Levels Of Diversity Research Articles

Comparing species richness and abundance of bumble bees between urban and natural areas using a photographic survey approach

Bumble bees are essential pollinators that provide critical ecosystem services yet, studies are documenting global species declines while recognizing those declines may be understated due to insufficient baseline data. This study investigates bumble bee species richness and abundance across urban and natural sites in Prince Edward Island, Canada, focusing on Charlottetown (urban) and Prince Edward Island National Park (natural). We conducted fieldwork in August and September 2019 using a non-invasive photographic survey technique. We used published keys and sought feedback from citizen science platforms like iNaturalist and Bumble Bee Watch to verify species identification. Our results revealed nine bumble bee species, with Bombus impatiens being the most abundant and Bombus perplexus the rarest. Species richness was higher in natural sites, while urban sites demonstrated moderate levels of bumble bee diversity. Additionally, our findings suggest that sites containing a mix of natural and human-cultivated plant types, predominantly found in our urban study sites, may support higher diversity and evenness levels than those of homogenized plant types (natural or human-cultivated). This research illustrates the practicality of photographic surveys to document the species richness and diversity of bumble bees while avoiding disturbance to populations in urban and natural habitats of Prince Edward Island.

Modeling and Analysis of College English from the Perspective of Connected Intelligent Algorithms

To explore the realm of English education through contemporary advancements in artificial intelligence (AI), language education methods have developed significantly traditional approaches that usually have trouble with individualized learning needs and cannot handle diverse proficiency levels. This paper reveals the most prominent problem of inefficiency and non-personalized learning experiences in college English as a significant concern in the existing literature. In response, it suggests a novel method called Artificial Intelligence based English Teaching Method (AI-ETM). It has linked intelligent algorithms that can dynamically adapt teaching strategies and learning materials according to individual student’s needs, rate of comprehension and proficiency levels. The main aim of AI-ETM is to integrate AI technologies with hybrid particle swarm optimization (PSO) into English language teaching to improve effectiveness and efficiency and provide personalized learning experiences for students. This paper expects several outcomes from the implementation of AI-ETM. Among these is enhanced student engagement and motivation due to personalized learning experiences customized according to personal preferences and level of competence. Additionally, AI-ETM is expected to improve learning outcomes by offering targeted feedback and adaptive learning resources. This paper suggests that once AI-ETM is introduced, efficiency in delivering language instruction services will improve, thereby optimizing the allocation of educational resources.

Effects of Different Production Methods on the Quality and Microbial Diversity of Sauerkraut in Northeast China

Sauerkraut is a popular fermented food in Northeast China. However, owing to the different production methods used, the quality of commercial sauerkraut is often quite different, which is reflected mainly in the differences between starter culture (Group-L), additive addition (Group-P) and natural fermentation (Group-H) methods. The purpose of this study was to explore the differences among the three fermentation methods by measuring physical and chemical indices, microbial diversity indices, flavour indices and volatile substances. The results revealed that there was no significant difference in the physical or chemical indices among the groups. The content of esters and alcohols in Group-L was the highest, and the taste richness, aftertaste-a and aftertaste-b were the highest, which had a positive effect on flavour. The highest level of microbial diversity was found in Group-H, which contained many pathogenic bacteria, such as Janibacter, Pseudomonas, and Vagococcus, which reduced the food safety of sauerkraut. At the genus level, the dominant bacterial genera in the starter and additive groups included Lactobacillus and Pediococcus. The correlation analysis revealed that Group-L was positively correlated with the contents of Lactobacillus plantarum, Lactobacillus brevis, Pediococcus, ethyl oleate and vanillin. In summary, this study evaluated the different production methods of northeast sauerkraut, providing theoretical support for the production of high-quality northeast sauerkraut.

Genetic Analysis of the Brown Bear Sub-Population in the Pindos Mountain, Central Greece: Insights into Population Status and Conservation

Habitat fragmentation poses a significant threat to the existence and reproduction of large carnivores, such as brown bears, as it affects the genetic connectivity of populations and, consequently, their long-term viability. Understanding the genetic makeup and dispersal patterns in areas where brown bears live is crucial for developing effective conservation plans and promoting human-brown bear coexistence. In this study, 214 hair samples were collected non-invasively from brown bears and were genetically analyzed using fifteen specific microsatellite loci to shed light on the genetic status and demography of a sub-population residing in Central Greece (Trikala-Meteora area). The broader Central and South Pindos regions have not been studied for over a decade; however, high levels of genetic diversity, a lack of heterozygosity deficiency, and no signs of inbreeding, along with an estimated effective population size (Ne = 99), confirm the good conservation status of this sub-population. Moreover, the existence of a natural and apparently functional corridor in Central Pindos was demonstrated by bear movements between the western and eastern parts of the project area, enhancing the sustainability of the population. These findings will contribute to future efforts to conserve natural corridors that enable functional connectivity among large areas of brown bear territories in Greece.

Patent Activity of Countries and Sectors in Graphene-Based Technologies

Purpose: The aim of this article is to analyse the patent activity of various countries, regions, and sectors (academic, private, governmental) from 2000 to 2018, identifying global leaders in graphene-based technologies. Design/methodology/approach: The study is based on an analysis of patent filings from the PATSTAT (EPO) database covering the years 2000-2018. Bibliometric techniques were employed to quantify trends in patent filings, combined with statistical analysis to identify areas with the highest growth dynamics. The data was segmented by countries and sectors, enabling a statistical examination of regional and sectoral diversity. Findings: The findings reveal a diverse level of development in graphene technologies across different regions and sectors, influenced by local innovation strategies and varying levels of research and development engagement. Initially, the provision of essential research resources and infrastructure played a crucial role in enabling the growth of graphene-based technologies. As research progressed, there was a notable increase in patent activity, reflecting the intensification of research and development efforts and the gradual implementation of new technologies across various industrial sectors. Research limitations: The research limitations stem from the quality of patent data, which does not always reflect the full scope of research and development activity. Issues may arise from classification errors, inconsistencies in name standardization, transcription errors, and data incompleteness, all of which may affect the accuracy of the analysis results. Research implications: This study provides valuable insights into the development and commercialization of graphene technologies, which can support innovation strategies across various sectors. The findings can assist policymakers in making decisions regarding resource allocation and setting research and development priorities, as well as understanding the dynamics of activity and collaboration between sectors. Originality/value: The article contributes to the literature on innovation management, particularly in the context of breakthrough technologies represented by graphene-based technologies. The study provides detailed insights into the leaders in this field, highlighting the importance of cross-sector collaboration in the effective implementation of new technologies and fostering innovation dynamics.

Complete Genomic Landscape Reveals Hidden Evolutionary History and Selection Signature in Asian Water Buffaloes (Bubalus bubalis).

To identify the genetic determinants of domestication and productivity of Asian water buffaloes (Bubalus bubalis), 470 genomes of domesticated river and swamp buffaloes along with their putative ancestors, the wild water buffaloes (Bubalus arnee) are sequenced and integrated. The swamp buffaloes inherit the morphology of the wild buffaloes. In contrast, most river buffaloes are unique in their morphology, but their genomes cluster with the wild buffaloes. The levels of genomic diversity in Italian river and Indonesian swamp buffaloes decrease at opposite extremes of their distribution range. Purifying selection prevented the accumulation of harmful loss-of-function variants in the Indonesian buffaloes. Genes that evolved rapidly (e.g., GKAP1) following differential selections in the river and swamp buffaloes are involved in their reproduction. Genes related to milk production (e.g., CSN2) and coat color (e.g., MC1R) underwent strong selections in the dairy river buffaloes via soft and hard selective sweeps, respectively. The selective sweeps and single-cell RNA-seq data revealed the luminal cells as the key cell type in response to artificial selection for milk production of the dairy buffaloes. These findings show how artificial selection has been driving the evolutionary divergence and genetic differentiation in morphology and productivity of Asian water buffaloes.

Task-Based Needs Analysis: A Triangulated Methodology

This study presents a task-based needs analysis of female English major seniors at a Saudi university to identify the academic tasks needed for their academic progress. The study utilized triangulated sources and methods, including the department’s written materials; semi-structured interviews with instructors and students; and questionnaires. Academic tasks were found to be essential for academic progress, providing insights that could be overlooked without such analysis. The interviews revealed that students’ proficiency levels ranged from low to average and that course content was not adapted to support below-average students. According to the questionnaire, the most essential skills for students’ academic progression were effectively using the university’s Learning Management System, time management, and delivering presentations. Listening to teachers as well as writing coherent and cohesive paragraphs were also important, whereas critical thinking and writing research papers were the most difficult tasks. The findings of this study emphasize the importance of adapting course content and pedagogical strategies to accommodate diverse student proficiency levels, thereby enhancing academic success.

Utilizing Open Access Spatial Data for Flood Risk Mapping: A Case Study in the Upper Solo Watershed

Indonesia is experiencing a rise in natural disasters due to its geographical position within a tropical region, with the Upper Solo River watershed exhibiting a heightened risk of flooding. This region has already suffered numerous floods due to excessive precipitation and insufficient drainage. Susceptibility, hazard, and risk studies have been conducted to investigate this phenomenon but have been limited to specific regions within the catchment area. This study aims to construct a GIS-based flood risk model using Open-Access Spatial Data (OASD) based on diverse physical characteristics, urbanization levels, and population. We used several OASD, including SRTM, Sentinel 2 MSI, GPM v6, NASA-USDA Enhanced SMAP Global Soil Moisture Data, GHS-SMOD R2023A - Global Human Settlement Layers, and GHSL: Global Population Surfaces 1975-2030 (P2023A). The model integrates the risk parameters to identify flood risk using a weighted overlay in ArcGIS. The results demonstrate spatial heterogeneity in flood risk throughout the watershed. The result also reveals that Surakarta City, with a high proportion of its area in the 'High' (57.3%) and 'Very High' (29.54%) risk categories, is at the highest risk of flooding within the watershed. The study enhances understanding of this topic by comprehensively evaluating flood hazards, vulnerabilities, and risks. It highlights the significance of utilizing low-cost OASD to improve flood preparedness and response strategies.

Does national intellectual capital matter for productivity? International evidence

PurposeIn the context of the contemporary globalized environment and the rapid progression of Industry 4.0, the existing literature suggests that national intellectual capital does play a significant role in shaping diverse economic metrics. However, the connection between national intellectual capital and total factor productivity (TFP) has been largely overlooked. This paper examines the effect of national intellectual capital on productivity across 84 countries, encompassing diverse income levels, human development index (HDI) levels and continents.Design/methodology/approachThis study utilizes dynamic ordinary least squares (DOLS), fully modified ordinary least squares (FMOLS), two-stage least squares (2SLS), generalized method of moments (GMM) and pooled mean group (PMG) estimation techniques on a sample of 84 economies from 2000 to 2019.FindingsThe results reveal a significant effect of national intellectual capital on productivity. Countries with robust intellectual capital exhibit enhanced productivity and, by extension, sustainable economic growth. The findings are nuanced, illustrating varied impacts across low, middle and high-income countries and offering insights into tailored strategies for each income group. Nations with lower HDI levels derive significant benefits from investments in intellectual capital, whereas higher HDI countries experience lower returns in productivity gains from additional intellectual capital investments. Interestingly, Latin America exhibits a paradoxical negative effect of national intellectual capital on TFP.Practical implicationsThis paper makes a significant contribution to the literature by extending the discourse on intellectual capital to the national level, an area that has been relatively underexplored. The comparative analysis across income groups, human development index levels and continents enriches the understanding of the multifaceted impacts of intellectual capital on productivity. These insights are valuable for policymakers, researchers and international development agencies, providing a comprehensive perspective on how intellectual capital influences productivity in diverse economic and developmental contexts.Originality/valueTo the best of our knowledge, this is the first empirical study to investigate the impact of national intellectual capital on productivity across 84 countries, considering diverse income levels, HDI levels and continents.

Understanding Factors Contributing to Glaucoma in Populations of African Descent

Glaucoma is the leading cause of irreversible blindness globally, with the commonest subtype being primary open angle glaucoma (POAG). POAG is characterised by an increase in intraocular pressure (IOP), optic nerve damage and irreversible visual field loss. People of African descent (AD) are significantly more susceptible to POAG when compared to people of European descent (ED), and the reasons for this are complex and multifaceted. The vast level of genetic diversity in AD populations has allowed, through genome-wide association studies (GWAS), for the identification of several single nucleotide polymorphisms (SNPs) as well as differences in mitochondrial haplogroups, which could explain the pathophysiology underlying the increased susceptibility of AD populations to POAG. The altered expression of genes such as MYOC as well as the expression of inflammatory mediators influencing reactive astrocytes have also been implicated. There are also several differences in morphology between AD and ED eyes which must be considered, including differences in central corneal thickness (CCT) and corneal hysteresis (CH) as well as variation in properties of optic discs. The link between all the aforementioned factors and the increased prevalence of POAG in AD populations will be explored in this review.

Preserving tororaro’s legacy: conservation genetics of in-situ and ex-situ populations of Muehlenbeckia astonii (Polygonaceae)

ABSTRACT Tororaro, a Threatened Nationally Endangered species in eastern South Island and southern North Island, New Zealand, is primarily found in coastal or lowland droughty habitats with small, isolated populations, notably the largest on Kaitōrete Spit, Canterbury. Due to recent issues with the conservation management of the Kaitōrete Spit population, the importance of protecting this species has been highlighted. While widely cultivated in gardens for its horticultural appeal and resilience, recruitment failure in wild populations and the genetic structure and variation within wild and cultivated populations is unknown, which raises questions about in-situ and ex-situ conservation strategies. Microsatellite markers were developed to assess the level of natural variation present in wild populations and that of cultivated material present throughout New Zealand. The results reveal natural populations can be grouped into three clusters with a low to medium level of diversity for each cluster (Na = 1.647–3.647, Ho = 0.194–0.457, He = 0.181–0.478), and the diversity of each group is captured in cultivation (Na = 2.471–3.588, Ho = 0.207–0.511, He = 0.173–0.519). Cultivated material largely follows ecosourcing guidelines whereby cultivated plants in Wellington, Marlborough and Canterbury are often sourced from the regional meta-population, however, there are some exceptions that have implications for management of this species. In Otago, where M. astonii does not naturally occur, cultivated populations comprise representatives of all regional populations. An interesting outcome is that we recovered from among the cultivated plants several individuals that are likely to be putative intraspecific hybrids between plants from Wellington populations and those from either Marlborough or Canterbury; these hybrid genotypes are unknown in wild populations. Clonal plants were also represented among the wild and cultivated populations by individual plants having identical genotypes. We also demonstrate the utility of these markers across other Muehlenbeckia species.

Genetic Diversity Analysis and Identification of Candidate Genes for Growth Traits in Chengkou Mountain Chicken

Growth traits constitute critical factors in the breeding program of broiler chickens. The Chengkou mountain chicken A-lineage (CMC-A) represents a breed specifically bred for meat production. To further explore the growth performance of the CMC-A population, this study conducted whole-genome sequencing on 464 CMC-A roosters to systematically evaluate their genetic diversity. Additionally, runs of homozygosity (ROH) islands and genome-wide association studies (GWASs) were employed to identify the loci and functional genes influencing the growth traits in Chengkou mountain chickens. The results revealed a high level of genetic diversity and low levels of inbreeding in Chengkou mountain chickens. Several genes associated with stress resistance, muscle growth, and fat deposition were pinpointed through ROH island identification. Moreover, 52 SNP loci were detected, along with 71 candidate genes. These findings enhance our understanding of the genetic architecture underlying the growth traits in Chengkou mountain chickens and provide a theoretical foundation for subsequent breeding endeavors.

Genetic Diversity and Structure of the Darkfin hind (Cephalopholis urodeta) in the Spratly Islands, Vietnam

The darkfin hind, Cephalopholis urodeta, is a commercially valuable reef fish species inhabiting the ecologically important Spratly Islands. Understanding this species’ genetic diversity and population structure is crucial for developing effective conservation strategies, particularly given the increasing pressures on coral reef ecosystems. This study investigated the genetic diversity and population structure of C. urodeta within the Spratly archipelago using mitochondrial COI and Cyt b gene markers. We analyzed 30 individuals for COI and Cyt b, revealing high levels of haplotype diversity (Hd=0.9563±0.0226 for COI; Hd=0.9402±0.0229 for Cyt b). However, despite this high overall diversity, our analyses also revealed significant genetic structuring within the archipelago, suggesting restricted gene flow among some populations. This structuring is likely influenced by the complex oceanographic currents in the region and the spatial distance between reefs, which can limit larval dispersal. These findings highlight the need for spatially explicit conservation and management strategies for C. urodeta in the Spratly Islands. Recognizing the genetic differentiation within the archipelago and implementing management measures tailored to specific zones will be crucial for preserving genetic diversity, maintaining connectivity, and ensuring the long-term sustainability of this important resource.

Evolutionary Genomics Provides Insights Into Endangerment and Conservation of a Wild Apple Tree Species, Malus sieversii.

Understanding the evolutionary history of a species is essential for effective conservation management. Malus sieversii, a relict broad-leaf forest tree found in arid Central Asian mountains, has a narrow and fragmented distribution and is classified as an endangered species in China. This species is considered one of the ancestors of the domesticated apple trees. In the present study, we sampled five populations of M. sieversii and its wide-ranging congener M. baccata from China. Through deep whole-genome resequencing, we analyzed the population's genetic diversity, genetic structure, demographic history, fixation of deleterious mutations, and genomic divergence. Our results revealed that M. baccata exhibits a higher level of genetic diversity than M. sieversii. The effective population size of M. sieversii decreased, whereas that of M. baccata recovered after the bottleneck effect. In M. sieversii, the genetic structure of the Yili region was distinct from that of the Tacheng region. Populations at the rear edge of the Tacheng region showed a stronger fixation of deleterious mutations than those in the Yili region. Genomic divergence indicated that the positively selected genes were associated with physiological processes within the genomic islands between the Yili and Tacheng regions. Based on these findings, we recommend the establishment of two separate conservation units for the Yili and Tacheng lineages to preserve their genetic resources. Given the limited distribution range and high fixation rate of deleterious mutations, urgent protective measures are recommended for the Tacheng lineage.

Does corporate board gender diversity influence shareholder value?

This study investigates the influence of board gender diversity on the shareholder value of South African-listed non-financial companies on the JSE from 2013 to 2022. The study used a quantitative quasi-experimental method to examine the influence of board gender diversity on shareholder value creation measures from a multi-theoretical perspective. The board gender diversity measures include the proportion of women directors on the board, the Blau index for board gender diversity, and dummy variables indicating the presence of one, two, three, or more women directors on the board, as well as skewed board, tilted board, and balanced board. Shareholder value creation is proxied using standardised market value added, market-to-book ratio, and Tobin’s Q. The study utilises fixed effects models based on linear and curvilinear models to test the hypotheses. According to linear models, all board gender diversity measures demonstrate a significant positive, negative, or no effect on shareholder value creation measures, aligning with the multi-theoretical perspective of corporate governance research. However, curvilinear quadratic models suggest that the Blau index for board gender diversity and the proportion of women directors on board positively and negatively affect shareholder value creation, highlighting an inverted U-shaped effect. The results recognise the "too much- of- a -good- thing” effect and a possible optimal(or worse) level of board gender diversity as crucial. In conclusion, this study demonstrates that the claim of the ‘‘one size fits all’’ board gender diversity mechanism in creating and maximising shareholder value, often implicitly stated by regulators and advisors, may be misleading.

LabEmbryoCam: An opensource phenotyping system for developing aquatic animals

Phenomics is the acquisition of high-dimensional data on an individual-wide scale and is proving transformational in areas of biological research related to human health including medicine and the crop sciences. However, more broadly, a lack of accessible transferrable technologies and research approaches is significantly hindering the uptake of phenomics, in contrast to molecular-omics for which transferrable technologies have been a significant enabler. Aquatic embryos are natural models for phenomics, due to their small size, taxonomic diversity, ecological relevance, and high levels of temporal, spatial and functional change. Here, we present LabEmbryoCam, an autonomous phenotyping platform for timelapse imaging of developing aquatic embryos cultured in a multiwell plate format, and while optimised for embryos, the instrument is extremely versatile. The LabEmbryoCam capitalises on 3D printing, single board computers, consumer electronics and stepper motor enabled motion. These provide autonomous X, Y and Z motion, a web application streamlined for rapid setup of experiments, user email notifications and a humidification chamber to reduce evaporation over prolonged acquisitions. Downstream analyses are provided, enabling automated embryo segmentation, heartbeat detection, motion tracking, and energy proxy trait (EPT) measurement. LabEmbryoCam is a scalable, and flexible laboratory instrument, that leverages embryonic and early life stage organisms to tackle key global challenges including biological sensitivity assessment, toxicological screening, but also to support broader engagement with the earliest stages of life.

Deep-amplicon sequencing of the complete beta-tubulin gene in Trichuris trichiura before and after albendazole treatment

Concerns about the emergence of benzimidazole resistance in soil-transmitted helminths (STH) infections, particularly against Trichuris trichiura, have arisen. Previous studies of veterinary nematodes have linked benzimidazole resistance to single-nucleotide polymorphisms (SNPs) at three specific codons in the beta-tubulin gene, but similar associations in STH have not been consistently observed. In this work, we screened the complete beta-tubulin gene previously linked to benzimidazole resistance in T. trichiura by deep-amplicon sequencing to identify genetic variants and associate levels of diversity with drug response to albendazole. We used 99 DNA samples extracted from T. trichiura pooled eggs, previously semi-purified from human stool samples collected in Manhiça district, Mozambique. We obtained a set of 39 amplicons of the complete gene by subjecting the pooled eggs to long-read PCR and subsequently sequencing them. Of those amplicons, 22 and 17 were obtained from stool samples collected before, and 21 days after albendazole treatment, respectively. We observed genetic variation across the whole gene sequence, in both exons and introns; however, none were associated with the previously proposed resistance-associated SNPs, and none were predicted to significantly affect protein function. No significant differences in genetic diversity were observed between pre- and post-treatment samples. Using publicly available genome-wide data, we also analysed a second beta-tubulin isotype in the T. trichiura genome. We focused on detecting the canonical SNPs and assessing for signatures of genetic selection around this second isotype gene. This analysis did not reveal evidence supporting this second isotype's role in anthelmintic resistance. Despite the limitations of our study, such as a small sample size, particularly paired pre- and post-treatment samples (n=6), or a restricted geographical area, we found no evidence linking either of the two beta-tubulin genes to benzimidazole resistance in T. trichiura, suggesting that genetic markers of drug resistance likely exist outside the beta-tubulin genes.

Unraveling the link between worldwide adakite-like rocks and porphyry Cu deposits

Adakite-like rocks, as an important recorder of magmatic evolution in mantle and crust, are closely associated with major porphyry Cu deposits. However, the underlying mechanism connecting these associations remains insufficiently elucidated. This study compiles ca. 7000 whole-rock geochemical data from Phanerozoic adakite-like rock samples and from ore-forming porphyries in porphyry Cu deposits. Machine learning investigations are performed to characterize the geochemical variations of adakite-like rocks from various orogenic or cratonic systems and investigate any geochemical similarities with rocks associated with porphyry ore systems. Principal component analysis (PCA), along with t-distributed Stochastic Neighbor Embedding (t-SNE), highlights elemental distinctions between adakite-like rocks formed in mature and juvenile crust and the similarities of rocks from porphyry CuMo deposits with the former and rocks from porphyry CuAu deposits with the latter. Extreme Gradient Boosting (XGBoost) and Support Vector Machine (SVM) analyses are applied to the original dataset and the PCA data derived from the dataset to discriminate adakite-like rocks from various geodynamic settings from each other and from rocks associated with porphyry ore deposits. Our models show that XGBoost and SVM can identify the tectonic regions of adakite-like rocks and rocks from porphyry copper systems with high efficiency and confidence e.g., accuracy = 0.88–0.94 and area under curve (AUC) = 0.69–0.86. The application of SHapley Additive exPlanations (SHAP) values is employed to elucidate the parameters that discriminate the different environments, providing insight into the underlying petrogenetic processes, including diverse levels of formation depth and extent of mantle interaction. Additionally, when examining ore-forming porphyries and adakite-like rocks, the incorporation of heatmaps into taxonomic classification (HTC) provides significant distinguishing factors with substantial geological implications. These findings suggest potential geological processes (e.g., remelting of Cu-sulfide-bearing cumulates or flotation of Cu-sulfide phases attached to vapor bubbles) that may enrich the source magma of ore-forming porphyries beyond the conventional geological processes responsible for adakite-like rock formation, which could serve as an exploration indicator.

Global trade dynamics' impact on food pricing and supply chain resilience: A quantitative model

This study explores the influence of global trade dynamics on food pricing and supply chain resilience, focusing on the development of a quantitative model that examines the relationships between trade policies, economic indicators, and trade volumes. As fluctuations in trade policies—such as tariffs, quotas, and subsidies—directly impact food prices and market stability, this model provides a structured framework for assessing these variables’ interdependencies. By integrating data on trade flows, currency exchange rates, and commodity prices, the model quantifies the effects of protective and liberalized trade measures on both local and international food markets. This approach allows for identifying trends in pricing volatility linked to policy shifts, thereby offering insights into areas vulnerable to trade disruptions and external economic shocks. The resilience of the food supply chain is measured by evaluating metrics such as delivery times, supplier diversity, and inventory levels across regions affected by trade policy changes. The findings emphasize that trade barriers can result in price spikes, delays, and supply shortages, while open trade policies generally support market flexibility and pricing stability. Additionally, the model incorporates economic indicators such as Gross Domestic Product (GDP), inflation, and unemployment rates, which correlate with food demand and purchasing power, thereby further influencing price and supply chain stability. Future research could leverage this model to develop adaptive strategies that strengthen supply chain resilience under various global trade conditions. Suggested adaptations include diversifying suppliers, increasing inventory buffers, and enhancing predictive analytics for better demand forecasting. By integrating these adaptive measures, stakeholders can mitigate adverse effects on food accessibility and affordability in both developed and emerging economies. This research contributes to the literature on food security, highlighting the need for resilient trade policies and supply chain strategies in an increasingly interconnected global economy.

Modular Web-based Learning Model to Address Underdeveloped ICT Infrastructure for Smart E-learning Education System

Advancements in Information and Communication Technology (ICT) enhance learning and instructional practices, generating chances for novel techniques and tools while simultaneously transforming the learning model. Historically, smart education models mostly consisted of qualitative investigations that delineated the conceptual structure and its implications for the Smart E-learning Education System (SEES). While these theoretically organized SEES can enhance student learning, facilitate peer and instructor communication, and improve teaching practices—thereby aiding in the comprehension of the status of learners and needs and offering real-time synchronous/asynchronous guidance—many qualitative investigations conducted in the past lack empirical evidence to substantiate the prioritization of E-Learning scheduling. This research first examined the technological barriers to implementing the SEES in developing nations. As a result, the suggested framework for the SEES based on underdeveloped ICT has been introduced. The system utilizes an integrated online/offline Web-Based Learning Model (WLM) incorporating a Service-oriented Architecture (SA) architecture to create SEES. The online mode is enabled for a WLM when an internet connection is accessible. The offline variant of the system is provided in a packed format and is used when Internet access is unavailable in an isolated classroom. A working example was launched to get input from learners and instructors across diverse educational levels. The trial installation and survey results confirm the viability and benefits of the suggested system.