Past Studies Research Articles

Metabarcoding is (usually) more cost effective than seining or qPCR for detecting tidewater gobies and other estuarine fishes.

Many studies have shown that environmental DNA (eDNA) sampling can be more sensitive than traditional sampling. For instance, past studies found a specific qPCR probe of a water sample is better than a seine for detecting the endangered northern tidewater goby, Eucyclogobius newberryi. Furthermore, a metabarcoding sample often detects more fish species than a seine detects. Less consideration has been given to sampling costs. To help managers choose the best sampling method for their budget, I estimated detectability and costs per sample to compare the cost effectiveness of seining, qPCR and metabarcoding for detecting endangered tidewater gobies as well as the associated estuarine fish community in California. Five samples were enough for eDNA methods to confidently detect tidewater gobies, whereas seining took twice as many samples. Fixed program costs can be high for qPCR and seining, whereas metabarcoding had high per-sample costs, which led to changes in relative cost-effectiveness with the number of locations sampled. Under some circumstances (multiple locations visited or an already validated assay), qPCR was a bit more cost effective than metabarcoding for detecting tidewater gobies. Under all assumptions, seining was the least cost-effective method for detecting tidewater gobies or other fishes. Metabarcoding was the most cost-effective sampling method for multiple species detection. Despite its advantages, metabarcoding has gaps in sequence databases, can yield vague results for some species, and can lead novices to serious errors. Seining remains the only way to rapidly assess densities, size distributions, and fine-scale spatial distributions.

Alcohol consumption and dependence risk among male and female Veterans: Trajectories and predictors

BackgroundWith few exceptions, previously conducted research on hazardous drinking among Veterans has employed samples in which the majority of participants identify as male. In addition, past studies have solely focused on alcohol consumption, rather than associated risk for dependence. In this study, we expanded upon the extant literature by investigating sex differences in trajectories and predictors of change in alcohol consumption and dependence risk among post-9/11 Veterans. MethodsA national sample of 1649 Veterans (50.0% female) were recruited in a five-wave longitudinal study that followed Veterans for up to 16 years after deployment. We used growth curve modeling to investigate trajectories of change in alcohol consumption and dependence risk among men and women Veterans. We examined predictors of growth, including demographics, support and resources, psychiatric symptoms, and trauma exposure. ResultsAmong male Veterans, alcohol consumption and dependence risk remained stagnant, which is in contrast to past work using non-Veteran samples. For female Veterans, consumption exhibited initial reductions that decelerated, and dependence risk reduced at a continuous rate. PTSD diagnosis was a significant predictor of individual differences in growth for men. Psychiatric symptoms (i.e., PTSD diagnosis, probable depression diagnosis, suicidal ideation) and psychosocial functioning were significant predictors of decreasing alcohol use for women. ConclusionsResults highlight important sex differences in patterns and predictors of change in alcohol consumption and dependence risk among post-9/11 Veterans. Findings are discussed in relation to screening for hazardous alcohol use and intervention strategies in this at-risk population.

Estimation of pollutant baseline concentration in Delhi city: An opportunity from coupled effect of rainfall scavenging and lockdown restriction

The accurate measurement of pollutant baseline concentration is a crucial step for robust assessment, prediction and forecasting of air pollution in any region, especially in metro cities that witness extreme high level of pollution. The present study is an attempt to fill this gap and derive the baseline concentrations of two critical air pollutants, i.e., PM2.5 and NOx in Delhi city. The study critically analyzes the data of winter period having consistent rainfall followed by complete weekend lockdown due to COVID-19. The findings indicate that the estimated baseline concentration is in the range of 20–36 μg/m3 and 12–63 μg/m3 for PM2.5 and NOx (NO + NO2), respectively during winter period of year 2022. The estimated baseline levels can be reasonably well compared with other reported values, both in the past studies as well as estimated using other referred methods. The baseline values are found higher in central areas of the city compared to outskirt located stations. The estimated baseline concentrations can be used in models for predicting the actual urban increment (actual increase in the source contribution with respect to the baseline), which will further help in decision making of target-oriented control actions.

Male reproductive output and sperm competition as indicated by gonadosomatic index in Paddlefish stocks

AbstractObjectiveWe investigated if large Paddlefish Polyodon spathula invest in testis weight disproportionately more than smaller males, as expressed by the gonadosomatic index (GSI). The approach was to assess the relation between testis weight F (i.e., the combined weight of both testes) and fish weight W in the expression F = aWb. The hypothesis was that sperm competition in Paddlefish would be expected (with b > 1) based on observations of several male fish attending a female spawner in a past study in the Osage River, Missouri.MethodsWe used a large, three‐state data set from three fisheries (Montana, North Dakota, and Oklahoma) to evaluate isometry and allometry in the power function relationship between fish weight and testis weight.ResultAll three data sets showed hyperallometric increases in testis weight with fish weight (i.e., b > 1). For Montana males, hyperallometry was greatest (b = 1.56; n = 8798), followed by North Dakota (b = 1.36; n = 8209) and Oklahoma (b = 1.22; n = 9571). Paddlefish from Montana and North Dakota had much lower testis weights through age 18 and much lower fish weights through age 25 than Oklahoma Paddlefish. By ages 17–25, mean male GSI in Oklahoma declined, whereas it remained level at about 1.5 for combined Montana and North Dakota Paddlefish. Throughout their lives, at each age, Montana and North Dakota Paddlefish allocated a higher percentage of their total weight to testis weight and reached a higher asymptotic GSI (GSI∞) than did Oklahoma Paddlefish; GSI∞ was 1.50 for Montana fish, 1.44 for North Dakota fish, and 1.26 for Oklahoma fish.ConclusionResults provide evidence supporting the occurrence sperm competition (i.e., b > 1), as would occur when two or more males compete to fertilize the eggs of a female spawning Paddlefish. Comparisons among species and stocks are made but were limited by an acute shortage of data on male testis weights and other testis characteristics (e.g., sperm size, energy content), and reproductive investment in Paddlefish and most other fishes in other localities.

Analysis of Mechanical Response of Epoxy Asphalt-Repaired Pavement in Pothole Interface on Steel Bridge Deck under Coupled Temperature-Dynamic Loading

The persistence of pothole maintenance represents an enduring challenge. Past studies have largely concentrated on the materials and techniques used for remediation, with a lack of attention given to the pothole interface. This paper employed epoxy asphalt rubber (EAR-10) as the repair material, exploring the impact of coupled temperature-dynamic loading on the mechanical response of the interface. Finite element modelling (FEM), adopting the viscoelastic characteristics of EAR-10, was deployed to investigate the mechanical response of the interface under three temperature service conditions high, medium, and low when a dynamic load traversed the pothole. The stress variations in the interface at various inclinations and thicknesses of the repair blocks were also studied. In addition, the comparative analysis of high-temperature rut resistance for powdered rubber composite-modified asphalt and SBS modified asphalt was conducted via the multiple stress examination in terms of its high-temperature resilience, resistance to moisture-induced damage, and fatigue life by employing the asphalt mixture rutting test, low-temperature bending test on small beams, and the water immersion Marshall stability test, respectively. The repair efficacy of EAR-10 was appraised through post-repair water immersion rutting tests and bending tests on composite structural small beams. The results indicated that incorporating coupled temperature-dynamic loading led to a considerable increase in stress, particularly under low-temperature service conditions. An inclination angle of 30 degrees was found to be optimal for the interface. The research methodology presented here is pertinent to guiding the pothole repair in the steel bridge pavement, ensuring the strength and durability of the interface rivals that of newly constructed layers.

Single cell-transcriptomic analysis informs the lncRNA landscape in metastatic castration resistant prostate cancer

Metastatic castration-resistant prostate cancer (mCRPC) is a lethal form of prostate cancer. Although long-noncoding RNAs (lncRNAs) have been implicated in mCRPC, past studies have relied on bulk sequencing methods with low depth and lack of single-cell resolution. Hence, we performed a lncRNA-focused analysis of single-cell RNA-sequencing data (n = 14) from mCRPC biopsies followed by integration with bulk multi-omic datasets. This yielded 389 cell-enriched lncRNAs in prostate cancer cells and the tumor microenvironment (TME). These lncRNAs demonstrated enrichment with regulatory elements and exhibited alterations during prostate cancer progression. Prostate-lncRNAs were correlated with AR mutational status and response to treatment with enzalutamide, while TME-lncRNAs were associated with RB1 deletions and poor prognosis. Finally, lncRNAs identified between prostate adenocarcinomas and neuroendocrine tumors exhibited distinct expression and methylation profiles. Our findings demonstrate the ability of single-cell analysis to refine our understanding of lncRNAs in mCRPC and serve as a resource for future mechanistic studies.

The violence of literature review and the imperative to ask new questions

Abstract Writing the literature review is not a neutral act. In fact, the key central aim of consolidating work in a particular research area is to demonstrate one’s knowledge of this area; that is, one must know the ‘conversations’ concerning the research topic. Literature review becomes violent in the Bourdieusian sense because it imposes particular configurations of privileged knowledge on researchers. Thus, in this paper, we argue that literature review is an enactment of symbolic violence and, in the process, epistemic theft, and central to this practice is the construction of research questions. Literature review, as a site of scholarly conversations, dictates the kinds of questions we ask, thus unwittingly framing our research according to the epistemic demands of past and recent studies. By asking a different set of questions, ‘new’ or different understandings about certain social phenomena may emerge.

Bias correction of OMI HCHO columns based on FTIR and aircraft measurements and impact on top-down emission estimates

Abstract. Spaceborne formaldehyde (HCHO) measurements constitute an excellent proxy for the sources of non-methane volatile organic compounds (NMVOCs). Past studies suggested substantial overestimations of NMVOC emissions in state-of-the-art inventories over major source regions. Here, the QA4ECV (Quality Assurance for Essential Climate Variables) retrieval of HCHO columns from OMI (Ozone Monitoring Instrument) is evaluated against (1) FTIR (Fourier-transform infrared) column observations at 26 stations worldwide and (2) aircraft in situ HCHO concentration measurements from campaigns conducted over the USA during 2012–2013. Both validation exercises show that OMI underestimates high columns and overestimates low columns. The linear regression of OMI and aircraft-based columns gives ΩOMI=0.651Ωairc+2.95×1015 molec.cm-2, with ΩOMI and Ωairc the OMI and aircraft-derived vertical columns, whereas the regression of OMI and FTIR data gives ΩOMI=0.659ΩFTIR+2.02×1015 molec.cm-2. Inverse modelling of NMVOC emissions with a global model based on OMI columns corrected for biases based on those relationships leads to much-improved agreement against FTIR data and HCHO concentrations from 11 aircraft campaigns. The optimized global isoprene emissions (∼445Tgyr-1) are 25 % higher than those obtained without bias correction. The optimized isoprene emissions bear both striking similarities and differences with recently published emissions based on spaceborne isoprene columns from the CrIS (Cross-track Infrared Sounder) sensor. Although the interannual variability of OMI HCHO columns is well understood over regions where biogenic emissions are dominant, and the HCHO trends over China and India clearly reflect anthropogenic emission changes, the observed HCHO decline over the southeastern USA remains imperfectly elucidated.

Modeling retroreflectivity degradation of pavement markings across the US with advanced machine learning algorithms

Retroreflectivity is the primary metric that controls the visibility of pavement markings during nighttime and in adverse weather conditions. Maintaining the minimum level of retroreflectivity as specified by Federal Highway Administration (FHWA) is crucial to ensure safety for motorists. The key objective of this study was to develop robust retroreflectivity prediction models that can be used by transportation agencies to reliably predict the retroreflectivity of their pavement markings utilizing the initially measured retroreflectivity and other key project conditions. A total of 49,632 transverse skip retroreflectivity measurements of seven types of marking materials were retrieved from the eight most recent test decks covered under the National Transportation Product Evaluation Program (NTPEP). Decision Tree (DT) and Artificial Neural Network (ANN) algorithms were considered for developing performance prediction models to estimate retroreflectivity at different prediction horizons for up to three years. The models were trained with randomly selected 80% data points and tested with the remaining 20% data points. Sequential ANN models exhibited better performance with the testing data than the sequential DT models. The training and testing R2 ranges of the sequential ANN models were from 0.76 to 0.96 and 0.55 to 0.94, respectively, which were significantly higher than the R2 range (0.14 to 0.75) from the regression models proposed in past studies. Initial or predicted retroreflectivity, snowfall, and traffic were found to be the most important inputs to model predictions.

Numerical Modelling of the Thermoforming Behaviour of Thermoplastic Honeycomb Composite Sandwich Laminates.

Lightweight component design is effectively achievable through sandwich structures; many past research studies in the aerospace and racing sectors (since the 1920s) have proven it. To extend their application into the automotive and other transport industries, manufacturing cycle times must be reduced. This can be achieved by sandwich materials made of continuous fibre-reinforced thermoplastic (CFRTP) cover layers and thermoplastic honeycomb cores. To widen the application of flat thermoplastic-based sandwich panels into complex parts, a novel forming technology was developed by the Fraunhofer Institute of Microstructure of Materials and Systems (IMWS). Manufacturing defects like wrinkling and surface waviness should be minimised to achieve high reproducibility of the sandwich components. Studying different manufacturing parameters and their influence on the final part is complex and challenging to analyse through experiments, as it is time-consuming. Therefore, a finite element (FE) modelling approach is implemented to reduce such efforts. Initially, a thermoforming model is developed and validated with experimental results to check its reliability. Further, different simulations are performed to optimise the novel sandwich-forming process. In this study, a thermoplastic sandwich made of polypropylene (PP) honeycomb core and polypropylene glass fibre (PP/GF) cross-ply as cover layers was used, and its numerical model was executed in LS-DYNA software release R11.2.1.

Characterizing Speech Errors Across Primary Progressive Apraxia of Speech Subtypes.

Apraxia of speech (AOS) is a motor speech disorder affecting articulatory planning and speech programming. When AOS is the sole manifestation of neurodegeneration, it is termed primary progressive apraxia of speech (PPAOS). Recent work has shown that there are distinct PPAOS subtypes: phonetic, prosodic, and those that do not clearly align with either (mixed). PPAOS subtypes differ with respect to the predominating motor speech difficulties, as well as disease progression and underlying pathology. Because past studies have determined PPAOS subtype based on clinical impression, the goal of the present study was to quantitatively determine the distribution of speech error types across PPAOS subtypes in a word repetition task and to investigate how word complexity affects the type and number of speech errors across PPAOS subtypes. Forty-five patients with PPAOS (13 phonetic, 23 prosodic, and nine mixed) and 45 healthy controls produced multiple repetitions of words that varied in phonetic complexity. Sound additions, deletions, and substitutions/distortions (phonetic errors) and within-word segmentations (prosodic errors) were calculated. All three PPAOS groups produced significantly more errors than controls, but the total number of errors was comparable among subtypes. The phonetic group produced more phonetic-type errors compared to the prosodic group but comparable to the mixed group. The prosodic group produced more segmentations compared to the phonetic and mixed PPAOS groups. As word complexity increased, the total number of errors increased for PPAOS patients. The phonetic and prosodic groups were more likely to produce phonetic- and prosodic-type errors, respectively, as word complexity increased. This study provides novel quantitative data showing that PPAOS subtype can be supported by the type and distribution of speech errors in a word repetition task. This may facilitate earlier, more reliable differential diagnosis and aid in disease prognosis, as PPAOS subtypes have distinct disease trajectories.

Factors Affecting the Recruitment of Foreign Migrant Workers in Taiwan: A Case Study of Vietnamese Migrant Workers

Abstract The global development has led to a huge increase in the number of cross-border mobile employment, and many advanced industrialized countries have introduced cross-border migrant workers in order to continue their economic development. Taiwan began to introduce foreign migrant workers in 1989, and has since opened up various application qualifications and quotas for migrant workers in different sectors. By the end of 2022, there were about 228,000 Vietnamese industrial migrant workers in Taiwan, which was the largest number, accounting for 45% of the total number. Therefore, this study discusses the distribution of countries from which Taiwan imports foreign workers and the countries to which Vietnam exports workers, and compares and analyzes the relevant laws and policies of Taiwan government and Vietnamese government. In addition, issues related to migrant worker policies and human resources agencies are discussed through in-depth interviews with human resources agents and questionnaires on Vietnamese migrant workers in Taiwan. Although many past studies focused on foreign workers, in recent years, the demand for industrial workers has changed due to the pandemic, and Taiwan has faced low birth rate, aging and other factors, which has also impacted the labor supply in the job market. Under this situation, the problem of labor shortage may become more serious. Therefore, this study also analyzes the influence of pandemic and other related factors, hoping that the research results can provide references for related fields of industry, official and university. JEL classification numbers: E24, J21, J48. Keywords: Migrant worker policies, Human resources agencies, In-depth interviews.

TFFNet: A robust approach with anti-noise and domain shift adaptation for intelligent fault diagnosis of rotating machinery

Recently, deep learning has been a predominantly used technique for intelligent fault diagnosis of industrial machines. It has accomplished satisfactory performance as well. However, noise is present in a real-life industrial working environment, and the operational load also constantly changes. This work proposes a Time-Frequency Fusion Network (TFFNet) for intelligent fault diagnosis. It is robust convolutional neural network based deep-learning algorithm and eliminates the signal processing required for denoising. The success of the developed model is verified in the presence of real-time noisy conditions and under a load-varying environment. The proposed model attained 99.98% accuracy in a noisy environment and 98.6% average accuracy under six cases of domain shift. Finally, the results are compared with past studies using accuracy as a performance indicator.

Making a case for nature‐based solutions for a sustainable built environment in Africa

AbstractThe potential of using nature‐based solutions to address issues of climate change has continued to gain momentum, especially in developed nations. However, the same cannot be said for developing countries, particularly in Africa, where the knowledge and awareness of natural solutions are low, and research on their application within the built environment is scant. Using a sciento‐metric and narrative review of published literature, this paper makes a case for research exploration on nature‐based solutions for a sustainable built environment in Africa. The findings revealed an opportunity for significant research contributions on nature‐based solutions in addressing flood risk management, climate change and urban planning, water quality and carbon emission, sustainable development, and green infrastructure and urban development. These areas are the critical focus of past studies explored. Also, the findings offer guidance for further studies to be conducted in less explored areas, such as carbon sequestration, greenhouse gases, energy utilisation, indoor comfort, and numeric models for using nature‐based solutions within the African context. The findings of the study offer an excellent theoretical background to direct researchers and practitioners who seek to attain and promote sustainable built environments through nature‐based solutions, especially in Africa.

A benchmarking study on existing communities of practice in higher education institutions: A comparison between Europe and US

ABSTRACT This study explores the establishment of communities of practice within teaching and learning centres (TLC) as strategies for advancing faculty development in higher education, examining their implementation in the US and Europe, with a specific focus on Italy. Utilising organisational benchmarking, we employed an explanatory, comparative, and best practice approach to map existing communities of practice within TLCs. Our sample included 334 centres in the US, 37 in Europe, and 13 in Italy. Findings reveal active communities, particularly in the US, attributed to a longer history of faculty development research within TLC initiatives. The prevalence of individual and formal training approaches highlights a need for increased cooperation strategies to build more cohesive communities of practice. These results align with past studies demonstrating the effectiveness of such communities, suggesting the potential for broader global networks.

How does trade policy uncertainty affect green innovation in the USA and China? A nonlinear perspective.

Green innovations are the most critical factor in promoting environmental sustainability worldwide. Trade can speed up the adoption of green innovations by facilitating the transfer of information, skills, and technology. However, trade policy uncertainty can create significant challenges for businesses investing in eco-innovations, leading to increased risk, reduced investment, and slower progress toward sustainable technologies. Recently, a growing number of researchers have shown their interest in finding the factors that can impact green innovations, but none have investigated the influence of trade policy uncertainty on green innovations in the USA and China. In addition, none of the past studies has relied on the nonlinear assumption. This analysis fills these gaps by examining the nonlinear impacts of trade policy uncertainty on eco-innovations in China and the USA over 2000Q1-2021Q4 by employing a nonlinear ARDL model. The finding reveals that a positive shock in trade policy uncertainty results in a decrease in green innovation in the USA and China, while a negative shock in trade policy uncertainty leads to an increase in green innovation in the USA over the long run. The nonlinear models also indicate that a positive shock in trade policy uncertainty harms green innovation in both the USA and China in the short run. The robustness of these results is confirmed by the NQARDL model, which confirms that an upsurge in trade policy uncertainty lowers green innovation in most quantiles in the USA and China in the short and long run. Conversely, negative shocks in trade policy uncertainty stimulate green innovation at most quantiles in both China and the USA, in the short and long run. Thus, policymakers need to consider the potential impact of trade policies on eco-innovations and work to create stable and predictable trade environments that support the growth of renewable technologies and other sustainable solutions.

Natural History of Secundum ASD in Preterm and Term Neonates: A Comparative Study.

Atrial septal defects(ASDs) are common in neonates. Although past studies suggest ASDs ≥ 3mm in term neonates(TNs) are less likely to close, there is paucity of data regarding the natural history in preterm neonates(PNs), information that would inform surveillance. We sought to compare spontaneous closure rates and need for intervention for ASDs in TNs/near term (≥ 36weeks) versus PNs (< 36weeks). We included all TNs and PNs who underwent echocardiography at ≤ 1month between 2010 and 2018 in our institution with an ASD ≥ 3mm, without major congenital heart disease, and with repeat echocardiogram(s). Spontaneous resolution was defined as size diminution to < 3mm or closure. We included 156 TNs (mean gestational age at birth 38.6 ± 1.4weeks) and 156 PNs (29.6 ± 3.7weeks) with a mean age at follow-up of 16 ± 19 and 15 ± 21months, respectively (p = 0.76). Based on maximum color Doppler diameter, in TNs, ASD resolution occurred in 95% of small (3-5mm), 87% of moderate (5.1-8mm), and 60% of large (> 8mm) defects; whereas, in PNs, resolution occurred in 79% of small, 76% of moderate, and 33% of large ASDs. There was a significant association between size and ASD resolution in TNs (p = 0.003), but not PNs (p = 0.17). Overall, ASD resolution rate was higher in TNs (89%) versus PNs (78%) (p = 0.009), and fewer TNs (1%) compared to PNs (7%) required ASD intervention (p = 0.02). Most ASDs identified in TNs and PNs spontaneously resolve. PNs, however, demonstrate lower ASD resolution and higher intervention rates within all size groups. These data should inform follow-up of affected neonates.

Investigating Preschoolers’ Perspectives on Aggression Through Observation and Video-Stimulated Recall

ABSTRACT This article explores video-stimulated recall as a novel approach to understanding children’s decisions to engage in relational and physical aggression. Past studies have relied on caregiver and observer reports to investigate children’s social behaviors, omitting children’s experience and interpretation of their own behavior. Within this Australian study, 68 children age 3 to 5 years were assessed for relational aggression by teachers. Nine children identified by teachers with high relational aggression and seven children identified with average levels of relational aggression were video recorded while engaging in free play. Immediately afterward, video footage of the child engaging in aggressive behavior was shown to the child to stimulate recall of the reasons for their behavior. Subsequent analysis were focused on assessing the intentions and functions of children’s aggressive behaviors, as reported by the child. Focusing on children’s own interpretations enabled a more nuanced and accurate understanding of the child’s social cognitive processes about the intent and functions of their aggression. We demonstrate that video observations alongside video-stimulated interviews can be used to effectively elicit children’s interpretations of their own behaviors. Incorporating children’s perspectives in research and practice has several implications, such as improving communication between children and adults and fostering children’s self-reflective awareness.

An Analysis of the Subjective Well-Being in the Italian Regions Through an ANN Algorithm

AbstractThis research aims to analyze the determinants of subjective well-being in the Italian regions. To this extent, a new ISTAT-BES database has been used, with data for the Italian regions between 2004 and 2021. An artificial neural network (ANN) experiment was conducted to explore the link among these variables. Empirical findings show that subjective well-being is positively associated with education, income, and social relations. Our results align with those provided by past studies on the determinants of subjective well-being. These results imply that governments should improve subjective well-being by increasing the level of investment in education, deepening economic growth, reducing income inequality, and promoting social relations.

Sri Lankan Contribution to Climate Change by Enteric Fermentation of Large Ruminants: An Overview

&#x0D; &#x0D; &#x0D; The Sri Lankan livestock sector (LS) which is essential to rural households' food systems and means of subsistence, contributed to 0.6% of the GDP in 2020. The cattle industry has contributed &lt;40% to the LS. The objective of the review was to determine how Sri Lankan LS, especially ruminants contributed to climate change (CC) by emitting greenhouse gasses (GHG). In the year 2020, in total there were 1 426 570 cattle, including neat cattle and buffaloes. Sri Lanka has experienced various impacts of CC as it is a tropical island in the Indian Ocean. The cattle industry is involved in CC directly and indirectly. Global warming (GW) is a predominant factor in CC. The emission of GHG in different ways is a root cause of GW. As a GHG, 17% of methane emissions in the atmosphere are accounted by the enteric fermentation of ruminants, especially by the large ruminants; cattle, and buffaloes. It is a complex process that occurs within the fore stomach (rumen) of ruminants where gases are released outside via a process called eructation. As a GHG, methane (CH4) contributes to GW 28 times higher than carbon dioxide produced in large ruminants by enteric fermentation. In Sri Lanka, the majority of the local indigenous cattle and buffaloes are used to eat low-quality grasses, straws, and other roughage which significantly increases the emission of CH4. A past study revealed that the CH4 emission factor estimated according to the IPCC (2006) Tier 2 methodology for an improved dairy cattle is 42 kg /head /year while a local dairy cow is 52 kg /head /year and 65 kg /head /year for dairy buffalo in Sri Lanka and the values are lower compared to default emission factors given by the IPCC (2006). The expected temperature rise in Sri Lanka, which would be primarily caused by GHG, will be slightly less than the average worldwide. However, the highest emission scenario predicts a 2.9o C–3.5o C increase in temperature by the 2090s. Therefore, instead of focusing solely on production, it is important to investigate measures to minimize GHG emitted by large ruminants under local management conditions.&#x0D; Keyword: Climate change, Enteric fermentation, Livestock, Methane&#x0D; &#x0D; &#x0D;