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  • Open access
  • 228 Reads
Enhanced Defluoridation from Aqueous Solutions using Zirconium – coated Pumice in Fixed-bed Column Systems

Millions of people across the globe suffer from health issues related to excessive fluoride levels in drinking water. The objective of this study was to test natural and modified rock materials as adsorbents for the cleanup of fluoride-laden waters. Fluoride uptake onto natural pumice and zirconium–coated pumice (Zr – Pu) packed fixed-bed adsorption column was investigated. The extent of surface modification with enhanced porosity of Zr – Pu was evident from recorded SEM micrographs. A FTIR study of pumice and Zr – Pu before and after adsorption did not reveal any significant structural changes. The pH drift method demonstrated that pumice and Zr – Pu possesses positive charges at pHPZC lower than 7.3 and 6.5, respectively. The highest removal capacity of 225 mg/kg and 110 mg/kg were gained for Zr – Pu and pumice, respectively at pH = 2 and QO = 1.25 mL/min. Breakthrough time increases with decreasing pH and flow rate. The experimental adsorption data was well-matched by the Thomas and Adams-Bohart models with correlation coefficients (R2), of ≥ 0.980 (Zr – Pu) and ≥ 0.897 (natural pumice), confirming that the models are appropriate tools to design fixed-bed column systems using volcanic rock materials. Overall, coating of pumice with zirconium improved the defluoridation capacity of pumice, hence, Zr – Pu packed fixed-bed could be applied for the defluoridation of excess fluoride from groundwater. However, additional investigations on, for instance, competitive ions effects are advisable to draw definite conclusions.

  • Open access
  • 71 Reads
On the Use of Artificial Intelligence in Medicine
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Artificial intelligence in computing is a tool capable of analyzing large amounts of medical data of varying complexity. The work published by A N Ramesh and collaborators in Ann R Coll Surg Engl 2004 Sep; 86 (5): 334-8. doi: 10.1308 / 147870804290 does an analysis on the subject. The great power of artificial intelligence techniques to study a significant amount of data is very useful in the diagnosis, treatment and prediction of results in various fields of medicine. The article analyzes the various artificial intelligence techniques to apply in the medical area.

The broad power of artificial intelligence has been studied in most fields of the clinical area. For example, the artificial neural network was the most widely used data analysis tool, but there are other artificial intelligence techniques, such as fuzzy expert systems, evolutionary computing, and hybrid intelligent systems, which have been used in different clinical settings.

Artificial intelligence has the power to apply in most fields of medicine. More well-designed clinical trials are required before applying these techniques in the real clinical world.

  • Open access
  • 42 Reads

Artificial Intelligence in Biomedical Engineering

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The article published by Yoav Mintz and Brodie in Minim Invasive Ther Allied Technol, 2019 Apr describes the use of artificial intelligence techniques in medicine. Artificial intelligence has developed over the years, being proposed by John McCarthy in 1956 at a conference held on this subject, but the possibility that machines can perform human activity and think was raised earlier by Alan Turing, who developed the Turing test to differentiate humans from machines. Since that time, the power of computing and artificial intelligence have developed to the point of instant calculations and the ability to analyze new data, relative to previously evaluated data, in real time. Currently, AI is used in our daily lives in various ways, for example personal assistants (Siri, Alexa, Google assistant, etc.), automated mass transport, aviation and computer games. In recent years, AI has also begun to be used in medicine to achieve better patient care since it can speed up processes with greater precision, thus opening the way to provide better comprehensive medical care. For example, it is used in the analysis of radiological images and pathology slides of patients, which helps in the quality and speed of diagnosis and treatment and increases the capabilities of physicians. For this reason, the development of this science applied to medicine is of great importance.

  • Open access
  • 66 Reads
Radiowave Propagation Models

Radiowave propagation model is an empirical mathematical formulation for characterization of radiowave propagation as a function of frequency, distance and other conditions. Much like 4G or 3G before it, the radio waves used in 5G are low frequency and non-ionizing radiation. These are on the opposite end of the electromagnetic spectrum to ionizing radiation sources like X-rays, gamma rays, and ultraviolet rays.This study explains the various attenuating factors prevalent in radiowave propagation. It highlights the various types of radiowave propagation; its classification based on their propagation paths; its layers in the atmosphere, its frequency bands and propagation mechanism. The study also entails the various radiowave propagation models and their application in VHF and UHF band.

  • Open access
  • 104 Reads
Opinion on the use of artificial intelligence in drug design
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Artificial intelligence (AI) techniques play an important role in drug development. In the work published by Gerhard Hessler and Karl-Heinz Baringhaus in Journal Lis tMolecules vol.23 (10); 2018 makes an analysis on the subject. There are techniques that have largely developed this field, such as artificial neural networks, deep neural networks or recurrent networks. In recent years, various applications have been developed in predictions of properties or activities, such as physicochemical properties and ADMET, which demonstrate the importance of this technology in quantitative structure-property relationships (QSPR) or quantitative structure-activity relationships (QSAR). The use of artificial intelligence in de novo design generates the creation of new biologically active molecules that have the desired properties. There are numerous examples that demonstrate the importance of artificial intelligence in drug development. In the near future, computers are expected to discover more and more drugs in an automated way.

  • Open access
  • 117 Reads
Coconut Tree Disease Identification Using Image Processing -To Set A New Trend In Agriculture

The proposed System helps in identification of coconut tree disease and provide the remedies that can be used as a protective mechanism against the disease it is the major objective of the project, in which it focuses on increasing the quality of the product and yield. It is difficult for a farmer to monitor the coconut tree disease manually which may consume a lot of time. The symptoms can be found on leaf, stem, fruits and lesions of a tree. The proposed system provides the usage of mobile phones to capture the image of the affected parts of a tree, and then it will be verified by the expertise and the result will be sent to the farmer and the also the remedy that can be taken as a cure.

  • Open access
  • 94 Reads
Significance of Software Development Models in Current Context

As we know with the advancement of a various software development models over the past years, it became a subject of an extreme interest to a reason and segregates them relying upon the applications, favorable circumstances and inconveniences. There are different elements that influence the software development activities; they must even be taken care of once we choose a development model. Several software products come to fail because of reasons like an associate unskilled developer, a time limit, a poor quality, a less client association and considerably more. A software development models ought to be selected with wisdom watching the conditions, and a quality of the developer, a user, a time and the complexes of the project. Of these factors play an important role within the success of the project. A software development models will be categorized as lightweight models and hefty weight models. This paper discusses various models on completely different metrics with execs associated cons of each of them and additionally facilitate to choose an acceptable model relying upon the project.

  • Open access
  • 136 Reads
Obtaining QSPR models for the prediction of physicochemical properties of topical antimicrobials

The traditional form of development and investigation of the antimicrobials has been resulting inefficient according to the delay of the new candidates discovery in the last years. Several limitations have been demonstrated, such as the long time invested, the expensive experimental trials or the errors in the manipulation of the researcher. From bottom of the problem, it is already necessary change for another form that would be more convenient and efficient satisfying the high demands of humans. Thanks to the evolution of technology at the final of XX century, the application of the computational methods in the design of drugs raised as a promised alternative. Specifically, the structure-property relationship studies are oriented to determent the function capable to predict a particular property of a compound, using the information contained in their molecular descriptors. This strategy allowed us to analyze a great quantity of molecules in a minor time and with less resources. Five specific models were defined in the present work in order to predict the interested physicochemical properties (aqueous solubility (S), coefficient of partition (P), constant of distribution (D), constant of acid dissociation (Ka) and superficial tension (σ)) for the external use only of a series of 400 antimicrobial compounds, with simplified representations, physicochemical properties and molecular descriptors were obtained through the softwares ACD-Labs and MODESLAB. After an exhaustive validation, the specific models of log P and log D demonstrated a better prediction capacity with the standard errors of estimate for the specific functions were inferior or close to the logarithmic unit. Also, the prediction coefficients were 0.849 and 0.737 respectively. The results suggest the employment of them in the design and development of antimicrobials for topical use.

  • Open access
  • 42 Reads
The future of Artificial Intelligence in the European Union.

A critical analysis of the Proposal for a Regulation on Artificial Intelligence and its coexistence and compatibility with the Proposal for a European Regulation on the protection of personal data.

SCIENTIFIC PREMISES: In the fourth Industrial Revolution, Artificial Intelligence is an important and fundamental technology, and occupies a not inconsiderable place in the future development of humanity, its recognition is based on the need to facilitate scientific progress, achieve technological leadership, ensure that new technologies are at the service of all citizens, but at the same time these respect the established fundamental rights and improve the quality of life of these, by improving it and also contributes to business development and services of public interest. The impact of Artificial Intelligence systems must always be seen in two perspectives, one individual perspective and another as a society as a whole, they are inextricably linked.

Its regulation from the legislative point of view is fundamental to provide a safe, reliable development of Artificial Intelligence, which respects the values and fundamental rights of citizens, with an ethical use of them and whose fundamental pillars are excellence and trust, not only of artificial intelligence providers but also of their users. In both cases they must always be seen not from the perspective of each of the member states of the union, but as a union itself, being also a driving force to achieve the sustainable development goals foreseen in the 2030 agenda and the objectives foreseen in the Green Pact.

It is visible the need to regulate, from the legislative point of view, artificial intelligence, because it is inextricably linked to data. There is no artificial intelligence without data. What makes it necessary to coexist and make compatible with the established regulations on data protection with the established regulations on artificial intelligence, both must go hand in hand and indissolubly linked. The data is necessary not only for the AI to reach its maximum performance, but also so that it can avoid biases or errors when performing a treatment.

Is it possible to combine the development of AI with an adequate processing of personal data? In our opinion if, the treatment of personal data entails privacy, and this is transcendent to AI systems, in the first order because they are developed learning from the information provided and also because it can make automated decisions, this implies that to AI systems this regulation will be applied when these systems are developed with information containing personal data, and decision-making about individuals, then the dichotomy arises between algorithmic biases (according to some authors there are three types of these, the statistical, the cultural, and the cognitive) and the principle of legality

In this sense, regulations on artificial intelligence have been established in the approved regulation, that in our opinion lacks essential aspects for its implementation and happy existence, which were even reflected in the White Paper on Artificial Intelligence, which contains a European approach aimed at excellence and confidence in it but which also provides a common approach in this regard.

  • Open access
  • 62 Reads
Good Vibes for Artificial Intelligence

When Ctesibius of Alejandria in 250 BC built the first self-controlled machine (the first water flow regulator) he never imagined that it would take several centuries, for the term Artificial Intelligence to be spoken of for the first time at the Dartmounth Conference in 1956, even though there being signs of it throughout the years, prior to this date. Today, talking about this terminology and its importance for the development of humanity is a reality.

Simply, man has proposed to build, design, implement systems with intelligence similar to human intelligence, something we cannot be oblivious to, if we take into account the benefits that it would bring to humanity itself, which is experiencing the Fourth Industrial Revolution with development of digitization, where Artificial Intelligence plays a great role in the digital transformation of society. We are living in the digital age, so it is very inspiring to address this issue, if we take into account that this is already part of our daily lives, not only with the improvement that it entails in health care, but also in different sectors such as agriculture , energy, the economy, transport, communications, climate change, citizen security, and even the conquest of space and other planets by man. The opportunities offered by Artificial Intelligence are unlimited, not only to citizens, but also contributes to business development and public interest services, which makes the impact of the aforementioned systems verifiable in two perspectives, the individual and the society as a whole, all with a supreme purpose. That is, to achieve the increase of the well-being of the human being, therefore we must be aware that artificial intelligence is a means, not an end, it must be at human service.