Sistema e gerenciamento de telecomunicações

The advancements of computer science and its related fields are making our tasks easier in almost every scientific and non-scientific field. The use of machine
learning in the field of drug discovery and development is accelerating so fast and helping us to discover anti-viral drugs for devastating viruses like coronavirus.
The author will discuss using a deep reinforcement learning model 'ORGAN' which is a modified version of Generative Adversarial Network for predicting the
potential anti-viral of coronavirus. The author used the deep reinforcement learning model (ORGAN) to generate potential candidates’ drugs, with a λ of 0.2
and epochs of 240 and a sample set of 6400, 10 good sample SMILES were generated and the Solubility or LogP of these samples is 0.7098. Then using the
coronavirus as a target, all the good samples of SMILES were bounded and the drug with the highest binding affinity (Most negative value) is C18H15ClN4O2
also known as Olutasidenib which can be the potential anti-viral drug of coronavirus.

Recent information technologies are able to facilitate the transformation of traditional administrative processes to services which can be performed online. The
rapid growth of ICT is proved to be aligned with its application for the 4th Industry Revolution. Today, information security has become a vital entity to most
organizations due to current trends in information transfer through a borderless and vulnerable world. The concern and interest in information security is mainly
due to the fact that information security risk analysis (ISRA) is seen as a focal method not only to identify and prioritize information assets but also to identify
and monitor the specific threats that an organization induces; especially the chances of these threats occurring and their impact on the respective businesses.
Thus, a total of 18 years research in Information Security were conducted, and their findings were gathered and analysed meticulously. Most of the research
were particularly focusing in exploring the various aspect of security threats and its countermeasure through empirical researches, tool development, systematic
literature review and dynamic analysis impacted from theoretical knowledge development to its implementation growth in Organization. Our reviews suggested
that risks analysis demand critical and deep research to make sure they are able to introduce effective security counter measure. Our research focused on
critical information infrastructure such as Healthcare, Power System and Manufacturing. One of the study, we applied empirical study to categorize threats
and calculate risks for Healthcare system. In addition to that we developed tool using Machine Learning to explore various type of risks categories using the
same dataset. In other cases our research explored information requirements needed for SME based company in implementing risk analysis and comply with
standard. With the same objectives i.e., to introduce effective security counter measure, we explored different methods for analyzing risks, vulnerabilities and
threats using survival analysis. We further explored those parameters at critical sectors such as Oil& GAS and Manufacturing. For this, terms used are slightly
different yet aim/intention/ motive almost similar. The research finding explored Cyber Terrorism and its impact to critical system. Our come concluded that
Cyberterrorism required advanced technology for protection. The protection system should incorporated latest technology, expert, and systematic process. Our
proposed safeguards for cyber terrorism activities comply with international standard ISO 27100. Complexity in performing risks analysis is due to various type
of data i.e., either qualitative or quantitative or both. Most of risk analysis tools in the market only allow single type of data to be analysed. Therefore, in order to
facilitate this issue we explored and introduced techniques that allow both type of data to be treated as one. As a conclusion from the 18 years research in Risks,
Vulnerabilities and Threats Analysis in Information Security involved with various type of platform, software, hardware, middleware and Cyber Physical System.
Those technologies rapidly growth and backbone for Industry Revolution 5.0.

SMILE (Smartphone Intuitive Likeness and Engagement) application, a portable Android application that allows a human to control a robot using speech input.
SMILE is a novel open source and platform independent tool that will contribute to the robot soccer research by allowing robot handlers to verbally command
robots. The application resides on a smartphone embedded in the face of a humanoid robot, using a speech recognition engine to analyze user speech input
while using facial expressions and speech generation to express comprehension feedback to the user. With the introduction of intuitive human robot interaction
into the arena of robot soccer, we discuss a couple specific scenarios in which SMILE could improve both the pace of the game and autonomous appearance
of the robots. The ability of humans to communicate verbally is essential for any cooperative task, especially fast-paced sports. In the game of soccer, players
must speak with coaches, referees, and other players on either team. Therefore, if humanoids are expected to compete on the same playing field as elite soccer
players in the near future, then we must expect them to be treated like humans, which include the ability to listen and converse. SMILE (Smartphone Intuitive
Likeness and Engagement) is the first platform independent smartphone based tool to equip robots with these capabilities. Currently, humanoid soccer research
is heavily focused on walking dynamics, computer vision, and intelligent systems; however human-robot interaction (HRI) is overlooked. We delved into this
area of robot soccer by implementing SMILE, an Android application that sends data packets to the robot’s onboard computer upon verbal interaction with a user.

According to the report, about 1 in 50 families live with paralysis – around 5.4 million individuals. It is the same number of individuals as the collective residents
of Los Angeles, Philadelphia, and Washington D.C., which is almost 40% greater than the standard figures. Typical forms of paralysis include Monoplegia,
Hemiplegia, Diplegia, Paraplegia, and Quadriplegia. Another paralysis, except for Diplegia, had lower limbs (either partly or wholly) requiring a wheelchair to
support them in terms of mobility. Many wheelchairs, however, enable them to use their hands to maneuver around. It may concern patients with Hemiplegia or
Quadriplegia, as their hand movements are very restricted. As a result, this study suggested a wheelchair motion control using eye-tracking. The wheelchair is
portrayed by a differential mobile robot, where the same moving principle is shared. This project's key feature is that the patient determines the direction of travel
of the wheelchair without physically stressing it. This project consists of a video streaming module, a face detection module, an eye recognition module, and a
robot control module. The camera streams video to detect the face in live mode. The video frames will then be analyzed to identify the eye and decide the eye's
location by interacting with the mobile robot to drive the robot forward, turn left, turn right, and stop. Machine learning is used to detect the face and identify the
eye to achieve better results using the face hallmark detector that implements the One Millisecond Face Alignment and the Regression Tree Ensemble. Several
studies carried out have shown that the concept of monitoring the motion of a wheelchair by eye-tracking is achievable.

Background: Nasal carriage of Community-Acquired Methicillin-resistance Staphylococcus aureus (CA-MRSA) is recognized for its rapid community spread and
tendency to cause various infections especially in communities with a large population where personal hygiene is poor. We sought to investigate the prevalence
and evaluated the possible risk factors of CA-MRSA among the healthy population.
Methods: Nasal swabs collected from 392 males and 308 females using the multi-stage sampling technique were cultured for Staphylococcus aureus. Isolates
were identified by conventional biochemical tests, Microbact™ 12S identification kit and confirmed with 16SrRNA. Antibiotic susceptibility testing was performed
using the Kirby-Bauer disc diffusion technique. Finally, isolates were further investigated for methicillin resistance by using the cefoxitin disk diffusion test
followed by polymerase chain reaction amplification of MecA and Nuc genes. Proportions were tested using Chi-Square and Fisher’s Exact Probability Test in
Epi InfoTM.
Results: The results showed 31.9% and 9.4% prevalence of S. aureus nasal carriage and Methicillin-resistance Staphylococcus aureus respectively. Low
educational background (Ï°2 =36.817, P Ë? .001), age >40-50 years (Ï°2 = 8.849, P = .003), recent antibiotics use (Ï°2 = 7.556, P = .006), recent hospital visitation
(Ï°2 = 8.693, P = .003) and male gender (Ï°2 = 9.842, P = .002) are significantly associated with CA-MRSA. The results of this research study show that CA-MRSA
are highly multi-drug resistant.
Conclusion: The study established a high prevalence and resistance burden of CA-MRSA in the population; this poses a serious public health concern in the
region and necessitates the demands for continuous surveillance on the colonization state of CA-MRSA to restrict the transmission of the bacterium in the
community.

We are pleased to welcome you to the “International Conference on Stem Cell, Tissue Engineering and Regenerative Medicine” after the successful completion
of the series of Stem Cell Research 2020. The congress is scheduled to take place in the beautiful city of Rome, Italy on September 29-30, 2021. This Stem Cell
Research 2021 conference will provide you with an exemplary research experience and huge ideas.
The perspective of the Stem Cell Conference is to set up transplant research to help people understand how treatment techniques have advanced and how the
field has developed in recent years.
Longdom proffers our immense pleasure and honour in extending you a warm invitation to attend Stem Cell Research 2021 in Rome, Italy on September 29-30,
2021. It is focusing on “Advancement in Stem Cell Biology and Regenerative Medicine”, to enhance and explore knowledge among Stem Cell community and to
establish corporations and exchanging ideas. Providing the right stage to present stimulating Keynote talks, Plenary sessions, Discussion Panels, B2B Meetings,
Poster symposia, Video Presentations and Workshop Stem Cell Research 2021 anticipates over 200 participants around the globe with path breaking subjects,
discussions and presentations. This will be a splendid feasibility for the researchers, delegates and the students from Global Universities and Institutes to interact
with the world class scientists, speakers, Analyst, practitioners and Industry Professionals.
Longdom all the experts and researchers from the Stem Cell, Tissue Engineering and Regenerative Medicine sector all over the world to attend “International
Conference on Stem Cell, Tissue Engineering and Regenerative Medicine (Stem Cell Research 2021) which is going to be held on Rome, Italy on September
29-30, 2021. Stem Cell Research 2021 conference includes Keynote presentations, Oral talks, Poster Presentations, Workshops, and Exhibitors.
Stem Cell Research 2021 conference is also comprised of Best Post Awards, Best Oral Presentation Awards, Young Researchers Forums (YRF) and also
Video Presentation by experts. We are glad to welcome you all to join and register for the “International Conference on Stem Cell, Tissue Engineering and
Regenerative Medicine” which is going to be held in Rome, Italy on September 29-30, 2021.