Local Level Research Articles

The Adrenal Gland and Pancreatic Islets - A Beneficial Endocrine Alliance.

Intraportal islet transplantation in patients with type 1 diabetes enables restoration of glucose-regulated insulin secretion. However, several factors hamper a widespread application and long-term success: chronic hypoxia, an inappropriate microenvironment and suppression of regenerative and proliferative potential by high local levels of immunosuppressive agents. Therefore, the identification of alternative and superior transplant sites is of major scientific and clinical interest. Here, we aim to evaluate the adrenal as an alternative transplantation site. The adrenal features a particular microenvironment with extensive vascularization, anti-apoptotic and pro-proliferative, anti-inflammatory and immunosuppressive effects. To validate this novel transplantation site, an in vitro co-culture system of adrenal cells and pancreatic islets was established and viability, islet survival, functional potency and antioxidative defense capacity were evaluated. For in vivo validation, an immune-deficient diabetic mouse model for intra-adrenal islet transplantation was applied. The functional capacity of intra-adrenally grafted islets to reverse diabetes was compared to a standard islet transplant model and measures of engraftment such as vascular integration were evaluated. The presence of adrenal cells positively impacted on cell metabolism and oxidative stress. Following transplantation, we could demonstrate enhanced islet function in comparison to standard models with improved engraftment and superior re-vascularization. This experimental approach allows for novel insights into the interaction of endocrine systems and may open up novel strategies for islet transplantation augmented through the bystander effect of other endocrine cells or the active factors secreted by adrenal cells modulating the microenvironment.

Anomaly Detection Algorithms for Low-Dimensional and High-Dimensional Data: A Critical Study

Suspicious events or objects that differ from the norm in data can be discovered using anomaly identification. Identifying anomalies is critical for many applicable domains of life, e.g., preventing credit card theft and spotting intrusions into networks. It is possible to detect anomalies on a global scale as well as at the local level. A global outlier is a data point beyond the norm for the entire dataset, while a local outlier may be inside the norm for the entire dataset but outside the surrounding data points. Data outlier identification methods that are performed locally are inadequate. Therefore, better algorithms are required to investigate the high velocity of data and identify local outliers. Machine learning and data mining techniques need to be investigated to determine the pros and cons of anomaly identification residing inside data. The density based LOF method can be applied as the best choice to identify local outliers. While many variants of LOF exist for low-dimensional data, none are suitable for high-dimensional data. This research study discusses LOF, COF, and CBLOF methods for spotting local outliers in low and high-dimensional data. Regarding the size of the dimension, the performance of density-based algorithms is examined based on accuracy and time complexity. In this scenario, CBLOF achieves outstanding results due to its distinctive method of employing cluster-based local outlier detection.

Optimizing Crop Yield Estimation through Geospatial Technology: A Comparative Analysis of a Semi-Physical Model, Crop Simulation, and Machine Learning Algorithms

This study underscores the critical importance of accurate crop yield information for national food security and export considerations, with a specific focus on wheat yield estimation at the Gram Panchayat (GP) level in Bareilly district, Uttar Pradesh, using technologies such as machine learning algorithms (ML), the Decision Support System for Agrotechnology Transfer (DSSAT) crop model and semi-physical models (SPMs). The research integrates Sentinel-2 time-series data and ground data to generate comprehensive crop type maps. These maps offer insights into spatial variations in crop extent, growth stages and the leaf area index (LAI), serving as essential components for precise yield assessment. The classification of crops employed spectral matching techniques (SMTs) on Sentinel-2 time-series data, complemented by field surveys and ground data on crop management. The strategic identification of crop-cutting experiment (CCE) locations, based on a combination of crop type maps, soil data and weather parameters, further enhanced the precision of the study. A systematic comparison of three major crop yield estimation models revealed distinctive gaps in each approach. Machine learning models exhibit effectiveness in homogenous areas with similar cultivars, while the accuracy of a semi-physical model depends upon the resolution of the utilized data. The DSSAT model is effective in predicting yields at specific locations but faces difficulties when trying to extend these predictions to cover a larger study area. This research provides valuable insights for policymakers by providing near-real-time, high-resolution crop yield estimates at the local level, facilitating informed decision making in attaining food security.

Trends in air toxics cancer risk in Southern California, 1998-2018

Air toxics are an important category of air pollutants that are known to cause adverse health effects, including increased cancer risk. Regulatory efforts at federal, state, and local levels have aimed to decrease air toxics emissions over the past several decades. This study evaluated trends in air toxics cancer risks in Southern California using data from 1998 to 2018. We estimated air toxics cancer risk for each of four iterations of the South Coast Air Quality Management District’s Multiple Air Toxics Exposure Study, which included at least one year of measurements at 10 stations and air toxics modeling for each iteration. Cancer risks were calculated using the measured and modeled air toxics concentrations averaged over a one to two year period and multiplied by the corresponding cancer potency factor and combined exposure factor that accounted for multiple exposure pathways and children’s increased sensitivity to the health effects of air pollution. We examined temporal trends in overall air toxics cancer risks and evaluated changes in the air toxics species that contributed most to cancer risk in the region. Both measurement and modeling results show that air toxics cancer risk in Southern California decreased by more than 80% between 1998 and 2018, including a decrease of about 50% from 2012 to 2018. Diesel particulate matter was the main risk driver, followed by benzene, 1,3-butadiene, and formaldehyde. We found that more densely populated communities showed larger decreases than sparsely populated areas. The substantial decrease in air toxics levels over this 20-year period points to the success of air pollution policies aimed at addressing air toxics emissions and can inform future policy efforts to further reduce air toxics health impacts.

Spatial analysis of food and water-borne diseases in Ahmedabad, India: Implications for urban public health planning

Spatial analysis of infectious diseases can play an important role in mapping the spread of diseases and can support policy making at local level. Moreover, identification of disease clusters based on local geography and landscape forms the basis for disease control and prevention. Therefore, this study aimed to examine the spatial-temporal variations, hotspot areas, and potential risk factors of infectious diseases (including Viral Hepatitis, Typhoid and Diarrhea) in Ahmedabad city of India. We used Moran's I and Local Indicators of Spatial Association (LISA) mapping to detect spatial clustering of diseases. Spatial and temporal regression analysis was used to identify the association between disease incidence and spatial risk factors. The Moran's I statistics identified presence of positive spatial autocorrelation within the considered diseases, with Moran's I from 0.09 for typhoid to 0.21 for diarrhea (p < 0.001). This indicates a clustering of affected wards for each disease, suggesting that cases were not randomly distributed across the city. LISA mapping demonstrated the clustering of hotspots in central regions of the city, especially towards the east of the river Sabarmati, highlighting key geographical areas with elevated disease risk. The spatial clusters of infectious diseases were consistently associated with slum population density and illiteracy. Furthermore, temporal analysis suggested illiteracy rates could increase risk of viral hepatitis by 13 % (95 % Confidence Interval (CI): 1.01–1.26) and of diarrhea by 18 % (95 % CI: 1.07–1.31). Significant inverse association was also seen between viral hepatitis incidence and the distance of wards from rivers. Conclusively, the study highlight the impact of socio-economic gradients, such as slum population density (indicative of poverty) and illiteracy, on the localized transmission of water and foodborne infections. The evident social stratification between impoverished and affluent households emerges as a notable contributing factor and a potential source of differences in the dynamics of infectious diseases in Ahmedabad.

On the emergence of cooperative industrial and labour relations

AbstractWe explore the long‐run determinants of current differences in the degree of co‐operative labour relations at the local level. We do this by estimating the effect of the medieval communes –that were established in certain cities in Centre‐Northern Italy towards the end of the 11th century – and that contributed to the emergence of a co‐operative attitude in the population on various proxies for current co‐operative labour relations. Conditional on a large set of firm and municipality level controls, as well as a full set of province fixed effects, we find that firms located in municipalities that had been a free medieval commune in the past have higher current probabilities to adopt two‐tier bargaining structures and to be unionized. We also report instrumental variables (IV) and propensity score estimates that confirm our main results.

Targeted Delivery of Catalase and Photosensitizer Ce6 by a Tumor-Specific Aptamer Is Effective against Bladder Cancer In Vivo.

Photodynamic therapy (PDT) is often applied in a clinical setting to treat bladder cancer. However, current photosensitizers report drawbacks such as low efficacy, low selectivity, and numerous side effects, which have limited the clinical values of PDT for bladder cancer. Previously, we developed the first bladder cancer-specific aptamer that can selectively bind to and be internalized by bladder tumor cells versus normal uroepithelium cells. Here, we use an aptamer-based drug delivery system to deliver photosensitizer chlorine e6 (Ce6) into bladder tumor cells. In addition to Ce6, we also incorporate catalase into the drug complex to increase local oxygen levels in the tumor tissue. Compared with free Ce6, an aptamer-guided DNA nanotrain (NT) loaded with Ce6 and catalase (NT-Catalase-Ce6) can specifically recognize bladder cancer cells, produce oxygen locally, induce ROS in tumor cells, and cause mitochondrial apoptosis. In an orthotopic mouse model of bladder cancer, the intravesical instillation of NT-Catalase-Ce6 exhibits faster drug internalization and a longer drug retention time in tumor tissue compared with that in normal urothelium. Moreover, our modified PDT significantly inhibits tumor growth with fewer side effects such as cystitis than free Ce6. This aptamer-based photosensitizer delivery system can therefore improve the selectivity and efficacy and reduce the side effects of PDT treatment in mouse models of bladder cancer, bearing a great translational value for bladder cancer intravesical therapy.

Boosting the Spanish Urban Agenda through urban living labs: The case study of Madrid

AbstractThe Spanish Urban Agenda (SUA) intends to promote sustainable development through the implementation of the 2030 Agenda at the local level. Since all world stakeholders are called to participate in the achievement of the Sustainable Development Goals, diverse instruments adopting a collaborative approach between social actors have gained importance. Among them, urban living labs (ULLs) involve distinct participants to handle urban issues by proposing and testing solutions. This research determines the role of ULLs conducted in Madrid since 2000 as drivers of the SUA. A two‐tier methodology was adopted to develop a framework after first conducting an in‐depth literature review to identify key features of ULLs. Second, the connection between the SUA and ULLs was defined. Findings revealed a limited impact of the analyzed labs in reaching the SUA. The under‐representation of social agents undermines the effectiveness of ULLs. A higher engagement of public institutions is recommended to overcome this shortcoming.

HANDLOOM AND CONSTRUCTION OF IDENTITY: A STUDY AMONG THE BODO WOMEN WEAVERS OF ASSAM

The practice of handloom weaving holds significant historical and cultural importance for the Bodo community, serving as an integral aspect of their socio-economic fabric for countless generations. In addition to engaging in agricultural activities, the Bodo community, along with the wider rural and semi-urban population of India, have traditionally pursued handloom weaving as a secondary occupation. The significance of handloom textile and weaving in the lives of the Bodo weavers can be understood via two distinct dimensions. Firstly, at the local level, it serves as a manifestation of local wisdom and tradition deeply ingrained into their cultural practices. Secondly, at the national level, it acts as a tangible representation of the community's distinctive identity. This article attempts to comprehend the importance of weaving within the Bodo community, specifically among women weavers, and examines how their involvement in the handloom sector contributes to the development of cultural identity. Nevertheless, it is crucial to comprehend the viewpoint of the weavers in their commitment to the preservation of the weaving practice, as they assume the role of custodians and guardians of this longstanding heritage.

Actors participation and power relations of REDD+ implementation in Bale Eco Region, Ethiopia

ABSTRACT The study focuses on actor participation and power dynamics in the REDD+ project within the Bale eco-region, a vital facet of global climate policy for sustainable forest resource management. The Forest Carbon Partnership Facility (FCPF) of the World Bank supports developing countries in preparing for international REDD+ policy implementation, emphasizing the necessity of effective actor participation. The study uses text documents, Socio metric survey, and interviews with project actors and participants. This study employs both qualitative framework and social network analysis (SNA). While SNA looks at power dynamics and interactions between actors, the qualitative framework allows for a comprehensive evaluation of actor participation. The social network data was analyzed using an open source software called NodeXL. Results show that Bale eco-region REDD+ involves actors from different groups. Actors contribute to national strategies, funding, capacity building, and knowledge sharing. However, local communities have limited involvement in decision-making, lack knowledge sharing and capacity building. This hinders the implementation process and contributes to unequal power dynamics and lack the comprehensive input needed for effective and tailored strategies in the region. Calculated centrality values highlight a strong alliance among Ethiopia's national government entity overseeing REDD+ Environment, Forest and Climate Change Commission (EFCCC), and the regional entities Oromiya Forest and Wildlife Enterprise (OFWI), as well as Farm Africa, indicating significant institutional power across national and local levels. EFCCC holds influence in decision-making and strategy development, while OFWI wields substantial regional institutional power in information control and collaboration. Thus, climate policies must prioritize involvement of local communities in decision-making, capacity development, and resource accessibility. This helps to tackle power imbalances through collaborative governance structures. It also enables stakeholders to actively manage forests through imparting skills, knowledge and share benefits equally.

RESEARCH WITH REFUGEES: WORKING WITH ETHNIC COMMUNITY-BASED ORGANIZATIONS

ABSTRACT The U.S. Refugee Admissions Program (USRAP) has functioned as a partnership between the federal government and a number of nonprofit partners for more than four decades. Yet resettlement is dependent on more than these particularly visible actors, and also includes states, municipalities, and a range of other organizations. In this paper I look at one part of the resettlement assemblage in the United States—ethnic community-based organizations (ECBOs)—from my own perspective as a researcher who has collaborated with one such entity over a number of years. Focusing on the shifting sands of refugee resettlement and drawing on research with staff at this agency, I examine some of the possibilities and pitfalls of engaging in praxis-oriented refugee research, especially at the local level. I suggest that the particular nuances and context of the ECBO is central to our understanding of contemporary resettlement practice in the United States.

Aryl Hydrocarbon Receptor Involvement in the Sodium-Dependent Glutamate/Aspartate Transporter Regulation in Cerebellar Bergmann Glia Cells.

Glutamate, the major excitatory neurotransmitter in the vertebrate brain, exerts its functions through the activation of specific plasma membrane receptors and transporters. Overstimulation of glutamate receptors results in neuronal cell death through a process known as excitotoxicity. A family of sodium-dependent glutamate plasma membrane transporters is responsible for the removal of glutamate from the synaptic cleft, preventing an excitotoxic insult. Glial glutamate transporters carry out more than 90% of the brain glutamate uptake activity and are responsible for glutamate recycling through the GABA/Glutamate/Glutamine shuttle. The aryl hydrocarbon receptor is a ligand-dependent transcription factor that integrates environmental clues through its ability to heterodimerize with different transcription factors. Taking into consideration the fundamental role of glial glutamate transporters in glutamatergic synapses and that these transporters are regulated at the transcriptional, translational, and localization levels in an activity-dependent fashion, in this contribution, we explored the involvement of the aryl hydrocarbon receptor, as a model of environmental integrator, in the regulation of the glial sodium-dependent glutamate/aspartate transporter. Using the model of chick cerebellar Bergmann glia cells, we report herein that the aryl hydrocarbon receptors exert a time-dependent decrease in the transporter mRNA levels and a diminution of its uptake activity. The nuclear factor kappa light chain enhancer of the activated B cell signaling pathway is involved in this regulation. Our results favor the notion of an environmentally dependent regulation of glutamate removal in glial cells and therefore strengthen the notion of the involvement of glial cells in xenobiotic neurotoxic effects.

Spatial Patterns of Nonprofit Founding: Toward a Local Ecology

Nonprofit organizations are vital to the implementation of social policy and provide myriad benefits to those nearby, yet few studies consider founding patterns in small areas. Conceptualizing ecological processes at the local level and in the context of developmental regimes, this article investigates nonprofit founding events among neighborhoods with a unique data set aggregated by census tract from 2010 to 2016 in one northeast Ohio county (United States) using a hierarchical Bayesian model. The results broadly support the density dependence hypothesis, however, suggest high density is required to reduce founding rates in small areas. The results indicate nonprofit founding rates are lower in tracts with higher levels of economic disadvantage and higher shares of Latino residents. The paper calls for further research into nonprofit population dynamics among small areas and for policymakers to closely consider nonprofit founding events, as founding determines the future of a region’s nonprofit infrastructure.

China’s Crackdown on Crypto Mining from a Climate Perspective: Unified Efforts from Administrative Authorities and the Judiciary

Abstract This article presents an examination of the unified efforts by China’s central authorities and the judiciary in the crackdown on crypto mining within the country. It discusses the environmental ramifications of crypto mining and traces its development in China, highlighting the resource-intensive nature of the process. Crypto mining risks China’s national objectives of promoting high-quality economic and social development, as well as industrial optimisation, energy conservation and emissions reduction. The central government’s commitment to climate goals and ecological civilisation, coupled with the perceived minimal economic benefits and substantial environmental damage caused by crypto mining, led to the issuance of the Notice on Rectifying Mining Activities of Virtual Currencies in September 2021. This article discusses the implications of the Notice and how it has been implemented at both national and local levels by the administrative authorities. With reference to typical cases, it examines how the judiciary in delivering judgments has kept in line with the spirit of the Notice by analysing mining-related civil disputes as they arise in courts and reflects on the interplay of legal and administrative measures in shaping a sustainable and environmentally conscious approach to emerging technologies in China and beyond.

URBAN PLANNING APPROACHES TO PLANNING THE BEAUTIFICATION SYSTEM OF RESIDENTIAL AREAS DURING THEIR RECONSTRUCTION

The analysis of planning experience of inhabited localities urban beautification in view of reconstruction was undertaken in the article. The question of Ukrainian experience of urban beautification system in accordance with approved standards and State Constructional Standards was envisaged. Analysis of validation state of local documents in urban beautification field was carried out and it has shown deficient percentage of regulatory documents approval on local level, which is one of key issues of urban beautification development. Furthermore, detailed analysis of foreign experience of urban beautification planning and development trend of this system I such countries, as USA, Canada, France, Singapore, Hong Kong, Japan was carried out. It is shown that first and critical stage of planning of effective urban beautification is preparing and approving corresponding certificates and standards. Emphasis added to functioning normative legal documents on issues relating to urban beautification, in accordance to which the territory reconstruction in mentioned countries is realized. It was established that reference direction of urban beautification development in mentioned countries lies in parking lots removing out of the borders of curtilage or underground parking arrangement, landscape gardening development and classification of such territories by levels of urban gardening, territory reconstruction in accordance with typical schemes of street infrastructure development, urban gardening, cycle paths, etc. It is shown that problem solution of habitable open grounds organization on city level resides in usage intensification of such territories, and on the level of residential compounds – in increasing exploitation properties of open grounds. As a result of undertaken analysis it was established that raised problem of increasing the effectiveness of residential area usage within residential areas imposes complex approach, including question of land development intensiveness, architectural and planning organization and open grounds beautification.

SPIRIT: Style-guided Patch Interaction for Fashion Image Retrieval with Text Feedback

Fashion image retrieval with text feedback aims to find the target image according to the reference image and the modification from the user. This is a challenging task, as it requires not only the synergistic understanding of both visual and textual modalities but also the ability to model a wide variety of styles that fashion images contain. Hence, the crucial aspect of addressing this problem lies in exploiting the abundant semantic information inherent in fashion images and correlating it with the textual description of style. Recognizing that style is generally situated at the local level, we explicitly define style as the commonalities and differences between local areas of fashion images. Building upon this, we propose a Style-guided Patch InteRaction approach for fashion Image retrieval with Text feedback (SPIRIT), which focuses on the decisive influence of local details of fashion images on their style. Three corresponding networks are designed pertinently. The Patch-level Style Commonality network is introduced to fully leverage the semantic information among patches and compute their average as the style commonality. Subsequently, the Patch-level Style Difference network employs a graph reasoning network to model the patch-level difference and filter out insignificant patches. By considering the above two networks, mutual information about style is obtained from the interaction between patches. Finally, the Visual Textual Fusion network is utilized to integrate visual features with rich semantic information and textual features. Experimental results on four benchmark datasets demonstrate that our proposed SPIRIT achieves state-of-the-art performance. Source code is available at https://github.com/PKU-ICST-MIPL/SPIRIT_TOMM2024 .

Remote Sensing &amp; GIS Integration Bases Evaluation of Ground Water Quality in Telangana State, India

About 85% of drinking water needs in rural and 40% drinking water needs in urban areas are met from groundwater resources in Telangana state. There is a huge demand of ground water for different uses like agriculture, drinking and industrial purposes as the command area is very low in the state and it is evidenced by the fact that around 70% irrigation is dependent on ground water sources as compared to other surface sources like Tanks/Canals/Reservoirs etc. Climate change has affected the hydrological cycle with uncertain and increased variability in rainfall followed by with high rainfall in a short span of time resulting more surface runoff which ultimately decreases there charge to groundwater. Decreased recharge to the groundwater and excess withdrawal of groundwater has accelerated the depletion of groundwater resources there by resulting in stress on groundwater regime in terms of quality as well as quantity. The groundwater quality evaluation of Telangana state is carried out by using legacy quality data (2012-14) collected from Rural Water Supply &amp; Sanitation Department, Government of Telangana. Contamination spread of groundwater is one of the most important concerns that have received attention at regional, local and global levels because of their importance on public health and its further impact in ecosystems. The spatial distribution of chemical parameters like pH, Total Dissolved Solids (TDS), Total Hardness (TH), Total Alkalinity (TA), Fluoride (F), Chloride (Cl), Iron (Fe), Nitrate (NO3) and Sulfate (SO4) are examined with respect to its contamination level. The spatial distribution and concentration of chemical elements is carried out by using spatial interpolation technique namely Inverse Distance Weightage (IDW) method from the point source data. The distribution maps reveal important information to understand the hot spot areas of the groundwater systems and for identification of potential areas for providing safe drinking water supply. Site specific water conservation and artificial recharge measures are needed to be taken up with scientific lines by using Remote Sensing &amp; GIS techniques, for enhancing the groundwater storage and also improving its quality.

Analysing Groundwater Governance in Uzbekistan through the Lenses of Social-Ecological Systems and Informational Governance

Worldwide, groundwater is often poorly understood and misgoverned due to difficulties in monitoring and collective action organisation. Problems occur due to groundwater’s invisible nature, consequent poor groundwater understanding, and systemic institutional failures. In Central Asia, groundwater coordination is important at local as well as national levels, considering regional water competition since state transitions. Historic water overuse further emphasises a need for groundwater coordination between states. Information on aquifer status is often publicly unavailable and rarely shared, even between national governmental agencies. Considering the region’s arid climate and dependence on glacial melt for seasonal flows, protection of groundwater is vital to ensure water access amid pressures such as climate change. Groundwater has historically provided drinking water, with recent increased use as an alternative water source for the agriculture sector. Institutional failures in groundwater governance can be understood as “soft limits” to adaptation in the region, which governance capacity improvements could ameliorate. To understand the current status of Central Asian groundwater governance through an illustrative case of Uzbekistan, we consider its social-ecological system, associated problems (e.g., pollution, and overexploitation), and institutional context. This paper summarises findings specific to Uzbekistan from a systematic literature review on the subject in Central Asia, outlining governance challenges and opportunities. Informational governance is analysed and reveals a clear impact on groundwater use and outcomes. They include: i) uncertainty over status (i.e., quantity and quality); ii) governance complexities at various levels due to multiple knowledges; iii) power constellations and a lack of cooperation suggest increased uncertainty; iv) interest in information reform. Public data access and coordination across the region should better support collective action at local levels, reduce governance complexities, and reduce status quo hierarchies.

Working Paper 49: Dirty deals – Case studies on corruption in waste management and trade

Waste management is a huge industry at the local, national and international levels. Public services play a key role in dealing especially with waste generated by households. Getting waste management right is essential if we are to achieve a circular economy and the Sustainable Development Goals.&#x0D; Complex legal frameworks and their weak implementation open up spaces for criminals to profit from illegally managing or trading in waste. The consequences on the environment and human health can be severe. The role of corruption in crimes involving waste is unexplored.&#x0D; An initial analysis shows the potential for corruption to play a role in:&#x0D; &#x0D; influencing policy decisions involving waste management;&#x0D; corrupt deals involving the selection of waste management companies linked to powerful elites;&#x0D; schemes to gain lucrative waste management contracts through systematic bribery;&#x0D; illegal imports of hazardous substances for profit, avoiding or suppressing formal controls.&#x0D; &#x0D; The report explores five case studies (Albania, Lebanon, North Macedonia, Canada–Philippines, US–South America) and proposes a typology of corruption patterns in crimes involving waste management and trade.

Modelling foraging strategies of honey bees as agents in a dynamic landscape representation

Introduction: Both intrinsic colony mechanisms and external environmental variables affect the honey bee colony development rates and response and a key aspect of this is the use of resources within the landscape by honey bees. Although several models have been developed to explore the foraging behaviour of bees, none fully considered the spatial and temporal dynamics of landscape resources and the role of the colony in the process. Methodology: Here, we introduce a new honey bee foraging model being developed as a part of the ApisRAM honey bee colony model. Based on agent-based modelling, we used a dynamic ALMaSS landscape model enhanced with floral resource modelling to assess the impacts of weather conditions and resource availability on the possible foraging behaviour of honey bees. Several possible mechanisms (defined, based on honey bee traits) for scouting and foraging were investigated, separately for nectar and pollen collection, including prioritising foraging polygons for nectar foraging according to their distance to the colony, the quality or the energetic efficiency and, for pollen foraging, according to their distance to the colony and pollen quantity. Results: If model foraging bees prioritised the polygons, based on their distance from the colony, the number of unsuccessful flights increased compared to other tested strategies and the total amount of sugar collected showed a high variability. Contrary to expectations, the energetic efficiency strategy did not provide the colony with the highest amount of sugar. Overall, the tested strategies provide different outcomes on the collection of resources, the number of performed flights and their success rate, evidencing that the model's outcome at the colony level arises from the individual types of behaviour. Conclusions and Relevance: Variability in the mass of collected nectar and pollen was found mostly when scout bees applied the distance strategy. This higher variability in sugar collection means that model bees were not able to find the most profitable foraging sites at the landscape level, but only at the local level. Other strategies showed less dependence on the surrounding landscape (i.e. quality or random), but it comes at a cost (i.e. lower production for both nectar and pollen collection). These outputs help us evaluate which strategies could be used for future model development and confirm the models' ability to create dynamic responses. These responses at the colony level were only possible thanks to the implementation of a dynamic landscape model and dynamic spatiotemporal resource model, as well as implementing a social communication mechanism for bees to share information about the resources. Plant nectar production and quality information is essential to predict honey bee foraging distribution. In future model development, the implementation of pollen quality should also be explored to evaluate if it influences the overall pollen collection.