Sufficiently high voltage applied between two metal electrodes, even in ultra high vacuum conditions, results in an inevitable discharge that lights up the entire gap, opening a conductive channel through the vacuum and parasitically consuming large amounts of energy. Despite many efforts to understand the processes that lead to this phenomenon, known as vacuum arc, there is still no consensus regarding the role of each electrode in the evolution of such a momentous process as lightning. Employing a high-speed camera, we capture the entire lightning process step-by-step with a nanosecond resolution and find which of the two electrodes holds the main responsibility for igniting the arc. The light that gradually expands from the positively charged electrode (anode), often is assumed to play the main role in the formation of a vacuum arc. However, both the nanosecond-resolution images of vacuum arc evolution and the corresponding theoretical calculations agree that the conductive channel between the electrodes is built in the form of cathodic plasma long before any significant activity develops in the anode. We show evidently that the anode illumination is weaker and plays a minor role in igniting and maintaining the conductive channel. However, in most cases the vacuum arcs occur undesirably in an uncontrollable manner, causing problems in various vacuum devices such as fusion reactors4, vacuum interrupters5, satellite systems7, X-ray tubes8 and large particle accelerators.Electrical breakdowns in general and vacuum electrical breakdowns, in particular, regain their important role in the development of modern technologies. The increasing usage of electric power in different environments inevitably leads to failure of surfaces facing electric fields. In vacuum, even high or ultra-high, the electric breakdowns appear in the form of vacuum arcs. The latter in various cases are controllable and serve various technological advances, like ion sources10 or tiny micro- or nano-electromechanical system (MEMS or NEMS) and capacitors12. For instance, micro-fabricated devices such as nano electro-spray thruster arrays for spacecraft are built to withstand large electric fields between electrodes. However, if an arc occurs, the entire chip is destroyed13.Vacuum arcs are particularly detrimental for high precision devices that are built to employ high electric and electromagnetic fields. Amongst these are multi-kilometre devices such as powerful particle colliders10, free electron lasers14 or medical hadron accelerators for cancer treatment purposes15. Some of these devices are designed to operate with fields up to hundreds of MV/m10, which cause intolerably high frequency of vacuum breakdowns. This, in turn, increases wasteful power consumption, reduces the final luminosity of accelerated particles and overall destabilizes the performance of the device10.Recently, particular attention obtained technologies that employ high accelerating field gradients for high energy physics19, there is still no consensus on what are the physical processes that lead to its ignition. The most common hypothesis is that a vacuum arc starts from micro-protrusions that exist due to different reasons on the metal surface and locally enhance the applied electric field. If the local field reaches a critical value (about 1010 V/m)21, an intense and increasing field emission current appears. The latter initiates violent physical processes that within a few ns form a plasma that is able to conduct very high current densities at very small voltage23, thus rendering the gap conductive. The high current flowing from the anode to the cathode is accompanied by intermittent light emission from the gap25.Vacuum arcs have been under close attention of researchers since the early 1950s. In spite of many empirical attempts to describe and quantify the phenomenonet al.17 suggest that whether an arc is anode-initiated or cathode-initiated depends on the value of local enhancement factor β on the cathode. Others, make this distinction based on the time delay between the application of a pulse and the occurrence of an arc27. Slade5 proposed to use the gap length as a criterion to consider a vacuum arc to be cathode- or anode-dominated. According to the last suggestion, in a short gap electrode systems, the cathode plays a dominant role in initiating breakdowns, while in contrast, for larger gaps, greater than 2 mm, the anode effect takes over the cathode and the processes developed near the electrode with the higher electric potential determine the evolution of the vacuum arc.Several mechanisms have been proposed to explain the formation of plasma in such high voltage conditions. Some of them attribute the arc initiation to physical processes appearing in the cathode, while others to ones in the anode side. For example, Charbonnier et al.31 have proposed explosive electron emission mechanism (known as the “ecton” model) on the cathode electrode, which leads to plasma formation. Timko et al.23 reported Particle-In-Cell plasma (PIC) simulations showing that plasma can gradually build up from intensively emitting cathodes due to positive feedback ion bombardment, if a minimum initial neutral evaporation rate is assumed. A possible origin for the latter was recently given by Kyritsakis et al.32, who performed multi-scale atomistic simulations and reported a thermal runaway mechanism on cathodic metal nano-tips. All the above proposed mechanisms, along with various experimental studies33, attribute the vacuum arc ignition to processes in the cathode and consider the processes near the anode negligible. In general, the scientific community has not reached a consensus about the role of each electrode on the vacuum arc ignition.Meanwhile, other proposed mechanisms attribute the dominant role for the initiation of a vacuum arc to cathodic processes. Mesyats In the present work we follow the development of a vacuum arc with a nanosecond resolution, for gap lengths varying from 0.5 mm to 5 mm. We observe the evolution of the light emission in the gap by an ultra-fast camera, while recording the gap current and voltage simultaneously. Our experiments in combination with theoretical calculations we conducted, reveal that regardless the gap length, the vacuum arc is always ignited on the cathode side, within a few ns after the field in its vicinity reaches a critical value.−4 Pa, placed at a distance of a few mm from one another. This distance, or the gap length dg, was varied from 0.5 to 5 mm in different experiments. A pulsed high voltage source with a pulse width ΔtV = 1 − 5 μs was connected to the cathode and provided up to Vmax = −40 kV, which was sufficiently high to ensure the appearance of an arc in every single pulse.The geometry of our experiments allowed for a clear distinction between the cathode (thin tip) and the anode (flat surface). The electrodes were installed in a high-vacuum chamber with a vacuum level of 2.5 × 10dg = 5 mm and ΔtV = 1μs . During P0, the gap capacitor along with parasitic capacitances of the system  are being charged and the gap voltage starts rising. P0 ends at t = t0, when the current starts rapidly rising up. t0 is also defined as the origin the time axis in our experiments. During the next phase P1, the current rises up to Imax = 80 A. We note that the voltage continues growing for a short time until tVP; only after this point it drops to a near-zero value, when the current reaches Imax. However, we associate the initial point of the vacuum arc with t0 and not with tVP, since the voltage is expected to keep growing after the current through the gap has appeared. At this initial stage of the arc, the current is not sufficient to consume the voltage over the gap yet. This expectation is corroborated by Simulink34 simulations performed for the same circuit and conditions as used in the experiment  lasts longer. We analysed these variations and the results are presented in Fig. dg, while the initial point of the vacuum arc t0 is much less dependent on the size of the gap between the electrodes.As we observe in this figure, both current Fig.  and voltt0, is shown to decrease systematically with increasing gap length. This clearly indicates that the arc ignites when the local electric field at the apex of the cathode needle reaches a certain critical value. To minimize the impact of surface conditioning on the breakdown voltage, the measurements shown in Fig. dg, the maximum electric field at t0 is 160 ± 30 MV/m, which is in surprisingly good agreement with the breakdown fields measurements for flat Cu electrodes35.In Fig. Based on our experiments, we conclude that the increase of the gap length has affected the duration of the identified phases of vacuum arc evolution, however, it did not affect the process of vacuum arcing dramatically, which would have indicated the switch of leading roles of electrodes in this process.tw down to 2 ns. However, the physical limitation of the device allows five snapshots per second at maximum. Since the pulse width is only a few μs, we were able to obtain only one shot per pulse.We observed the vacuum arcs through a glass window by an intensified charge-coupled device camera . The electronic gate control of the ICCD allows an exposure time t ns with respect to the breakdown time t0 (see the method Section for details). The repeatability of the experiments is verified and shown in the Supplementary Material  is longer and the breakdown voltage at dg = 3 mm, and the voltage pulse width was ΔtV = 1 μs. Figure B = 280 mT applied either outwards  tests on the cathode and anode surface both before and after electrical discharges. was used. Figure To this end, we solved numerically the one-dimensional time-dependent heat diffusion equation for a flat copper plate, as described in the method section. Knowing both waveforms of the voltage over the gap and the current through the gap, we can estimate the heating power deposited by the electrons arriving at the surface of the anode (see the method section for details). This estimation is done under the assumption that during the cathode-radiance stage of the arc (before the anode starts glowing), the electrons are freely accelerated by the gap voltage and deposit all their energy on the anode plate.dg = 1, 3 and 5 mm. We see that the temperatures reach the melting temperature of Cu (1356 K) for all gap distances, with the corresponding vapour pressure exceeding 0.1 Pa. Such a pressure corresponds to neutral atom densities of the order of 1018–1019 m−3. The electrons colliding with these neutral atoms may cause the expanding glow that appears near the anode.In Fig. dg = 1, 3, 5 mm correspondingly). These time scales are in agreement with the times that the anodic glow appears , we integrated over the whole cathode surface the current density obtained by the Child-Langmuir law. The details of this calculation can be found in the Supplementary Material  near the cathode. If the first scenario is true, the tip is heated to a very high temperature due to the Joule and Nottingham effects and emit light due to black body radiation. It is well known that any type of intensive electron emission  is limited by the space charge effect. For very high emitted current density, the forming cloud of the emitted electrons creates a significant space charge in the vacuum above the emitting surface, that screens the applied field and thus causes a negative feedback that reduces the emission. The maximum limit of the current density that can be emitted from a cathode depends on the local surface field and the total applied voltage. This dependence is given by the Child-Langmuir lawdg. This consideration allows us to conclude that the strong light emission seen at the cathode surface cannot be caused by electron emission heating phenomena, since the currents measured through the gap at the time of the strong cathodic glow are much higher than those limited by the intensively building-up space charge. Furthermore, the spherical shape and the high intensity of the cathodic glow that are independent of the gap length, also confirm that the glow is due to the full arc plasma that forms within a few ns after the local field reaches a critical value.Comparing the experimental current waveform with the calculated space charge limit, we can verify the nature of the cathodic glow. Shortly after the beginning of the current rise phase P1  make the anode glow expansion and the gap bridging appear much later, revealing their dissociation from the voltage collapse and the conductive channel formation. Thus, our experiments reveal the anodic glow plays secondary role in the development of the breakdown, which has been previously considered to be of significant importance.The anodic glow appears to be rather different by nature from the cathodic one. The response of the system to the application of a magnetic field shown in Fig. After the conductive channel is formed, the energy available to heat the anode decreases rapidly due to the collapse of the gap voltage. As a result, the anode material gradually cools and stops providing Cu vapour. Thus, the vapour gradually expands and diffuses away, leading to the decay of the light radiation on the anode surface and in the gap. On the contrary, the cathode radiance spot remains at the same high intensity until the end of the pulse. This scenario is consistent with our anode heat calculations, which show that the electron impact power available in the gap is sufficient to heat the anode to high temperatures, within time intervals that are in agreement with the ICCD camera measurements.Given the above, although we do not investigate here whether the anodic glow fulfils the plasma criteria, we can conclude that in contrast to the cathodic glow, it is neither stable nor necessary to sustain the arc. It is rather a transient side-effect of the fact that the gap voltage does not collapse immediately after the arc is ignited, but has a delay time that depends on the gap length.The vacuum breakdown is triggered at the cathode once the surface field reaches a critical value of about 160 MV/m. Immediately after this, a localized intense radiance appears near the cathode; strong experimental and theoretical evidence shows that the latter is produced by a dense plasma that is formed at the cathode and drives the discharge allowing the gap current to grow to breakdown values.A while after the breakdown initiation, another light emission starts from the anode, gradually growing to cover the whole gap. We suggest that this glow results from the electrons that escape the cathodic arc plasma and bombard the anode. Our heat diffusion calculations and the observations of the deflection of the anode glow in a magnetic field, are consistent with the correlation between the anodic glow and electrons escaping from the cathode plasma.Although both the cathode and the anode contribute in the vacuum arc evolution, the role of the cathode is more crucial, since the processes developing at the cathode surface initiate the breakdown and maintain constant radiance from the cathode surface throughout the whole arc process, driving the arc in a stable manner. On the contrary, the anode is active only during a fraction of the arc process, and the anode glow covers the gap long after a full conductive channel is established.In summary, by conducting vacuum breakdown experiments between Cu electrodes under rectangular pulse voltages and using a high-speed ICCD camera, we reconstructed the entire vacuum arc process with nanosecond resolution. Combining these results with theoretical estimations of the electron emission characteristics, breakdown currents and anode heat evolution, we conclude:−4 Pa by a turbo molecular pump. A pair of electrodes was installed in the chamber and the gap length was adjusted by a micrometer manipulator. High voltage was provided by the pulsed voltage source with the output voltage set to −40 kV and a discharge current with the maximum value of 80 A, which was determined by a 500 Ω current limiting resistor installed in the circuit. In addition, the width of the voltage pulse was also adjustable for specific purposes, between 1 μs and 5 μs. The upper and lower electrodes were connected to the high voltage terminal and the ground, respectively.Figure We observed the vacuum breakdowns through a glass window by an intensified charge-coupled device camera . This ICCD has an electronic gate control to ensure a minimum exposure time of 2 ns and offers a gate monitor signal to indicate the time instant of an observation. A high voltage probe (NorthStar PVM-7) was used to measure the voltage across the gap, which has a bandwidth of 110 MHz. The current through the circuit was measured by a Pearson current sensor (Model 6595) with a bandwidth of 200 MHz. The voltage signal, the current signal and the gate monitor signal were all recorded by a four-channel oscilloscope.t0, the delay generator causes a delay time Δt, after which at t1 a signal is given to the ICCD camera shutter to open for an exposure time tw.In addition, a digital delay generator (SRS DG645) controlled the sequence of the experiments, in the manner that is shown in Fig. 39. The schematic in Fig. h = 3dg is converged so that its increase does not affect the field on the conical area.We calculated the electric field distribution around the needle by the Finite Element Method (FEM), using the open-source tools Gmsh-GetDPCv is the volumetric heat capacity, κ(T) is the heat conductivity of Cu (depends on the temperature) and p(z) is the deposited heat density as a function of the material depth z.Since the depth of the heated volume is much smaller than its lateral dimensions, we ignore the lateral heat flow and solve the heat equation in one dimension in order to obtain the heat distribution and evolution. The heat equation can be written asp(z) with the “continuous slowing down approximation – CSD”40. This means that we consider the deposited heating power density to be constant over the CSDA range zd and zero deeper than it, i.e. p(z > zd) = 0 and p(z < zd) = P/zd, with P being the deposited heating power per unit area. The heat conductivity of Cu is calculated by applying the Wiedemann-Franz law on the values of the Cu electric conductivity found in the literature42 and the CSDA range zd is found by the ESTAR database40.For the purposes of this work we approximate P, we have to consider a certain distribution for the current density of the electron beam impinging on the anode. We assume that this roughly follows a Gaussian distribution with its width σ being estimated from the width of the anodic glow appearing in the camera images as σ = 0.3, 0.85, and 0.95 mm for dg = 1, 3, and 5 mm correspondingly. Then the peak power in the center of the beam can be found as V(t)I(t) gives the total power deposited on the anode by the discharge and is taken from the measured waveforms.In order to estimate the deposited heating power T. The equation is solved over a total depth domain of 20 μm, sampled at 512 equidistant points, with zero-heat-flux Neumann boundary conditions at the boundaries. The initial temperature is assumed to be uniform at 300 K and we used a forward-time-central-space finite difference integration scheme43 with a time-step of 0.2 ps. When the temperature profile T is calculated, the corresponding vapour pressure and vapour density are obtained from the surface temperature T by interpolating tabulated temperature-pressure data46.With the above assumptions, we solve the equation  to obtaiSupplementary to: Direct observation of vacuum arc evolution with nanosecond resolution


MIGS) devices and are among the smallest devices implanted in the human body. This review discusses the design criterion and constraints as well as the user requirements for MIGS devices. We review how recent devices have attempted to meet these challenges and give our opinion as to the necessary characteristics for the development of future devices.Glaucoma is the leading cause of irreversible blindness with over 70 million people affected worldwide. The surgical management of glaucoma aims to lower intraocular pressure by increasing aqueous outflow facility. The latest manufacturing techniques have allowed for the development of a number of novel implantable devices to improve safety and outcomes of glaucoma surgery. These are collectively referred to as minimally invasive glaucoma surgery ( FigureGlaucoma is a group of optic neuropathies characterized by progressive degeneration of retinal ganglion cells and resulting in damage to the optic nerve head and loss of visual field.Conventional GDDs, such as the Ahmed glaucoma valve  or Baerveldt glaucoma implant , were traditionally used in patients at high risk of failure for standard trabeculectomy  due to the increased risk of fibroblast proliferation and episcleral scarring.Although the use of aqueous shunts shows some positive short‐term benefits, potential postoperative complications include corneal decompensation, suprachoroidal hemorrhage, and hypotony. Device failure also occurs due to suboptimal tissue compatibility, a design “failure” resulting in a fibrovascular response surrounding the end plate; reports suggest a failure rate of 10% per year.FigureTableab interno or ab externo approach, associated with little or no scleral dissection and minimal or no conjunctival manipulation.”To meet this clinical need, a number of devices have recently been developed labeled as either micro‐incision or minimally invasive glaucoma surgery (MIGS) devices that modulate aqueous humor outflow facility via one of several routes Figure. Table1In this paper, we review MIGS devices from the engineering design perspective. This provides the clinical community with a greater understanding of the necessary design criterion and constraints to develop a novel MIGS device. We review the literature to assess how novel MIGS devices have attempted to meet these challenges. We conclude with a summary of the challenges facing novel MIGS devices and our opinion as to the necessary characteristics for future devices.Design is a core engineering component with a rigorous methodology.FigureQaq, daytime measurements in adults aged 20–83 years) being estimated as:In a healthy eye, IOP is necessary to maintain visual function by ensuring that the eye is turgid. The IOP is maintained by a sustained flow of aqueous humor, whose pathway is shown in FigureQaq is the rate of aqueous humor formation, Pi is the intraocular pressure, Pe is the episcleral venous pressure, and C is the tonographic facility of outflow.Diurnal variation means that the flow rate can be 3.0 μL/minutes in the morning or 1.5 μL/minutes at night.Pafter. This should be contrasted with the IOP prior to surgery, Pbefore. There are at least three ways of defining the relationship between Pafter and Pbefore and these have important design implications:The purpose of a MIGS device is to reduce the IOP to levels that will reduce visual field progression (close to 10 mmHg) while causing minimal postoperative complications.R. Because the aqueous flow is assumed to be unchanged, then this criterion reduces the device to having a fixed resistance and from this a fixed shape.Criterion (a) expresses a percentage reduction of IOP by a factor Pdesign is set). This can only be applied if the MIGS device has a variable resistance and the IOP would be the same. This means that a valve mechanism must be present so the resistance is variable.Criterion (b) expresses a target design pressure after the operation for all the patients (where Criterion (c) expresses a defined reduction in IOP. This only works if the MIGS device has a variable resistance and so is the same as (b); more challenging still is that the valve opening pressure is different for different patients.R would ideally be in the region of 0.5–0.8,R, including the aqueous outflow path following device insertion or the influence of the bleb with devices that drain into the subconjunctival space . Therefore, the design criterion (a) where the IOP is reduced by a specific fraction is the more appropriate choice when developing a novel MIGS device (Criterion (a) is applicable to most MIGS devices. e Figurea. ThereTableP) and flow rate (Q) through a pipe of length L and diameter D:μ is the dynamic viscosity. The right hand side of Eq. De is the equivalent diameter and RMGS is the flow resistance. De is the equivalent to the pipe internal diameter for a circular tube. Using Eqs. RMGS in terms of IOP reduction and volume flux. It is observed from Figureb that assuming a flow rate of 2 μL/minute and a device length of 10 mm, a tube of 300 μm inner diameter (ID), such as that found in conventional GDDs like the Ahmed glaucoma valve and BGI, there is no resistance to flow and R is close to zero, resulting in hypotony  if secondary flow resistance mechanisms are not in place.The design criterion is cast in terms of a fixed resistance. There is a wide range of MIGS devices with many different geometries, yet they have the same function Table. To compmeter D:PQ=128μLπmeter D:PQ=128μLπe of Eq. De=128μLπFigurec demonstrates the relative volume flux of aqueous flow through the device depending on the size of the device lumen. Although a larger lumen will result in the MIGS contributing to a greater proportion of the overall flow through all outflow pathways, it also means there is a greater risk of hypotony, as previously discussed. Therefore, the design of the MIGS is critical to ensure that it has enough of a role on aqueous outflow while also reducing the risk of hypotony.Care needs to be taken in applying these resistance relationships because only a portion of the total aqueous humor generated will pass through the device with the remaining draining through the normal anatomic drainage pathway. Although the aim of the MIGS device is to reduce the risk of glaucoma progression through reducing IOP, other patient factors also need to be considered. Biomaterials refer to any medical technology that is designed to interact with human tissues/components, including devices, cell therapies, synthetic polymers, and biopolymers.DS) of the device can be defined asE is the Young's Modulus and L is the length of the device. l is the second moment of area, a geometrical property of an area that reflects how its points are distributed in relation to an arbitrary axis. For an annulus of inner radius r1 and outer radius r2, the second moment of area can be defined asBiocompatibility refers to both material type and how tissue responds to an embedded device. One useful measure is the stiffness of the device. Stiffness of the device is critical to keep it in a fixed position and not fail due to fatigue. The real challenge is that the bendability of MIGS devices needs to match the properties of the tissue otherwise there may be complications, including encapsulation and tube erosion, another late postoperative complication observed following implantation of a GDD that is not observed following trabeculectomy surgery.Figurea shows the Young's modulus of a number of MIGS devices that have been released for clinical use or are currently undergoing clinical trial , manipulation under the extra‐ocular muscles. These steps require additional time to complete, subspecialty training, and carry risk of complications, including diplopia.ab interno or ab externo incision. MIGS devices are often placed at the time of cataract surgery. In order to access the insertion site, the device is often inserted via a contralateral limbal incision. To ensure there is enough space in the anterior chamber for the device to safely pass over the pupil or for visualization of the anterior chamber angle, cataract surgery is often performed but is not always necessary.In order to decrease the risk of complications and to aid surgeon handling, novel devices should be minimally invasive while having a size constraint of <25 mm depending on the insertion location. Novel insertion techniques may be required via either an MIGS devices are clustered into three groups depending on the aqueous drainage site.The iStent  is a titanium L‐shaped tube with a curved open lumen fitting into Schlemm's canal connected to a smaller‐sized tube  designed to traverse the trabecular meshwork and connect with the anterior chamber.The Hydrus Microstent  is an 8 mm long nonluminal open Nitinol scaffoldab interno approach. The iStent and Hydrus Microstent have a relatively open scaffold, compared with the iStent Inject.The common feature of devices that increase aqueous outflow facility into Schlemm's canal is that they are inserted via an The CyPass Micro‐Stent  is a fenestrated polyimide microstent of 6.35 mm length and 510 μm external diameter.The Solx Gold Shunt  generates an aqueous flow from the anterior chamber into the suprachoroidal space for eventual drainage via the uveoscleral outflow pathway.The iStent Supra is the third device developed by Glaukos. It is a heparin‐coated device composed of polyethersulfone and titanium and is 4 mm in length with a luminal diameter of 165 μm. It is curved to conform to the contour of the globe and has ridges to improve implant retention.ab externo approach.The STARflo  is inserted into the suprachoroidal space via an FigureThe EX‐PRESS glaucoma filtration device  is a stainless steel, non valved tube with a disc like flange at the subconjunctival space end and a spur like projection at the anterior chamber end to prevent extrusion.ab interno and has different lumen IDs  to allow titration of different IOP control.The XEN gel stent  is a hydrophilic tube of porcine gelatin cross‐linked with glutaraldehyde that is placed ab externo and is composed of Poly (Styrene‐block‐IsoButylene‐block‐Styrene (SIBS)), a thermoplastic elastomer whose physical properties overlap both silicone rubbers and polyurethanes.The InnFocus/PreserFlo MicroShunt  is also a tube that drains aqueous humor into the subconjunctival space but differs from the XEN gel stent as it is inserted Figureb shows the relationship between the length of the device and their equivalent diameter. Generally, it is observed that devices that drain into the subconjunctival space tend to be long and narrow. Given that the outflow resistance of the bleb is low during the early postoperative period, the device dimensions need to control the majority of the pressure drop, otherwise there is a risk of hypotony.in vitro studies have been performed with all three devices and shown similar levels of increased outflow facility between them: 0.12–0.22 μL/minutes/mmHg (83% increase) for a single iStent and 0.16–0.38 μL/minutes/mmHg (138%) with the iStent Inject,Devices that increase drainage into Schlemm's canal have a larger hydraulic diameter than those that drain into the subconjunctival space in order to dilate Schlemm's canal adequately to increase its outflow resistance. The iStent devices tend to be very short as their aim is just to bypass the juxtacanalicular portion of the trabecular meshwork that is presumed to be the main resistance to outflow.Because all the devices are inserted into the eye, they all must meet the requirement of biocompatibility in terms of material selection using a variety of metals, plastics, or gels.ab interno need to be designed in such a way that they can be introduced easily with an inserter device into the anterior chamber via such an approach. The majority of the MIGS devices have a tubular structure that allows them to be inserted via a needle tract  where they have an aspect ratio (height/width) close to 1. Exceptions to this include the Solx gold shunt, STARflo, iStent, and the Hydrus microstent, the latter acting more like a scaffold to dilate Schlemm's canal. The Solx Gold Shunt and STARflo drain into the suprachoroidal space and are at risk of scarring.Figurea).MIGS devices that are inserted t Figurec where The voluntary withdrawal of the CyPass was due to concerns relating to corneal endothelial cell loss with a 3% risk of loss per year compared with 1% per year in control patients at 5 years. This may be related to the stiffness of the device and contact between the CyPass and the corneal endothelium. Although further data are required to assess whether these findings are visually significant, it may be appropriate to monitor patients who have undergone surgery before further action is required.in situ in order to maintain excellent long‐term outcomes.Device geometry plays an important role in modulating outflow resistance, but has to be matched with appropriate materials that can not only provide the necessary support to maintain the device structure but can also be delivered with minimal trauma to the surrounding ocular tissue and stay The stainless steel Ex‐PRESS glaucoma shunt was designed to create a more reproducible and less traumatic alternative to a trabeculectomy procedure.Figurea, to reduce the risk of tube extrusion. Long‐term animal studies using the XEN showed no change in implant cross‐section up to 6 years following implantation.in situ conforming to the implant site with a high degree of flexibility that mimics the natural scleral tissue. A misplaced XEN implant during early‐stage pilot surgery of the implant in a human eye showed that it remained in the subconjunctival space for 6 months with no fibrosis or vascularization around it.The XEN Gel Stent and InnFocus Microshunt also drain into the subconjunctival space, but as they do not rely on the scleral flap to affect outflow resistance, they have to be longer devices than the ExPRESS and, therefore, made of soft materials, as shown in The InnFocus made of SIBS has been shown to cause minimal inflammation or scar formation with 100% patency at 6 months in animal studies.Figurea. Minimal histological data are available to assess the tissue response to the iStent, but Hays et al.Devices that increase outflow facility in Schlemm's canal need to be made of relatively rigid materials to maintain the lumen diameter, as shown in Figurea). Clinical studies of the Solx Gold Shunt have shown the formation of a fibrotic capsule around the device that could be either due to noninflammatory connective tissue proliferation or as a result of chronic inflammation in the suprachoroidal space affecting their long‐term efficacy.et al.Suprachoroidal devices that are relatively flat with a low aspect ratio need to be relatively stiff in comparison to devices implanted into the subconjunctival space Figurea. CliniThe National Eye Institute Audacious Goals Initiative challenged participants to imagine the greatest achievement for vision research during the next 10–15 years. We proposed a 10‐10‐10 aspiration goal, which was an implanted GDD and associated therapy that could control IOP to 10 mmHg  to optimize the wound healing response and increase the likelihood of the device sustaining low IOP to 10 years.The material properties of the device should be such that they conform to the surrounding tissue environment with minimal risk of extrusion or development of fibrous encapsulation. Whereas devices that drain into the subconjunctival route can be inserted via either the Many of these new devices have not been in patients for long, but there seems to be growing evidence (up to 5 years at present) that the 10‐year challenge will be met. Together with the 10‐minute challenge below, developing a device that can last for 10 years will most likely increase the cost‐effectiveness of MIGS devices. Given the relative cost of these devices at present, there is currently insufficient evidence to demonstrate their cost‐effectiveness. A device that can sustain low IOP for up to 10 years and takes 10 minutes to insert will most likely be a cost‐effective treatment option for glaucoma and play a significant role in altering the treatment paradigm for patients with glaucoma. Developments in anti‐inflammatory agents and device coating may also play a role toward achieving the 10‐year challenge, but a discussion of these factors is beyond the scope of this review.Ab interno surgeries tend to be fast, after the eye has been prepared. For example, the XEN device can take about 15–20 minutes for implantation (including eye preparation). The difficulty with fast surgery is that the level of surgical skill rises and the outcome of failure  can be traumatic. Ab externo surgeries provide a safer route for surgical implantation and also include the introduction of pharmacological agents to promote wound healing. For example, the InnFocus device takes around 20–30 minutes for implantation (including eye preparation). Although this is slightly longer than a device inserted via the ab interno approach, it may also play a role in helping to achieve the 10 mmHg challenge as well. We, therefore, feel that until a method of insertion and application of wound healing agents for devices inserted via an ab interno approach has been optimized, the ab externo approach provides the best route for insertion. Further refinement of the insertion technique will, therefore, enable the 10‐minute challenge to be met.This is the most difficult element of the challenge and is essentially aspirational. Indeed, the waiting time of the patient to prepare the eye for device implantation tends to be much longer than the implantation duration and application of antimetabolites. It is useful to compare times against the gold standard, the trabeculectomy, which takes ~ 30−60 minutes to complete depending on the complexity of the patient. We have reviewed the design criterion and design challenges of MIGS devices, without focusing on a specific device. This has enabled us to identify common features across a wide range of devices and understand why they work.We have shown that most suprachoroidal devices are quite stiff and have low flow resistances. The evidence is that the IOP is maintained because the devices are encapsulated and the encapsulation is the origin of the flow resistance. Here, the IOP is not controllable.The trend for subconjunctival MIGS is now toward devices with lower stiffness and higher flow resistance. Still, we estimate that at least one‐half to two‐thirds of the flow resistance is caused by the bleb. The low stiffness of the devices assists in the biocompatibility element.ab interno and ab externo approaches through improved device design.We have reviewed the current state of MIGS devices in relation to the 10:10:10 goal. Although there are a number of MIGS devices available on the market and still in development, none currently meet the 10:10:10 goal. This review aims to discuss the necessary aspects to reach this goal, and until such a device is available, research should continue and future devices should still be developed in order to treat glaucoma and reduce the global burden of sight loss. There is a strong chance that two of the challenges will be met within the next few years with the 10‐minute challenge being an aspirational goal. This can only be achieved by combining the benefits of The authors acknowledge the support of the Medical Research Council, Moorfields Special Trustees & Moorfields Eye Charity, the Haymans Trust, the Helen Hamlyn Trust in memory of Paul Hamlyn, and Fight for Sight (UK) Ron and Liora Moskovitz, John Nolan, Richard Desmond Foundation, and the Michael and Ilse Katz Foundation. This research has received a portion of its funding from the National Institute for Health Research (NIHR) Biomedical Research Centre at Moorfields Eye Hospital, and the UCL Institute of Ophthalmology.P.T.K. has been on advisory boards for Pfizer, Bausch and Lomb, Alcon, and Teva Pharmaceuticals. All other authors declare no conflict of interest.Supplementary MaterialClick here for additional data file.


Spindle epithelial tumor with thymus‐like differentiation (SETTLE) is a rare tumor of the thyroid gland occurring in children and young adults. This report presents SETTLE as a tumor that can also affect young children (under fives). Although majority of the reports were in Caucasians, the tumor can affect all races. Examination revealed a nontender, mobile, and multinodular left‐sided neck mass measuring 8 cm × 6 cm in dimension and there were no cervical or supraclavicular lymphadenopathies.Thyroid function test was normal while ultrasound of the neck revealed a solid lesion mainly on the upper pole of the left lobe of the thyroid gland. Fine needle aspiration cytology was suspicious of malignancy. Plain radiograph of the neck showed deviation of the trachea to the right side. At surgery, the left lobe of the gland was involved and a left lobectomy was done with no adjuvant therapy. Gross (macroscopic) examination of the tumor showed a nodular mass measuring 6 cm × 4 cm × 4 cm and weighing 35 g. Cut sections revealed a tan colored lobulated tumor, firm in consistency, and disposed in whorled appearance. Focal areas of cystic spaces were seen. The tumor was highly cellular with proliferating spindle and polygonal  cells occurring predominantly in lobulated and fasciculated patterns Figure . The spiImmunohistochemical study showed that both the spindle and polygonal cells were positive for pan cytokeratin (AE1/AE3), galectin‐3, and HBME but were negative for CEA, S‐100, CD 31, CD 34, chromogranin, calcitonin, p53, and CD117. Cytoplasmic positivity for smooth muscle actin (SMA) was seen in few of the spindle cells while about 5% of the tumor cells were Ki‐67 nuclear positive suggestive of low proliferative index. The final diagnosis of spindle epithelial tumor with thymus‐like differentiation (SETTLE) was made based on the histopathologic features and immunohistochemistry. Postoperatively, the recovery was good. She was discharged and followed up for about six years with no recurrence.3Spindle epithelial tumor with thymus‐like differentiation (SETTLE) is an uncommon tumor arising from the thyroid gland but yet to be well characterizedThe tumor has a slight male preponderance than female with sex ratio of 1.5:1.Macroscopically, SETTLE appears encapsulated or partially circumscribed; it is firm, bosselated grayish white with an undefined whorled cut surface that may be lobular and cystic.SETTLE has atypical clinical symptoms and signs and this makes preoperative diagnosis difficult as depicted from the review of previous cases.There is wide variation in the duration of clinical symptoms before the diagnosis is made with the range being 3 weeksAlthough SETTLE exhibits delayed metastasis, it must be treated as a potentially malignant tumor as it can metastasize several years after surgical resection with the lungs as one of the commonest sites of metastasis.In conclusion, we report here the first case of SETTLE in Nigeria and most probably from sub‐Saharan Africa. The clinical presentation and behavior were typical and similar to the previously reported cases. Early diagnosis and surgical resection of the tumor with meticulous long‐term follow‐up of the patients is key to ensuring a good prognosis.We also want to declare that there are no conflicts of interest in the production of this manuscript and the work was solely funded by the authors.OOO: Has made substantial contributions to conception and design and acquisition of data; has been involved in drafting the manuscript and revising it critically for important intellectual content. Has given final approval of the version to be published and has agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. GOO: Has been involved in analysis and interpretation of data; drafting the manuscript and revising it critically for important intellectual content. Has given final approval of the version to be published and has agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. AOO: Has made substantial contributions to conception and design; acquisition of data; analysis and interpretation of data. Has been involved in drafting the manuscript and revising it critically for important intellectual content and has given final approval of the version to be published. TAJ: Has been involved in analysis and interpretation of data; drafting the manuscript and revising it critically for important intellectual content. Has given final approval of the version to be published and has agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.


Indoor localization systems assume that the user’s current building is known by the GPS . However, such assumptions do not hold true in GPS denied environments or where the GPS cannot determine the user’s definite location. We present a novel solution to identify the building where the user is present now. The proposed building identification method works on the pervasive magnetic field using a smartphone. The accelerometer data determines the user’s activity of being stationary or walking. An Artificial Neural Network is used to identify the user’s activities and it shows good results. The magnetometer data is used to identify the user’s current building using the fingerprinting approach. Contrary to a traditional fingerprinting approach which stores intensity values, we utilize the patterns formed by the magnetic field strength in the form of a Binary Grid (BG). The BG approach overcomes the limitation of Dynamic Time Warping (DTW) whose performance is degraded when the magnitude of the magnetic data is changed. The experiments are performed with Samsung Galaxy S8 for eight various buildings with different altitudes and number of floors in Yeungnam University, Korea. The results demonstrate that the proposed building identification method can potentially be deployed for building identification. The precision, UAR , F score, and Cohen’s Kappa values are used to determine the performance of the proposed system. The proposed systems shows very promising results. The system operates without any aid from any infrastructure dependent technologies like GPS or WiFi. Furthermore, we performed many experiments to investigate the impact of isolated points data to build fingerprint database on system’s accuracy with 1 m and 2 m distance. Results illustrate that by trading off a minor accuracy, survey labor can be reduced by 50 percent. In the modern era of ubiquitous computing where the demand for Location Based Services (LBS) is increasing exponentially, positioning requires two fundamental characteristics: pervasive coverage and infrastructure independence. Precise location determination plays a very crucial role, not only for LBS but also for health care, assets monitoring, emergency search, rescue response, etc. Outdoor localization is mostly based on the GPS technology as it can provide an estimated location as accurate as 5 m. However, in many situations where the user location is surrounded by high-rise buildings or cloudy environments, the positioning accuracy can drop drastically to as low as 50 to 76 meters ,2. GPS, The researchers spotlighted other emerging technologies that can be used for positioning, especially in the indoor, and GPS denied environments. The primary focus of such research is to utilize the modern smartphones which are pervasive and infrastructure independent. Unlike RFID (Radio Frequency ID), IR (Infrared), iBeacons, Ultrasound, vision, and Wi-Fi based indoor positioning systems, smartphone based systems use built-in sensors of smartphones . RFID, WThe smartphone based systems are cheap as the installation and maintenance of additional infrastructure is not needed. One limitation of these systems is their dependence on GPS to know the place/building information before indoor positioning can be performed. Many such techniques consider that the starting position is known as a priori or consider a naive approach that the GPS calculated position of a building is correct where the user currently is, before localizing it indoors. The building identification is an important element of localization systems which perform both indoor and outdoor localization. GPS accuracy to determine the user’s current building is limited as stated above. Many current indoor localization systems operate on the assumption that the correct building information is already known. Thus, the localization is performed with respect to the known building, e.g., in the case of the Wi-Fi based system, the map of the current building and the database is loaded to perform the localization. The correct building information of the user plays a pivotal role in such localization systems. Thus, many research works have proposed the integration of GPS with other sensors ,6. Howevx, y, and z values that can be used for this purpose. The earth’s uniform magnetic field within a small constrained area is disturbed by the presence of ferromagnetic materials like elevators, door, and concrete structures and causes direction anomalies. However, such disturbances are researched to serve as a unique signature also called the fingerprint [We propose the use of the magnetic field data to identify the building where the user is currently walking. The magnetic sensor in the smartphone provides magnetic gerprint  and can gerprint  as well  systems ,14,15,16This research presents a novel technique which makes the use of the smartphone magnetometer for building identification and, to the best of authors’ knowledge, it is the very first attempt to utilize the magnetic field to identify buildings. The contributions of this research include an infrastructure free building identification model which solely works on smartphone sensors and a deep learning based ANN model which can predict a user’s activity of walking and stationary. Additionally, we use the Binary Grid (BG) to prepare the fingerprint database which stores the patterns formed by the magnetic field instead of magnetic magnitude itself. This overcomes the limitation of Dynamic Time Warping (DTW) whose performance is affected by the varying magnitude of magnetic data collected over different time.The rest of the paper is organized in five sections. The building identification is not a new problem and has been studied for quite a long time. GPS is considered the chief technology for building localization and it works quite fine. Besides GPS, other assisting technologies including cameras and most recently barometers are used to achieve a higher accuracy.The authors in  presenteThe authors in  propose The authors in  propose Several similar research works focus on IO (indoor-outdoor) environment detection as it is one of the important tasks in the active field of indoor positioning and localization. The majority of existing research works on indoor localization operates on the assumption that the user is in an indoor environment already when they start to locate him indoors. However, this poses challenges in scenarios where the localization environment contains both the indoor and outdoor environments, like the open covered space between two buildings and over bridge open corridors, etc. Thus, building identification is also very important in such situations where the positioning system needs contextual status to switch between indoor and outdoor positioning modules. The authors in  propose The authors in  use BlueThe proposed building identification method utilizes the built-in sensors of the smartphone. (i)The user is entering a specific building now.(ii)The user is already in a building.The fingerprint database is built using the magnetometer data for this purpose. The concept of the fingerprint is to connect a fingerprint/signature to relevant locations in a given indoor environment. The fingerprint represents a feature like signal strength, a pattern of a signal or any other similar characteristic which makes it possible to distinguish between various locations. Analogous to the Wi-Fi fingerprinting where RSSI   serves aFor the first option, the building identification can be performed by making a fingerprint database of only the portion close to the entrances. Since we use only 4 sec data, we need to collect the fingerprints of only a 4 to 6 meter area, starting from the entrances. However, the second scenario requires building the database for the complete building, as we do not know where the user is exactly right now. Thus, keeping these two possibilities in mind, we make the fingerprint database of the whole building. Since during the building identification the magnetic data is collected while the user is walking, we need the fingerprints between the selected location points as well. The spline interpolation is applied to generate the intermittent values between the grid points. The fingerprint collection process and the resulting interpolated values are shown in Traditional magnetic fingerprint-based systems use the magnetic intensity as the fingerprint and thus have two major limitations. First, the magnetic intensity value may be different during different collection times even with the same device, which limits the performance. Second, various devices show different magnetic intensity even for the same location, which leads to device dependence. These issues are handled by using the magnetic field patterns in . The magAlgorithm 1 Generate the magnetic pattern1:2:3:4:5:6:fordo7:    8:    9:end forN shows the number of rows and M is the number of columns. Then, each magnetic data point is taken and converted to a row number by subtracting it from the maximum magnitude of data and rounding it. Afterwards, a 1 is added to the calculated row and this process is repeated for all the data values. The BG shown in Let’s assume that the magnetic values shown in W shows a contiguous set of matrix elements which defines a mapping between the given elements of X and Y. The warping path is built by arranging the elements of X and Y on the sides of a grid as shown in The matching between the user collected samples and magnetic pattern database is performed using the Dynamic Time Warping (DTW). The DTW was first proposed by Berndt and Clifford in 1994 . It was Each cell of the grid shows the distance between the elements of two sequences. The warping path is through the cells that show the minimum distance. The overall distance represents the minimum of the sum of distances between the individual elements of given sequences. The DTW technique is good at comparing the sequences of varying lengths, yet it compares the magnitude of the given sequences. This limitation severely confines the systems which are based on the magnetic field data. The reason is the varying magnitude of the magnetic data. For example, We already mentioned that the magnetic data for a given location may show different magnitudes every time we collect the data. Thus, if we use traditional DTW, it will produce erroneous results. Experiments reveal that the magnetic data magnitude may change; however, the patterns of magnetic data remain almost similar. Thus, we utilize the patterns formed by the magnetic data. The Euclidean distance calculated using the magnetic pattern of the given samples are very similar. Contrary to the previously calculated distance of 11.94 and 26.92, now the distance is 11.31 and 12.72 for the given samples. It shows that, when the DTW is used with the BG of magnetic patterns, it becomes more accurate and less prone to the changes in the magnitude of magnetic field data. The data collected from the magnetic sensor is used to make the fingerprint database while the building identification process uses the data from the accelerometer and magnetometer. The data from these sensors are collected over 4 sec and split into four frames each containing 1 sec data. Each frame is processed separately and the final decision is made after the processing of four frames is completed.f. The size of a frame is 1 sec and it contains 10 measured values of acceleration data along x, y, and z-axis as the data is collected at a sampling rate of 10 Hz (new measurement after 100 ms). Using the given three axes of accelerometer, the total acceleration is calculated as:i shows the measurement for the given frame f. We want to use the acceleration magnitude to detect if the user is walking. The acceleration data as shown in The accelerometer is used to identify the user’s state of walking or stationary in a given time frame A simple threshold-based movement detection can also be used to identify if the user is walking or standing stationary. However, the limitation of using the threshold-based heuristic approach is its low accuracy in many cases. Occasionally, phone shaking during the stationary mode generates the acceleration and the data crosses the threshold set to detect the user walking state. The ANN  identifies the sequence patterns formed while walking and its accuracy is higher than that of a simple threshold-based movement detection. The ANN has shown good performance even in such cases. We use an ANN for the classification of user activities as many types of research ,27,28 hax, y, z, and total acceleration, and variance of x, y, z, and total acceleration. The variance of acceleration in x, y, z, and total acceleration have higher importance so they are used in the ANN model. The Soft-max activation function is used for ANN. A total of 3000 samples of each feature are used for supervised training. The data is collected at a sampling frequency of 10 Hz and a low pass filter is used in the pre-processing phase to reduce the effect of noise. The ANN achieves an accuracy of 92.67% with 10,000 samples tested.The ANN is the mathematical modeling of human brain which imitates the function of brain neurons. Similar to a neuron, it is comprised of three layers: an input layer, an output layer and hidden layer(s). Edges are used to connect these layers and each edge bears a weight. Edge weights are determined during the process called back-propagation. An important process in ANN modeling is the selection of the appropriate feature set. Thus, a feature importance analysis is desirable before features are used for training. The Repetitive Feature Elimination (RFE) is performed for the current study to select the most suitable features. The RFE recursively eliminates less important features, and builds the prediction model on those features only, which remain present after the specified iterations. We use a set of eight features including The pivotal part in identifying a building is performed by the magnetometer module as the identification process is totally performed using the data collected by the magnetometer. The correct building is found by matching the collected data against the fingerprint database which is built during the offline phase of the system. The proposed algorithm BLocate is used for localization. Algorithm 2BLocate Building identification with sensors’ data.  1:if User is walking then  2:fordo      3:          4:fordo          5:              6:              7:end for           8:          9:        10:end for    11:end if12:The algorithm follows these steps to predict the building where the user is currently walking.Step 1: The data is collected using magnetometer and accelerometer with a smartphone. First of all, the accelerometer data is utilized to classify the user’s mode of walking or stationary. If the user is in a walking state, then the magnetic data is used for further processing.Step 2: The magnetic data is transformed into magnetic patterns. As it is previously mentioned that the magnetic fingerprint database is made up of magnetic patterns during the offline phase, we need to transform the magnetic data to magnetic patterns during the online phase to match them against the fingerprint database.Step 3: During the third step, the online magnetic field pattern is matched against the database of all the floors of all buildings. Since the user’s walking speed varies, it results in different magnetic patterns depending upon the walking speed. We use the DTW for matching as it serves as a tool to compare two time-dependent sequences of varying length [g length . The DTWStep 4: Once the Euclidean distance between the user sample and the fingerprint database is calculated, we need to find the point where the error/distance is the minimum as that point is the most suitable candidate. Thus, each floor’s candidate is the lowest error estimate.Step 5: Once the minimum error for each floor of each building is calculated, these errors are to be normalized. Since each building has a different number of floors and each floor may have a different error depending upon which floor the user is actually on. The magnetic field shows higher similarity to floors of the building where they are taken from. It infers that the magnetic data collected from a floor of a building A should show similar matching results to the other floors of building A as well. Thus, comparing the error value of a single floor is not appropriate. Instead, if we normalize the error with the total number of floors that would give more accurate results. The normalization is done using: Step 6: After normalization, the minimum error value represents the building where the user is right now. As mentioned earlier, the total user collected data is split into four consecutive frames, so this process of building identification is repeated for the four frames. Each frame possesses a vote and the final decision is based upon the votes of the four frames. After this process is complete, we have four predicted buildings which are called building candidates. In certain situations, it is also possible that the predicted buildings are very different so we need to correct the predictions. Since we use four frames data so the output candidates are four buildings and can have one of the following forms:The prediction set has only one building as output.The prediction set has three predictions for one building and one prediction for the other.The prediction set has two predictions each for two different buildings.The prediction set has one prediction for four different buildings.The first set is very perfect. As the prediction is only one building, there are no outliers. In the second case, the building that has three predictions in the prediction set is selected as the building where the user is positioned. For the third option, where we get two various buildings, the building with lower error is selected as the target buildings. However, if the error is the same as well, then the building with the higher number of floors is the target building. The same procedure is adopted for the fourth case and first priority is given to the candidate with the lower error, and then to the building with a higher number of floors, when each building candidate possesses the same value of error:We need to understand four basic notations used in the classification before we move forward to calculate the accuracy measures of a classifier .True Positives (TP): These represent the positive tuples of a class that are correctly labeled by the classifier.True Negatives (TN): These represent the negative tuples that are correctly labeled by the classifier.False Positives (FP): These are the negative tuples that are incorrectly labeled as positive by the classifier.False Negatives (FN): These are the positive tuples that are incorrectly labeled as negative by the classifier.TP, TN, FP, and FN, accuracy is calculated using:F score is a statistical analysis measure of classification, which considers both precision and recall of the classifier and computes a score between 0 and 1. The values closer to 1 represent the higher performance of the classifier and F reaches 1 when the classifier performs 100% correct classification. The F score reflects the average effect of both precision and recall. It is calculated as:k is a statistic that is used to measure the true inter-rater agreement [Accuracy is a measure widely used to evaluate the performance of a classifier and it is defined in terms of the percentage of the buildings predicted correctly . Using tfficient  also repgreement . It defithors in  state thThe experiment is conducted in various buildings located in Yeungnam University, Republic of Korea. The buildings are selected with two points in consideration. First, the buildings should have a various number of floors and different indoor infrastructure. Secondly, two groups of buildings are selected including closely located buildings and buildings separated geographically apart by at least 1/2 mile. The goal of this setting is to make the scenario more realistic so that the algorithm’s performance can be evaluated for real applications. The indoor space available for the data collection is different within each building as well as for each floor in some cases. The details of indoor maps of each building and the area used for the experiment is shown in Initially, we tested the algorithm with four buildings including IACT, ITE, MSE, and CRC to evaluate its performance with respect to both the response time and accuracy. The results show that the algorithm performs very well both for the classification accuracy and the response time. The response time is averaged over 5000 user requests and it includes only the processing time. The processing is done on the server side which is an Intel Core i5 3.2 GHz  operating on Windows 8.1  with 8 GB RAM. The second experiment is conducted with eight various buildings. The purpose of this experiment is twofold: to analyze how the prediction accuracy is affected and what impact it has on the processing time.The classification results with eight buildings are shown with a confusion matrix in The reason for an increase in the response time is quite obvious; the higher number of databases led to the increased processing time for matching the user given sample. The rationale for lower performance is that when the number of fingerprint database increases, the probability of databases with similar fingerprint increases likely. This is caused by two factors. First, the closely located buildings may have a similar magnetic field. Second, although still located separately, a similar internal infrastructure may lead to a similar magnetic field. The second reason is more logical and valid because, in university campuses, traditionally many departments are built in an identical internal design which may lead to very similar magnetic behavior. We perform an experiment to check the similarity of magnetic databases with each other. We match each building database to the database of every other building to analyze which buildings exhibit similar magnetic behavior and the results are shown in Results indicate that the magnetic databases of MSE and TE and MSE and EE  approach which transforms the magnetic magnitude into magnetic patterns and then stores them. The BG approach overcomes the limitation of Dynamic Time Warping (DTW) as well. The DTW approach shows different results for the data of the same place collected during different times. The BG approach followed in this paper shows very similar results for the data collected over different times. The data is collected at points which are 1 m apart and then interpolation is applied to generate the intermittent values between these points. The two important factors associated with a successful model i.e., response time and accuracy are investigated using two scenarios.The first scenario involves the localization with four buildings which are geographically well separated. The proposed method performs very well both in terms of accuracy and response time and obtains an accuracy of 90.54% and a response time of 0.21 sec, which involves processing 4 sec data gathered from the accelerometer and magnetometer. The second scenario is more realistic where the experiment involves eight buildings with 29 floors in total. In spite of the fact that with an increased number of databases the accuracy can be severely affected, the overall accuracy of the proposed method is 86.37% and the average response time is 0.32 sec only. The accuracy of only two buildings is depraved and lowers under 70%, while other six buildings sustain the accuracy over 80%. In addition, Cohen’s Kappa value for classification with eight buildings is 0.84, which shows the strong inter-rater agreement. Supplementary experiments are carried out to investigate the factors which reduce the accuracy. The fundamental cause of the reduced accuracy is the higher similarity between the fingerprint databases which reduces the classification accuracy in essence. Despite the fact that the results illustrate that the proposed method has huge potential and can be utilized to work in GPS denied environments.One criticism of the traditional process of fingerprinting approach is the laborious survey that requires both cost and time. Traditionally, during surveys, the data are collected at specified points separated by 1 m; we followed the same procedure. In addition, we, however, performed experiments with a database built using the data collected at points separated by 2 m. The results demonstrate that the overall accuracy is reduced to 81.47% from 86.37%. The elementary reason is the incorrectness of the interpolated values that are generated using the interpolation. The higher the distance between the points used for the interpolation, the more smoothed the interpolated values are that affect the uniqueness of the fingerprints. Thus, the labor for surveys can be reduced, but there is a trade-off between the surveying cost and accuracy.F score and Kappa values show very strong agreement between the predicted and labeled buildings. The prediction accuracy of the proposed scheme is 81.47% when we use the fingerprint database with data points which are 2 m apart. However, the system accuracy is reduced by a margin of 4.9%, yet the surveying labor can be reduced by 50% with a 2 m database. The proposed system is totally infrastructure free and leverages the data collected using the smartphone built-in sensors alone. The system utilizes only four frames of magnetometer and accelerometer data collected at 10 Hz. We intend to perform further experimentation with an increased number of buildings and database building using crowdsourcing for public places including the shopping malls in the future.Recent indoor localization systems that leverage the smartphone built-in sensors operate on the assumption that the system has former information of the building where the user is currently walking. It is assumed that the system knows the starting position as a priori or use a naive approach that the GPS calculated position is correct. Such assumptions may plot a pedestrian in the building other than where he currently is. Additionally, GPS deprived environments make it very challenging to know the building information for such systems to operate properly. This research presents a building identification scheme which utilizes the pervasive magnetic field to identify the specific building where the user is now. The magnetic patterns based fingerprinting database approach is used and two databases are built with data collected at 1 m and 2 m separated points to investigate the impact of isolated points on the prediction accuracy. The proposed scheme is able to predict accurately at 86.37% considering eight buildings that contain twenty nine floors in total. Similarly, the proposed system is able to accomplish a precision of 0.85, UAR  of 0.84, F score of 0.84 and Cohen’s Kappa value of 0.84, respectively, which show high prediction as well as higher inter-rater agreement. The


An ultra-high-speed optical trap enabled direct observation of the timing and amplitude of the working stroke, which can occur within <200 μs of actin binding by β-cardiac myosin. The initial actomyosin state can sustain loads of at least 4.5 pN and proceeds directly to the stroke or detaches before releasing ATP hydrolysis products. The rates of these processes depend on the force. The time between binding and stroke is unaffected by 10 mM Pi which, along with other findings, indicates the stroke precedes phosphate release. After Pi release, Pi can rebind enabling reversal of the working stroke. Detecting these rapid events under physiological loads provides definitive indication of the dynamics by which actomyosin converts biochemical energy into mechanical work.Key steps of cardiac mechanochemistry, including the force-generating working stroke and the release of phosphate (P Understanding the connections between the formation of a force-bearing actin-bound state, the biochemical step of Pi release, and the mechanical action of the working stroke is fundamental to understanding energy transduction. Although substantial physiological and biophysical experiments have provided key details associated with these transitions  with actin using the three-bead optical trapping geometry, where a bead-actin-bead ‘dumbbell’ assembly is brought near to a single myosin molecule attached to a pedestal bead . The myoUFFC uses a feedback loop to maintain a constant force on an actin filament dumbbell by rapid (µs) control of the trapping laser position. The applied force  causes the filament and two beads to move through the assay solution at a constant velocity set by the bead size and water viscosity and the force is alternated in direction to maintain the dumbbell within 200 nm excursion . When a i under force that hinder or assist the stroke. To distinguish brief, reversible actomyosin attachments from longer attachments when myosins complete the ATPase cycle, most experiments were performed at a low (1 μM), rate-limiting MgATP concentration. Under both assisting and hindering loads, the distributions of event durations span a range from less than 1 ms to greater than 1 s , are more than 10-fold faster than the slowest detachment rate, ks (blue closed symbols). kf increases from 1 × 103 s−1 at low loads to up to 3–6 × 103 s−1 with increasing hindering or assisting forces. Events which detach at kf composed 20–40% (Af) of all observed interactions  (−1 in the presence of 1 mM MgATP (As) represents motors that have completed the ATPase cycle  , increasmM MgATP . This obse cycle   increases with assisting and hindering forces  of 700 to 5,250 s-1, that increase with force from 1.5 pN to 3 pN and then plateau (k+5) and rate for reversing actomyosin attachment  increased in 10 mM Pi at loads < 3 pN, suggesting an increase in the fraction of events that detach from weak-binding states  does not occur between attachment and the stroke.The presence of 10 mM free P stroke. . Compariion data  Table 2,i showed reversals in the working stroke to the pre-stroke level  during attachments, or lifetime distributions consistent with paired dissociation events that might signal double-headed attachment. Thus, the data are interpreted as resulting from single myosin heads. The short-lived state detected in this study can stop the motion of an actin filament and maintain forces of up to 4.5 pN for hundreds of microseconds. In earlier publications, a weak-binding state of myosin has been described in several ways, and we considered whether the observed short-lived interactions may be in such a weak-binding state.kf) is substantially more force dependent under hindering loads as compared to assisting loads  and the similarity between kstroke and kf  from the same states. If Pi release were to happen before, or simultaneously with, the stroke at a rate of 17 s−1, less than 0.4–4% (high load to zero load) of the molecules occupying the short-lived state would produce a stroke, the rest detaching at ≥500–5000 s−1. The event duration data show that >10–40% (high - low load) of interactions proceed through the entire biochemical cycle  may mask the effects of Pi on attachment durations. Ensemble averages of the long events (>25 ms) show that added Pi leads to a larger and more delayed dip in the displacement  that increases with hindering load. Phosphate release occurs after the stroke and rebinding of phosphate allows reversals of the stroke.The model in The scheme of i may occasionally be released before the stroke, if this occurred more than 20% of the time, there would be a discernable delay in the stroke rate in the presence of Pi which was not observed  construct of human β-cardiac myosin (MHY7) was expressed in C2C12 myoblasts and purified as previously described . The HMM2, and 1 mg/mL BSA. The calculated ionic strength of the experimental solutions was held constant across ATP and Pi conditions. The values of the components and total ionic strength of the solutions for the various Pi and MgATP conditions are given in Experiments were conducted in flow cells constructed and prepared as previously described . The ass−1 500 nm diameter beads , coated nonspecifically with neutravidin  system to our UFFC instrument to improve stability and accuracy of the force signal as a result of thermal changes and other variations. This system is described in the below and Relative to acousto-optic deflectors (AODs) more commonly used in dynamic optical trap instruments, the electro-optic deflectors (EODs) used here provide a much smoother angular deflection of the IR beams (constant slope of deflection vs. input voltage) at the expense of maximum deflection angle . The EODF0) signal values and correct for the drift. While the feedback system is briefly paused, the trap positions are not updated and (when myosin is not interacting with actin) the only force on the beads is from the pretension applied to the filament. The force signals observed during each pause can be used to reset the zero-force voltage and calculate the setpoint in the feedback loop to the recorded F0 level plus the applied force.Even with regular alignment, thermal drifts and or air currents produced instrumental 0.25–2 pN fluctuations over an hour period of recording. To obtain accurate and reliable force signals, we utilized an real time drift and slope correction (DSC) system which periodically pauses the feedback system during an experiment to probe the true ‘zero load’ EODslThis slope value can then be used in the FPGA to update the setpoint value as the trap positions change in order to account for the slope in the force signals.Examples of the drift offset and the calculated slope values over a 30 s trace are shown in When the data are analyzed, the recorded force signals can be transformed into the actual force signals by using a similar algorithm in the analysis software that was used in real time on the FPGA . When deσt) can be calculated and ranged from 500 μs at 1.5 pN to <60 μs at 4.5 pN applied load. From each data trace, a theoretical minimum detectable event length (deadtime) was calculated based on the velocity distributions and the threshold value as previously described  used previously for UFFC experiments . Brieflyescribed . Events i). Parameters for deadtime corrected single, double, and triple exponential distributions were estimated in MEMLET  before the detected end of the event, meaning this value was used in the averages for all time points longer than the actual event duration. The value of σt depends on the smoothing of the velocity for event detection, and thus was smaller (more accurate) for larger forces. The average value of σt varied from 0.5 ms for 1.5 pN to ~72 μs for 4.5 pN. Ensembles were weighted such that each molecule contributed equally to the final average.Ensemble averages were carried out as have been described previously . The begi conditions in i data and for analysis of the 0 Pi data which was directly compared to that with 10 mM Pi  when the ensemble average reached its maximum within the first 1.2 ms following the minimum position, with the exception of the 1.5 pN data, which were searched over the first 5 ms. The displacement from a window of 200 µs centered on tinit was averaged to determine the maximum initial position. The minimum and maximum positions were used to normalize the displacements to range from 0 to 1, as plotted in tinit was used to fit a single exponential rise with an amplitude of 1 to determine the rate of the working stroke as reported in Quantification of the ensemble average was done programmatically, using the methods and parameters reported below. The minimum position of the ensemble average within the first millisecond of detected actin binding was set to be zero displacement. The size of the initial displacement was calculated from the raw (unfiltered) ensemble averages by finding the time , and for each transition out of that state (i and the transition associated with that time was used to assign the next state (j). This method leads to the expected results that the flux through a transition ; Arne Gennerich (Reviewer #3).Thank you for submitting your article "Single molecule mechanics resolves the earliest events in force generation by cardiac myosin" for consideration by The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.The reviewers and I felt that this is a significant piece of work that needs to be widely read and understood. It is a major technical achievement – to have such high time resolution optical trap data and the authors have chosen an ideal protein to use. Rather than the fast myosins used in Captianio's earlier work laser trap studies they use a β cardiac myosin which is several fold slower for some of the key molecular events. This allows fine detail of myosin attachment and the subsequent events to be mapped in great detaili) still present in the motor. Each of these is a significant observation and if the interpretations are correct then the results have a big impact on some of the major questions about how myosin generates force. The interpretation of the data will be argued over for some time.Here for the first time the authors appear to be seeing myosin heads weakly attached to actin and the transition through the power stroke to a strongly attached form, significantly with phosphate  The authors do not state clearly in the main text what the myosin construct is that they are using; human β HMM with a flag tag. The details are important and should not be left in the Materials and methods alone. It is only in the 2nd paragraph where they state that this is human β myosin but do not say this is HMM or how it is attached to the surface. The experiments would not be possible with any myosin faster than β and to my knowledge it is only the human β protein that is currently available in a form that can be expressed with tags.In summary the reasons for using the β-cardiac myosin, rather than other isoforms, need to be explained clearly in the text.2) The authors do provide a brief paragraph at the end of the manuscript referring to other myosins. For a general reader the possibility of isoform differences between myosins needs to be addressed in relation to the major conclusions.3) The use of HMM rather than long S1 does raise issues of any involvement of the 2nd head in the events observed. This is not mentioned in the paper but will add a complication to interpretations of the data. The authors should address why HMM is used and how this affects their interpretation4) Figure 2—figure supplement 2, in contrast to the data shown on a log time base in Figure 2 does show a marked asymmetry in the stiffness . This requires some comment and may be one of the very interesting features of the data that requires further explanation. In contrast Figure 2—figure supplement 2 is instead as showing symmetry, a single d value for assisting and hindering loads. There has been a lot of debate about asymmetry in the crossbridge stiffness and its consequences. This is worth commenting on.5) Many of the issues here have been long debated and in this short report the authors cannot be expected to cover all the literature but some of the citations reflect a narrow view of the debate. For example:a) In several places the authors state that their data is compatible with published data and then refer to the published data on pig myosin . There is a substantial literature on the human protein including from some of the authors. The work on human form should surely be a better reference.b) Similarly the references to the weakly attached sate  seem an odd mixture. Bagshaw and Trentham, 1974, is all work in the absence of actin. Essential revisions:1) The authors do not state clearly in the main text what the myosin construct is that they are using; human β HMM with a flag tag. The details are important and should not be left in the Materials and methods alone. It is only in the 2nd paragraph where they state that this is human β myosin but do not say this is HMM or how it is attached to the surface. The experiments would not be possible with any myosin faster than β and to my knowledge it is only the human β protein that is currently available in a form that can be expressed with tags.In summary the reasons for using the β-cardiac myosin, rather than other isoforms, need to be explained clearly in the text.We have added to the main text to clearly state the nature of the construct:“The myosin protein was a heavy meromyosin (HMM) construct with a Flag-tag placed at the N-terminus for purification. […] Although this is a two-headed construct, we did not observe evidence that both heads interacted simultaneously with actin in the presence of ATP (see Discussion).”We also have added to the Discussion about the isoform in response to questions 2 and 3 as mentioned below.2) The authors do provide a brief paragraph at the end of the manuscript referring to other myosins. For a general reader the possibility of isoform differences between myosins needs to be addressed in relation to the major conclusions.We expounded upon the last paragraph to further emphasize that there may be differences between the various myosin isoforms.“The possibility remains that other myosin isoforms which exhibit different kinetic properties than muscle myosin, such as non-muscle myosins V and VI, may proceed through actin binding, the working stroke, and phosphate release with different dynamics or even different sequences . Specific experiments on those systems are needed to clarify the mechanisms.”3) The use of HMM rather than long S1 does raise issues of any involvement of the 2nd head in the events observed. This is not mentioned in the paper but will add a complication to interpretations of the data. The authors should address why HMM is used and how this affects their interpretationWe have added the following sentences near the beginning of the Discussion:“Although we have used a two-headed, HMM construct in our experiments to emulate biological structure, we did not observe changes in the stiffness  during attachments, or lifetime distributions consistent with paired dissociation events that might signal double-headed attachment. Thus, the data are interpreted as resulting from single myosin heads.”4) Figure 2—figure supplement 2, in contrast to the data shown on a log time base in Figure 2 does show a marked asymmetry in the stiffness . This requires some comment and may be one of the very interesting features of the data that requires further explanation. In contrast Figure 2—figure supplement 2 is instead as showing symmetry, a single d value for assisting and hindering loads. There has been a lot of debate about asymmetry in the crossbridge stiffness and its consequences. This is worth commenting on.d) values obtained from the Bell fit have been used as an estimate of the force dependence of the kinetic transitions being observed. This asymmetry in force sensitivity may be related to myosin stiffness, but it does not have to be. We interpreted the difference in the d values for kf for assisting vs. resisting loads to be due to the transition of pulling myosin forward off of actin vs. backwards off of actin to be fundamentally different in terms of the molecular interactions. For kint, we have interpreted the single d value for assisting and resisting loads to indicate that a single transition is affected for both directions of force which slows under assisting load. This directionality is consistent with reversals of the working stroke. These points are outlined in the subsection “The myosin working stroke is rapid and more likely for long events” and subsection “Experimental protocol”.The distance parameters (5) Many of this issues here have been long debated and in this short report the authors cannot be expected to cover all the literature but some of the citations reflect a narrow view of the debate. For example:a) In several places the authors state that their data is compatible with published data and then refer to the published data on pig myosin . There is a substantial literature on the human protein including from some of the authors. The work on human form should surely be a better reference.We thank the reviewer for pointing this out and have updated the references to cite the most relevant work done on the human protein, namely Deacon, et al., 2012, and Bloemink et al., 2014 in the places listed.b) Similarly the references to the weakly attached sate  seem an odd mixture. Bagshaw and Trentham, 1974, is all work in the absence of actin.We thank the reviewer for pointing this out and have updated the references to include Stein, Chock, and Eisenberg, 1984 and Brenner 1991.