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The patent-intensive industries play a leading and exemplary role in innovation driven, it is crucial to research evaluation methods to draw their levels and difference of innovation efficiency. This article proposes a new definition method for the patent-intensive industry with the ratio of inventions in force and research and development (RD constructing evaluation index system by comprehensive analysis of previous researches and objective judgment; extracting evaluation data. It evaluates the innovation efficiency of patent-intensive industries, demonstrates the corresponding characteristics: 1) the overall level of innovation efficiency is not high; 2) the RD and 3) the industry with better overall innovation efficiency has better transformation capability. It also provides the targeted industrial policy suggestions by dividing the patent-intensive industries into four categories. The research result shows that the proposed method is suitable for the innovation efficiency evaluation for the patent-intensive industries, and its research framework could be applied to the evaluation of other industries.

The physical built environment has long been an area of interest for researchers and can have large impacts on occupants in terms of their satisfaction and productivity. This research thesis utilizes post-occupancy data in occupied buildings to examine the effects of the physical workstation environment and the broader building amenities on occupants. Multi-variate regression models were used to analyze the data, taking into account demographic and workstation factors, the physical workstation environment, and satisfaction with amenity features. While the explained variance in the regression models were generally small, the results showed significant effects of various demographic factors, workstation characteristics, and physical workstation parameters on components of occupant satisfaction. Analyses of satisfaction with the broader building amenities further illustrated that elements outside of the immediate workstation can influence occupant satisfaction, well-being, and organizational productivity.

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.

Synonymous single nucleotide variants (sSNVs) are common in the human genome but are often overlooked. However, sSNVs can have significant biological impact and may lead to disease. Existing computational methods for evaluating the effect of sSNVs suffer from the lack of gold-standard training/evaluation data and exhibit over-reliance on sequence conservation signals. We developed synVep (synonymous Variant effect predictor), a machine learning-based method that overcomes both of these limitations. Our training data was a combination of variants reported by gnomAD (observed) and those unreported, but possible in the human genome (generated). We used positive-unlabeled learning to purify the generated variant set of any likely unobservable variants. We then trained two sequential extreme gradient boosting models to identify subsets of the remaining variants putatively enriched and depleted in effect. Our method attained 90% precision/recall on a previously unseen set of variants. Furthermore, although synVep does not explicitly use conservation, its scores correlated with evolutionary distances between orthologs in cross-species variation analysis. synVep was also able to differentiate pathogenic vs. benign variants, as well as splice-site disrupting variants (SDV) vs. non-SDVs. Thus, synVep provides an important improvement in annotation of sSNVs, allowing users to focus on variants that most likely harbor effects. Availability synVep webserver for online query: https://services.bromberglab.org/synvep; For local runs Python script (https://bitbucket.org/bromberglab/synvep_local) and prediction database (https://zenodo.org/record/4763256) are also available.

Rural schools face unique challenges recruiting teachers. Rural school administrators report difficulties finding qualified applicants. Unique challenges rural special education teachers face, e.g., working with a more diverse group of students including those with significant disabilities, heighten the difficulties rural administrators experience when recruiting and retaining qualified special education teachers. Leveraging university/rural school partnerships, e.g., resident teacher university/school partnerships, can help rural schools recruit and retain qualified special education teachers. This article describes the Teachers College Special Education Fellowship Program (TCSEFP), a virtual residency in teaching program. This program established virtual partnerships between the university and numerous rural school districts throughout the state. The article includes a description of the program, evaluation data, and implications for other virtual university/school residency in teaching programs.

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 study aims to determine the role of the Madrasah Working Group (KKM) in accordance with the Decree of the Directorate General of Islamic Religious Education Number 5852 of 2020 concerning Technical Guidelines for the Implementation of the KKM. The research was conducted with a qualitative descriptive case study type approach. The research findings show that the role of KKM can be optimal by using several programs and activities as follows: (1) sharing strategies among madrasah principals on best practices, (2) implementing inter-institutional benchmarking as part of honing, compassion and fostering, (3) making programs periodic collective evaluation (cognitive and psychomotor) to get superior seeds through programs and activities as well as a show-a-force institutional promotion, and (4) fostering and enhancing the professionalism of madrasah principals through programmed KKM on an ongoing basis by referring to the results of the evaluation conducted by the madrasah supervisor. Through KKM, efforts can be made to improve the quality of Islamic education whenever it is carried out programmatically and continuously based on evaluation data.

Zusammenfassung. Uber- und Fehlversorgung, mit der entsprechenden Gefahrdung von Patienten und Verschwendung von Ressourcen im Gesundheitswesen, fuhrte vor knapp zehn Jahren zur internationalen «Choosing Wisely» Kampagne (CWC). In der Schweiz startete diese Bewegung 2014 / 15 unter dem Namen «Smarter Medicine» mit einer ersten Top-5-Liste fur die ambulante Allgemeine Innere Medizin (AIM), auf welche Interventionen besser zu verzichten sei. Die Wirksamkeit der internationalen CWC wurde schon fruh in Frage gestellt und ob die «Smarter Medicine» Top-5-Liste fur die ambulante AIM Uber- und Fehlversorgung wirksam reduziert, wissen wir nicht – es gibt kaum Daten dazu. Voraussetzungen dafur, dass Uber- und Fehlversorgung durch CWC wirksam verbessert werden kann, sind die wissenschaftliche Evidenz zu den Verzichtempfehlungen, eine glaubwurdige Herausgeberschaft, verlassliche Daten zur Evaluation und vor allem das Engagement von Offentlichkeit, Patienten, Fachgesellschaften und Gesundheitspolitikern. Ein weiterer Schlusselfaktor fur die spatere erfolgreiche Umsetzung ist der fruhe Einbezug der Anwender bei der Entwicklung von Empfehlungen. Mit diesem Fokus haben wir kurzlich zusammen mit 538 praktizierenden Hausarztinnen und Hausarzten neue Vorschlage von Interventionen entwickelt, auf die besser zu verzichten sei. Diese Vorschlage bilden die Basis fur die nachste Top 5 Liste fur die ambulante AIM. “Smarter Medicine” in ambulatory general internal medicine, at present and in future Abstract. Overuse and inappropriate care resulting in potential harm and unwarranted waste of healthcare resources were leading to the international “Choosing Wisely” campaign (CWC) almost a decade ago. In Switzerland, the movement started 2014 / 15 under the label “Smarter Medicine”, with a top-5 list of interventions better to avoid in ambulatory general internal medicine (GIM). Yet from the beginning of the international CWC campaign, its effectiveness has been questioned, and we don’t know if the “Smarter Medicine” top-5 list for ambulatory GIM efficiently is reducing overuse and inappropriate care, as there is almost no evaluation data available. The prerequisites for an efficient reduction of overuse and inappropriate care are a. the scientific evidence for the recommendations, b. the recommendations coming from a trusted source, c. reliable data for the evaluation, d. the active role of patients, the public, professional healthcare societies and politicians. Another key factor for a successful implementation is the involvement of the final users at an early stage of recommendation development. Keeping this in mind, we recently developed new suggestions for interventions better to avoid, in collaboration with 538 general practitioners. These suggestions lead to a next top-5 list for the ambulatory GIM.

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

Herein, to decompose and reconstruct surface morphology after machining, the high- and low-frequency roughness surface and roughness evaluation data for titanium alloy (Ti-5553) are obtained using ...

Professors’ evaluations are carried out differently throughout individual universities, but it is an important part of a university internal quality regardless the evaluation system. The institutions with a large number of teaching employees are forced to use quantitative means of evaluation to be able to capture differences between individual science fields. We provide the means of meta-evaluation based on the Markov chain approach that allows to further assess the subjects of evaluation on a long-term basis. The approach is demonstrated on the vast evaluation data gathered in the university in Mexico City. The methodology of using Markov chains is explained on the theoretical level and it is applied to the real data afterwards. Results indicate that the lowest-evaluated professors are more likely to remain within the lowest -evaluated ones over a longer period. This may correspond with professors’ unwillingness to make changes in their courses. Moreover, we provide ample commentary on how the results should be understood. In the end, it occurs that using the Markov chain can even provide a reflection on the evaluation system as such.

Changes in academia have occurred quickly in response to the COVID-19 pandemic. In-person simulation-based education has been adapted into a virtual format to meet course learning objectives. The methods and procedures leveraged to onboard faculty, staff, and graduate nurse practitioner students to virtual simulation-based education while ensuring simulation best practice standards and obtaining evaluation data using the Simulation Effectiveness Tool-Modified (SET-M) tool are described in this article.

In this paper, we amend a multi-criteria methodology known as MURAME, to evaluate the creditworthiness of a large sample of Italian Small and Medium-sized Enterprises, using as input their balance sheet data. This methodology produces results in terms of scoring and of classification into homogeneous rating classes. A distinctive goal of this paper is to consider a preference disaggregation method to endogenously determine some parameters of MURAME, by solving a nonsmooth constrained optimization problem. Because of the complexity of the involved mathematical programming problem, for its solution we use an evolutionary metaheuristic, coupled with a specific efficient initialization. This is combined with an unconstrained reformulation of the problem, which provides a reasonable compromise between the quality of the solution and the computational burden. An extensive numerical experience is reported, comparing an exogenous choice of MURAME parameters with our approach.

This study proposes an innovative use of optimized extreme gradient enhancement based on grid search best parameters (Extreme Gradient Boosting, XGBoost) machine learning analyzer evaluates the prognostic state of emergency patients with severe trauma, with two prognostic outcomes, including rehabilitation and death. For patients with a trauma severity score (Injury Severity Score, ISS) greater than 15 in the ISS category of “serious trauma”, the use of XGBoost collects 3 parts of data into a database through emergency trauma patients to the prognostic result analysis, respectively, for hospitalization injury data, physician evaluation data, physician disposal data, and analysis prognotation status. After experimenting with the results of different methods, data attributes and predictive prognosis systems use the XGBoost method with a higher accuracy rate, thus achieving the goal of cost studies, so that medical personnel can learn about some vital signs and trauma scores and other data, you can estimate the prognostic status of patients, better treat emergency trauma patients, improve the probability of prognosis rehabilitation and reduce the risk of fatal.

Risk assessment methods are often used in complex industrial systems to avoid risks and reduce losses. The existing methods have not effectively solved the problems of lack of evaluation data and the interpretability of the entire evaluation process. This paper proposes a new risk assessment model based on the belief rule base (BRB) and Fault Tree Analysis (FTA). The FTA algorithm overcomes the difficulties of traditional BRB model in obtaining expert knowledge, clear indicators, and establishing logical relationships. This method establishes FTA rules based on the BRB model and expands the knowledge base through the FTA algorithm. A Bayesian network is applied as a conversion bridge between the FTA and BRB model. In addition, the model is optimized to reduce the uncertainty in the model. The method proposed is described by a case and its effectiveness is verified.

Aloe vera is a potential natural ingredient that can be used as a cosmetic ingredient because it has antioxidant properties and nutrients that are good for the skin. The purpose of this study was to determine the effect of differences in PVA concentrations as a basis for evaluating peel off gel mask preparations.The type of research to be carried out is experimental research. The sample that will be used is the extract of aloe vera meat (aloe vera). The peel off mask formulation from aloe vera extract was made from 3 formulas with different concentrations of PVA, namely 10%, 15%, and 20%. After that, a physical evaluation of the gel exfoliating mask preparation was carried out which included the organoleptic test, viscosity, pH test, spreadability, and drying time. The evaluation data will be analyzed statistically using one way analysis of variance (ANOVA). The results showed that differences in the concentration of PVA in each formula could affect the viscosity value and the drying time of the preparation. It can be concluded that the formula that meets the standards is formula I with a concentration of 10%.

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.

In community service, especially village administration, ideally, village officials have essential Microsoft word competencies. However, from the report from the village apparatus of Gelang, only one person who mastered the basic Microsoft word was not comprehensive. Basic Microsoft word skills are considered necessary by the village apparatus of Gelang. This material chose because this material has not been mastered and deemed to be most often needed to handle the Gelang village office's administration, so it is necessary to hold basic Microsoft word training activities for the village apparatus of Gelang. This activity was born on September 7, 2016, introducing the presenter followed by a pre-test to determine the participants' initial abilities. After that, the presentation of material about basic Microsoft word accompanied by mentoring, practice, discussion and ended with a post-test continued with the material's production. The activity evaluation data shows that the participant's post-test scores' lowest score wa perfect compared to the participant's pre-test scores. The lowest score for the participant's post-test was 75, and the highest score for the participant was 90 compared to the pre-test score with the highest score only reaching 60/ Thus, it can say that there was a significant increase in the score.

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.

To improve high quality and/or retain achieved high quality of an academic program, time to time evaluation for quality of each covered course is often an integrated aspect considered in reputed institutions, however, there has been little effort regarding humanities courses. This research article deals with analysis of evaluation data collected regarding humanities course from a College of Commerce & Economics, Mumbai, Maharashtra, India, on Likert type items. Appropriateness of one parametric measure and three non-parametric measures are discussed and used in this regard which could provide useful clues for educational policy planners. Keeping in view of the analytical results using these four measures, regardless of the threshold regarding satisfaction among students, overall performance of almost every subject has been un-satisfactory. There is a need to make a focused approach to take every course at the level of high performance. The inconsistency noticed under every threshold further revealed that under such poorly performing subjects globally, one needs to analyze merely at the global level item. Once the global level analysis reveals high performance of a course, then only item specific analysis may need to be focused to find out the items requiring further improvements.

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.

School psychologists often have reason to suspect that students may not be putting forth full effort during diagnostic tests, or that questionnaire or rating scale data are not credible. However, such suspicions must be tested carefully to yield data-based conclusions. Structured, empirically supported methods for assessing the “response validity” of evaluation data are available, to help gauge effort, motivation, and honesty in clients and informants. The present paper reviews a number of methods, places them in the context of research showing the effects of motivation and incentives on performance, and addresses concerns about including these methods in school-based psychoeducational evaluations. The paper concludes with practical, research-based recommendations for school psychologists when conducting evaluations and writing reports.

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.

Nurse educators have long recognized the need for an increased focus on environmental health education in nursing. For decades, schools of nursing have answered the call to action put forth by the Institute of Medicine and the American Nurses Association to incorporate environmental health content into nursing curricula. This article details the experiences of faculty and staff at the University of Maryland School of Nursing as they launched a national environmental health nursing organization, developed individual undergraduate elective courses on environmental health and climate change, and created a post-baccalaureate certificate program. We also report student registration and evaluation data from five environmental health courses over 10 years. Five hundred five undergraduate and 291 graduate nursing students from a variety of programs received formal environmental health education. Relevance of content was consistently highly rated, ranging from 4.17 to 4.61 out of 5, and students completed projects on a wide range of environmental health topics. Graduates of the certificate program have greatly impacted their communities in the areas of nursing practice, education, and policy.

The purpose of this study is to examine social work professional identity development through interprofessional education and practice. The Integrated Mental and Behavioral Health Training Program (IMBTP) was developed to prepare students for collaborative practice in integrated behavioral health settings. Interprofessional education and training was a core component of the IMBTP. At the conclusion of five cohorts (graduating 2014-2018), 61 MSW students had completed the training program. Content analysis of qualitative evaluation data revealed professional identity development as a recurring theme across multiple domains. Results demonstrate that providing opportunities for social work students to participate in interprofessional education and training allows for a greater understanding of other professional roles and perspectives, while at the same time helping to solidify the role and identity of a social worker. Social work education programs should consider including interprofessional education experiences for all students.

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.

Introduction The multiple mini interview (MMI) has been incorporated into the holistic review process in the selection of students to US medical schools. The MMI has been used to evaluate interpersonal and intrapersonal attributes which are deemed as necessary for future physicians. We hypothesized that there would be little difference in overall MMI evaluation data compared with traditional interview ratings. Methods The University of North Carolina School of Medicine developed an interview process that included a traditional interview and MMI format during the 2019 admissions cycle. Evaluation data along with key demographic variables for 608 MD program applicants were analyzed using descriptive and inferential statistical analyses. Results The MMI format slightly favored female over male applicants (p = 0.002) but did not select for or against applicants based on age, race/ethnicity, underserved/rural area upbringing, or indicators of disadvantage. Out of 608 applicants, 356 (59%) completed a post-interview survey in which the experience was positively rated. Discussion Based on our experience, the use of a hybrid model of traditional interviews complemented with MMI stations provided greater details in the assessment of medical school applicants while obtaining equivalent data and acceptability amongst applicants.

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.

A tanulmány a klasszikus és modern migrációelméletek tanait követve, azok elemzésének felhasználásával, tudományelméleti módszertan alkalmazásával vizsgálja a Magyarország schengeni külső határain jelentkező irreguláris migrációt. Az értékelési adatokból beazonosítható egy olyan migrációs jellemző, amely korábban sem európai, sem más földrészek nemzeteit nem érintette abban a komplexitásában, mint Magyarországot a 2014. és 2015. években. Az adatok vizsgálatának és a kapcsolódó elemek összefüggéseinek elemzéséből leírható a migráció hatásának egy újszerű megközelítése, a migrációt kezelő rendészeti szervek tevékenységének objektív túlterhelése, amit új fogalomként írok le. Atanulmányban bemutatok egy korábban még nem rögzített migrációtipológiai elemet, amely a vándor személyazonossága hiteles megállapításának lehetőségét vizsgálja. A migrációs túlterhelés által a magyar rendészeti szervekre gyakorolt objektív hatásokat a 20. századi tömeges migrációs események jellemzőivel hasonlítom össze. Az eltérések megerősítik a túlterheléses és a tömeges migráció fogalma közti eltérést. A túlterheléses migrációra jellemző szerveződési felületeket és annak célját leírva szintén a fogalom újszerűségét erősítem. A rendészeti szervekre gyakorolt objektív migrációs túlterhelési hatásokat újszerű módszertannal lehet érdemben kezelni, amelynek öt elemét mutatom be a tanulmányban.

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

The development of a novel snack bar based on sesame paste (SP) and date syrup (DS) was investigated. The aim of this study was to evaluation the effects of SP/DS ratio and encapsulated thymol (thymol-loaded nanostructured lipid carrier [TNLC]) on physicochemical, textural, rheological, and sensorial properties of snack bars. The effect of butylated hydroxytoluene (BHT), thymol, and TNLC showed that the addition of 100 ppm TNLC could improve the oxidative stability of SP/DS mixtures even better than BHT, while a higher concentration of TNLC had a negative effect. The unpleasant taste and odor of thymol could be overcome by its encapsulation in nanostructured lipid carriers. The textural properties of the formulations with different SP/DS ratios (1:2, 1:1, 2:1) and an overall concentration of 7 g of gelatin/kg of mixtures were evaluated. The texture profile analysis showed that the sample with an SP/DS ratio of 1:1 had higher hardness, adhesiveness, springiness, cohesiveness, and gumminess in comparison with the other ratios. From the sensory evaluation data, the bar prepared with an SP/DS ratio of 1:1 had the most acceptable texture. According to the results, the SP/DS ratio of 1:1 with gelatin and 100 ppm TNLC can be used in developing SP/DS blends as a highly acceptable functional food.

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.

Background Plant height (PH) and fruit branch number (FBN) are important traits for improving yield and mechanical harvesting of cotton. In order to identify genes of PH and FBN in cotton germplasms to develop superior cultivars, quantitative trait loci (QTLs) for these traits were detected based on the phenotypic evaluation data in nine environments across four locations and 4 years and a previously reported genetic linkage map of an recombinant inbred line (RIL) population of upland cotton. Results In total, 53 QTLs of PH and FBN, were identified on 21 chromosomes of the cotton genome except chromosomes c02, c09-c11, and c22. For PH, 27 QTLs explaining 3.81%–8.54% proportions of phenotypic variance were identified on 18 chromosomes except c02, c08-c12, c15, and c22. For FBN, 26 QTLs explaining 3.23%–11.00% proportions of phenotypic variance were identified on 16 chromosomes except c02-c03, c06, c09-c11, c17, c22-c23, and c25. Eight QTLs were simultaneously identified in at least two environments. Three QTL clusters containing seven QTLs were identified on three chromosomes (c01, c18 and c21). Eleven QTLs were the same as previously reported ones, while the rest were newly identified. Conclusions The QTLs and QTL clusters identified in the current study will be helpful to further understand the genetic mechanism of PH and FBN development of cotton and will enhance the development of excellent cultivars for mechanical managements in cotton production.

AIM: Sample size and species characteristics, including prevalence and habitat specialization, can influence the predictive performance of species distribution models (SDMs). There is little agreement, however, on which metric of model performance to use. Here, we directly compare AUC and partial ROC as metrics of SDM performance through analyses on the effects of species traits and sample size on SDM performance. LOCATION: Three counties dominated by agricultural lands and coniferous forest in Oregon's Willamette Valley and Coast Range ecoregions. METHODS: We systematically reduced a large avian point count dataset to alter sample sizes of 22 species of songbird. We used boosted regression trees to run SDMs for each species, quantified habitat specialization, and used mixed effects models to compare the influence of sample size, prevalence, and habitat specialization on SDM performance, calculated as AUC and partial ROC, across species. We calculated AUC and partial ROC with subset and independent evaluation data separately to more comprehensively investigate differences in metrics. RESULTS: We found a positive quadratic effect of sample size and a strongly positive effect of habitat specialization on both metrics of model performance. We found a weak effect of prevalence on partial ROC and no effect in AUC. Contrary to expectations, when evaluated with a subset evaluation data, partial ROC was consistently highest in models with the smallest sample sizes. These small sample size models had correspondingly small sample sizes in subset evaluation datasets. Partial ROC evaluated with independent data and AUC evaluated with subset or independent data showed the expected positive correlation between sample size and model performance. MAIN CONCLUSIONS: We found that small evaluation datasets can artificially inflate partial ROC. With literature recommended minimum SDM sample sizes as low as three, attention must be given to the effects of correspondingly low sample sizes in evaluation datasets.

Based on the study of other social evaluation indexes, this paper studies the management and control of teaching quality by using the research methods of system science, aiming to find a calculation method that can comprehensively reflect the overall quality characteristics of the teaching system. On this basis, the paper puts forward the construction scheme of Higher Vocational Education Teachers’ teaching quality index, which includes five dimensions such as student attendance data, student evaluation data, supervision data, peer evaluation data, management organization inspection data and several observation indexes. At the same time, a comprehensive empirical analysis is made on the 2019 teachers’ teaching quality index of our school. The average teaching quality index of teachers is 86.0, indicating that the quality is in a good state.

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.

To evaluate the environmental performance of manufacturing systems, practitioners often deploy ad-hoc methods or implement one-off solutions that are difficult to replicate in similar scenarios. Such situations can drive-up costs and cause significant delays. Hence, there is a strong need for standard methods that help describe and replicate environmental performance evaluation (EPE) processes. In response, ISO 20140 provides guidelines for converting and aggregating environmental performance evaluation data. This paper provides an overview of ISO 20140, and showcases the usefulness of ISO 20140 by describing and analyzing the usage view of the EPE process. The analysis is conducted with an evaluation experiment about the machining of a mill-tern part, in which energy consumption of a variety of process modes such as active machining, tools change, rapid traverse, and pausing, are evaluated. The experiment is jointly conducted by National Institute of Standards and Technology in the United States and the National Institute of Advanced Industrial Science and Technology in Japan.

This paper finds out the existing problems in learning and implements effective intervention to stimulate students’ enthusiasm for learning by analyzing the teachers’ evaluation data of all classes in a semester. The results show that there is a significant positive correlation at the level of 0.01 through the correlation analysis of learning attitude, learning process and learning effect, and the correlation is above medium level. The prediction model of learning effect is established through regression analysis, which improves students’ awareness of autonomous learning, standardizes the learning process and improves the learning effect.