test (ARDT) is proposed to measure the consistency of HSID methods in measuring the absolute differences in rankings. Further, three commonly used HSID methods are applied to estimate crashes on Texas rural two-lane roadway segments with eight years of crash data. The performance of these three HSID methods were evaluated to validate the proposed criteria. Comparisons between the existing criteria and the generalized criteria revealed that: (1) the generalized criteria are capable of evaluating different HSID methods over multiple periods; and (2) the generalized criteria are enhanced with a consistent result and with less discrepancy in scores of the best identified HSID method.

Key performance indicators to explain energy & economic efficiency across water utilities, and identifying suitable proxies

Water companies consume up to 8% of global energy demand, at billions of dollars' cost. Benchmarking of performance between utilities can facilitate improvements in efficiency; however, inconsistencies in benchmarking practices may obscure pathways to improvement. The aspiration was to conduct an unbiased efficiency comparison within a sample of 17 water only companies and water and sewerage companies in England and Wales, accounting for exogenous factors, whilst evaluating the accuracy of common proxies. Proxies were tested, and bias-corrected energy and economic efficiency scores with explanatory factors were analysed using a double-bootstrap data envelopment method. Bias correction altered the rankings of two companies for energy efficiency only. Results imply that on average, companies could reduce energy inputs by 91.7%, and economic inputs by 92.3%, which was symptomatic of the companies specialising in drinking water supply considerably out-performing combined water and sewerage companies. As exogenous influences were likely to be a factor in the disparity between the companies, five indicators were evaluated. The results varied but of note were average pumping head height, which displayed a significant negative effect for energy efficiency, and proportion of water passing through the largest four treatment works, that exhibited a significant negative effect on economic efficiency. Within proxy performance, population served for drinking water was an adequate replacement for volume of water produced, with results matching the core variable apart from two companies changing rank in the economic analysis. Conversely, length of water mains performed poorly when replacing capital expenditure, implying companies were on average 12.6% more efficient, resulting in ten companies changing their rank and causing explanatory variables to contradict direction of influence and significance. The findings contribute new insights for benchmarking, including how different types of water companies perform under bias-correcting methods, the degree to which factors affect efficiency and how appropriate some proxies are.

A methodology of evaluating sustainability index of a biomass processing enterprise: a case study of native cow dung-urine biorefinery

Agriculture and its allied sector contribute significantly to the gross domestic product of every country. Several small-scale enterprises engaged in waste biomass processing have been setup recently. Such industrial setups not only help in solving the waste management issues but also play an important role in offering employment at the grass root level generating a significant social impact along with economic advantage to the local entrepreneur. Hence, assessment of such biomass processing enterprise (BPE) based on economic, environment, and social parameters has become necessary. In this paper, a general framework for sustainability assessment is discussed using a case study of cow dung-urine biorefinery as a representative BPE. Real-time data of BPE has been collected for evaluation and a sustainability index (SI) is evaluated using multicriteria decision method. The SI is calculated as per the weightage assigned and value function of the indicator and criteria. The SI for the BPE was observed to be 0.69 for the chosen set of criteria and indicator and weightages. A sensitivity analysis has been performed to check the dependence of the results on the weightages assigned to various criteria and indicators. It was also observed that the results were more sensitive to the indicators having a low value function.

Nouveau design solar septic tank: Reinvented toilet technology for sanitation 4.0

The up-flow solar septic tank (UTST) and multi-soil layering (MSL) system has been developed and proposed as "Nouveau Design Solar Septic Tank". The objective of this study was to verify functionality of the integrated UTST and MSL system for treatment of toilet wastewater (or black water) under actual conditions over a year at the Asian Institute of Technology campus, Pathumthani province, central Thailand. During the operation period which involved fluctuating flow rates, ambient temperatures and black water characteristics, the UTST unit yielded satisfactory performance with the average treatment efficiencies of 92 ± 10% for total chemical oxygen demand (TCOD), 79 ± 10% for soluble chemical oxygen demand (SCOD), 93 ± 9% for total 5-days biochemical oxygen demand (TBOD) and 90 ± 12% for soluble 5-days biochemical oxygen demand (SBOD), respectively, while the MSL unit could remove 95 ± 3%, and 88 ± 15% of total kjeldahl nitrogen (TKN) and total phosphorus (TP), respectively. The effluent TCOD, TBOD, TKN, nitrite (NO₂-N), nitrate (NO₃-N), ammonia (NH₃) and TP concentrations of the integrated UTST and MSL system were 39 ± 27,8 ± 27,5 ± 5 mg/L, 2 ± 2,39 ± 24,8 ± 9,2 ± 5 and 1 ± 1 mg/L, respectively, meeting the ISO requirements. The removal efficiencies of TCOD, SCOD, TBOD and SBOD exhibited positive correlation with the ratios of TBOD/TKN, TBOD/SBOD and TBOD/TP. With high treatment efficiencies and effluent quality meeting the ISO requirements, the nouveau design solar septic tank has been demonstrated as an innovative technology toward the sanitation 4.0 concept and the Sustainable Development Goal no. 6 (SDG6).

Performance characteristics of the digital uMI550 PET/CT system according to the NEMA NU2-2018 standard

Background

The aim of this study is to conduct physical performance evaluation on the uMI550 whole-body PET/CT system according to the NEMA NU2-2018 standard.

Methods

According to the NEMA NU2-2018, spatial resolution, sensitivity, scatter fraction, count-rate performance, accuracy of count losses and random corrections, image quality, and timing resolution were evaluated. Spatial resolution was measured by using a ²²Na point source. System sensitivity was measured by inserting an ¹⁸F line-source in six concentric aluminum sleeves with varying diameters. Scatter fraction, count-rate performance, accuracy of count loss, and timing resolution were all calculated by analyzing dynamically acquired data of an ¹⁸F line-source inside a polyethylene cylinder in 20 cm diameter and 70 cm length. Image quality was assessed using a NEMA IEC body phantom with a 4:1 ratio of activity concentration of spheres to the warm background. Additionally, three patient studies were performed, with one brain scan and two whole-body scans, separately. The patient images were evaluated to get a visual first impression of uMI550.

Results

The tangential, radial, and axial spatial resolutions were measured as 2.91 mm, 2.98 mm, and 2.97 mm FWHM, respectively, at 1 cm radial offset. The total system sensitivity to line source at center was 10.24 cps/kBq. A NECR peak was measured as 124.4 kcps at 18.85 kBq/mL. The scatter fraction at NECR peak was 36.65%, and the maximum count-rate error at and below NEC peak was 1.55%. Contrast recovery coefficients were from 46.5 (10 mm) to 83.9% (37 mm). The timing resolution was measured as 372 ps at low count rate.

Conclusion

NEMA NU-2 2018 testing was performed on the new SiPM-based uMI550 PET/CT system. The uMI550 shows a high-spatial resolution of less than 3 mm and a good timing resolution of 372 ps. It shows clinical significances on improving potentially diagnostic ability on small lesions.

Comparative analysis of similarity measurements in miRNAs with applications to miRNA-disease association predictions

BACKGROUND

As regulators of gene expression, microRNAs (miRNAs) are increasingly recognized as critical biomarkers of human diseases. Till now, a series of computational methods have been proposed to predict new miRNA-disease associations based on similarity measurements. Different categories of features in miRNAs are applied in these methods for miRNA-miRNA similarity calculation. Benchmarking tests on these miRNA similarity measures are warranted to assess their effectiveness and robustness.

RESULTS

In this study, 5 categories of features, i.e. miRNA sequences, miRNA expression profiles in cell-lines, miRNA expression profiles in tissues, gene ontology (GO) annotations of miRNA target genes and Medical Subject Heading (MeSH) terms of miRNA-associated diseases, are collected and similarity values between miRNAs are quantified based on these feature spaces, respectively. We systematically compare the 5 similarities from multi-statistical views. Furthermore, we adopt a rule-based inference method to test their performance on miRNA-disease association predictions with the similarity measurements. Comprehensive comparison is made based on leave-one-out cross-validations and a case study. Experimental results demonstrate that the similarity measurement using MeSH terms performs best among the 5 measurements. It should be noted that the other 4 measurements can also achieve reliable prediction performance. The best-performed similarity measurement is used for new miRNA-disease association predictions and the inferred results are released for further biomedical screening.

CONCLUSIONS

Our study suggests that all the 5 features, even though some are restricted by data availability, are useful information for inferring novel miRNA-disease associations. However, biased prediction results might be produced in GO- and MeSH-based similarity measurements due to incomplete feature spaces. Similarity fusion may help produce more reliable prediction results. We expect that future studies will provide more detailed information into the 5 feature spaces and widen our understanding about disease pathogenesis.

Investigation of estimation performance for different soil areas

Soil plays a vital role in the climate system. This paper performs decision tree regression to estimate soil moisture (SM) by considering different parameters that include air temperature, time, relative humidity, and soil temperature. Besides, this paper investigates the effects of the parameters of decision tree regression by utilizing the response surface. The obtained estimation results of two distinct soil areas, Field and Forest, indicate that two different soil areas have distinct estimation quality. Furthermore, numerical results of the training stage show that the estimation of SM for Field and Forest soil performing decision tree regression offers 0.0019 and 0.0025 mean absolute error (MAE), respectively. Moreover, numerical results show that the interaction of the parameters of the performed algorithm plays a vital role in the estimation stage of Field and Forest soils.

Dataset for WWW landing pages webobject retrieval performance evaluation

This dataset describes data obtained from a multi-day World Wide Web (WWW) measurement campaign distributed internationally across multiple Amazon Web Service (AWS) datacentres. The Chrome web browser was controlled by the Selenium framework to make repetitive requests to several popular websites; the resulting webobjects were captured by a proxy server and details about them stored in the provided SQLite3 databases. A Python script is provided to evaluate the webobjects with respect to their configured as well as their actual expiration times, as part of our more detailed analysis that we provide in [1]. Researchers and practitioners can readily employ this dataset in their own research endeavours with little efforts for avenues of inquiry beyond webobject expiration times we described in [1], as we provide additional information about each webobject and each website visit during the measurement campaign time horizon.

Mixed-methods library evaluation integrating the patron, library, and external perspectives: The case of Namibia regional libraries

The article presents a mixed-methods evaluation of regional libraries in Namibia, which incorporates three perspectives: the patron perspective (library users), the library perspective (library staff, management, and related officials), and the external perspective (including evaluators and monitoring data). Seven data collection methods were used: patron surveys, patron panel studies, focus group discussions, key informant and staff interviews, secondary data analysis, media analysis, and observations. The goal of the evaluation was to assess library performance for both formative and summative purposes by addressing evaluation questions on areas such as library services, use, and operations. Building upon the literature review of how mixed-methods approaches can contribute to library evaluation, the aim of this article is to show how a mixed-methods evaluation can be designed to examine multi-faceted library performance and to illustrate how the evaluation design allows information complementarity and can be utilized to present diverse viewpoints of the above three perspectives. The evaluation design, analysis process, and lessons learned from this study may be useful to evaluators engaged in evaluation of public services or programs (including public libraries) that examine multiple aspects of service performance and involve a variety of stakeholders.

Efficient removal of Cu(II) organic complexes by polymer-supported, nanosized, and hydrated Fe(III) oxides through a Fenton-like process

In this study, a polymer-supported, nanosized, and hydrated Fe(III) oxide (HFOD) was developed as a Fenton-like catalyst for the efficient removal of metal complexes in water. HFOD was prepared through the irreversible impregnation of hydrated iron(III) oxide (HFO) nanoparticles into cation exchange resin and characterized through X-ray photoelectron spectroscopy (XPS) and ion chromatography. The mechanism of Cu(II) ion removal and the degradation pathway of Cu(II)-citrate were analyzed through UV-vis spectrophotometry (UV) and liquid chromatography-mass spectrometry (LC-MS). The optimal removal rate of Cu(II) and TOC by a Fenton-like reaction at pH 4 and 40 mM H₂O₂ reached 81.6 % and 75.6 %, respectively. The removal efficiency of Cu(II)-citrate was remarkably affected with the addition of humic acid. However, the addition of competitive ions did not significantly reduce the removal rate of Cu(II)-citrate, thereby proving that the Fenton-like reaction by HFOD had a certain salt tolerance. Simultaneously, hydroxyl radical (•OH) was verified as the main free radical for Cu(II)-citrate degradation in a Fenton-like reaction, and citrate degradation was a process decarboxylation. HFOD recycling experiments and stability experiments showed that HFOD had high stability with good acid/alkali resistance and showed remarkable potential in the practical application of fixed-bed as catalysts for Fenton-like reactions.

General principles of machine learning for brain-computer interfacing

Brain-computer interfaces (BCIs) are systems that translate brain activity patterns into commands that can be executed by an artificial device. This enables the possibility of controlling devices such as a prosthetic arm or exoskeleton, a wheelchair, typewriting applications, or games directly by modulating our brain activity. For this purpose, BCI systems rely on signal processing and machine learning algorithms to decode the brain activity. This chapter provides an overview of the main steps required to do such a process, including signal preprocessing, feature extraction and selection, and decoding. Given the large amount of possible methods that can be used for these processes, a comprehensive review of them is beyond the scope of this chapter, and it is focused instead on the general principles that should be taken into account, as well as discussing good practices on how these methods should be applied and evaluated for proper design of reliable BCI systems.

Development of a charcoal fired plantain (Musa paradisiaca) roasting equipment

Conventional method of roasting plantain is cumbersome and leads to the contamination of the food items with different toxicants due to contact of the food item with combustion gases. Thus, a need for a roaster oven which utilizes indirect charcoal heat for roasting plantain is of paramount importance. In this study, a charcoal fired plantain roasting equipment was designed and developed and performance testing carried out. A roaster oven with the capacity of 20 plantain fingers per batch was constructed. Experiments were conducted on the constructed system and results obtained indicated that averages of 2.42 kg of 20 plantain fingers were roasted in 21.16 min using an average of 0.61 kg of charcoal. The percentage reduction of PAHs in the plantain roasted from the roasting equipment is 99.7% in comparison with direct roasting while the percentage reduction in roasting time in the equipment is averagely 47.45% in comparison with previous similar works. The cost of producing the roasting equipment in this work is ₦36,500.00.

Supervised learning in spiking neural networks: A review of algorithms and evaluations

As a new brain-inspired computational model of the artificial neural network, a spiking neural network encodes and processes neural information through precisely timed spike trains. Spiking neural networks are composed of biologically plausible spiking neurons, which have become suitable tools for processing complex temporal or spatiotemporal information. However, because of their intricately discontinuous and implicit nonlinear mechanisms, the formulation of efficient supervised learning algorithms for spiking neural networks is difficult, and has become an important problem in this research field. This article presents a comprehensive review of supervised learning algorithms for spiking neural networks and evaluates them qualitatively and quantitatively. First, a comparison between spiking neural networks and traditional artificial neural networks is provided. The general framework and some related theories of supervised learning for spiking neural networks are then introduced. Furthermore, the state-of-the-art supervised learning algorithms in recent years are reviewed from the perspectives of applicability to spiking neural network architecture and the inherent mechanisms of supervised learning algorithms. A performance comparison of spike train learning of some representative algorithms is also made. In addition, we provide five qualitative performance evaluation criteria for supervised learning algorithms for spiking neural networks and further present a new taxonomy for supervised learning algorithms depending on these five performance evaluation criteria. Finally, some future research directions in this research field are outlined.

Comments on the NEMA NU 4-2008 Standard on Performance Measurement of Small Animal Positron Emission Tomographs

The National Electrical Manufacturers Association’s (NEMA) NU 4-2008 standard specifies methodology for evaluating the performance of small-animal PET scanners. The standard’s goal is to enable comparison of different PET scanners over a wide range of technologies and geometries used. In this work, we discuss if the NEMA standard meets these goals and we point out potential flaws and improvements to the standard.For the evaluation of spatial resolution, the NEMA standard mandates the use of filtered backprojection reconstruction. This reconstruction method can introduce star-like artifacts for detectors with an anisotropic spatial resolution, usually caused by parallax error. These artifacts can then cause a strong dependence of the resulting spatial resolution on the size of the projection window in image space, whose size is not fully specified in the NEMA standard. If the PET ring has detectors which are perpendicular to a Cartesian axis, then the resolution along this axis will typically improve with larger projection windows.We show that the standard’s equations for the estimation of the random rate for PET systems with intrinsic radioactivity are circular and not satisfiable. However, a modified version can still be used to determine an approximation of the random rates under the assumption of negligible random rates for small activities and a constant scatter fraction. We compare the resulting estimated random rates to random rates obtained using a delayed coincidence window and two methods based on the singles rates. While these methods give similar estimates, the estimation method based on the NEMA equations overestimates the random rates.In the NEMA standard’s protocol for the evaluation of the sensitivity, the standard specifies to axially step a point source through the scanner and to take a different scan for each source position. Later, in the data analysis section, the standard does not specify clearly how the different scans have to be incorporated into the analysis, which can lead to unclear interpretations of publicized results.The standard’s definition of the recovery coefficients in the image quality phantom includes the maximum activity in a region of interest, which causes a positive correlation of noise and recovery coefficients. This leads to an unintended trade-off between desired uniformity, which is negatively correlated with variance (i.e., noise), and recovery.With this work, we want to start a discussion on possible improvements in a next version of the NEMA NU-4 standard.

An analytical model to evaluate reminders for medication adherence

OBJECTIVES

Several interventions have been proposed to improve medication adherence including those using reminders. The performance of reminders, including effectiveness and side effects, varies widely in different settings. We must study this for improving decision making on how, when, and where to use what type of reminders.

METHODS

Analytical modeling is an effective and low-cost method to derive preliminary or intermediate results and insights for further study of interventions for medication adherence. We developed an analytical model that can be used to evaluate the performance of reminders in various settings, including effectiveness, side effects, and healthcare cost savings for medication adherence.

RESULTS

Context-aware reminders perform better than simple reminders for willing patients even when they completely rely on reminders for taking their doses. Simple reminders lead to more side effects than context-aware reminders. Further, context-aware reminders generate more healthcare savings without side effects and a comparable cost of the intervention. The results contribute to an improved understanding of reminders and are used to derive a set of guidelines for patients, healthcare professionals, decision-makers, and mobile app developers.

CONCLUSIONS

The proposed model is a low cost and effective tool to derive results and insights for the use of reminders in different settings to improve medication adherence. Therefore, the model can be utilized as a decision-making tool for deciding whether to pursue an RCT on healthcare interventions. The analytical model can be extended for complex scenarios of multiple interdependent medications, adaptation with patients' condition and behavior, and composite interventions.

Evaluation of the Beckman Coulter DxC 700 AU chemistry analyzer

OBJECTIVES

We evaluated and defined the analytical performance of the Beckman Coulter DxC 700 AU analyzer compared to the Siemens Dimension Vista 500 analyzer.

DESIGN

and Methods: Performance characteristics included intra and inter-run precision, linearity/analytical measurement range, method correlation, and reference range verification. A total of 53 assays including 11 critical care, 19 general chemistries, 11 proteins, 10 urines, and 2 CSF analytes were tested. We also evaluated similarities and differences in assay methodologies between the 2 systems.

RESULTS

The DxC 700 AU demonstrated excellent precision, comparable analytical measurement ranges and strong method correlation with the Dimension Vista 500 for most serum/plasma assays. 95% of the intra-run and 95% of the inter-run precision QC levels showed <3.0%CV and <6.0%CV, respectively. None of the deviations were clinically significant. The AMRs for all analytes except 5 met the manufacturer's stated range. ALP, Lactate, U-glucose and CSF-glucose all recovered above the stated upper limit range, while prealbumin showed a smaller range. All analytes, except 14, showed slopes between 0.9 and 1.1 and/or biases <10%. Only ammonia, ferritin and lipase required significant reference range changes. The urine and CSF assays correlated very well with no adjustments in reference ranges required.

CONCLUSIONS

The analytical performance of the DxC 700 AU analyzer was acceptable with only a small number of analytes requiring significant reference range changes.

Does the Central Environmental Inspection actually work?

Central Environmental Inspection (CEI) is a particularly important innovative strategy in the transition of environmental governance in China. The first round of CEI for all provincial regions in mainland China has been finished by the end of 2017, but its actual performance remains to be seen. In this study, a multi-dimensional index system was developed under the framework of Balanced Scorecard. Using the content analysis method, we comprehensively evaluated the performance of CEIs in all provinces inspected from the perspectives of target achievement, local rectification, direct effect, and social involvement. The results indicate that CEI has made encouraging progress in the area of environmental governance and the accumulated experiences of the inspections in the early stage greatly boosted the subsequent performance of CEIs. The provincial performance of the central region was significantly higher than that of other regions. For target achievement, the focal points has been basically realized. Despite some neglect of CEI feedback, local environmental governance is experiencing a promising shift from passive to active in general. For social involvement, the CEI has not only promoted the awakening of public environmental consciousness, but also driven public participation in environmental protection. It is notable that the implementation of environmental co-responsibility between Party and governmental officials needs to be further improved. In addition, the shortcomings of each province were identified as well and policy recommendations for existing problems were offered to guide future optimization of local environmental governance and CEI practice.

Managing the performance of general practitioners and specialists referral networks: A system for evaluating the heart failure pathway

High quality chronic disease management requires coordinated care across different healthcare settings, involving multidisciplinary teams of professionals, and performance evaluation systems able to measure this care. Inter-organizational performance should be measured considering the professional relationships between general practitioners (GPs) and specialists, who are usually linked through informal referral networks. The aim of this paper is to identify and evaluate the performance of naturally occurring networks of GPs and hospital-based specialists providing care for congestive heart failure (CHF) patients in Tuscany, Italy. The analysis focuses on the identification and classification of networks, following CHF patients (n = 15,841) through primary care and inpatient care using administrative data, and on the assessment of process and outcome indicators for CHF patients in these referral networks. We demonstrate the existence of informal links between GPs and hospitals based on patterns of patient flow. These networks which are not geographically based vary in the intensity of relationships and quality of care. Such referral networks may represent the most effective accountability level for chronic disease management, since they encompass the multiple care settings experienced by patients. Overall, an integrated approach to evaluation and performance management that considers the naturally occurring links between professionals working in different settings may enable more efficient, integrated care and quality improvements.

Experimental data from the simulation of on-chip communication architectures using RedScarf simulation environment

This article presents data from an extensive set of simulation-based experiments to compare the performance of on-chip communication architectures. These experiments were performed using the RedScarf simulation environment [1], which is described in the article entitled ‘RedScarf: an open-source multi-platform simulation environment for performance evaluation of Networks-on-Chip’ [2]. In the experiments presented here, several intra-chip communication architectures were compared under different traffic patterns. Latency, jitter, and throughput metrics were collected. Data is useful for researchers investigating on-chip communication architectures who need baseline data for comparison.

Performance evaluation of Cerenkov luminescence imaging: a comparison of 68Ga with 18F

BACKGROUND

Cerenkov Luminescence Imaging (CLI) is an emerging technology for intraoperative margin assessment. Previous research only evaluated radionuclide 18-Fluorine (¹⁸F); however, for future applications in prostate cancer, 68-Gallium (⁶⁸Ga) seems more suitable, given its higher positron energy. Theoretical calculations predict that ⁶⁸Ga should offer a higher signal-to-noise ratio than ¹⁸F; this is the first experimental confirmation. The aim of this study is to investigate the technical performance of CLI by comparing ⁶⁸Ga to ¹⁸F.

RESULTS

The linearity of the system, detection limit, spatial resolution, and uniformity were determined with the LightPath imaging system. All experiments were conducted with clinically relevant activity levels in vitro, using dedicated phantoms. For both radionuclides, a linear relationship between the activity concentration and detected light yield was observed (R² = 0.99). ⁶⁸Ga showed approximately 22 times more detectable Cerenkov signal compared to ¹⁸F. The detectable activity concentration after a 120 s exposure time and 2 × 2 binning of ¹⁸F was 23.7 kBq/mL and 1.2 kBq/mL for ⁶⁸Ga. The spatial resolution was 1.31 mm for ¹⁸F and 1.40 mm for ⁶⁸Ga. The coefficient of variance of the uniformity phantom was 0.07 for the central field of view.

CONCLUSION

⁶⁸Ga was superior over ¹⁸F in terms of light yield and minimal detection limit. However, as could be expected, the resolution was 0.1 mm less for ⁶⁸Ga. Given the clinical constraints of an acquisition time less than 120 s and a spatial resolution < 2 mm, CLI for intraoperative margin assessment using ⁶⁸Ga could be feasible.

Nanomaterials-based treatment options for chromium in aqueous environments

Sustainable development and the restoration of ecosystems are the important goals for civilization. Currently, heavy metal contamination of aquatic environments has become a serious issue. Chromium (Cr) is simultaneously an essential metallic element and one of 20 chemicals posing a maximum threat to living beings. To mitigate that threat, various treatment methods have been developed, including adsorption, electrocoagulation, photoelectrocatalysis, fuel cells, bioremediation, chemical precipitation, ultrafiltration, ion exchange, and co-precipitation. However, selection of the most energy- and cost-efficient wastewater treatment option has proven challenging, as each approach is subject to shortcomings involving energy consumption, treatment capacity, and efficiency. This review describes the potential role of diverse functional nanomaterials (e.g., iron/iron oxide nanoparticles, carbon nanostructures, metal organic frameworks, and their commercial counterparts) in treatment of Cr in aqueous environments with respect to key figure of merits, such as, adsorption capacity, removal efficiency, and partition coefficient. In addition, their performance was compared with the most common treatment options. The results of this study will help determine the most effective and economical options for control of Cr in aquatic environments.

Automated Detection of Alzheimer's Disease Using Brain MRI Images- A Study with Various Feature Extraction Techniques

The aim of this work is to develop a Computer-Aided-Brain-Diagnosis (CABD) system that can determine if a brain scan shows signs of Alzheimer's disease. The method utilizes Magnetic Resonance Imaging (MRI) for classification with several feature extraction techniques. MRI is a non-invasive procedure, widely adopted in hospitals to examine cognitive abnormalities. Images are acquired using the T2 imaging sequence. The paradigm consists of a series of quantitative techniques: filtering, feature extraction, Student's t-test based feature selection, and k-Nearest Neighbor (KNN) based classification. Additionally, a comparative analysis is done by implementing other feature extraction procedures that are described in the literature. Our findings suggest that the Shearlet Transform (ST) feature extraction technique offers improved results for Alzheimer's diagnosis as compared to alternative methods. The proposed CABD tool with the ST + KNN technique provided accuracy of 94.54%, precision of 88.33%, sensitivity of 96.30% and specificity of 93.64%. Furthermore, this tool also offered an accuracy, precision, sensitivity and specificity of 98.48%, 100%, 96.97% and 100%, respectively, with the benchmark MRI database.

Practical determination of LODP (limit of detection for microarray platform) for the evaluation of microarray platforms

The performance indicator called limit of detection for microarray platform (LODP) was defined in ISO 16578:2013. The methods to determine practical LODP were explored. In general, + 3 SD of the background is used as the signal strength of limit of detection and criteria for dividing positive and negative results. Since the negative signal had been defined differently for each microarray platform, signals obtained from Non-Probe Spots (NPS) installed on the microarrays were defined as the "background" of microarrays. LODP was determined as the lowest concentration of which the average signal exceeded Avg. + 3 SD of the background (NPS) and the signal was significantly different from those of the lower and higher adjacent concentration points measured with a diluted series of reference materials. For reliable qualitative analysis, the positive results can be defined as signals higher than those corresponding to LODP and negative results as lower signals, without determining limit of detection for all target probes. The use of LODP also enables comparisons of platform performances without checking sequence dependencies, and assists to select reliable and fitting platforms for experimental purposes.

FLAIR2 improves LesionTOADS automatic segmentation of multiple sclerosis lesions in non-homogenized, multi-center, 2D clinical magnetic resonance images

Background

Accurate segmentation of MS lesions on MRI is difficult and, if performed manually, time consuming. Automatic segmentations rely strongly on the image contrast and signal-to-noise ratio. Literature examining segmentation tool performances in real-world multi-site data acquisition settings is scarce.

Objective

FLAIR², a combination of T₂-weighted and fluid attenuated inversion recovery (FLAIR) images, improves tissue contrast while suppressing CSF. We compared the use of FLAIR and FLAIR² in LesionTOADS, OASIS and the lesion segmentation toolbox (LST) when applied to non-homogenized, multi-center 2D-imaging data.

Methods

Lesions were segmented on 47 MS patient data sets obtained from 34 sites using LesionTOADS, OASIS and LST, and compared to a semi-automatically generated reference. The performance of FLAIR and FLAIR² was assessed using the relative lesion volume difference (LVD), Dice coefficient (DSC), sensitivity (SEN) and symmetric surface distance (SSD). Performance improvements related to lesion volumes (LVs) were evaluated for all tools. For comparison, LesionTOADS was also used to segment lesions from 3 T single-center MR data of 40 clinically isolated syndrome (CIS) patients.

Results

Compared to FLAIR, the use of FLAIR² in LesionTOADS led to improvements of 31.6% (LVD), 14.0% (DSC), 25.1% (SEN), and 47.0% (SSD) in the multi-center study. DSC and SSD significantly improved for larger LVs, while LVD and SEN were enhanced independent of LV. OASIS showed little difference between FLAIR and FLAIR², likely due to its inherent use of T₂w and FLAIR. LST replicated the benefits of FLAIR² only in part, indicating that further optimization, particularly at low LVs is needed. In the CIS study, LesionTOADS did not benefit from the use of FLAIR² as the segmentation performance for both FLAIR and FLAIR² was heterogeneous.

Conclusions

In this real-world, multi-center experiment, FLAIR² outperformed FLAIR in its ability to segment MS lesions with LesionTOADS. The computation of FLAIR² enhanced lesion detection, at minimally increased computational time or cost, even retrospectively. Further work is needed to determine how LesionTOADS and other tools, such as LST, can optimally benefit from the improved FLAIR² contrast.

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FLAIR² improves automatic MS lesion segmentation with LesionTOADS compared to FLAIR.

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Segmentation similarity improves for higher lesion volumes, particularly for FLAIR².

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FLAIR² provides greater sensitivity independent of lesion volume than FLAIR alone.

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Other segmentation tools need further optimization to fully benefit from FLAIR².

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FLAIR² provides immediate benefits at 1.5 T and visually improves segmentation at 3 T.

Taxonomy based performance metrics for evaluating taxonomic assignment methods

Background

Metagenomics experiments often make inferences about microbial communities by sequencing 16S and 18S rRNA, and taxonomic assignment is a fundamental step in such studies. This paper addresses the weaknesses in two types of metrics commonly used by previous studies for measuring the performance of existing taxonomic assignment methods: Sequence count based metrics and Binary error measurement. These metrics made performance evaluation results biased, less informative and mutually incomparable.

Results

We investigated weaknesses in two types of metrics and proposed new performance metrics including Average Taxonomy Distance (ATD) and ATD_by_Taxa, together with the visualized ATD plot.

Conclusions

By comparing the evaluation results from four popular taxonomic assignment methods across three test data sets, we found the new metrics more robust, informative and comparable.

Performance evaluation of the Diasorin LIAISON® XL Zika capture IgM CLIA test

Because Zika virus (ZIKV) can cause serious birth defects and is involved in cases of Guillain-Barré syndrome, the ZIKV outbreak in the American continent in 2015 resulted in an enormous need for ZIKV diagnostic tools. We evaluated the LIAISON® XL Zika Capture IgM test on 106 samples from patients, mainly travelers, with a confirmed or probable ZIKV infection. Sensitivity between 0 and 84 days after onset of symptoms was 92.5%. Specificity was evaluated on a panel of 56 samples known to cause possible cross-reactions. Cross-reaction with DENV antibodies was limited (10.5%) but false-positive results occurred in samples from patients with malaria, CMV and EBV infections.

Automated detection of congestive heart failure from electrocardiogram signal using Stockwell transform and hybrid classification scheme

BACKGROUND AND OBJECTIVE

The congestive heart failure (CHF) is a life-threatening cardiac disease which arises when the pumping action of the heart is less than that of the normal case. This paper proposes a novel approach to design a classifier-based system for the automated detection of CHF.

METHODS

The approach is founded on the use of the Stockwell (S)-transform and frequency division to analyze the time-frequency sub-band matrices stemming from electrocardiogram (ECG) signals. Then, the entropy features are evaluated from the sub-band matrices of ECG. A hybrid classification scheme is adopted taking the sparse representation classifier and the average of the distances from the nearest neighbors into account for the detection of CHF. The proposition is validated using ECG signals from CHF subjects and normal sinus rhythm from public databases.

RESULTS

The results reveal that the proposed system is successful for the detection of CHF with an accuracy, a sensitivity and a specificity values of 98.78%, 98.48%, and 99.09%, respectively. A comparison with the existing approaches for the detection of CHF is accomplished.

CONCLUSIONS

The time-frequency entropy features of the ECG signal in the frequency range from 11 Hz to 30 Hz have higher performance for the detection of CHF using a hybrid classifier. The approach can be used for the automated detection of CHF in tele-healthcare monitoring systems.

Analytical and Clinical Performance of the Nanopia Krebs von den Lungen 6 Assay in Korean Patients With Interstitial Lung Diseases

BACKGROUND

Krebs von den Lungen 6 (KL-6) is a sensitive marker for diagnosing, monitoring, and predicting the prognoses of interstitial lung diseases (ILDs). This study aimed to evaluate the performance of the Nanopia KL-6 assay (Sekisui Medical, Tokyo, Japan) and to test the relationship between KL-6 concentrations and clinical results.

METHODS

In total, 230 patients diagnosed as having ILDs were enrolled. All underwent high-resolution computed tomography (HRCT) followed by the pulmonary function test (PFT). We also enrolled 116 disease controls and 200 healthy controls. Evaluation of the Nanopia KL-6 assay involved determination of precision, linearity, and limit of quantification (LOQ). Results from the Nanopia KL-6 assay were compared with those from ELISA and correlated with the HRCT and PFT results.

RESULTS

The within-laboratory precisions were <2% of CV, and linearity was acceptable between 52.2 and 4,966.5 U/mL. The LOQ was 45.2 U/mL. Nanopia and ELISA results were strongly correlated (r=0.979). The average concentration of KL-6 was greater in ILD patients (711.5 U/mL) than in the disease (168.4 U/mL) and healthy (209.4 U/mL) controls. Serum KL-6 concentrations were strongly and moderately correlated with the extent of lung involvement and presence of typical HRCT abnormalities, respectively, and moderately correlated with PFT parameters.

CONCLUSIONS

The overall analytical and clinical performance of the Nanopia KL-6 assay was acceptable. Our study is the first to compare assay platforms and show correlations between KL-6 concentrations and HRCT or PFT results in Korean ILD patients.

Analyzing big datasets of genomic sequences: fast and scalable collection of k-mer statistics

Background

Distributed approaches based on the MapReduce programming paradigm have started to be proposed in the Bioinformatics domain, due to the large amount of data produced by the next-generation sequencing techniques. However, the use of MapReduce and related Big Data technologies and frameworks (e.g., Apache Hadoop and Spark) does not necessarily produce satisfactory results, in terms of both efficiency and effectiveness. We discuss how the development of distributed and Big Data management technologies has affected the analysis of large datasets of biological sequences. Moreover, we show how the choice of different parameter configurations and the careful engineering of the software with respect to the specific framework under consideration may be crucial in order to achieve good performance, especially on very large amounts of data. We choose k-mers counting as a case study for our analysis, and Spark as the framework to implement FastKmer, a novel approach for the extraction of k-mer statistics from large collection of biological sequences, with arbitrary values of k.

Results

One of the most relevant contributions of FastKmer is the introduction of a module for balancing the statistics aggregation workload over the nodes of a computing cluster, in order to overcome data skew while allowing for a full exploitation of the underlying distributed architecture. We also present the results of a comparative experimental analysis showing that our approach is currently the fastest among the ones based on Big Data technologies, while exhibiting a very good scalability.

Conclusions

We provide evidence that the usage of technologies such as Hadoop or Spark for the analysis of big datasets of biological sequences is productive only if the architectural details and the peculiar aspects of the considered framework are carefully taken into account for the algorithm design and implementation.

A combined mono- and multi-turbine approach for fault indicator synthesis and wind turbine monitoring using SCADA data

The monitoring of wind turbines using SCADA data has received lately a growing interest from the fault diagnosis community because of the very low cost of these data, which are available in number without the need for any additional sensor. Yet, these data are highly variable due to the turbine constantly changing its operating conditions and to the rapid fluctuations of the environmental conditions (wind speed and direction, air density, turbulence, …). This makes the occurrence of a fault difficult to detect. To address this problem, we propose a multi-level (turbine and farm level) strategy combining a mono- and a multi-turbine approach to create fault indicators insensitive to both operating and environmental conditions. At the turbine level, mono-turbine residuals (i.e. a difference between an actual monitored value and the predicted one) obtained with a normal behavior model expressing the causal relations between variables from the same single turbine and learnt during a normal condition period are calculated for each turbine, so as to get rid of the influence of the operating conditions. At the farm level, the residuals are then compared to a wind farm reference in a multi-turbine approach to obtain fault indicators insensitive to environmental conditions. Indicators for the objective performance evaluation are also proposed to compare wind turbine fault detection methods, which aim at evaluating the cost/benefit of the methods from a production manager's point of view. The performance of the proposed combined mono- and multi-turbine method is evaluated and compared to more classical methods proposed in the literature on a large real data set made of SCADA data recorded on a French wind farm during four years : it is shown than it can improve the fault detection performance when compared to a residual analysis limited at the turbine level only.

A novel robotic system for vascular intervention: principles, performances, and applications

PURPOSE

This paper describes the design, principles, performances, and applications of a novel image-guided master-slave robotic system for vascular intervention (VI), including the performance evaluation and in vivo trials.

METHODS

Based on the peer-to-peer (P2P) remote communication system, the kinetics analysis, the sliding-mode neural network self-adaptive control model and the feedback system, this new robotic system can accomplish in real time a number of VI operations, including guidewire translation and rotation, balloon catheter translation, and contrast agent injection. The master-slave design prevents surgeons from being exposed to X-ray radiation, which means that they are not required to wear a heavy lead suit. We also conducted a performance evaluation of the new system, which assessed the speed, position tracking, and accuracy, as well as in vivo swine trials.

RESULTS

The speed and position tracking effects are really good, which contribute to the high level of performance in terms of the translational (error ≤ 0.45%) and rotational (error ≤ 2.6°) accuracy. In addition, the accuracy of the contrast agent injection is less than 0.2 ml. The robotic system successfully performed both the stent revascularization of an arteria carotis and four in vivo trials. The haptic feedback data correspond with the robotic-assisted procedure, and peaks and troughs of data occur regularly.

CONCLUSIONS

By means of the performance evaluation and four successful in vivo trials, the feasibility and efficiency of the new robotic system are validated, which should prove helpful for further research.

Comprehensive performance evaluation of LID practices for the sponge city construction: A case study in Guangxi, China

Sponge city construction is a new concept of urban stormwater management, which can effectively relieve urban flooding, reduce non-point source pollution, and promote the usage of rainwater resources, often including the application of Low Impact Development (LID) techniques. Although 30 cities in China have been chosen to implement sponge city construction, there is a lack of a quantitative evaluation method to evaluate the environmental, economic, and social benefits of LID practices. This paper develops a comprehensive evaluation system to quantify the benefits of different combinations of LID units using the Storm Water Management Model (SWMM) and the Analytical Hierarchy Process (AHP) method. The performance of five LID design scenarios with different locations and sizes of the bio-retention facility, the grassed swale, the sunken green space, the permeable pavement, and the storage tank were analyzed for a sports center project in Guangxi, China. Results indicated that the green scenario that contains 34.5% of bio-retention facilities and 46.0% of sunken green spaces had the best comprehensive performance regarding meeting the requirements of 75% annual total runoff reduction and the attainment of good operation performance, rainwater utilization, landscape promotion, and ecological service functions, mainly because they are micro-scale and decentralized facilities that can manage stormwater at the source through the natural process. The optimal scenario was adopted to construct the project, and the proposed evaluation system can also be applied to optimal selection and performance effect evaluation of LID practices in other sponge city projects.

ACS NSQIP Surgical Risk Calculator: Pilot Analysis on Feasibility in an Academic Safety Net Hospital

BACKGROUND

Hospitals are looking for effective methods to track outcomes that are risk-adjusted for patient population characteristics. This is especially relevant for safety net hospitals (SNHs) servicing high-risk populations and in an era of quality-based reimbursement incentives. One such program with these goals is the American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP). This is an institution-based quality audit whereby we determined the presence and consistency of charted data required to compute perioperative risk in the ACS NSQIP risk calculator.

MATERIALS AND METHODS

A retrospective chart review of 28 elective colorectal procedures was performed at an urban, academic SNH over a 1-y period. For each case, it was determined whether the required NSQIP variables were readily presented via preoperative documentation. Univariate and bivariate statistics were employed to compare data field completion rates.

RESULTS

Of the 28 reviewed patient charts, none (n = 0) had all preoperative risk documentation required to complete an ACS NSQIP risk analysis. 89.3% of charts (n = 25) had ≤ 55% of required data to complete a risk assessment. However on bivariate analysis, demographic variables were more likely to have been recorded (P < 0.001) than other risk factors.

CONCLUSIONS

Preoperative risk assessment and corresponding charting practices at the SNH reviewed was fragmented and incomplete. There was lack of definitive documentation of risk factors and preoperative interventions used to modulate risk. Under current reimbursement models such as the MACRA Quality Payment Program, these findings are crucial for like-institutions to consider to critically evaluate their own documentation practices.

A comprehensive performance evaluation of heterogeneous Bi2Fe4O9/peroxymonosulfate system for sulfamethoxazole degradation

In this study, a Bi₂Fe₄O₉ catalyst with nanoplate morphology was fabricated using a facile hydrothermal method. It was used as a catalyst to activate peroxymonosulfate (PMS) for aqueous sulfamethoxazole (SMX) removal. A comprehensive performance evaluation of the Bi₂Fe₄O₉/PMS system was conducted by investigating the effects of pH, PMS dosage, catalyst loading, SMX concentration, temperature, and halides (Cl^- and Br^-) on the degradation of SMX. The Bi₂Fe₄O₉/PMS system demonstrated a remarkable catalytic activity with >95% SMX removal within 30 min (conditions: pH 3.8, [Bi₂Fe₄O₉] = 0.1 g L^-1, [SMX]:[PMS] mol ratio =1:20). It was found that both Cl^- and Br^- can lead to the formation of PMS-induced reactive halide species (i.e. HClO, HBrO, and Br₂) which can also react with SMX forming halogenated SMX byproducts. Based on the detected degradation byproducts, the major SMX degradation pathway in the Bi₂Fe₄O₉/PMS system is proposed. The SMX degradation by Bi₂Fe₄O₉/PMS system in the wastewater secondary effluent (SE) was also investigated. The results showed that SMX degradation rate in the SE was relatively slower than in the deionized water due to (i) reactive radical scavenging by water matrix species found in SE (e.g.: dissolved organic matters (DOCs), etc.), and (ii) partial deactivation of the catalyst by DOCs. Nevertheless, the selectivity of the SO₄^•- towards SMX degradation was evidenced from the rapid SMX degradation despite the high background DOCs in the SE. At least four times the dosage of PMS is required for SMX degradation in the SE to achieve a similar SMX removal efficiency to that of the deionized water matrix.

Focus Group in Community Mental Health Research: Need for Adaption

The article presents an analysis of the use of focus groups in researching community mental health users, starting with the reasons for using them, their implementation in mental health service users' research, and the adaptations of focus group use when researching the experiences of users. Based on personal research experience and a review of scientific publications in the Google Scholar, Web of Science, ProQuest, EBSCOhost, and Scopus databases, 20 articles published between 2010 and 2016 were selected for targeted content analysis. A checklist for reporting on the use of focus groups with community mental health service users, aiming to improve the comparability, verifiability and validity was developed. Adaptations of the implementation of focus groups in relation to participants' characteristics were suggested. Focus groups are not only useful as a scientific research technique, but also for ensuring service users' participation in decision-making in community mental health and evaluating the quality of the mental health system and services .

Effect of sand dust accumulation on photovoltaic performance in the Saharan environment: southern Algeria (Adrar)

Many climatic conditions have a negative impact on production of photovoltaic (PV) systems, and sand dust could be one of the main reasons of degradation of PV panels. The objective of this study is to investigate the reduction in the electrical performance caused by sandstorm and the accumulation of sand dust on the photovoltaic module surface installed in the Saharan area of south Algeria (Adrar). For this purpose, four PV modules (ISO-100/24) were selected and their current-voltage characteristics were measured to evaluate the sand dust effect on their performances. Our results show that sandstorm and dust accumulation on the surface of the module reduce the performance in terms of energy and power, due to a decrease of the transmittance. Obtained outcomes show that in sandstorm periods, the particle deposition density is much higher. This study reveals that leaving PV module without any cleaning in the Saharan environmental conditions significantly reduces PV power output, in addition to the presence of the shading mismatch effects in case of partial cleaning.

The performance of a community-based colorectal cancer screening program: Evidence from Shanghai Pudong New Area, China

Despite the rising disease burden of colorectal cancer (CRC), CRC screening has not yet been widely introduced as a large organized program in developing countries. To facilitate better delivery of screening in these areas, we investigated the performance of a large community-based CRC screening program implemented in Shanghai Pudong New Area during the period 2013-2016. We conducted a prospective cohort study by following up the screening behavior and results of tested participants in the program. Data from the program reporting system and monthly progress reports were collected. We used standard measures and indicators with modifications to evaluate the performance of the program. Disparities in CRC screening by age categories, primary screening results, and geographic areas were examined. A total of 403,098 individuals participated in the program, 25,764 of them were further screened by diagnostic colonoscopy (COL), and 505 people were eventually diagnosed with CRC as a result of the program. The program produced the following rates: participation (35.18%), primary screening positivity (24.89%), positive primary screening follow-up (26.26%), diagnostic COL (6.37%), and cancer detection (1.25‰). Vast variations in the quality of the program were observed across areas with different socioeconomic environments. The experience and lessons from the program suggest that incorporating the screening with other public health campaigns, using better-developed risk assessment tools, and allowing individual screening decisions for those aged above the target are possible practical ways to promote a better delivery of organized CRC screening programs.

Multi-criteria decision-making for sustainable metropolitan cities assessment

The recent development of metropolitan cities, especially in Europe, requires an effective integrated management of city services, infrastructure, and communication networks at a metropolitan level. A preliminary step towards a proper organizational and management strategy of the metropolitan city is the analysis, benchmarking and optimization of the metropolitan areas through a set of indicators coherent with the overall sustainability objective of the metropolitan city. This paper proposes the use of the Analytic Hierarchy Process multi-criteria decision making technique for application in the smart metropolitan city context, with the aim of analysing the sustainable development of energy, water and environmental systems, through a set of objective performance indicators. Specifically, the 35 indicators defined for the Sustainable Development of Energy, Water and Environment Systems Index framework are used. The application of the approach to the real case study of four metropolitan areas (Bari, Bitonto, Mola, and Molfetta) in the city of Bari (Italy) shows its usefulness for the local government in benchmarking metropolitan areas and providing decision indications on how to formulate the sustainable development strategy of the metropolitan city. Based on the Analytic Hierarchy Process characteristics, the results highlight that although one specific area (Mola in the considered case) is globally ranked at the first place, it is only ranked first with respect to some dimensions. Such a result has strong implications for the metropolitan city's manager who has the possibility to identify and implement targeted actions, which may be designed ad hoc to improve specific dimensions based on the current state of the city, thus maximizing the efficiency and effectiveness of the actions undertaken for the sustainable development of energy, water and environmental systems of the whole metropolitan city.

How to foster the well-being of police officers: The role of the employee performance management system

This study focuses on employee performance management in policing. We specifically aim to contribute to a better understanding of how the combined effect of performance planning and performance evaluation fosters the well-being of police officers. In the slipstream of public sector reforms many public organizations adopted employee performance management. Although such system is found to increase performance, it might simultaneously elevate job demands, jeopardizing employees' well-being. Based on data gathered in one of the largest police departments of Belgium, structural equation modelling results demonstrate that the combination of performance planning and evaluation positively affects police officers' well-being. Satisfaction with the system was found to explain this relationship. The findings imply that police forces should ensure that performance evaluations are preceded and combined by performance planning in order to foster well-being.

Evaluation of the Luminex ARIES HSV 1&2 Assay and Comparison with the FTD Neuro 9 and In-house Real-Time PCR Assays for Detecting Herpes Simplex Viruses

Background

Human herpes simplex virus type 1 (HSV-1) and type 2 (HSV-2) are responsible for a plethora of human diseases, of which cutaneous and mucocutaneous infections are the most prevalent. In its most severe form, HSV infection can cause meningitis/encephalitis. We compared the Luminex ARIES HSV 1&2 assay (Luminex Corp., Austin, TX, USA), an automated sample-to-result molecular solution, to two non-automated HSV DNA assays.

Methods

A total of 116 artificial controls were used to determine the analytical performance of the ARIES assay. Controls were prepared by spiking universal transport medium (UTM) and cerebrospinal fluid (CSF) samples from patients who tested negative for HSV by an in-house HSV-1 and -2 DNA assay with reference materials (SeraCare Life Sciences, MA, USA; ZeptoMetrix Corp., MA, USA). Another 117 clinical samples were then used to compare the clinical performance of the ARIES assay with those of an in-house assay and the FTD Neuro 9 assay (Fast Track Diagnostics, Junglinster, Luxembourg).

Results

The analytical sensitivity (95% limit of detection) of the ARIES assay was 318 copies/mL (UTM samples) and 935 copies/mL (CSF samples) for HSV-1 strain 96 and 253 copies/mL (UTM samples) and 821 copies/mL (CSF samples) for HSV-2 strain 09. No cross-reactivity was observed in samples spiked with 14 non-HSV microorganisms. Compared with the reference result (agreement between the in-house and FTD Neuro 9 results), the ARIES assay had overall concordance rates of 98.2% (111/113) and 100% (113/113) for HSV-1 and HSV-2, respectively.

Conclusions

The ARIES assay appears to be an excellent alternative for rapid detection and differentiation of HSV in skin and genital infections, meningitis, and encephalitis.

Allergen Microarrays for In Vitro Diagnostics of Allergies: Comparison with ImmunoCAP and AdvanSure

BACKGROUND

In vitro detection of the allergen-specific IgE antibody (sIgE) is a useful tool for the diagnosis and treatment of allergies. Although multiple simultaneous allergen tests offer simple and low-cost screening methods, these platforms also have limitations with respect to multiplexibility and analytical performance. As an alternative assay platform, we developed and validated a microarray using allergen extracts that we termed "GOLD" chip.

METHODS

Serum samples of 150 allergic rhinitis patients were used in the study, and the diagnostic performance of the microarray was compared with that of AdvanSure (LG Life Sciences, Daejun, Korea) and ImmunoCAP (Phadia, Uppsala, Sweden). Standard IgE samples were used for the quantitative measurement of sIgEs.

RESULTS

The microarray-based assay showed excellent performance in the quantitative measurement of sIgEs, demonstrating a linear correlation within the range of sIgE concentrations tested. The limit of detection (LOD) was lower than 0.35 IU/mL, which is the current standard for the LOD cut-off. The assay also provided highly reproducible sets of data. The total agreement percentage of positive and negative calls was 92.2% compared with ImmunoCAP. Moreover, an outstanding correlation was observed between the microarray and the ImmunoCAP results, with Cohen's kappa and Pearson correlation coefficient values of 0.80 and 0.79, respectively.

CONCLUSIONS

The microarray-based in vitro diagnostic platform offers a sensitive, reproducible, and highly quantitative method to detect sIgEs. The results showed strong correlations with that of ImmunoCAP. These results suggest that the new allergen microarray can serve as a useful alternative to current screening platforms, ultimately becoming a first-line screening method.

A novel mixed sustainability-resilience framework for evaluating hospital information systems

Information systems (ISs) are one of the most widely used systems in different organizations especially hospitals. Improving the performance of a hospital information system (HIS) is one of the most important tasks for patient satisfaction and health. To do this, a mixed sustainability-resilience framework for evaluating HISs is proposed in this study in order to enhance their performance from a mixed sustainability-resilience view. First, a comprehensive framework including suitable sustainable and resilience indicators for performance enhancement of HISs is provided. Then, the importance weight of each indicator is achieved by using the best-worst method (BWM). Required data is obtained through a standard questionnaire. A data envelopment analysis (DEA) is applied to evaluate HIS performance in different departments of a real case study. Additionally, improvement actions are obtained by considering the effect of each selected indicator on the HIS performance through a sensitivity analysis. Also, appropriate strategies for improving the resilience and sustainability aspects of the HIS are presented using strengths-weaknesses-opportunities-threats (SWOT) matrix. Using the results, designers can build more intelligent HISs from both sustainability and resilience perspectives.

Performance evaluation of oil spill software systems in early fate and trajectory of oil spill: comparison analysis of OILMAP and PISCES 2 in Mersin bay spill

The aim of this study is to evaluate the performance level of two advanced oil spill software systems in early transport and fate of oil spill through algorithms accepted in oil spill literature. To do this, the performance level of software systems mostly used in real cases have been compared. OILMAP (the oil spill prediction modeling system) and PISCES 2 (potential incident simulation, control and evaluation system) have been used for spill trajectory in the light of four spill scenarios. The findings reveal that the OILMAP has predicted a relatively larger area of spill. In addition, OILMAP has achieved closer results to the calculations of approaches adopted in the literature for evaporation calculations. Besides, OILMAP software has provided highly reliable results in the evaporation rates of oil compared to the calculations of PISCES 2. On the other hand, as for the determination of the risky area, both software systems have yielded results with high reliability values, which could be used in taking precautions against oil spill in such areas.