Evaluation of Composted Sewage Sludge/Straw Mixture for Horticultural Utilization

1989 ◽  
Vol 21 (8-9) ◽  
pp. 889-897 ◽  
Author(s):  
J. M. Lopez-Real ◽  
E. Witter ◽  
F. N. Midmer ◽  
B. A. O. Hewett

Collaborative research between Southern Water and Wye College, University of London, has led to the development of a static aerated pile composting process for the treatment of dewatered activated sludge cake/straw mixtures. The process reduces bulk volume of the sludge producing an environmentally acceptable, stabilised, odour and pathogen-free product. Characteristics of the compost make it a suitable general purpose medium for container grown plants, providing the salt concentration is reduced by washing the compost prior to planting. Compared with peat the compost has a higher bulk density, a lower waterholding capacity, a lower cation exchange capacity, a high content of soluble salts, and a higher content of plant nutrients. A compost mixture was successfully developed in the growing trials containing equal quantities of compost, Sphagnum peat, and horticultural vermiculite. The compost has been used successfully to grow a wide range of plants. Plants grown in mixtures based on the compost were in general similar to those grown in peat-based growing media. The compost is a valuable soil conditioner and slow release fertilizer.

2020 ◽  
Vol 26 (27) ◽  
pp. 3234-3250
Author(s):  
Sushil K. Kashaw ◽  
Prashant Sahu ◽  
Vaibhav Rajoriya ◽  
Pradeep Jana ◽  
Varsha Kashaw ◽  
...  

Potential short interfering RNAs (siRNA) modulating gene expression have emerged as a novel therapeutic arsenal against a wide range of maladies and disorders containing cancer, viral infections, bacterial ailments and metabolic snags at the molecular level. Nanogel, in the current medicinal era, displayed a comprehensive range of significant drug delivery prospects. Biodegradation, swelling and de-swelling tendency, pHsensitive drug release and thermo-sensitivity are some of the renowned associated benefits of nanogel drug delivery system. Global researches have also showed that nanogel system significantly targets and delivers the biomolecules including DNAs, siRNA, protein, peptides and other biologically active molecules. Biomolecules delivery via nanogel system explored a wide range of pharmaceutical, biomedical engineering and agro-medicinal application. The siRNAs and DNAs delivery plays a vivacious role by addressing the hitches allied with chronic and contemporary therapeutic like generic possession and low constancy. They also incite release kinetics approach from slow-release while mingling to rapid release at the targets will be beneficial as interference RNAs delivery carriers. Therefore, in this research, we focused on the latest improvements in the delivery of siRNA loaded nanogels by enhancing the absorption, stability, sensitivity and combating the hindrances in cellular trafficking and release process.


2017 ◽  
Vol 11 (1) ◽  
pp. 50-62 ◽  
Author(s):  
Rajendran Mala ◽  
Ruby Selvaraj ◽  
Vidhya Sundaram ◽  
Raja Rajan ◽  
Uma Gurusamy

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1031
Author(s):  
Joseba Gorospe ◽  
Rubén Mulero ◽  
Olatz Arbelaitz ◽  
Javier Muguerza ◽  
Miguel Ángel Antón

Deep learning techniques are being increasingly used in the scientific community as a consequence of the high computational capacity of current systems and the increase in the amount of data available as a result of the digitalisation of society in general and the industrial world in particular. In addition, the immersion of the field of edge computing, which focuses on integrating artificial intelligence as close as possible to the client, makes it possible to implement systems that act in real time without the need to transfer all of the data to centralised servers. The combination of these two concepts can lead to systems with the capacity to make correct decisions and act based on them immediately and in situ. Despite this, the low capacity of embedded systems greatly hinders this integration, so the possibility of being able to integrate them into a wide range of micro-controllers can be a great advantage. This paper contributes with the generation of an environment based on Mbed OS and TensorFlow Lite to be embedded in any general purpose embedded system, allowing the introduction of deep learning architectures. The experiments herein prove that the proposed system is competitive if compared to other commercial systems.


1997 ◽  
Vol 61 (1) ◽  
pp. 43-46 ◽  
Author(s):  
F. Ramírez ◽  
V. González ◽  
M. Crespo ◽  
D. Meier ◽  
O. Faix ◽  
...  

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Seyed Hossein Jafari ◽  
Amir Mahdi Abdolhosseini-Qomi ◽  
Masoud Asadpour ◽  
Maseud Rahgozar ◽  
Naser Yazdani

AbstractThe entities of real-world networks are connected via different types of connections (i.e., layers). The task of link prediction in multiplex networks is about finding missing connections based on both intra-layer and inter-layer correlations. Our observations confirm that in a wide range of real-world multiplex networks, from social to biological and technological, a positive correlation exists between connection probability in one layer and similarity in other layers. Accordingly, a similarity-based automatic general-purpose multiplex link prediction method—SimBins—is devised that quantifies the amount of connection uncertainty based on observed inter-layer correlations in a multiplex network. Moreover, SimBins enhances the prediction quality in the target layer by incorporating the effect of link overlap across layers. Applying SimBins to various datasets from diverse domains, our findings indicate that SimBins outperforms the compared methods (both baseline and state-of-the-art methods) in most instances when predicting links. Furthermore, it is discussed that SimBins imposes minor computational overhead to the base similarity measures making it a potentially fast method, suitable for large-scale multiplex networks.


Cellulose ◽  
2021 ◽  
Author(s):  
Iris Amanda A. Silva ◽  
Osmir Fabiano L. de Macedo ◽  
Graziele C. Cunha ◽  
Rhayza Victoria Matos Oliveira ◽  
Luciane P. C. Romão

AbstractUrea-based multi-coated slow release fertilizer was produced using water hyacinth, humic substances, and chitosan, with water rich in natural organic matter as a solvent. Elemental analysis showed that the nitrogen content of the fertilizer (FERT) was around 20%. Swelling tests demonstrated the effectiveness of the water hyacinth crosslinker, which reduced the water permeability of the material. Leaching tests showed that FERT released a very low concentration of ammonium (0.82 mg L−1), compared to the amount released from urea (43.1 mg L−1). No nitrate leaching was observed for FERT, while urea leached 13.1 mg L−1 of nitrate. In water and soil, FERT showed maximum releases after 30 and 40 days, respectively, while urea reached maxima in just 2 and 5 days, respectively. The results demonstrated the promising ability of FERT to reduce nitrogen losses, as well as to minimize environmental impacts in the soil–plant-atmosphere system and to improve the efficiency of nitrogen fertilization. Graphic abstract


2021 ◽  
Vol 215 ◽  
pp. 112148
Author(s):  
Ifra Saleem ◽  
Muhammad Aamer Maqsood ◽  
Muhammad Zia ur Rehman ◽  
Tariq Aziz ◽  
Ijaz Ahmad Bhatti ◽  
...  

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