Dataset of measurable indicators of the Slovak state institutions' websites

The dataset contains 11 measurable indicators for the website evaluation from different points of view. These indicators were collected for 60 websites of the Slovak state institutions. It provides information about the directly measurable variables, which may affect or reflect the usability, popularity and visibility of the website. Most variables were measured by online tools. The dataset is a mixture of binary, ordinal, discrete numeric and continuous numeric variables, which gives many opportunities to analyze the relations between the measurable websites' indicators. It can be used to find the structure consisting of latent variables, which cannot be directly measured (such as usability or popularity of the website). Another use is to find subgroups of state institutions, which have similar websites from some point of view.

Development and use of Biocheck.UGent™ scoring system to quantify biosecurity in conventional indoor (turkey, duck, breeder) and free-range (layer and broiler) poultry farms

To assess and enhance the application of biosecurity measures in poultry farming, an objective measurement tool (Biocheck.UGent™) was already available for broiler and layer. This study describes the development, validation and application of a risk-based weighted scoring tool for breeder, turkey, duck, free-range layer and free-range broiler production. In collaboration with an expert panel (n= 38), five different questionnaires were developed, following the format of the existing Biocheck.UGent scoring tools. Weights were attributed to external (7-9 subcategories) and internal (3-4 subcategories) biosecurity categories, as well as to the corresponding individual questions within each subcategory. The biosecurity measures were prioritized and weighed based on their relative importance in preventing disease transmission. Upon completion of the questionnaire, and upload of all answers to the Biocheck.UGent website, the algorithm generates a biosecurity score varying between ''0'' which equals the total absence of any biosecurity measure up to ''100'' which refers to full application of all biosecurity measures. The final scoring systems are available online (https://biocheckgent.com/en) for free and have been used to assess biosecurity in 70 breeders, 100 turkeys, 23 ducks, 16 free-range broilers, and 15 free-range layer farms originating from 12 countries so far. On average, the overall biosecurity score (mean ± std. dev) was 78 ± 7 % for breeders, 73 ± 11 % for turkeys, 71 ± 8 % for ducks, 73 ± 8 % for free-range layers and 70 ± 13 % for free-range broilers. There were significant differences (p < 0.05) in biosecurity (both at the overall and subcategory levels) across different poultry types. The overall farm biosecurity score for breeders was significantly higher than that for turkey (p <.001) and duck production (p = 0.001). External biosecurity levels were highest in breeders in comparison to turkeys (p < 0.001), ducks (p = 0.008) and broiler free-range (p = 0.005). There was a notable difference in internal biosecurity levels between duck and turkey (p = 0.041) production as well. The study contributed to the poultry biosecurity database which allows benchmarking of the biosecurity levels of the users' farm results to national or international averages, indicating room for improvement and aiding to motivate stakeholders to enhance their biosecurity levels.

Pre-Operative Rank of Expectations for Shoulder Surgery (PRESS): A Novel Survey

BACKGROUND

Patient expectations for orthopedic surgeries, and elective shoulder surgery in particular, have been shown to be important for patient outcomes and satisfaction. Current surveys assessing patient expectations lack clinical applicability and allow patients to list multiple expectations at the highest level of importance. The purpose of this study was to develop and evaluate the use of a novel, rank-based survey assessing the relative importance of patient expectations for shoulder surgery.

METHODS

The Preoperative Rank of Expectations for Shoulder Surgery (PRESS) survey was developed by polling 100 patients regarding their expectations for surgery. The PRESS survey consisted of eight common expectations for elective shoulder surgery by importance and a 0-100% scale of expected pain relief and range of motion improvement. After initial development of the PRESS survey, it was administered preoperatively to 316 patients undergoing surgery for shoulder arthritis, rotator cuff tear, subacromial pain syndrome, or glenohumeral instability between August 2020 and April 2021. Patients also completed preoperative outcome measures such as ASES, PROMIS PF, and PROMIS PI surveys. PROM surveys were administered six months postoperatively.

RESULTS

Improvement in range of motion was the expectation most often ranked first for the entire study group (18%), arthritis subgroup (23%), and rotator cuff tear subgroup (19%). Subacromial pain syndrome patients most often ranked improving ability to complete ADL's and relieving daytime pain first (19%). Shoulder instability patients most often ranked improving ability to participate in sports first (31%). Patients that ranked improving range of motion or sports highly had better PROMs. Those who ranked relieving pain highly had worse PROMs. Patients with high (>90%) expectations of pain relief had better PROMIS PI scores. Patients with high pain relief expectations in the arthritis and subacromial pain syndrome groups had better PROMs, while patients with instability were less satisfied.

CONCLUSION

The novel PRESS survey assesses patient expectations for shoulder surgery in a new, more clinically applicable rank-based format. The responses provided by patients provide actionable information to clinicians and are related to postoperative outcomes. Therefore the PRESS survey represents a useful tool for guiding discussions between patients and surgeons, as well as aiding in overall patient-centered clinical decision making.

Sentiment analysis of U.S. News & World Report Best Children's Hospital urology rankings: A difference in positivity between the public and academic worlds

INTRODUCTION

Initiated in 2009, the U.S. News & World Report (USNWR) pediatric urology rankings aim to guide patients and families towards high-quality urologic care. Despite this, the pediatric urology community remains divided, with significant debate over the rankings' accuracy, utility, and potential for misleading information. While some professionals argue for a collective opt-out from these rankings, citing these concerns, others highlight their positive impact on patient care, hospital benchmarking, and financial support.

OBJECTIVE

Recognizing the lack of formal evaluation on how these rankings are viewed beyond the pediatric urology community, this research endeavors to fill the gap through sentiment analysis of public news articles and academic publications.

STUDY DESIGN

We captured news articles from Google News and academic papers from Ovid Medline and Embase, focusing specifically on content related to the USNWR pediatric urology rankings from 2009 to 2023. Sentiment analysis was conducted using the Valence Aware Dictionary and Sentiment Reasoner (VADER) package on both news and academic texts, aiming to capture the overall sentiment through a compound score derived from the presence of sentiment-laden words. Sensitivity analysis was performed using TextBlob Pattern Analyzer tool.

RESULTS

The analysis revealed a significant divergence in sentiment between news articles and academic literature. News articles exhibited a predominantly positive sentiment, with an average compound score of 0.681, suggesting a general approval or celebration of the rankings in the public sphere. Conversely, academic literature showed a more moderate sentiment, with an average score of 0.534, indicating a nuanced perspective that includes both positive views and critical reflections on the rankings. Sensitivity analysis confirmed this observation (Figure).

DISCUSSION

This difference may reflect the distinct nature of news media and academic discourse. While news outlets may prioritize celebratory narratives that align with public interest and institutional pride, academic discussions tend to offer a balanced view that critically assesses both the merits and limitations of the rankings. This discrepancy underscores the complexity of interpreting and acting upon the rankings within the pediatric urology community.

CONCLUSION

While the USNWR pediatric urology rankings are generally received positively by the public, as reflected in news media, the academic community presents a more reserved sentiment. These findings suggest the need for ongoing dialogue and research to understand the implications of these rankings fully. It also calls for a strategic approach to address the concerns and perceptions of healthcare professionals, aiming to leverage the rankings in a way that truly benefits patient care and informed decision-making.

Node-personalized multi-graph convolutional networks for recommendation

Graph neural networks have revealed powerful potential in ranking recommendation. Existing methods based on bipartite graphs for ranking recommendation mainly focus on homogeneous graphs and usually treat user and item nodes as the same kind of nodes, however, the user-item bipartite graph is always heterogeneous. Additionally, various types of nodes have varying effects on recommendations, and a good node representation can be learned by successfully differentiating the same type of nodes. In this paper, we develop a node-personalized multi-graph convolutional network (NP-MGCN) for ranking recommendation. It consists of a node importance awareness block, a graph construction module, and a node information propagation and aggregation framework. Specifically, a node importance awareness block is proposed to encode nodes using node degree information to highlight the differences between nodes. Subsequently, the Jaccard similarity and co-occurrence matrix fusion graph construction module is devised to acquire user-user and item-item graphs, enriching correlation information between users and between items. Finally, a composite hop node information propagation and aggregation framework, including single-hop and double-hop branches, is designed. The high-order connectivity is used to aggregate heterogeneous information for the single-hop branch, while the multi-hop dependency is utilized to aggregate homogeneous information for the double-hop branch. It makes user and item node embedding more discriminative and integrates the different nodes' heterogeneity into the model. Experiments on several datasets manifest that NP-MGCN achieves outstanding recommendation performance than existing methods.

Simplified Spectrum Score (S3) app for pathogen-agnostic antimicrobial drug spectrum ranking to assess for antimicrobial de-escalation events

Antimicrobial/antibiotic de-escalation (ADE) is a key feature of antimicrobial stewardship programs (ASP) that relies mainly on individual panels for determining ADE events based on subjective ranking of antibiotics' spectrum activity. The lack of consensus among ASP experts leads to reproducibility issues in the measure of this clinical outcome, making difficult to assess its real impact on patient care. The S3 score (Simplified Spectrum Score) app was developed to allow an objective ranking of antibiotics. Ranking was achieved by developing a database harboring pairs of bacteria-antibiotics for which each molecule was assigned a score based on published and clinically validated data from a recognized international committee. S3 score shows a strong correlation relationship and substantial agreement to a clinically validated spectrum score, and its framework enables any person to use it for ADE detection without assuming prior knowledge or training. In addition, its design enables regular updates and sustainability.

A new distance between rankings

This paper analyzes the behavior of the well-known Spearman's footrule distance (F-distance) to measure the distance between two rankings over the same set of objects. We show that F-distance is not invariant to labeling, and therefore, it suffers from a serious drawback for its use in applications. To circumvent this problem, we propose a new distance between rankings which is invariant under indexing (i.e., labeling) and appears as a good alternative to the direct use of F-distance between rankings, and also the invariant-under-indexing Kemeny's distance as well. We also show how our new distance can work with importance weights. Some simple examples are given to show the interest of our method with respect to the classical one based on F-distance and Kemeny's distance.

Associations Between Program Doximity Reputation Rank and Well-Being in General Surgery Residents

INTRODUCTION

Burnout and mistreatment are prevalent among surgical residents with considerable program-level variation. Applicants consider "program reputation," among other factors, when ranking programs. Although highly subjective, the only available measure of program reputation is from a physician survey by Doximity. It is unknown how program reputation is associated with resident well-being and mistreatment.

METHODS

Resident burnout and personal accomplishment were assessed via the 2019 post-American Board of Surgery In-Training Examination survey. Additional outcomes included mistreatment, thoughts of attrition, and suicidality. Residents were stratified into quartiles based on their program's Doximity reputation rank. Multivariable logistic regression models examined the relationship between each outcome with Doximity rank quartile.

RESULTS

6956 residents (85.6% response rate) completed the survey. Higher-ranked programs had significantly higher burnout rates (top-quartile 41.3% versus bottom-quartile 33.2%; odds ratio [OR] 1.35, 95% confidence interval [CI] 1.04-1.76). There was no significant difference in personal accomplishment by program rank (OR 1.26, 95% CI 0.86-1.85). There also was no significant association between program rank and sexual harassment (OR 0.90, 95% CI 0.70-1.17), gender discrimination (OR 1.14, 95% CI 0.86-1.52), racial discrimination (OR 1.18, 95% CI 0.91-1.54), or bullying (OR 1.03, 95% CI 0.76-1.40). Suicidality (P = 0.97) and thoughts of attrition (P = 0.80) were also not associated with program rank.

CONCLUSIONS

Surgical residents at higher-ranked programs report higher rates of burnout but have similar rates of mistreatment and personal accomplishment. Higher-ranked programs should be particularly vigilant to trainee burnout, and all programs should employ targeted interventions to improve resident well-being. This study highlights the need for greater transparency in reporting objective program-level quality measures pertaining to resident well-being.

Preventing postpartum hemorrhage: A network meta-analysis on routes of administration of uterotonics

1.

OBJECTIVE

To perform a network meta-analysis to specify the route of administration that maximises the effectiveness of each of the available prophylactic uterotonics without increasing the risk for side effects. 2.

DATA SOURCES

Literature searches on 12th September 2022 included: CENTRAL, MEDLINE, Embase, CINAHL, ClinicalTrials.gov and the WHO International Clinical Trials Registry Platform. The reference lists of the retrieved study records were also searched. 3.

STUDY ELIGIBILITY CRITERIA

Population: Randomized controlled trials involving women in the third stage of labour after a vaginal or caesarean delivery in hospital or community settings.

INTERVENTIONS

Systemically administered prophylactic uterotonics of any route and dose for primary postpartum hemorrhage prevention. Comparison: Any other prophylactic uterotonic, or a different route or dose of a given uterotonic, or placebo, or no treatment. Outcomes (primary): postpartum hemorrhage ≥ 500 mL and ≥ 1000 mL. 4.

STUDY APPRAISAL AND SYNTHESIS METHODS

Risk of bias and trustworthiness assessments were performed, according to Cochrane's guidance. Direct, indirect and network meta-analyses were conducted, and results were summarized either as risk ratio or mean difference with 95% confidence intervals for dichotomous and continuous outcomes, respectively. The certainty of generated evidence was assessed according to the GRADE approach. Cumulative probabilities were calculated and the surface under the cumulative ranking curve was used to create a ranking of the available drugs. 5.

RESULTS

One hundred eighty-one studies involving 122,867 randomised women were included. Most studies were conducted in hospital settings in lower-middle income countries and involved women delivering vaginally. When compared with intramuscular oxytocin, carbetocin (RR 0.58, 95 % CI 0.40-0.84) and oxytocin (RR 0.75, 95 % CI 0.59-0.97) by an intravenous bolus, and intramuscular ergometrine plus oxytocin combination (RR 0.71, 95 % CI 0.56-0.91) are probably more effective in preventing primary postpartum hemorrhage. Intramuscularly administered oxytocin and carbetocin by an intravenous bolus have a favourable side effects profile. 6.

CONCLUSIONS

Generated evidence was generally moderate and global inconsistency was low. Carbetocin and oxytocin by an intravenous bolus, and intramuscular ergometrine plus oxytocin combination are probably the top uterotonics for primary postpartum hemorrhage prevention. Large scale studies exploring different routes of administration for available prophylactic uterotonics, and women's views should be conducted.

Barriers to adoption of electric vehicles in Texas

Sustainable mobility options such as electric vehicles (EVs) have the potential to improve the quality of life for Americans as well as those in other countries, as they can enhance the quality of the air we breathe, while reducing greenhouse gas emissions, fossil fuel consumption, and the adverse impacts of global warming. Despite their many benefits, however, the demand for EVs remains low. Therefore, this study aims to identify the barriers that affect the widespread EV adoption in the United States. Seventeen barriers were identified from the literature, and a questionnaire survey was designed and distributed to potential consumers of EVs. The survey yielded 733 responses, and various statistical tests like cluster analysis and chi-squared tests were performed. The results revealed that the high purchase price of the vehicle, high battery replacement cost, and the lack of public infrastructures for charging them were the primary concerns. The results also revealed that middle-aged men with high education and income are more enthusiastic about adopting EVs. The results presented in this study indicate a range of developments that different stakeholders could implement. To surmount the economic barriers to EV adoption, policymakers should strengthen incentives countrywide, and automakers should introduce more affordable EVs to the market. To overcome the challenges associated with charging, it is necessary to make investments in rapid charging infrastructure along the primary toll routes.

Composite environmental indices-a case of rickety rankings

Composite indices have been widely used to rank the environmental performance of nations. Such environmental indices can be useful in communicating complex information as a single value and have the potential to generate political and media awareness of environmental issues. However, poorly constructed, or poorly communicated indices, can hinder efforts to identify environmental failings, and there are considerable differences in rank among existing environmental indices. Here, we provide a review of the conceptual frameworks and methodological choices used for existing environmental indices to enhance our understanding of their accuracy and applicability. In the present study, we review existing global indices according to their conceptual framework (objectives of the index and set of indicators included) and methodological choices made in their construction (e.g., weighting and aggregation). We examine how differences in conceptual frameworks and methodology may yield a more, or less, optimistic view of a country's environment. Our results indicate that (1) multidimensional environmental indices with indicators related to human health and welfare or policy are positively correlated; (2) environment-only indices are positively correlated with one another or are not correlated at all; (3) multidimensional indices and environment-only indices are negatively correlated with each other or are not correlated at all. This indicates that the conceptual frameworks and indicators included may influence a country's rank among different environmental indices. Our results highlight that, when choosing an existing environmental index-or developing a new one-it is important to assess whether the conceptual framework (and associated indicators) and methodological choices are appropriate for the phenomenon being measured and reported on. This is important because the inclusion of confounding indicators in environmental indices may provide a misleading view of the quality of a country's environment.

Probiotic potential of gluten degrading Bacillus tequilensis AJG23 isolated from Indian traditional cereal-fermented foods as determined by Multiple Attribute Decision-Making analysis

The present study reported the characterization of gluten hydrolyzing strains of Bacillus sp. from fermented cereal dough. The strains were characterized for probiotic as well as technological attributes. A total of 45 presumptive gluten degrading isolates were obtained on gliadin agar plate assay. Based on hemolytic and antibiotic susceptibility pattern, only six isolates were considered safe which also indicated gliadinase activity on zymography. All the six strains were able to resist the pH 2.0, 0.25% bile and also possessed ability to adhere to the organic solvents and mucin. The cell free supernatant of five strains exhibited antimicrobial activities against Gram-positive and Gram-negative pathogens. A more than 50% survival of the isolated strains was obtained at a salt concentration of 2%, phenol concentration of 0.1% and temperature upto 45 °C. All the strains exhibited antioxidant activities and biofilm forming ability. Furthermore, the ranking of strains based on probiotic as well as other functional attributes was determined using multidimensional Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). A matrix of multidimensional indicators was prepared using alternatives and criteria, the analysis indicated the strain Bacillus tequilensis AJG23 as the potential probiotic candidate based on all screening criteria. Further work still needs to be done about the protective role of the potential strain against gluten sensitivity using in vitro models.

Bayesian belief network modelling approach for predicting and ranking risk factors for malaria infections among children under 5 years in refugee settlements in Uganda

BACKGROUND

Malaria risk factors at household level are known to be complex, uncertain, stochastic, nonlinear, and multidimensional. The interplay among these factors, makes targeted interventions, and resource allocation for malaria control challenging. However, few studies have demonstrated malaria's transmission complexity, control, and integrated modelling, with no available evidence on Uganda's refugee settlements. Using the 2018-2019 Uganda's Malaria Indicator Survey (UMIS) data, an alternative Bayesian belief network (BBN) modelling approach was used to analyse, predict, rank and illustrate the conceptual reasoning, and complex causal relationships among the risk factors for malaria infections among children under-five in refugee settlements of Uganda.

METHODS

In the UMIS, household level information was obtained using standardized questionnaires, and a total of 675 children under 5 years were tested for malaria. From the dataset, a casefile containing malaria test results, demographic, social-economic and environmental information was created. The casefile was divided into a training (80%, n = 540) and testing (20%, n = 135) datasets. The training dataset was used to develop the BBN model following well established guidelines. The testing dataset was used to evaluate model performance.

RESULTS

Model accuracy was 91.11% with an area under the receiver-operating characteristic curve of 0.95. The model's spherical payoff was 0.91, with the logarithmic, and quadratic losses of 0.36, and 0.16 respectively, indicating a strong predictive, and classification ability of the model. The probability of refugee children testing positive, and negative for malaria was 48.1% and 51.9% respectively. The top ranked malaria risk factors based on the sensitivity analysis included: (1) age of child; (2) roof materials (i.e., thatch roofs); (3) wall materials (i.e., poles with mud and thatch walls); (4) whether children sleep under insecticide-treated nets; 5) type of toilet facility used (i.e., no toilet facility, and pit latrines with slabs); (6) walk time distance to water sources (between 0 and 10 min); (7) drinking water sources (i.e., open water sources, and piped water on premises).

CONCLUSION

Ranking, rather than the statistical significance of the malaria risk factors, is crucial as an approach to applied research, as it helps stakeholders determine how to allocate resources for targeted malaria interventions within the constraints of limited funding in the refugee settlements.

Evaluation of the accuracy of intraoral scanners for complete-arch scanning: A systematic review and network meta-analysis

OBJECTIVES

This network meta-analysis (NMA) aimed to compare the complete-arch scanning accuracy of different intraoral scanners (IOSs) to that of reference standard tessellation language (STL) files.

DATA

Studies comparing the trueness and precision of IOS STL files with those of reference STL scans for different arch types (dentate, edentulous, completely edentulous with implants, and partially edentulous with implants) were included in this study.

SOURCES

An electronic search of five databases restricted to the English Language was conducted in October 2021.

STUDY SELECTION

A total of 3,815 studies were identified, of which 114 were eligible for inclusion. After study selection and data extraction, pair-wise comparison and NMA were performed to define the accuracy of scanning for four arch subgroups using four outcomes (trueness and precision expressed as mean absolute deviation and root mean square values). Cochrane guidelines and the QUADAS-2 tool were used to assess the risk of bias. GRADE was used for certainty assessment.

RESULTS

Fifty-three articles were included in this NMA. Altogether, 26 IOSs were compared directly and indirectly in 10 network systems. The accuracy of IOSs scans were not significantly different from the reference scans for dentate arches (three IOSs), edentulous arches (three IOSs), and completely edentulous arches with implants (one IOS). The accuracy of the IOSs was significantly different from the reference scans for partially edentulous arches with implants. Significant accuracy differences were found between the IOSs, regardless of clinical scenarios.

CONCLUSIONS

The accuracy of complete-arch scanning by IOSs differs based on clinical scenarios.

CLINICAL SIGNIFICANCE

Different IOSs should be used according to the complete arch type.

Rating versus ranking in a Delphi survey: a randomized controlled trial

BACKGROUND

The Delphi technique has steeply grown in popularity in health research as a structured approach to group communication process. Rating and ranking are two different procedures commonly used to quantify participants' opinions in Delphi surveys. We explored the influence of using a rating or ranking approach on item prioritization (main outcome), questionnaire completion time, and evaluation of task difficulty in a Delphi survey aimed at identifying priorities for the organization of primary cardiovascular care.

METHODS

A randomized controlled parallel group trial was embedded in a three-round online Delphi survey. After an "open" first round, primary care patients, trained patient partners, and primary care clinicians from seven primary care practices were allocated 1:1 to a rating or ranking assessment group for the remainder of the study by stratified permuted block randomization, with strata based on participants' gender and status. Agreement on item prioritization between the experimental groups was measured by calculating Krippendorff's alpha reliability coefficient on the aggregate rank order of items in each group after the final round. Self-reported ease or difficulty with the assessment task was measured with the Single Ease Question.

RESULTS

Thirty-six panelists (13 clinic patients, 7 patient partners, 16 clinicians; 60% females) were randomized to the rating (n = 18) or ranking (n = 18) group, with 30 (83%) completing all rounds. Both groups identified the same highest priorities from a set of 41 items, but significant discrepancies were found as early as the seventh top item. There was moderately strong agreement between the priority ordering of top items common to both groups (Krippendorff's alpha = 0.811, 95% CI = 0.669-0.920). A 9-min mean difference to complete the third-round questionnaire in favor of the rating group failed to achieve statistical significance (p = 0.053). Ranking was perceived as more difficult (p < 0.001).

CONCLUSIONS

A rating or ranking procedure led to modestly similar item prioritization in a Delphi survey, but ranking was more difficult. This study should be replicated with a larger number of participants and with variations in the ranking and rating procedures.

TRIAL REGISTRATION

Not applicable.

Toxicity of Heavy Metals that Affect Germination, Development and Cell Cycle of Allium cepa L

This study aimed to investigate the impact of heavy metals copper, cadmium, lead, aluminum and nickel, on the growth, physiology, metabolism, and cell cycle of Allium cepa L. Five treatments with increasing concentrations (0, 50, 100, 250, and 500 µM) were applied to the seeds. The results showed that the highest concentrations of copper and cadmium had phytotoxic and biochemical effects on the onion. Additionally, copper concentrations caused an increase in mitodepressive effect and chromosomal abnormalities. Aluminum also induced several chromosomal abnormalities. The study found that Cd > Cu > Pb > Ni > Al and Cu > Al > Ni > Pb > Cd had the highest phytotoxic and cytotoxic potentials, respectively. Furthermore, the UPGMA method revealed three divergent groups. These results suggest that heavy metals, especially copper, have a significant pollution potential when present in high concentrations.

Blockchain Technology Application Challenges in Renewable Energy Supply Chain Management

With the advent of new technologies and globalization of business, supply chains have turned into indispensable tools for gaining competitive advantage. The application of new technologies like blockchain can benefit sustainable energy supply chains by improving chain and logistics operations in the areas of trust, transparency and accountability, cooperation, information sharing, financial exchanges, and supply chain integration. However, the efforts to adopt such technologies in supply chains tend to face many challenges and challenges, which can seriously threaten their success. Therefore, it is crucial to carefully examine the challenges to blockchain technology application. This research focuses on identifying the criteria and challenges to the application of blockchain in renewable energy supply chains and also ranks the identified challenges in terms of their capacity to disrupt the process. The applicability of the suggested structure is examined in a case study of the renewable energy supply chain of Iran. In this study, the challenges are evaluated and ranked by the hybrid developed methods by the integration of the concept of gray numbers into the gray stepwise weight assessment ratio analysis (SWARA-Gray) and the gray evaluation based on distance from average solution (EDAS-Gray). Another group of hybrid methods including the gray weighted sum method (WSM-Gray), the gray complex proportional assessment (COPRAS-Gray), and the gray technique for order of preference by similarity to ideal solution (TOPSIS-Gray) is used to validate the results. The rankings obtained from all of these techniques show high degree of correlation. Among the identified challenges, "high investment cost" is found to be the most important challenge to the application of blockchain in sustainable energy supply chains.

Analysis of Current Neurological Surgery Residents and Prior Medical Education: Do Medical School Attributes Matter?

BACKGROUND

With the recent changes to the U.S. Medical Licensing Examination grading system, an understanding of the factors that influence the neurological surgery residency match process is crucial for residency directors. The aim of the present retrospective study was to explore the associations of medical school location, ranking, private school status, size, and presence of an American Association of Neurological Surgeons (AANS) chapter or neurological surgery interest group (NSIG) with the neurosurgery match outcomes.

METHODS

An enrollment list of all accredited U.S. neurosurgery residency programs was compiled on June 28, 2021. For the included residents, the residency program, degree, and previously attended medical school were retrieved. The geographic location, ranking, private school status, and size were collected for the residency programs and medical schools attended by the residents at each program.

RESULTS

A total of 1437 residents from 101 neurosurgery residency programs (89%) were included. Graduates from the top 25 medical schools were more likely to match into their home residency programs (P < 0.001) and highly ranked residency programs (P < 0.001). Students from larger medical schools were also more likely to match into larger (P < 0.001) and highly ranked (P < 0.001) programs than were applicants from smaller schools. Students from medical schools with an AANS chapter or NSIG were also more likely to match into top ranked programs (P < 0.001 for both).

CONCLUSIONS

Medical students from the top 25 medical schools, private medical schools, medical schools with an AANS chapter, and medical schools with an NSIG were more likely to match into a prestigious residency program. These findings suggest that underlying biases might be present for program directors to consider in the resident selection process.

TiO2 nanoparticles' library toxicity (UV and non-UV exposure) - High-throughput in vivo transcriptomics reveals mechanisms

The hazards of nanomaterials/nanoparticles (NMs/NPs) are mostly assessed using individual NMs, and a more systematic approach, using many NMs, is needed to evaluate its risks in the environment. Libraries of NMs, with a range of identified different but related characters/descriptors allow the comparison of effects across many NMs. The effects of a custom designed Fe-doped TiO₂ NMs library containing 11 NMs was assessed on the soil model Enchytraeus crypticus (Oligochaeta), both with and without UV (standard fluorescent) radiation. Effects were analyzed at organism (phenotypic, survival and reproduction) and gene expression level (transcriptomics, high-throughput 4x44K microarray) to understand the underlying mechanisms. A total of 48 microarrays (20 test conditions) were done plus controls (UV and non-UV). Unique mechanisms induced by TiO₂ NPs exposure included the impairment in RNA processing for TiO₂_10nm, or deregulated apoptosis for 2%FeTiO₂_10nm. Strikingly apparent was the size dependent effects such as induction of reproductive effects via smaller TiO₂ NPs (≤12 nm) - embryo interaction, while larger particles (27 nm) caused reproductive effects through different mechanisms. Also, phagocytosis was affected by 12 and 27 nm NPs, but not by ≤11 nm. The organism level study shows the integrated response, i.e. the result after a cascade of events. While uni-cell models offer key mechanistic information, we here deliver a combined biological system level (phenotype and genotype), seldom available, especially for environmental models.

Origami plot: a novel multivariate data visualization tool that improves radar chart

OBJECTIVES

We propose the origami plot, which maintains the original functionality of a radar chart and avoids potential misuse of its connected regions, with newly added features to better assist multicriteria decision-making.

STUDY DESIGN AND SETTING

Built upon a radar chart, the origami plot adds additional auxiliary axes and points such that the area of the connected region of all dots is invariant to the ordering of axes. As such, it enables ranking different individuals by the overall performance for multicriteria decision-making while maintaining the intuitive visual appeal of the radar chart. We develop extensions of the origami plot, including the weighted origami plot, which allows reweighting of each attribute to define the overall performance, and the pairwise origami plot, which highlights comparisons between two individuals.

RESULTS

We illustrate the different versions of origami plots using the hospital compare database developed by the Centers for Medicare & Medicaid Services (CMS). The plot shows individual hospital's performance on mortality, readmission, complication, and infection, as well as patient experience and timely and effective care, as well as their overall performance across these metrics. The weighted origami plot allows weighing the attributes differently when some are more important than others. We illustrate the potential use of the pairwise origami plot in electronic health records (EHR) system to monitor five clinical measures (body mass index [BMI]), fasting glucose level, blood pressure, triglycerides, and low-density lipoprotein ([LDL] cholesterol) of a patient across multiple hospital visits.

CONCLUSION

The origami plot is a useful visualization tool to assist multicriteria decision making. It improves radar charts by avoiding potential misuse of the connected regions. It has several new features and allows flexible customization.

DNAsmart: Multiple attribute ranking tool for DNA data storage systems

In an ever-growing need for data storage capacity, the Deoxyribonucleic Acid (DNA) molecule gains traction as a new storage medium with a larger capacity, higher density, and a longer lifespan over conventional storage media. To effectively use DNA for data storage, it is important to understand the different methods of encoding information in DNA and compare their effectiveness. This requires evaluating which decoded DNA sequences carry the most encoded information based on various attributes. However, navigating the field of coding theory requires years of experience and domain expertise. For instance, domain experts rely on various mathematical functions and attributes to score and evaluate their encodings. To enable such analytical tasks, we provide an interactive and visual analytical framework for multi-attribute ranking in DNA storage systems. Our framework follows a three-step view with user-settable parameters. It enables users to find the optimal en-/de-coding approaches by setting different weights and combining multiple attributes. We assess the validity of our work through a task-specific user study on domain experts by relying on three tasks. Results indicate that all participants completed their tasks successfully under two minutes, then rated the framework for design choices, perceived usefulness, and intuitiveness. In addition, two real-world use cases are shared and analyzed as direct applications of the proposed tool. DNAsmart enables the ranking of decoded sequences based on multiple attributes. In sum, this work unveils the evaluation of en-/de-coding approaches accessible and tractable through visualization and interactivity to solve comparison and ranking tasks.

Considering multiple outcomes with different weights informed the hierarchy of interventions in network meta-analysis

OBJECTIVES

Ranking metrics in network meta-analysis (NMA) are computed separately for each outcome. Our aim is to 1) present graphical ways to group competing interventions considering multiple outcomes and 2) use conjoint analysis for placing weights on the various outcomes based on the stakeholders' preferences.

STUDY DESIGN AND SETTING

We used multidimensional scaling (MDS) and hierarchical tree clustering to visualize the extent of similarity of interventions in terms of the relative effects they produce through a random effect NMA. We reanalyzed a published network of 212 psychosis trials taking three outcomes into account as follows: reduction in symptoms of schizophrenia, all-cause treatment discontinuation, and weight gain.

RESULTS

Conjoint analysis provides a mathematical method to transform judgements into weights that can be subsequently used to visually represent interventions on a two-dimensional plane or through a dendrogram. These plots provide insightful information about the clustering of interventions.

CONCLUSION

Grouping interventions can help decision makers not only to identify the optimal ones in terms of benefit-risk balance but also choose one from the best cluster based on other grounds, such as cost, implementation etc. Placing weights on outcomes allows considering patient profile or preferences.

Using filled prescription sequences to rank antidepressants: A nationwide replication study

Ranking antidepressants according to their acceptability (i.e., a combination of both efficacy and tolerability) in the general population may help choosing the best first-line medication. This study aimed to replicate the results of a proof-of-concept study ranking anti-depressants according to the proportion of filled prescription sequences consistent with a continuation of the first treatment versus those consistent with a change. We used a nationwide cohort from the French national health data system (SNDS) to support the use of this method as a widely available tool to rank antidepressant treatments in real life settings. About 1.2 million people were identified as new antidepressant users in the SNDS in 2011. The outcome was clinical acceptability as measured by the continuation/failure ratio over the six-month period following the introduction of the first-line treatment. Continuation was defined as at least two refills of the same treatment. Failure was defined as a psychiatric hospitalization, death or at least one filled prescription of another antidepressant, an antipsychotic medication, or a mood-stabilizer. Adjusted Odds Ratios (aOR) and 95% Confidence Interval (CI) were computed through multivariable binary logistic regressions. We ranked antidepressant medications according to clinical acceptability. Escitalopram again was the most acceptable option, and the five following antidepressants were the same as in the replication sample of the proof-of-concept study, in order Fluoxetine, Paroxetine, Sertraline, Citalopram and Venlafaxine with aOR (95% CI) for continuation ranging from 0.79 (0.77-0.81) to 0.66 (0.64-0.67). The present study provides evidence that filled prescription sequences is a widely available, robust and reproductible tool to rank antidepressant treatments in real life settings.

The Probabilistic Final Standing Calculator: a fair stochastic tool to handle abruptly stopped football seasons

The COVID-19 pandemic has left its marks in the sports world, forcing the full stop of all sports-related activities in the first half of 2020. Football leagues were suddenly stopped, and each country was hesitating between a relaunch of the competition and a premature ending. Some opted for the latter option and took as the final standing of the season the ranking from the moment the competition got interrupted. This decision has been perceived as unfair, especially by those teams who had remaining matches against easier opponents. In this paper, we introduce a tool to calculate in a fairer way the final standings of domestic leagues that have to stop prematurely: our Probabilistic Final Standing Calculator (PFSC). It is based on a stochastic model taking into account the results of the matches played and simulating the remaining matches, yielding the probabilities for the various possible final rankings. We have compared our PFSC with state-of-the-art prediction models, using previous seasons which we pretend to stop at different points in time. We illustrate our PFSC by showing how a probabilistic ranking of the French Ligue 1 in the stopped 2019-2020 season could have led to alternative, potentially fairer, decisions on the final standing.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10182-021-00416-6.

More than just a number of publications: Unity Index, an alternative "ranking" for bibliometric analyses

This paper presents the unity index- an index designed in response to the call to find a more holistic way to assess scientific production. In this case, the scientific production is understood from a multivariate perspective using existing measurements, such as the number of publications, the number of, and the H-Index. It can be used especially when generating or assessing production in bibliometric studies. The index consists of a 3-part point system where points are assigned to the authors based on their position in the rank of the 3 traditional indicators for production, acceptance and impact. The index is calculated by attributing 1 point to the author with most published articles and increasing the number of points attributed by 1 to all the subsequent authors. The same point attribution is done to the remaining 2 indicators, acceptance -citations- and impact -h-index-. In the presented method, 3 different means of calculation are shared. Finally, the method is validated and different ways to analyze the results and generate insights are suggested.•The Unity Index offers a new way to assess scientific production from a multivariate perspective.•The index can be calculated easily using MS Excel formulas, but automatic ways of calculation are also easily available.•Bibliometric studies can profit from a less linear way to analyze the information and generate more insightful information and guide the research.