Writing with a purpose means that you need to make sure your writing communicates amessage. However, doing this effectively might mean taking a few extra steps as you write. Inthis article, we will look at seven ways you can improve your writing and communication skills.

Writing with a purpose means that you need to make sure your writing communicates amessage. However, doing this effectively might mean taking a few extra steps as you write. Inthis article, we will look at seven ways you can improve your writing and communication skills.

L(\lambda_j)={A\cdot\Delta\lambda\cdot R_c(\lambda_j)\cdot FF_j\cdot\cdot(1-S_l)}

Market SizeHealthy TissueDiseased TissueCurrent TreatmentsApproaches to Tissue EngineeringMy Approach

MATERIALS AND METHODS RESULTS Computational Electronic structures for 20 full-length Aβ40 conformer structures and inter-atomic interaction energies from these electronic structures using natural bonding orbital (NBO) formalism  revealed: 1. C-terminus:helix region interactions 2. N-terminus:helix region interactions 3. strong interactions of residues within the 15-24 region that stabilize the helix 4. interactions between residues 40-35, 33-27, and 3-9 Experimental Structure 3 synthesis 1. lactam bridge between Asp23 and a Lys residue that we substituted for Val40 2. covalent linkage prevents interaction of the C-terminus with the core helix 3. predicted to preclude formation of the stable dimer state formed through concerted collapse of two monomers and produce distinct assembly behavior [ENGINEERED PEPTIDES. Design principles and positions of lactam bridges () are noted above each structure. Predicted effects are shown to the right of each structure. ka is assembly rate. Peptide regions: green, N-terminal; red, central helical (His13–Asp23); blue, C-terminal.] SDS-PAGE showed that structure 3 vs Aβ40 1. displayed no dimer band, but an intense monomer band 2. a band migrating below monomer 3. suggesting that structure 3 is capable of forming two conformers in SDS-PAGE, one with an Mr consistent with wild type Aβ40 and one with a smaller Mr of ≈3500. [SDS-PAGE/SILVER STAINING OF Aβ40 AND STRUCTURE 3 AFTER 10 D INCUBATION. “MWM” signifies molecular weight markers. Arrows: _2_, dimer; _1_, monomer; _a_, band of Mr ≈ 3500.] Mass spectrometry of structure 3 vs Aβ40 revealed: 1. structure 3 spectrum contained a large -7/2 dimer (formed from -4 and -3 monomers) peak 2. suggesting that self association of structure 3 produces a dimer structure unique from that formed by wild type Aβ40 Ion mobility spectroscopy (IMS) studies of structure 3 vs Aβ40 revealed: 1. “collision cross section” (σ) value for structure 3 was larger than that of wild type Aβ40 (620 vs 607 Ų) 2. supporting the explanation that structure 3 forms a unique conformer [MASS SPECTROMETRY. Negative ion MS of wild type Aβ40 and Structure 3 (inset). Scale of abscissa is m/z, where m=mass and z=charge. Numbers above peaks are z/n, where n is number of monomers.] ThT fluorescence to monitor formation of extended β-sheet in structure 3 vs Aβ40 revealed: 1. an immediate monotonic increase in fluorescence that plateaued at 12 days at a level that was ≈1/2 that of Aβ40 2. appears to self-associate without a substantial lag phase (<<1 days) 3. appears to produce aggregates that display substantially less β-sheet than do wild type assemblies [THT FLUORESCENCE.] EM to compare assembly morphology of structure 3 vs Aβ40 revealed: 1. far fewer fibrils 2. a number of structures not seen with WT Aβ40, including short worm-like structures, longer worm-like structures, and fibrils with prominent helical twists 3. multifilar rod-like structures 4. some of the rod-like structures had “sausage-link” morphologies with the links occurring at intervals of ≈270 nm

Introduction and Background

Low-Cost EEG-based Seizure Monitoring Hat with Improved Patient ComplianceTiffany Kyu, Hilary Yen, Tiana Baghdikian, Julius Yee, Phillip Cox, Chang-Min HurAbstract—Traditional epileptic seizure monitoring is achieved in a hospital setting; however, it is limited by its cost, lack of mobility, and constant maintenance. Advances in biotechnology have enabled seizure monitoring in nonclinical environments, however, these devices are expensive and obtrusive. We present a low-cost EEG-based seizure monitoring hat that promotes long-term patient compliance through its comfortable and socially-acceptable design without compromising signal quality. This device utilizes Biopac’s dry electrode technology, and we validate the efficacy of its signal acquisition compared to the gold standard wet Ag/AgCl electrodes used in clinical settings. Sewn fabric integrated into a plastic frame achieves high comfort and subtlety. This device is effective in capturing and identifying seizure signals with a 98% accuracy utilizing a custom signal processing algorithm with FFT and the Neural Pattern Recognition toolbox in MATLAB. Our prototype overcomes many of the current clinical and market limitations and achieves long-term and continuous acquisition of seizure signals throughout a patient’s daily life.Index Terms—EEG, dry electrodeI. IntroductionEpilepsy is the fourth most common neurological disorder in the United States, and it is characterized by unpredictable, recurrent, and unprovoked seizures \cite{Alarc_n}. 65 million people around the world suffer from epilepsy where one-third of these people live with seizures that cannot be controlled by anti-epileptic drugs \cite{Baker_1997}. Uncontrollable seizures can even be fatal in cases of Sudden Unexpected Death in Epilepsy (SUDEP) [1, 2, 4, 5-7]. There is no known cause of SUDEP, but preliminary studies have shown that seizures may be a precipitating factor. Early SUDEP research has identified that improving active monitoring of seizures, especially at night, can enable a rapid human response (i.e. shoulder tapping) that could potentially prevent SUDEP [1, 5, 6]. This work aims to develop an at-home wearable EEG (electroencephalogram) monitoring device.Standard hospital EEG monitoring requires constant replenishment of conductive gels, which can cause skin discomfort [2, 3, 4]. In addition, hospital monitoring is costly and requires long-term inpatient care. Current available EEG epilepsy monitoring devices fail to promote active seizure monitoring throughout patients’ daily lives due to their obtrusive design. This research overcomes this limitation and provides epileptic patients with a dry electrode-based EEG monitoring device that is comfortable, low-cost, and socially acceptable. Our device provides near real-time and continuous seizure monitoring and hopes to improve the scientific community’s understanding of the relationship between seizures and SUDEP.In this study, an EEG hat is proposed for long-term measurement and improved patient compliance. First, we evaluated various commercially available dry electrodes focusing on the electrode-skin impedance, attenuation, noise, movement artifacts, and accuracy. Dry electrodes are chosen because they reduce impedance presented by hair through protrusions that penetrate to the scalp [10-12]. In addition, the use of dry electrodes allows us to measure biopotentials without preparation of the skin and replenishment of conductive gel. We use a circuit tested by Sullivan et al to increase the signal by a gain of 1000, and filter out signals with a bandpass filter with a cutoff between 1Hz and 100Hz [9]. Acquired data is Fourier transformed, filtered to extract features, and is then identified as seizures by the Neural Pattern Recognition toolbox in MATLAB®. Hardware, data acquisition algorithms, and electrodes are combined into an adjustable plastic frame to promote patient compliance through a socially acceptable and comfortable design.II. Materials and MethodsA. Evaluation of Dry ElectrodesTwo types of electrodes were studied in this project: the Biopac® 10mm Ag/AgCl post dry electrode and the Cognionics® Flexible Dry EEG sensor as shown in Fig. 1. Dry electrodes are designed to operate without electrolyte or conductive gel [12]. Electrode characteristic data was compared to hospital-grade wet electrodes. With each electrode and test, data was collected using a human skin and tissue substitute, represented by a sausage. In these experiments, we fed signals of varying frequencies (30, 10, 5 Hz) and amplitudes (150, 80, 20mV) to simulate a seizure. The dry electrodes and Ag/AgCl wet electrode disc were consistently placed 1 cm from the edge of the system, and they were fixed to the model using Smith and Nephew Hypafix®. A current was applied, using the 33500B series waveform generatorFig.1: The Biopac® 10mm Ag/AgCl (upper right) and Cognionics® Flexible Dry EEG sensor (upper left) were compared to a standard wet electrode (bottom).(Keysight Technologies, Westlake Village, CA), to the system from a constant height and distance from each electrode to ensure reliable and reproducible results. The electrode output was directly read by the InfiniiVision 3000A X-series oscilloscope (Keysight Technologies, Westlake Village, CA). Using this method, we can measure attenuation, noise, and movement artifact [9, 11]. Experiments were repeated with this phantom utilizing an artificial wig, mimicking hair, in order to study the effects of its interference.B. Development and Integration of HardwareThe EEG circuit was developed according to the schematic used by Sullivan et al as shown in Fig. 2 [9]. The circuit consists of two operational amplifiers that result in a net gain of 1000. Signals are passed through a bandpass filter with cutoff frequencies of 1Hz and 100Hz.As the circuit was designed for use with dry electrodes the circuit uses the INA116, an instrumental amplifier with guard pins to protect high impedance inputs [9]. There is also a reset circuit to protect against offset currents. Both measures are put in place to alleviate problems which arise from high impedances inherent to dry electrodes.The INA116 instrumental amplifier (Texas Instruments, Dallas, TX) and LT6010 operational amplifier (Linear Technology, Milpitas, CA) are used. The INA116 was chosen for its low input bias current of 3fA, low input current noise of 0.1fA/(Hz)½, and integrated guard pins. The LT6010 was chosen for its low noise (14nV/Hz1/2). Both components draw minimal power, as the circuit only uses 10.5mW. Signals are transmitted remotely to a computer via a Wi-Fi component attached to the circuit.The circuit was tested by inputting known signals, using a 33500B series waveform generator (Keysight Technologies, Westlake Village, CA), with frequencies between 10-1 Hz to 104 Hz and observed using a InfiniiVision 3000A X-series oscilloscope (Keysight Technologies, Westlake Village, CA) to ensure signals are properly filtered and to observe mid-band gain.C. Signal Processing AlgorithmAfter the signal is amplified and filtered by the circuit, we must differentiate between seizure and non-seizure signals. The steps we took are illustrated in Fig. 3. A low pass filter is used on input EEG signal files. Fast Fourier Transform (FFT) is then applied to decompose the signal into the amplitude and frequency domain [13, 14]. The decomposed signal is separated into five feature categories: δ, 𝜃, α, 𝛽, γ, which have bandwidths of 0.5 - 3 Hz, 3 - 8 Hz, 8 - 12 Hz, 12 – 38 Hz, and 38 – 42 Hz respectively, as shown in Fig. 4. These five features are used to obtain a power spectrum at a certain period of time. The neural pattern recognition toolbox in MATLAB® is then used to distinguish between the seizure and non-seizure signals [18]. Using Bonn University’s EEG Database, the neural network is trained to detect potential seizure waves. The EEG database consists of 100 files per patient, each of which contains 4096 data points. EEG data from two patients: one with seizures and one without seizures is used. The mean of the absolute value of all the points in aFig.2: EEG amplifying circuit. The two operational amplifiers create a gain of 1000. The reset circuit protect against offset current. The shield is driven by the guard pins, and minimizes the noise the electrode picks up. [9]Fig.3: Signal Processing Flowchart. The original EEG signal is subjected to various steps in order to identify seizures.Fig. 4: The raw EEG signal of a patient is filtered via FFT and separated into the five feature categories δ, 𝜃, α, 𝛽, and γ.frequency band wave was calculated. The neural pattern recognition toolbox uses the first 75 files for both patient’s data to train and define seizure and non-seizure pattern classes. Scalar target values are set to either 1 or -1, which indicates whether an input is classified as seizure or non-seizure. Once the neural network is trained, the remaining 25 files for both patients are tested for seizure detection accuracy. With the algorithm trained, it can now detect whether a patient is having a seizure or not.D. EEG Cap AssemblyThe EEG-based seizure-monitoring hat is comfortable and inconspicuous in its design. The hemisphere-shaped hat frame is made of plastic with an adjustable strap to accommodate individuals with heads of various sizes (Fig. 6). Twelve dry electrodes are securely attached to the angled supports, with two electrodes on each support and an arc length of three inches from each other. These 12 electrodes are placed in specific reference positions F3, AFZ, F4, FC1, FZ, FC2, CP1, CP2, P3, PZ, P4, and POZ as depicted in Fig. X, which is labeled according to the 10-20 International System of Electrode Placement. These electrode positions are sufficient for accurate EEG readings as shown from literature [11]. The reference and ground electrodes are placed at the back of the ear labeled A1 and A2 in Fig. 5.Electrode leads and wires are securely attached to the angled supports to reduce wire movement. 5 mm diameter holes in the plastic frame permit electrode leads and wires to be threaded through and aligned on the outside of the head frame. These wires terminate with the connection to the flexible circuit attached at the front of the frame as labeled (Fig. 6).50% cotton and 50% polyester fabric is sewn to surround the inside and outside of the plastic frame, improving user comfort and maintaining an inconspicuous design. On the inside of the frame, the fabric is sewn around the electrodes to prevent diminished signal acquisition. Epileptic patients can place the hat on their head (Fig. 6) and easily adjust the strap to ensure a tight fit while still permitting movement. Patients can wear this EEG-based seizure monitoring hat in their daily environment.III. Results and DiscussionA. Highest Performing Dry ElectrodeEach electrode was characterized for their signal quality through attenuation, noise, and movement artifact to determine which is most comparable to the current standard of wet electrodes. Attenuation was calculated as already reported by Chen et al [13]. The observed negative attenuations reflect an increase in signal as it travels through the electrode. Additionally, lower amplitudes have a smaller attenuation, which can be explained by an increase in noise artifact at these low values. Fig. 7 shows the averaged values and standard deviations of attenuation measurement results for each of the three aforementioned electrodes. Results showed that the attenuation of the Biopac® electrode is similar to that of the conventional wet electrode for different amplitudes and frequencies that mimic a seizure, and this electrode’s result isFig. 5 Montage of dry electrode placement on patient scalp labeled according to the International System of Electrode Placement.

                The community college system has imparted numerous individuals a chance, or in certain cases a second chance, at pursuing their education at a higher institute of education, having unbolted pathways that were once seemingly unattainable and inaccessible to these individuals, and thus, indiscriminately generating opportunities for everyone, in spite of race, ethnicity or nationality, who desire to ameliorate their prospects of a more advantageous future. Likewise, over the span of the past decade or so, community colleges have begun to rapidly emerge as gateway entrances for an influx of international students who wish to complete their university studies in America, perceiving the community college nexus to be a “stepping stone to achieving an education that might otherwise be beyond their reach” (Anayah&Kuk), illustrating that the reasons that motivate international students to select the non-traditional community college route are pretty similar to those of their domestic counterparts. Although there have been multiple prior research studies conducted on the community college system, alongside the transitional experiences of transfer students, there has been a relatively minute amount of literature revolving around the subject matter of the challenges and adjustments that international transfer students encounter as they proceed toward achieving their bachelor's degree at 4-year universities, despite the fact that as of the 2015-2016 academic year, there is an estimated total of 95,376 international students who are enrolled at community colleges nationwide. That is about 1.9% of the overall community college student populace matriculated in the system (Open Doors, 2016). Thus, the focus of my research question is how does being an international transfer student from a community college impact one's sense of belonging on a 4-year university campus? 

The abstract is a condensation of the information (facts) in the paper and should be brief(150 - 250 words), specific and self-contained including the methods of the research and the principalresults. The abstract should not include trivial experimental details, references, figures or equations.KeywordsImmediately after the abstract, provide a maximum of 6 keywords, using American spelling and avoiding general and plural terms and multiple concepts (avoid, for example, "and", "of").only abbreviations firmly established in the field may be eligible.Each heading should appear on its own separate line.1.IntroductionThis section should state the objectives of the work and provide an adequate background. It should also describe briefly the work presented in the paper. Avoid a detailed literature survey or a summary of the results.2. Material and methodsIt should provide sufficient detail to allow the work to be reproduced. Methods already published should be indicated by a reference: only relevant modifications should be described.3.ResultsResults should be clear and concise.4.DiscussionThis should explore the significance of the results of the work, not repeat them. Avoid extensive citations and discussion of published literature. A combined Results and Discussion section is often appropriate. The Results and Discussion should deals with the interpretation of the results in the light of previously published findings.5.ConclusionsIt should be kept short and must be fully supported by the results reported. The Conclusions section should include the major conclusions, the limitations of the work and the future work.AcknowledgementsArtwork• Make sure you use uniform lettering and sizing of your original artwork.• Save text in illustrations as 'graphics' or enclose the font.• Only use the following fonts in your illustrations: Arial, Courier, Times, Symbol.• Number the illustrations according to their sequence in the text.• Use a logical naming convention for your artwork files.• Provide captions to illustrations separately.• Produce images near to the desired size of the printed version.• Submit each figure as a separate file.• The figures/schemes/tables should be inserted directly where the authors want them in the text.Reference StyleAll citations in the text should refer to:1. Single author: the author's name (without initials, unless there is ambiguity) and the year ofpublication;2. Two authors: both authors' names and the year of publication;AUTHOR INFORMATION PACK 25 Jan 2017 www.elsevier.com/locate/bios 133. Three or more authors: first author's name followed by "et al." and the year of publication.Citations may be made directly (or parenthetically). Groups of references should be listed firstalphabetically, then chronologically.List: References should be arranged first alphabetically and then further sorted chronologically if necessary.

Abstractcomphwe comprehensively evaluated the Advanced Research Weather Research and Forecasting (WRF-ARW; WRFV3.7) model skill in simulating the track,landfall and intensity  of the tropical cyclone Hudhud that formed over the northeastern Bay of Bengal during  7th-14th October 2014 sensitivity to the physics parameterizations and initial conditions. Kain-Fritsch cumulus parameterization has shown relatively superior performance when compared to other available schemes, similarly  YSU PBL physics and Ferrier (new eta) micro physics parameterizations  has shown the superior performance,  In addition to this we also evaluated the model skill sensitivity to the initial conditions in 24 hour interval. Overall model able to simulate the  cyclone reasonably in terms of track, rainfall and intensity. The error/bias of these variables increased with  the increasing lead time.

IXYS COLORADO LASER DIODE DRIVER MODULES IXYS sells a variety of laser diode driver modules. I have disregarded those that had potentiometer controls, large form factor, and closed design. All driver modules have mounting pads provided to mount laser diode directly to driver unless otherwise stated. PCO-7110 Series Laser Diode Driver Module The PCO-7110 series driver module is a compact pulsed laser diode driver designed to provide fast and high current pulses for applications needing nanosecond pulses and up to 50 A pulse output current. The PCO-7110 model comes in 6 different models, two models that may closely match with this project. Their specifications are listed in the excel sheet. The PCO-7110-40-4 laser diode driver module providing pulse currents to 40 A, fixed pulse widths of 4 ns, and at frequencies up to 50Khz. The PCO-7110-50-15 provides pulse currents to 50 A, fixed pulse widths of 15 ns, and frequencies up to 11 Khz. Both models allow for current monitoring by oscilloscope. Output currents for PCO-7110 models are adjusted by varying applied voltage (Vin). Output current depends on available charge of capacitor CPFN, shown in figure 2 in an equivalent circuit diagram.

1. Abstract

1. Abstract

SETUP INFORMATION The Silicon Photomultiplier (SiPM) is operated using a few Ortec Nuclear Instrument Modules in room B309. Specifically, The model 113 preamplifier, the 570 amplifier, and the 927 Aspec MCA that has a USB port in the back of it for data collection. There are 3 SMA ports that are available to use in the front of the box (Figure 1). Currently the third SMA port is not being used but can be in the future and is okay to be left alone. SMA port 1 is used to apply bias to the SiPM. This is to be negatively biased only. The power supply used is a BK Precision 9110. This was specifically used because it allows control of how much current the SiPM will get. In the event the cover of the box is removed, the exposed SiPM won’t be fried. The second and third SMA ports are used for signal out of the SiPM. Specifically, it is wired to read signal out of SMA port 2.

THE P-N JUNCTION The Silicon Photomultiplier (SiPM) is essentially an array of silicon avalanche p-n photodiodes operating in Geiger-mode. It is necessary to review some basics of the p-n junction to understand how the SiPM operates. A p-n junction is the fusion of a p-type and n-type semiconductor together. A P-type region contains a majority of hole (positive) carriers and few electrons. A N-type region contains a majority of mobile electrons and few holes. Properties exist that can be exploited for the use of the SiPM when the two regions are brought into contact, diffusion of carrier concentration being one of those properties. Holes from the p-type region diffuse to the n-type region and electrons from n-type region diffuse to the p-type region leaving behind negatively charged ionized acceptor atoms and positively charges ionized donor atoms respectively. As a result of this diffusion, a narrow region on both sides of the p-n junction become nearly depleted of mobile charge carriers, called the depletion layer [1]. The depletion layer contains only fixed charges of negative ions in the p-region and positively charged ions in the n-region. These fixed charges created an internal electric field that points from n-side to p-side as seen in figure 1. There then exists a built in voltage at the interface preventing electrons moving into p-side and holes into n-side. The built in voltage goes as $V_{bi}={q}ln({n_i^2})$, where ND are donor concentrations, NA are acceptor concentrations, and ni is the intrinsic carrier concentration [3]. No net current will flow across the junction while unbiased.

HISTORY OF PHOTONICS RELEVANT TO CMOS INTEGRATED CIRCUITS In 1909, Arnold Sommerfeld published his proposed analytical proof of surface polarization waves [3] marking in our history of Photonics the cornerstone of the all nanophotonics is motivated. Sixty years following Sommerfeld’s publication, Chinese physicist Charles Kao published a solution for guiding Sommerfeld’s surface excitations using optical fiber [4] which in 2009 he would also receive a Nobel Prize. Today nanophotonic research is being conducted by many countries for many applications, yet their approach is surprising similar. The majority of resources and funding for nanophotonics is the development of better materials. This point will be further evident in following sections, but for now it should be mentioned that of those resources only a marginal portion is allocated in the direction of CMOS integration. Initially, this discovery was quiet shocking for two big reasons. First of all, in recent years Moore’s law’s famous exponential curve of computing performance and affordability over time has become less exponentially improving and we know one major cause of the bottleneck occurring in integrated circuits is interconnects. Illustrated in figure 1 is a comparison of the performance capability of optical fibers vs coaxial cables. Also in figure 1 is a relation of current nanophotonic waveguide capability compared to optical fiber which has strong implications for what is possible on chips and the potential need for an enhancing technology. Secondly, the CMOS business has been so profitable and so heavily investing in machinery that it seems logical to continue investing as a lot of the infrastructure exists. The answer to the initial shock is illustrated in figures 2. CMOS compatible nanophotonics occupies an extremely narrow space on a wide spectrum of possible use cases and therefore to expect so much of the resources to be allocated so narrowly this early in such a young immature science could greatly delay the achievable possibilities. The following sections, however, will discuss the results of the resources that were allocated for CMOS integrated nanophotonics and the modules that are in development to address Moore’s law.

In 1909, Arnold Sommerfeld published his proposed analytical proof of surface polarization waves [11] marking in our history of Photonics the cornerstone of the all nanophotonics is motivated. Sixty years following Sommerfeld’s publication, Chinese physicist Charles Kao published a solution for guiding Sommerfeld’s surface excitations using optical fiber [12] which in 2009 he would also receive a Nobel Prize. Today nanophotonic research is being conducted by many countries for many applications, yet their approach is surprising similar. The majority of resources and funding for nanophotonics is the development of better materials. This point will be further evident in following sections, but for now it should be mentioned that of those resources only a marginal portion is allocated in the direction of CMOS integration. Initially, this discovery was quiet shocking for two big reasons. First of all, in recent years Moore’s law’s famous exponential curve of computing performance and affordability over time has become less exponentially improving and we know one major cause of the bottleneck occurring in integrated circuits is interconnects. Illustrated in figure 1 is a comparison of the performance capability of optical fibers vs coaxial cables. In figure 2 is a relation of current nanophotonic waveguide capability compared to optical fiber which has strong implications for what is possible on chips and the potential need for an enhancing technology. Secondly, the CMOS business has been so profitable and so heavily investing in machinery that it seems logical to continue investing as a lot of the infrastructure exists. The answer to my initial shock is illustrated in figures 3. CMOS compatible nanophotonics occupies an extremely narrow space on a wide spectrum of possible use cases and therefore to expect so much of the resources to be allocated so narrowly this early in such a young immature science could greatly delay the achievable possibilities. The following sections, however, will discuss the results of the resources that were allocated for CMOS integrated nanophotonics and the modules that are in development to address Moore’s law.

a) Overlap integral given by \[ \eta=^{\infty} } ^{output} ^{input} dx\] The paper by tong et al, explains that they adjusted the overlap until the output is maximized. I think that for that occur then say the input was a gaussian E = E(0)eax² where E(0) would be a central maximum, then overlap adjusted until the output was E(0), making the overlap integral just integrating a gaussian. b) Using the mode solver for this part. I wanted to see how modes would look after LP₀₁, not single moded. So I went back to the paper and looked at the equation for the diameters that allow for single mode operation, $D< {\pi }$, where n₁ is 1 for air, and n₀ is the index of refraction for the medium in use. From the tong paper, the second page of the paper, or pg.817 of the nature journal it was published in, index of refraction for Silica is said to be n₀ = 1.46. This gives NA = 1.063, using λ = 633nm, the max diameter is then given to be 454.6 nm for single mode operation. So I will put diameters larger then this for non single modes. Using 600 nm for the diameter. The image generated looks just like two very sharp gaussians c) I believe this is due to when the diameter of the wire is decreased below the wavelength its supposed to be guiding, more of the light is guiding outside the wire as a surface wave. So for 1550 nm , looking at the graph for loss, starting at wire diameters of 1200 nm we are already operating below the wavelength we want to guide so as the diameter decreases , more light is outside the wire leading to more loss. Compared to the 633 nm wavelength, you can see the increase in loss occurs when operating below 633 nm diameter wire but we are lower loss from 1200 nm until we get to 633 nm d) To go along with this, the loss mechanism is from surface contamination. The silica wires are’t perfectly uniform. By virtue of that, when light is guided by surface waves it is more susceptible to the surface contaminations.