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In view of the consensus that climate change is happening, scientists have documented several findings about Uganda’s recent climate, as well as its variability and change. The purpose of this study is to review what has been documented, thus it gives an overview of what is known and seeks to explain the implications of a changing climate, hence what ought to be known to create a climate resilient environment.

Terms such as “climate”, “climate change” and “climate variability” were identified in recent peer-reviewed published literature to find recent climate-related literature on Uganda. Findings from independent researchers and consultants are incorporated. Data obtained from rainfall and temperature observations and from COSMO-CLM Regional Climate Model-Coordinated Regional Climate Downscaling Experiment (CCLM CORDEX) data, European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Re-Analysis (ERA-Interim) data and Global Precipitation Climatology Centre (GPCC) have been used to generate spatial maps, seasonal outputs and projections using GrADS 2.02 and Geographic Information System (GIS) software for visualization.

The climate of Uganda is tropical in nature and influenced by the Inter-Tropical Convergence Zone (ITCZ), varied relief, geo-location and inland lakes, among other factors. The impacts of severe weather and climate trends and variability have been documented substantially in the past 20-30 years. Most studies indicated a rainfall decline. Daily maximum and minimum temperatures are on the rise, while projections indicate a decrease in rainfall and increase in temperature both in the near and far future. The implication of these changes on society and the economy are discussed herein. Cost of inaction is expected to become huge, given factors like, the growing rate of the population and the slow expanding economy experienced in Uganda. Varied forms of adaptation to the impacts of climate change are being implemented, especially in the agricultural sector and at house hold level, though not systematically.

This review of scientific research findings aims to create a better understanding of the recent climate change and variability in Uganda and provides a baseline of summarized information for use in future research and actions.

The empirical literature on climate change and agriculture does not adequately address the issue of potential endogeneity between climatic variables and agriculture, which makes their estimates unreliable. This paper aims to investigate the relationships between climate change and agriculture and test the potential reverse causality and endogeneity of climatic variables to agriculture.

This study introduces a geographical instrument, longitude and latitude, for temperature to assess the impact of climate change on agriculture by estimating regression using IV-two-stage least squares method over annual panel data for 60 countries for the period of 1999-2011. The identification and F-statistic tests are used to choose and exclude the instrument. The inclusion of some control variables is supposed to reduce the omitted variable bias.

The study finds a negative relationship between temperature and agriculture. Surprisingly, the magnitude of the coefficient on temperature is mild, at least 20 per cent, as compared to previous studies, which may be because of the use of the instrumental variable (IV), which is also supported by an alternative robust measure when estimated across different regions.

The study provides strong implications for policymakers to confront climate change, which is an impending danger to agriculture. In designing effective policies and strategies, policymakers should focus not only on crop production but also on other agricultural activities such as livestock production and fisheries, in addition to national and international socio-economic and geopolitical dynamics.

This paper contributes to the growing literature in at least four aspects. First, empirical settings introduce an innovative geographical instrument, Second, it includes a wider set of control variables in the analysis. Third, it extends previous studies by involving agriculture value addition. Finally, the effects of temperature and precipitation on a single aggregate measure, agriculture value addition, are separately investigated.

The purpose of this paper is to understand local perceptions on climate change and its impacts on biodiversity, rangeland, agriculture and human health.

A household survey with 300 interviewees and focus group discussions with key stakeholders were conducted and validated at two steps, using the climate data from the nearest weather stations and reviewing literatures, to correlate the local perceptions on climate change and its impacts.

Majority of the respondents reported an increase in temperature and change in the precipitation pattern with increased hazardous incidences such as floods, avalanches and landslides. Climate change directly impacted plant distribution, species composition, disease and pest infestation, forage availability, agricultural productivity and human health risks related to infectious vector-borne diseases.

Because of the remoteness and difficult terrain, there are insufficient local weather stations in the mountains providing inadequate scientific data, thus requiring extrapolation from nearest stations for long-term climate data monitoring.

The research findings recommend taking immediate actions to develop local climate change adaptation strategies through a participatory approach that would enable local communities to strengthen their adaptive capacity and resilience.

Local knowledge-based perceptions on climate change and its impacts on social, ecological and economic sectors could help scientists, practitioners and policymakers to understand the ground reality and respond accordingly through effective planning and implementing adaptive measures including policy formulation.

This research focuses on combining local knowledge-based perceptions and climate science to elaborate the impacts of climate change in a localised context in Rakaposhi Valley in Karakoram Mountains of Pakistan.

The purpose of this paper is to review cases of artificial reefs built through additive manufacturing (AM) technologies and analyse their ecological goals, fabrication process, materials, structural design features and implementation location to determine predominant parameters, environmental impacts, advantages, and limitations.

The review analysed 16 cases of artificial reefs from both temperate and tropical regions. These were categorised based on the AM process used, the mortar material used (crucial for biological applications), the structural design features and the location of implementation. These parameters are assessed to determine how effectively the designs meet the stipulated ecological goals, how AM technologies demonstrate their potential in comparison to conventional methods and the preference locations of these implementations.

The overview revealed that the dominant artificial reef implementation occurs in the Mediterranean and Atlantic Seas, both accounting for 24%. The remaining cases were in the Australian Sea (20%), the South Asia Sea (12%), the Persian Gulf and the Pacific Ocean, both with 8%, and the Indian Sea with 4% of all the cases studied. It was concluded that fused filament fabrication, binder jetting and material extrusion represent the main AM processes used to build artificial reefs. Cementitious materials, ceramics, polymers and geopolymer formulations were used, incorporating aggregates from mineral residues, biological wastes and pozzolan materials, to reduce environmental impacts, promote the circular economy and be more beneficial for marine ecosystems. The evaluation ranking assessed how well their design and materials align with their ecological goals, demonstrating that five cases were ranked with high effectiveness, ten projects with moderate effectiveness and one case with low effectiveness.

AM represents an innovative method for marine restoration and management. It offers a rapid prototyping technique for design validation and enables the creation of highly complex shapes for habitat diversification while incorporating a diverse range of materials to benefit environmental and marine species’ habitats.

This study aims to introduce a deep neural network (DNN) to estimate the effective thermal conductivity of the flat heat pipe with spreading thermal resistance.

A total of 2,160 computational fluid dynamics simulation cases over up to 2,000 W/mK are conducted to regress big data and predict a wider range of effective thermal conductivity up to 10,000 W/mK. The deep neural networking is trained with reinforcement learning from 10–12 steps minimizing errors in each step. Another 8,640 CFD cases are used to validate.

Experimental, simulational and theoretical approaches are used to validate the DNN estimation for the same independent variables. The results from the two approaches show a good agreement with each other. In addition, the DNN method required less time when compared to the CFD.

The DNN method opens a new way to secure data while predicting in a wide range without experiments or simulations. If these technologies can be applied to thermal and materials engineering, they will be the key to solve thermal obstacles that many longing to overcome.

Cognitive computing is part of AI and cognitive applications consists of cognitive services, which are building blocks of the cognitive systems. These applications mimic the human brain functions, for example, recognize the speaker, sense the tone of the text. On this paper, we present the similarities of these with human cognitive functions. We establish a framework which gathers cognitive functions into nine intentional processes from the substructures of the human brain. The framework, underpins human cognitive functions, and categorizes cognitive computing functions into the functional hierarchy, through which we present the functional similarities between cognitive service and human cognitive functions to illustrate what kind of functions are cognitive in the computing. The results from the comparison of the functional hierarchy of cognitive functions are consistent with cognitive computing literature. Thus, the functional hierarchy allows us to find the type of cognition and reach the comparability between the applications.

The COVID-19 pandemic has prompted the fast growth of online music festivals. This paper explores how festivalgoers' experience affects their satisfaction and drives their loyalty to re-attend online music festivals in China.

Based on an understanding of the music festival experience and the characteristics of live-streamed performances, this paper investigates five factors that affect festivalgoers' satisfaction and loyalty, namely the music experience, ambience experience, separation experience, social experience and novelty experience. The relationships between festivalgoers' experience, satisfaction and loyalty are also explored using structural equation modelling techniques.

The empirical results suggest that four of the above-mentioned five factors of the online music festival experience directly affect festivalgoers' satisfaction and loyalty. The online mode is a rapid adaptation of and preferred alternative to offline music festivals, whilst the creation of the experience, along with satisfaction with and loyalty to the online music festival, are determined by different factors compared to offline modes. Overall festival satisfaction positively enhances the relationship between festivalgoers' experience and loyalty to online music festivals.

This study offers a range of practical and managerial implications for organisers of online music festival, similar activities such as live-streaming concerts and stage performances and hybrid events.

This study explores a phenomenon that has evolved quickly since COVID-19 and will, potentially, have an ongoing and enduring impact on the music festival sector. It differentiates the understanding of festivalgoers' experience in online and offline modes, which is a new addition to the literature. It also enriches the theoretical understanding of the experience of, satisfaction with and loyalty to online music festivals.

The purpose of this paper is to present a quantitatively supported explanation of the intellectual development, the schools of thought and the sub-areas of the food cold chain (FCC) research to derive meaningful avenues for future research.

This study builds on bibliometric analysis and network analysis to systematically evaluate a sample of 1,189 FCC articles published over the past 25 years. The descriptive statistics and science mapping approaches using co-citation analysis were performed with VOSviewer software.

The findings reveal a state-of-the-art overview of the top contributing and influential countries, authors, institutions and articles in the area of FCC research. A co-citation analysis, coupled with content analysis of most co-cited articles, uncovered four underlying research streams including: application of RFID technologies; production and operation planning models; postharvest waste, causes of postharvest wastage and perishable inventory ordering polices and models; and critical issues in FCC. Current research streams, clusters and their sub-themes provided meaningful discussions and insights into key areas for future research in FCC.

This study might reshape practitioners’, researchers’ and policy-makers’ views on the multifaceted areas and themes in the FCC research field, to harness FCC’s benefits at both strategic and tactical level. Finally, the research findings offer a roadmap for additional research to yield more practical and modeling insights that are much needed to enrich the field.