Comparison between the capacitive power transfer and inductive power transfer.
\r\n\tAn update on clinical manifestations, their assessment, monitoring, and imagiology, including peripheral arthritis, enthesopathy, and extra-articular findings, and, the differential diagnosis with other diseases which evolves with axial and peripheral calcifications will be provided.
\r\n\r\n\t
\r\n\tAn important component of this book must be dedicated to the more recent treatments namely with biologic therapies but focusing also on new small molecule inhibitors and experimental therapies.
Deliver long-range power over great distances is very interesting in the future. For this reason, the Wireless Power transfer (WPT) is a versatile modern technique that can be used by a range of electrical devices. Batteries play an important role in the mobility but have a high initial cost and a short life. For example, the first application of quick wireless charging has been applied in vehicles for public transportation in the traditional bus stations [1]. This form of application has such a small distance between stations and a short waiting period that it has been readily embraced by the WPT for electrical charging. Furthermore, research into EV wireless charging while driving or parking is really appealing and is helping to grow the industry [2]. Another case in point is the spread of so-called commercial electronics. This sector has already seen commercial successes of these WPT systems, particularly for smart-phone chargers, due to the problem of limited battery time and the large use [3]. Although it is difficult to realise those applications because the power must penetrate a thick material like the skin, the benefits of using a WPT device are definitely clear in implantable equipment for health care [4]. Wireless power distribution removes the need for percutaneous cables or surgeries to replace batteries, which may be uncomfortable and infection-prone. This results in a reduced size and lighter weight, or the removal of an energy storage feature that provides patient comfort. In both of these implementations, the propagation distance is critical to the application’s reliability.
An electric power is transmitted from a source such as a generator or a battery to a load if an electric potential differential is applied over a conductor. The use of cables and wires to link the source to a load is the preferred method to allow the electrons flow. However, electronic devices are getting smaller and more compact as technology progresses. Obtaining energy from a cable attached to a power outlet can no longer be a viable option. Mobile devices that involve a smart power supply management are being built and implemented. As a result, a wired connections restrict their mobility and, in some situations, may not be a secure choice if they are damaged.
Electrical energy can be converted into other types of energy that can be transmitted through a particular medium without the use of conductive wires. The use of radio waves to transmit information, such as sound, video and data is a clear example of transmitting energy wirelessly. In a radio station, a voltage signal reflecting the information is produced and then converted into an electromagnetic energy pulse, which is broadcast into the atmosphere, where it spreads in all directions. An antenna detects the electromagnetic energy signal at a lower energy frequency. This signal is then converted back into an electrical voltage signal from which the information is derived.
Depending on the distance between transmitter and receiver, the power can also be converted in energy and then transmitted. Electromagnetic waves are generated in the surrounding media by any electromagnetic field source (point particle, dipole, antenna, or coil). The electromagnetic waves are distinguished by the properties of the fields and how these are associated with the medium in which they are travelling. These fields are normally divided into two types: the near-field and far-field (shown in Figure 1), based on their distance from the source and, more specifically, the characteristics of the dominant waves in this area.
Representation of wireless power transmission in (a) far field where is highlighted the rectenna, and (b) near field.
In addition to the near-field, it can be further subdivided into the reactive (non-radiative) near-field and the radiative. The wavelength of the field source is normally used to define these limits as shown in Figure 2. As a consequence, an electromagnetic (EM) wave’s wavelength, which is proportional to its energy, defines how it interacts with its surroundings. Its limits depends on the wavelength
Region partition depending from the wavelength
The reactive (non-radiative) region is on the very short range of
The first methods of electromagnetic coupling were discovered by Tesla in the 1900s [7], by capacitive coupling, which is possible to use the electric field for power transfer in the near-field. However, there was a high voltage present between the transmitter and receiver, which could result in electric shock. The main reason is that the experiment was based on the electric arc. The two electrodes on the capacitor are the transmitter and the receiver of the power transfer system with the air being the dielectric. During each voltage pulse, the output voltage rises to the point where the air around the high voltage terminal ionises, causing corona, brush discharges, and streamer arcs to emerge from the terminal, as shown in the Figure 3. This event occurs only when the electric field strength surpasses the air’s dielectric strength, which is around
Recent demonstration of the Tesla experiment in Ref. [
The CPT is based on this functionality, where two parallel plates (a capacitor) are on a very small distance apart because of safety issues of the above mentioned electric arc. The transmitter is attached to the first plate on each capacitor, and the receiver is connected to the second plates, as shown in Figure 4. Air is the dielectric forming a capacitor of:
Principle of the capacitive power transfer (CPT).
where
This design can be expanded by adding two connected capacitor plates in both sides (transmitter and receiver) with an electric field between them, as shown in Figure 4. The created electric field causes an alternating current to pass in the receiver plates. Thus, power is being sent through the secondary plates of the receiver. The capacitive area is designed after the application, where plates can take on multiple shapes, for example, rectangular, disc, or cone, or specific architecture such as a matrix [10].
The amount of power transmitted (power loss on the components is neglected) through the capacitor electric field is thus approximately calculated:
where
The use of a magnetic field for power transfer has the safety benefit of not using high voltages and not interacting with most biological material. As a result, the magnetic field is used in the majority of modern near-field WPT studies and has a vast range of applications. A non-radiative magnetic field is produced by passing an alternating current (AC) through a coil known as the transmitter, as shown in Figure 5. When a load circuit is in vicinity to the reactive area, an electromotive force (EMF) is produced in a second coil, known as receiver. In this way, the electrical power is passed from the transmitter’s coil to the receiver’s coil. There is a mutual inductance between between the transmitting and receiving coils. This inductance is one of the most significant parameters that affects the power transmitted in inductively coupled wireless power transfer systems.
Principle of the inductive power transfer (IPT).
The mutual inductance M between two coils, Tx and Rx, is shown in Figure 5, where alternating current is guided inside coil, Tx, and induced current appears in the coupled coil, Rx. The current flowing in
where
The amount of power transmitted (power loss on the components has been neglected) through the magnetic field is thus approximately calculated:
where
Research studies into the inductive power transfer in IPT has been focused on increasing the yield. Performance and reliability are sure to be improved as new designs, components, such as core, coil shapes and configurations, and ways of handling conductivity, are further researched [11, 12, 13]. Finite element analysis (FEA) is a computerised method to predicting how the magnetic field is distributed in the air and how coils react to real-world forces, heat and other physical effects. In Figure 6 it is shown the simulation of WPT system by using ANSYS Electronic v14, where it can be seen the diffusion (Figure 6a) and the flux lines (Figure 6b) of the magnetic field.
Magnetic field shown in ANSYS software simulation: (a) the diffusion and (b) the flux lines of the magnetic field.
A largely adopted technique in the near-field magnetic coupling is the resonance which has largely extended the potential of the near-field WPT. A capacitor is connected to the coils to form the LC resonant tank. Therefore, an impedance transformation network is made by the resonant tank at the oscillation frequency
where
As a whole, WPT (both IPT and CPT) throughput power decreases in a linear trend (for a log scale) with increasing frequency. It is likely that this limitation is primarily determined by power electronics limitations, rather than coupling characteristics, since it affects IPT and CPT equally. As the frequency increases, the output power is limited by losses. This limitation appears in both IPT and CPT applications. The average power is increased by 10-fold in the last 10 years, with the frequency also increased by 10-fold. In part, this is attributed to the development of wide bandgap devices and the refinement of coupling structures to minimise losses. It is expected that the power-frequency empirical limitation will continue to increase with time, essentially like a “Moore’s Law” trend or variant for WPT. In Table 1, there is a further summary between typical differences in the development between CPT and IPT.
Inductive power transfer | Capacitive power transfer | |
---|---|---|
Switching frequency | 10 kHz | 100 kHz |
Coupling field | Magnetic | Electric |
Foreign objects (metal) | Will generate heat | Will not generate heat |
Material | Litz wires, ferrites | Copper/aluminium plates |
Cost | High | Low |
Safety | Good | Excellent |
Size | Small | Large |
Misalignment | Poor | Good |
Efficiency | Excellent | Excellent |
Voltage stress | Medium | High |
Power level | High | Medium |
Stationary or dynamic | Better for stationary | Both |
Comparison between the capacitive power transfer and inductive power transfer.
When the distance between transmitter and receiver is smaller than the geometry of the transmitter, is indicated as a small-range WPT. As a practical rule, the mid-range refers to the situation when the gap is 2 to 3 times the size of either device involved in the power transfer.
Two coil systems are used for charging both portable and heavy power devices like powerbanks. An optimal alignment has the greatest coupling co-efficient where the coils are the same size and parallel to each other. The mutual inductance declines as the ratio of the two coils’ primary magnetic field decreases, particularly when there is a broad separation between the two coils.
Multiple coils in the transmitter, receiver, or in the middle are adopted essentially for two main reasons: (a) more degrees of freedom to maximise the efficiency and desensitise the link gain versus coupling factor; (b) highly coupled transmitter-repeater or repeater-receiver link work greatly as impedance matching elements at both sides. Although this last configuration requires four or more coils, it offers a better efficiency-distance than a three coils system [14]. For this reason, the three coil WPT is not very popular, unless the application has no space for additional coils.
Let us consider a four-coil resonator system with two intermediate repeaters coils called “2” and “3” where an impedance (capacitor) compensation
Four coils WPT system with the coupling factors. The couplings are marked following their value.
calling
Combining these equations in the Eq. (8)c, it is possible to obtain the impedance reflected in the primary transmitter:
where simplifying we obtain:
In this equation we can notice that the reflected impedance of the all system depends directly only by the total coupling coefficient and the value of receiver impedance. Moreover, the WPT system can be seen as an equivalent total coupling coefficient defined by:
It is a design rule making sure that the following condition can be met:
the reflected load will be matched and we will have the maximum power transferred. In such a way, the four coils system creates a possibility to extend the distance from primary to the load using more and more coils. In order to maximise the transmission distance, the mutual coupling coefficient between the repeaters could be minimised. Additional intermediate coils with still be loose coupled between them but they will increase the total coupling coefficient of the system. For example, even if the coefficient
However, the impedance matching such a system is not endowed with a high overall efficiency because it is restricted by the merit factor given by the Eq. (9) Nonetheless, the four-coil system still offers (in terms of efficiency-distance) a better solution rather the two-coil systems when the distance is much bigger than the coil size.
The power transfer in short transmission distance is commonly achievable with good coupling coefficient which depends on the medium between coils whether it is air or any material with permeability 1 or above. In addition, the best coupling coefficient is obtained when the coils have the same dimensions, negligible gap and they are perfectly aligned. The alignment of the transmitter not correct with the receiver has been the first challenge to overcome in this technology. Therefore, the charging appliance are usually fabricated in a similar size in order to have a visible matching. Although the system efficiency and power transferred can be maximised, the following problems can arise in these systems.
Cross-talking or localised charging happens if the transmitter is much larger than the receiver. The magnetic flux path should only occur between the transmitter coil and the receiver coil. Only the transmitter coil that is closest to the receiver is powered on with others around in standby mode. This type of WPT are mostly used on dynamic EV charging applications where power consumption by each transmitter coil can be monitored to roughly identify the position of the receiving coil.
Not-alignment between primary-secondary coil is usually measured in degrees, from perfectly aligned
The foreign objects detection (FOD) near the transmitter coil or pad cause safety issue because of the eddy current created inside metallic objects. An increased temperature can be observed in daily metal objects such as coins, keys and metallic packaging materials. In Figure 8 is shown the effect of a commercial chew-gum in its typical aluminium wrap. Eddy currents have increased temperature and a begin of fire have started.
FOD to a chew-gum aluminium wrap which have begun a fire.
In the far-field range, the power is transmitted through microwaves and in practice has been developed for low-power applications, because of its low efficiency. However, despite the low intensity the light rays are able to transmit the power. For instance, Sun rays can generate large amounts of energy in spite of travelling enormous distances. Similar to the other far field sources, the power generation occurs in specific conditions and in large amounts. A great use of this technique will be the solar farms in large areas of Saudi Arabia, which are able to generate nearly the same level of electricity per year compared to the traditional power generation stations [15].
The Radio Frequency (RF) signals have powered very low power application and is more considered as a harvesting energy solution. The ultrasound waves and vibrations are also utilised in similar applications. The waves are converted through the piezoelectric effect as transducer for electrical signal and are considered as energy harvesting from the environment.
Microwaves are electromagnetic waves of frequencies ranging from 1 to 30 GHz. They are widely used in today’s applications, especially in communications. Microwaves, differently from radio waves, can be sent in narrow beams, allowing the transmitter to concentrate its energy on the receiver. Microwaves are emitted or radiated from an antenna that is fed with a high frequency current in low power applications such as mobile phones. Another antenna will then pick up the microwaves and transform them back to an electric current.
The conversion of microwaves back to electricity was the biggest barrier to overcome in order to convert back the highest amounts of power. When an antenna picks up a microwave signal, it generates an alternating current of the same frequency as the microwave signal and equal to the microwave’s signal strength. Since all applications and devices run on either an AC voltage of 50 Hz or 60 Hz or a constant DC voltage, the microwave antenna’s high frequency current must be converted to a suitable voltage type. A great development of this technology was the invention of the ‘rectenna’ or ‘rectifying antenna’ by W. Brown. Using a rectifier, the rectenna converts the microwave antenna’s high frequency current into a DC voltage. Further advancements in the semiconductor technology coupled with the availability of Schottky-barrier diodes resulted in higher efficiencies, higher power capabilities and smaller rectenna designs [16].
The power efficiency, seen as Power Conversion Efficiency (PCE) in the Figure 9, is the capability of a rectifier to transform radio frequency (RF) energy into DC current. The PCE depends on the diode conduction and reverse leakage losses. The input voltage varies according to the frequency, which means the diode impedance varies, leading to a difference in the performance loss. In low input power, the efficiency is low because the input voltage dynamic is lower or equal to the forward biasing voltage of the diode.
Receiver block diagram where it has been highlighted the rectifier ant its efficiency.
In general, the PCE varies with the input dynamic which in turn depends on
Diode efficiency function depends on the breakdown voltage and the load resistance.
Diode-based rectifier circuits are the most common because they have a lower forward voltage drop compared to the CMOS circuits. In rectenna applications, Schottky barrier diodes are widely used due to offering the best alternative to achieve higher PCE, a diode with a lower forward voltage.
The simplest rectifier circuit consists of a series shown in Figure 11a (or parallel in Figure 11b) and a parallel (or series) capacitor. The series diode circuit is also known as Villard Rectifier or DC restorer. The waveform produced is shown in Figure 12a. The parallel version is the well-known half-wave rectifier. When AC voltage comes through D1, only the positive cycle goes in the output, as shown in Figure 12b. Because of the reduction of the input, the full-wave rectifier, as shown in Figure 11c, is the most popular circuit. The output voltage sees two capacitors in series (each one is storing a voltage of Vpeak). Thus, Vout is a DC voltage twice the Vpeak, as shown in Figure 12c. For this reason this circuit is also known as a single-stage voltage doubler circuit or Cockroft Walton voltage doubler.
The four typical configuration of the rectifier: (a) series, (b) parallel, (c) full-wave (d) bridge rectifier.
Voltage waveforms (y-axis) simulated towards time (x-axis). The input test is a 1 Volt peak-to-peak (10 kHz) voltage. For each configuration of the rectifier, the red colour represents the input voltage and the blue represents the output voltage, respectively: (a) series rectifier waveforms, (b) parallel rectifier waveforms, (c) full-wave rectifier waveforms, (d) bridge rectifier waveforms.
Therefore, this topology is more stable and efficient than the halfwave rectifier. There is also the bridge rectifier shown in Figure 11d, which rectifies both positive and negative. The figures in Figure 12 summarise the waveforms obtained. As we can see, the full-wave and the Bridge rectifier “double” voltage have the highest output voltage, as shown in Figure 12d.
Different configuration of circuits that convert AC to DC by increasing the values goes with the name of voltage multiplier. The most fundamental configuration is the Cockcroft–Walton voltage multiplier shown in Figure 13a. This circuit’s operational principle is similar to the full-wave rectifier but has more stages for higher voltage gain. The Dickson multiplier in Figure 13b is a modification of Cockcroft–Walton’s configuration with stage capacitors being shunted to reduce parasitic effects. Thus, the Dickson multiplier is preferable for small voltage applications. However, it is challenging to obtain high PCE due to the fact that the high threshold voltage among diodes creates leakage current, thus reducing the overall efficiency. Additionally, for high resistance loads, output voltage drops drastically leading to low current supply to the load.
Most common voltage multiplier configurations: (a) three stages Cockcroft–Walton voltage multiplier, (b) four stages Dickson voltage multiplier, (c) four stage Dickson voltage multiplier using CMOS technology, (d) two stages voltage multiplier comprised of differential drive unit.
Limitation of diodes can be overcome by MOSFET technology. Major advantage of MOSFET is the fast switching speed. Dickson charge pump is also designed using MOSFETs in order to merge it in integrated circuits as shown in Figure 13c. Relatively low threshold voltages and high PCEs are features of this design.
Moreover, differential drive voltage multiplier Figure 13d is widely used because of its low leakage current and potential for further modification in specific applications. The number of stages in a voltage multiplier has a close relationship with its sensitivity and efficiency. If the number of stages grows, the amount of losses per stage increases. However, the tradeoff consists of a higher voltage multiplication and small threshold voltage at the first stage. On the other hand, a voltage multiplier with a few stages has less voltage drop between its stages, but it requires higher threshold voltage for all stages to work simultaneously. As a result, when a large number of stages are present, a voltage multiplier becomes more susceptible, whereas when smaller stages are present, it becomes more effective. Therefore, based on the implementation goals, the optimum number of steps should be considered.
The voltage loss across MOSFET devices leads to low efficiency. This is further deteriorated by reverse leakage current. Another major disadvantage of MOSFET based circuits is that as frequency increases, the efficiency decreases. This happens due to increased power losses from the reverse leakage current in the MOSFET.
The wireless power transfer technique has received a lot of research attention in recent years. As a result, it is becoming a more popular application in consumer electronics and electric cars. There are, however, other methods for transmitting electricity, which can be categorised further based on their working ranges, such as near-field and far-field transmission. This chapter provides an outline of the concepts of various methods of wireless power transfer. The investigation of the receiver block is then addressed by looking at the characteristics of rectifier technologies. Later in the book, the Rectenna device (rectifying antenna) is defined in relation to Internet of Things (IoT) wireless charging in remote locations.
Evolution in one region of science and technology leads to the discovery of a new one. In less than a century, research and development of functional computing technologies have renovated science, technology, and nation massively. The first practical computer around the 20th century was not capable of doing mathematical computations, on its own. Practical devices need a solid physical implementation of theoretical concepts. Nowadays, computers are solving problems instantly and accurately provided the input is relevant, and a set of instructions given are favorable. It all started from World War II when Alan Turing created a real general-purpose computer with a storable program model and is known as the ‘Universal Turing Machine’. It was redesigned by Von Neumann and is now the most important architecture for almost every computer. The computers and their physical parts kept improving with time in terms of performance and their strengths. And gradually, the industry of computers became larger than the military department which initiated it. The advancement in control and understanding of humans over nature and physical systems has given us the latest electronic devices we are utilizing today [1].
Today’s computers are smaller, cheaper, faster, greatly efficient, and even more powerful as compared to early computers that used to be huge, costly, and more power-consuming. It becomes possible due to improvements in architecture, hardware components, and software running on them. Electronic circuits used in computers are getting smaller and smaller day by day. Transistors are small semiconductor devices that are used to amplify and also switch electric or electronic signals. They were used to be fabricated on a piece of silicon. The circuit was made by connecting these transistors together into a single silicon surface. The shape of circuits in an IC was printed together in all layers of silicon at the same time. This process takes the same amount of time even if the number of transistors in the circuit was increased. The cost of production of IC was decided by the size of silicon and not the number of transistors. This reduced the price of products due to which manufacturing and selling of IC increased and thus benefits and sales also. From the idea of connecting individual transistors to the collection of these transistors (Logic Gates) and finally, the collection of these Logic Gates used to get connected into a single integrated circuit (IC). Nowadays, a single IC can even integrate small computers onto it.
Gordon Moore, co-founder of Intel, in 1965, discovered that the number of transistors on a silicon microprocessor chip had made twice as much every year while the prices were reduced to half since their invention. This is known as Moore’s Law. Moore’s Law is considerable because it means that computers and their computing power get smaller and faster over time. Though this law is putting the brakes on now and consequently, the improvement in classical computers is not like before it used to be [2].
This leads to the idea of the smallest computer by reducing the size of the circuit up to the size of an atom. But then these circuits will not be able to act as a switch as electrons inside an atom can become invisible from one side of a barrier and appear on another side, i.e. they can exist in more than one place at the same time. This is due to the teleporting phenomena in quantum mechanics called “Quantum Tunneling”. It shows that the size of the circuits of the classical computer after 5–7 nanometers has reached their limit. The representation and processing of these computers can be illustrated by the law of classical physics that gives us an only deterministic justification of the Universe. But it fails to forecast all noticeable phenomena occurring in nature and this led to the discovery of quantum mechanics, the biggest changeover in physics. Thus, there is a need for new computing other than current classical computing to put its state into some physical information rather than a circuit. Since the quantum phenomena are bringing up more constraints on the design of the computers. It changes the basic building blocks of a computer that not only expects new type of hardware creation but also a new design, software, and layers of abstraction to facilitate the designers to create and exploit these systems even if their complexities scale over time. The design of the hardware components has to be governed by quantum properties [3].
Quantum computers can solve any computational problem that any classical computer can. According to the Church-Turing thesis, the converse is also true that classical computers can solve all the problems of quantum computers too. It means they provide no extra benefit over classical computers in terms of computability but there are some complex and impossible problems that cannot be solved by today’s conventional computers in a practical amount of time. It needs more computational power. Quantum computers can solve such problems in reasonably and exponentially lower time complexities, also known as “
Peter Shor in 1993 showed that Quantum computers can help to solve these problems considerably more efficiently like in seconds without getting overheated. He developed algorithms for factoring large numbers quickly. Since their calculations are based on the probability of an atom’s state before it is actually known. These are having the potential to process data in an exponentially huge quantity. It also explains that a practical quantum computer could break the cryptographic secret codes. It can risk the security of encrypted data and communication. It can expose private and protected secret information. But the advantages of quantum computers are also kept in mind that is significantly more than its flaws. Hence, they are still needed and further research is going towards a brighter future.
While designing the conventional computer, it was kept in mind that transistors’ performance especially when getting smaller, will be affected by noise if any type of quantum phenomenon takes place. They tried to avoid quantum phenomena completely for their circuits. But the quantum computer adapts a different technique instead of using classical bits and even works on the quantum phenomenon itself. It uses quantum bits that are analogous to classical bits and have two quantum states where it can be either 0 or 1 except it follows some quantum properties where it can have both values simultaneously leading to a concept of superposed bits.
Transistors are the fundamental construction blocks for an IC which are connected through wires in a circuit. They conduct electric signals between devices. The communication between transistors within an IC takes place through electric signals. The behavior of the signals is analog in nature. Therefore, their values are real numbers that change smoothly between 0 and 1. These electric signals can also interact with the environment resulting in noise. Therefore, a little change from 0 to 0.1 due to temperature or vibrations from the environment can drastically change the system’s behavior. There are two types of noise present in the environment. The first type of noise results from energy instabilities occurring suddenly within the object like temperature above absolute zero Kelvin. These are fundamental in nature. Other types of noise are the consequences of signal interactions. This type of noise could have corrected or designed. But neither of them got designed nor corrected or maybe left intentionally uncorrected at the hardware layer. They are systematic in nature [5].
To overcome these noises in analog circuits, the IC is built with transistors in such a way that it could work on digital signals (binary bits) instead of analog signals. These circuits are called ‘Logic Gates’. They perceive the electric signals containing values of real numbers as a binary digit or ‘bit’ of either 0 (low voltage) or 1 (high voltage). Registers are another type of Gate which stores a bit or the number of bits present in an input value to process further. Gates can remove noise from a signal by limiting the set of values a signal can hold. Constructing IC using logic gates rather than transistors simplifies the designing by creating a powerful circuit that is not sensitive to design and fabrication issues and facilitates abstraction to designers so that they can focus only on gate functions (Boolean functions) rather than circuit issues. Boolean functions are defined by the rules of Boolean algebra. They can use an automated design tool for mapping the required logic gates. A standard library containing a set of tested logic gates is integrated into the silicon chip design with the help of their manufacturing technology. Negligible error rates can be achieved using digital logic and standard libraries. This helps in making the design robust. Also, the data is encoded by adding some redundant bits in the memory using an error correction code. This code is checked at regular intervals to detect the error. It also helps in other traits of design like testing and debugging.
Qubit has two quantum states similar to the classical binary states. The qubit can be in either state as well as in the superposed state of both states simultaneously. There is a representation of these quantum states also known as Dirac notation [6].
In this notation, the state label is kept between two symbols | and ⟩. Therefore, states are written as |0⟩ and |1⟩ which are literally having analog values and both are participating to give any value between 0 and 1 given that sum of probability of occurrence of each state must be 1. Thus any quantum bit wave function can be expressed as a two-state linear combination each with its own complex coefficient i.e. |w⟩ = x |0⟩ + y |1⟩ where x and y are coefficients of both the states. The probability of the state is directly proportional to the square of the magnitude of its coefficient. |x|2 is the probability of identifying the qubit state 0 and |y|2 is the probability of identifying the qubit state 1. These probabilities when summed up must give a total of 1 or say 100% mathematically, i.e. |x|2 + |y|2 = 1.
In quantum physics, the quantum object does not exist in an entirely determined state. It looks like a particle but behaves like a wave when not being observed. This dual nature of particles leads to interesting physical phenomena. The state of any quantum object is expressed as a sum of possible participating states or a wave-function. Such states are coherent due to the interference of all the participating states either in a constructive or a destructive manner. Observation of quantum objects when they interact with some larger physical system results in the extraction of information. Such observation of quantum objects is called quantum measurement. Measurement can also result in the loss of information by disrupting the quantum state. These are some of the properties of quantum objects. Quantum objects referred here are the qubits in the case of quantum computing. The progress of any quantum system is regulated by Schrodinger’s equation that tells us about the change in the wave-function of the system due to the energy environment. This environment is the system Hamiltonian which is a mathematical description of energies experiencing from all forces felt by all components of the system. To control any quantum system, there is a need to control this environment by isolating the system from the forces of the universe that cannot be controlled easily and by assigning energy within this isolated area only. A system cannot be completely isolated. However, energy and information exchanges can be minimized. This interaction with the outside environment can lead to loss of coherence and can result in “Decoherence” [7].
The properties are the conceptual rules and mathematical manifestations that describe the behavior of the particles. Quantum computers use three fundamental properties of quantum mechanics to store, represent, and perform operations on data in such a way so that it can compute exponentially faster than any classical computer. The three properties are given as follows [8]:
Superposition
Superposition in quantum mechanics states that any two quantum states can be summed up (superposed) resulting in another valid quantum state. It is a fundamental principle of quantum mechanics. Oppositely we can say that any quantum state is the sum of two or more than two other unique states.
Superposition in quantum computing refers to the ability of a quantum system where quantum particle or qubit can exist in two different positions or say, in multiple states at the same time. It provides high-speed parallel processing in an unbelievable way and is very different from their classical equivalents that have binary constraints. The quantum computer system holds the information that exists in two states simultaneously. Qubits are brought into a superposition by influencing them with the help of lasers so that it can simultaneously store 0 and 1 at the same time. In classical computing, if there are 2 bits, the total possible values after combining we get are 4, out of which only 1 value is possible at any instant. But on the other hand, if there are 2 qubits in the quantum computer. The total possible values after combination are 4 and all are possible at once. It looks like unthinkable because it is not like gravity that can be proved easily just by looking at the falling of an apple. The laws of classical physics fail here because superposition only exists in the territory of quantum particles.
For example, when solving a puzzle-like maze, a quantum particle can decide to take the various paths at the same time using superposition. This process matches the function of the parallel computer. Due to this property, the qubit is able to navigate the maze in exponentially less time than a classical bit
Entanglement
Entanglement in quantum mechanics is a physical phenomenon where two or more quantum objects are inherently linked such that measurement of one rules the possible measurement of another. In other words, a pair or a group of particles interacts or share spatial locality such that the quantum state of each particle cannot be characterized independently of the other particle’s state in the same group even when they are separated by a large distance.
Entanglement is one of the important properties of quantum computing. It refers to the strong correlation existing between two quantum particles (physical properties of systems) or qubits. Qubits are linked together in a perfect instantaneous connection, even if they are isolated at any large distances such as located at the opposite ends of the Universe. They are entangled or defined with reference to each other. The fact is that the state of one particle influences the state of the other. It creates strong communication between qubits. Once they got entangled, they will stay connected even after separated at any distance. In classical computers, if bits are doubled, computational power also gets doubled. But in the case of Entanglement, adding extra bits to a quantum computer can increase its computational power exponentially. Quantum computer uses this property in a sort of quantum daisy chain.
Some examples of entanglement can be seen in nature such as electrons separated from each other at some distance inside an electron cloud are massively entangled with one another. If one electron is at both the states of spin-up and spin-down with each state having a probability of ½, a similar case is with the other electron.
Interference
The property of interference in quantum computers is similar to wave interference in classical physics. Wave interference happens when two waves interact with each other in the same medium. It forms a resultant wave with either their amplitudes added together when they are aligned in the same direction known as constructive interference or a resultant wave with their amplitudes canceled out when waves are in opposite direction known as destructive interference. The net wave can be bigger or smaller than the original wave depending on the type of interference. Since all subatomic particles along with light pose dual nature, i.e. particle and wave nature both. The quantum particle may experience interference. If each particle goes through both the slits (Young’s double-slit experiment) simultaneously due to superposition, they can cross its own path interfering with the path direction. The idea of interference allows us to intentionally bias the content of the qubit towards the needed state. However, it can also result in a quantum computer to combine its various computations into one making it more error-prone [9].
The quantum phenomena are not limited to just quantum computing but they apply to other technologies also including quantum information science, quantum communication, and quantum metrology. The progresses of all these technologies are mutually dependent on each other and can control as well as transform the entire quantum system. They share the same theory of physics, common hardware and related methods [10].
Comparison key | Classical computer | Quantum computer |
---|---|---|
Large scale integrated multipurpose computer based on classical physics | High speed parallel computer based on quantum mechanics | |
Bit based information storage using voltage/ charge | Quantum bit (qubit) based information storage using electron spin | |
Bits having a value of either 0 or 1 and can have a single value at any instant | Qubits having a value of 0,1 or sometimes negative and can have both values at the same time | |
The number of possible states is 2 which is either 0 or 1 | The number of possible states is infinite since it can hold combinations of 0 or 1 along with some complex information | |
Deterministic- (repetition of computation on the same input gives the same output) | Probabilistic- (repetition of computation on superposed states gives probabilistic answers) | |
Logic gates process the information sequentially, i.e. AND, OR, NOT, etc. | Quantum logic gates process the information parallel | |
Defined and limited answers due to the algorithm’s design | probabilistic and multiple answers are considered due to superposition and entanglement properties | |
Operations use Boolean Algebra | Operations use linear algebra and are represented with unitary matrices. | |
Circuits implemented in macroscopic technologies (e.g. CMOS) that are fast and scalable | Circuits implemented in microscopic technologies (e.g. nuclear magnetic resonance) that are slow and delicate |
Architecture can be seen as a blueprint. The architecture of the quantum computer is a combination of classical and quantum parts and can be divided into 5 layers where each layer is represented as the functional part of the computer (Figure 1).
The architecture of a practical quantum computer. It can be divided into five layers, each performing different types of processing [
There should be an interface between the quantum computer and conventional computers for tasks related to data, networks, and users. In order to function usefully, the quantum qubit system needs organized control that can be managed by a conventional computer. The necessary hardware components for analog quantum computers are designed in 4 conceptual layers. First is the “quantum data plane” where qubit is present. Second is the “control and measurement plane” which is liable for performing operations and measurement on qubits as needed. The third is the “control processor plane” which defines the sequence of those operations and measurement outcomes to inform successive quantum operations required by the algorithm. And the last one is “host processor” which is a classical computer running a conventional operating system that handles user interfaces, network access, and big storage data structures. The processor is controlled using a high bandwidth connection that it provides [13].
A functional Quantum computer also requires software components in addition to the hardware. It is comparable to classical computers. Various new tools including programming languages are needed to substantiate quantum operations so that programmers can formulate algorithms, compilers that can map them to the hardware used by quantum computers and some other supports which can evaluate, optimize, debug and test programs. The programming language must be designed for any targeting quantum architecture. Some preparatory tools have been developed to support quantum computers and are accessible on the web [14]. These tools must be designed in an abstract way so that software developers can think more algorithmically without much concern for details of quantum mechanics. This software must be flexible enough to adapt to the changes in hardware and algorithms. This is one of the biggest challenges in quantum computing to develop complete software architecture. Other than programming languages, there must be simulation tools for modeling quantum operations and tracking quantum states and optimization tools for evaluating needed qubit resources so that it can perform different quantum algorithms in an efficient manner. The main goal is to minimize the number of qubits and the operations required for the hardware [15].
An algorithm is a sequence of instructions or a set of rules to be followed to perform any task or calculation. It is a step-by-step process for solving a problem, especially by a computer. Any algorithm that can be executed on a quantum computer is called the
Quantum algorithms are characterized by a quantum circuit. A quantum circuit is a prototype for quantum computation that includes each step of the quantum algorithm as a quantum gate. A quantum gate is an operation that can be performed on any number of qubits. It changes the quantum state of the qubit. It can be divided into a single-qubit or multi-qubit gate, depending on the number of qubits on which it is applied at the same time. A quantum circuit is determined with qubit measurement [16].
An algorithm executing on a simulator rather than hardware is very profitable in terms of execution time by replacing the measurement overhead at the end of the algorithm. It is also known as simulation optimization. A quantum algorithm is always reversible when compared to the classical algorithm. It implies that if the measurement is not considered, a quantum circuit can be traversed back which can undo all the operations done by a forward traversing of the circuit. According to the undecidability problem, all problems that are unsolvable by a classical algorithm cannot be solved by quantum algorithms too. But these algorithms can solve problems significantly faster than classical algorithms. Some examples of the quantum algorithm are Shor’s algorithm and Grover’s algorithm. The Shor’s algorithm can do factorization of very large numbers in exponentially faster than best-known classical algorithms [17], whereas, Grover’s algorithm is used for searching large unordered list or unstructured databases that is four times faster than the classic algorithm [18].
There are various quantum algorithms available so far are as follows [19]:
Fourier transform-based quantum algorithms
Amplitude amplification-based quantum algorithms
Quantum walks based algorithm
BQP-complete problems
Hybrid quantum/classical algorithms
The exponential computing power of quantum computers can be accomplished by assessing and rectifying any kind of design limitation which helps to avoid their quality degradation. There are four major design limitations. The first limitation is that the number of coefficients in Dirac notation that defines the state of a quantum computer rise exponentially with the rise in the number of qubits, only when all the qubits get entangled with each other. To obtain the full potential of quantum computing, qubits must follow the property of entanglement where the state of any qubit must be linked with states of other qubits. It cannot be achieved directly since it is hard to generate a direct relation between qubits. But it can be decomposed into a number of simple fundamental operations directly aided by the hardware. One can also perform indirect coupling which is known to be an overhead in machines in classical computing and is crucial at the early stages of development especially when qubits and gate operations are confined.
The second limitation is that it is impossible to copy an entire quantum system because of a principle called a no-cloning principle [20]. There is a risk of deletion of arbitrary information from the original qubits since the state of qubits or set of qubits are moved to another set of qubits rather than being copied. The generation and storage of copies of intermediate states or partial outcomes in memory is a necessary aspect of classical computing. But quantum computers need a different strategy. There are quantum algorithms that help to access classical bits from the storage so that it can be known which bits are loaded and being queried into the memory of the quantum system to perform its task successfully.
The third limitation is due to the absence of noise protection of qubit operations. The small deformities in gate operations or input signals are collected over time disturbing the state of the system because they are not discarded by the fundamental gate operations. This can highly affect the calculation preciseness, measurements and coherence of the quantum systems and lessen the qubit operations integrity [21].
The final limitation is the incapability of the quantum machine to identify its full state even after it has finished its operation. Assume quantum computer has introduced an initial set of qubits with the superposition of all states combination. After applying a function to this state, the new quantum state will have information about the function value for each possible input and measuring this quantum system will not give this information. Therefore, a successful quantum algorithm can be achieved by manipulating the system in such a way so that states after finishing the operations have a higher probability of getting measured than any other probable result.
If we can design each gate slightly different from others, then the generated electric signals on communicating with each other produce periodic noise in each other. Thus, the noise immunity of gates used will be adequate to cancel the impact of various noise origins. Therefore, the concluding system will produce the same outcome as the logical gate model, even with millions of gates operating in parallel. The goal of the design is to minimize the noise in qubit that can prevent the qubit state to pass through noisy channels. The qubit state can be changed by changing its physical energy environment.
Thus, it leads to 2 approaches to quantum computing. In the first approach, the energy environment representing Hamiltonian is frequently changed smoothly as qubits operations are analog in nature and smoothly changes from 0 to 1 which cannot be completely corrected. It initializes the quantum state and then uses Hamiltonian directly to develop the quantum state. This is known as
The second approach is similar to the classical computer approach where the problem is decomposed into a sequence of fundamental operations or gates. These gates have adequately defined digital outcomes for some input states. The set of fundamental operations of quantum computing is different from that of classical computing. This approach is referred to as
This type of system performs its operation by manipulating the analog values in the Hamiltonian representation. It does not use quantum gates. It includes
There are three basic types of analog quantum computing. These are divided on the basis of the required amount of processing power (number of qubits) and time to become practically and commercially available.
Quantum Annealing
A basic rule of physics is that everything inclines towards a minimum energy state of a problem. This behavior is also true in the world of quantum physics. Quantum annealing is naturally used for real low-energy solutions such as optimization problems [22]. It is useful where the best solution is needed out of all possible solutions available. However, it is least powerful among all the types available. An example of this demonstrates an experiment to optimize traffic flows in a crowded city. Such an algorithm could successfully decrease traffic by choosing a convenient path. Volkswagen performs this with Google and D-wave system partnership. Such an experiment can be applied on a universal scale for all to get the cost-productive travel. This method can be applied to a collection of industry problems. For example, optimization of the flight route, petroleum price, weather and temperature information and passenger details, developing commercial aircraft.
Quantum annealing is also used for digital modeling, sampling problems and other science fields. This will take only a couple of hours to model all the individual atoms of air flowing over an airplane’s wing at every tilts and speeds to formulate an optimized wing design. Using a sampling problem from energy-based distribution, the shape of energy can be characterized and is useful in machine learning problems. The samples improve the model using information about the state of the model for the given parameters.
Quantum Simulation
Quantum simulations examine certain problems in quantum mechanics that are beyond classical physics. Simulating quantum phenomena that are complex in nature is one of the most important applications of quantum computing such as quantum chemistry. It includes modeling of chemical reactions on a large number of quantum subatomic particles. Quantum simulators can be used to simulate the misfolded protein structure [23]. Diseases like Alzheimer’s are caused by misfolded proteins. Using random computer simulation, researchers test new treatment drugs and learn reactions. To achieve correctly folded protein structure and study all drug-induced effects, sequential sampling is done which could take more than a million years. Quantum computers can help evaluate it for making more effective treatments and medicines and it would be a significant healthcare improvement. In the future, quantum simulations will facilitate quick drug designing and testing by evaluating every possible drug combinations of protein.
Adiabatic Quantum Computing
Adiabatic quantum computing is the most dominant, commonly applicable and hardest to create. A truly adiabatic quantum computer will use over a million of qubits. The maximum qubits we can access is less than 128 today. The basic idea behind this is that the machine can be directed at any complex calculation and obtain an immediate solution. This comprises analyzing the annealing equations, quantum phenomena simulation, etc. [24]. At least fifty unique algorithms other than Shor’s and Grover’s algorithm have been formulated to run on this quantum computer.
There is a possibility that quantum computers could revolutionize the area of artificial intelligence and machine learning. Some work has been done on algorithms that would operate as building blocks of machine learning but the hardware and software for quantum AI are still not practically accessible.
NISQ stands for Noisy Intermediate-Scale Quantum. It is also known as the Digital NISQ computer. These type of systems are gate-based and operates on a collection of qubits without full error correction and cannot restrict all the errors. The computations must be designed in a way so that they remain practical on a quantum system with little noise and can be finished in fewer and sufficient steps so that Decoherence and gate errors do not hide the outcomes [25].
Such computers also perform gate-based operations on a set of qubits with the implementation of the Quantum Error Correction algorithm. It reduces or corrects the noise in the system occurring during the computation period. Errors may include inadequate signals, device forgery or undesired bonding of qubits to the environment or with each other. The error is reduced to such a limit that the system seems valid and precise for all computations. Such quantum computers can have various realizations and they must fulfill some conditions such as there must be an availability of a well-defined two-level system that can be used as qubits, a potential to initialize those qubits, a sufficiently extended amount of Decoherence time which can perform error correction and computation, quantum gates (a set of quantum operations) common for every quantum computation and a capability of measuring each quantum bit individually without bothering others [26]. The analog quantum computers and digital NISQ computers are in progress while the gate-based computers with full error corrections are much more difficult and demanding.
According to researchers, quantum computers will be able to
It provides that
Due to the teleportation phenomenon known as ‘quantum tunneling,’ it can work in parallel and use less amount of electricity, hence,
A general quantum computer is “thousands of times” faster than any classical computer. For example, Google has made a quantum computer [27] that is 100 million times
It can solve complex problems
It can easily
It can bring up
Due to advancements in quantum computers, the
The Quantum Computer will work as a different device and cannot
It has
It is very delicate and error-prone. Any kind of vibrations affects subatomic particles like atoms and electrons. Due to which noise, faults, and even failures are possible. It leads to “
Quantum processors are very unstable and are very hard to test even. For the stability of the quantum computer, it is kept at 0.2 Kelvin (absolute Kelvin) which is nearly below the universe temperature [28]. It is very hard to maintain and regulate such temperature. The main problem is to really develop it as a personal computer with the price range in the budget of consumers. They will be firstly accessible to large scale industry then come to retail markets.
Many quantum algorithms have been evolved for quantum computers that deliver speedup which is a result of some fundamental mathematical methods like Fourier transform, Hamiltonian simulation, etc. Most algorithms require a large number of qubits of the best quality and some error correction to provide useful functionalities. These algorithms are formed in blocks rather than as a whole combined application since it is not practical. Therefore, it is a great challenge to create quantum applications that are really practically useful along with providing speedup with no error. The potential utility or say useful application of a quantum computer is an area of ongoing research. It is predicted that those applications require fewer qubits and can be carried out with a lesser amount of codes. It is possible to build algorithms that can run faster on quantum computers because of the distinct features of the qubit. Below are some of the primary applications that we will see soon in the upcoming era:
Cryptography
Many important elements of IT security and online security such as e-commerce and electronic secrecy depend on encryption and mathematical algorithms which are difficult to break such as factoring very huge numbers into primes (RSA technique). It is done by traversing through every possible factor using conventional computers which takes a significant amount of time. Also, some modern algorithms other than RSA like AES, ECDSA, etc. cannot be cracked using even high computing power. It makes it costly and cracking them even less practical. Quantum computers can do all these kinds of stuff in exponentially less amount of time. New quantum algorithms (e.g. Shor’s algorithm) are able to do it and more unique algorithms will develop [29]. But before that, new encryption techniques are being made to resist the quantum ones. Since the already running techniques and digital applications security are at greater risks.
Optimization Problems
Optimizing a problem implies finding the best solution to that problem out of all the possible solutions. It can be done by minimizing the error and even minimizing the steps available. Quantum computers are best in solving optimization problems. There are a lot of quantum algorithms out of which quantum optimization algorithms might improve the already existing optimization problems which are solved using conventional computers currently. Some of them are quantum semi-definite programming, quantum data fitting, and quantum combinatorial optimization. Some of the examples include simulating the molecular model like protein behavior for medical research which can lead to the new discovery of drugs for serious diseases like cancer, lung disease, etc. Another example is the Simulation of the cellular structure of batteries for improving battery power and life in electric vehicles. It could also solve travel-related problems in real traffic just like traveling salesman problems to find the shortest path between many cities, going to each city once and returning back, modeling the entire finance market, and many more. Traveling optimization is the major work under Volkswagen recently [30].
Artificial Intelligence
Artificial Intelligence counts on processing large and complex datasets. It is responsible for learning, inferring, and understanding. It learns until it stops mistaking and making errors in its task. It takes a significant amount of time in learning too. But quantum computing can make it easy and more accurate. Since conventional computers are only training the learning model from a specific size of the dataset to restrict the computation time. Quantum computers can train these models over a huge dataset without sticking into the exponential time. The more data it uses to train, the more accurate it will be. Generative models generate output such as image, audio, etc. that can be fed to quantum computers to improve its quality and accuracy. Natural Language processing is another example that can understand complete sentences. Quantum computers can make it understand all the phrases and speech in real-time with improved quality, which is computationally costly with today’s computer.
Quantum Simulation
It is an important utility in the field of quantum chemistry and material science [31]. This problem needs solving ground state energies of electrons and their wave functions, with or without the presence of some external electric or magnetic field. From the structure of atoms and electrons in chemistry to the rate at which chemical reactions are taking place, everything can be simulated very well. The classical computer when applied to this problem often fails to reach the level of precision needed to predict the rate of the chemical reaction.
It could also have commercial applications in areas such as medical and healthcare fields, chemical catalysts, storage of energy, pharmaceutical advancement and device displays.
The good news is that at any instant of time, the quantum state with the same number of quantum bits can stretch over all possible states as compared to classical computers and thus works in an exponentially massive space. However, to be able to use this space requires all qubits to remain interconnected. Even after such progress, improvements are still needed. The bad news is that making new and high-quality qubits does not guarantee the creation and efficient use of fault-tolerant quantum computers and is still having challenges in its path [32].
Qubits cannot naturally ignore the noise. Hence, the quantum system is more error-prone. It suffers from
Qubits are neither completely binary nor digital. It is having analog properties also. Gate can reject noise by dealing with the input signal value of 0.8 and treating it as 1. But in the analog signal, every value between 0 and 1 is permitted since they have their meanings. Signals cannot be checked for any kind of noise or corruption. Since 0.8 can be 1 with some error or 0.8 without error. Presuming the error as 0 like Gates do or taking some noise value even if it was not present there can affect the adherence of the resulting quantum computation. Hence, there is a need for algorithms like quantum error correction similar to the logical error correction in classical computers. These algorithms can be run on a noisy gate-based quantum computer to eliminate the errors and noises present in them [34].
It is possible to employ a
Further
Debugging quantum hardware and software is of utmost importance which depends on memory and intermediate machine states in classical computers. But in the case of quantum computing, states cannot be copied directly for later evaluation, and
It is clearly possible to build a quantum computer that could perform computations that would run a lifetime on a classical computer. Practical applications of quantum computing need controlling the quantum phenomena and thus the quantum world to an exceptional level. This job requires substantial engineering and research to build, manage and employ a noiseless quantum system. The experiment with quantum supremacy is an important test of the theory of quantum mechanics that will help to improve the support of quantum theory and leads to unexpected discoveries. The development of aspects and components of quantum information technology and computing has already started to influence the area of physics. The quantum error correction theory to attain the fault-tolerant quantum system has proven important. The quantum information theory is practically useful to study physics and dynamics of multibody systems like a massive number of quantum subatomic particles and even in blackhole and related concepts. Advancement in this area is important for an accurate understanding of various physical structures. It has contributed to many other engineering fields like physics, mathematics, chemistry, computer science, material science, etc. It has also advanced classical computing. Strategies to develop a quantum computing algorithm have helped in improving the classical computing algorithm also. Research in the quantum algorithm has answered many questions in the computer science area. It can help to evaluate the safety of cryptographic systems, clarifying the limitations of physical computational and advancing computational methods. It will help to advance the human’s understanding of the universe. The qubits that are recently being used in quantum computing is also used for building sensors, precision clocks, and other applications. Quantum communication is used for communicating two quantum systems at distance. There is an increased risk of asymmetric cryptography as well as the entire security system. Hence, the actions are being taken towards new quantum cryptography. The development of quantum information, science, technology and computing is a global area now.
A significant amount of struggle is remaining before a practical quantum computer can be launched. There are some future advancements that are needed. Some of the future needs are enabling a Quantum Error Correction algorithm that requires low overhead and decreases the error rates in qubits, developing more algorithms with lesser qubits for solving problems, reducing circuit thickness so that NISQ computers can be operated, the advancement of methods which can verify, debug, and simulate the quantum computers, scaling the number of qubits per processor in such a way so that error rate is maintained or can be improved if possible, interleaving of operations in a qubit, recognizing more algorithms that can reduce the computation time and creating input–output for the quantum processor.
Such ‘
‘
AI and machine learning problems could be solved in a practical amount of time that can be reduced from hundreds of thousands of years to seconds. Several quantum algorithms have been developed such as Grover’s algorithm for searching and Shor’s algorithm for factoring large numbers. More quantum algorithms are coming soon. Google has also declared that it would produce a workable quantum computer in the following 5 years with a 50-qubit quantum computer and will achieve quantum supremacy. IBM is also offering commercial quantum computers soon.
The progress of development in the field of quantum computers depends on many factors. Interest and financial support from the private sector can help developing commercial applications for NISQ computers. It depends on the progress of quantum algorithm development, availability of enough investment in the quantum technology field from government and the exchange of ideas within researchers, scientists and engineers [36]. To illuminate the limitations of quantum technology, a defensive result is also beneficial. It can help in overcoming those negative results which can lead to a new discovery.
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He is also a faculty member in the Molecular Oncology Program. He obtained his MSc and Ph.D. at Oregon State University and Texas Tech University, respectively. He pursued his postdoctoral studies at Rutgers University Medical School and the National Institutes of Health (NIH/NIDDK), USA. His research focuses on biochemistry, biophysics, genetics, molecular biology, and molecular medicine with specialization in the fields of drug design, protein structure-function, protein folding, prions, microRNA, pseudogenes, molecular cancer, epigenetics, metabolites, proteomics, genomics, protein expression, and characterization by spectroscopic and calorimetric methods.",institutionString:"University of Health Sciences",institution:null},{id:"180528",title:"Dr.",name:"Hiroyuki",middleName:null,surname:"Kagechika",slug:"hiroyuki-kagechika",fullName:"Hiroyuki Kagechika",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/180528/images/system/180528.jpg",biography:"Hiroyuki Kagechika received his bachelor’s degree and Ph.D. in Pharmaceutical Sciences from the University of Tokyo, Japan, where he served as an associate professor until 2004. He is currently a professor at the Institute of Biomaterials and Bioengineering (IBB), Tokyo Medical and Dental University (TMDU). From 2010 to 2012, he was the dean of the Graduate School of Biomedical Science. Since 2012, he has served as the vice dean of the Graduate School of Medical and Dental Sciences. He has been the director of the IBB since 2020. Dr. Kagechika’s major research interests are the medicinal chemistry of retinoids, vitamins D/K, and nuclear receptors. He has developed various compounds including a drug for acute promyelocytic leukemia.",institutionString:"Tokyo Medical and Dental University",institution:{name:"Tokyo Medical and Dental University",country:{name:"Japan"}}},{id:"40482",title:null,name:"Rizwan",middleName:null,surname:"Ahmad",slug:"rizwan-ahmad",fullName:"Rizwan Ahmad",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/40482/images/system/40482.jpeg",biography:"Dr. Rizwan Ahmad is a University Professor and Coordinator, Quality and Development, College of Medicine, Imam Abdulrahman bin Faisal University, Saudi Arabia. Previously, he was Associate Professor of Human Function, Oman Medical College, Oman, and SBS University, Dehradun. Dr. Ahmad completed his education at Aligarh Muslim University, Aligarh. He has published several articles in peer-reviewed journals, chapters, and edited books. 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Dr. Badria was listed among the world’s top 2% of scientists in medicinal and biomolecular chemistry in 2019 and 2020. He is a member of the Arab Development Fund, Kuwait; International Cell Research Organization–United Nations Educational, Scientific and Cultural Organization (ICRO–UNESCO), Chile; and UNESCO Biotechnology France",institutionString:"Mansoura University",institution:{name:"Mansoura University",country:{name:"Egypt"}}},{id:"329385",title:"Dr.",name:"Rajesh K.",middleName:"Kumar",surname:"Singh",slug:"rajesh-k.-singh",fullName:"Rajesh K. Singh",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/329385/images/system/329385.png",biography:"Dr. Singh received a BPharm (2003) and MPharm (2005) from Panjab University, Chandigarh, India, and a Ph.D. (2013) from Punjab Technical University (PTU), Jalandhar, India. He has more than sixteen years of teaching experience and has supervised numerous postgraduate and Ph.D. students. He has to his credit more than seventy papers in SCI- and SCOPUS-indexed journals, fifty-five conference proceedings, four books, six Best Paper Awards, and five projects from different government agencies. He is currently an editorial board member of eight international journals and a reviewer for more than fifty scientific journals. He received Top Reviewer and Excellent Peer Reviewer Awards from Publons in 2016 and 2017, respectively. He is also on the panel of The International Reviewer for reviewing research proposals for grants from the Royal Society. He also serves as a Publons Academy mentor and Bentham brand ambassador.",institutionString:"Punjab Technical University",institution:{name:"Punjab Technical University",country:{name:"India"}}},{id:"142388",title:"Dr.",name:"Thiago",middleName:"Gomes",surname:"Gomes Heck",slug:"thiago-gomes-heck",fullName:"Thiago Gomes Heck",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/142388/images/7259_n.jpg",biography:null,institutionString:null,institution:{name:"Universidade Regional do Noroeste do Estado do Rio Grande do Sul",country:{name:"Brazil"}}},{id:"336273",title:"Assistant Prof.",name:"Janja",middleName:null,surname:"Zupan",slug:"janja-zupan",fullName:"Janja Zupan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/336273/images/14853_n.jpeg",biography:"Janja Zupan graduated in 2005 at the Department of Clinical Biochemistry (superviser prof. dr. Janja Marc) in the field of genetics of osteoporosis. Since November 2009 she is working as a Teaching Assistant at the Faculty of Pharmacy, Department of Clinical Biochemistry. In 2011 she completed part of her research and PhD work at Institute of Genetics and Molecular Medicine, University of Edinburgh. She finished her PhD entitled The influence of the proinflammatory cytokines on the RANK/RANKL/OPG in bone tissue of osteoporotic and osteoarthritic patients in 2012. From 2014-2016 she worked at the Institute of Biomedical Sciences, University of Aberdeen as a postdoctoral research fellow on UK Arthritis research project where she gained knowledge in mesenchymal stem cells and regenerative medicine. She returned back to University of Ljubljana, Faculty of Pharmacy in 2016. She is currently leading project entitled Mesenchymal stem cells-the keepers of tissue endogenous regenerative capacity facing up to aging of the musculoskeletal system funded by Slovenian Research Agency.",institutionString:null,institution:{name:"University of Ljubljana",country:{name:"Slovenia"}}},{id:"357453",title:"Dr.",name:"Radheshyam",middleName:null,surname:"Maurya",slug:"radheshyam-maurya",fullName:"Radheshyam Maurya",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/357453/images/16535_n.jpg",biography:null,institutionString:null,institution:{name:"University of Hyderabad",country:{name:"India"}}},{id:"311457",title:"Dr.",name:"Júlia",middleName:null,surname:"Scherer Santos",slug:"julia-scherer-santos",fullName:"Júlia Scherer Santos",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/311457/images/system/311457.jpg",biography:"Dr. Júlia Scherer Santos works in the areas of cosmetology, nanotechnology, pharmaceutical technology, beauty, and aesthetics. Dr. Santos also has experience as a professor of graduate courses. Graduated in Pharmacy, specialization in Cosmetology and Cosmeceuticals applied to aesthetics, specialization in Aesthetic and Cosmetic Health, and a doctorate in Pharmaceutical Nanotechnology. Teaching experience in Pharmacy and Aesthetics and Cosmetics courses. She works mainly on the following subjects: nanotechnology, cosmetology, pharmaceutical technology, aesthetics.",institutionString:"Universidade Federal de Juiz de Fora",institution:{name:"Universidade Federal de Juiz de Fora",country:{name:"Brazil"}}},{id:"219081",title:"Dr.",name:"Abdulsamed",middleName:null,surname:"Kükürt",slug:"abdulsamed-kukurt",fullName:"Abdulsamed Kükürt",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRNVJQA4/Profile_Picture_2022-03-07T13:23:04.png",biography:"Dr. Kükürt graduated from Uludağ University in Turkey. He started his academic career as a Research Assistant in the Department of Biochemistry at Kafkas University. In 2019, he completed his Ph.D. program in the Department of Biochemistry at the Institute of Health Sciences. He is currently working at the Department of Biochemistry, Kafkas University. He has 27 published research articles in academic journals, 11 book chapters, and 37 papers. He took part in 10 academic projects. He served as a reviewer for many articles. He still serves as a member of the review board in many academic journals. His research interests include biochemistry, oxidative stress, reactive species, antioxidants, lipid peroxidation, inflammation, reproductive hormones, phenolic compounds, female infertility.",institutionString:"Kafkas University",institution:{name:"Kafkas University",country:{name:"Turkey"}}},{id:"178366",title:"Associate Prof.",name:"Volkan",middleName:null,surname:"Gelen",slug:"volkan-gelen",fullName:"Volkan Gelen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/178366/images/system/178366.jpg",biography:"Volkan Gelen is a Physiology specialist who received his veterinary degree from Kafkas University in 2011. Between 2011-2015, he worked as an assistant at Atatürk University, Faculty of Veterinary Medicine, Department of Physiology. In 2016, he joined Kafkas University, Faculty of Veterinary Medicine, Department of Physiology as an assistant professor. Dr. Gelen has been engaged in various academic activities at Kafkas University since 2016. There he completed 5 projects and has 3 ongoing projects. He has 60 articles published in scientific journals and 20 poster presentations in scientific congresses. His research interests include physiology, endocrine system, cancer, diabetes, cardiovascular system diseases, and isolated organ bath system studies.",institutionString:"Kafkas University",institution:{name:"Kafkas University",country:{name:"Turkey"}}},{id:"418963",title:"Dr.",name:"Augustine Ododo",middleName:"Augustine",surname:"Osagie",slug:"augustine-ododo-osagie",fullName:"Augustine Ododo Osagie",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/418963/images/16900_n.jpg",biography:"Born into the family of Osagie, a prince of the Benin Kingdom. I am currently an academic in the Department of Medical Biochemistry, University of Benin. Part of the duties are to teach undergraduate students and conduct academic research.",institutionString:null,institution:{name:"University of Benin",country:{name:"Nigeria"}}},{id:"192992",title:"Prof.",name:"Shagufta",middleName:null,surname:"Perveen",slug:"shagufta-perveen",fullName:"Shagufta Perveen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/192992/images/system/192992.png",biography:"Prof. Shagufta Perveen is a Distinguish Professor in the Department of Pharmacognosy, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia. Dr. Perveen has acted as the principal investigator of major research projects funded by the research unit of King Saud University. She has more than ninety original research papers in peer-reviewed journals of international repute to her credit. She is a fellow member of the Royal Society of Chemistry UK and the American Chemical Society of the United States.",institutionString:"King Saud University",institution:{name:"King Saud University",country:{name:"Saudi Arabia"}}},{id:"49848",title:"Dr.",name:"Wen-Long",middleName:null,surname:"Hu",slug:"wen-long-hu",fullName:"Wen-Long Hu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/49848/images/system/49848.jpg",biography:"Wen-Long Hu is Chief of the Division of Acupuncture, Department of Chinese Medicine at Kaohsiung Chang Gung Memorial Hospital, as well as an adjunct associate professor at Fooyin University and Kaohsiung Medical University. Wen-Long is President of Taiwan Traditional Chinese Medicine Medical Association. He has 28 years of experience in clinical practice in laser acupuncture therapy and 34 years in acupuncture. He is an invited speaker for lectures and workshops in laser acupuncture at many symposiums held by medical associations. He owns the patent for herbal preparation and producing, and for the supercritical fluid-treated needle. Dr. Hu has published three books, 12 book chapters, and more than 30 papers in reputed journals, besides serving as an editorial board member of repute.",institutionString:"Kaohsiung Chang Gung Memorial Hospital",institution:{name:"Kaohsiung Chang Gung Memorial Hospital",country:{name:"Taiwan"}}},{id:"298472",title:"Prof.",name:"Andrey V.",middleName:null,surname:"Grechko",slug:"andrey-v.-grechko",fullName:"Andrey V. Grechko",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/298472/images/system/298472.png",biography:"Andrey Vyacheslavovich Grechko, Ph.D., Professor, is a Corresponding Member of the Russian Academy of Sciences. He graduated from the Semashko Moscow Medical Institute (Semashko National Research Institute of Public Health) with a degree in Medicine (1998), the Clinical Department of Dermatovenerology (2000), and received a second higher education in Psychology (2009). Professor A.V. Grechko held the position of Сhief Physician of the Central Clinical Hospital in Moscow. He worked as a professor at the faculty and was engaged in scientific research at the Medical University. Starting in 2013, he has been the initiator of the creation of the Federal Scientific and Clinical Center for Intensive Care and Rehabilitology, Moscow, Russian Federation, where he also serves as Director since 2015. He has many years of experience in research and teaching in various fields of medicine, is an author/co-author of more than 200 scientific publications, 13 patents, 15 medical books/chapters, including Chapter in Book «Metabolomics», IntechOpen, 2020 «Metabolomic Discovery of Microbiota Dysfunction as the Cause of Pathology».",institutionString:"Federal Research and Clinical Center of Intensive Care Medicine and Rehabilitology",institution:null},{id:"199461",title:"Prof.",name:"Natalia V.",middleName:null,surname:"Beloborodova",slug:"natalia-v.-beloborodova",fullName:"Natalia V. Beloborodova",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/199461/images/system/199461.jpg",biography:'Natalia Vladimirovna Beloborodova was educated at the Pirogov Russian National Research Medical University, with a degree in pediatrics in 1980, a Ph.D. in 1987, and a specialization in Clinical Microbiology from First Moscow State Medical University in 2004. She has been a Professor since 1996. Currently, she is the Head of the Laboratory of Metabolism, a division of the Federal Research and Clinical Center of Intensive Care Medicine and Rehabilitology, Moscow, Russian Federation. N.V. Beloborodova has many years of clinical experience in the field of intensive care and surgery. She studies infectious complications and sepsis. She initiated a series of interdisciplinary clinical and experimental studies based on the concept of integrating human metabolism and its microbiota. Her scientific achievements are widely known: she is the recipient of the Marie E. Coates Award \\"Best lecturer-scientist\\" Gustafsson Fund, Karolinska Institutes, Stockholm, Sweden, and the International Sepsis Forum Award, Pasteur Institute, Paris, France (2014), etc. Professor N.V. Beloborodova wrote 210 papers, five books, 10 chapters and has edited four books.',institutionString:"Federal Research and Clinical Center of Intensive Care Medicine and Rehabilitology",institution:null},{id:"354260",title:"Ph.D.",name:"Tércio Elyan",middleName:"Azevedo",surname:"Azevedo Martins",slug:"tercio-elyan-azevedo-martins",fullName:"Tércio Elyan Azevedo Martins",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/354260/images/16241_n.jpg",biography:"Graduated in Pharmacy from the Federal University of Ceará with the modality in Industrial Pharmacy, Specialist in Production and Control of Medicines from the University of São Paulo (USP), Master in Pharmaceuticals and Medicines from the University of São Paulo (USP) and Doctor of Science in the program of Pharmaceuticals and Medicines by the University of São Paulo. Professor at Universidade Paulista (UNIP) in the areas of chemistry, cosmetology and trichology. Assistant Coordinator of the Higher Course in Aesthetic and Cosmetic Technology at Universidade Paulista Campus Chácara Santo Antônio. Experience in the Pharmacy area, with emphasis on Pharmacotechnics, Pharmaceutical Technology, Research and Development of Cosmetics, acting mainly on topics such as cosmetology, antioxidant activity, aesthetics, photoprotection, cyclodextrin and thermal analysis.",institutionString:null,institution:{name:"University of Sao Paulo",country:{name:"Brazil"}}},{id:"334285",title:"Ph.D. Student",name:"Sameer",middleName:"Kumar",surname:"Jagirdar",slug:"sameer-jagirdar",fullName:"Sameer Jagirdar",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/334285/images/14691_n.jpg",biography:"I\\'m a graduate student at the center for biosystems science and engineering at the Indian Institute of Science, Bangalore, India. I am interested in studying host-pathogen interactions at the biomaterial interface.",institutionString:null,institution:{name:"Indian Institute of Science Bangalore",country:{name:"India"}}},{id:"329795",title:"Dr.",name:"Mohd Aftab",middleName:"Aftab",surname:"Siddiqui",slug:"mohd-aftab-siddiqui",fullName:"Mohd Aftab Siddiqui",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/329795/images/15648_n.jpg",biography:"Dr. Mohd Aftab Siddiqui is currently working as Assistant Professor in the Faculty of Pharmacy, Integral University, Lucknow for the last 6 years. He has completed his Doctor in Philosophy (Pharmacology) in 2020 from Integral University, Lucknow. He completed his Bachelor in Pharmacy in 2013 and Master in Pharmacy (Pharmacology) in 2015 from Integral University, Lucknow. He is the gold medalist in Bachelor and Master degree. He qualified GPAT -2013, GPAT -2014, and GPAT 2015. His area of research is Pharmacological screening of herbal drugs/ natural products in liver and cardiac diseases. He has guided many M. Pharm. research projects. He has many national and international publications.",institutionString:"Integral University",institution:null},{id:"255360",title:"Dr.",name:"Usama",middleName:null,surname:"Ahmad",slug:"usama-ahmad",fullName:"Usama Ahmad",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/255360/images/system/255360.png",biography:"Dr. Usama Ahmad holds a specialization in Pharmaceutics from Amity University, Lucknow, India. He received his Ph.D. degree from Integral University. Currently, he’s working as an Assistant Professor of Pharmaceutics in the Faculty of Pharmacy, Integral University. From 2013 to 2014 he worked on a research project funded by SERB-DST, Government of India. He has a rich publication record with more than 32 original articles published in reputed journals, 3 edited books, 5 book chapters, and a number of scientific articles published in ‘Ingredients South Asia Magazine’ and ‘QualPharma Magazine’. He is a member of the American Association for Cancer Research, International Association for the Study of Lung Cancer, and the British Society for Nanomedicine. Dr. Ahmad’s research focus is on the development of nanoformulations to facilitate the delivery of drugs that aim to provide practical solutions to current healthcare problems.",institutionString:"Integral University",institution:{name:"Integral University",country:{name:"India"}}},{id:"30568",title:"Prof.",name:"Madhu",middleName:null,surname:"Khullar",slug:"madhu-khullar",fullName:"Madhu Khullar",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/30568/images/system/30568.jpg",biography:"Dr. Madhu Khullar is a Professor of Experimental Medicine and Biotechnology at the Post Graduate Institute of Medical Education and Research, Chandigarh, India. She completed her Post Doctorate in hypertension research at the Henry Ford Hospital, Detroit, USA in 1985. She is an editor and reviewer of several international journals, and a fellow and member of several cardiovascular research societies. Dr. Khullar has a keen research interest in genetics of hypertension, and is currently studying pharmacogenetics of hypertension.",institutionString:"Post Graduate Institute of Medical Education and Research",institution:{name:"Post Graduate Institute of Medical Education and Research",country:{name:"India"}}},{id:"223233",title:"Prof.",name:"Xianquan",middleName:null,surname:"Zhan",slug:"xianquan-zhan",fullName:"Xianquan Zhan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/223233/images/system/223233.png",biography:"Xianquan Zhan received his MD and Ph.D. in Preventive Medicine at West China University of Medical Sciences. He received his post-doctoral training in oncology and cancer proteomics at the Central South University, China, and the University of Tennessee Health Science Center (UTHSC), USA. He worked at UTHSC and the Cleveland Clinic in 2001–2012 and achieved the rank of associate professor at UTHSC. Currently, he is a full professor at Central South University and Shandong First Medical University, and an advisor to MS/PhD students and postdoctoral fellows. He is also a fellow of the Royal Society of Medicine and European Association for Predictive Preventive Personalized Medicine (EPMA), a national representative of EPMA, and a member of the American Society of Clinical Oncology (ASCO) and the American Association for the Advancement of Sciences (AAAS). He is also the editor in chief of International Journal of Chronic Diseases & Therapy, an associate editor of EPMA Journal, Frontiers in Endocrinology, and BMC Medical Genomics, and a guest editor of Mass Spectrometry Reviews, Frontiers in Endocrinology, EPMA Journal, and Oxidative Medicine and Cellular Longevity. He has published more than 148 articles, 28 book chapters, 6 books, and 2 US patents in the field of clinical proteomics and biomarkers.",institutionString:"Shandong First Medical University",institution:{name:"Affiliated Hospital of Shandong Academy of Medical Sciences",country:{name:"China"}}},{id:"297507",title:"Dr.",name:"Charles",middleName:"Elias",surname:"Assmann",slug:"charles-assmann",fullName:"Charles Assmann",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/297507/images/system/297507.jpg",biography:"Charles Elias Assmann is a biologist from Federal University of Santa Maria (UFSM, Brazil), who spent some time abroad at the Ludwig-Maximilians-Universität München (LMU, Germany). He has Masters Degree in Biochemistry (UFSM), and is currently a PhD student at Biochemistry at the Department of Biochemistry and Molecular Biology of the UFSM. His areas of expertise include: Biochemistry, Molecular Biology, Enzymology, Genetics and Toxicology. He is currently working on the following subjects: Aluminium toxicity, Neuroinflammation, Oxidative stress and Purinergic system. Since 2011 he has presented more than 80 abstracts in scientific proceedings of national and international meetings. Since 2014, he has published more than 20 peer reviewed papers (including 4 reviews, 3 in Portuguese) and 2 book chapters. He has also been a reviewer of international journals and ad hoc reviewer of scientific committees from Brazilian Universities.",institutionString:"Universidade Federal de Santa Maria",institution:{name:"Universidade Federal de Santa Maria",country:{name:"Brazil"}}},{id:"217850",title:"Dr.",name:"Margarete Dulce",middleName:null,surname:"Bagatini",slug:"margarete-dulce-bagatini",fullName:"Margarete Dulce Bagatini",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/217850/images/system/217850.jpeg",biography:"Dr. Margarete Dulce Bagatini is an associate professor at the Federal University of Fronteira Sul/Brazil. She has a degree in Pharmacy and a PhD in Biological Sciences: Toxicological Biochemistry. She is a member of the UFFS Research Advisory Committee\nand a member of the Biovitta Research Institute. She is currently:\nthe leader of the research group: Biological and Clinical Studies\nin Human Pathologies, professor of postgraduate program in\nBiochemistry at UFSC and postgraduate program in Science and Food Technology at\nUFFS. She has experience in the area of pharmacy and clinical analysis, acting mainly\non the following topics: oxidative stress, the purinergic system and human pathologies, being a reviewer of several international journals and books.",institutionString:"Universidade Federal da Fronteira Sul",institution:{name:"Universidade Federal da Fronteira Sul",country:{name:"Brazil"}}},{id:"226275",title:"Ph.D.",name:"Metin",middleName:null,surname:"Budak",slug:"metin-budak",fullName:"Metin Budak",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/226275/images/system/226275.jfif",biography:"Metin Budak, MSc, PhD is an Assistant Professor at Trakya University, Faculty of Medicine. He has been Head of the Molecular Research Lab at Prof. Mirko Tos Ear and Hearing Research Center since 2018. His specializations are biophysics, epigenetics, genetics, and methylation mechanisms. He has published around 25 peer-reviewed papers, 2 book chapters, and 28 abstracts. He is a member of the Clinical Research Ethics Committee and Quantification and Consideration Committee of Medicine Faculty. His research area is the role of methylation during gene transcription, chromatin packages DNA within the cell and DNA repair, replication, recombination, and gene transcription. His research focuses on how the cell overcomes chromatin structure and methylation to allow access to the underlying DNA and enable normal cellular function.",institutionString:"Trakya University",institution:{name:"Trakya University",country:{name:"Turkey"}}},{id:"243049",title:"Dr.",name:"Anca",middleName:null,surname:"Pantea Stoian",slug:"anca-pantea-stoian",fullName:"Anca Pantea Stoian",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/243049/images/system/243049.jpg",biography:"Anca Pantea Stoian is a specialist in diabetes, nutrition, and metabolic diseases as well as health food hygiene. She also has competency in general ultrasonography.\n\nShe is an associate professor in the Diabetes, Nutrition and Metabolic Diseases Department, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania. She has been chief of the Hygiene Department, Faculty of Dentistry, at the same university since 2019. Her interests include micro and macrovascular complications in diabetes and new therapies. Her research activities focus on nutritional intervention in chronic pathology, as well as cardio-renal-metabolic risk assessment, and diabetes in cancer. She is currently engaged in developing new therapies and technological tools for screening, prevention, and patient education in diabetes. \n\nShe is a member of the European Association for the Study of Diabetes, Cardiometabolic Academy, CEDA, Romanian Society of Diabetes, Nutrition and Metabolic Diseases, Romanian Diabetes Federation, and Association for Renal Metabolic and Nutrition studies. She has authored or co-authored 160 papers in national and international peer-reviewed journals.",institutionString:null,institution:{name:"Carol Davila University of Medicine and Pharmacy",country:{name:"Romania"}}},{id:"279792",title:"Dr.",name:"João",middleName:null,surname:"Cotas",slug:"joao-cotas",fullName:"João Cotas",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/279792/images/system/279792.jpg",biography:"Graduate and master in Biology from the University of Coimbra.\n\nI am a research fellow at the Macroalgae Laboratory Unit, in the MARE-UC – Marine and Environmental Sciences Centre of the University of Coimbra. My principal function is the collection, extraction and purification of macroalgae compounds, chemical and bioactive characterization of the compounds and algae extracts and development of new methodologies in marine biotechnology area. \nI am associated in two projects: one consists on discovery of natural compounds for oncobiology. The other project is the about the natural compounds/products for agricultural area.\n\nPublications:\nCotas, J.; Figueirinha, A.; Pereira, L.; Batista, T. 2018. An analysis of the effects of salinity on Fucus ceranoides (Ochrophyta, Phaeophyceae), in the Mondego River (Portugal). Journal of Oceanology and Limnology. in press. DOI: 10.1007/s00343-019-8111-3",institutionString:"Faculty of Sciences and Technology of University of Coimbra",institution:null},{id:"279788",title:"Dr.",name:"Leonel",middleName:null,surname:"Pereira",slug:"leonel-pereira",fullName:"Leonel Pereira",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/279788/images/system/279788.jpg",biography:"Leonel Pereira has an undergraduate degree in Biology, a Ph.D. in Biology (specialty in Cell Biology), and a Habilitation degree in Biosciences (specialization in Biotechnology) from the Faculty of Science and Technology, University of Coimbra, Portugal, where he is currently a professor. In addition to teaching at this university, he is an integrated researcher at the Marine and Environmental Sciences Center (MARE), Portugal. His interests include marine biodiversity (algae), marine biotechnology (algae bioactive compounds), and marine ecology (environmental assessment). Since 2008, he has been the author and editor of the electronic publication MACOI – Portuguese Seaweeds Website (www.seaweeds.uc.pt). He is also a member of the editorial boards of several scientific journals. Dr. Pereira has edited or authored more than 20 books, 100 journal articles, and 45 book chapters. He has given more than 100 lectures and oral communications at various national and international scientific events. He is the coordinator of several national and international research projects. In 1998, he received the Francisco de Holanda Award (Honorable Mention) and, more recently, the Mar Rei D. Carlos award (18th edition). He is also a winner of the 2016 CHOICE Award for an outstanding academic title for his book Edible Seaweeds of the World. In 2020, Dr. Pereira received an Honorable Mention for the Impact of International Publications from the Web of Science",institutionString:"University of Coimbra",institution:{name:"University of Coimbra",country:{name:"Portugal"}}},{id:"61946",title:"Dr.",name:"Carol",middleName:null,surname:"Bernstein",slug:"carol-bernstein",fullName:"Carol Bernstein",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/61946/images/system/61946.jpg",biography:"Carol Bernstein received her PhD in Genetics from the University of California (Davis). She was a faculty member at the University of Arizona College of Medicine for 43 years, retiring in 2011. Her research interests focus on DNA damage and its underlying role in sex, aging and in the early steps of initiation and progression to cancer. In her research, she had used organisms including bacteriophage T4, Neurospora crassa, Schizosaccharomyces pombe and mice, as well as human cells and tissues. She authored or co-authored more than 140 scientific publications, including articles in major peer reviewed journals, book chapters, invited reviews and one book.",institutionString:"University of Arizona",institution:{name:"University of Arizona",country:{name:"United States of America"}}},{id:"182258",title:"Dr.",name:"Ademar",middleName:"Pereira",surname:"Serra",slug:"ademar-serra",fullName:"Ademar Serra",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/182258/images/system/182258.jpeg",biography:"Dr. Serra studied Agronomy on Universidade Federal de Mato Grosso do Sul (UFMS) (2005). He received master degree in Agronomy, Crop Science (Soil fertility and plant nutrition) (2007) by Universidade Federal da Grande Dourados (UFGD), and PhD in agronomy (Soil fertility and plant nutrition) (2011) from Universidade Federal da Grande Dourados / Escola Superior de Agricultura Luiz de Queiroz (UFGD/ESALQ-USP). Dr. Serra is currently working at Brazilian Agricultural Research Corporation (EMBRAPA). His research focus is on mineral nutrition of plants, crop science and soil science. Dr. Serra\\'s current projects are soil organic matter, soil phosphorus fractions, compositional nutrient diagnosis (CND) and isometric log ratio (ilr) transformation in compositional data analysis.",institutionString:"Brazilian Agricultural Research Corporation",institution:{name:"Brazilian Agricultural Research Corporation",country:{name:"Brazil"}}}]}},subseries:{item:{id:"14",type:"subseries",title:"Cell and Molecular Biology",keywords:"Omics (Transcriptomics; Proteomics; Metabolomics), Molecular Biology, Cell Biology, Signal Transduction and Regulation, Cell Growth and Differentiation, Apoptosis, Necroptosis, Ferroptosis, Autophagy, Cell Cycle, Macromolecules and Complexes, Gene Expression",scope:"The Cell and Molecular Biology topic within the IntechOpen Biochemistry Series aims to rapidly publish contributions on all aspects of cell and molecular biology, including aspects related to biochemical and genetic research (not only in humans but all living beings). We encourage the submission of manuscripts that provide novel and mechanistic insights that report significant advances in the fields. Topics include, but are not limited to: Advanced techniques of cellular and molecular biology (Molecular methodologies, imaging techniques, and bioinformatics); Biological activities at the molecular level; Biological processes of cell functions, cell division, senescence, maintenance, and cell death; Biomolecules interactions; Cancer; Cell biology; Chemical biology; Computational biology; Cytochemistry; Developmental biology; Disease mechanisms and therapeutics; DNA, and RNA metabolism; Gene functions, genetics, and genomics; Genetics; Immunology; Medical microbiology; Molecular biology; Molecular genetics; Molecular processes of cell and organelle dynamics; Neuroscience; Protein biosynthesis, degradation, and functions; Regulation of molecular interactions in a cell; Signalling networks and system biology; Structural biology; Virology and microbiology.",coverUrl:"https://cdn.intechopen.com/series_topics/covers/14.jpg",hasOnlineFirst:!0,hasPublishedBooks:!0,annualVolume:11410,editor:{id:"165627",title:"Dr.",name:"Rosa María",middleName:null,surname:"Martínez-Espinosa",slug:"rosa-maria-martinez-espinosa",fullName:"Rosa María Martínez-Espinosa",profilePictureURL:"https://mts.intechopen.com/storage/users/165627/images/system/165627.jpeg",biography:"Dr. Rosa María Martínez-Espinosa has been a Spanish Full Professor since 2020 (Biochemistry and Molecular Biology) and is currently Vice-President of International Relations and Cooperation development and leader of the research group 'Applied Biochemistry” (University of Alicante, Spain). Other positions she has held at the university include Vice-Dean of Master Programs, Vice-Dean of the Degree in Biology and Vice-Dean for Mobility and Enterprise and Engagement at the Faculty of Science (University of Alicante). She received her Bachelor in Biology in 1998 (University of Alicante) and her PhD in 2003 (Biochemistry, University of Alicante). She undertook post-doctoral research at the University of East Anglia (Norwich, U.K. 2004-2005; 2007-2008).\nHer multidisciplinary research focuses on investigating archaea and their potential applications in biotechnology. She has an H-index of 21. She has authored one patent and has published more than 70 indexed papers and around 60 book chapters.\nShe has contributed to more than 150 national and international meetings during the last 15 years. 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