Web Metrics Research Articles

Mimicking nature to design eco-industrial parks: Exploring the influence of connectance on industrial network optimization

The accelerating exhaustion of non-renewable natural resources and the urgent need for sustainable practices have prompted the exploration of alternative methodologies in production processes. Food webs illustrate the predator-prey relationships between species in natural ecosystems, and their properties can offer valuable insights for improving economic and industrial systems, potentially leading to reduced emissions, costs, and improved process efficiency. While some food web metrics have been used for various purposes like establishing industry-nature analogies, comparing industrial networks to natural ecosystems, and configuring industrial networks, investigation of the role of the connectance metric in designing industrial networks, particularly in optimizing theoretical EIPs, is still scarce. This study investigates the role of connectance in optimizing industrial networks within eco-industrial parks, specifically focusing on the construction sector. A scenario analysis for seven conceptual eco-industrial parks serves as an illustration of how this approach can be used. The food web metric values of these eco-industrial parks are compared among themselves and against biological averages. The results reveal that maximizing connectance in eco-industrial parks is not an effective strategy for network optimization, as indicated by previous literature which points to potential instability. Instead, configurations that closely resemble natural food web metrics may provide better sustainability and efficiency if the limitations of the study are addressed, and the validity of this assumption is confirmed through quantitative tests. This study contributes theoretically by developing a guide for designing eco-industrial parks and introduces two key methodologies: based on particular criteria, a method for identifying and selecting potential future industrial symbiosis implementations targeted a sector and an innovative approach for sector-specific park design based on natural objectives and constraints, serving as a valuable decision-making tool for practitioners and policymakers.

Web metrics and key performance indices of the Villagemath instructional content repository

This study presents the outcomes of common web metrics and key performance indices of VillageMath, an online culture-based Instructional Content Repository for STEM learners and teachers. The study adopts a developmental research design. The developed intervention is accessible at (https://villagemath.net). Data collection on common web metrics and key performance indices (KPIs) was handled using standard web performance assessment tools such as WP Statistics, Pingdom Tools, Google PageSpeed Insights, GTmetrix, and WebPage Test. The metric platforms were chosen based on their industry standing, ease of use, and the wide range of KPIs that they measure. The metrics provide a median run performance result accounting for Time to First Byte (when did the content start downloading?), Start Render (when did pixels start to appear?), Speed Index (how soon did the page look usable?), Cumulative Layout Shift (how much did the design shift while loading?), Page Weight (how many bytes downloaded?), speed (from 7 different locations on five continents strategically placed around the globe), total page size, and suggestions for improvement. The data collected was analysed using descriptive statistics such as tables, charts, and averages. The analysis of results obtained from the web performance assessment tools indicated that the web-based VillageMath Repository appeals to a wide range of highly engaged users. Key performance indicators such as speed index, page size, and last painted hero for the VillageMath Instructional Content Repository were above industry averages and affirmed that the platform is robust, elegantly designed, and fast.

Lipid extraction alters amino acid composition and bulk, but not amino acid, carbon and nitrogen isotope values.

Concerns exist over observed shifts in value and variance of nitrogen isotopes following physicochemical extraction of lipids from organic matter. The mechanisms behind these apparent changes in bulk tissue δ15N values are not fully understood yet have major implications for analytical costs and integrity of data interpretations. Changes in proximate analysis, amino acid composition, C:N ratios, bulk tissue and amino acid δ13C and δ15N values, and resulting isotope-based food web metrics were compared between lipid-intact and lipid-extracted muscle tissue of fishes spanning <1% to >20% muscle fat content to identify mechanisms of nitrogen isotope fractionation associated with physicochemical lipid extraction. Bulk δ13C and δ15N values increased and %N, C:N ratios and crude protein content decreased following lipid extraction. Resulting bulk isotope niche spacing and overlap varied significantly between lipid-intact and lipid-extracted tissues. While amino acid composition significantly changed during lipid extraction, particularly for lipid-associated amino acids (e.g., Glu, Lys, Ser), individual amino acid δ13C and δ15N values, and their associated compound-specific isotope analysis of amino acids (CSIA-AA)-based food web metrics, did not. Physicochemical lipid extraction caused significant tissue composition changes (e.g., leaching of amino acids and 15N-deplete nitrogenous waste) that affected δ13C and δ15N values and tissue %C and %N beyond simply removing lipids. However, lipid extraction did not alter individual amino acid δ13C or δ15N values or their associated CSIA-AA-based food web metrics.

Long-term recovery of benthic food webs after stream restoration

The assessment of restoration success often neglects trophic interactions within food webs, focusing instead on biodiversity and community structure. Here, we analysed the long-term recovery of food web structure based on stable isotopes (δ13C and δ15N) of benthic invertebrates and quantified responses of food web metrics to time since restoration. The samples derived from twelve restored sites with different restoration ages, sampled annually from 2012 to 2021, and covering an investigation period of up to 28 years after restoration for the whole catchment. Temporal developments of the restored sites were compared to the development of two near-natural sites. The restoration measures consisted of the cessation of sewage inflow and morphological restoration of the channels. As a clear and consistent result over almost all sites, trophic similarity (proportion of co-existing species occupying similar trophic niches) increased with time since restoration, and reached values of near-natural sites, suggesting an increase in the stability and resilience of the food webs. Surprisingly, resource diversity decreased at most restored sites within 10 years after restoration, probably due to the removal of wastewater-derived resources, and a shift towards leaf litter as the dominant resource following the regrowth of the riparian vegetation. Food chain length showed no consistent pattern over time at the different sites both increasing and decreasing with time since restoration. Overall, restoration had clear effects on the food web structure of stream ecosystems. While some effects such as the increase in trophic similarity were consistent at almost all sites, others such as response of the food chain length were context dependent. The study demonstrates the potential of utilizing food web metrics, particularly trophic similarity, in restoration research to achieve a more holistic understanding of ecosystem recovery.

Digital reputation indicator: A webometric approach for a global ranking of digital media

In this article we present the Digital Reputation Indicator (DRI), an innovative methodological tool that allows evaluating and comparing the reputation of digital news media on a global scale. In use since January 2023 by SCImago Media Rankings ( scimagomedia.com ), DRI is a composite assessment and measurement instrument that weighs web metrics originating from trusted, stable, and globally accessible sources. DRI provides a resource for the qualitative comparison of digital media according to a webometric model based on its level of citation by other websites ( citationflow ), the quality of the sites that link to the media (trustflow) and the level of authority scores associated with their domain (domain rating and authority score). This article explores the reliability of this webometric approach, which overcomes the limitations of the two media measurement paradigms used up to now: the most traditional, based on audience measurement, and the most recent, oriented towards popularity in social networks. In this article we present and test the consistency of the DRI as a resource for the building of a global ranking of digital media, an instrument that we consider to be of interest to both the academic and professional communities.

The Mediating Influence of Leadership Style within the Nexus of Organizational Agility and Performance Outcomes in Public Universities in Kenya

Public universities in Kenya have been operating in an environment that has been changing over the past few years, and the numerous uncertainties have made survival difficulty. Ineffectiveness and inefficiencies in the public universities, low global ranking of public universities, low research output and the weak university-industry partnerships due to the closed system nature of public universities and other internal and external factors have continued to affect university performance. The application of the concept of organizational agility may be viewed as a panacea to addressing the above pertinent issues and bring the public universities to a higher level of performance in uncertain changing environment. Therefore, the goal of this study is to examine the mediating influence of leadership style within the nexus of organizational agility and performance outcomes of public universities in Kenya. The research is anchored on Dynamic Capability theory, Resource based view theory and Learning organization theory. Semi-structured questionnaires were used to measure both quantitative and qualitative data, using descriptive and explanatory research methodologies for empirical analysis. Content analysis was used to analyze the qualitative data, and the results presented in accordance with patterns and themes. The target population was the 31 fully fledged public universities in Kenya out of which 10 were sampled systematically from best to worst ranked institution based on January 2023 web metrics global university ranking scale. The study targeted 220 respondents comprising of Deputy Vice Chancellors, Deans of schools and faculty, academic department heads and key senior staff in administration. Out of this, only 207 returned the questionnaire accounting for 94.1% success rate. Due to the characteristics of the respondents and the goal of the investigation, a proportionate random sample technique was employed to choose the respondents for the study. A drop-and-pick methodology was used to collect data by trained research assistants. The questionnaire was subjected to both validity and reliability tests by carrying out a pilot test on different group from the study group but with similar characteristics and use of SPSS version 27 to process the data. Using a multiple regression analysis approach, descriptive and inferential statistics were employed to analyze the data in accordance with the specific research objectives and hypotheses. Results from quantitative data analysis were presented using figures and tables while qualitative data was analyzed based on common themes and presented in narrative form. The findings of the study established that leadership style fully mediated effect on relationship between organizational agility and university performance outcomes. These findings were found useful in management of public universities in the face of uncertainties. Furthermore, these findings are expected to provide a framework for enhancing performance outcomes of public universities in the midst of adverse environmental circumstances.by forming appropriate policies and strategies through application of appropriate leadership styles.

SCImago Media Rankings (SMR): situation and evolution of the digital reputation of the media worldwide

In this paper, we present the results of the first global ranking that assesses the status and evolution of the media according to their digital reputation. We analyzed 4,541 general information digital newspapers, both legacy and native, published in 200 countries and in more than 80 languages. Methodologically, we applied a new Digital Reputation Indicator (DRI) as a composite evaluation and measurement tool, weighting web metrics from globally recognized, balanced, and validated sources such as Semrush, Ahrefs, and Majestic. This establishes the foundations of the SCImago Media Rankings (SMR) as a balanced watchdog resource for analysis of the digital transformation of the media and as an international catalog of journalistic websites, with a consensus-based and homologous classification and typification that can be applied to different countries. The main conclusion of the first three quarterly waves, carried out between September 2022 and March 2023, is that there is a direct relationship between the degree of socioeconomic and cultural development of the countries and the digital reputation achieved by their media outlets in the ranking. Additionally, the influence of language is notable as a determining factor in the positioning of the media in the ranking. The top positions are occupied by reference digital newspapers located in Western countries of the Northern Hemisphere, especially those in the English language.

Quantitative Research Approach and its Applications in Library and Information Science Research

This paper discusses the quantitative research approach and how it applies to Library and Information Science (LIS). Although many different research methodologies are used in the diverse subject of LIS to analyze data, the quantitative approach infrequently preferred. Quantitative research is most appropriate for phenomena stated in numbers since it requires numerical measurements and the analysis of variables to get results. The most common quantitative research techniques employed in LIS nowadays are survey studies, correlation research, descriptive research, and experimental research. To assess many facets of library activities and user satisfaction, the current study scientifically examines numerous quantitative research methods, including checklists, structured interviews, and questionnaires. Researchers can examine the effect factors of scholarly communications thanks to the study's insights into biblio metrics, sciento metrics, info metrics, web metrics, and altmetrics for research trends in metric studies. The study also highlighted the advantages, disadvantages, and limitations of quantitative research methodologies when researchers use this strategy.

Analysis of cost estimation using the web metrics and cost driver in the high performance of web developers

In recent years, many researchers and software industries have given significant attention to the estimation of software effort. Software effort estimation is a challenge that often appears in the project of making software. To address this issue, various software expansion cost estimations have been familiarized. A basic traditional method for cost estimation is the Constructive Cost Model II (COCOMO II Model), which generates huge gradations of substantiality. The proposed COCOMO II model employs cost drivers, measures and the streak of programmes to predict the energy and the growth period of a web rise. However, the model is still lacking in terms of accuracy in effort and development time estimation. In this study, we do investigate the influence of components and attributes to achieve new better accuracy improvement on the COCOMO II model. The NASA93 dataset is used to test the suggested methodology. The system has outperformed earlier investigations and arrangements capable of imperfect data input, and further advancements in the reliability of the estimated technique.

Who cares for the carers? carerhelp: development and evaluation of an online resource to support the wellbeing of those caring for family members at the end of their life

BackgroundMost people living with a terminal illness and approaching death will need the assistance of a non-professional carer such as a family member, friend, or neighbour to provide physical, emotional, and practical caring supports. A significant portion of these carers can feel overwhelmed, isolated and experience psychological and/or financial distress. Carers can have unmet information needs and information needs can change across the caring period.MethodsGuided by an Australian National Reference Group, this project undertook a multiphase set of activities to enable the development of an online carer resource. These activities included a literature review of key issues and considerations for family carers supporting someone with a terminal illness, a scoping scan of existing online resources, and interviews and focus groups with eighteen carers to understand their needs and context of caring. This information formed the basis for potential digital content. A web project team was established to create the information architecture and content pathways. User testing survey and usability assessment of the CarerHelp Website was undertaken to assess/optimise functionality prior to release. An evaluation process was also devised.ResultsThe literature review identified carer needs for practical and psychological support along with better education and strategies to improve communication. The scoping scan of available online resources suggested that while information available to carers is plentiful, much of that which is provided is general, disparately located, inadequately detailed, and disease specific. The eighteen carers who were interviewed highlighted the need for helpful information on: services, symptom management, relationships, preparation for death, managing the emotional and psychological burden that often accompanies caring, and support during bereavement. User testing and usability assessment of the prototype resource led to changes to enhance the user experience and effectiveness of navigation. It also highlighted a lack of awareness of existing resources and the needs of marketing and communication to address this problem.ConclusionsThe project led to the development of an open access online resource, CarerHelp (www.carerhelp.com.au), for use by carers and families caring for a person who has palliative care needs. The web metrics demonstrate substantial use of the resources.

Identifying the Key Hazards behind Website Drop-Offs by Solving a Survival Problem

Within the modern era, corporates are compelled to own an appealing and effective website to survive and thrive within the competitive global digital marketplace. Whilst there are several web metrics to focus on, a key focus area of web analytics is the level of drop-offs. The drop-off rate represents the proportion of visitors that prematurely drop-off a website. Whilst the exact reason behind the drop-off may only be assumed (could be due to the loss of Internet connectivity or dis-interest), this study attempted to identify the triggers behind website drop-offs through a survival problem. Each person entering the website, at a given instance, can view any number of web pages (such as home, contact us, about us, etc.). However, on the studied website, roughly one in five visitors have prematurely dropped-off. The study was conducted on an engineering corporate website with the data collected via the Google Analytics tracking tool. The aim was to determine the key hazards that contributed to the observed drop-off rate through the use of a cox proportional hazard model and a survival random forest model. On the studied website, based on empirical evidence, the online visitors were censored so that those who viewed three or more webpages within the visit were labelled as ‘survived’. Visitors who viewed two or less webpages before leaving the website were labelled as ‘did not survive’. Thereby, the ‘did not survive’ observations represented the visits that prematurely dropped off the website. Using the visitor’s physical and behavioral characteristics, as tracked by Google Analytics, the cox-proportional hazard and survival random forest models were employed to determine the hazards that influence survival. Visitor’s physical characteristics include the device used to access the website, geolocation at the time of the visit, number of previous visits, etc., whilst the behavioral characteristics include the landing page on website, level of engagement, whether entry into the website originated through an organic search or not. Whilst both models have identified similar features as being key hazards, the survival random forest model has been shown to out-perform on the non-linear features relative to the cox proportional hazard model and obtained a higher classification accuracy. During the validation process, the survival random forest model (63%) outperformed the cox model (58%) on classification accuracy. The features that were identified as hazardous indicated that some webpages needed further attention, the visitor’s level of engagement with the website (the degree of scrolling and clicks), the distance between a visitor’s location and the studied corporate’s location, the historic frequency of visiting the website, and if the website entry point was through an organic search. Whilst the study of drop-offs has been a commonly researched problem, this study details the investigation of key hazards through the use of survival models and compares the outcomes of a regression-based model to a machine learning survival model.

Simplification effect of lead soil contamination on the structure and function of a food web of plant-associated insects

Anthropogenic activities such as mining, industry, urban waste production, and the overuse of agricultural inputs may result in the contamination of the environment by heavy metals, which are toxic to organisms mainly due to their potential to accumulate in tissues. This contamination causes the simplification of aquatic and edaphic food webs, which show impaired structure and function. We investigated whether soil contamination with heavy metal at the permitted concentrations affects the structural or functional properties of a terrestrial food web of insects living in the aboveground parts of a plant. As study models we used lead (Pb) and kale-associated insects. Kale plants (Brassica oleracea var. acephala) were grown in soil experimentally contaminated with four lead nitrate concentrations: 0 (control), 144 (T1), 360 (T2), and 600 (T3) mg/kg of soil. The experiment was conducted in an open greenhouse for natural insect colonization. The insects were collected twice in the field using trap bags attached to the plant leaf and by direct removal. In general, we observed a simplification of the food web as the Pb concentrations increased, resulting in visually smaller food webs. The food web metrics decreased from the T2 treatment (the Pb limit for agricultural soils). Structurally, the Number of Species (whose values were highly positively correlated to the Number of Links and Link Density values) decreased with increasing contamination, while Connectance increased. Functionally, the Predator/Prey Ratio and Trophic Vulnerability and Generality became lower. This study shows that soil contamination by Pb can simplify insect food webs in the aboveground parts of plants, negatively affecting the structure and function of the webs, even at permitted concentrations.

The driving mechanism of soil organic carbon biodegradability in the black soil region of Northeast China

The biodegradability of soil organic carbon (BSOC), defined as soil mineralization C per unit of soil organic carbon (SOC), is considered to be an important indicator of SOC stability and is closely related to the global C cycle. However, the magnitude and driving mechanism of BSOC in farmland remain largely unexplored, especially at the regional scale. Here, we conducted regional scale sampling to investigate latitude distribution pattern of BSOC and the relative contributions of biotic (soil micro-food web) and abiotic (climate and soil) drivers to BSOC in the black soil region of Northeast China. Results showed that BSOC declined with increasing latitude, which indicates that as the latitude increases, SOC becomes more stable in the black soil region of Northeast China. Over a range of latitude from 43°N to 49°N, BSOC was negatively correlated with soil micro-food web metrics of diversity (indicated by species richness), biomass and connectance, and soil factors of soil pH and clay content (CC), while it was positively correlated with climate factors of mean annual temperature (MAT), mean annual precipitation (MAP) and soil factor of soil bulk density (SBD). Among those predictors, soil micro-food web metrics were the most direct factors contributing to the variations of BSOC, which exerted the largest total effect on BSOC (−0.809). Collectively, our results provide convincing evidence that soil micro-food web metrics play a direct vital role in determining the distribution pattern of BSOC over a range of latitudes in the black soil region of Northeast China. This highlights the necessity of considering the role of soil organisms in regulating C dynamics in prediction of SOC mineralization and retention in the terrestrial ecosystem.

Reach, acceptability and impact of an online parent healthy lifestyle intervention during the COVID-19 lockdown: A pilot study.

There is growing evidence that online parent-focused child healthy lifestyle interventions can improve healthy eating practices and food environments in the home. Greater understanding of whether and how parents engage with these online interventions is needed. This study evaluated the reach, acceptability and impacts of an online parent healthy lifestyle intervention. A pilot study was conducted in New South Wales during the COVID-19 pandemic when stay-at-home public health orders were in place (July-August 2021). A concurrent mixed methods design was adopted. Data collection measures were: an online participant survey at baseline, post-intervention and 3-month follow-up; two online post-intervention focus groups; and web metrics at post-intervention and 3-month follow-up. There were 181 intervention participants, primarily mothers with high education levels and living in advantaged areas: 43 (24%) completed surveys post-intervention; and of these, 35 (81%; 19% of participants) completed surveys at follow-up. Sixteen mothers participated in focus groups. Parents' knowledge, self efficacy, role modelling and behaviours improved, but there were no significant differences detected over time. Metrics and survey data indicated webinar recordings, particularly the topics of 'Fussy Eating' and 'Screen time and sleep', had the greatest engagement and most perceived them as useful (93% and 96%, respectively). An online healthy lifestyle intervention to support parents in providing opportunities for their children to engage in healthier lifestyle behaviours was appealing and acceptable to mothers and has the potential to improve families' healthy lifestyle behaviours. Enhancing intervention reach amongst fathers and priority populations, as well as incorporating design elements to enhance engagement will be important. SO WHAT?: An online healthy lifestyle intervention reached and engaged parents, despite being faced with additional parenting challenges arising from COVID-19 stay-at-home orders.

Composition and Food Web Structure of Aphid-Parasitoid Populations on Plum Orchards in Chile

By increasing plant diversity in agroecosystems, it has been proposed that one can enhance and stabilize ecosystem functioning by increasing natural enemies' diversity. Food web structure determines ecosystem functioning as species at different trophic levels are linked in interacting networks. We compared the food web structure and composition of the aphid- parasitoid and aphid-hyperparasitoid networks in two differentially managed plum orchards: plums with inter-rows of oats as a cover crop (OCC) and plums with inter-rows of spontaneous vegetation (SV). We hypothesized that food web composition and structure vary between OCC and SV, with network specialization being higher in OCC and a more complex food web composition in SV treatment. We found a more complex food web composition with a higher species richness in SV compared to OCC. Quantitative food web metrics differed significantly among treatments showing a higher generality, vulnerability, interaction evenness, and linkage density in SV, while OCC presented a higher degree of specialization. Our results suggest that plant diversification can greatly influence the food web structure and composition, with bottom-up effects induced by plant and aphid hosts that might benefit parasitoids and provide a better understanding of the activity, abundance, and interactions between aphids, parasitoids, and hyperparasitoids in plum orchards.

Food web structure and microenvironment affect Chagas disease vector infection and abundance in a rural landscape

AbstractVector‐borne pathogen transmission is shaped by multiple abiotic and biotic factors. Understanding the relative importance of these factors on vector abundance and infection is important for developing vector‐borne disease control strategies. The crown of the Attalea butyracea palm provides a natural arboreal mesocosm suitable for studying how food web relations and microclimate affect Chagas disease vectors of the genus Rhodnius, which feed on vertebrate blood and interact with many vertebrate and invertebrate species, vegetation, and detritus within the palm crown. We performed a cross‐sectional, observational study of A. butyracea crowns using a community ecology network approach to evaluate abiotic and biotic conditions associated with Rhodnius pallescens abundance and infection with Trypanosoma cruzi, the Chagas disease etiologic agent. We collected 1098 R. pallescens from 105 A. butyracea crowns in rural landscapes of Panama. In a palm subset (N = 49), we recorded microclimate and habitat conditions and counted vertebrate and invertebrate species in order to characterize palm crown food webs. We used food web metrics, namely Generality (average number of prey per predator) and Vulnerability (average number of predators per prey) to evaluate associations between palm community trophic structure, vector predators, vector blood meal species composition, vector abundance, and vector T. cruzi infection. Field data analyzed with generalized linear models showed that vector abundance and infection in a given palm crown were influenced by a combination of geographic location, land‐use type, palm crown animal community composition, and microhabitat conditions. Vector abundance was negatively associated with increased overall palm crown community diversity. However, vector abundance was positively associated with the invertebrate predator and mammal community. R. pallescens Vulnerability score, which measures predation pressure on the vector within the palm crown, was positively associated with vector abundance. Vector infection with T. cruzi was positively associated with mammal presence; vectors in palms with mammals were about 25 times more likely to be infected with T. cruzi compared with vectors in palms without mammals. Our findings suggest that a holistic study of food webs and environmental variables at the local scale can provide useful information for vector‐borne disease management across a wide habitat range.

E-Commerce Website Usability Analysis Using the Association Rule Mining and Machine Learning Algorithm

The overall effectiveness of a website as an e-commerce platform is influenced by how usable it is. This study aimed to find out if advanced web metrics, derived from Google Analytics software, could be used to evaluate the overall usability of e-commerce sites and identify potential usability issues. It is simple to gather web indicators, but processing and interpretation take time. This data is produced through several digital channels, including mobile. Big data has proven to be very helpful in a variety of online platforms, including social networking and e-commerce websites, etc. The sheer amount of data that needs to be processed and assessed to be useful is one of the main issues with e-commerce today as a result of the digital revolution. Additionally, on social media a crucial growth strategy for e-commerce is the usage of BDA capabilities as a guideline to boost sales and draw clients for suppliers. In this paper, we have used the KMP algorithm-based multivariate pruning method for web-based web index searching and different web analytics algorithm with machine learning classifiers to achieve patterns from transactional data gathered from e-commerce websites. Moreover, through the use of log-based transactional data, the research presented in this paper suggests a new machine learning-based evaluation method for evaluating the usability of e-commerce websites. To identify the underlying relationship between the overall usability of the eLearning system and its predictor factors, three machine learning techniques and multiple linear regressions are used to create prediction models. This strategy will lead the e-commerce industry to an economically profitable stage. This capability can assist a vendor in keeping track of customers and items they have viewed, as well as categorizing how customers use their e-commerce emporium so the vendor can cater to their specific needs. It has been proposed that machine learning models, by offering trustworthy prognoses, can aid in excellent usability. Such models might be incorporated into an online prognostic calculator or tool to help with treatment selection and possibly increase visibility. However, none of these models have been recommended for use in reusability because of concerns about the deployment of machine learning in e-commerce and technical issues. One problem with machine learning science that needs to be solved is explainability. For instance, let us say B is 10 and all the people in our population are even. The hash function’s behavior is not random since only buckets 0, 2, 4, 6, and 8 can be the value of h(x). However, if B = 11, we would find that 1/11th of the even integers is transmitted to each of the 11 buckets. The hash function would work well in this situation.

A novel research method to measure the usage of web-based information

This research method contributes to the literature by measuring commensurably ‘the usage of information for (or web traffic on) web-based research studies’. The introduced method deepens the understanding the functionality of online media by focusing on specific web metrics to make the usage of this type of media efficient for disclosure function. The inputs of new method are originally based on publicly available data, and it can be applied through 3 consecutive steps. Accordingly, this method is applicable to assess stakeholders’ engagement for any web-based research study. In sum, this method presents:•The inputs of the method are publicly available data.•This method is applicable for variety web-based research studies regardless of the applied methodological approach (e.g., qualitative, quantitative).

Effects of land use change on inter‐species and intra‐guild trophic interactions of fish communities in tropical headwater streams

Abstract Freshwater ecosystems are subjected to a broad range of anthropogenic threats. Understanding the responses of aquatic biota to these threats and identifying potential mitigating actions presents a major challenge for ecologists and natural resource managers. Here, we investigated the responses of fish communities to land use change at different scales. We assessed patterns of food web structure of fish across a gradient of human impacts in the Atlantic Forest ecoregion of southeast Brazil. We analysed stomach contents of fish and evaluated the response of five food web metrics to variation in land use change. We also calculated four metrics for intra‐guild comparisons in the omnivore, insectivore, and algivore–insectivore guilds. The proportional abundance of omnivores increased as temperature increased and canopy cover decreased. Food web specialisation decreased in deforested streams with higher nutrient input, suggesting higher resource sharing by those fish communities. Fish in the algivore–insectivore guild consumed fewer types of macroinvertebrates in streams with low canopy cover. The opposite pattern was observed within the insectivore guild with individuals consuming a larger variety of prey in impacted streams. Deforestation, and increases in water temperature and nutrient input, influenced inter‐species and intra‐guild trophic interactions in fish communities in these Atlantic Forest streams, even though the richness of fish community and composition of intra‐guild species remained unchanged. Some food web metrics were sensitive to the direct and indirect effects of disturbance on these fish communities. Our study has shown that assessments of trophic interactions can detect the effects of land‐use disturbance on fish communities that may not be evident from simple measures of species richness and composition. This approach provides direct insights into the functional integrity of fish communities and should be considered for monitoring the success of programmes aimed to protect and, where necessary, restore freshwater ecosystems.

Temporal changes of the food web structure and function driven by changes in hydrological regimes and water quality in a large shallow lake

Assessing food web structural properties and energy fluxes under changing hydrological regimes and water quality reveals the temporal patterns of ecosystem dynamics in shallow lakes. Here, we studied northern China’s largest shallow lake (Lake Baiyangdian) using quantitative food web models for five representative years (1958, 1980, 1993, 2009, and 2019). We analyzed the temporal patterns of food web structure and function by combining a Bayesian isotope mixing model with a food web energetics model. We further examined the temporal changes of unweighted and weighted food web topological attributes. Lake Baiyangdian changed from a detritus-based into a phytoplankton-based food web based on the relative contributions of basal food sources and energy flux distributions. The trophic position of fingerlings, large omnivorous fish, and carnivorous fish decreased with increasing eutrophication. The highest energy fluxes were from detritus to zooplankton and mollusks in 1958, from detritus and phytoplankton to zooplankton in 1980, 1993, and 2009, and from phytoplankton to zooplankton and detritus to mollusks in 2019. The highest total energy flux was in 1993, followed by 2019, with the lowest value in 1958. Unweighted food web metrics showed similar patterns. We observed more pronounced temporal variability in the node- and link-weighted food web metrics than in the unweighted metrics. In addition, hydrological factors (threshold, duration, reversals between high, and low water levels), eutrophication, and some water quality factors (chemical oxygen demand, dissolved oxygen, and pH) played important roles in the temporal changes of food web dynamics in Lake Baiyangdian. Our findings demonstrate the importance of integrating unweighted and weighted indicators to holistically comprehend how highly aggregated food webs respond to changing hydrological regimes and water quality, thereby improving management and restoration of shallow lake ecosystems.