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Given the heightened importance of revolutionising 4D BIM-based construction scheduling in modular construction, it has become vital to explore how 4D-BIM could be integrated with the lean concept. Therefore, this research aims to develop a lean-integrated process model to revolutionise the 4D BIM-based construction scheduling in modular construction projects. A case study approach was used to obtain the data. The data was obtained using semi-structured interviews with construction scheduling professionals, site observations, and extracts from the BIM model used within the selected case in the UK. Findings showed that conventional (component/object based) 4D BIM supersedes conventional scheduling methods in terms of foreseeing potential implications during design and construction. The findings also showed that lean-integrated 4D BIM in modular construction have different considerations when compared with component/object-based scheduling. A lean-integrated 4D BIM process model was developed from the analysis and it was validated using an interactive workshop with eight participants from two UK construction companies and two modular construction manufacturers. The developed process model identified a number of considerations for 4D BIM in modular projects including constructability, operations, health and safety risks and time. This study suggested the further potential of 4D BIM in scheduling for modular construction projects. [ABSTRACT FROM AUTHOR]

Purpose: Technology challenges have been recognized as one of the growth retarding factors of Small and Medium Enterprises (SMEs), which further reduced their potential contribution to the national economy. Hence, this research aims to study the Sri Lankan agribusiness SMEs' overall perception of institutional support towards facing technology challenges. Research Method: A qualitative case study-based methodology was adopted, and a series of key informant interviews were held with 10 SME owners in the Agribusiness sector, using purposive sampling. An indepth thematic area analysis was used to analyze the data gathered from the interviews and identified five technology challenges faced by SMEs. Findings: SMEs repeatedly stated weak financial base, lack of technical know-how, lack of institutional support, and practical problems that arose when commercializing new products. Many respondents showed a low tendency towards adopting E-Commerce/M-Commerce/E-Marketing and database management systems. The study revealed that they had built network partnerships with other SMEs in the industry on their own. Most SMEs are currently facing difficulties in connecting with Multi-National Companies (MNCs)/Trans-National Companies (TNCs)/Large-scale companies. According to the SMEs' overall perception of institutional support, many had low satisfaction in most of the areas. Originality/value: This study is important for the government institutions and relevant policymakers to identify the requirements of SMEs, and thereby, organize customized supportive programs to overcome technology challenges. [ABSTRACT FROM AUTHOR]

The CYN degradation kinetics of each bacterial species were studied using High Performance Liquid Chromatography. The greatest CYN degradation (28.22 ± 0.24%) was shown by the bacterium B. cereus-S in 5.0 mg/L CYN within 14 days. The CYN degradation by the other strains was lower than 10% under the same conditions. Further studies employing different initial concentrations of CYN revealed that B. cereus-S could degrade lower CYN concentrations at a higher percentage (1.0 mg/L, 2.5 mg/L, and 5.0 mg/L of CYN removal percentages were 36.83 ± 2.43%, 32.25 ± 1.25%, and 24.72 ± 0.40%, respectively, after 14 days of incubation at 28℃ and pH 7). The maximum average degradation rates were recorded for 1.0 mg/L, 2.5 mg/L, and 5.0 mg/L CYN on the 6th (0.05 ± 0.00 mg/L/day), 8th (0.04 ± 0.01 mg/L/day), and 12th (0.02 ± 0.01 mg/L/day) days of incubation, respectively. The study showed the potentiality of the bacterium B. cereus-S on the application for degrading CYN among the tested bacteria species. [ABSTRACT FROM AUTHOR]

The challenges of historic building adaption for reuse are well documented and often refer to building fabric, listed status, historical significance, environmental sustainability, and structural layout as limitations to their successful re-development. However, few studies have explored how such issues manifest in the operational use of historic buildings developed for reuse, the significance on cities, and the long-term socioeconomic value. This study proposes a stewardship-based strategy to manage facilities to improve the socioeconomic value of historic buildings and support the socioeconomic demand in cities and territories. Within the context of a selected case study in the UK, a mixed-method approach was used to attain the data. Quantitative evidence, using a questionnaire survey with building users, and qualitative evidence, using semi-structured interviews with the facility management team, are presented. The results suggest that historic buildings are empowered by an organisational stewardship strategy, resulting in an acceptable operational compromise that involves an acceptance of building issues and their impact on the building users' experience, and this can support the more operational adaption of facilities by the facility management team. The research proposes a stewardship-based strategy to support an improved socioeconomic value by incorporating user perspectives while ensuring a less preservation-centred and a more flexible-oriented approach towards managing facilities in historic buildings. This study constructively forms a base for further research into facility management strategies in historic buildings and their impact on cities' needs. [ABSTRACT FROM AUTHOR]

Lung cancer, a leading cause of cancer-related deaths worldwide, necessitates early detection and effective management tools. This research introduces an assistive system leveraging machine learning to identify risk factors and prioritize treatments based on severity. Critical sociodemographic data, like age, gender, and smoking history, enable accurate risk assessment and personalized profiles. The system adapts to lifestyle changes post-diagnosis, offering tailored healthcare solutions. Integrating Mask RCNN, a deep learning algorithm for medical imaging, enhances lung cancer diagnosis precision and treatment strategies. The user-friendly interface allows healthcare providers, caregivers, and patients easy access via mobile or computer applications. The implementation includes natural language processing for questionnaires and data preprocessing. The system's design consists of three components: front-end interface, back-end server, and Mask R-CNN for tumor identification. Correlation analysis for patient prioritization to generate a list. The proposed system aims to revolutionize lung cancer care, delivering accurate risk assessments, personalized treatment plans, and continuous monitoring, ultimately improving patient outcomes and saving lives. [ABSTRACT FROM AUTHOR]

Rice (Oryza sativa L.) is the staple food in Sri Lanka and phosphorus (P) and potassium (K) are major nutrients for the rice plant. However, the variation of P and K contents (mg kg-1) in rice soils and rice grains as affected by agro-climatic zones (ACZs), water source used (i.e., major irrigation, minor irrigation and rain-fed) and cropping systems adopted (i.e., fallow, vegetable, perennials, other field crops) by Sri Lankan farmers are not well elucidated, and are thus investigated in the present study. A total of 200 rice soil and 230 rice grain samples across the country were collected from farmer fields, representing different ACZs, water sources used, and cropping systems adopted using a stratified random sampling approach. The total and available P and K contents in rice soil, and the P and K contents in rice grains were determined. The plant-available P contents in soil were similar among ACZs, water sources, and rice-based cropping systems. Exchangeable K content was higher in rice fields where vegetables were cultivated in the previous season. Grain P and K contents were similar among the water sources used and rice-based cropping systems. Grain P contents was the lowest in the Low country Wet zone. Soil available-P and total-P contents (r = 0.29, p < 0.0001), and grain P and K contents were positively correlated (r = 0.51, p < 0.0001). The knowledge generated in the present study is important in P and K nutrient management in rice cultivation in the country. [ABSTRACT FROM AUTHOR]

The transportation problem (TP) is a significant factor in operational research. Numerous researchers have put forth various solutions to these problems. The goal is to reduce the overall cost of distributing resources from multiple sources to numerous destinations. If there are road risks (snow, flood, etc.), traffic limitations, etc., it might not be feasible to transport products from one place to another. In these circumstances, the appropriate route(s) can be given an extremely high unit cost, such as M (or ∞). Following that, a specific case of the prohibited transportation problem is introduced. Therefore, the focus of this study is to provide a novel algorithm that will reduce the cost of restricted transportation problems. With a few modifications, the traditional Vogel approach has been enhanced. The proposed method would perform better than the other approaches now in use. The numerical problem is resolved to demonstrate the effectiveness of the proposed approach and make comparisons with different approaches already in use. [ABSTRACT FROM AUTHOR]

Inspired by multiple benefits, including competitive advantages from developing resilient supply chains, this study was designed for the development of effective assessment models to evaluate Supply Chain Capabilities (SCC), improving resilience in Industrialised Construction (IC) in one of the high-density cities: Hong Kong (HK). First identifying appropriate SCC, this study aimed to develop multi-stage-mathematical models to evaluate the adoption of SCC of IC in HK. Experts' judgements were solicited and analysed using fuzzy synthetic evaluation. Forty-one measurement items were grouped under nine critical SCC components, and their 'importance' and 'current practice' indices were determined. The importance index of SCC is high, spotlighting the significance of the contribution of SCC to resilience whereas the current practice index is comparatively low, highlighting the dire need to bridge this gap with capability improvements. To the authors' knowledge, these evaluation models are the first set of structured models designed to assess SCC of IC, providing valuable insights to practitioners for well-informed decision-making in formulating strategies to initiate and nurture resilient supply chains in IC in HK. [ABSTRACT FROM AUTHOR]

Amid the epoch of global overpopulation, the agroforestry system can intervene as a novel practice that can safeguard agricultural sustainability, provide a means of livelihood, yield ecological benefits, and contribute to household food security. However, the adoption of sustained agroforestry practices requires an understanding of both farmers' personal characteristics and perceived statuses, constituting a difficult task to anticipate, analyze, and visualize. To this end, it is crucial to understand and identify the most significant factors driving the adoption of agroforestry. This research attempts to examine the determinants and psychological drivers of smallholder farmers' intention to plant trees on farmland and the factors that may discourage them from doing so. The conceptual framework of the study was developed based on the theory of planned behavior. We draw on survey data from 400 smallholder farmers in a northern irrigated plain of Pakistan. A binary logistic regression model was employed to explore how socio-psychological drivers influence farmers' decision to adopt agroforestry practices. The study results reveal that 60.5% of the respondents prefer to adopt agroforestry practices. The results from a logit estimation showed that socio-economic variables such as family size, land ownership, subsidies, livestock rearing, sources of energy, and total income had a significant positive influence on the planting of trees on farmland, while age had a negative influence. Moreover, runoff control and the control of heat significantly affect the perceptions of farmers regarding the adoption of agroforestry. The findings suggest that implementing policies that enhance the delivery of robust agricultural extension services and training programs for farmers could disseminate the agroforestry system countrywide, which might offer substantial benefits for farmers in the long term while maintaining environmental integrity. [ABSTRACT FROM AUTHOR]

This study examined and analyzed the contribution of forestry sector on the Nigerian economy and the factors affecting the contribution of forestry Sector on the Economy in Nigeria. Data was sourced from National Bureau of Statistics and the Central Bank of Nigeria for the period of 1970–2015. The data collected was analyzed using unit root test and multiple regression analysis. The study found that population, crop production, oil sector, and forestry sector have significant positive impact on economy while inflation has significant adverse effect on the economy. The study further found that rural and urban population, permanent cropland and net forest depletion are the main factors affecting sustainable forestry contribution significantly and negatively. Therefore, the main factors affecting forestry sector contribution to the national economy were rapid human population growth in both rural and urban areas, arable land, permanent cropland, and net forest depletion. It was based on these that we recommended that the present practice of accepting forestry as public venture is not ideal. The private firms and industries that derived their raw materials from the forest should be made to pay back some of their considerable profits to forest regeneration programs. [ABSTRACT FROM AUTHOR]

The prevailing wisdom in scholarly and policy-making institutions dealing with public health is that skillful use of price and taxation policy will reduce the prevalence of tobacco consumption because of the inverse relationship between tobacco price and consumption. Empirical evidence of this axiomatic inverse relationship has been sparse. This paper analyzes the effects of increased taxation on consumption of tobacco products in 162 countries during 2005-2020. Results indicate that there is weak negative relationship between change in adult smoking prevalence and change in taxation suggesting that higher tax rates on tobacco products tend to lower adult smoking prevalence, but in a modest rather than robust sort of way. The small negative association indicates that perhaps it will take very large tax increases to meaningfully affect adult smoking. [ABSTRACT FROM AUTHOR]

Heat pump drying systems require a method to change the inflow air temperature of the drying chamber. Pulse-widthmodulation (PWM) technique with duty cycle provides a measure of controlling the voltage supplied to the electric motors. Therefore, we conducted this research to PWM control a heat pump dryer to change the air circuit parameters. In the Parallel-Flow condensers, inlet and outlet temperatures, and relative humidity, data were collected, and the average temperature values were recorded. The duty cycle was changed by developing a program using the Python programming language. An Excel-based psychrometric calculator was developed to analyze the collected data. The average condenser outlet temperatures were 56.6±0.1 °C, 54.9±0.1 °C, and 52.6±0.1°C, and the average condenser inlet temperatures were 43.2±0.0 °C, 42.8±0.1 °C, and 41.2±0.1 °C for 60%, 80%, and 100% duty cycles, respectively. The power consumption rate of the condenser reduced with an increasing duty cycle. The results concluded that the PWM control system is a viable method to control the inflow air temperature to the drying chamber. [ABSTRACT FROM AUTHOR]

Given the heightened imperatives for supply chain resilience (SCR) in industrialized construction (IC) in Hong Kong, this study modeled the dynamic impact of supply chain vulnerabilities (SCVs) and supply chain capabilities (SCCs) on IC supply chains. The data collected through expert surveys, interviews, and case studies were analyzed using social network analysis (SNA) and system dynamics modeling (SDM) to develop the research models. Onsite assembly was identified as the most vulnerable supply chain phase, and anticipation as the most influential capability. Further, the use of an interoperable smart software package and other suggested strategies were shown to enhance IC's resilient capabilities. As key practical contributions, these findings provide evidence-based insights for adopting well-focused performance-enhancing measures to achieve SCR in IC. Moreover, this is the first initiative to explore the potential applications of SDM and SNA to assess IC supply chain dynamics, targeting a goal of enhanced resilience. This study, therefore, contributes substantially to the IC and SCR knowledge domains. Findings should also motivate and provide insights for scholars pursuing similar industry-specific improvements in other jurisdictions. [ABSTRACT FROM AUTHOR]

The objective of this study is to investigate the nexus between financial development (FD) in economic growth (GROWTH) in developing countries. The study uses panel data from 138 developing countries during the period 1980-2018. The relationship between financial development and economic growth is investigated using four explanatory variables that are commonly used to measure the level of financial development and several other control variables, including a dummy variable representing the financial and banking crises. The sample of 138 developing countries is also classified into six geographic regions. We have carried out panel unit-root tests and panel cointegration tests before estimating the specified models using both Panel Least Squares (Panel LS) and Panel Fully Modified Least Squares (FMOLS) methods. In addition, panel Granger causality tests have been conducted to identify the direction of causality between FD and GROWTH for each of the regions. The results of the study provide evidence of a direct relationship between FD and GROWTH in developing countries. Furthermore, there is evidence of bi-directional causality running from FD to GROWTH and from GROWTH to FD in samples of Europe and Central Asia, South Asia, and all countries, but not in East Asia and Pacific, Latin America and the Caribbean, Middle East and North Africa, and Sub-Saharan Africa. [ABSTRACT FROM AUTHOR]

Various environmental, economic and health problems have arisen in the world due to the continuous application of N-fertilisers for crop production, especially in the third world countries. The current study was undertaken to develop effective rhizobial inoculants for three major legume crops in Sri Lanka, namely Vigna mungo, Vigna radiata and Glycine max to replace the application of nitrogen fertilisers. Rhizobial isolates were obtained from the root nodules of different cultivars of edible legumes, non-edible wild legumes and wild relatives of Vigna spp. Authentication and screening for effectiveness of the isolates were carried out, and five strains were selected as effective isolates and cross inoculated with the three legumes along with a stress tolerant strain, which was previously screened. A pot experiment was followed by a field trial in the dry zone of Sri Lanka under farmers' conditions as single and multi-strain inoculations. The results of the pot experiment indicated that the addition of rhizobial inoculants increased the growth performance in all treatments. In the field trial, both single and multi-strain inoculants gave significant increases in yield, compared to N-fertiliser application in all three crops, viz; an increase of the yield from 3 % to 39 % in V. mungo, 5 % to 14 % in V. radiata, and 4 % to 13 % in G. max. In conclusion, the current study has shown that single and multi-strain rhizobial inoculants are capable of completely replacing urea application to V. mungo, V. radiata and G. max, in Sri Lanka without any yield reduction. [ABSTRACT FROM AUTHOR]

Emerging renal biomarkers (e.g., kidney injury molecule-1 (KIM-1) and neutrophil gelatinaseassociated lipocalin (NGAL)) are thought to be highly sensitive in diagnosing renal injury. However, global data on reference intervals for emerging biomarkers in younger populations are lacking. Here, we aimed to determine reference intervals for KIM-1 and NGAL across a pediatric population in Sri Lanka; a country significantly impacted by the emergence of chronic kidney disease of unexplained etiology (CKDu). Urine samples were collected from children (10-18 years) with no prior record of renal diseases from the dry climatic zone of Sri Lanka (N = 909). Urinary KIM-1 and NGAL concentrations were determined using the enzyme-linked immunosorbent assay (ELISA) and adjusted to urinary creatinine. Biomarker levels were stratified by age and gender, and reference intervals derived with quantile regression (2.5th, 50th, and 97.5th quantiles) were expressed at 95% CI. The range of median reference intervals for urinary KIM-1 and NGAL in children were 0.081-0.426 ng/mg Cr, 2.966-4.850 ng/mg Cr for males, and 0.0780-0.5076 ng/mg Cr, 2.0850-3.4960 ng/mg Cr for females, respectively. Renal biomarkers showed weak correlations with age, gender, ACR, and BMI. Our findings provide reference intervals to facilitate screening to detect early renal damage, especially in rural communities that are impacted by CKDu. [ABSTRACT FROM AUTHOR]

Irrigation Water Management (IWM) being considered essential as it contributes to crop production all over the world. Nonetheless, water losses throughout the system, inefficient irrigation practices and lack of attention towards the proper maintenance of existing infrastructure were the constraining factors to achieve the benefits of sustainable use of water. Hence, this paper develops strategies to achieve sustainable water management of irrigation systems. Sixteen semi-structured interviews were conducted for industry professionals in the IWM sector in Sri Lanka as the main data collection method in this study. The collected data were analysed using a code-based content analysis based on the directed approach. The research findings identified four main categories of strategies, namely, engineering, management, operational and regulatory. The findings are substantially beneficial for industry practitioners in the water management sector to overcome the issues in IWM practices regarding the water use efficiency, equity of water distribution, environmental integrity and economic acceptability. This study can be further extended to prioritise the issues and strategies to statistically generalise the findings. [ABSTRACT FROM AUTHOR]

Mineral detection using remote sensing techniques is important since it saves the time and effort of carrying out manual land surveys. In this paper a novel algorithm, which can be used to detect ilmenite using hyperspectral image analysis is discussed. To investigate this task, a hyperspectral image obtained from the Earth Observing-1 (EO-1) satellite's Hyperion sensor was used. In the proposed algorithm, first, principal component analysis (PCA) was used for dimensionality reduction and an Euclidean distancebased method was used to extract the pixels containing soil. Thereafter, lab spectral data of typical ilmenite deposits were considered as the reference and a correlation factor analysis was carried out to determine the soil pixels, which are most likely to contain ilmenite and most unlikely to contain ilmenite. Using these two sets of pixels, a training set was constructed to apply Fisher's discriminant analysis (FDA) in order to separate the dataset into two distinct classes - ilmenite and non-ilmenite. Based on the spectral similarity, each pixel of the image was classified under one of these classes. This paper also introduces a probability-based approach to obtain results that are more accurate. A probability density function was designed considering the spatial distribution of the mineral. Thereafter, classification was done considering the probability measure as well. Lab tests performed on the soil samples collected from the locations, which were detected by the algorithm validate that the algorithm is accurate. [ABSTRACT FROM AUTHOR]

The heightened risk exposure of construction supply chains (SCs) calls for greater resilience. Focussing on industrialized construction (IC), this study examines how supply chain resilience (SCR) can be boosted through clear identification of the relevant and appropriate supply chain capabilities (SCC) that construction firms would then need to nurture and/or develop further. This study conducted a systematic review of SCC related literature, followed by an in-depth analysis and consolidation of the findings which enabled the development of a proposed action framework for achieving SCR in IC. The results revealed 58 SCC related to IC and mapped the yearly publication trend, publications by country and methodological approaches followed in previous research. Thematic analysis was conducted to categorize the identified SCC into 12 newly formulated constructs. Further, the findings help to identify a suite of capabilities (SCC) to develop value-enhanced resilient SCs in IC and provide a foundation for further research in SCR in the construction industry. [ABSTRACT FROM AUTHOR]

Preceding studies have mostly concentrated on the impact of international trade of primary goods on forest cover change dynamics, but few studies focused on the international trade and adjustment of trade structure on forest density. Hence this study is specifically trying to identify the links between trade, adjustment of trade structure and forest density in 52 developing countries. Similarly, we examined the forest quality as compare to traditional forest cover change research. We used common conditional mean methods and quantile regression model for data analysis. The results of the conditional mean methods (OLS, random-effect model, GMM) and quantile regression model indicated that the percentage of non-primary goods in total exports (PNPEXP) and total export of manufacturing and services goods (TEXP) show the significant positive impact on forest density. These results of the study specify that a nation or region can improve the forest density condition by the trade and adjustment of trade structure. [ABSTRACT FROM AUTHOR]

Sri Lanka's community forestry (CF) program emerged in the early 1980s following a global trend to conserve forest resources and provide benefits to the local community. However, very little is known about the effect of CF on forest resources. We assess the impacts of CF on forest conditions of semi-mixed evergreen forest in the intermediate zone of Sri Lanka using the before-after control-impact method. The study examines tree density, regeneration, woody species diversity, and evidence of disturbance as parameters to analyze the impact of the CF program. Data are analyzed using the difference in differences approach. The results show that the CF program has increased seedling and sapling density to a significant degree and reduced human disturbances. A major contribution of the CF program is that it was found to reduce invasive species and forest fires. The program reduced the amount of invasive species up to six times less than previous. The findings revealed that the impact of CF on forests may vary depending on pre-existing forest conditions, length of period to implement, perception, and decisions by local people. Community understanding and decision-making, in tandem with government policy, will weigh heavily on its future effectiveness. [ABSTRACT FROM AUTHOR]

Hyperspectral unmixing (HU) is a crucial step in the hyperspectral image (HSI) analysis. It aims at decomposing the observed spectrum at each pixel into a collection of constituent endmembers, weighted by their abundances. In a close spatial neighborhood, due to spatial autocorrelation, the abundances of an endmember tend to be similar to each other. Therefore, the spectra at the neighboring pixels are also very much alike. Recently, many studies have focused on graph-regularized nonnegative matrix factorization (NMF) approaches to address the blind HU problem. This is mainly because graph structures allow spatial–spectral relations to be effectively embedded in the NMF framework. This article takes one step further by defining each abundance map as a signal on a suitable graph, which enables the HU problem to be analyzed for the first time from a graph signal processing perspective. This article introduces a novel Laplacian regularizer based on the $l_{1}$ -norm, where graph spectral analysis is utilized to show that the regularizer has natural piecewise smooth (PWS) signal promotion and noise rejection capabilities. A graph-based blind HU algorithm is developed by incorporating this regularizer and an $l_{1/2}$ -abundance sparsity constraint into the NMF problem. Since the featured regularizer exploits the PWS property of abundance maps, the proposed method is effective in HU. The experiments conducted on synthetic and real HSIs demonstrate that it has superior performance compared with several popular HU algorithms. [ABSTRACT FROM AUTHOR]

Two fungal strains capable of decolourisation of CI Direct Blue 201 textile dye were isolated from textile wastewater effluent sites in Sri Lanka and they were identified as Aspergillus aculeatus and Aspergillus nomius using 18s rRNA analysis. A. nomius and A. aculeatus showed 98% decolourisation of CI Direct Blue 201 textile dye (50 mg/L) at 3rd day of incubation with the supplement of modified Kirk's medium. Both fungal strains were found to be more effective for dye decolourisation at temperatures ranging from 24 °C to 36 °C. Further, it was found that the decolourisation potential increased at pH 5 and 10 under shaking condition (100 rpm) with the presence of glucose and nitrate as additional carbon and nitrogen sources. Seed germination assay showed less germination (22.2 ± 5.0% and 10.0 ± 3.3% for Oryza sativa and Vigna radiata, respectively) when seeds were exposed to the original dye in comparison to 100% seed germination observed when exposed to fungal treated dye effluent, showing the detoxification of dye by the fungal isolates. [ABSTRACT FROM AUTHOR]

Invasive alien plants (IAPs) are a significant cause of socio-ecological change in Sri Lanka. Many studies have focused on the ecological dimensions of this problem, but few have addressed sociological factors such as the knowledge and perceptions of individuals and groups tasked with addressing IAPs. This study investigates how IAP issues are understood and perceived by professional forest and wildlife officers in Sri Lanka. The data analyzed were gathered using a questionnaire that covered three themes: the respondents' ability to identify IAPs, the impacts of IAPs and the threats they pose, and knowledge regarding control and mitigation. The questionnaire was completed by 186 field officers, and the resulting descriptive statistics and a probit regression analysis were used to analyze the data. The results show that almost all of the participating forest and wildlife officers were aware of the problems associated with IAPs but more than 75% of them lacked an accurate understanding of scientific means for controlling them and control policies established by the government of Sri Lanka. Generally, wildlife officers had a better understanding than forest officers. In addition, the analysis shows that officers' knowledge and perceptions of IAPs were positively correlated with their level of education and position within the organization. The analysis points to several recommendations for Sri Lankan officials when designing and implementing comprehensive policies and professional programs, particularly for lower-level field officers. [ABSTRACT FROM AUTHOR]

The present paper aims to investigate the impact of coffee exports on long-term economic growth in an open economy for 32 countries exporting coffee over the period of 1994-2013. The study applied a dynamic panel Auto-Regressive Distributive Lag (ARDL) modelling approach with estimators. All variables involved in the specified model were found to be stationary of order I (1) at a first difference. The Pooled Mean-Group (PMG) long-run results suggest the presence of a significant positive effect of coffee exports on economic growth. The empirical findings of the study suggest policy implications, promoting the coffee sector to boost the countries' economy. [ABSTRACT FROM AUTHOR]

The prevailing wisdom in tobacco control literature is that adroit use of taxation policy will reduce the prevalence of tobacco use because when tobacco prices go up, consumption goes down. Empirical evidence of this axiomatic inverse relationship has been sparse. This paper analyzes the effects of increased taxation on consumption of tobacco products in 136 countries during 2009-2015. Results indicate that there is weak negative relationship between change in adult smoking prevalence and change in taxation suggesting that higher tax rates on tobacco products tend to lower adult smoking prevalence, but in a modest rather than robust sort of way. [ABSTRACT FROM AUTHOR]

The study attempts to assess the degree to which Corporate Environmental Reporting (CER) contributes to firm performance in Sri Lanka. Four qualitative characteristics of financial information as stated in the Conceptual Framework for Financial Reporting (i.e., relevance, faithful representation, understandability and comparability) and three performance indicators (i.e., ROA, ROE and EPS) have been used to measure the decision usefulness of CER information and firm performance, respectively while three variables, namely, growth, firm size and leverage, were controlled in the study. For this purpose, top 30 companies based on the market capitalization in the Colombo Stock Exchange (CSE) of Sri Lanka were selected as the sample. Data were gathered from the annual reports of these companies during the period from 2013 to 2016, and data analysis was carried out using content analysis, descriptive statistics, Pearson correlation coefficient and multiple regression analysis. The findings show that scores for the two fundamental characteristics (i.e., relevance and faithful representation) were relatively lower than those of the enhancing qualitative characteristics (i.e., comparability and understandability), indicating a lower level of decision usefulness. With regard to the association between CER reporting and firm performance, it was evident that there is a positive association between the two variables. The findings of the study have significant policy implications such as the importance of provision of environmental information for decision making purposes rather than merely satisfying the stakeholders of companies. [ABSTRACT FROM AUTHOR]

The objective of this study was to develop an environmental friendly, low cost technology for cultivation of livestock forage legumes so as to minimise the use of nitrogen fertiliser (N-fertiliser) that pollute the pristine highland watersheds. Inoculants were prepared by screening several rhizobial isolates obtained from farm cultivated clover plants and selecting the most efficient strain. In field tests at three separate sites, the average amount of biomass produced by inoculated Trifolium plants was higher compared with the plants fertilised with urea. Root nodulation and other plant parameters were assessed on several randomly harvested plants 60 days after planting. The results indicate that root nodulation and plant growth increased significantly in inoculated plants. Average results obtained from nine crop cuts taken during a period of 15 months showed that regeneration and biomass production after crop cutting were better under inoculation than under N-fertiliser application. It is inferred that rhizobial inoculation has the potential to replace N-fertiliser applications to Trifolium repens L. in the Sri Lankan highland farming systems. [ABSTRACT FROM AUTHOR]

Purpose Increasing demand for the best value for client’s money necessitates waste reduction while enhancing the project functionality in construction industry. The purpose of this paper is to propose Lean integrated Value Engineering (LiVE) approach by establishing the synergy between Lean and Value Engineering (VE) concepts for construction industry.Design/methodology/approach A literature survey and in-depth un-structured interviews with six subject matter experts in three steps were used to investigate the synergy between Lean principles and VE job plan to develop LiVE approach for the construction industry. The gathered data were analysed using code-based content analysis and the LiVE approach was finally validated using interviews by two additional subject matter experts representing industry and academia.Findings Research findings established that there is a synergy between Lean principles and VE job plan. Accordingly, the study developed a LiVE approach, which specify client’s value, identify the value stream, make value flow without interruption, let the client pull functional requirements and pursue perfection during “value establishment”, “value analysis of functional requirements”, “value creativity”, “value evaluation”, “value development”, “value verification” and “value achievement” phases.Originality/value The novel LiVE approach will guide construction industry practitioners on how to integrate Lean concept with VE in order to reduce unnecessary costs and wastes, to enhance project functionality and ultimately to achieve value for client’s money. [ABSTRACT FROM AUTHOR]

We determined the genetic diversity of the Green Turtle Chelonia mydas (Linneaus, 1758) nesting at Kosgoda rookery, the second largest sea turtle aggregation on the southwestern coast of Sri Lanka. Skin tissue samples were collected from 68 nesting females and genetic diversity was estimated using six microsatellite loci. High genetic diversity was observed within the population as all loci analyzed were highly polymorphic with a total of 149 alleles observed. The mean number of alleles per locus was 24.7 and the mean observed and expected heterozygosity across all loci were 0.75 and 0.93, respectively. It appears that five out of six loci were not in Hardy-Weinberg equilibrium, while micro-checker analysis suggested that the Kosgoda Green Turtle population was possibly in equilibrium. The viability of a population is unlikely to be reduced if high genetic diversity is maintained within it. Although the Green Turtle population nesting at Kosgoda is small compared to other nesting rookeries in the world, the high genetic diversity observed suggests that the population may not be undergoing a bottleneck. [ABSTRACT FROM AUTHOR]

Molecular communication (MC) has recently emerged as a novel paradigm for nano-scale communication utilizing molecules as information carriers. In diffusion-based molecular communication, the system performance is constrained by the inter-symbol-interference caused by the crossover of information carrying molecules in consecutive bits. To cope with this, we propose the Reed-Solomon (RS) codes as an error recovery tool, to improve the transmission reliability in diffusion-based MC systems. To quantify the performance improvement due to RS codes, we derive the analytical expression for the approximate bit error probability (BEP) of the diffusion-based MC system with the full absorption receiver. We further develop the particle-based simulation framework to simulate the proposed system with RS code to verify the accuracy of our derived analytical results. Our results show that, as the number of molecules per bit increases, the BEP of the system with RS codes exhibits a substantial improvement than that of non-coded systems. Furthermore, the BEP of the proposed system with RS codes can be greatly improved by increasing the minimum distance of the codeword. [ABSTRACT FROM PUBLISHER]

The detection of crowd density levels and anomalies is a hot topic in video surveillance. Especially in human-centric action and activity-based movements. In some respects, the density level variation is considered an anomaly in the event. Crowd behaviour identification relies on a computer-vision-based approach and basically deals with spatial information of foreground video information. In this work, we focused on a deep-learning-based attention-oriented classification system for identifying several basic movements in public places, especially, human flock movement, sudden motion changes and panic events in several indoor and outdoor places. The important spatial features were extracted from a bilinear CNN and a multicolumn multistage CNN with preprocessed morphological video frames from videos. Finally, the abnormal and crowd density estimation was distinguished by using an attention feature combined with a multilayer CNN feature by modifying the fully connected layer for several categories (binary and multiclass). We validate the proposed method on several video surveillance datasets including PETS2009, UMN and UCSD. The proposed method achieved an accuracy of 98.62, 98.95, 96.97, 99.10 and 98.38 on the UCSD Ped1, UCSD Ped2, PETS2009, UMN Plaza1 and UMN Plaza2 datasets, respectively, with the different pretrained models. We compared the performance between recent modern approaches and the proposed method (MCMS-BCNN-Attention) and achieved the highest accuracy. The anomaly detection performance on the UMN and PETS2009 datasets was compared with that of a state-of-the-art method and achieved the best AUC results as 0.9953 and 1.00 for both scenarios, respectively, with a binary classification. [ABSTRACT FROM AUTHOR]

Purpose Delays represent one of the most critical factors that affect the cost of a construction project. They have to be therefore analysed comprehensively using appropriate techniques. The purpose of this paper is to find out the delay analysis techniques (DATs) that are most commonly used in road projects in Sri Lanka, the extent of their usage, the criteria that can be used in selecting them and the technique that is most appropriate for the selection.Design/methodology/approach The research methodology adopted included an extensive literature review, expert interviews and a questionnaire survey.Findings In road projects in Sri Lanka, five types of DATs are mainly used. The “As-planned v. As-built Analysis” technique is the most commonly used technique while “Window Analysis” is the least used technique. Out of the nine criteria identified for selecting a DAT, the most important criterion is the acceptability of the technique to courts and tribunals. “Window Analysis” was found to be the most appropriate DAT that can be used in road construction projects in Sri Lanka.Originality/value “Window Analysis” can be recommended as the most appropriate DAT for road projects in Sri Lanka. [ABSTRACT FROM AUTHOR]