Bioremediation of palm industry wastes using vermicomposting technology: its environmental application as green fertilizer

Several technologies are being applied for treatment of palm oil mill wastes. Among them, the biological treatments (vermicomposting) have widely been recognized as one of the most efficient and eco-friendly methods for converting organic waste materials into valuable products. The present study focuses on vermicomposting of acidic palm oil mill effluent (POME) mixed with the palm pressed fibre (PPF) which are found difficult to decompose in the environment. The industrial waste (POME) was vermicomposted using Lumbricus rubellus under laboratory conditions for a period of 45 days. A significant improvement in nitrogen, phosphorus, and potassium content was monitored during vermicomposting process. In addition, the decline in C:N ratio of vermicompost (up to 17.20 ± 0.60) reflects the degree of stabilization of POME–PPF mixture. Different percentages of the vermicompost extract obtained from POME–PPF mixture were also examined for the germination of mung bean (Vigna radiata) seed. The results showed that 75% vermicompost extract demonstrated better performance for the seed germination. On the basis of significant findings, POME–PPF mixture can be successfully used as a feeding material for the earthworms, while on the other hand, it can also be used as a cost-effective fertilizer for the germination and the proper growth of mung bean

The opportunity of magnetic induction tomography modality in breast cancer detection

The needs for non-invasive technique in breast cancer detection could enhance and preserve the future of medical field in Malaysia as well as countries around the world. Breast cancer has become the main concern nowadays not only for women but for man as well. In overall, the risk of women getting breast cancer is higher than man due to the denser tissue of breast in women compare to man. Beside the unawareness for the disease, the reason which contributes to this increasing number of breast cancer reported is also due to the limitations arising from modalities such as MRI, Mammography, ultrasound and other modalities. An alternative to current technologies should be improved for early detection and treatment which causes no physical harm to patients if possible. Thus, non-invasive and better technology in detecting breast cancer is very much needed in the current market. This paper will be discussing the insights of Magnetic Induction Tomography techniques in breast cancer detection

Robust efficiency and output elasticity of broiler production in Peninsular Malaysia

This study investigates issues on efficiency and elasticity of broiler production in Peninsular Malaysia. Data from 296 broiler farms were subjected to SFA, DEA and bootstrap methods for technical efficiency; Translog and Tobit regression analyses to estimate elasticity of production and determinants of efficiency respectively in broiler production. We found that farmers produce mean efficiency of 94, 95 and 97% with robust for small, medium and large scale farms respectively. Apart from inefficiency, we also found evidence that minimal bias/noise exists in broiler production. Relative to output elasticity, we observed an inelastic relationship in feeds but an elastic relationship in DOC, medications and utilities. Most of the socio-economic attributes (experience, age, education, business status and number of farms) show highly significant statistical relationship with efficiency and with appropriate signs. To ensure production at higher marginal returns and lower marginal costs, farms operating under increasing returns to scale should scale-up production while those producing at decreasing returns to scale need to scale-down production. The study also advocates to farmers to embrace adequate training/better education, contract farming and ownership of fewer number of farms in order to enhance efficiency, productivity and sustainability of the broiler industry

Preventive Hoof Trimming and Animal-Based Welfare Measures Influence the Time to First Lameness Event and Hoof Lesion Prevalence in Dairy Cows

Background: The objectives of this study were to, (1) investigate the impact of the Dutch five-step hoof trimming (HT) technique on time to lameness and hoof lesion prevalence in grazing (GR) and non-grazing (NGR) dairy cows, and (2) determine the association between potential benefits of HT and animal-based welfare measures during lactation. A total of 520 non-lame cows without hoof lesions from 5 dairy farms (GR = 2, NGR = 3) were enrolled at early (within 30 days in milk; DIM) and late lactation (above 200 DIM), and randomly allocated to either trimmed (HGR or HNGR) or control groups (CON-GR and CON-NGR). Locomotion scores, body condition, hock condition, leg hygiene, and hoof health were assessed at monthly intervals until the following 270 days in milk. The data were analyzed using Kaplan-Meier survival analysis, multivariable Cox, and logistic regression models. The overall incidence rate of lameness was 36.2 cases/100 cows/month, with corresponding rates of 27.4, 31.9, 48.4, and 45.8 cases/100 cows/month in HGR, HNGR, CON-GR, and CON-NGR, respectively. Time to first lameness event was significantly higher in HGR (mean ± S.E; 8.12 ± 0.15) compared to CON-GR (7.36 ± 0.26), and in HNGR (8.05 ± 0.16) compared to CON-NGR (7.39 ± 0.23). The prevalence of hoof lesions in the enrolled cows was 36.9%, with a higher occurrence in CON-GR (48.8%) than HGR (23.2%), and in CON-NGR (52.6%) compared to HNGR (32.2%). The majority of hoof lesions were non-infectious in grazing (HGR vs. CON-GR; 21.3 vs. 33.3%) and non-grazing herds (HNGR vs. CON-NGR; 25.0 vs. 40.4%). The risk of lameness was higher in underconditioned cows (Hazard ratio; HR = 3.1, 95% CI 1.2–7.4), presence of hoof lesion (HR = 33.1, 95% CI 17.6–62.5), and there was variation between farms. Aside HT, lower parity (OR = 0.4, 95% CI 0.2–0.8), normal hock condition (OR = 0.06; 95% 0.01–0.29), and absence of overgrown hoof (OR = 0.4; 95% 0.2–0.7) were protective against non-infectious hoof lesions. Functional HT is beneficial as a lameness preventive strategy during lactation; however, ensuring older cows are in good body condition and free from hock injuries are equally important

Assessing the technical efficiency of maize production in northern ghana: the data envelopment analysis approach

Maize is a major source of food and cash for smallholder farmers. However, average yield in Ghana is less than a third of the achievable yield and thus the need to close this gap by improving the technical efficiency of farming households through employing the right combination of productive resources to achieve food sustainability. This study used the input-oriented data envelopment analysis to examine the technical efficiency of maize production in northern Ghana1 using cross-sectional data for the 2011/2012 cropping season. The mean technical efficiency was 77%, giving credence to the existence of production inefficiency. Technically, efficient farmers used an average of 395.80 kg of chemical fertilizer, 27.04 kg of seed, 4.04 l of weedicides and hired labour of three persons to produce a yield of 2.34 tons/ha of maize. Largely, maize production exhibited increasing returns to scale. Agricultural mechanization and level of formal education did not have positive effects on technical efficiency, whereas agricultural extension had a positive effect on technical efficiency. Technical efficiency in maize production could be improved through informal and non-formal educational platforms where farmers without formal education learn improved cultivation practices. The agricultural extension department should be strengthened to provide effective extension services to farmers to improve on their technical efficiency. Animal and other non-mechanized power sources are complementary technologies and as such should be allowed to co-exist in Ghanaian agriculture

Principles of environmentally-sustainable anaesthesia: a global consensus statement from the World Federation of Societies of Anaesthesiologists

The Earth’s mean surface temperature is already approximately 1.1°C higher than pre-industrial levels. Exceeding a mean 1.5°C rise by 2050 will make global adaptation to the consequences of climate change less possible. To protect public health, anaesthesia providers need to reduce the contribution their practice makes to global warming. We convened a Working Group of 45 anaesthesia providers with a recognised interest in sustainability, and used a three-stage modified Delphi consensus process to agree on principles of environmentally sustainable anaesthesia that are achievable worldwide. The Working Group agreed on the following three important underlying statements: patient safety should not be compromised by sustainable anaesthetic practices; high-, middle- and low-income countries should support each other appropriately in delivering sustainable healthcare (including anaesthesia); and healthcare systems should be mandated to reduce their contribution to global warming. We set out seven fundamental principles to guide anaesthesia providers in the move to environmentally sustainable practice, including: choice of medications and equipment; minimising waste and overuse of resources; and addressing environmental sustainability in anaesthetists’ education, research, quality improvement and local healthcare leadership activities. These changes are achievable with minimal material resource and financial investment, and should undergo re-evaluation and updates as better evidence is published. This paper discusses each principle individually, and directs readers towards further important references

Modelling urban growth evolution and land-use changes using GIS based cellular automata and SLEUTH models: the case of Sana'a metropolitan city, Yemen.

An effective and efficient planning of an urban growth and land use changes and its impact on the environment requires information about growth trends and patterns amongst other important information. Over the years, many urban growth models have been developed and used in the developed countries for forecasting growth patterns. In the developing countries however, there exist a very few studies showing the application of these models and their performances. In this study two models such as cellular automata (CA) and the SLEUTH models are applied in a geographical information system (GIS) to simulate and predict the urban growth and land use change for the City of Sana’a (Yemen) for the period 2004–2020. GIS based maps were generated for the urban growth pattern of the city which was further analyzed using geo-statistical techniques. During the models calibration process, a total of 35 years of time series dataset such as historical topographical maps, aerial photographs and satellite imageries was used to identify the parameters that influenced the urban growth. The validation result showed an overall accuracy of 99.6 %; with the producer’s accuracy of 83.3 % and the user’s accuracy 83.6 %. The SLEUTH model used the best fit growth rule parameters during the calibration to forecasting future urban growth pattern and generated various probability maps in which the individual grid cells are urbanized assuming unique “urban growth signatures”. The models generated future urban growth pattern and land use changes from the period 2004–2020. Both models proved effective in forecasting growth pattern that will be useful in planning and decision making. In comparison, the CA model growth pattern showed high density development, in which growth edges were filled and clusters were merged together to form a compact built-up area wherein less agricultural lands were included. On the contrary, the SLEUTH model growth pattern showed more urban sprawl and low-density development that included substantial areas of agricultural lands

A review of applying second-generation wavelets for noise removal from remote sensing data.

The processing of remotely sensed data includes compression, noise reduction, classification, feature extraction, change detection and any improvement associated with the problems at hand. In the literature, wavelet methods have been widely used for analysing remote sensing images and signals. The second-generation of wavelets, which is designed based on a method called the lifting scheme, is almost a new version of wavelets, and its application in the remote sensing field is fresh. Although first-generation wavelets have been proven to offer effective techniques for processing remotely sensed data, second-generation wavelets are more efficient in some respects, as will be discussed later. The aim of this review paper is to examine all existing studies in the literature related to applying second-generation wavelets for denoising remote sensing data. However, to make a better understanding of the application of wavelet-based denoising methods for remote sensing data, some studies that apply first-generation wavelets are also presented. In the part of hyperspectral data, there is a focus on noise removal from vegetation spectrum