Miracle-dz/UniFAR-FTUs huggingface dataset:
Using Metamorphic Testing to Improve the Quality of Tags in OpenStreetMap

We present a metamorphic testing approach to validate the information included in OpenStreetMap, a collaborative effort to produce a free map of the world. We focus on the quality of the tags storing the information about the elements of the map. We identified metamorphic relations with the potential to detect different types of tagging errors. In particular, we carefully designed mechanisms to automatically generate follow-up inputs, a fundamental component in the successful application of a metamorphic testing approach. The intrinsic nature of automatically analysing tags implies that we will detect real errors but some false positives as well. In order to obtain a good trade-off between real errors and false positives, we introduce thresholds. Our MRs will raise an error associated with a certain value if, depending on the nature of the MR, we have a certain number of elements (not) fulfilling a given condition. In order to evaluate the goodness and versatility of our framework, we chose four cities in different continents with the goal of analysing very heterogeneous contributors adding information in different languages. The application of this framework to the analysis of the chosen cities revealed errors in all of them and in all the considered categories. In addition, around 66% of the errors found by our MRs in the analysed areas have not been previously reported by Osmose, the de facto standard OSM error checker.
The Workplace and Psychosocial Experiences of Australian Senior Doctors during the COVID-19 Pandemic: A Qualitative Study

The coronavirus disease 2019 (COVID-19) pandemic has had significant mental health impacts among healthcare workers (HCWs), related to resource scarcity, risky work environments, and poor supports. Understanding the unique challenges experienced by senior doctors and identifying strategies for support will assist doctors facing such crises into the future. A cross-sectional, national, online survey was conducted during the second wave of the Australian COVID-19 pandemic. Inductive content analysis was used to examine data reporting workplace and psychosocial impacts of the pandemic. Of 9518 responses, 1083 senior doctors responded to one or more free-text questions. Of the senior doctors, 752 were women and 973 resided in Victoria. Four themes were identified: (1) work-life challenges; (2) poor workplace safety, support, and culture; (3) poor political leadership, planning and support; and (4) media and community responses. Key issues impacting mental health included supporting staff wellbeing, moral injury related to poorer quality patient care, feeling unheard and undervalued within the workplace, and pandemic ill-preparedness. Senior doctors desired better crisis preparedness, HCW representation, greater leadership, and accessible, authentic psychological wellbeing support services from workplace organisations and government. The pandemic has had significant impacts on senior doctors. The sustainability of the healthcare system requires interventions designed to protect workforce wellbeing.
Dietary Intake of Adults Who Participate in CrossFit® Exercise Regimens

Background: The combination of high-intensity aerobic and high-load resistance training, as in CrossFit®, exerts similar or superior benefits to other exercise modalities. This study aimed to assess dietary habits and characterize the nutritional goals, exercise habits, and clinical health outcomes of individuals who participate in CrossFit®. Methods: Adults who are 19 y or older, with >6 mo of CrossFit® participation, completed an electronic survey and the dietary health questionnaire III. In separate models, multiple stepwise linear regressions were performed to detect the associations between (i) dietary intake, (ii) exercise habits, (iii) clinical measures, and a priori selected predictors (sex, weight status, age, and exercise frequency) in each case. Odds ratios were detected between nutritional and fitness goals, clinical outcomes, and predictors. Results: In total, 449 respondents completed both questionnaires. Of these, 443 respondents were used for relative macronutrients assessment due to not reporting body weight. Dietary intake was associated with sex, weight status, age, exercise frequency, and nutritional goals. Nutritional and fitness goals and clinical outcomes were associated with sex, weight status, age, and exercise frequency. Conclusion: Nutritional goals are underlying factors that affect eating behaviors in non-competitive CrossFit® participants. It is imperative to consider the sex, age, exercise habits, and nutritional goals of CrossFit® participants when investigating and prescribing dietary outcomes.
Prospects of temperature performance enhancement through higher resonant phonon transition designs in GaAs-based terahertz quantum-cascade lasers

In this work we discuss terahertz quantum cascade laser designs that employ resonant phonon mechanism to assist the lasing process. We investigate whether the higher energy separation would be more beneficial for high temperature performance than commonly used resonant value of 36 meV (in GaAs). We show that our density matrix model can be used for reliable cut-off temperature estimation and we present design improvement of several exemplary structures by enhancing their material gain to attain 10–50 K higher cut-off temperature.
Detection of Airborne Nanoparticles through Enhanced Light Scattering Images

A new method is proposed in this paper to detect airborne nanoparticles, detecting the light scattering caused by both the particle and the surrounding molecules, which can surpass the limitations of conventional laser optical methods while maintaining simplicity and cost-effectiveness. This method is derived from a mathematical analysis that describes the particle light scattering phenomenon more exactly by including the influence of light scattered from surrounding gas molecules. The analysis shows that it is often too much of a simplification to consider only light scattering from the detected nanoparticle, because light scattering from the surrounding gas molecules, whether visible or invisible to the sensor, is important for nanoparticle detection. An image detection approach utilizing the light scattering from surrounding air molecules is described for the detection of airborne nanoparticles. Tests using monodisperse nanoparticles confirm that airborne particles of around 50 nm in size can even be detected using a low-cost testing device. This shows further that even when using a simple image processing code, captured particle light scattering images can be converted digitally into instantaneous particle counts or concentrations. The factors limiting conventional pulse detection are further discussed. This new method utilizes a simple static light scattering (SLS) approach to enable the development of new devices with better detection capabilities, paving the way for the further development of nanoparticle detection technology.
AN OVERVIEW OF EXPERIMENTAL RODENT PATHOGENS: HEALTH MONITORING AND LATEST DIAGNOSTIC TECHNIQUES

The system of Rodent health monitoring is critically and crucially dependent upon diagnostics. There are two most important reasons to keep research rodents healthy and free from infections those are; to protect the health and welfare of research rodents and detection and subsequent elimination of disease factors at early stages by using ideal methods can prevent infections from negatively impacting research. Sub clinical infections in rodents modify or alteration in research outcome. In India, over and above 1500 facilities are using laboratory animals for biomedical research. However, majority of them have not implemented the comprehensive disease diagnostic programme or health monitoring due to prohibitive cost of the diagnostic kits. Few facilities in India have implemented international guidelines in health monitoring/disease diagnosis and this includes conventional methods, ELISA and PCR for rapid diagnosis. The expansion of various molecular techniques has developed diagnostic procedures by providing specific diagnosis or detailed characterization of any pathogen or host pathogen interactions. Some of the current immunological and molecular techniques in addition to the conventional ones for the diagnostic technique are discussed in brief. These techniques have been advanced and recognized elsewhere needs to be implemented for rapid and accurate diagnosis of rodent pathogens.
Platform Operations in the Industry 4.0 Era: Recent Advances and the 3As Framework

In the Industry 4.0 era, implementing advanced technologies to enhance platform operations is crucial. Motivated by the importance of platforms and the wide implementation of Industry 4.0-related advanced technologies, we conduct this study on platform operations. Specifically, the platforms discussed herein are classified into (pure) product selling platforms and service platforms. We identify the platform-related operational issues in four categories: 1) the use of information, 2) operating/manufacturing processes, 3) decision support, and 4) consumer behavior and marketing. Based on the examined real-world practices and reviewed prior studies, we propose the novel “3As” framework to indicate how platforms should “adopt” advanced technologies to “address” operational issues to “achieve” outcomes. In addition, the “3As” framework uncovers possible platform innovations with three extended developments. Finally, we present a future agenda for further studies on the use of advanced technologies in platform operations. This article contributes to the operations and engineering management literature by generating insights regarding the implementation of advanced technologies in platform operations in the Industry 4.0 era.
Noninvasive Cardiac Imaging in Formerly Preeclamptic Women for Early Detection of Subclinical Myocardial Abnormalities: A 2022 Update

Preeclampsia is a maternal hypertensive disease, complicating 2–8% of all pregnancies. It has been linked to a 2–7-fold increased risk for the development of cardiovascular disease, including heart failure, later in life. A total of 40% of formerly preeclamptic women develop preclinical heart failure, which may further deteriorate into clinical heart failure. Noninvasive cardiac imaging could assist in the early detection of myocardial abnormalities, especially in the preclinical stage, when these changes are likely to be reversible. Moreover, imaging studies can improve our insights into the relationship between preeclampsia and heart failure and can be used for monitoring. Cardiac ultrasound is used to assess quantitative changes, including the left ventricular cavity volume and wall thickness, myocardial mass, systolic and diastolic function, and strain. Cardiac magnetic resonance imaging may be of additional diagnostic value to assess diffuse and focal fibrosis and perfusion. After preeclampsia, sustained elevated myocardial mass along with reduced myocardial circumferential and longitudinal strain and decreased diastolic function is reported. These findings are consistent with the early phases of heart failure, referred to as preclinical (asymptomatic) or B-stage heart failure. In this review, we will provide an up-to-date overview of the potential of cardiac magnetic resonance imaging and echocardiography in identifying formerly preeclamptic women who are at high risk for developing heart failure. The potential contribution to early cardiac screening of women with a history of preeclampsia and the pros and cons of these imaging modalities are outlined. Finally, recommendations for future research are presented.
PCL/Sodium-Alginate Based 3D-Printed Dual Drug Delivery System with Antibacterial Activity for Osteomyelitis Therapy

Chronic osteomyelitis is mostly caused by bacteria such as S. aureus, and is often treated with oral antibiotics or injections to suppress the bacteria. In severe cases, however, surgical treatment using antibiotic beads and metal supports may be required. In these surgeries, bacterial attachment to the metal may lead to biofilm formation and reduce antibiotics’ penetration to the bacteria. Reoperation must be performed to prevent bacterial inflammatory reactions and antibiotic resistance. Thus, in this study, we developed a dual-drug-releasing PCL/sodium-alginate-based 3D-printed scaffold to effectively treat osteomyelitis by removing the biofilm. We proposed an antibiotic-loaded biodegradable polymer scaffold using 3D printing, which was encapsulated by a second antibiotic-containing hydrogel. Then, we successfully established a dual-drug-based scaffold that consisted of a cefazolin (CFZ)-containing polycaprolactone 3D scaffold and a rifampicin (RFP)-loaded alginate hydrogel encapsulating the 3D scaffold. Our scaffold showed a synergistic effect, whereby biofilm formation was inhibited by RFP, which is an external drug, and bacterial activity was inhibited by CFZ, which is an internal drug that increases antibacterial activity. We also confirmed that the dual-drug-based scaffold did not affect the proliferation of human osteoblasts. Our findings suggest that this dual drug delivery system may serve as a new therapeutic treatment for osteomyelitis that overcomes the limitations of individual drugs.
Diagnosis of Cubital Tunnel Syndrome Using Deep Learning on Ultrasonographic Images

Although electromyography is the routine diagnostic method for cubital tunnel syndrome (CuTS), imaging diagnosis by measuring cross-sectional area (CSA) with ultrasonography (US) has also been attempted in recent years. In this study, deep learning (DL), an artificial intelligence (AI) method, was used on US images, and its diagnostic performance for detecting CuTS was investigated. Elbow images of 30 healthy volunteers and 30 patients diagnosed with CuTS were used. Three thousand US images were prepared per each group to visualize the short axis of the ulnar nerve. Transfer learning was performed on 5000 randomly selected training images using three pre-trained models, and the remaining images were used for testing. The model was evaluated by analyzing a confusion matrix and the area under the receiver operating characteristic curve. Occlusion sensitivity and locally interpretable model-agnostic explanations were used to visualize the features deemed important by the AI. The highest score had an accuracy of 0.90, a precision of 0.86, a recall of 1.00, and an F-measure of 0.92. Visualization results show that the DL models focused on the epineurium of the ulnar nerve and the surrounding soft tissue. The proposed technique enables the accurate prediction of CuTS without the need to measure CSA.
Integrated Inductor Design for a Highly Compact Embedded Battery Charger

An integrated inductor for a highly compact embedded battery charger is designed in this article. A zero-voltage switching (ZVS) buck converter is the selected topology to achieve high power density. ZVS is achieved by sizing the inductor based on energy balance and introducing the <inline-formula><tex-math notation="LaTeX">$k$</tex-math></inline-formula> factor. A novel four-leg magnetic core structure is proposed as the integrated inductor. By introducing a modified parameter <inline-formula><tex-math notation="LaTeX">$\alpha _{\mathrm{eff}}$</tex-math></inline-formula> to the improved generalized Steinmetz equation method, the optimal switching frequency for core losses can be found. From the constructed inductor model and semiconductor loss calculation, the design tradeoff and optimization is analyzed. The optimal <inline-formula><tex-math notation="LaTeX">$f_{\mathrm{sw}}$</tex-math></inline-formula> is found to be around 2 MHz, which is when the performance factor for the core material peaks. As a proof of concept, a highly compact prototype, featuring stacked printed circuit board solution, with 16.2 × 19.2 × 6 mm<inline-formula><tex-math notation="LaTeX">$^{3}$</tex-math></inline-formula> dimension is built. The input voltage ranges from 6 to 12 V, and the converter is capable of delivering up to 10 A at the 4-Voutput. Converter peak efficiency of 96% is achieved, and the inductor design has a power density of 113.6 W/cm<inline-formula><tex-math notation="LaTeX">$^{3}$</tex-math></inline-formula>. This shows improvement over several state-of-the-art designs. This article is accompanied by a video demonstrating the flux distribution in the magnetic core over the switching period.
USING MAUT BASED MULTI-CRITERIA DECISION SUPPORT TECHNIQUES FOR INTEGRATING EXPERT KNOWLEDGE IN DESIGNING FASHION ORIENTED PRODUCTS

The present paper proposes a new technique to integrate expert judgment in new product development process. The technique is based in the Multi attribute Utility Theory, and has been developed in order to obtain a better interpretation of the expert preferences as he or she evaluates a product sample. A utility function is determined by polynomial approximation, from a database outcome of the individual’s expert evaluations concerning six predetermined fashion themes. The obtained results allow to define the utility function’s shape and the weights of the set of criteria. This identification will leads to a better interpretation of the expert preferences, the degree of exigency and importance of each design criterion. The approach is tested and validate on two set of products price driven market and fashion driven market.
Breast Cancer and Atrial Fibrillation

This study aims to establish the incidence of atrial fibrillation (AF) in breast cancer (BC) patients, focusing on staging and anti-cancer treatment. A meta-analysis was conducted to investigate the incidence of AF in BC patients and compare this incidence to other cancers. Furthermore, we evaluated the occurrence of AF as an adverse effect of biological therapies vs. non-biological therapies vs. biological therapies + non-biological therapies in BC. Finally, we compared the incidence of AF in early BC and metastatic BC. Thirty studies were included. Twenty-two studies focused on BC, encompassing 166,271 patients. In the BC group, 2.7% of patients developed AF, while in the “all cancer” group, 5.8% of patients developed AF. In addition, there was no difference between different types of therapies (p = 0.61) and between early and metastatic BC (p = 0.57). The type of anti-cancer therapy and the staging of BC does not influence AF’s occurrence in this neoplastic disease.
How Does Environmentally Specific Servant Leadership Fuel Employees’ Low-Carbon Behavior? The Role of Environmental Self-Accountability and Power Distance Orientation

Environmental problems caused by excessive carbon emissions are becoming increasingly prominent and have received heightened attention in recent years. Encouraging people to adopt low-carbon behavior to reduce carbon emissions is desirable. Based on social learning theory, we developed and tested a moderated mediation model to investigate when and how environmentally specific servant (ESS) leadership impacts employees’ low-carbon behavior (i.e., private low-carbon behavior and public low-carbon behavior). We tested our theoretical framework with a sample of 483 subordinates and their direct supervisors working in northern China. The results indicate that ESS leadership is positively related to employees’ low-carbon behavior, and that environmental self-accountability plays a mediating role in this relationship. In addition, power distance orientation strengthens the direct effects of ESS leadership on employees’ environmental self-accountability and low-carbon behavior, as well as the indirect effect of ESS leadership on private low-carbon behavior via environmental self-accountability. Our findings contribute to the literature surrounding ESS leadership and low-carbon behavior, and help to promote green development and thus achieve the goals of carbon neutrality and decreasing carbon dioxide emissions.
Black Box Approach for Energy Monitoring of Commercial Buildings

The potential to save energy by changing operational parameters especially in existing commercial buildings – is in the magnitude of 5-30%. In order to realize this saving potential in the long term, continuous commissioning of the building is a key issue. Necessary for successful continuous commissioning is real time monitoring of the building performance which allows for Fault Detection and Diagnosis (FDD). This paper presents a method to monitor building operation and detect faulty or unusual behaviour using a black box model approach. The approach is to identify a building’s basic operating characteristics by means of measured data from a building to train a multiple linear regression model based on energy signatures of the building. In addition to supplying measured building data to the regression a clustering process is added which determines the building’s day-types. Once the model is trained it can predict the energy consumption at the building site and unusual or faulty days can be identified by comparing the predictions to real measurements. Models to monitor the daily heating and electricity demand are developed and applied to measured data from two demonstration buildings.
A HepG2 Cell-Based Biosensor That Uses Stainless Steel Electrodes for Hepatotoxin Detection

Humans are frequently exposed to environmental hepatotoxins, which can lead to liver failure. Biosensors may be the best candidate for the detection of hepatotoxins because of their high sensitivity and specificity, convenience, time-saving, low cost, and extremely low detection limit. To investigate suitability of HepG2 cells for biosensor use, different methods of adhesion on stainless steel surfaces were investigated, with three groups of experiments performed in vitro. Cytotoxicity assays, which include the resazurin assay, the neutral red assay (NR), and the Coomassie Brilliant Blue (CBB) assay, were used to determine the viability of HepG2 cells exposed to various concentrations of aflatoxin B1 (AFB1) and isoniazid (INH) in parallel. The viability of the HepG2 cells on the stainless steel surface was quantitatively and qualitatively examined with different microscopy techniques. A simple cell-based electrochemical biosensor was developed by evaluating the viability of the HepG2 cells on the stainless steel surface when exposed to various concentrations of AFB1 and INH by using electrochemical impedance spectroscopy (EIS). The results showed that HepG2 cells can adhere to the metal surface and could be used as part of the biosensor to determine simple hepatotoxic samples.