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GOALS This paper discusses the need for a predictable method to evaluate gains and gaps of collaborative technology-mediated workflows and introduces an evaluation framework to address this need. METHODS The Collaborative Space Analysis Framework (CS-AF), introduced in this research, is a cross-disciplinary evaluation method designed to evaluate technology-mediated collaborative workflows. The 5-step CS-AF approach includes: (1) current-state workflow definition, (2) current-state (baseline) workflow assessment, (3) technology-mediated workflow development and deployment, (4) technology-mediated workflow assessment, (5) analysis, and conclusions. For this research, a comprehensive, empirical study of hypertension exam workflow for telehealth was conducted using the CS-AF approach. RESULTS The CS-AF systemized approach reveals critical cross-disciplinary evaluation data concerning gains and gaps of collaborative workflows when technology-mediated enhancements are characterized and compared with a baseline workflow for the goal of continuous workflow improvement. CONCLUSION The CS-AF is an effective approach that can be adapted for use in multiple domains.

Background The use of physician review websites by patients is increasingly frequent. One potential way for shoulder and elbow surgeons to enhance their online reputation and attract patients is via social media, yet its impact is unknown. This study sought to analyze the effect of social media use on the number of online ratings and overall rating of shoulder and elbow surgeons. We secondarily studied variables affecting social media use. Methods The American Shoulder and Elbow Surgeons directory was probed to identify practicing surgeons. Surgeon evaluation data, including ratings, comments, and reviews, were compiled from 3 physician review websites (Google, Healthgrades, and Vitals). Google was queried to assess for a professional Facebook, Twitter, or Instagram account, as well as obtain information on surgeon training, practice location, and other demographic variables. Results A total of 646 surgeons met the inclusion criteria (93.8% male and 6.2% female surgeons). Overall, 37% had a professional social media account (Facebook, 23.1%; Twitter, 24.1%; and Instagram, 9.4%). Linear regression analysis showed that Facebook use correlated with an average increase of 48.6 in the number of ratings. No social media platform correlated with physician rating. The surgeons more likely to use social media were those who graduated residency in 2000 or later (40.8% vs. 29.2%), those who practiced in cities with higher populations (mean, 1188.9 vs. 708.4 [per 1000]), and those with more surgeons practicing in the same city (mean, 7.0 vs. 5.0). Conclusion The majority of shoulder and elbow surgeons do not have a professional social media account. Those using this platform are younger and located in more populous cities with more competition. Having a professional social media profile was not correlated with ratings, but there was a positive association with the number of online ratings, and Facebook had the strongest association. Surgeon ratings are overwhelmingly positive with minimal variability; therefore, a high number of ratings confirms a surgeon’s exceptional reputation. The residency graduation year, city population, and number of nearby surgeons affected ratings, although the absolute differences were minimal. For shoulder and elbow surgeons, a professional social media account correlates with an increase in the number of online physician ratings. Recent graduates practicing in competitive locations may feel increased pressure to leverage this in an attempt to build their practices.

Trusted network is currently evaluated based on the trustworthiness of the nodes in the network; thus, trust in the nodes is required to achieve trust in the network. The methods for calculating node trust mainly utilize the following three types of models:node behavior model, multiple-attribute decision-making model and reputation model. User behavior model always determines trust values based on harmful node behaviors. Multi-attribute decision-making model can be regarded as refinements of node behavior model. The trust values of the nodes are determined based on compromised trust attribute data and not just harmful behavior data. Reputation model calculates the trust values of nodes using subjective evaluation data for nodes. This paper presents a comprehensive trust model that combines subjective evaluation data and objective attribute data to calculate node trust. The experimental results show that malicious nodes can be effectively identified, which improves the service success rate of the system.

The estimated ultimate recovery (EUR) of shale gas wells is influenced by many factors, and the accurate prediction still faces certain challenges. As an artificial intelligence algorithm, deep learning yields notable advantages in nonlinear regression. Therefore, it is feasible to predict the EUR of shale gas wells based on a deep-learning algorithm. In this paper, according to geological evaluation data, hydraulic fracturing data, production data and EUR evaluation results of 282 wells in the WY shale gas field, a deep-learning-based algorithm for EUR evaluation of shale gas wells was designed and realized. First, the existing EUR evaluation methods of shale gas wells and the deep feedforward neural network algorithm was systematically analyzed. Second, the technical process of a deep-learning-based algorithm for EUR prediction of shale gas wells was designed. Finally, by means of real data obtained from the WY shale gas field, several different cases were applied to testify the validity and accuracy of the proposed approach. The results show that the EUR prediction with high accuracy. In addition, the results are affected by the variety and number of input parameters, the network structure and hyperparameters. The proposed approach can be extended to other shale fields using the similar technic process.

Background Static eyelid reconstruction surgery, such as ptosis repair or brow lift, is widely performed for patients with facial paralysis. Complications include exposure keratitis and possible vision loss mainly due to eyelid closure impairment in spontaneous blinking. However, no quantitative evaluation data has been available regarding postoperative closure deterioration. Methods To elucidate factors associated with postoperative eyelid closure impairment, a retrospective study was performed for 51 patients who underwent an initial static eyelid reconstruction surgery from October 2017 to August 2020. A static eyelid reconstruction surgery consisted of either 1 or more of the following: (1) levator advancement, (2) brow lift, and (3) orbicularis oculi myectomy. Eyelid closure ratios (0% for complete closure impairment and 100% for perfect closure) at spontaneous blinks were measured on 6 occasions: before operation and at postoperative 1, 3, 6, 9, and 12 months. Comparison was made between preoperative and postoperative values by using mixed-effects model. Results Overall, average closure ratio was significantly increased. However, 10 patients had >10% closure ratio decreases at at least 1 postoperative measurement point, and all those patients had undergone brow lift procedures. Conclusions Although eyelid closure at spontaneous blinks may, contrary to assumptions, generally be improved after static eyelid reconstruction surgery, brow lift was suggested to be associated with eyelid closure impairment.

This research aimed to study whether Enteromorpha polysaccharide-zinc (EP-Zn) can act as an alternative to antibiotics in weaned piglet feeds. Two hundred and twenty-four weaned piglets from 14 pens were randomly assigned into 1 of 2 groups according to their body weight and litter size (7 pens/group). The piglets in the antibiotics group were fed with olaquindox at 400 mg/kg and enduracidin at 800 mg/kg basal diet, and piglets in the EP-Zn group were fed with EP-Zn at 800 mg/kg basal diet. One piglet per pen was selected to collect samples after 14 d of feeding. Results showed that EP-Zn supplementation significantly increased the plasma anti-oxidants level compared with the antibiotics group. However, a nonsignificant difference was observed in growth performance between treatment groups. Additionally, the intestinal tight junction (TJ) protein expression and the histopathologic evaluation data showed that EP-Zn contributed to improving intestinal development. Further, piglets in the EP-Zn group had a lower level of intestinal inflammation-related cytokines including IL-6 (P

Problematic physical activity (PPA) is a symptom commonly present in patients suffering from anorexia nervosa (AN). This study aims to refine the clinical description of children with early-onset AN and adolescents with standard-onset AN and associated PPA, in order to better understand their associated features, and to offer them adapted care and physical activity programs. 107 participants treated at the Salvator University Hospital Centre of Marseille for AN were retrospectively evaluated by the Exercise Dependence Scale Revised concerning PPA. Other self-report questionnaires were used to evaluate eating disorder, anxiety and depressive symptoms, quality of life, emotions, sleep, and attention deficit disorder with or without hyperactivity. In the entire sample, the presence of PPA was associated with significantly higher levels of eating disorder (EDI-2: p = 0.001) and body image concerns (p = 0.002), anxiety (STAI-Y-trait: p = 0.013) and depression (p = 0.006), as well as significantly lower psychological well-being (p

Introduction 1 in 2 women and 1 in 5 men over the age of 50 will break a bone and a significant proportion will suffer from osteoporosis.A fragility fracture will double the risk of future fractures. Between 1990 and 2000, there was nearly a 25% increase in hip fractures worldwide. A hip fracture is one of the most devastating, and often terminal, injury for an older person. Intervention The Fracture Liaison Service (FLS) captures patients aged 50 and above that present to fracture clinic with possible fragility fractures with the aim to reduce further fracture incidence. Patients are assessed for osteoporosis and recommendations made for treatment. Results Here we present the results of our FLS service evaluation after 6 years in operation, using the rate of hip fractures (number of hip fractures/Emergency Department [ED] attendances over 75’s) as a surrogate marker for effectiveness. Evaluation Summary Trend analysis of our data indicates a reduction in the number of patients attending the Trust with fractured neck of femur (NOF) despite the increase in ED attendances. This is against the trend nationally where fractured NOF numbers are rising (National Hip Fracture Database, accessed online August 2019). Next steps The FLS to attempt to comprehensively capture muscular-skeletal patients and to consider opportunities present to target case finding to high risk cohorts.

Gas protective walls are safety elements that can withstand the pressure of fires or explosions caused by gas leaks, thus preventing the spread of explosion damage to other facilities or operators. However, in the new construction or expansion of gas facility rooms in existing buildings, the barrier must often be built even if it does not satisfy the legal standards regarding the accepted construction methods. In these cases, the gas barrier for the existing building should be constructed by the new construction method using chemical anchor bolts. However, no performance evaluation data or reliable engineering verification results are available for the entire gas facility room based on actual experiments. In this study, based on a review of regulations on gas barriers, the protective performances of the new barriers were compared in terms of displacement, rotation angle, rebar strain, and yield value of the concrete surface through actual strength demonstration experiments. Based on these results, the protection performance of an entire gas facility room that could not be constructed and tested in real time was evaluated by a fluid structure interaction (FSI) analysis using the TNT(Trinitrotoluene) equivalency method and three-dimensional AUTODYN.

Background: One of the efforts to improve community nutrition is through PMBA training for cadres. In the implementation, training has been carried out in several generations in the Kalasan sub-district, but there is no evaluation data on the level of knowledge about Infant and Young Child Feeding (IYCF) to cadres. Objective: To know the description of cadres' knowledge level on the Infant and Young Child Feeding in Kalasan District. Method: This study used a quantitative descriptive method. The sampling technique used was purposive sampling by involving 52 Posyandu cadres in Kalasan District. Results: The results showed that 33 people (63.5%) are in the good category, 18 people (34.6%) are in the moderate category and 1 person (1.9%) is in the poor category. Most of the cadres who already knew the definition of IMD is 51 (98.1%) people but had a lack of understanding about the implementation of IMD at surgical birth (36.5%), a sign of good attachment during breastfeeding (17.3%), and about snacks in infants 6-9 months (44.2%). Conclusion: The distribution results on the knowledge levels of infant and child feeding are mostly good, especially in understanding the definition of IMD, although there is a lack of knowledge on understanding the implementation of IMD in operative births, about signs of attachment during breastfeeding, and about complementary foods.

Background In this study, we developed online interactive clinician education modules highlighting best practices to minimize opioid prescribing at discharge after surgery. The modules were implemented as part of a multicomponent quality improvement initiative across a six-hospital health system. This article describes the development and evaluation of this educational intervention. Materials and Methods Clinician education modules targeting surgical prescribers, nurses, and pharmacists were developed and implemented by an interdisciplinary team. Clinicians were invited to participate in an evaluation survey after completing the modules. Survey items assessed clinicians’ rating of the module and intention to change clinical practice because of the module. Quantitative and qualitative survey responses were analyzed by the study team. Results A total of 2119 clinicians completed the module and 1831 of these clinicians (86.4%) completed the survey. Of clinicians completing the survey, 65.6% reported that they intend to change clinical practice after completing the module. Intended changes were related to increased knowledge and awareness, provider empowerment, opioid prescribing practices, nonopioid prescribing practices, and patient education. Many clinicians who indicated they do not intend to change practice reported that their clinical practices were already in line with module recommendations. Some clinicians did not perceive the module to be relevant to their role. Conclusions Module completion was associated with the intention to improve clinical practice in areas related to provider empowerment, opioid prescribing, nonopioid prescribing, and patient education. Evaluation data will inform future module improvements. There is an opportunity to ensure that all clinicians, including those who are not prescribers, recognize their role in opioid stewardship.

This work explores the application of Cognitive Work Analysis (CWA) in the context of Explainable Artificial Intelligence (XAI). We built an AI system using a loan evaluation data set and applied an XAI technique to obtain data-driven explanations for predictions. Using an Abstraction Hierarchy (AH), we generated domain knowledge-based explanations to accompany data-driven explanations. An online experiment was conducted to test the usefulness of AH-based explanations. Participants read financial profiles of loan applicants, the AI system’s loan approval/rejection decisions, and explanations that justify the decisions. Presence or absence of AH-based explanations was manipulated, and participants’ perceptions of the explanation quality was measured. The results showed that providing AH-based explanations helped participants learn about the loan evaluation process and improved the perceived quality of explanations. We conclude that a CWA approach can increase understandability when explaining the decisions made by AI systems.

BackgroundHackathons aim to develop solutions to preidentified problem domains and catalyse startup cultures. Recently, the teaching and learning potential of hackathons has also been documented. In this study, we make the case for utilisation of hackathons as an alternative teaching and learning tool geared towards entrepreneurship and as an opportunity for interprofessional integration.MethodsThis research study followed up with participants from the third hackathon at the Aga Khan University in Karachi, Pakistan. Hack MedEd was about solutions to problems of undergraduate and postgraduate medical education with an emphasis on low-income to middle-income countries. Participant evaluation data were filled at the end of the hackathon and gathered from three focused group discussions (FGDs): immediately before and after the event, a delayed follow-up after 11 months was recorded.ResultsOf 116 participants, the majority (71%) were under 30 years old, and over half were female. The evaluations provided by hackers were positive overall with a mean score of 4.37 out of 5 on a Likert Scale. During the FGDs, participants spoke positively of the process and felt that, by the end of the hackathon, they had learnt something new. In the delayed follow-up FGD, teams that had undergone incubation expressed that they had gained a critical and simple skillset that they might not have acquired otherwise.ConclusionHackathons business incubation programmes may be considered an alternative teaching and learning tool—especially for individuals studying or working within the healthcare discipline within low-resource settings.

This paper describes the interface and testing of an indoor navigation app - ASSIST - that guides blind & visually impaired (BVI) individuals through an indoor environment with high accuracy while augmenting their understanding of the surrounding environment. ASSIST features personalized interfaces by considering the unique experiences that BVI individuals have in indoor wayfinding and offers multiple levels of multimodal feedback. After an overview of the technical approach and implementation of the first prototype of the ASSIST system, the results of two pilot studies performed with BVI individuals are presented – a performance study to collect data on mobility (walking speed, collisions, and navigation errors) while using the app, and a usability study to collect user evaluation data on the perceived helpfulness, safety, ease-of-use, and overall experience while using the app. Our studies show that ASSIST is useful in providing users with navigational guidance, improving their efficiency and (more significantly) their safety and accuracy in wayfinding indoors. Findings and user feed-back from the studies confirm some of the previous results, while also providing some new insights into the creation of such an app, including the use of customized user interfaces and expanding the types of information provided.

Translating deep learning research from theory into clinical practice has unique challenges, specifically in the field of neuroimaging. In this paper, we present DeepNeuro, a Python-based deep learning framework that puts deep neural networks for neuroimaging into practical usage with a minimum of friction during implementation. We show how this framework can be used to design deep learning pipelines that can load and preprocess data, design and train various neural network architectures, and evaluate and visualize the results of trained networks on evaluation data. We present a way of reproducibly packaging data pre- and postprocessing functions common in the neuroimaging community, which facilitates consistent performance of networks across variable users, institutions, and scanners. We show how deep learning pipelines created with DeepNeuro can be concisely packaged into shareable Docker and Singularity containers with user-friendly command-line interfaces.

It is an important and challenging task to develop concepts and skills of undergraduate engineering students in computer programming course and hence their evaluation on higher order skills. Already several methods are developed to evaluate the students of this course for various engineering programs, but a method for undergraduate electrical and electronic engineering (EEE) program was not found in the literature. In this paper, a simple evaluation method for the students of computer programming course of undergraduate EEE (BSc in EEE) program has been reported using result-oriented learning. Detail methodology, course syllabus design, course outcomes (COs) and mapping it with program outcomes (POs) of BSc in EEE, question setting following Bloom’s taxonomy, laboratory experiment, assessment plan, course and PO evaluation data and graphs have been presented along with relevant statistics. All data are presented for a cohort of students who took this course in summer 2019 Semester at EEE Department of Southeast University. It has been observed that the target set by the course teacher has been achieved by the students. Recommendations of the course teacher for further improvement of the COs’ achievement have also been presented. Keywords: CO evaluation, programming course, OBE

Cooperative Extension programs across the United States are embracing food systems and local food as a new topic area. Previous studies indicate that successful local food programming requires cross-program collaboration. However, research in this area has underrepresented Extension educators from non-agricultural program areas, although understanding their perspectives is key to fostering cross-program collaboration. The case study pre­sented in this paper examines qualitative evaluation data from the pilot year of the NC State Extension Master Food Volunteer (EMFV) program, which provides training in food systems and local food to Family and Consumer Sciences (FCS) educators and their volunteers. Data from semistructured interviews with educators in the pilot program and from focus groups with their volunteers provide the opportunity to explore areas of intersection and divergence between local food and the FCS pro­gram area in order to determine how to best inte­grate FCS and local food. Findings suggest that integrating local food into FCS pro­gramming will require special attention to poten­tially controversial issues that require educators and volunteers to communicate with the public about scientific issues that also invoke personal values, such as pesticide use and genetic engineering. We also found that educators and volunteers felt that promoting local food was not always compatible with an FCS focus on healthy eating. Overall, this case study demon­strates the potential to engage FCS educators and volunteers in cross-program, community-based food system projects, and to provide public educa­tion in the growing field of food systems and local food. See the press release for this article.

Problem identification Cancer screening may reduce mortality and frequency of the disease. Lesbian, gay, bisexual, transgender, or queer (LGBTQ) individuals are less likely than non-LGBTQ individuals to present for cancer screening. Literature search A literature search was performed using CINAHL®, PsycINFO®, and PubMed®. Articles were included if they were published in English from 2008 to 2018 and addressed barriers or facilitators to cancer screening in LGBTQ populations. Data evaluation Data were organized by thematic matrix and classified according to the multilevel influences on the cancer care continuum framework. Synthesis This integrative review found that the lack of cancer screening data and knowledge about screening guidelines by LGBTQ populations and providers were major barriers to cancer screening adherence. Provider-created welcoming environments and caregiver inclusion were facilitators. Implications for practice Determinants of health-seeking behavior included patients' and providers' lack of cancer screening knowledge, as well as perceived discrimination. Nurses are in a unique position to provide cancer screening information and culturally sensitive care for LGBTQ populations with adequate education.

Bacterial drugs for the treatment of malignant tumors have been discovered more than a hundred years ago, but their use in clinical practice has been very limited. In the past decade, there has been a revival of interest in the development of bacterial-based cancer biotherapies, which is associated with advances in genetic engineering and in depth knowledge of the mechanisms of the infectious process and immunity. The purpose of this review is to examine the current state and prospects for the development and use of drugs based on live bacterium, intended for the treatment of malignant tumors. The review presents evaluation data on experimental models of the antitumor potential of various species and strains of bacteria; the most significant results of clinical trials of bacterial antitumor agents; current trends in the design of bacterial strains for targeted drug delivery to the tumor. It is concluded that development of bacterial drugs for cancer therapy is a perspective branch of experimental oncology.

There is great interest in reshaping the Supplemental Nutrition Assistance Program (SNAP) so that it better supports family nutrition, and an array of program changes have been proposed. We note the importance of considering the unique needs of rural SNAP participants when considering and implementing these changes. We also describe the SNAP-related needs and challenges unique to rural SNAP participants, and through this lens we discuss changes to SNAP that have been proposed and special considerations related to each. The special considerations we identified include allowing canned, frozen, and dried fruits and vegetables as eligible items in financial incentive programs in rural areas; changing direct education programming to address transportation-related barriers many rural families face in attending in-person classes; and supporting rigorous research to evaluate the potential benefits and unintended consequences of proposed program changes for which scant high-quality evaluation data exist. Evaluation studies should include rural SNAP participants so that effects in this important population group are known.

Power quality evaluation data are heterogeneous and fluctuating, and there are large subjective factors in the evaluation process. To solve this problem, a power quality evaluation method based on ...

The comparative performances of physiologically‐based pharmacokinetic (PBPK) modeling and allometric scaling for predicting the pharmacokinetics (PKs) of large molecules in pediatrics are unknown. Therefore, both methods were evaluated for accuracy in translating knowledge of infliximab PKs from adults to children. PBPK modeling was performed using the base model for large molecules in PK‐Sim version 7.4 with modifications in Mobi. Eight population PK models from literature were reconstructed and scaled by allometry to pediatrics. Evaluation data included seven pediatric studies (~4–18 years). Both methods performed comparably with 66.7% and 68.6% of model‐predicted concentrations falling within twofold of the observed concentrations for PBPK modeling and allometry, respectively. Considerable variability was noted among the allometric models. Therefore, pediatric clinical trial planning would benefit from using approaches that require predictions depending on the specific question i.e., PBPK modeling and allometry.

BACKGROUND High-altitude cardiovascular adaptations increase lung pressure. This effect on the right ventricle (RV) of transplanted hearts at altitudes above 2,500 meters above sea level (masl) has not been described. OBJECTIVE The objective of the study was to describe echocardiography RV behavior in the immediate post-operative period (Days 1-7 post-Heart transplant [HTx]), 3, 6, 12, and 24 months after HTx in patients at 2640 masl. METHODS Historical cohort of HTx patients in the period between 2005 and 2019, in a hospital located in Bogota, Colombia. Socio-demographic, clinical, and echocardiographic evaluation data of the RV at 5 follow-up moments were analyzed. RESULTS 91 patients underwent HTx, 64% remained at a height > 2500 masl in the post-operative period. Transthoracic echo was available in 37 patients (40.6%). Right ventricular dysfunction was found in 95% of patients, which was predominantly moderate (43%), with improvement 3 months after transplant. The immediate post-operative Tricuspid annular plane systolic excursion was 8.9 ± 4.9 mm, with recovery from the 3rd post-operative month (15.1 ± 3.6 mm) and without significant changes in month 24 (15.8 ± 4.9 mm). Immediate post-operative systolic pulmonary artery pressure (sPAP) was 39.2 ± 8.2 mmHg, showing a decrease at 24 post-operative months (31.0 ± 5.0 mmHg). The 5-year survival was 78% Confidence Interval 95% 60-85. CONCLUSION After HTx, most patients present right ventricular dysfunction, improving at the 3rd month of transplant. There were no significant differences between patients living at more than 2500 masl and < 2500 masl.

Background Clinical diagnostics of whole-exome and whole-genome sequencing data requires geneticists to consider thousands of genetic variants for each patient. Various variant prioritization methods have been developed over the last years to aid clinicians in identifying variants that are likely disease-causing. Each time a new method is developed, its effectiveness must be evaluated and compared to other approaches based on the most recently available evaluation data. Doing so in an unbiased, systematic, and replicable manner requires significant effort. Results The open-source test bench “VPMBench” automates the evaluation of variant prioritization methods. VPMBench introduces a standardized interface for prioritization methods and provides a plugin system that makes it easy to evaluate new methods. It supports different input data formats and custom output data preparation. VPMBench exploits declaratively specified information about the methods, e.g., the variants supported by the methods. Plugins may also be provided in a technology-agnostic manner via containerization. Conclusions VPMBench significantly simplifies the evaluation of both custom and published variant prioritization methods. As we expect variant prioritization methods to become ever more critical with the advent of whole-genome sequencing in clinical diagnostics, such tool support is crucial to facilitate methodological research.

Computational human body models (HBMs) of drivers for pre-crash simulations need active shoulder muscle control, and volunteer data are lacking. The goal of this paper was to build shoulder muscle dynamic spatial tuning patterns, with a secondary focus to present shoulder kinematic evaluation data. 8M and 9F volunteers sat in a driver posture, with their torso restrained, and were exposed to upper arm dynamic perturbations in eight directions perpendicular to the humerus. A dropping 8-kg weight connected to the elbow through pulleys applied the loads; the exact timing and direction were unknown. Activity in 11 shoulder muscles was measured using surface electrodes, and upper arm kinematics were measured with three cameras. We found directionally specific muscle activity and presented dynamic spatial tuning patterns for each muscle separated by sex. The preferred directions, i.e. the vector mean of a spatial tuning pattern, were similar between males and females, with the largest difference of 31° in the pectoralis major muscle. Males and females had similar elbow displacements. The maxima of elbow displacements in the loading plane for males was 189 ± 36 mm during flexion loading, and for females, it was 196 ± 36 mm during adduction loading. The data presented here can be used to design shoulder muscle controllers for HBMs and evaluate the performance of shoulder models.

The semiconductor industry is enjoying the “Semiconductor super cycle” catalyzed by the pandemic. In addition, the variety of semiconductor chips are increasing driven by electronification of everything resulting the demand for laser based mask writers are increasing due to lower exposure cost per mask. However, many laser mask writers in operation today are getting old. As a response to the growing demand Mycronic introduced SLX series, a new generation cost-efficient laser mask writer and the superiority of the system is demonstrated by sharing recent evaluation data with two different laser sources.

The popularity of cannabidiol (CBD) in consumer products is soaring as consumers are using CBD for general health and well-being as well as to seek relief from ailments especially pain, inflammation, anxiety, depression, and sleep disorders. However, there are limited data currently in the public domain that provide support for these benefits. By contrast, a significant amount of safety evaluation data for CBD have been obtained recently from pre-clinical and clinical studies of the CBD therapeutic Epidiolex®. Yet some key data gaps concerning the safe use of CBD still remain. Furthermore, current regulations on CBD use in consumer products remain uncertain and often conflict between the state and federal level. In light of the rapidly expanding popularity of CBD-related products in the marketplace, here we review the current understanding of the benefits, safety, and regulations surrounding CBD in consumer products. This review does not advocate for or against the use of CBD in consumer products. Rather this review seeks to assess the state-of-the-science on the health effects and safety of CBD, to identify critical knowledge gaps for future studies, and to raise the awareness of the current regulations that govern CBD use in consumer products.

At the shortcomings of low convergence efficiency and weak generalization performance in current scientific research management, a scientific research management model based on neural network AHP-BP is proposed. Construct the performance evaluation index system, collect the corresponding performance evaluation data, use neural network AHP-BP to simulate the human brain to train the performance data, and use the gradient method to determine the parameters of the neural network AHP-BP to establish a performance evaluation model. Finally, its performance is tested through simulation experiments. Actually, this paper studies the management of colleges and universities in Guangxi based on neural network of AHP and BP.

Objectives: The results of coronary CTA for patients with arrhythmia were compared under different phase One-Beat scanning mode. Methods: 100 patients with arrhythmia were selected and randomly divided into control group and observation group. The relative phase-scanning mode and absolute phase-scanning mode were used for examination. Subjective and objective evaluation methods were used for image quality analysis, while variance analysis and Spearman correlation analysis were used for statistical analysis. Results: The subjective scores of all 13 segments in the observation group were higher than those in the control group, and the differences in 6 segments were statistically significant (P

Most of the existing calculation method of expert evaluation ability directly call data onto calculation, which leads to the risk of privacy leakage of expert review information and affects the peer review environment. With regard to this problem, a privacy protection method of experts' evaluation ability calculation of peer review is proposed. Privacy protection and data usability are adjusted according to privacy preferences. Using Gauss distribution and combining with the distributive law of real evaluation data, the virtual projects are generated, and the project data are anonymized according to the virtual projects. Laplace distribution is used to add noise to the evaluation sub score for perturbation, and the evaluation data are obfuscation according to the perturbation sub score. Based on the protected project data and evaluation data, the expert evaluation ability is calculated, and the review privacy is protected. The experimental results show that the proposed method can effectively balance the privacy protection and the accuracy of the calculation results.

One important approach to human brain mapping is to define a set of distinct regions that can be linked to unique functions. Numerous brain parcellations have been proposed, using cytoarchitectonic, structural or functional Magnetic Resonance Imaging (fMRI) data. The intrinsic smoothness of brain data, however, poses a problem for current methods seeking to compare different parcellations. For example, criteria that simply compare within-parcel to between-parcel similarity provide even random parcellations with a high value. Furthermore, the evaluation is biased by the spatial scale of the parcellation. To address this problem, we propose the Distance Controlled Boundary Coefficient (DCBC), an unbiased criterion to evaluate discrete parcellations. We employ this new criterion to evaluate existing parcellations of the human neocortex in their power to predict functional boundaries for an fMRI data set with many different tasks, as well as for resting-state data. We find that common anatomical parcellations do not perform better than chance, suggesting that task-based functional boundaries do not align well with sulcal landmarks. Parcellations based on resting-state fMRI data perform well; in some cases, as well as a parcellation defined on the evaluation data itself. Finally, multi-modal parcellations that combine functional and anatomical criteria perform substantially worse than those based on functional data alone, indicating that functionally homogeneous regions often span major anatomical landmarks. Overall, the DCBC advances the field of functional brain mapping by providing an unbiased metric that compares the predictive ability of different brain parcellations to define brain regions that are functionally maximally distinct.

Problem identification This review identifies specific cardiotoxicity related to anthracycline chemotherapy, specific risk factors related to increased anthracycline chemotherapy-induced cardiotoxicity, and underlying mechanisms of action of anthracycline chemotherapy-induced cardiotoxicity. Literature search PubMed®, CINAHL®, Embase®, and Web of Science were searched in May 2018 using keywords related to heart diseases, anthracycline chemotherapy, and breast cancer. Data evaluation Data were extracted, and study quality was assessed according to PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Synthesis 1,117 articles were identified through the literature search. After a review of the abstracts and articles, 15 clinical studies were identified for the final analysis by using exclusion and inclusion criteria. Implications for practice Nurses should recognize the critical elements for prevention and early detection of anthracycline chemotherapy-induced cardiotoxicity.

Although interest in hospice and palliative care for companion animals is on the rise, formal training in these areas is limited. Veterinary teaching institutions, professional organizations, and accrediting bodies have much to gain from the human palliative medicine field. Core competencies, curricular milestones, and scope of practice for palliative medicine are identified. A formal palliative care intervention has been implemented in a US veterinary teaching institution, and preliminary evaluation data reflect significant potential for integration of palliative care training into veterinary teaching. Positive outcomes for veterinarian well-being and ability to cope with emotional demands are suggested.

Background: Basic pentavalent immunization coverage in Sinjai Regency in 2017 has reached the target, but the advanced pentavalent immunization rate is still low (52.90%). This condition leads to make a huge gap in toddlers’ immunization status. Purpose: This study aims to determine the factors associated with advanced pentavalent immunization status in the work area of Kampala Health Service Center (PUSKESMAS), Sinjai Regency. Methods: The cross-sectional study was used in this study. The mothers who have the children aged 18-36 months were used as population. About 145 samples were obtained by using simple random sampling technique. The two-way data collection technique, namely primary data obtained through questionnaires and secondary data obtained from the evaluation data of pentavalent immunization at Kampala Health Service Center, Sinjai Regency. Furthermore, chi-square was used for data analysis. Results: Generally, the respondents were 25-29 years old in average (26.90%) and had a high school/ equivalent education degree (53.80%). The respondents’ occupation are mostly housewives (83, 40%). Moreover, the toddlers were 24-29 months-old (46.90%) in average. This study showed that the majority of respondents did not take advanced pentavalent immunization (61.38%). Factors affecting the immunization status of the pentavalent were maternal knowledge (p = 0.03), family support (p=

This study examines the alignment of quantitative and qualitative assessment data in end-of-rotation evaluations using longitudinal cohorts of residents progressing throughout the five-year general surgery residency.Rotation evaluation data were extracted for 171 residents who trained between July 2011 and July 2016. Data included 6069 rotation evaluations forms completed by 38 faculty members and 164 peer-residents. Qualitative comments mapped to general surgery milestones were coded for positive/negative feedback and relevance.Quantitative evaluation scores were significantly correlated with positive/negative feedback, r = 0.52 and relevance, r = -0.20, p .001. Themes included feedback on leadership, teaching contribution, medical knowledge, work ethic, patient-care, and ability to work in a team-based setting. Faculty comments focused on technical and clinical abilities; comments from peers focused on professionalism and interpersonal relationships.We found differences in themes emphasized as residents progressed. These findings underscore improving our understanding of how faculty synthesize assessment data.

The data presented in this article are related to the research article entitled: “Accuracy of cadmium-zinc-telluride imaging in detecting single and multivessel coronary artery disease: is there any gender difference?” (Gimelli et al., 2018). We evaluated gender-related differences in diagnostic accuracy of cadmium-zinc-telluride (CZT) myocardial perfusion imaging (MPI) in detecting single- and multi-vessel coronary artery disease (CAD). We included 1161 consecutive patients with known or suspected coronary artery disease (228, 25% women and 873, 75% men) who had been referred to our laboratory for stress–rest myocardial perfusion imaging (single-day stress–rest low-dose ultrafast protocol). All patients underwent coronary angiography within 30 days; CAD was defined in the presence of a coronary stenosis >70%. Summed stress scores (SSS), summed rest scores (SRS) and summed difference scores (SDS) were obtained. Image quality was graded “good” or better in more than 90% of patients.

Background The effectiveness of patient decision aids (PtDA) is rarely evaluated in the “real world” where patients vary in their preferences related to decision support. Purpose To determine how Canadian patients use and evaluate our widely available PtDA for early-stage prostate cancer treatment with its 8 components. Methods Google Analytics and online tracking provided usage information. A Usability Assessment (UA) following the PtDA provided evaluation data; main outcomes [scale: 1 (strongly disagree) to 5 (strongly agree)] were (a) the aid was helpful, and (b) I would recommend it to other patients. Results Usage data were from 993 users, and UAs from 168 of them. Mean “helpfulness” score was 4.1(5 max); mean “recommend” score was 4.2 (5 max). For each PtDA component, there was no significant difference on each main outcome, between those who used it and those who did not. Conclusion Overall, patients who completed the UA rated the PtDA as helpful and would recommend it to other patients. The widely available PtDA accommodated expected variation in decision support desired, and helpfulness was not associated with variation in components used. Practice implication The internet can be an effective medium for making appropriately designed decision support widely available to prostate cancer patients.

We propose to utilize machine learning to predict the electron density, ne, and temperature, Te, from He I line intensity ratios. In this approach, training data consist of measured He I line ratios as input and ne and Te measured using other diagnostic(s) as desired output, which is a Langmuir probe in our study. Support vector machine regression analysis is, then, performed with the training data to develop a predictive model for ne and Te, separately. It is confirmed that ne and Te predicted using the developed models agree well with those from the Langmuir probe in the ranges of 0.28 × 1018 ≤ ne (m−3) ≤ 3.8 × 1018 and 3.2 ≤ Te (eV) ≤ 7.5. The developed models are, further, examined with an evaluation data, which are not included in the training data, and are found to well reproduce absolute values and radial profiles of probe-measured ne and Te.

A New Generation Cost-efficient Laser Mask Writer for Mature Semiconductor Nodes Mycronic introduces SLX series – a new generation cost-efficient laser mask writer – to meet the ever increasing demand for laser based photomask writer driven by new semiconductor trends such as “More than Moore” and “Electronification of everything”. Photomasks of mature design nodes are required due to large variety of designs combined with price-sensitive low volume manufacturing. In this paper, Mycronic shares key technologies used in SLX series and how to achieve the cost effective mask manufacturing and demonstrates the superiority of the system by trecent evaluation data.

Problem identification Physical activity, a precision health strategy, positively affects biopsychosocial health in adult cancer survivors. However, understanding its effects among young adult (YA) cancer survivors is limited. The purpose of this scoping review was to explore existing research on physical activity in YA cancer survivors. Literature search CINAHL®, PubMed®, PsycINFO®, SPORTDiscus, Web of Science, and Cochrane Library were searched, producing 63 articles and 28 grey materials. Data evaluation Data extraction, guided by the revised symptom management model, included research aims, sample, design, primary outcome measures, and effects of physical activity. Synthesis Findings of 35 review articles were reported under three main categories. Implications for research Lack of clinical guidelines and limited research specific to YA cancer survivors hinders physical activity's use as a symptom management strategy. Research is needed that addresses the development and clinical implementation of physical activity guidelines.

Using 6 years of evaluation data, we assess the medium- and long-term impacts upon a diverse range of students, teachers, and schools from participating in a programme of protracted university-mentored projects based on cutting-edge space science, astronomy, and particle physics research. After having completed their 6-month-long projects, the 14–18-year-old school students report having substantially increased in confidence relating to relevant scientific topics and methods as well as having developed numerous skills, outcomes which are corroborated by teachers. There is evidence that the projects helped increase students' aspirations towards physics, whereas science aspirations (generally high to begin with) were typically maintained or confirmed through their involvement. Longitudinal evaluation 3 years later has revealed that these projects have been lasting experiences for students which they have benefited from and drawn upon in their subsequent university education. Data on students' destinations suggest that their involvement in research projects has made them more likely to undertake physics and STEM degrees than would otherwise be expected. Cases of co-created novel physics research resulting from Physics Research in School Environments (PRiSE) has also seemed to have a powerful effect, not only on the student co-authors, but also participating students from other schools. Teachers have also been positively affected through participating, with the programme having influenced their own knowledge, skills, and pedagogy, as well as having advantageous effects felt across their wider schools. These impacts suggest that similar “research in schools” initiatives may have a role to play in aiding the increased uptake and diversity of physics and/or STEM in higher education as well as meaningfully enhancing the STEM environment within schools.

We propose a method for recognizing tasks performed by care workers. Time-series sample data for each feature amount during tasks are defined as a task history, which is used as a basis for creating spatiotemporal task information in reference to Niitsuma’s spatial memory. We perform simulated care tasks in an environment that recreates an actual care site, and measure time-series data of worker feature amounts by a motion capture system. We divide this data into learning and evaluation data, and verify the recognition accuracy. Recognition accuracy for seven defined elemental tasks is close to 80% on average, demonstrating the effectiveness of this method.

Automatic unreliable news detection is a research problem with great potential impact. Recently, several papers have shown promising results on large-scale news datasets with models that only use the article itself without resorting to any fact-checking mechanism or retrieving any supporting evidence. In this work, we take a closer look at these datasets. While they all provide valuable resources for future research, we observe a number of problems that may lead to results that do not generalize in more realistic settings. Specifically, we show that selection bias during data collection leads to undesired artifacts in the datasets. In addition, while most systems train and predict at the level of individual articles, overlapping article sources in the training and evaluation data can provide a strong confounding factor that models can exploit. In the presence of this confounding factor, the models can achieve good performance by directly memorizing the site-label mapping instead of modeling the real task of unreliable news detection. We observed a significant drop (>10%) in accuracy for all models tested in a clean split with no train/test source overlap. Using the observations and experimental results, we provide practical suggestions on how to create more reliable datasets for the unreliable news detection task. We suggest future dataset creation include a simple model as a difficulty/bias probe and future model development use a clean non-overlapping site and date split., EACL 2021 (11 pages, 3 figures, 8 tables)

Detecting when there is a domain drift between training and inference data is important for any model evaluated on data collected in real time. Many current data drift detection methods only utilize input features to detect domain drift. While effective, these methods disregard the model’s evaluation of the data, which may be a significant source of information about the data domain. We propose to use information from the model in the form of explanations, specifically gradient times input, in order to utilize this information. Following the framework of Rabanser et al. [11], we combine these explanations with two-sample tests in order to detect a shift in distribution between training and evaluation data. Promising initial experiments show that explanations provide useful information for detecting shift, which potentially improves upon the current state-of-the-art.