Longitudinal Scalar Wave(LSW)Fact:It Is a True Science,Neither Pseudoscience Nor Fiction(A Short Memorandum)

The discovery of scalar energy many years ago has mostly been ignored since then.Scalar energy is still misunderstood,underappreciated,and underutilized today.To comprehend the future,one must look back at the past.Scalar energy was first discovered by Scottish physicist James Clark Maxwell,who was born in 1831.Maxwell made significant advances in mathematical physics.He developed the theories relating to electromagnetic fields and radiation.Maxwell’s discoveries were advanced by Nikola Tesla,who also created instruments that demonstrated the presence of scalar energy.Nicola Tesla discovered an electromagnetic longitudinal wave in the early 1900s.It is capable of lossless energy transmission over great distances,lossless power transmission through solid metal objects,and wireless energy transmission.In this patent,Tesla neither named it nor provided a description of how it operated.Now,in the twenty-first century,it is referred to as LSWs(longitudinal scalar waves).Instantaneous longitudinal waves called scalars cover the entire field.In contrast to electromagnetic waves,which are transverse and move along an axis in a certain direction,they do not propagate along an axis or have a direction.As“vector”waves,electromagnetic waves lose power as they travel farther and pass through solid metal objects.Scalar waves also offer a unique property that Tesla does not include in his patent,which concentrates on the transportation of energy.These waves can transmit information as well.

The Symbiotic Relationship Unraveling the Interplay between Technology and Artificial Intelligence(An Intelligent Dynamic Relationship)

This article investigates the dynamic relationship between technology and AI(artificial intelligence)and the role that societal requirements play in pushing AI research and adoption.Technology has advanced dramatically throughout the years,providing the groundwork for the rise of AI.AI systems have achieved incredible feats in various disciplines thanks to advancements in computer power,data availability,and complex algorithms.On the other hand,society’s needs for efficiency,enhanced healthcare,environmental sustainability,and personalized experiences have worked as powerful accelerators for AI’s progress.This article digs into how technology empowers AI and how societal needs dictate its progress,emphasizing their symbiotic relationship.The findings underline the significance of responsible AI research,which considers both technological prowess and ethical issues,to ensure that AI continues to serve the greater good.

Is the Genie of Artificial Intelligence Technology Out of the Bottle and Control?(A Short Review)

In recent years,AI(artificial intelligence)has made considerable strides,transforming a number of industries and facets of daily life.However,as AI develops more,worries about its potential dangers and unforeseen repercussions have surfaced.This article investigates the claim that AI technology has broken free from human control and is now unstoppable.We look at how AI is developing right now,what it means for society,and what steps are being taken to reduce the risks that come with it.We seek to highlight the need for responsible development and implementation of this game-changing technology by examining the opportunities and challenges that AI presents.

Is Zero Point Energy(ZPE)True Science or Fiction?(A Short Memorandum)

ZPE(zero-point energy)is a concept in physics that refers to the lowest possible energy state that a quantum mechanical physical system can have.It is the energy that remains even at absolute zero temperature,where all classical forms of energy are assumed to be absent.Within quantum physics,the idea of ZPE is well-established.According to quantum field theory,quantum fields fluctuate even in empty space,resulting in a constant emergence and disappearance of particles and antiparticles.The ZPE comes from these fluctuations.ZPE can be used as a useful energy source;however,this idea is still up for discussion.ZPE has occasionally been linked in popular culture to pseudoscientific claims about“free energy”and perpetual motion machines.These assertions are usually unfounded and go beyond what is currently known about ZPE.There are currently no practical applications or tools that can extract useful energy from ZPE,even though it has fascinating theoretical implications and has been researched in the context of quantum field theory.Within the confines of currently understood physics,researchers are still exploring the concept’s potential ramifications and uses.

RFID Adaption in Healthcare Organizations:An Integrative Framework

Radio frequency identification(RFID),also known as electronic label technology,is a non-contact automated identification technology that recognizes the target object and extracts relevant data and critical characteristics using radio frequency signals.Medical equipment information management is an important part of the construction of a modern hospital,as it is linked to the degree of diagnosis and care,as well as the hospital’s benefits and growth.The aim of this study is to create an integrated view of a theoretical framework to identify factors that influence RFID adoption in healthcare,as well as to conduct an empirical review of the impact of organizational,environmental,and individual factors on RFID adoption in the healthcare industry.In contrast to previous research,the current study focuses on individual factors as well as organizational and technological factors in order to better understand the phenomenon of RFID adoption in healthcare,which is characterized as a dynamic and challenging work environment.This research fills a gap in the current literature by describing how user factors can influence RFID adoption in healthcare and how such factors can lead to a deeper understanding of the advantages,uses,and impacts of RFID in healthcare.The proposed study has superior performance and effective results.

Renewable and Nonrenewable Energy Flow Resiliency for Day-to-Day Production and Consumption

Energy resilience is about ensuring a business and end-use consumers have a reliable,regular supply of energy and contingency measures in place in the event of a power failure,generating a source of power such as electricity for daily needs from an uninterrupted source of energy no matter either renewable or nonrenewable.Causes of resilience issues include power surges,weather,natural disasters,or man-made accidents,and even equipment failure.The human operational error can also be an issue for grid-power supply to go down and should be factored into resilience planning.As the energy landscape undergoes a radical transformation,from a world of large,centralized coal plants to a decentralized energy world made up of small-scale gas-fired production and renewables,the stability of electricity supply will begin to affect energy pricing.Businesses must plan for this change.The challenges that the growth of renewables brings to the grid in terms of intermittency mean that transmission and distribution costs consume an increasing proportion of bills.With progress in the technology of AI(Artificial Intelligence)integration of such progressive technology in recent decades,we are improving our resiliency of energy flow,so we prevent any unexpected interruption of this flow.Ensuring your business is energy resilient helps insulate against price increases or fluctuations in supply,becoming critical to maintaining operations and reducing commercial risk.In the form short TM(Technical Memorandum),this paper covers this issue.

The Utility of Artificial Intelligence for Mood Analysis,Depression Detection,and Suicide Risk Management

Mood disorders are often an indication or a sign of depression,and individuals suffering from mood swings may face higher probability and increased suicidal tendencies.Depression-also called“clinical depression”or a“depressive disorder”-is a mood disorder that adversely impacts how an individual feels,thinks,and handles daily activities,such as sleeping,eating,or working.To be diagnosed with depression,symptoms must be present most of the time,nearly every day for at least minimum of 2 to 3 weeks.Feeling sad or having low emotional energy may be common among people.For most,however,these feelings are transitory and can be managed by changing daily life routines.But for some,prolonged mood disorders can lead to depression and foster suicidal tendencies.Suicide is a major public health concern.Over 47,000 people died by suicide in the United States in 2017.It is the 10th leading cause of death overall according to NIMH(National Institute of Mental Health).Suicide is complicated and tragic,but it is often preventable.Identifying the warning signs for suicide and how to get help can be a major mitigating factor.In this short communication,we are reviewing the promise and limitations of AI(artificial intelligence)with its integrated tools such as ML(machine learning)and DL(deep learning)for mood analysis as a means for detecting early signs of depression and increased suicidal tendencies for possible suicide risk management.

Artificial Intelligence Integration with Energy Sources (Renewable and Non-renewable)

In the past decade or so,AI(artificial intelligence)technology has been growing with such a mesmerizing speed that today its presence in almost any industry that deals with any huge sheer volume of data is taking advantage of AI by integrating it into their day-to-day operation.Meanwhile,seven billion people worldwide shape the world’s energy system and directly impact the fundamental drivers of energy,both renewable and non-renewable sources,to meet the demand for electricity from them.These energy sources can be reached from nature such as solar,wind,etc.,and human-made such as NPPs(nuclear power plants)in the form of either fission as an old technology since the Manhattan project and in the near future as fusion in the form of magnetic or inertial confinements.Meanwhile,AI controlling nuclear reactors are about to happen.The basic idea is to apply AI with its two subset components as ML(machine learning),and DL(deep learning)techniques to go through the mountains of data that come from a reactor,spot patterns in it,and calling them to the unit’s human attention operators is not invadable either.Designers of such nuclear reactors will combine simulation and real-world data,comparing scenarios from each to develop“confidence[in]what they can predict and what is the range of uncertainty of their prediction”.Adding that,in the end,the operator will make the final decisions in order to keep these power plants safe while they are in operation and how to secure them against cyber-attack natural or human-made disasters.In this short communication article,we would like to see how we can prove some of these concepts;then a NPP manufacturer can pick it up and use it in their designs of a new generation of these reactors.

Dimensional Analysis and Similarity Method Driving Self-similar Solutions of the First and Second Kind Inducing Energy

Nearly all scientists,at conjunction with simplifying a differential equation,have probably used dimensional analysis.Dimensional analysis(also called the Factor-Label Method or the Unit Factor Method)is an approach to the problem that uses the fact that one can multiply any number or expression without changing its value.This is a useful technique.However,the reader should take care to understand that chemistry is not simply a mathematics problem.In every physical problem,the result must match the real world.In physics and science,dimensional analysis is a tool to find or check relations among physical quantities by using their dimensions.The dimension of a physical quantity is the combination of the fundamental physical dimensions(usually mass,length,time,electric charge,and temperature)which describe it;for example,speed has the dimension length/time,and may be measured in meters per second,miles per hour,or other units.Dimensional analysis is necessary because a physical law must be independent of the units used to measure the physical variables in order to be general for all cases.One of the most derivation elements from dimensional analysis is scaling and consequently arriving at similarity methods that branch out to two different groups namely self-similarity as the first one,and second kind that through them one can solve the most complex none-linear ODEs(Ordinary Differential Equations)and PDEs(Partial Differential Equations)as well.These equations can be solved either in Eulearian or Lagrangian coordinate systems with their associated BCs(Boundary Conditions)or ICs(Initial Conditions).Exemplary ODEs and PDEs in the form of none-linear can be seen in strong explosives or implosives scenario,where the results can easily be converted to induction of energy in a control forms for a peaceful purpose(i.e.,fission or fusion reactions).

Nanomaterials Driven Magnetic Nuclear Fusion Confinement Approaches(A Technical Memorandum)

Nuclear energy driven magnetic confinement via donut shape device known as Tokamak,a toroidal apparatus,for producing controlled fusion reactions in hot plasma,was originally suggested as a basic yet more promising fusion reactor.Today the more innovative version of this apparatus that is known as an ITER(international thermonuclear experimental reactor)shows a way toward MCF(magnetic confinement fusion)of hot plasma goal by satisfying Lawson’s Criteria to some degree of achievement.However,since this fusion driven reactor of hot plasma needs to operate at almost 150 million Celsius,the internal material of this reactor is a matter of concern for scientists that are involved with its fabrication.Uniqueness of nanomaterials from the point of view of physical and chemical properties is suggested as a possible potential application for this special and innovative reactor for a nuclear fusion device.Convergence of nanotechnology in study of new generation of materials of this kind can shape the path for various technological developments and a large variety of disciplines,including MCF driven plasma of hot fusion as well.This short TM(technical memorandum)written by these two authors will cover this aspect of technology in a holistic way and the more granular level is left to the reader of this TM to investigate further.

Transcranial and Repetitive Transcranial Magnetic Stimulation Driving a Noninvasive Depression Treatment

These days the most devasting disease that is even worse than the new pandemic COVID19 is commonly spreading and exists is human depression to be more specific.The world-wide episode of depression is something that has no permanent cure either among the youngsters in particular and older people in general.Researchers and scientists in the field of medicine and psychology are looking for some noninvasive approaches to treat this disease.Present chemical medications available in the market that are subscribed to patients are not effective as one set of solution across all the patients and in case of deep depression invasive solution such as clinical Electro-Convulsive Therapy(ECT)in most cases should not be prescribed due to tremendous and devasting side effects of it on patients that are going through such treatment for long term as a means of solution to their depression problem.New studies and clinical results are supporting a new generation of magnetic treatment approach that is known as Transcranial Magnetic Stimulation(TMS)or in case of a longer term suggests repetitive Transcranial Magnetic Stimulation(rTMS),both as very non-invasive approaches with almost no adverse side effects on patients that are receiving such clinical treatments.In this paper we study these two recently approved approaches by Food and Drug Administration(FDA)as well as a newly suggested electric energy medicine by utilizing a new form of wave that is known as a Scalar Wave,which is a non-linear,non-Hertzian,standing wave capable of supporting significant effects including carrying information and inducing higher levels of cellular energy,which greatly enhances the performance and effectiveness of the body and immune system.

Thermal Physics and Statistical Mechanics Driven Inertial Confinement Fusion(ICF)Inducing a Controlled Thermonuclear Energy

In the 1970s,scientists began experimenting with powerful laser beams to compress and heat the hydrogen isotopes to the point of fusion,a technique called ICF(Inertial Confinement Fusion).In the“direct drive”approach to ICF,powerful beams of laser light are focused on a small spherical pellet containing micrograms of deuterium and tritium.The rapid heating caused by the laser“driver”makes the outer layer of the target explode.In keeping with Isaac Newton’s Third Law“For every action,there is an equal and opposite reaction”,the remaining portion of the target is driven inwards in a rocket-like implosion,causing compression of the fuel inside the capsule and the formation of a shock wave,which further heats the fuel in the very center and results in a self-sustaining burn.The fusion burn propagates outward through the cooler,outer regions of the capsule much more rapidly than the capsule can expand.Instead of magnetic fields,the plasma is confined by the inertia of its own mass—hence the term inertial confinement fusion.A similar process can be observed on an astrophysical scale in stars and the terrestrial uber world,that have exhausted their nuclear fuel,hence inertially or gravitationally collapsing and generating a supernova explosion,where the results can easily be converted to induction of energy in control forms for a peaceful purpose(i.e.,inertial fusion reaction)by means of thermal physics and statistical mechanics behavior of an ideal Fermi gas,utilizing Fermi-Degeneracy and Thomas-Fermi theory.The fundamental understanding of thermal physics and statistical mechanics enables us to have a better understanding of Fermi-Degeneracy as well as Thomas-Fermi theory of ideal gas,which results in laser compressing matter to a super high density for purpose of producing thermonuclear energy in way of controlled form for peaceful shape and form i.e.CTR(Controlled Thermonuclear Reaction).In this short review,we have concentrated on Fundamental of State Equations by driving them as it was evaluated in book Statistical Mechanics written by Mayer,J.and Mayer,M.in this article.

Energy Sources Driven Electricity Production: A Global Tactical and Strategical Paradigm

Energy forecasting for electricity productivity is the process of applying statistics with possible Quantum or Classical Computing with help from new innovative techniques offered by artificial intelligence to make predictions about consumption levels.This kind of computation presents corresponding utility costs in both the tactical and strategical or short term and long term.Energy forecasting models take into account historical data,trends,weather inputs,tariff structures,and occupancy schedules in the urban city due to population growth,etc.to make predictions.Additionally,energy forecasting as future paradigm is driven by electricity production demand and it is a cost-effective technique to predict future energy needs,which is a paradigm to achieve demand and supply chain equilibrium based on available energy both renewable and non-renewable sources.

Artificial Intelligence Driven Nuclear Power Reactors(A Technical Memorandum)

The 21st Century era and new modern technologies surrounding us day-in and day-out have opened a new door to“Pandora Box”,that we do know it as AI(artificial intelligence)and its two essential integrated components namely ML(machine learning)and DL(deep learning).However,the strive and progress in AI,ML,and DL pretty much has taken over any industry that we can think of,when it comes to dealing with cloud of structured data in form of BD(big data).A NPP(nuclear power plant)has multiple complicated dynamic system-of-components that have nonlinear behaviors.For controlling the plant operation under both normal and abnormal conditions,the different systems in NPPs(e.g.,the reactor core components,primary and secondary coolant systems)are usually monitored continuously,which leads to very huge amounts of data.Of course Nuclear Power Industry in form of GEN-IV(Generation IV)has not been left behind in this 21st century era by moving out of GEN-III(Generation III)to more modulars form of GEN-IV,known as SMRs(small modular reactors),with a lot of electronic gadgets and electronics that read data and information from it to support safety of these reactor,while in operation with a built in PRA(probabilistic risk assessment),which requires augmentation of AI in them to enhance performance of human operators that are engaged with day-to-day smooth operation of these reactors to make them safe and safer as well as resilience against any natural or man-made disasters by obtaining information through ML from DL that is collecting massive stream of data coming via omni-direction.Integration of AI with HI(human intelligence)is not separable,when it comes to operation of these smart SMRs with state of the art and smart control rooms with human in them as actors.This TM(technical memorandum)is describing the necessity of AI playing with nuclear reactor power plant of GEN-IV being in operation within near term sooner than later,when specially we are facing today’s cyber-attacks with their smart malware agents at work.

Materials Response to High Power Energy Lasers(A Short Course—PartⅣ)

A complete understanding of laser interaction with materials is still a matter of trials and adjustments.The real physical processes of laser beam interaction(drilling,cutting,welding,or being used as a directed energy weapon application)with materials are very complex.Problem of laser interaction with materials presents many difficulties,both from modeling as well as from experimental sides.One would expect a reasonable description of the main phenomena occurring during laser interaction,but this is complicated because many of physical processes equally contribute to the development of conservation equations,producing drawback because of a great complexity of the equations to be solved.In most instances,this leads to formulation of a model needed to be solved numerically.A lack of pertinent experimental data to compare with,forces one to simplify some equations and use previous analytical and computational work done in this field.In Part IV here,we cover the absorption coefficient,which can be derived from the material’s dielectric function and conductivity,determines the absorption of light as a function of depth.However,the specific mechanisms by which the absorption occurs will depend on the type of material.In general,photons will couple into the available electronic or vibrational states in the material depending on the photon energy.In insulators and semiconductors,the absorption of laser light predominantly occurs through resonant excitations such as transitions of valence band electrons to the conduction band(inter-band transitions)or within bands(inter-sub-band transitions).In this part we cover all the aspect of the“Mathematical of Laser Absorption in Metals”that fits into this part of our suggesting short courses in different parts so far.

Materials Response to High Power Energy Lasers(A Short Course-Part V(b))

As we have stated in conclusion of PART IV of these series including PART V,here in wrapping up and ending these series,we are producing with PART VI,which is nothing more than continuation of PART V.

Our Daily Life Dependency Driven by Renewable and Nonrenewable Source of Energy

Our dependency on energy is so vital that it makes it difficult to imagine how humans can live on our planet earth without it.The demand for electricity,for example,is directly related to the growth of the population worldwide,and presently,to meet this demand,we need both renewable and nonrenewable energy.While nonrenewable energy has its shortcomings(negative impact on climate change,for example),renewable energy is not enough to address the ever-changing demand for energy.One way to address this need is to become more innovative,use technology more effectively,and be aware of the costs associated with different sources of renewable energy.In the case of nuclear power plants,new innovative centered around small modular reactors(SMRs)of generation 4th of these plants make them safer and less costly to own them as well as to protect them via means of cyber-security against any attack by smart malware.Of course,understanding the risks and how to address them is an integral part of the study.Natural sources of energy,such as wind and solar,are suggesting other innovating technical approaches.In this article,we are studying these factors holistically,and details have been laid out in a book by the authors’second volume of series title as Knowledge Is Power in Four Dimensions under Energy subtitle.

Materials Response to High Power Energy Lasers (A Short Course-Part III)

With recent attention to high power energy and its interaction with materials of different type,both in industry and military application,this paper covers a short review course into subject of materials response in respect to such high power energy lasers.In this paper,we are covering laser interaction with solid and going through steps of phase changes,from solid to liquid and finally vapor stage.As we indicated in this part of short course mainly Part I and Part II,we have started a series of articles on the subject of Materials Responses to High Power Energy Lasers and continue these series by starting to introduce the Laser Light Propagation into materials.In this part namely Part III,we are discussing,one of the most important effects of intense laser irradiation is the conversion of the optical energy in the beam into thermal energy in the material.This is the basis of many applications of lasers,such as welding and cutting.We shall summarize here this thermal response.It is basically a classical problem,namely heat flow,in a usual manner of heat conduction,we show solutions to the equation which governs the flow of heat and discuss change of phases in targeting material from solid to liquid and finally vapor and plasma stages step by step.

Energy Driven by Internet of Things Analytics and Artificial Intelligence

Developing an integrated and intelligent approach to securing the ITE(information technology environment)is an emergent and evolving concern for every organization and consumer entity during the last few decades.Major topics of concern include“SI”(security intelligence),“D-DA”(data-driven analytics),“PE”(proven expertise),and“R-TD”(real-time defense)capabilities.“DRBTs”(dynamic response behavior types)include“incident response”,“endpoint management”,“threat intelligence”,“network security”,and“fraud protection”.The consumer demand for electricity as essential public access and service is indexed to population growth estimates.Consumer-driven economies continue to add electrical consumption to their grids even though improvements in lower-power consumption and higher design efficiencies are present in new electric-powered products.Dependence on the production of electrical energy has no peer replacement technology and creates a societal vulnerability to targeted public electrical grid interruptions.When access to,or production of,electrical power is interrupted,the result is a“Mass Effect”every consumer feels with equal distribution.Electric grid security falls directly into the levels of authorized,and unauthorized,access via the“IoT”(Internet of Things)concepts,and the“IoM2M”(Internet of Machine-to-Machine)integration.Electrical grid operations that include production and network management augment each other in order to support the demand for electricity every day either in peak or off-peak,thus cybersecurity plays a big role in the protection of such assets at our disposal.With help from AI(artificial intelligence)integrated into the IoT a resilient system can be built to protect the electric grid system nationwide and will be able to detect and preempt Smart Malware attacks.

Materials Response to High Power Energy Lasers(A Short Course—Part II)

With recent attention to high power energy and its interaction with materials of different types,both in industry and military application,this paper covers a short review course into subject of materials response in respect to such high power energy lasers.In this paper,we are covering laser interaction with solid and going through steps of phase changes,from solid to liquid and finally vapor stage.As we indicated in this part of short course mainly Part I,we have stated of series of article on the subject of Materials Responses to High Power Energy Lasers and continue these series by starting to introduce the Laser Light Propagation either in vacuum or through atmosphere by also introducing thermal blooming effects as well,then we cover,subjects such as Optical Reflectivity,thermal responses of materials by looking at Latent Heat of Fusion as well as Vaporization,No Phase Changes in both Semi-Infinite Solid or Slab of Finite Thickness,Melting and Vaporization and then move on to Effects of Pulsed or Continuous Laser Radiation as well,throughout of next few parts that we report them as further Short Courses content.