Top Ranking Research Articles

WOA: Wombat Optimization Algorithm for Solving Supply Chain Optimization Problems

Supply Chain (SC) Optimization is a key activity in today’s industry with the goal of increasing operational efficiency, reducing costs, and improving customer satisfaction. Traditional optimization methods often struggle to effectively use resources while handling complex and dynamic Supply chain networks. This paper introduces a novel biomimetic metaheuristic algorithm called the Wombat Optimization Algorithm (WOA) for supply chain optimization. This algorithm replicates the natural behaviors observed in wombats living in the wild, particularly focusing on their foraging tactics and evasive maneuvers towards predators. The theory of WOA is described and then mathematically modeled in two phases: (i) exploration based on the simulation of wombat movements during foraging and trying to find food and (ii) exploitation based on simulating wombat movements when diving towards nearby tunnels to defend against its predators. The effectiveness of WOA in addressing optimization challenges is assessed by handling the CEC 2017 test suite across various problem dimensions, including 10, 30, 50, and 100. The findings of the optimization indicate that WOA demonstrates a strong ability to effectively manage exploration and exploitation, and maintains a balance between them throughout the search phase to deliver optimal solutions for optimization problems. A total of twelve well-known metaheuristic algorithms are called upon to test their performance against WOA in the optimization process. The outcomes of the simulations reveal that WOA outperforms the other algorithms, achieving superior results across most benchmark functions and securing the top ranking as the most efficient optimizer. Using a Wilcoxon rank sum test statistical analysis, it has been proven that WOA outperforms other algorithms significantly. WOA is put to the test with twenty-two constrained optimization problems from the CEC 2011 test suite and four engineering design problems to showcase its ability to solve real-world optimization problems. The results of the simulations demonstrate that WOA excels in real-world applications by delivering superior solutions and outperforming its competitors.

Benchmarking ANI potentials as a rescoring function and screening FDA drugs for SARS-CoV-2 Mpro

Here, we introduce the use of ANI-ML potentials as a rescoring function in the host–guest interaction in molecular docking. Our results show that the “docking power” of ANI potentials can compete with the current scoring functions at the same level of computational cost. Benchmarking studies on CASF-2016 dataset showed that ANI is ranked in the top 5 scoring functions among the other 34 tested. In particular, the ANI predicted interaction energies when used in conjunction with GOLD-PLP scoring function can boost the top ranked solution to be the closest to the x-ray structure. Rapid and accurate calculation of interaction energies between ligand and protein also enables screening of millions of drug candidates/docking poses. Using a unique protocol in which docking by GOLD-PLP, rescoring by ANI-ML potentials and extensive MD simulations along with end state free energy methods are combined, we have screened FDA approved drugs against the SARS-CoV-2 main protease (Mpro). The top six drug molecules suggested by the consensus of these free energy methods have already been in clinical trials or proposed as potential drug molecules in previous theoretical and experimental studies, approving the validity and the power of accuracy in our screening method.

COMPARATIVE ANALYSIS OF AUTOMATION FUNCTIONAL TESTING TOOLS PERFORMANCE FOR PLAYSTORE APPS WITH DIA METHOD

The complexity of smartphone applications presents challenges for developers, who must ensure flawless functionality despite limitations such as budget and time constraints. Manual testing is time-consuming, prompting a shift towards automated testing methods to ensure efficiency and reliability. In this context, researchers are evaluating the efficacy of three leading test automation frameworks—Robot Framework, Katalon Studio, and UI Path—against key performance parameters. Using the Distance to the Ideal Alternative (DIA) method on playstore apps. The main performance parameters used as a reference are automated testing progress and tools usability. Katalon Studio emerges as the top performer, securing the top rank with a remarkably close to the alternative ideal positive distance (Ri) value of 0.00001. UI Path occupies the second position with a Ri value of 0.00135, while Robot Framework trails behind with a Ri value of 0.00295. This research contributes to the understanding of the performance of different automation frameworks in the context of functional testing, providing valuable insights for developers and organizations seeking to optimize their testing processes. The findings underscore the significance of Katalon Studio's exceptional performance and highlight opportunities for improvement in UI Path and Robot Framework. Additionally, implementing a robust monitoring and evaluation framework is crucial for tracking the ongoing performance and optimizing the efficiency of these automation frameworks.

Abstract 4427: Do changes in lipid metabolism link obesity to pancreatic cancer

Abstract The near equal incidence and mortality rates of pancreatic cancer, combined with projections that pancreatic cancer will become the second-most common cancer-related deaths by 2050, underscore the need to identify patients with early disease and interrupt this trajectory. Obesity, weight gain and waistline have been implicated in increasing the risk of pancreatic cancer. Although metabolomic analyses of pancreatic cancer patients have established correlations between phospholipids, lysophospholipids with treatment outcomes, the association between metabolites, obesity, and pancreatic cancer remains largely understudied. The objective of this pilot study was to determine differences in serum metabolites in obese and overweight pancreatic cancer patients compared with healthy non-obese subjects. Our long-term goal is to develop serum marker(s) that may be used to prevent advanced pancreatic cancer and thus improve outcomes for these patients. Serum was obtained from healthy subjects (n=11; BMI range from 18-25), overweight (n=9; 25-30) and obese (n=7; >30) pancreatic cancer patients from an IRB approved study. Males (n=12) and females (n=15) were represented in the study. Global metabolic profiles were determined using Ultrahigh performance liquid chromatography-tandem mass spectroscopy. Raw data was extracted, peaks were identified and processed at Metabolon using the Laboratory Information Management System. Comparison between overweight pancreatic cancer patients and healthy controls identified 403 biochemicals (111 upregulated and 292 downregulated; p <0.05) and 93 biochemicals (40 upregulated and 53 downregulated; 0.05<p<0.10). Comparison of the differences in biochemicals between obese pancreatic cancer patients and healthy controls showed changes in 293 biochemicals (71 upregulated and 222 downregulated; p <0.05) and 123 biochemical changes at 0.05<p<0.10 (42 increased and 81 decreased). 38 (p <0.05) and 47 (0.05<p<0.10) differential levels of biochemicals were identified when obese and overweight pancreatic cancer patients were compared. Random forest analysis showed that the 30 top ranking biochemicals were involved in lipid metabolism, amino acid metabolism, nucleotide metabolism, peptide, xenobiotics, and carbohydrate metabolism. These data suggest an association between changes in lipid metabolism may be another link between obesity and pancreatic cancer. This project was funded in part by VA-Merit Award (I01 BX003876). Citation Format: Rita Ghosh, Deepa Ajit, Jillian Woodworth, Danielle Fritze, Francisco G. Cigarroa, Glenn A. Halff, Addanki Pratap Kumar. Do changes in lipid metabolism link obesity to pancreatic cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4427.

Benzothiazole based sulfonamide scaffolds as active inhibitors of alpha-Amylase and alpha-glucosidase; synthesis, structure confirmation, In Silico molecular docking and ADME analysis

In the current research study, benzothiazole based sulfonamide scaffolds were designed and synthesized having promising efficacy as dual inhibitors of alpha-Amylase & alpha-Glucosidase with a purpose to cure one of the chronic diseases, Diabetes Mellitus. Synthetic confirmation of all the derivatives was accomplished through different spectroscopic techniques, 13C NMR, 1H NMR and HREI-MS. For the evaluation of drug potency of the newly synthesized ligands, biological activity was conducted using the standard drug acarbose (IC50 = 5.40 ± 0.30 µM for α-amylase and 5.70 ± 0.50 µM for α-glucosidase). A wide span of inhibitory potentials were shown by the analogs of current series covering a range of IC50 = 20.70 ± 0.20 µM and 2.10 ± 0.70 µM for α-amylase and 21.40 ± 0.20 µM and 2.40 ± 0.10 µM for α-glucosidase. Potency of the analogs is mainly dependent on the attached substituent moieties, their nature, number and position on the phenyl ring. Based on these protocols, analog-4 with an IC50 = 2.10 ± 0.70 µM for α-amylase and 2.40 ± 0.10 µM for α-glucosidase was found to be the top ranking scaffold with excellent inhibition against the target enzymes in the series. In analog-4, the trifluoromethyl moiety at the para position of the ring, capable to interact through hydrogen bond with active site of the enzyme, is the contributing factor to the efficacy of the analog. Binding insight of the protein-ligand interaction of all the potent analogs was gained through molecular docking study. Furthermore, the drug likeness attributes of the potent derivatives were explored through ADME analysis.

Statistical analysis of sequential motifs at biologically relevant protein-protein interfaces

Understanding protein-protein interactions (PPIs) at the molecular level may lead to innovations in medicine and biochemistry. The assumption that there are certain “hot spots” on protein surfaces that mediate their interactions with other proteins has led to a search for specific sequences involved in protein-protein contacts. In this work, we analyze sequential amino acid motifs, both at the single motif and at the motif-motif level, across a large and diverse dataset of biologically relevant protein-protein interfaces retrieved from the PDB, comparing their presence at interfaces and surfaces in a statistically rigorous manner. At the single motif level, our results indicate statistically significant over-presence of hydrophobic and in particular aromatic residues and under-presence of charged residues at protein-protein interfaces. Certain PPI-mediating motifs reported in the literature (e.g., the Tyrosine-based Motif YxxΦ and the PDZ-Binding Motif X-S/T-X-V/I) were confirmed to have a significant presence at interfaces. In addition, multiple PPI-mediating motifs were reported in the ELM database and from those present in our dataset, half were confirmed to have a statistically significant presence at interfaces whereas others were not. At the single residue, motif-motif level, Cysteine-Cysteine contacts were found to be the most abundant ones followed by interactions involving aromatic/hydrophobic residues. Top ranking, longer motif-motif pairs show predominance of Leucine and aromatic residues. Finally, preliminary energy calculations (using the MM/GBSA procedure) indicate a partial correlation between the probability of motifs-pair to be a part of a protein-protein interface and the strength of the interactions between the motifs. In conclusion, this study points to specific characteristics of motifs that have a higher probability to mediate protein-protein interactions. Prominent motifs identified in this study may be used in the future as possible components in protein engineering.

A Tutorial on Cross-layer Optimization Wireless Network System Using TOPSIS Method

Wireless network system. Introduction: The availability and rising demand of ubiquitous connectivity has been one of the most revolutionary technological trends of the last ten years. Today, we anticipate being able can access these internet services at any time, from everywhere, for a variety of purposes, including checking email, using the phone, browsing the web, and a plethora of other uses, such as when travelling by car, subway, airline, or anywhere else. Although we still need to actively seek out connections today (by looking for a Wi-Fi hotspot nearby), the future will undoubtedly feature ubiquitous connectivity and Internet access. Central to this movement are wireless networks. A wireless network is any network that is not linked by cables and provides the user with the comfort and mobility they need. We may anticipate that dozens of various wireless technologies will be available to satisfy the demands, each with distinct performance requirements and each tailored for a particular task and environment, given the enormous variety of use cases and applications. Research signification: The densest wireless network deployments up until recently took place in campus-like settings, with the cell architecture being meticulously planned by professionals. The wireless environment is evolving quickly due to the increasing adoption of low-cost 802.11 equipment as well as other personal wireless devices (2.4 GHz cordless telephones, Bluetooth devices). There are two significant differences between dense installations of wireless networking hardware in locations like neighborhoods, shopping centers, and apartment buildings and campus-type deployments. First, numerous separate people or devices, each installing one or a small number of APs, result in complicated installations that are meticulously planned to enhance coverage and reduce cell overlap. The concentration of wireless sensor nodes and APs produced by this kind of haphazard, unplanned deployment is widely varied (and sometimes quite high). Methodology: Alternative: 1G, 2G, 3G, and 4G. Evaluation Preference: Multiplexing, Implementation, Services, Standards, Core Network. Results: from the result it is seen that Core Network is got the first rank where as is the Services is having the lowest rank. Conclusion: The value of the dataset for Wireless network system in TOPSIS method shows that it results in Core Network and top ranking.

Strengthening Students’ Proficiency in Digital Technologies and the SMART Society

The relevance of the article is that nowadays digital technologies are an effective means of differentiation and personalization of educational activities, they change the face of today’s education, turning it into the top rank of human capital investment in the digital age. The shift to digital education requires the collaborative effort of instructors, administrators, and learners to create and meet educational goals, using data analysis to provide individualised learning plans for students. The article is devoted to the issue of formation of digital skills in the learning process of students. The concept of digital literacy and digital skills, as well as the classification of digital skills is considered. The author proposes indicators and criteria for assessing digital skills, as well as theoretical and practical training of students, presented in the form of several modules. The choice of research methods is conditioned by the peculiarities of studying informatization and digitalization, as well as the peculiarities of using up-to-date information technologies in the educational process. The following methods were chosen: analysis of psychological, pedagogical and methodological literature, descriptive method, method of generalization, system-structural analysis, method of interpretation and semantic reconstruction of pedagogical sources.

Hippopotamus optimization algorithm: a novel nature-inspired optimization algorithm

The novelty of this article lies in introducing a novel stochastic technique named the Hippopotamus Optimization (HO) algorithm. The HO is conceived by drawing inspiration from the inherent behaviors observed in hippopotamuses, showcasing an innovative approach in metaheuristic methodology. The HO is conceptually defined using a trinary-phase model that incorporates their position updating in rivers or ponds, defensive strategies against predators, and evasion methods, which are mathematically formulated. It attained the top rank in 115 out of 161 benchmark functions in finding optimal value, encompassing unimodal and high-dimensional multimodal functions, fixed-dimensional multimodal functions, as well as the CEC 2019 test suite and CEC 2014 test suite dimensions of 10, 30, 50, and 100 and Zigzag Pattern benchmark functions, this suggests that the HO demonstrates a noteworthy proficiency in both exploitation and exploration. Moreover, it effectively balances exploration and exploitation, supporting the search process. In light of the results from addressing four distinct engineering design challenges, the HO has effectively achieved the most efficient resolution while concurrently upholding adherence to the designated constraints. The performance evaluation of the HO algorithm encompasses various aspects, including a comparison with WOA, GWO, SSA, PSO, SCA, FA, GOA, TLBO, MFO, and IWO recognized as the most extensively researched metaheuristics, AOA as recently developed algorithms, and CMA-ES as high-performance optimizers acknowledged for their success in the IEEE CEC competition. According to the statistical post hoc analysis, the HO algorithm is determined to be significantly superior to the investigated algorithms. The source codes of the HO algorithm are publicly available at https://www.mathworks.com/matlabcentral/fileexchange/160088-hippopotamus-optimization-algorithm-ho.

Ranking‐based architecture generation for surrogate‐assisted neural architecture search

AbstractArchitectures generation optimization has been received a lot of attention in neural architecture search (NAS) since its efficiency in generating architecture. By learning the architecture representation through unsupervised learning and constructing a latent space, the prediction process of predictors is simplified, leading to improved efficiency in architecture search. However, searching for architectures with top performance in complex and large NAS search spaces remains challenging. In this paper, an approach that combined a ranker and generative model is proposed to address this challenge through regularizing the latent space and identifying architectures with top rankings. We introduce the ranking error to gradually regulate the training of the generative model, making it easier to identify architecture representations in the latent space. Additionally, a surrogate‐assisted evolutionary search method that utilized neural network Bayesian optimization is proposed to efficiently explore promising architectures in the latent space. We demonstrate the benefits of our approach in optimizing architectures with top rankings, and our method outperforms state‐of‐the‐art techniques on various NAS benchmarks. The code is available at https://github.com/outofstyle/RAGS‐NAS.

Darien Gap Forested Jungles and Waterways (APDDGFJW) of Latin America and the Caribbean (LAC) in the Post-COVID 19 of the 21st Century

This paper deals with the identification of the Darien Gap as the main channel of continuous clandestine, illegal, undocumented and irregular migratory pathways of African Youths which caught our attention in the post-COVID 19 of the 21st Century with gross ambitions to get richer faster through the slogan of greener pastures with the majority giving off their lives ignorantly and embarrassingly to tilapias of the Mexican deep rivers in an attempt to cross to North American countries of United States and Canada. The end results was the untimely psychological tortures of their parents and sporadic internal crises of blaming even those who never contributed to such unwanted illegal movements but raising voices to educate on the dangers of un official migration both internally or externally. In fact the majority of the youths having such ambitions of illegal crossing of the Darien Gap are totally ignorant of the nature of the route which has been above the imagination of top ranking Engineers to open it to be more possible for vehicles to use. The hilly, mountainous, muddy, swampy, smugglers, kidnapping, ripping and all sorts of trafficking are characteristics of the Darien Gap which none of the agent involve in such illegal route can account to their victims. It is just certain that any of such irregular extra-continental travelling without passing through official diplomatic services which moderate bilateral relations can only be termed as above. It is also our findings that the clandestine pathway routes those using are passing is characterized with wild animals, dangerous human criminals of trafficking, bandits, muddy, dense forested, not motorable as even top engineers have not been able to successfully mapped out a good road that can be constructed with the Darien deadly jungle. Our inspirations were drawn from lecturing of Post-Graduate students on the question of International Migration and Black Diasporas around the World during which most of them were ......

The impact of strategic napping on peak expiratory flow and respiratory function in young elite athletes

Respiratory health is a critical determinant of athletic performance, and the utilization of restorative strategies, such as strategic napping, may offer a competitive edge to athletes. This study investigates the effects of nap duration on the respiratory function of young elite athletes who have achieved top rankings national competitions. Participants engage in three test sessions with varying nap durations: no nap (N0), a 25-minute nap (N25), and a 45-minute nap (N45), with a minimum 72-hour interval between sessions. Respiratory parameters including Forced Vital Capacity (FVC), Forced Expiratory Volume in one second (FEV1), FEV1/FVC ratio, Peak Expiratory Flow rate (PEF), Forced Expiratory Flow at 25–75% of FVC (FEF25-75%), and Forced Expiratory Time (FET) are assessed. Results reveal a significant enhancement in PEF values following a 45-minute nap (N45) compared to the no-nap control (N0) [F1 − 11=7.356, p =.004, ηp2 = 0.401, (95% CI for difference: -1.56 to − 0.056)], indicating a potential positive influence of napping on maximum expiratory flow rate and, consequently, athletes’ respiratory performance. While no significant changes are observed in other respiratory parameters across different nap durations, these findings underscore the potential benefits of strategic napping in optimizing respiratory health in young elite athletes.

A bibliometric analysis of the literature on crop yield prediction: insights from previous findings and prospects for future research.

This research presents a bibliometric analysis of articles predicting crop yield using machine learning methods. While several systematic review articles exist, a comprehensive bibliometric analysis illustrating the knowledge structure and research trends, along with collaboration networks among authors, institutions, and countries in this field, has not been conducted. The study focused on 826 articles published over a 32-year period (1992 to 2023) and revealed a significant increase in publications, particularly in recent years. Zhang Zhao from China authored the majority of articles, while the highest number of citations was associated with articles by Zhu Yan and Lobell. Leading countries in article publications are the USA, China, India, Germany, Australia, and Canada, showing strong interconnections in citing each other's research. The Chinese Academy of Sciences and the US Department of Agriculture are the institutions with the highest number of articles and citations in this domain. The journals Agricultural and Forest Meteorology and Remote Sensing are recognized as top ranking journals in this field (Q1). Based on co-occurrence analysis, three main thematic domains were identified: weather and crop yield prediction, plant growth simulation models, and crop yield prediction using remote sensing data. The research suggests a focus on variables such as disease, pests, insects, and soil salinity when predicting yield. Additionally, greater attention should be given to discussions on food security and crop yield, especially in developing countries.

Monitoring Perkembangan Program Bank Sampah Menggunakan Tableau Public di RW 05 Kelurahan Cipinang Besar Selatan

This community service focuses on managing the Waste Bank in RW 05, Cipinang Besar Selatan Subdistrict with the aim of overcoming the lack of public interest in the Waste Bank program. Through a mentoring approach using Tableau Public, this activity aims to increase public understanding of the program. By using qualitative analysis, the results of the waste movement dashboard visualization are expected to provide an understanding of the influence of the Waste Bank on increasing waste volume. The research results show that data visualization using Tableau Desktop successfully achieved service objectives, providing significant insight into the effectiveness and development potential of the Waste Bank program. Features such as Total Waste per Month, Top Customer Rank, Top District, Top Types of Waste, and RT Participation provide an in-depth understanding of program dynamics. Data visualization has succeeded in increasing public interest, effectively reducing environmental pollution, and providing transparency of contributions, positive comparisons, personal understanding of environmental impacts, and motivation through growth and achievement. Therefore, the use of Tableau data visualization in the Waste Bank program is not only a data management tool, but also a driver of active participation and public awareness of the importance of protecting the environment. The Waste Bank program supported by data visualization has great potential to achieve sustainability goals and reduce negative impacts on the environment.

Improving The E-Satisfaction and E-Loyalty Based on E-Trust and E-Service Quality on Shopee Customer

The lack of consumer disloyalty in the shopping process, especially amid Shopee's dominance as a market leader, is the focal point of this research. Shopee managed to achieve top rankings in shaping customer loyalty in the online marketplace. This study aimed to identify several factors that affect customer loyalty on the Shopee platform through trust, good service at Shopee, and satisfaction. Considers related to the important role e-satisfaction plays as a mediating variable in understanding the impact of e-trust and e-service quality on Shopee customer loyalty. A quantitative research design was used, with 100 respondents receiving a questionnaire via Google Form, using simple random sampling techniques in data collection. Data analysis was performed through Structural Equation Modeling (SEM) using the SMART PLS application. Research findings show that the impact of e-trust on Shopee consumer loyalty is quite significant and that the quality of e-service also significantly impacts Shopee customer e-loyalty. In contrast, e-satisfaction is a mediator that significantly affects customers’ e-loyalty levels. Managers must focus on improving the quality of e-services for customer satisfaction. This can include continuous measurement and improvement in website consistency, response speed, and information availability.

SOSIALISASI PENANGGULANGAN BULLYING BERBASIS TEAM BUILDING MENGGUNAKAN PSIKOEDUKASI DI SMK BINA SRIWIJAYA INDONESIA PALEMBANG

Bullying cases in Indonesia occupy the top ranking. Bullying behavior often occurs when someone has shortcomings, both physically and mentally. The impact of bullying on students is in the form of decreased appetite, headaches, embarrassment, and feeling afraid to socialize in social environments. Increasing students' understanding regarding bullying behavior can reduce bullying cases. Bullying can start from uncontrolled levels of aggressive behavior during childhood. However, this can be prevented by increasing supervision of negative associations from children and friends, starting from modeling good things, filtering out children's friends who have a positive effect. The aim of this intervention is to provide students with understanding and knowledge regarding bullying, its types, etc. Bullying affects both boys and girls. The method based on this intervention consists of 4 stages, namely needs assessment for the Counseling Guidance teacher, distribution of bullying questionnaires to students, Focus Group Discussion (FGD) with students, provision of materials and games in team building. The series of activities were attended by 40 students consisting of 20 men and 20 women from several representatives of departments at Bina Sriwijaya Indonesia Palembang Vocational School. The results of the intervention activities that have been implemented are that students feel openness in terms of both thoughts and feelings regarding bullying behavior. The service activities at Bina Sriwijaya Indonesia Palembang Vocational School have had a very good impact on the entire school community, especially students, subject teachers, guidance and counseling teachers and all staff and equipment at the school. The Principal welcomed and looked forward to further positive activities at Bina Sriwijaya Indonesia Palembang Vocational School. From the results of a questionnaire conducted on community service participants, 87.5% of students strongly agreed with socialization activities to overcome bullying and 12.5% ​​agreed.

Decision Support System for the Presidential Election of the Student Executive Board Using the Multi-Factor Evaluation Process Method

Student Executive Board is a student organization or executive institution found in every tertiary institution and can represent the existence of a tertiary institution. The student Executive Board is headed by the Student Executive Board President, who is assisted by the Secretary-General, three Coordinating Ministers, and several ministries that represent student needs. In carrying out its function as a forum for student aspirations to make changes (agents of change) in paradigm, emotional, intellectual, and religious values, the Student Executive Board requires student candidates who are in synergy with their vision and mission. The Student Executive Board Presidential Election is usually held every year. A decision support system (DSS) was built by implementing the Multi-Factor Evaluation Process (MFEP) method to easily and efficiently elect the Student Executive Board President quickly and efficiently. The criteria used are communication skills (C1), leadership attitude (C2), vision and mission (C3), skills (C4), and organizational experience (C5). Each criterion is weighted where the total weight of all criteria equals 1. Next, calculate the evaluation weight value (EW), total evaluation weight (TEW), and ranking. The research results show that alternative 7 (A7), with the highest score of 4.35, is the student candidate with the top ranking, meaning A7 is the most recommended to be elected as President of the Student Executive Board. With this DSS, we can provide appropriate recommendations for Student Executive Board Presidential candidates and assist universities and students in carrying out the selection process quickly and efficiently.

CMC: Cancer miRNA Census - a list of cancer-related miRNA genes.

A growing body of evidence indicates an important role of miRNAs in cancer; however, there is no definitive, convenient-to-use list of cancer-related miRNAs or miRNA genes that may serve as a reference for analyses of miRNAs in cancer. To this end, we created a list of 165 cancer-related miRNA genes called the Cancer miRNA Census (CMC). The list is based on a score, built on various types of functional and genetic evidence for the role of particular miRNAs in cancer, e.g. miRNA-cancer associations reported in databases, associations of miRNAs with cancer hallmarks, or signals of positive selection of genetic alterations in cancer. The presence of well-recognized cancer-related miRNA genes, such as MIR21, MIR155, MIR15A, MIR17or MIRLET7s, at the top of the CMC ranking directly confirms the accuracy and robustness of the list. Additionally, to verify and indicate the reliability of CMC, we performed a validation of criteria used to build CMC, comparison of CMC with various cancer data (publications and databases), and enrichment analyses of biological pathways and processes such as Gene Ontology or DisGeNET. All validation steps showed a strong association of CMC with cancer/cancer-related processes confirming its usefulness as a reference list of miRNA genes associated with cancer.

Defining quality indicators, pharmaceutical care bundles and outcomes of clinical pharmacy service delivery using a Delphi consensus approach.

Clinical pharmacy quality indicators are often non-uniform and measure individual activities not linked to outcomes. To define a consensus agreed pharmaceutical care bundle and patient outcome measures across an entire state health service. A four-round modified-Delphi approach with state Directors of Pharmacy was performed (n = 25). They were asked to rate on a 5-point Likert scale the relevance and measurability of 32 inpatient clinical pharmacy quality indicators and outcome measures. They also ranked clinical pharmacy activities in order from perceived most to least beneficial. Based upon these results, pharmaceutical care bundles consisting of multiple clinical pharmacy activities were formed, and relevance and measurability assessed. Response rate ranged from 40 to 60%. Twenty-six individual clinical pharmacy quality indicators reached consensus. The top ranked clinical pharmacy quality indicator was 'proportion of patients where a pharmacist documents an accurate list of medicines during admission'. There were nine pharmaceutical care bundles formed consisting between 3 and 7 activities. Only one pharmaceutical care bundle reached consensus: medication history, adverse drug reaction/allergy documentation, admission and discharge medication reconciliation, medication review, provision of medicines education and provision of a medication list on discharge. Sixteen outcome measures reached consensus. The top ranked were hospital acquired complications, readmission due to medication misadventure and unplanned readmission within 10 days. Consensus has been reached on one pharmaceutical care bundle and sixteen outcomes to monitor clinical pharmacy service delivery. The next step is to measure the extent of pharmaceutical care bundle delivery and the link to patient outcomes.

Understanding Consumer Attitudes Towards Sustainable Business Models—A Qualitative Study with Finnish Consumers

Sustainable business models have been presented in the literature as a way to gain stepwise improvements in environmental impact compared to just selling a product, and many companies have started experimenting with them. However, these models are not yet scaled up across sectors. One of the barriers is understanding how consumers perceive sustainable business models and how much they would be ready to pay products and services from sustainable offerings. To this extent, our study investigated the following research questions: How do consumers perceive the sustainability attributes of novel sustainable business models? How does this affect consumer willingness to pay (WTP) for the offering provided? This study uses a qualitative research approach, conducting online discussions among 44 Finnish consumers. Finland is in focus as it has a top ranking in sustainability country indexes. Through the study, it was found that consumers pay attention to sustainability of the products and services they consume. They are willing to use available information and assess this to make sustainable purchasing decisions. However, they lack trustworthy information and sometimes it is too time-consuming to find the data. When making purchasing decisions, consumers perceive certain positive environmental and social impacts. However, the environmental and social impact of the studied business models did not turn into consumer WTP especially when considering expensive products, or business models with a social impact only. Still, in general, over half of the participants are willing to pay more about responsible produced products.