Influences of a novel cylindrical solar dryer on farmer's income and its impact on environment

Poor grain drying facilities, along with the burden of drying cost, bound the farmers to market their produce soon after harvest. Thus, this research paper intends to study the influences of a novel cylindrical solar-assisted dryer on farmers' income and its impact on the environment. The paper also presents the design and fabrication of a drying system for maize cobs using non-conventional solar energy. The performance of the solar-assisted drying system was also investigated for drying of yellow dent maize cobs. As a very energy-intensive post-harvest process, drying consumes a lot of electricity, which is usually provided by conventional energy. Here, solar dryers are the perfect solution in terms of efficiency, uniform drying of agricultural food products, less drying time, increased marketability of agricultural products, and reducing the load on farmer's pocket for drying. With a high internal rate of return of 66 percent, the designed dryer proved to be technically and economically viable. Compared to open sun drying, the solar drying system produced better quality and drying time results. Compared to other models, the Midilli model fits the experimental maize drying data better, with a coefficient of determination of R² = 0.89729. Energy analysis inferred savings of 1352.97 kWh electrical energy and 128.18 liters of diesel fuel plus a reduction of 1.22 t CO₂ per annum can be achieved by using this dryer.

Efficiency evaluation of sewage treatment plants in Delhi, India, using tolerance-based data envelope analysis

Correct and effective performance evaluation of wastewater treatment plants is a tough task because of the complex biological, physico-chemical, and biochemical processes and associated variables affecting their performance. Conventionally, the efficiency of sewage treatment plants (STPs) are obtained using some index relating pollutant removal efficiency with energy used or costs. These indicators consider only one variable at a time. This leads to incorrect assessment of efficiency, which in turn could adversely affect decision-making of the regulatory authorities. The data envelope analysis (DEA) method utilizes a Linear programming technique which can handle multiple input/output variables without requiring the cost function. This makes it an appropriate tool for assessing the relative efficiency of treatment plants. The present study assess the efficiency of 30 STPs in Delhi, India, using the tolerance-based DEA model utilizing the variable return of scale (VRS). The uncertainty was incorporated into the model using the tolerance measure. The model is solved using the "Add on" option in spreadsheet toolbox of excel solver. Results reveal that out of the 30 plants considered for the study, 6 are performing well (20%). Further, it was observed that a slight change in the input data leads to instability of the efficiency results. Lastly, the ranking is used to determine the treatment plant with best efficiency under all scenarios for the larger period of the year. Such studies will help in chalking out the best management practices that could be adopted by other regulatory authorities.

A unified scheme for the benchmarking of upper limb functions in neurological disorders

BACKGROUND

In neurorehabilitation, we are witnessing a growing awareness of the importance of standardized quantitative assessment of limb functions. Detailed assessments of the sensorimotor deficits following neurological disorders are crucial. So far, this assessment has relied mainly on clinical scales, which showed several drawbacks. Different technologies could provide more objective and repeatable measurements. However, the current literature lacks practical guidelines for this purpose. Nowadays, the integration of available metrics, protocols, and algorithms into one harmonized benchmarking ecosystem for clinical and research practice is necessary.

METHODS

This work presents a benchmarking framework for upper limb capacity. The scheme resulted from a multidisciplinary and iterative discussion among several partners with previous experience in benchmarking methodology, robotics, and clinical neurorehabilitation. We merged previous knowledge in benchmarking methodologies for human locomotion and direct clinical and engineering experience in upper limb rehabilitation. The scheme was designed to enable an instrumented evaluation of arm capacity and to assess the effectiveness of rehabilitative interventions with high reproducibility and resolution. It includes four elements: (1) a taxonomy for motor skills and abilities, (2) a list of performance indicators, (3) a list of required sensor modalities, and (4) a set of reproducible experimental protocols.

RESULTS

We proposed six motor primitives as building blocks of most upper-limb daily-life activities and combined them into a set of functional motor skills. We identified the main aspects to be considered during clinical evaluation, and grouped them into ten motor abilities categories. For each ability, we proposed a set of performance indicators to quantify the proposed ability on a quantitative and high-resolution scale. Finally, we defined the procedures to be followed to perform the benchmarking assessment in a reproducible and reliable way, including the definition of the kinematic models and the target muscles.

CONCLUSIONS

This work represents the first unified scheme for the benchmarking of upper limb capacity. To reach a consensus, this scheme should be validated with real experiments across clinical conditions and motor skills. This validation phase is expected to create a shared database of human performance, necessary to have realistic comparisons of treatments and drive the development of new personalized technologies.

MCNN: a multi-level CNN model for the classification of brain tumors in IoT-healthcare system

The classification of brain tumors is significantly important for diagnosing and treating brain tumors in IoT healthcare systems. In this work, we have proposed a robust classification model for brain tumors employing deep learning techniques. In the design of the proposed method, an improved Convolutional neural network is used to classify Meningioma, Glioma, and Pituitary types of brain tumors. To test the multi-level convolutional neural network model, brain magnetic resonance image data is utilized. The MCNN model classification results were improved using data augmentation and transfer learning methods. In addition, hold-out and performance evaluation metrics have been employed in the proposed MCNN model. The experimental results show that the proposed model obtained higher outcomes than the state-of-the-art techniques and achieved 99.89% classification accuracy. Due to the higher results of the proposed approach, we recommend it for the identification of brain cancer in IoT-healthcare systems.

Development and integration of VGG and dense transfer-learning systems supported with diverse lung images for discovery of the Coronavirus identity

The contagious SARS-CoV-2 has had a tremendous impact on the life and health of many communities. It was first rampant in early 2019 and so far, 539 million cases of COVID-19 have been reported worldwide. This is reminiscent of the 1918 influenza pandemic. However, we can detect the infected cases of COVID-19 by analysing either X-rays or CT, which are presumably considered the least expensive methods. In the existence of state-of-the-art convolutional neural networks (CNNs), which integrate image pre-processing techniques with fully connected layers, we can develop a sophisticated AI system contingent on various pre-trained models. Each pre-trained model we involved in our study assumed its role in extracting some specific features from different chest image datasets in many verified sources, such as (Mendeley, Kaggle, and GitHub). First, for CXR datasets associated with the CNN trained model from the beginning, whereby is comprised of four layers beginning with the Conv2D layer, which comprises 32 filters, followed by the MaxPooling and afterwards, we reiterated similarly. We used two techniques to avoid overgeneralization, the early stopping and the Dropout techniques. After all, the output was one neuron to classify both cases of 0 or 1, followed by a sigmoid function; in addition, we used the Adam optimizer owing to the more improved outcomes than what other optimizers conducted; ultimately, we referred to our findings by using a confusion matrix, classification report (Recall & Precision), sensitivity and specificity; in this approach, we achieved a classification accuracy of 96%. Our three integrated pre-trained models (VGG16, DenseNet201, and DenseNet121) yielded a remarkable test accuracy of 98.81%. Besides, our merged models (VGG16, DenseNet201) trained on CT images with the utmost effort; this model held an accurate test of 99.73% for binary classification with the (Normal/Covid-19) scenario. Comparing our results with related studies shows that our proposed models were superior to the previous CNN machine learning models in terms of various performance metrics. Our pre-trained model associated with the CT dataset achieved 100% of the F1score and the loss value was approximately 0.00268.

Evaluation of a New Smartphone Powered Low-cost Pulse Oximeter Device

Background

Measurement of blood oxygen saturation is a vital part of monitoring coronavirus 2019 (COVID-19) patients. Pulse oximetry is commonly used to measure blood oxygen saturation and pulse rate for appropriate clinical intervention. But the majority of direct-to-consumer grade pulse oximeters did not pass through in-vivo testing, which results in their accuracy being questionable. Besides this, the ongoing COVID-19 pandemic exposed the limitations of the device in resource limited areas since independent monitoring is needed for COVID-19 patients. The purpose of this study was to perform an in-vivo evaluation of a newly developed smartphone powered low-cost pulse oximeter.

Methods

The new prototype of a smartphone powered pulse oximeter was evaluated against the standard pulse oximeter by taking measurements from fifteen healthy volunteers. The accuracy of measurement was evaluated by calculating the percentage error and standard deviation. A repeatability and reproducibility test were carried out using the ANOVA method.

Results

The average accuracy for measuring spot oxygen saturation (SPO2) and pulse rate (PR) was 99.18% with a standard deviation of 0.57 and 98.78% with a standard deviation of 0.61, respectively, when compared with the standard pulse oximeter device. The repeatability and reproducibility of SPO2 measurements were 0.28 and 0.86, respectively, which is in the acceptable range.

Conclusion

The new prototype of smartphone powered pulse oximeter demonstrated better performance compared to the existing low-cost fingertip pulse oximeters. The device could be used for independent monitoring of COVID-19 patients at health institutions and also for home care.

Benchmarking Canadian solid waste management system integrating fuzzy analytic hierarchy process (FAHP) with efficacy methods

Solid waste management is a recent challenge for both developed and developing countries because of urbanization and population growth. This research aims to identify and compare the economic efficiency of Canadian waste management systems integrating the fuzzy analytic hierarchy process (FAHP) with the efficacy method. Six economic indicators-diversion gross domestic product (DGDP) ratio, gross domestic product (GDP) of all industries, GDP of Sector 562, diversion rate, waste management output indicator, and diversion size indicator-are considered in this study. Initially, the FAHP method was used to calculate the indicator weights, and the efficacy method then ranked the DGDP ratio as the most influential factor for the GDP-related indicators. The DGDP ratio and diversion rate were determined to be most critical in the assessment of the economic efficiency of a solid waste management system in Canada. The result also revealed that the economic performance of the waste management systems of Nova Scotia, British Columbia, and Ontario are better compared to those of other provinces. The outcome of this study will aid the government and provincial organizations in establishing an effective solid waste management plan to improve their overall performance.

Live process modeling with the BPMN Sketch Miner

BPMN Sketch Miner is a modeling environment for generating visual business process models starting from constrained natural language textual input. Its purpose is to support business process modelers who need to rapidly sketch visual BPMN models during interviews and design workshops, where participants should not only provide input but also give feedback on whether the sketched visual model represents accurately what has been described during the discussion. In this article, we present a detailed description of the BPMN Sketch Miner design decisions and list the different control flow patterns supported by the current version of its textual DSL. We also summarize the user study and survey results originally published in MODELS 2020 concerning the tool usability and learnability and present a new performance evaluation regarding the visual model generation pipeline under actual usage conditions. The goal is to determine whether it can support a rapid model editing cycle, with live synchronization between the textual description and the visual model. This study is based on a benchmark including a large number of models (1350 models) exported by users of the tool during the year 2020. The main results indicate that the performance is sufficient for a smooth live modeling user experience and that the end-to-end execution time of the text-to-model-to-visual pipeline grows linearly with the model size, up to the largest models (with 195 lines of textual description) found in the benchmark workload.

Performance evaluation of dedicated brain PET scanner with motion correction system

OBJECTIVE

Various motion correction (MC) algorithms for positron emission tomography (PET) have been proposed to accelerate the diagnostic performance and research in brain activity and neurology. We have incorporated MC system-based optical motion tracking into the brain-dedicated time-of-flight PET scanner. In this study, we evaluate the performance characteristics of the developed PET scanner when performing MC in accordance with the standards and guidelines for the brain PET scanner.

METHODS

We evaluate the spatial resolution, scatter fraction, count rate characteristics, sensitivity, and image quality of PET images. The MC evaluation is measured in terms of the spatial resolution and image quality that affect movement.

RESULTS

In the basic performance evaluation, the average spatial resolution by iterative reconstruction was 2.2 mm at 10 mm offset position. The measured peak noise equivalent count rate was 38.0 kcps at 16.7 kBq/mL. The scatter fraction and system sensitivity were 43.9% and 22.4 cps/(Bq/mL), respectively. The image contrast recovery was between 43.2% (10 mm sphere) and 72.0% (37 mm sphere). In the MC performance evaluation, the average spatial resolution was 2.7 mm at 10 mm offset position, when the phantom stage with the point source translates to ± 15 mm along the y-axis. The image contrast recovery was between 34.2 % (10 mm sphere) and 66.8 % (37 mm sphere).

CONCLUSIONS

The reconstructed images using MC were restored to their nearly identical state as those at rest. Therefore, it is concluded that this scanner can observe more natural brain activity.

Validity evidence for summative performance evaluations in postgraduate community pharmacy education

INTRODUCTION

Workplace-based assessment of competencies is complex. In this study, the validity of summative performance evaluations (SPEs) made by supervisors in a two-year longitudinal supervisor-trainee relationship was investigated in a postgraduate community pharmacy specialization program in the Netherlands. The construct of competence was based on an adapted version of the 2005 Canadian Medical Education Directive for Specialists (CanMEDS) framework.

METHODS

The study had a case study design. Both quantitative and qualitative data were collected. The year 1 and year 2 SPE scores of 342 trainees were analyzed using confirmatory factor analysis and generalizability theory. Semi-structured interviews were held with 15 supervisors and the program director to analyze the inferences they made and the impact of SPE scores on the decision-making process.

RESULTS

A good model fit was found for the adapted CanMEDS based seven-factor construct. The reliability/precision of the SPE measurements could not be completely isolated, as every trainee was trained in one pharmacy and evaluated by one supervisor. Qualitative analysis revealed that supervisors varied in their standards for scoring competencies. Some supervisors were reluctant to fail trainees. The competency scores had little impact on the high-stakes decision made by the program director.

CONCLUSIONS

The adapted CanMEDS competency framework provided a valid structure to measure competence. The reliability/precision of SPE measurements could not be established and the SPE measurements provided limited input for the decision-making process. Indications of a shadow assessment system in the pharmacies need further investigation.

Substantial Improvement in Nontuberculous Mycobacterial Identification Using ASTA MicroIDSys Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry with an Upgraded Database

Identifying Mycobacterium using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is challenging. We evaluated the performance of MALDI-TOF MS in identifying nontuberculous mycobacteria (NTM) using the ASTA MicroIDSys system (ASTA Inc., Suwon, Korea) with the MycoDB v1.95s and upgraded MycoDB v2.0-beta databases. We tested 124 NTM isolates collected from Ogawa medium at Severance Hospital, Seoul, Korea, between January and April 2019. MicroIDSys scores were categorized into three groups: ≥140, reliable identification; 130-139, ambiguous identification; and <130, invalid identification. To validate the results, we used the reverse blot hybridization assay (Molecutech REBA MycoID, YD Diagnostics Corp., Korea). Initial analysis using MycoDB v1.95s resulted in 26.6% (33/124) reliable, 43.5% (54/124) ambiguous, and 29.8% (37/124) invalid identifications. Re-analysis using the upgraded MycoDB v2.0-beta database resulted in 94.4% (117/124) reliable, 4.0% (5/124) ambiguous, and 1.6% invalid (2/124) identifications. The percentage of reliable identifications that matched with the reference increased from 26.6% (33/124) with MycoDB v1.95s to 93.5% (116/124) with MycoDB v2.0-beta. The upgraded databases enable substantially improved NTM identification through deep learning in the inference algorithm and by considering more axes in the correlation analysis. MALDI-TOF MS using the upgraded database unambiguously identified most NTM species. Our study lays a foundation for applying MALDI-TOF MS for the simple and rapid identification of NTM isolated from solid media.

Comprehensive evaluation of structural variant genotyping methods based on long-read sequencing data

Background

Structural variants (SVs) play a crucial role in gene regulation, trait association, and disease in humans. SV genotyping has been extensively applied in genomics research and clinical diagnosis. Although a growing number of SV genotyping methods for long reads have been developed, a comprehensive performance assessment of these methods has yet to be done.

Results

Based on one simulated and three real SV datasets, we performed an in-depth evaluation of five SV genotyping methods, including cuteSV, LRcaller, Sniffles, SVJedi, and VaPoR. The results show that for insertions and deletions, cuteSV and LRcaller have similar F1 scores (cuteSV, insertions: 0.69–0.90, deletions: 0.77–0.90 and LRcaller, insertions: 0.67–0.87, deletions: 0.74–0.91) and are superior to other methods. For duplications, inversions, and translocations, LRcaller yields the most accurate genotyping results (0.84, 0.68, and 0.47, respectively). When genotyping SVs located in tandem repeat region or with imprecise breakpoints, cuteSV (insertions and deletions) and LRcaller (duplications, inversions, and translocations) are better than other methods. In addition, we observed a decrease in F1 scores when the SV size increased. Finally, our analyses suggest that the F1 scores of these methods reach the point of diminishing returns at 20× depth of coverage.

Conclusions

We present an in-depth benchmark study of long-read SV genotyping methods. Our results highlight the advantages and disadvantages of each genotyping method, which provide practical guidance for optimal application selection and prospective directions for tool improvement.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08548-y.

A novel hybrid evaluation framework for public organizations based on employees' performance factors

Performance evaluation is a comprehensive process for comparing activities compared with predetermined organizational criteria. Based on the results of performance evaluation, organizations can embark on purposeful actions to improve their situation. Obviously, the success of organizations and the economic development of the country depend on the performance of human resources (HR). This paper proposes a novel hybrid evaluation framework for analyzing the performance of public sector organizations. The suggested setting allows for performance evaluation based on a comprehensive approach involving expert knowledge. For this purpose, the research integrates the Balanced Scorecard (BSC) approach and fuzzy multi-criteria decision-making (MCDM) methods. Initially, the employees' performance factors (criteria) are identified from the literature based on the BSC dimensions. Then, the most relevant of them are finalized through the fuzzy Delphi method (FDM) questionnaires and experts' opinions. In the second stage, the weights of criteria are determined by adopting the fuzzy best-worst method (FBWM). Moreover, two fuzzy MCDM techniques, namely VIKOR and Grey Relational Analysis (GRA), are used to examine the performance of the eight important public sector organizations of Iran. Finally, a Monte Carlo simulation-based (MCSB) approach and a scenario-based (SCB) approach are applied to compare the effectiveness of fuzzy VIKOR and fuzzy GRA. The results suggest that the critical employees' performance factors include sharing knowledge with colleagues (0.136), optimal use of facilities (0.123) and participation in solving organizational issues (0.118). Additionally, based on the implemented sensitivity analysis approaches, fuzzy VIKOR generates more reliable results and also has higher robustness than fuzzy GRA.

Open ventilator evaluation framework: A synthesized database of regulatory requirements and technical standards for emergency use ventilators from Australia, Canada, UK, and US

Development of emergency use ventilators has attracted significant attention and resources during the COVID-19 pandemic. To facilitate mass collaboration and accelerate progress, many groups have adopted open-source development models, inspired by the long history of open-source development in software. According to the Open-source Hardware Association (OSHWA), Open-source Hardware (OSH) is a term for tangible artifacts - machines, devices, or other physical things - whose design has been released to the public in such a way that anyone can make, modify, and use them. One major obstacle to translating the growing body of work on open-source ventilators into clinical practice is compliance with regulations and conformance with mandated technical standards for effective performance and device safety. This is exacerbated by the inherent complexity of the regulatory process, which is tailored to traditional centralized development models, as well as the rapid changes and alternative pathways that have emerged during the pandemic. As a step in addressing this challenge, this paper provides developers, evaluators, and potential users of emergency ventilators with the first iteration of a pragmatic, open-source assessment framework that incorporates existing regulatory guidelines from Australia, Canada, UK and USA. We also provide an example evaluation for one open-source emergency ventilator design. The evaluation process has been divided into three levels: 1. Adequacy of open-source project documentation; 2. Clinical performance requirements, and 3. Conformance with technical standards.

Performance Evaluation of Construction Sub-contractors using Ordinal Priority Approach

The construction industry has been recognized as one of the crucial industries of a country. In large-scale public projects, it is frequently observed that the client, who serves the public, seeks the services of several sub-contractors (project outsourcing firms) to execute projects. It also seeks the consulting firms' services to monitor the progress and performance of these sub-contractors. However, performance evaluation of a large number of sub-contractors is not only a challenging phase but also a source of conflict and mistrust between the evaluators and evaluatees because of the subjectivity in the evaluation process. The current study classifies perceived organizational performance into two streams, arguing that the one involving the opinions from the independent evaluators is more objective than the self-evaluation one. The study also makes a pioneering attempt in post-qualification performance evaluation of sub-contractors through the Ordinal Priority Approach (OPA), a promising multi-attribute decision-making methodology. The deployment of the OPA allows the decision-makers to estimate the weights of the evaluation criteria, the sub-contractors to be evaluated, and the experts who evaluated them simultaneously. Thus, the methodology can minimize the causes of mistrust by uncovering unreliable experts and inappropriate criteria. Also, a novel Relative Performance Index (RPI) has been proposed to standardize the performance evaluation system. The results show that evaluation of the firms does not end at their evaluation as without evaluating the evaluators, such an evaluation is only partially effective.

Recent advances in performance improvement of Metal-organic Frameworks to remove antibiotics: Mechanism and evaluation

Antibiotic pollution is a serious global problem, which may threaten the health of human and ecosystem. Thereinto, water pollution is the most common way. Thus, it is necessary to develop effective methods to remove antibiotics from the natural aqueous environments. Metal-organic Frameworks (MOFs) - based adsorption and photocatalysis strategies have been demonstrated to be efficient, environmental and promising methods to solve antibiotic pollution and repair the environment. In this review, several strategies to improve the properties of MOFs for removal were summarized and discussed. And the removal mechanisms were also discussed. Besides, new and more reliable evaluation methods of MOFs to remove antibiotics were presented, including preferential adsorption (q_p), quantum yields (QY), space time yields (SY) and figure of merit (FOM). This paper provides alternative perspectives for researchers to improve the properties of MOFs and raise analytic efficiency of antibiotic removal.

Antecedents and enablers of supply chain reconfigurability and their effects on performance

The reconfiguration of supply chain is becoming a crucial concept used to deal with market disruptions and changes such as the COVID-19 pandemic, demand uncertainty, and new technologies. It can be defined as the ability of the supply chain to change its structure and functions in order to adapt to new changes. Its assessment requires an understanding of its quantitative factors to provide indicators that are easy to interpret. Effective reconfigurability assessment can be achieved by measuring quantitatively its six characteristics (modularity, integrability, convertibility, diagnosability, scalability, and customization). This paper aims at identifying the quantitative factors of each characteristic and their inter-relationships by using Total Interpretive Structural Modelling (TISM). The structural model obtained by TISM is applied to understand the dependency quantitative factors. Based on TISM results, a classification of quantitative factors is determined using "Matrice d'Impacts Croisés, Multiplication Appliquée à un Classement" (MICMAC) analysis. This article provides a better understanding of the six characteristics previously mentioned to improve the reconfigurability of supply chains by considering the interactions between their factors. Thus, this analysis helps managers to understand the characteristics that influence the change of the supply chain structure and those that enable changing the supply chain functions in order to optimize the supply chain reconfiguration process.

Performance evaluation of the IRIS XL-220 PET/CT system, a new camera dedicated to non-human primates

BACKGROUND

Non-human primates (NHP) are critical in biomedical research to better understand the pathophysiology of diseases and develop new therapies. Based on its translational and longitudinal abilities along with its non-invasiveness, PET/CT systems dedicated to non-human primates can play an important role for future discoveries in medical research. The aim of this study was to evaluate the performance of a new PET/CT system dedicated to NHP imaging, the IRIS XL-220 developed by Inviscan SAS. This was performed based on the National Electrical Manufacturers Association (NEMA) NU 4-2008 standard recommendations (NEMA) to characterize the spatial resolution, the scatter fraction, the sensitivity, the count rate, and the image quality of the system. Besides, the system was evaluated in real conditions with two NHP with ¹⁸F-FDG and (-)-[¹⁸F]FEOBV which targets the vesicular acetylcholine transporter, and one rat using ¹⁸F-FDG.

RESULTS

The full width at half maximum obtained with the 3D OSEM algorithm ranged between 0.89 and 2.11 mm in the field of view. Maximum sensitivity in the 400-620 keV and 250-750 keV energy windows were 2.37% (22 cps/kBq) and 2.81% (25 cps/kBq), respectively. The maximum noise equivalent count rate (NEC) for a rat phantom was 82 kcps at 75 MBq and 88 kcps at 75 MBq for energy window of 250-750 and 400-620 keV, respectively. For the monkey phantom, the maximum NEC was 18 kcps at 126 MBq and 19 kcps at 126 MBq for energy window of 250-750 and 400-620 keV, respectively. The IRIS XL provided an excellent quality of images in non-human primates and rats using ¹⁸F-FDG. The images acquired using (-)-[¹⁸F]FEOBV were consistent with those previously reported in non-human primates.

CONCLUSIONS

Taken together, these results showed that the IRIS XL-220 is a high-resolution system well suited for PET/CT imaging in non-human primates.

An integrated approach for evaluating and improving the performance of surgical theaters with resilience engineering

Operating rooms are among the most high-risk and vital parts of a hospital. Therefore, one of the most fundamental tasks of risk management is maintaining the safety of operating rooms. Resilience engineering (RE) can be introduced as a model for overcoming problems, and it seeks ways to raise success rates by focusing on and addressing complexities. To this end, an RE-based framework is presented to evaluate the performance of operating rooms. First, the RE indicators are identified, and the relative importance of each is calculated via the best-worst method (BWM). Subsequently, the required data are collected from operating room experts using a standard questionnaire. Next, a data envelopment analysis (DEA) method is employed to evaluate the performance of operating rooms in the study case. Lastly, drawing upon the sensitivity analysis and statistical tests, the effect of each RE indicator is examined on the surgical department. Accordingly, some improvement approaches are proposed. Besides, SWOT (strengths, weaknesses, opportunities, and threats) analysis is used to extract appropriate strategies to improve performance. To the best of our knowledge, this paper is the first to evaluate the performance of operating rooms quantitatively in terms of RE indicators, and the framework presented in this paper can have practical applications in different operating rooms.

Energy crypto currencies and leading U.S. energy stock prices: are Fibonacci retracements profitable?

This paper investigates the role of Fibonacci retracements levels, a popular technical analysis indicator, in predicting stock prices of leading U.S. energy companies and energy cryptocurrencies. The study methodology focuses on applying Fibonacci retracements as a system compared with the buy-and-hold strategy. Daily crypto and stock prices were obtained from the Standard & Poor's composite 1500 energy index and CoinMarketCap between November 2017 and January 2020. This study also examined if the combined Fibonacci retracements and the price crossover strategy result in a higher return per unit of risk. Our findings revealed that Fibonacci retracement captures energy stock price changes better than cryptos. Furthermore, most price violations were frequent during price falls compared to price increases, supporting that the Fibonacci instrument does not capture price movements during up and downtrends, respectively. Also, fewer consecutive retracement breaks were observed when the price violations were examined 3 days before the current break. Furthermore, the Fibonacci-based strategy resulted in higher returns relative to the naïve buy-and-hold model. Finally, complementing Fibonacci with the price cross strategy did not improve the results and led to fewer or no trades for some constituents. This study's overall findings elucidate that, despite significant drops in oil prices, speculators (traders) can implement profitable strategies when using technical analysis indicators, like the Fibonacci retracement tool, with or without price crossover rules.

Evaluating the performance of drug-repurposing technologies

Drug-repurposing technologies are growing in number and maturing. However, comparisons to each other and to reality are hindered because of a lack of consensus with respect to performance evaluation. Such comparability is necessary to determine scientific merit and to ensure that only meaningful predictions from repurposing technologies carry through to further validation and eventual patient use. Here, we review and compare performance evaluation measures for these technologies using version 2 of our shotgun repurposing Computational Analysis of Novel Drug Opportunities (CANDO) platform to illustrate their benefits, drawbacks, and limitations. Understanding and using different performance evaluation metrics ensures robust cross-platform comparability, enabling us to continue to strive toward optimal repurposing by decreasing the time and cost of drug discovery and development.

The influence of earnings management on bank efficiency: the case of frontier markets

Frontier market banks fill key funding gaps in the markets they serve, resulting in increased evaluation (a positive) and earnings management (EM) (a negative). Examination of a large sample of banks in 22 frontier market countries from 2001 to 2018 reveals a downward trend in efficiency, indicating that loan quality issues persist despite increasing economic growth in the respective countries. Using stochastic frontier analysis to quantify efficiency and random effects and truncated regression to investigate the EM-efficiency relation, this study demonstrates that efficiency is negatively associated with EM. Furthermore, there was no clear relationship between bank size and efficiency, which counters economic efficiency theory and implies that frontier market banks absorb higher non-performing loan costs. The findings herein support prospect theory by demonstrating that managers engage in risk-seeking behaviour while making risk-averse decisions. Overall, the study's implications suggest that banks employ alternative loan provision practices to optimise resource allocation and, by extension, performance.

β-eye: A benchtop system for in vivo molecular screening of labeled compounds

Preclinical nuclear molecular imaging speeds up the mean time from synthesis to market, in drug development process. Commercial imaging systems have in general high cost, require high-cost service contracts, special facilities and trained staff. In the current work, we present β-eye, a benchtop system for in vivo molecular screening of labeled compounds with Positron Emission Tomography (PET) isotopes. The developed system is based on a dual-head geometry, offering simplicity and decreased cost. The goal of the design is to provide 2D, real-time radionuclide images of mice, allowing the recording of fast frames and thus perform fast kinetic studies, with spatial resolution of ∼2 mm. Performance evaluation demonstrates the ability of β-eye to provide quantitative results for injected activities lower than 1.5 MBq, which is adequate for pharmacodynamic studies in small mice.

Safety and associated parameters influencing performance of rail road grade crossings: A critical review of state of the art

INTRODUCTION

Railroad grade crossings (RRGCs) have emerged as critical transportation infrastructures from the point of safety and operational aspects because two modes of transportation intermingle at the intersecting zone; the understanding of safety and traffic operation at RRGC is of prime concern while planning and designing this transportation facility.

METHOD

In this context, this work tries to comprehend RRGC performance-related parameters from published literature and figure out critical gaps. An international synthesis on the identified potential parameters influencing the RRGC performance (i.e., safety, driver behavior, and operational impact) was carried out by critically reviewing the articles published worldwide. Furthermore, key findings, used variables, analysis methods, research gaps, and recommendations were studied.

RESULTS

The review revealed that many researchers had explored the driver behavior and safety aspect based on past crash data and violations prevailing at RRGC. However, little research has been done to evaluate the effect of highways' operational characteristics on the performance of RRGC. Moreover, limited investigation has been carried out to understand the dilemma of drivers and the proactive safety evaluation of pedestrians and non-motorized vehicles at RRGC. A total of seven critical research gaps concerning parameters are recognized, facilitating a clear agenda for further research pertaining to RRGC performance.

Beyond financial proxies in Cohesion Policy inputs' monitoring: A system dynamics approach

European Union's Cohesion Policy aims to foster development and reduce disparities among regions by redistributing more than one-third of the European budget. Given the policy's importance and complexity, an elaborated monitoring and evaluation system has been established. While attention has been dedicated to evaluating policy impact, the monitoring of inputs (i.e., allocated financial resources) has been limited to the control of financial dimensions (i.e., funds' absorption rate). As the implementation process entails a sequence of steps, this research explores whether financial proxies alone are adequate to monitor the policy inputs. To test this hypothesis, a system dynamics model is built. Simulations highlight that the absorption rate captures shocks that might occur during the inputs' expenditure with significant delay. To that end, we elaborate three novel operative monitoring indicators (i.e., funds' demand, funds' offer, procedural efficiency), which may overcome the financial indicators' mono-dimensionality and time lags' limitations.

Cellular automata based framework for evaluating mitigation strategies of sponge city

Urban surface water flooding is increasing because of climate change and urbanization, and brings great challenges to urban sustainable development. It is, therefore, most important to develop urban flood management approaches to alleviate the consequences of floods. China is implementing a "sponge city" initiative to tackle urban surface water flooding and improve urban water management. There is, however, limited cost-effectiveness evaluation to support the choice of economically efficient mitigation strategies. To address this gap, this study developed an evaluation framework based on cellular automata and cost-benefit analysis to assess the performance of mitigation strategies in sponge city construction. This approach is demonstrated with a case study of Siergou (Dalian, China), which has a total area of 10.1 km². The mitigation measures of green roofs, permeable pavements and bio-retention were used to generate mitigation scenarios. A two-dimensional cellular automata-based model was used to simulate urban surface water flooding. The results obtained from the case study indicate that the framework can achieve cost-effective mitigation strategies for sponge city construction, which can support robust decision making. The distribution of mitigation strategies has great impacts on the effectiveness of alleviating urban flood risk. This study provides new insight into the development of cost-effective mitigation strategies for sponge city construction.

Prediction methods for microRNA targets in bilaterian animals: Toward a better understanding by biologists

MicroRNAs (miRNAs) are small noncoding RNAs that regulate gene expression at the posttranscriptional level. Because of their wide network of interactions, miRNAs have become the focus of many studies over the past decade, particularly in animal species. To streamline the number of potential wet lab experiments, the use of miRNA target prediction tools is currently the first step undertaken. However, the predictions made may vary considerably depending on the tool used, which is mostly due to the complex and still not fully understood mechanism of action of miRNAs. The discrepancies complicate the choice of the tool for miRNA target prediction. To provide a comprehensive view of this issue, we highlight in this review the main characteristics of miRNA-target interactions in bilaterian animals, describe the prediction models currently used, and provide some insights for the evaluation of predictor performance.

Performance evaluation of surrogate measures of safety with naturalistic driving data

Surrogate measures of safety (SMoS) play an important role in detecting traffic conflicts and in traffic safety assessment. However, the underlying assumptions of SMoS are different and a certain SMoS may be adequate/inadequate for different applications. A comprehensive approach to evaluate the validity and applicability of SMoS is lacking in the literature. This study proposes such a framework that supports evaluating SMoS in multiple dimensions. We apply the framework to gain insights into the characteristics of six widely-used SMoS for longitudinal maneuvers, i.e., Time to Collision (TTC), single-step Probabilistic Driving Risk Field (S-PDRF), Deceleration Rate to Avoid a Crash (DRAC), Potential Index for Collision with Urgent Deceleration (PICUD), Proactive Fuzzy Surrogate Safety Metric (PFS), and the Critical Fuzzy Surrogate Safety Metric (CFS). To ensure comparability, all measures are calibrated with the same risk detection criterion. Four performance indicators, i.e., Prediction Accuracy, Timeliness, Robustness, and Efficiency are computed for all six SMoS and validated using naturalistic driving data. The strengths and weaknesses of all six measures are compared and analyzed elaborately. A key result is that not a single SMoS performs well in all performance dimensions. S-PDRF performs best in terms of Robustness but consumes the most time for computation. TTC is the most efficient but performs poorly in terms of Timeliness and Robustness. The proposed evaluation approach and the derived insights can support SMoS selection in active vehicle safety system design and traffic safety assessment.

Featured services and performance of BDS-3

BeiDou Global Navigation Satellite System (BDS-3) not only performs the normal positioning, navigation and timing (PNT) functions, but also provides featured services, which are divided into geostationary orbit (GEO) and medium earth orbit (MEO) satellite-based featured services in this paper. The former refers to regional services consisting of the regional short message communication service (RSMCS), the radio determination satellite service (RDSS), the BDS satellite-based augmented service (BDSBAS) and the satellite-based precise point positioning service via B2b signal (B2b-PPP). The latter refers to global services consisting of the global short message communication service (GSMCS) and the MEO satellite-based search and rescue (MEOSAR) service. The focus of this paper is to describe these featured services and evaluate their performances. The results show that the inter-satellite link (ISL) contributes a lot to the accuracy improvement of orbit determination and time synchronization for the whole constellation. Compared with some other final products, the root mean squares (RMS) of the BDS-3 precise orbits and broadcast clock are 25.1 cm and 2.01 ns, respectively. The positioning accuracy of single frequency is better than 6 m, and that of the generalized RDSS is usually better than 12 m. For featured services, the success rates of RSMCS and GSMCS are better than 99.9% and 95.6%, respectively; the positioning accuracies of single and dual frequency BDSBAS are better than 3 and 2 m, respectively; the positioning accuracy of B2b-PPP is better than 0.6 m, and the convergence time is usually smaller than 30 min; the single station test shows that the success rate of MEOSAR is better than 99%. Due to the ISL realization in the BDS-3 constellation, the performance and capacities of the global featured services are improved significantly.

Performance evaluation of an EMS system using queuing theory and location analysis: A case study

In emergency medical services (EMS), response time is a key factor that shows the performance of the system. This factor is composed of two parts including activation time and travel time. The activation time of an emergency call is the time a call center spends on taking an incoming call for EMS and decides whether an ambulance should be dispatched or the emergency can be resolved by giving some medical advices. Having a good number of call center operators including call takers and dispatchers can help to reduce this time and thus the response time. However, this alone may not be enough to have a reasonable cycle time. In fact, having idle ambulances located in right places when emergency calls occur is an influential factor to reduce the travel time and thus have an optimal response time and save people's lives. Although many researchers have studied improving either the activation time or the travel time, to the best of our knowledge, there exists no study focusing on both. Motivated by this gap, in this study, a framework is proposed which uses queuing theory and location analysis to address both activation and travel times. In this regard, first, queuing theory is applied to evaluate the performance of an EMS call center and reduce the average activation time. Then, three mathematical models including mobile stations, MEXCLP and MECRP are applied to locate ambulances such that the average travel time is minimized. To shed light on the merits of using queuing theory and location models, computational results based on the real-world data from Tehran EMS Center are provided. The proposed methodology can reduce the average response time by approximately four minutes and increase the average coverage by 35%. This work is an example of the tremendous positive impact that the application of queuing theory and mathematical modeling can have. The proposed framework can significantly decrease the cycle time and increase the ambulance coverage level. The findings of this study help the policy makers of EMS centers with evaluating the performance of their systems and determining the optimal number of operators and locations of ambulances in a way that enhances the quality of emergency services.

Investigation into cavitational intensity and COD reduction performance of the pinned disc reactor with various rotor-stator arrangements

In this study, the hydrodynamic cavitation and wastewater treatment performance of a rotary generator with pin disk for hydrodynamic cavitation are investigated. Various geometrical features and arrangements of rotor and stator pins were evaluated to improve the configuration of the cavitation device. The pilot device used to perform the experiments was upgraded with a transparent cover that allows visualization of the hydrodynamic cavitation in the rotor-stator region with high-speed camera and simultaneous measurement of pressure fluctuations. Based on the hydrodynamic characteristics, three arrangements were selected and evaluated with respect to the chemical effects of cavitation on a 200-liter wastewater influent sample. The experimental results show that the rotational speed and the spacing of the rotor pins have the most significant effect on the cavitation intensity and effectiveness, while the pin diameter and the surface roughness are less significant design parameters. Cavitation intensity increases with pin velocity, but can be inhibited if the pins are arranged too close together. At best configuration, COD was reduced by 31% in 15 liquid passes, consuming 8.2 kWh/kg COD. The number of liquid passes also proved to be an important process parameter for improving the energy efficiency.

Heterojunction photocatalysts for degradation of the tetracycline antibiotic: a review

Antibiotic pollution is a major health issue inducing antibiotic resistance and the inefficiency of actual drugs, thus calling for improved methods to clean water and wastewater. Here we review the recent development of heterojunction photocatalysis and application in degrading tetracycline. We discuss mechanisms for separating photogenerated electron-hole pairs in different heterojunction systems such as traditional, p-n, direct Z-scheme, step-scheme, Schottky, and surface heterojunction. Degradation pathways of tetracycline during photocatalysis are presented. We compare the efficiency of tetracycline removal by various heterojunctions using quantum efficiency, space time yield, and figures of merit. Implications for the treatment of antibiotic-contaminated wastewater are discussed.

Nature-based solutions efficiency evaluation against natural hazards: Modelling methods, advantages and limitations

Nature-based solutions (NBS) for hydro-meteorological risks (HMRs) reduction and management are becoming increasingly popular, but challenges such as the lack of well-recognised standard methodologies to evaluate their performance and upscale their implementation remain. We systematically evaluate the current state-of-the art on the models and tools that are utilised for the optimum allocation, design and efficiency evaluation of NBS for five HMRs (flooding, droughts, heatwaves, landslides, and storm surges and coastal erosion). We found that methods to assess the complex issue of NBS efficiency and cost-benefits analysis are still in the development stage and they have only been implemented through the methodologies developed for other purposes such as fluid dynamics models in micro and catchment scale contexts. Of the reviewed numerical models and tools MIKE-SHE, SWMM (for floods), ParFlow-TREES, ACRU, SIMGRO (for droughts), WRF, ENVI-met (for heatwaves), FUNWAVE-TVD, BROOK90 (for landslides), TELEMAC and ADCIRC (for storm surges) are more flexible to evaluate the performance and effectiveness of specific NBS such as wetlands, ponds, trees, parks, grass, green roof/walls, tree roots, vegetations, coral reefs, mangroves, sea grasses, oyster reefs, sea salt marshes, sandy beaches and dunes. We conclude that the models and tools that are capable of assessing the multiple benefits, particularly the performance and cost-effectiveness of NBS for HMR reduction and management are not readily available. Thus, our synthesis of modelling methods can facilitate their selection that can maximise opportunities and refute the current political hesitation of NBS deployment compared with grey solutions for HMR management but also for the provision of a wide range of social and economic co-benefits. However, there is still a need for bespoke modelling tools that can holistically assess the various components of NBS from an HMR reduction and management perspective. Such tools can facilitate impact assessment modelling under different NBS scenarios to build a solid evidence base for upscaling and replicating the implementation of NBS.

Anisotropic ZnO nanostructures and their nanocomposites as an advanced platform for photocatalytic remediation

In pursuit of advanced heterogeneous photocatalysts, ZnO has emerged as a promising option for solar-driven heterogeneous photocatalyst with many advantageous properties (e.g., optical band structure and electronic properties). However, as the efficacy of such system can also be limited by a number of demerits (e.g., fast recombination of charge carriers and limited photon absorption), considerable efforts are needed for its effective and practical scale-up. This article provides a detailed literature review of the synthesis and modification of ZnO nanostructures with tuned band structures and controllable morphologies for solar light harvesting. The potential of anisotropic ZnO nanostructures is also discussed with respect to the photocatalytic degradation of organic/inorganic water pollutants. Further, the role of various metal dopants is discussed for the enhancement of photocatalytic activity along with evaluation of their photocatalytic performances under UV-visible or solar irradiation. Finally, our discussions are expanded to describe the prospects of developed ZnO nano-photocatalysts for real-world applications with respect to light-harvesting efficiency and mechanical stability.

Performance evaluation of FAO Penman-Monteith and best alternative models for estimating reference evapotranspiration in Bangladesh

Proper assessment of reference evapotranspiration (ET₀) is necessary for pastoral activity and water management. The Penman-Monteith FAO56 (ET_pmf) method has been recommended as the identical ET₀ estimation model; nonetheless, it belongs to a vast climatic data requirement. There is an urgent need to discover an ideal alternate model for evaluating ET₀ in particular places where all climatic data is insufficient. The performances of 15 empirical models were assessed to get the best alternative model by comparing it with the PMF-56 model. These 15 models were evaluated by employing a daily scatter plot and three well known numerical approaches: relative root-mean-square error, mean absolute error and Nash–Sutcliffe coefficient in this study. Furthermore, a linear regression model was implemented to calibrate and validate the empirical models' performances throughout the 1981–2005 and 2006–2018 time intervals, separately. The outcomes displayed that the ET_pmf rose primarily and declined later on a monthly period with the topmost amount in April and the lowermost amount in January. Overall, the Abtew model was the best alternate method showing the highest determination coefficient values more than 0.85 from January to December. In contrast, the Penman, WMO, Trabert, Valiantzas1, Valiantzas2, Valiantzas3 and Jensen-Haise models presented moderate performances with fewer inaccuracies. Afterwards, modification, the version of the above-described models every month has been upgraded deliberately related to actual. The Abtew model had simplicity in the computation process, only used maximum temperature and solar radiation data and linearly well connected to the PMF-56 model.

Development and implementation of standardized study performance metrics for a VA healthcare system clinical research consortium

The cost of conducting clinical trials is continuously increasing and is driven in large part by the time and resources required to activate trials and reach accrual targets. The impact of low enrollment in a clinical trial can negatively affect the validity of study results and delay its generalizability to the broader population. Quality is a multidimensional concept which could relate to the design, conduct, and analysis of a trial, its clinical relevance, protection/safety of study participants, or quality of reporting. Furthermore, the quality of controlled trials is of obvious relevance to systematic reviews and if the "raw material" or "data" is flawed then the conclusions of systematic reviews cannot be trusted. To date, the literature surrounding the establishment of standardized study enrollment and quality metrics to assess site performance in clinical trial consortiums is scarce. The lack of these metrics presents challenges to study site teams, sponsors, and other clinical research enterprise key stakeholders for adequately monitoring and evaluating study site performance as it relates to fulfilling trial enrollment and quality goals. The Department of Veterans Affairs (VA) Cooperative Studies Program (CSP) Network of Dedicated Enrollment Sites (NODES) undertook an effort to determine the feasibility of establishing and implementing standardized study enrollment and quality metrics for a clinical research consortium (NODES) as a tool to evaluate its performance. In this manuscript, we describe the development and implementation of standardized study enrollment and quality metrics to assess site performance across studies in our clinical research consortium.

Clinical performance evaluation of SARS-CoV-2 rapid antigen testing in point of care usage in comparison to RT-qPCR

BACKGROUND

Antigen rapid diagnostic tests (RDT) for SARS-CoV-2 are fast, broadly available, and inexpensive. Despite this, reliable clinical performance data from large field studies is sparse.

METHODS

In a prospective performance evaluation study, RDT from three manufacturers (NADAL®, Panbio™, MEDsan®, conducted on different samples) were compared to quantitative reverse transcription polymerase chain reaction (RT-qPCR) in 5 068 oropharyngeal swabs for detection of SARS-CoV-2 in a hospital setting. Viral load was derived from standardised RT-qPCR Cycle threshold (Ct) values. The data collection period ranged from November 12, 2020 to February 28, 2021.

FINDINGS

The sensitivity of RDT compared to RT-qPCR was 42·57% (95% CI 33·38%-52·31%). The specificity was 99·68% (95% CI 99·48%-99·80%). Sensitivity declined with decreasing viral load from 100% in samples with a deduced viral load of ≥108 SARS-CoV-2 RNA copies per ml to 8·82% in samples with a viral load lower than 104 SARS-CoV-2 RNA copies per ml. No significant differences in sensitivity or specificity could be observed between samples with and without spike protein variant B.1.1.7. The NPV in the study cohort was 98·84%; the PPV in persons with typical COVID-19 symptoms was 97·37%, and 28·57% in persons without or with atypical symptoms.

INTERPRETATION

RDT are a reliable method to diagnose SARS-CoV-2 infection in persons with high viral load. RDT are a valuable addition to RT-qPCR testing, as they reliably detect infectious persons with high viral loads before RT-qPCR results are available.

FUNDING

German Federal Ministry for Education and Science (BMBF), Free State of Bavaria.

Aligning efficiency benchmarking with sustainable outcomes in the United Kingdom water sector

The provision of fundamental services by water and sewage companies (WaSCs) requires substantial energy and material inputs. A sustainability assessment of these companies requires a holistic evaluation of both performance and efficiency. The Hicks-Moorsteen productivity index was applied to 12 WaSCs in the United Kingdom (UK) over a 6-year period to benchmark their sustainability, based on eight approaches using different input and output variables for efficiency assessment. The choice of variables had a major influence on the ranking and perceived operational efficiency among WaSCs. Capital expenditure (utilised as part of total expenditure) for example, is an important input for tracking company operations however, potential associated efficiency benefits can lag investment, leading to apparent poor short-term performance following capital expenditure. Furthermore, water supplied and wastewater treated was deemed an unconstructive output from a sustainability perspective since it contradicts efforts to improve sustainability through reduced leakage and consumption per capita. Customer satisfaction and water quality measures are potential suitable alternatives. Despite these limitations, total expenditure and water supplied and wastewater treated were used alongside customer satisfaction and self-generated renewable energy for a holistic sustainability assessment within a small sample. They indicated the UK water sector has improved in productivity by 1.8% on average for 2014-18 and still had room for improvement, as a technical decline was evident for both the best and worst performers. Collectively the sample's production frontier was unchanged but on average companies moved 2.1% closer to it, and further decomposition of productivity revealed this was due to improvements in economies of scale and scope. Careful selection of appropriate input and output variables for efficiency benchmarking across water companies is critical to align with sustainability objectives and to target future investment and regulation within the water sector.

Performance evaluation of medical service for breast cancer patients based on diagnosis related groups

Background

To evaluate the performance of medical service for patients with breast cancer in Henan Province, China, using diagnosis related groups (DRGs) indicators and to provide data to inform practices and policies for the prevention and control of breast cancer.

Methods

The data were collected from the front pages of medical records (FPMR) of all hospitals above class II that admitted breast cancer patients in Henan Province between 2016 and 2019. Breast cancer patients were the subjects in our study. China DRGs (CN-DRGs) was used as a risk adjustment tool. Three indicators, including the case mix index (CMI), number of DRGs, and total weight, were used to evaluate the range of available services for patients with breast cancer, while indicators including the charge efficiency index (CEI), time efficiency index (TEI) and inpatient mortality of low-risk group cases (IMLRG) were used to evaluate medical service efficiency and medical safety.

Results

Between 2016 and 2019, there were 103,760 patients with breast cancer. The total weight increased over the study period at an average annual rate of 21.71%. The TEI decreased over the study period by 15.60%. The CEI exhibited an increasing trend, but the average annual rate of increase was small (2.94%). The IMLRP was 0.02, 0, 0 and 0.01% in 2016, 2017, 2018 and 2019, respectively.

Conclusion

The performance of medical service improved between 2016 and 2019 for breast cancer patients discharged from study hospitals in Henan Province. The main area of improvement was in the range of available services, but medical institutions must still make efforts to improve the efficiency of medical services and ensure medical safety. DRGs is an effective evaluation tool.

Evaluation of staff nurses performance in Level III private hospitals in Region IV-A basis for continuing professional development program

This study determined the clinical performance of staff nurses in Level III private hospitals. Determination of the clinical competency measured using the questionnaire checklist adopted from the nursing core competency standards. Results indicated that the overall clinical performance of staff nurses in the Beginning Nurses' Role in Client Care, Leadership and Management, and Research are competent based on the evaluation of respondents. Staff nurses' performance, according to profile divulges no significant difference in client care, leadership, and management, while a significant difference is found in research when the highest educational attainment and location of hospital affiliation are considered. Evaluation of those with master's degree is significantly higher than those with bachelor's degree and with master's units. In terms of the current position, the findings disclosed a significant difference in beginning nurses' roles in leadership and management. The correlation of client care, leadership, and management, and research revealed a directly proportional relationship.

Performance evaluation for the design of a hybrid cloud based distance synchronous and asynchronous learning architecture

The COVID-19 emergency suddenly obliged schools and universities around the world to deliver on-line lectures and services. While the urgency of response resulted in a fast and massive adoption of standard, public on-line platforms, generally owned by big players in the digital services market, this does not sufficiently take into account privacy-related and security-related issues and potential legal problems about the legitimate exploitation of the intellectual rights about contents. However, the experience brought to attention a vast set of issues, which have been addressed by implementing these services by means of private platforms. This work presents a modeling and evaluation framework, defined on a set of high-level, management-oriented parameters and based on a Vectorial Auto Regressive Fractional (Integrated) Moving Average based approach, to support the design of distance learning architectures. The purpose of this framework is to help decision makers to evaluate the requirements and the costs of hybrid cloud technology solutions. Furthermore, it aims at providing a coarse grain reference organization integrating low-cost, long-term storage management services to implement a viable and accessible history feature for all materials. The proposed solution has been designed bearing in mind the ecosystem of Italian universities. A realistic case study has been shaped on the needs of an important, generalist, polycentric Italian university, where some of the authors of this paper work.

Performance of sewage treatment plants and impact of effluent discharge on receiving water quality within an urbanized area

In Brazil, wastewater treatment coverage is low. Even when treatment is carried out, many municipalities cannot achieve adequate levels of contaminant removal, and the usual practice of releasing raw or treated domestic effluent into water bodies remains. Thus, this pollution source puts pressure on water resources, compromising downstream uses of the disposal. This study has two aims: (1) to evaluate the performance of sewage treatment plants and (2) to determine the impact of discharging treated effluent on the water quality of receiving water bodies located within an urbanized area in the Velhas River basin, Minas Gerais State, Brazil. Monitoring data from raw wastewater were compared with typical ranges reported in literature, and effluent concentrations were compared between plants. The monitoring data of the receiving water bodies collected at points upstream and downstream of each disposal were statistically compared. Different performances between the systems and significant alterations in the receiving bodies resulting from the discharge of the treated effluents were found.

Standardized method for material flow data collection at city level

The collection of material flow data is the first step in the evaluation of the circular economy performance and material metabolism at the city level. However, Chinese statistical data are published by Chinese National Bureau of Statistics, and provincial and municipal Bureau of Statistics. This resulted in data being scattered in dispersed sources and varying between cities, even brings about mistakes. Therefore, we established a standardized data collection and accounting method with regular data sources for Chinese cities. In this data collection method, material flow accounting mainly consists of three parts: direct material input, material recycling, and waste disposal. It covers four types of materials, including fossil fuels, biomass, metal minerals, and non-metallic minerals with 155 items. We combined the data sources for the material flow accounting within a standardized Excel spreadsheet with detailed information on statistical data sources and equations to convert the information into material flow data. The statistical data were derived from the China City Statistical Yearbook, the provincial Statistic Yearbook, and the city's statistical yearbook. The estimated data in the material accounting were obtained by converting statistical data using relative coefficients. According to the main sources and features of materials use, the intersectoral material flows can also be estimated following this standardized method for urban metabolism analysis, circular economy performance evaluation, and ecological network analysis. The standardized method for material flow data collection was adopted in the article "H. Gao, X. Tian, Y. Zhang, L. Shi, F. Shi, 2021. Evaluating circular economy performance based on ecological network analysis: A framework and application at city level. 105257. Resources, Conservation & Recycling. https://doi.org/10.1016/j.resconrec.2020.105257".

Sustainability assessment of existing onshore wind plants in the context of triple bottom line: a best-worst method (BWM) based MCDM framework

Not only the steadily growing demand for electricity generation but also the environmental concerns in recent years have led to the belief in the importance of renewable energy. Wind is one of the most important renewable energy sources utilized in electricity generation for a sustainable environment. This paper deals with performance assessment for existing onshore wind plants in terms of triple bottom line of sustainability and aims to propose a structural methodology. Furthermore, the proposed framework is essentially formed through two stages: the first stage is the determination of relative weights for sustainability factors through the best-worst method (BWM) and the second stage is a sustainability performance assessment of the available 42 wind plants in Izmir, Turkey. According to the findings, the environmental dimension is the most significant, followed by the economic and social dimensions. The results also reveal that distance to protected areas is the most important factor among others in terms of sustainability performance and that the wind plants throughout the north side of Izmir have a higher sustainability performance. To validate the robustness and reliability of the introduced framework, a sensitivity analysis is also conducted. The proposed framework could be employed successfully in other scientific applications.

Assessing Industrial Robot agility through international competitions

Manufacturing and Industrial Robotics have reached a point where to be more useful to small and medium sized manufacturers, the systems must become more agile and must be able to adapt to changes in the environment. This paper describes the process for creating and the lessons learned over multiple years of the Agile Robotics for Industrial Automation Competition (ARIAC) being run by the National Institute of Standards and Technology.

Performance evaluation of a decentralized rooftop solar photovoltaic system with a heat recovery cooling unit

The present work represents a detailed performance analysis of a 5-kW_p on-grid solar photovoltaic rooftop system installed on a flat roof of a hospital building at a height of 12 m from the ground level, located at Perambalur (latitude 11° 23' N and longitude 78° 93' E), Tamilnadu, India. The daily, monthly and annual average performance parameters of the PV system including energy output, final yield, reference yield, array yield, photovoltaic array efficiency, system efficiency, inverter efficiency, performance ratio and capacity utilization factor have been analysed. The environmental benefit analysis and the payback period of the installed solar photovoltaic plant are also discussed. This solar photovoltaic power plant generates around 7144 kWh per annum of electrical energy, which is fed into the grid, and the annual average array, inverter, system efficiency, capacity utilization factor and performance ratio of the plant are found to be 12.15%, 97.12%, 11.72%, 16.31% and 76.83%, respectively, during the year 2019. The overall PV module electrical efficiency has been increased by 1.21% by applying the forced air circulation mechanism and 2.31% by applying the forced water circulation mechanism. Subsequently, the heat gained by the system can be utilized for heat load application. The installed solar photovoltaic power plant has a positive impact on greenhouse gas emissions with a reduction of 11.287 t of CO₂, 8.86 kg of SO₂, 18.50 kg of NO_x and 485.792 kg of ash per annum. The water-based cooling in photovoltaics can potentially generate an output energy of 7310 kWh, which is relatively higher than the energy generated by the photovoltaic module with air cooling.

Performance evaluation of a novel pilot-scale pinned disc rotating generator of hydrodynamic cavitation

This study investigates hydrodynamic performance of a novel pinned disc rotating generator of hydrodynamic cavitation in comparison with a serrated disc variant on a pilot-scale. Experimental results show that at a given rotational speed and liquid flow rate, the pinned disc generates more intense cavitation (i.e. lower cavitation number, higher volume fraction of vapor and higher amplitude of pressure fluctuations) than the serrated disc, while also consuming less energy per liquid pass (i.e., higher flow rate and pumping pressure difference of water at similar power consumption). Additionally, mechanical and chemical wastewater treatment performance of the novel cavitator was evaluated on an 800 L influent sample from a wastewater treatment plant. Mechanical effects resulted in a reduction of average particle size from 148 to 38 µm and increase of specific surface area, while the oxidation potential was confirmed by reduction of COD, TOC, and BOD up to 27, 23 and 30% in 60 cavitation passes, respectively. At optimal operating conditions and 30 cavitation passes, pinned disc cavitator had a 310% higher COD removal capacity while consuming 65% less energy per kg of COD removed than the serrated disc cavitator. Furthermore, the specific COD-reduction energy consumption of the pinned disc cavitator on the pilot scale is comparable to the best cases of lab-scale orifice and venturi devices operating at much lower wastewater processing capacity.

Thermal, hygric, and environmental performance evaluation of thermal insulation materials for their sustainable utilization in buildings

As energy use in the building sector is increasing worldwide, building materials with characteristics that save energy are becoming increasingly important; in addition, there is an emerging need for high-performance insulation materials with low thermal conductivity. However, thermal insulation should consider thermal conductivity, which is the main performance parameter, in addition to the water adsorption rate, acidity, and deformation and expansion due to drying conditions. This study evaluated the main performance of 21 insulation materials used at construction sites to objectively and clearly evaluate their overall performance, including their thermal conductivity. Thermal conductivity was measured by the heat flow meter method according to ASTM C518 and ISO 8301 standards; it was also evaluated according to the drying conditions. The water absorption rate was evaluated by ISO 2896 to ensure the sustainability and long-term thermal conductivity performance of the material. Acidity was evaluated with ASTM E861 to reduce the environmental load of the buildings and soil. The results of this study reviewed an appropriate method to measure the main performance according to the type of insulation.

Age of information of a server with energy requirements

We investigate a system with Poisson arrivals to two queues. One queue stores the status updates of the process of interest (or data packets) and the other handles the energy that is required to deliver the updates to the monitor. We consider that the energy is represented by packets of discrete unit. When an update ends service, it is sent to the energy queue and, if the energy queue has one packet, the update is delivered successfully and the energy packet disappears; however, in case the energy queue is empty, the update is lost. Both queues can handle, at most, one packet and the service time of updates is exponentially distributed. Using the Stochastic Hybrid System method, we characterize the average Age of Information of this system. Due to the difficulty of the derived expression, we also explore approximations of the average Age of Information of this system.

An Integrated Methodology Using Extended Swara and Dea for the Performance Analysis of Wastewater Treatment Plants: Turkey Case

Public and private companies make significant water infrastructure investments to meet increasing water demand. In this context, investments in wastewater treatment plants (WWTPs), which play an important role in recycling of used water, are also increasing. This study investigates determination of the efficiency scores of WWTPs considering each metropolitan municipality as a decision-making unit (DMU). In this study, a two-step methodology is established to determine efficiency scores of WWTPs. In the first step, the input and output parameters are searched by a literature review for the performance evaluation, and candidate parameters are determined. Then, to determine the most appropriate and related parameters, the importance weights of all candidate inputs and outputs are computed using the extended stepwise weight assessment ratio analysis (SWARA) method. Next, the inputs and outputs are chosen according to their importance weights. In the second step, efficiency scores of WWTPs are calculated using output-oriented data envelopment analysis (DEA) models. Based on the expert opinions, the parameters used as input variables are as follows: Daily Wastewater Amount per Person Discharged in Municipalities, WWTP Capacity, and Number of WWTPs; and the parameters used as output variables are as follows; Amount of Wastewater Treated in WWTPs and Municipal Population Served by WWTPs. The results are presented and discussed by sensitivity analysis. Results show that 14 metropolitan municipalities have total efficiency, 19 metropolitan municipalities have technical efficiency, and 21 metropolitan municipalities have scale efficiency.