Ranking Research Articles

Production of Xylitol and Ethanol from Agricultural Wastes and Biotransformation of Phenylacetylcarbinol in Deep Eutectic Solvent

Converting agricultural biomass wastes into bio-chemicals can significantly decrease greenhouse gas emissions and foster global initiatives towards mitigating climate change. This study examined the co-production of xylitol and ethanol from xylose and glucose-rich hydrolysates of corn cob (CC), sugarcane bagasse (SCB), and rice straw (RS) without prior detoxification, using C. magnoliae (C. mag), C. tropicalis (C. trop), and C. guilliermondii (C. guil). A score ranking system based on weighted yields and productivity assessed the best raw material and yeast strain combination. The study revealed that C. mag cultivated on RS hemicellulosic and CC cellulosic media exhibited statistically significant (p ≤ 0.05) superiority in xylitol (272 ± 5) and ethanol 273 ± 3, production. The single-phase emulsion system using frozen-thawed whole cells of CC—C. mag, CC—C. trop, and RS—C. guil was utilized for phenylacetylcarbinol (PAC) biotransformation. Although similar PAC concentration within 14.4–14.7 mM was obtained, the statistically significant higher (p ≤ 0.05) volumetric pyruvate decarboxylase (PDC) activity from C. mag at 360 min was observed by 28.3 ± 1.51%. Consequently, further utilization of CC—C. mag in a two-phase emulsion system (Pi buffer: vegetable oil (Vg. oil) and Pi buffer: deep eutectic solvents (DES)) revealed that Pi buffer: DES medium preserved volumetric PDC activity (54.0 ± 1.2%) statistically significant higher (p ≤ 0.05) than the Pi buffer: Vg. oil system (34.3 ± 1.3%), with no statistically significant difference (p > 0.05) in [PAC]. These findings outlined the sustainable pioneering approach for the co-production of chemicals and reusing the residual yeast cells for PAC biotransformation in the Pi buffer: DES system.

A Matching Policy to Address ESG and Non-ESG Risks Impacted by a Relocation Policy in China’s Chemical Industry

China’s chemical industry has faced severe environmental, social, and governance (ESG) issues, such as high safety and environmental accidents and risks. To address these issues and promote industrial upgrading, China’s central government has issued a national relocation and improvement policy targeting its chemical industry. However, its countrywide policy implementation may also lead to other ESG risks during the relocation of chemical enterprises, namely industrial transfer. The typical ESG risks that appear to occur in developed eastern region provinces include a one-size-fits-all solution and unemployment, while less developed central and western region provinces may encounter pollution transfer, carbon leakage, environmental injustice, and health disparities. These ESG risks might overlap with other economic and financial (non-ESG) risks, like stranded assets, industry hollowing-out, and debt sustainability issue. These ESG and non-ESG risks could result from potential mismatches between chemical enterprises and chemical parks, categorized as mismatching errors explained by social-ecological systems, behavioral economics, and information economics. To better manage these risks, we propose an ESG matching policy comprising a national standardized ESG scoring and ranking system, a deferred acceptance mechanism, and a score announcement instrument. Such a policy innovation aims at achieving fair and efficient chemical enterprise–chemical park pairs, which would help manage both ESG and non-ESG risks and provide a just transition toolkit for China and other developing countries.

A Leaf Chlorophyll Content Estimation Method for Populus deltoides (Populus deltoides Marshall) Using Ensembled Feature Selection Framework and Unmanned Aerial Vehicle Hyperspectral Data

Leaf chlorophyll content (LCC) is a key indicator in representing the photosynthetic capacity of Populus deltoides (Populus deltoides Marshall). Unmanned aerial vehicle (UAV) hyperspectral imagery provides an effective approach for LCC estimation, but the issue of band redundancy significantly impacts model accuracy and computational efficiency. Commonly used single feature selection algorithms not only fail to balance computational efficiency with optimal set search but also struggle to combine different regression algorithms under dynamic set conditions. This study proposes an ensemble feature selection framework to enhance LCC estimation accuracy using UAV hyperspectral data. Firstly, the embedded algorithm was improved by introducing the SHapley Additive exPlanations (SHAP) algorithm into the ranking system. A dynamic ranking strategy was then employed to remove bands in steps of 10, with LCC models developed at each step to identify the initial band subset based on estimation accuracy. Finally, the wrapper algorithm was applied using the initial band subset to search for the optimal band subset and develop the corresponding model. Three regression algorithms including gradient boosting regression trees (GBRT), support vector regression (SVR), and gaussian process regression (GPR) were combined with this framework for LCC estimation. The results indicated that the GBRT-Optimal model developed using 28 bands achieved the best performance with R2 of 0.848, RMSE of 1.454 μg/cm2 and MAE of 1.121 μg/cm2. Compared with a model performance that used all bands as inputs, this optimal model reduced the RMSE value by 24.37%. In addition to estimating biophysical and biochemical parameters, this method is also applicable to other hyperspectral imaging tasks.

Comparative investigation of nanomaterial-enhanced asphalt binders in the UAE: a multifaceted study

ABSTRACT This study explores the impact of incorporating six distinct nanomaterials into asphalt binders to determine their effectiveness in resisting permanent deformation, fatigue and thermal cracking. Additionally, the study aimed to establish the Optimum Nano Content (ONC) for each nanomaterial to achieve the best performance against these distresses. The key findings revealed that asphalt binders with 2% Carbon Nanotubes (CNT) or Nano CuO (NCO) demonstrated the best rheological properties, partially in enhancing Elastic Recovery (ER) and rutting resistance, making them ideal for use in hot climate regions. In terms of fatigue performance, all nanomodified asphalt binders, except 2% NAT, exhibited higher fatigue life (Nf) than the control, with the NCO-nanomodified asphalt binder exhibiting the highest Nf, achieving values six to seven times greater than the control. Most nanomaterials showed no noticeable improvement in low-temperature performance, where the best performance was observed for 2% CNT and 6% Nano Iron Trioxide (NIT). For rutting resistance, the ONC for most nanomaterials was approximately 2%, whereas the ONC for fatigue resistance was typically 6%. A proposed ranking system revealed that sixteen of the nanomodified asphalt binders outperformed the control, with the 2% CNT providing the best-balanced performance, while 2% NAT was the least effective.

Designing and testing a sustainability soft regulation system: rating and ranking the wild animal welfare practices of tourism distribution channels

ABSTRACT The lack of standards pertaining to wild animal welfare practices in tourism creates an opportunity to introduce soft regulations to improve public accountability and foster positive change. We developed a rating and ranking system to embed the ideologies of a non-governmental organisation to improve wild animal welfare practices, acting as institutional entrepreneurs to gain pragmatic legitimacy within tourism distribution channels. The new system aims to create change in three ways: (i) informing, (ii) ordering, (iii) surveyance and control of wild animal welfare. We candidly report on the methodological choices behind the system’s design and implementation. We evaluate tourism distribution channels on four aspects, their: (i) policy and commitment statements, (ii) target setting and performance measurement, (iii) industry engagement and (iv) consumer awareness initiatives. An analysis of data from 12 international companies in 2020 and 2022 demonstrates how the system allows for shallow engagement in wild animal welfare practices, yet also offers the potential for significant improvements. We reflect on three methodological challenges: (i) quantification and commensuration during system design, (ii) the availability and credibility of data sources and (iii) the transparency of results.

Assembling the Pediatric Emergency Medicine Social Care Toolkit: A Modified Delphi Study

BackgroundThe pediatric emergency department is a high-value site for screening and resource referral for health-related social needs. However, best practices for this unique environment remain unclear. This study’s objective was to introduce a consensus-based social care training toolkit for the pediatric emergency medicine (PEM) setting. MethodsWe conducted a modified Delphi study to establish consensus on social care practice and develop a user-friendly toolkit. Initially, five priority areas (sections) were identified. Participants reviewed literature and shared their expertise to draft preliminary sections of the toolkit. Two rounds of the modified Delphi process were conducted, involving a ranking system, significant qualitative feedback, and a final approval stage, resulting in the finalized toolkit. ResultsSeventeen participants were included in the Delphi process, including pediatric and general EM faculty and trainees, as well as a social worker and public health professor. Forty-two content items were ranked in the first Delphi round. Based on a combination of score cut-off and extensiveness of qualitative comments, items were either minorly edited and kept (29%) or sent back to their section for review (71%). The second Delphi round integrated further suggested edits, and all participants in this final round approved the publicly available version of the toolkit. ConclusionBy utilizing diverse sources of information and a consensus-driven process of the modified Delphi, we generated best practice recommendations for the design, implementation, and training of social care programs in the PEM setting.

How to rank schools of public health? The PHAR project

Abstract Background Since the shattering and abrupt withdrawal of several Ivy League universities from ranking systems in 2022, the debate on rankings has been raging in the academic world and beyond. Despite this, rankings have undeniable advantages and continue to be used on a daily basis by a variety of stakeholders. As a previous work has demonstrated that there is no ranking specifically designed for schools of public health, the aim of this project was to create one. Methods To create the Public Health Academic Ranking (PHAR), the InCites Benchmarking and Analytics™ software and the Web Of Science™ Core Collection database were employed. Bibliometric data on 26 schools of public health, from each continent, were collected between August and September 2022. Eleven research indicators and scores, covering four criteria (productivity, quality, accessibility for readers, international collaboration), for the period 2017-2021, were used. For some schools whose affiliation was not mentioned directly in the software, a specific methodology was designed and tested, with unique research queries applied to the database. Results The five top schools of the PHAR were: the London School of Hygiene and Tropical Medicine, the Public Health Foundation of India (PHFI), the Harvard T.H. Chan School of Public Health, the Swiss School of Public Health (SSPH+), and the Johns Hopkins Bloomberg School of Public Health. Conclusions The PHAR provides an international bibliometric ranking of schools of public health. As this is a pilot project, the results should be taken with caution and future improvements should be developed. Key messages • The PHAR is the first university ranking system specifically designed for schools of public health and focuses on the research field of this discipline. • The PHAR makes it possible to rank schools of public health with an unusual structure (such as the PHFI and the SSPH+), which are generally overlooked by traditional rankings.

Relativity, Rank, and the US News Health's Cardiology, Heart, and Vascular Surgery Best Hospitals.

Virtually anything can be ranked; the US News and World Report (USNWR or US News) ranks the top 50 hospitals specializing in cardiology, heart, and vascular surgery. Here the authors propose validating the effectiveness of rankings by comparing differences among the USNWR metrics across the top 50 hospitals. The ranking system for the top 50 hospitals specializing in cardiology, heart, and vascular surgery was derived from 16 variant scores. Each hospital's scores were collected from the USNWR. Hospitals were categorized into quintiles consisting of 10 institutions (1-10, 11-20, etc). An analysis of variance/χ2 comprehensive statistical analysis was run alongside a Wilcoxon/Kruskal-Wallis test to compare statistical outcomes. A significant threshold was deemed to be P < 0.05. Significant differences were noted between quintiles for advanced technologies (P = 0.05), US News specialty score (P < 0.001), number of patient referrals (P = 0.004), and expert opinion (P < 0.001). Non-statistically significant differences were found among patient experience, public transparency, Society of Thoracic Surgery transparency, American College of Cardiology transparency, recognition as a magnet hospital, and nursing staffing. Interestingly, a large variance was noted in the average number of referrals between the first quintile (13,371) and the last (6690). Expert opinion plays a critical role in the reputation of the USNWR's top 10 hospitals in cardiology, heart, and vascular surgery. Although many have argued about the merits of USNWR hospital rankings, taken together, rankings fill a strong customer demand and are sticky.

Crowdsourcing the Mitigation of disinformation and misinformation: The case of spontaneous community-based moderation on Reddit

Community-based content moderation, an approach that utilises user-generated knowledge to shape the ranking and display of online content, is recognised as a potential tool in combating disinformation and misinformation. This study examines this phenomenon on Reddit, which employs a platform-wide content ranking system based on user upvotes and downvotes. By empowering users to influence content visibility, Reddit's system serves as a naturally occurring community moderation mechanism, providing an opportunity to analyse how users engage with this system. Focusing on discussions related to climate change, we observe that in this domain, low-credibility content is spontaneously moderated by Reddit users, although the magnitude of this effect varies across Subreddits. We also identify temporal fluctuations in content removal rates, indicating dynamic and context-dependent patterns influenced by platform policies and socio-political factors. These findings highlight the potential of community-based moderation in mitigating online false information, offering valuable insights for the development of robust social media moderation frameworks.

Multi-omics PGT: re-evaluation of euploid blastocysts for implantation potential based on RNA sequencing.

In addition to chromosomal euploidy, can the transcriptome of blastocysts be used as a novel predictor of embryo implantation potential? This retrospective analysis showed that based on differentially expressed genes (DEGs) between euploid blastocysts which resulted and did not result in a clinical pregnancy, machine learning models could help improve implantation rates by blastocyst optimization. Embryo implantation is a multifaceted process, with implantation loss and pregnancy failure related not only to blastocyst euploidy but also to the intricate dialog between blastocyst and endometrium. Although in vitro studies have revealed the characteristics of trophectoderm (TE) differentiation in implanted blastocysts and the function of TE placentation at the implantation site, the precise molecular mechanisms of embryo implantation and their clinical application remain to be fully elucidated. This study involved 102 patients who underwent 111 cycles for preimplantation genetic testing for aneuploidies (PGT-A) between March 2022 and July 2023. The study included 412 blastocysts biopsied at Day 5 [D5] or Day 6 [D6] for patients who underwent PGT-A. The biopsy lysates were split and subjected to DNA and RNA sequencing (DNA- and RNA-seq). One part was used for PGT-A to detect DNA copy number variations, whereas the other part was assessed simultaneously by RNA-seq to determine the transcriptome characteristics. To validate the reliability and accuracy of RNA-seq obtained from this strategy, we initially analyzed the transcriptome of blastocysts with chromosomal aneuploidies. Subsequently, we compared the transcriptomic features of blastocysts with different rates of formation (D5 vs D6) and investigated the network of interactions between key blastulation genes and the receptive endometrium. Then to evaluate the implantation potential of euploid blastocysts, we identified DEGs between euploid blastocysts that resulted in clinical pregnancy (defined as the presence of a gestational sac detected by ultrasound after 5 weeks) and those that did not. These DEGs were then employed to construct a predictive model for optimizing blastocyst selection. The successful detection rate of PGT-A was remarkably high at 99.8%. The RNA data may infer aneuploidy for both trisomy and monosomy. Between the euploid blastocysts that formed on D5 and D6, 187 DEGs were predominantly involved in cell differentiation for embryonic placenta development, the PPAR signaling pathway, and the Notch signaling pathway. These D5/D6 DEGs also exhibited a functional dialog with the receptive phase endometrium-specific genes through protein-protein interaction networks, indicating that the embryo undergoes further differentiation for post-implantation development. Furthermore, a modeling strategy using 280 DEGs between blastocysts leading to successful clinical pregnancies or failing to produce clinical pregnancies was implemented to refine the euploid embryo optimization, achieving areas under the curves of 0.88, 0.71, and 0.84 for the random forest (RF), support vector machine, and linear discriminant analysis models, respectively. Finally, a retrospective analysis of 83 transferred euploid blastocysts using the RF model identified three types of euploid embryos with a decreasing trend in implantation potential. Notably, the implantation rate of the good group was significantly higher than that of the moderate group (88.6% vs 50.0% P = 0.001) and that of the moderate group was higher than that of the poor group (50.0% vs 20.8%, P = 0.035). The sample size was insufficient; thus, a prospective study is needed to verify the clinical effectiveness of the above model. Because we did not analyze blastocysts that led only to biochemical pregnancies but failed clinical pregnancies separately, our classification system still must be modified to screen these embryos. Transcriptomic analysis of blastocysts offers a novel approach for predicting embryo implantation potential, which can be utilized to optimize clinical embryo selection. The ranking system may be effective in reducing the times and costs involved in achieving a clinical pregnancy. This study was funded by the "Pioneer" and "Leading Goose" R&D Program of Zhejiang (No. 2023C03034), the National Natural Science Foundation of China (82101709), and the National Key Research and Development Program for Young Scientists of China (No. 2022YFC2702300). The authors state no competing interests. N/A.

An Attempt to Reform the Civil Rank System in the Russian Empire in 1883–1885

Based on new data from unpublished documents of the Russian State Historical Archive (RSHA), this study examines the activities of the Special Secret Meeting, which developed a draft of a new Civil Service Statute from 1883 to 1885. This document proposed fundamental reforms to the Russian system of ranks, including the complete abolition of ranks and their replacement with a hierarchy of positions. However, due to disagreements between ministries, the project was not approved by the State Council. The study of interdepartmental and intradepartmental documents from higher and central state institutions, using event analysis, chronological, and retrospective research methods, revealed the institutions' attitudes towards the draft statute and identified the reasons for their refusal to adopt it. The findings of this research broaden our understanding of the reasons behind the failures of attempts to reform the civil service repeatedly made in the Russian Empire throughout the 19th and early 20th centuries. The relevance of the research topic lies in the traditional interest in the historical experience of the functioning of the bureaucratic apparatus of the Russian Empire in the 19th and early 20th centuries, in the context of increased interest from various researchers in the activities of the modern Russian state mechanism.

Beyond the Metrics: Call for a Holistic Approach for Evaluating Hospitality and Tourism Journals

ABSTRACT Journal ranking serves as an important reference for research individuals and institutes in various academic activities such as promotion and position application. Currently, there are two major approaches in evaluating journal rankings, namely quantitative and qualitative approaches. However, each approach has pros and cons. In addition, two typical issues of adopting metrics-related journal ranking systems are identified, which are self-citation and incomparability among different areas. The purpose of this paper is not to propose an advanced evaluation method. Instead, this study advocates that researchers should prioritize conducting high-quality studies and look beyond the metrics.

Effects of Postmanufacture Conditioning on the Mechanical and Hygroscopic Properties of Extrusion Printed Wood–Sodium Silicate Composites

Abstract Additive manufacturing of wood–sodium silicate composites could aid in mitigating the carbon footprint of the building and construction industry. However, the effect of postmanufacture conditioning on the mechanical and physical properties of additively manufactured wood–sodium silicate composites is not well understood. This study investigated eight different postmanufacture drying processes, including: ambient indoor and outdoor conditions, oven-drying at two different temperatures, microwave drying, alcohol-induced dehydration using ethanol and denatured alcohol, and desiccant drying. Each postmanufacture conditioning treatment was assessed in terms of total moisture extraction and moisture extraction rate as well as the flexural strength, flexural stiffness, and hardness of the wood–sodium silicate samples after drying. In addition, the water absorption and volumetric swelling properties of the additively manufactured wood–sodium silicate samples were assessed via water submersion tests. The postmanufacture conditioning treatments were found to significantly affect the mechanical and physical properties of the samples. A universal ranking system was established based on cumulative rankings of each evaluated characteristic. Samples dried in ambient outdoor conditions achieved the best overall ranking and had the smallest carbon footprint. However, ovendried samples had the best flexural properties. Future studies investigating hybrid approaches in which composites are sequentially subjected to different drying methods will likely provide the most desirable mechanical and physical properties of wood–sodium silicate composites.

Performance of natural asphalt as a paving material: A laboratory and field evaluation

The ever-growing need to build roads to meet the necessary transportation demands is challenging, especially for developing countries. Low-volume roads (LVRs) are usually the backbone of catalyzing economic growth in these countries. With impediments surrounding Petroleum bitumen (price fluctuations) and environmental concerns, scientists are putting their effort into finding an alternative. The presented research is an attempt to check if Natural asphalt can be used as a full or partial replacement of the Petroleum bitumen. To the best of the authors' knowledge, only limited studies have focused on characterizing and understanding the engineering properties of Natural asphalt. The available techniques do not provide reliable information to the road authorities and hence they are discouraged from using it in practice. Particularly for countries, where the Natural asphalt source is available, the overall dependence on importing the Bitumen could be substantially reduced. Empirical and experience-based design criteria may not be sufficient as the standards were never developed for such materials, hence, a scientific approach is required before bringing it into practice. In this research, Natural asphalt sourced from different locations in Nigeria was assessed. Before performing the mixture level tests using Marshall and Cantabro design methods, the rheological and fatigue properties of the extracted Natural bitumen were examined in the laboratory. In the design of the experiment, various percentages of Natural asphalt were added between 0 % and 20 % by total mix weight; implying that the remaining required fraction of binder was fulfilled by the addition of petroleum bitumen. By using a ranking system (supported by statistics), an optimal design of mixture was obtained which was used in the field (exposed to normal traffic) at 30 different sections. Overall, results showed a good correlation between laboratory and field performance as compared to the petroleum-based mixture which was used as a reference mixture

New Assessment Model of Financing Treatment of Patients with Complete Tooth Loss

According to the World Health Organization, the global prevalence of complete tooth loss is estimated to be 7% among individuals aged 20 years and older, while for those aged 60 and over, this rate significantly increases to 23%. This study is relevant due to the psychological trauma, social challenges, and functional limitations caused by tooth loss, as well as the uneven availability of dental care worldwide. The goal of this research is to develop and implement a new model to assess the socioeconomic feasibility of investing in digital technologies for diagnosing and treating patients with complete tooth loss using removable polymer prostheses produced through additive 3D printing. The study employs scenario analysis, the clustered rankings coordination method, statistical methods, expert opinion assessment using Kendall’s coefficient of rank concordance, system analysis and design, questionnaires, sociometry, and functional modeling. The practical significance of this research lies in providing a quantitative assessment of economic opportunities for effectively using RPDs in three groups: RPDs without additional fixation means; those with special adhesive agents for improved fixation; and implant-supported prosthetics with conditionally removable dentures similar to RPDs. The scientific novelty of this study is the development of a new evaluation model that justifies the choice of prosthetic treatment technology for patients with complete tooth loss, enabling the most rational use of resources. Doi: 10.28991/ESJ-2024-08-05-014 Full Text: PDF

Alumni Rating Index and Monitoring Dashboard Technology to Improve University’s Performance and Service Quality

Limited number of university ranking systems have considered the perspectives of alumni or individuals who have availed themselves of the educational programs or services provided by the institutions. In Malaysia, there is a lack of comprehensive rankings or assessments that primarily focus on assessing university performance through the lens of student experiences. In the absence of authentic user experiences, prospective students and other relevant parties commonly rely on conventional academic rankings such as the QS or THE to ascertain the quality of a university. The primary aims of this research endeavour encompass the identification of pivotal variables for the evaluation of higher learning institution’s performance, the creation of an alumni rating index, and the establishment of a performance monitoring tool utilizing dashboard technology. The goals are to enhance performance and service quality of institutions of higher education. The present study utilizes a quantitative research approach and centres its investigation on many cohorts of graduates originating from a prominent Malaysian university. A rigorous cluster sampling procedure was implemented. The assessment of alumni rating is conducted across twelve dimensions, with each component being evaluated using appropriate variables that enable the calculation of the desired index and facilitate the execution of intricate studies. The analytics that were performed and the alumni rating index that was calculated were subsequently shared with stakeholders through the use of an analytical dashboard. The dashboard was developed on user experience (UX) design principles. The evaluation of the produced dashboard is thereafter conducted by a group of stakeholders who have direct involvement in enhancing alumni engagement. The findings suggest that the university attained elevated ratings in the domains of social involvement, educational resources, and financial value. However, the scores for financial aid, student development, and student well-being were significantly lower. Despite the provision of various financial support, the respondents hold the belief that these forms of assistance are inadequate. The paper concludes by demonstrating the implementation of an alumni rating dashboard. The research is expected to facilitate the development of a localise university rankings and ratings, as well as informed policy-making efforts at the ministry level.

The Influence of Open Access on Institutional Scientific Research Output in MENA Countries: A Comparative Analysis

The release of scientific research has substantial consequences for both the research and the institution in which it was carried out. The selection of publishing methods for scientific articles, such as journal type, quartile, indexed databases, and publishing models, plays a crucial role. Various publishing models exist, including platinum, gold, and green open access. In this study, we examine the implications of open access publishing on reputable journals for Middle East and North Africa (MENA) countries. Additionally, we explore the correlation between open access publishing and MENA country classification according to the World Bank. Bibliometric data from Scopus database are used, focusing on researchers from each MENA country. The World Bank determines if a country is low, middle, or high income. The total number of published documents and open access publications are also considered. The study investigates how open access publishing affects university and research center rankings within MENA countries, utilizing Scopus database information. This encompasses the number of open access documents indexed in Scopus and citations from MENA countries. Multiple ranking systems, such as 2024-QS World University Ranking (QSWUR) and 2023-Scimago Institutions Ranking, are assessed. Findings reveal that open access articles contribute to 72% to 95% of citations received by institutions in MENA countries, highlighting the influence of this publishing model. Additionally, the percentage of open access publishing ranges from 32% in low-income countries to 56% in other MENA countries. The study also demonstrates that MENA countries with higher numbers of open access publications are more likely to have institutions ranked in prestigious systems such as QS World University Ranking and Scimago Institutions. It is discovered that the average percentage of citations received from open access publications indexed in Scopus for MENA countries is 82%, indicating the significant impact of open access publishing on academic citations in these nations. We believe that the procedures done in this study for MENA countries can be generalized further for global countries.

Selection of Marketing Staff Using Simple Additive Weight and VIKOR Algorithm

In today’s rapidly evolving technological landscape, decision-making processes within organizations are increasingly relying on advanced computational methods to enhance efficiency and accuracy. This is particularly relevant in human resource management, where selecting suitable candidates for key positions is critical. Traditional methods of staff recruitment often rely on subjective assessments, which may lead to biases and inconsistencies. To address these challenges, this study proposes the use of the Simple Additive Weighting (SAW) and VIKOR (Vise Kriterijumska Optimizacija I Kompromisno Resenje) algorithms as multi-criteria decision-making tools for selecting marketing staff. The SAW method offers a straightforward approach by assigning weighted scores to various criteria. In contrast, the VIKOR method provides a ranking system that considers ideal and compromise solutions for candidate selection. Integrating these two algorithms makes the selection process more objective and data-driven, reducing the risk of human error and improving overall decision quality. This paper outlines implementing the combined SAW-VIKOR model in the marketing staff recruitment process, highlighting its potential to optimize candidate evaluation and selection. The results demonstrate that utilizing these algorithms enhances the decision-making process, leading to better alignment of selected staff with organizational goals. This approach is valuable for organizations looking to leverage technology in their recruitment strategies.

Mapping the Environmental Impact Assessment Landscape in the Fashion and Textile Industries: Critical Gaps and Challenges

The environmental impact of the fashion and textile industry (FTI) is measured and communicated through several interrelated methods, tools and platforms. In this paper, scholarly and grey literature have informed the mapping of the sector’s environmental impact assessment (EIA) landscape to identify key gaps and challenges in effectively quantifying and communicating environmental product performance. These preliminary insights informed the design of multiple focus group discussions where the on-the-ground challenges of EIA implementation were discussed with 85 FTI stakeholders, including industry professionals, academics, non-governmental organisations and local government. Key findings highlight the need for further refinement and harmonisation of assessment methodologies and approaches such as Life Cycle Analysis (LCA) to consider a wider range of impact categories to increase the comparability of results. Similarly, the communication asymmetries linked to a profusion of eco-labelling and ranking systems necessitates the development of better tools to communicate the environmental performance for the sector. Furthermore, as all EIA methods require the movement of data between various actors, there is a need for improvement and innovation in data-gathering and management systems to ensure greater quality and reliability.

Automated Mixture Analysis via Structural Evaluation.

The determination of chemical mixture components is vital to a multitude of scientific fields. Oftentimes spectroscopic methods are employed to decipher the composition of these mixtures. However, the sheer density of spectral features present in spectroscopic databases can make unambiguous assignment to individual species challenging. Yet, components of a mixture are commonly chemically related due to environmental processes or shared precursor molecules. Therefore, analysis of the chemical relevance of a molecule is important when determining which species are present in a mixture. In this paper, we combine machine-learning molecular embedding methods with a graph-based ranking system to determine the likelihood of a molecule being present in a mixture based on the other known species and/or chemical priors. By incorporating this metric in a rotational spectroscopy mixture analysis algorithm, we demonstrate that the mixture components can be identified with extremely high accuracy (≥97%) in an efficient manner.